Annual Report – September 2012

Two-page executive summary

Genotyping: SNP Genotyping: The barley iSelect 9,000 SNP barley chip was cross-referenced with previous chips, automatic SNP calling procedures were implemented and the SNP metadata were expanded. The TCAP wheat group mapped 7,517 SNPs from the previous 9,000 SNP wheat chip and played a key role in the development of a new 90,000 SNP wheat chip. Genotyping of the barley and wheat association mapping panels, elite breeding germplasm, and genomic selection populations is on target.

New genotyping technologies: The Nimblegen whole exome capture assays targeting 110 Mb of sequence in the wheat genome and 90 Mb of sequence in the barley genome have been designed and tested with promising results (77% of sequence reads mapped to the references and more than 90% of targeted exonic regions were represented). The previous results were used to design new rebalanced beta versions that are now being tested. Genotyping by sequencing (GBS) was expanded into new mapping populations generating thousands of polymorphic GBS tags and high-density maps.

The Triticeae toolbox database (T3): New phenotypic and genotypic datasets were incorporated into T3. The user interface was improved to enable more intuitive data searches and the integration of multiple datasets. Three online tutorials explaining data submission to T3 have been developed. Hyperlinks to other databases were created to facilitate users tracking down information about lines or markers. T3 now uses two-dimensional “materialized view” tables to access genotype data. This approach provides quicker access to large blocks of data as well as more compact storage.

Phenotyping: During this period we made significant improvements in the canopy spectral reflectance protocols: improved equipment configurations, developed a more precise measurement protocol and implemented scripts to facilitate the management and analysis of data. This technology was used to evaluate the National Small Grain Collection (NSGC) core collections of barley (500 six-row spring accessions) and wheat (540 spring wheat accessions). The best drought resistant lines from the NSGC screen from 2011 have been incorporated into the wheat breeding programs.

Water use efficiency (WUE): In barley, four association mapping populations were evaluated for WUE at six locations and one was planted for seed increase. In wheat, two association mapping panels were evaluated in five (spring) and three (winter) locations for agronomic and physiological traits, including canopy spectral reflectance data. Eight additional specialized wheat mapping populations were phenotyped for root characteristics, physiological traits associated with WUE, heat stress, and agronomic performance. The chromosome region defining drought tolerance in the rye 1RS translocation was identified and the beneficial effect of photoperiod sensitivity in early planting rain-fed northern latitudes was validated.

Nitrogen use efficiency (NUE): In barley, NUE was evaluated using the spring six-row (SP6), spring two-row (SP2), and winter six-row (WN6) association mapping panels in low (70%) nitrogen and normal (100%) nitrogen in three environments. Results are being analyzed and incorporated into T3. In wheat, both the hard and soft winter wheat panels were evaluated for NUE at two locations (at different N levels) and in four additional locations for yield. The genotyping of all these lines with the iSelect 90,000 SNP wheat chip is on track to be completed before the end of 2012.

Disease resistance: In barley, the NSGC was evaluated for resistance to spot blotch, spot form net blotch and stripe rust. Seventeen accessions resistant to the highly virulent isolate ND4008 of the spot blotch pathogen (Cochliobolus sativus) were identified. Nine lines were identified that are highly resistant to current virulent isolates of spot form net blotch from North Dakota, Australia, New Zealand, and Denmark. In wheat, the analyses of the 2011 and 2012 data for leaf, stem, and stripe rust (1000 spring lines) resulted in the identification of multiple resistance loci for the three diseases, which are being validated by backcrossing into a common susceptible line. Seedling screening of the complete core collection for the three rusts will be completed before the end of 2012.

Population development: The spring wheat Nested Association Mapping (NAM) population was completed and the barley and winter wheat NAM populations were advanced as planned. The development of the wild barley introgression population was completed and genotyped with a custom 384 SNP assay.

Education: A total of 69 graduate students (Appendix H3) have participated in the plant breeding training network. Sixty-two are directly mentored by a TCAP PI, with 38 students being funded by TCAP. Fifty-five undergraduates (Appendix H4) have participated in the TCAP with 37 being mentored by TCAP faculty and graduate students. Additionally, 17 students from Minority Serving Institutions (MSI) are being mentored MSI faculty.

Plant Breeding Training Network (PBTN): The online environment was used to deliver and archive three courses, including Plant Breeding Strategies, Entering Mentoring, and Quantitative Genetics. To insure sustainability of course offerings, the development of an online Plant Breeding Program through Ag*Idea was initiated. Undergraduate students have been supported in their development through three online meetings with industry representatives and TCAP PIs. The development of three undergraduate educational tools has continued and one tool was submitted to an education journal. The PBTN also has been used as a communication tool for project management both for the TCAP, Ag*Idea Executive Committee, and the National Association of Plant Breeders graduate student committee.

Newsletters, films and other communication resources: Information about research and education was shared both internally and externally through six meetings of the TCAP seminar series. Other communication tools include the quarterly newsletters and the face to face meetings at PAG. The TCAP produced film “Holding the future in the palm of your hand” was shown during three recruiting trips to about 200 students. Two of these students applied to TCAP graduate schools. Minority students have been attracted to several internships. The first year evaluation report was received and used to guide second year planning. Evaluation tools were also refined.

Publications and germplasm releases: TCAP participants generated 35 peer reviewed publications during the first 8 months of 2012, which exceeds the total number of publications for the complete first year, which shows accelerated progress. In addition, ten new wheat varieties and two wheat germplasm were released (initiated in previous BarleyCAP and WheatCAP and completed in TCAP).

TCAP PROJECT NARRATIVE

During the second year, the TCAP project progressed as planned without major pitfalls. Progress is described by objectives and deliverables proposed for the second year of the project. The report is organized into seven major sections followed by five appendices including publications, released germplasm, trained graduate and undergraduate students, and presentations by undergraduate students at the end of the report. The location of the different sections in the report are described in the Table of contents below.

Table of contents

Sections	Page
Two-page executive summary	1
Table of contents	3
A) Plan-of-Work for third year of funding	4
A1) Discovery of beneficial alleles	4
A2) Acceleration of breeding	11
A3) Sequence-based genotyping methodologies	13
A4) Databases and web-based tools (T3)	14
A5) Plant Breeding Education Network	14
B) Outcomes/Impacts	17
B1) Discovery of beneficial alleles	17
B2) Acceleration of breeding	20
B3) Sequence-based genotyping methodologies	20
B4) Databases and web-based tools (T3)	20
B5) Plant Breeding Education Network	21
C) Outputs	22
C1) Discovery of beneficial alleles	22
C2) Acceleration of breeding	34
C3) Sequence-based genotyping methodologies	36
C4) Databases and web-based tools (T3)	38
C5) Education	39
D) Milestones and Deliverables	48
D1) Discovery of beneficial alleles	48
D2) Acceleration of breeding	50
D3) Sequence-based genotyping methodologies	51
D4) Databases and web-based tools (T3)	51
D5) Education	52
E) Broad Impacts	53
F) Training	55
G) Concluding statements	55
H) Appendices	55
H1) Publications	56
H2) Germplasm releases	59
H3) Trained graduate students	60
H4) Trained undergraduate students	62
H5) Presentations by students	64

A. Plan-of-Work for year 3 (2013)

The activities that will be performed in year three of the TCAP with the resulting outputs, outcomes and impacts of each activity are organized in 15 tables distributed across the five central objectives of the project.

A.1. PLAN-OF-WORK FOR OBJECTIVE 1

Discover and deploy beneficial alleles from diverse wheat and barley germplasm.

The original proposal stated that a diverse set of barley and wheat germplasm would be genotyped with high-throughput genotyping platforms and phenotyped for climate change-related traits to identify and deploy valuable alleles that help mitigate the negative impacts of climate change. Plans for water use efficiency traits are summarized in Tables 1 to 4, for nitrogen use efficiency traits in Tables 5 and 6, and for disease resistance traits in Tables 7 and 8. Table 9 describes plans for phenotyping the NSGC core collections, Table 10 plans for population development, and Table 11 genotyping plans.

A.1.1. Water use efficiency (WUE)

Table 1. Spring wheat water use efficiency phenotyping.

Activity	Outputs	Outcome	Impact
Association mapping panel (250 entries) Evaluation: dry and irrigated in CA, MT, & WA; rainfed in CO, ID, Canada (3 loc), & Mexico.	Data collected for agronomic and CSR traits, analyzed, and entered into T3.	Identification of favorable alleles for dry conditions.	Development of new varieties for increased productivity in hot, dry conditions in the US and Canada.
Solid stem near-isogenic line pairs (16 entries). Evaluation: dry & irrigated in MT and WA.	Data collected for agronomic and CSR traits, analyzed, and entered into T3.	Determination of the value of solid stem trait for wheat improvement for dry conditions.	Potential use of solid stem trait for wheat improvement in dry conditions.
High tiller near-isogenic line. Evaluation: dry & irrigated in MT and WA.	Data collected for agronomic and CSR traits, analyzed, and entered into T3.	Determination of the value of high tiller number on WUE.	Potential use of high tiller trait for wheat improvement in dry conditions.
Hexaploid X tetraploid wheat RIL (200 entries). Evaluation: MT (2 loc.).	Data collected for agronomic and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for WUE.	Deployment of favorable alleles for WUE into variety development programs.
Drought tolerant B306 X PBW354 RIL (200 entries). Evaluation: KS & MT.	Data collected for agronomic and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for WUE.	Deployment of favorable alleles for WUE into variety development programs.
Chromosome substitution lines (100 entries). Evaluation: KS & MT.	Data collected for agronomic and CSR traits, analyzed and entered into T3.	Identification of favorable chromosome segments from wild species for WUE.	Deployment of favorable chromosome segments for WUE into varieties.
Rye chromosome 1RS substitution line (30 entries). Evaluation: California (dry and irrigated, 2 loc.).	Data collected for agronomic and CSR traits, analyzed and entered into T3.	Determine the impact of the rye segment on productivity under dry conditions.	Development of drought tolerant varieties.

Table 2. Winter wheat water use efficiency phenotyping.

Activity	Outputs	Outcome	Impact
Hard winter wheat association mapping panel (300 entries). Evaluation: CO and TX (dry & irrigated); KS and OK (rainfed).	Data collected for agronomic and CSR traits, analyzed, and entered into T3 database.	Identification of favorable alleles in elite germplasm for WUE.	Development of drought tolerant varieties.
Hard winter wheat association mapping panel (300 entries). Evaluation: OK (forage quality traits).	Data collected for forage quality, analyzed, and entered into T3.	Identification of favorable alleles in elite germplasm for improved forage.	Development of new varieties for dual grain and forage use in the southern Great Plains.
Hard winter wheat association mapping panel (subset of 30 lines). Evaluation: root architecture & agronomic traits	Data collected for root architecture, and agronomic traits, analyzed, and entered into T3. Correlations examined between root architecture and agronomic traits.	Identification of alleles associated with root traits. Knowledge of relationships among root characters and agronomic traits under drought stress.	Development of new varieties with root characteristics appropriate for dryland production in the Great Plains.
Twenty crosses (to confirm favorable alleles for agronomic traits in drought conditions) based on first year’s data.	Twenty F₁ crosses made.	Confirmation of allelic effects for agronomic traits.	Development of new varieties with improved levels of drought tolerance.

Table 3. Barley water use efficiency phenotyping.

Activity	Outputs	Outcome	Impact
Facultative/Winter 6-row association mapping panel (300 entries). Evaluation: OR (irrigated, and 60% of normal irrigation).	Data collected for agronomic traits and CSR, analyzed, and entered into T3.	Identification of favorable alleles in barley for WUE.	Deployment of favorable alleles for WUE into varieties. Adoption of WUE facultative varieties.
Spring 6-row association mapping panel (256 entries). Evaluation: CO (irrigated and 60% of normal irrigation).	Data collected for agronomic and CSR traits, analyzed, and entered into T3.	Identification of favorable alleles in elite barley germplasm.	Deployment of favorable alleles for WUE into variety development programs.
Spring 2-row association mapping panel (256 entries). Evaluation: ID and CO (irrigated & 60% irrigation), MT (dryland & irrigated).	Data collected for agronomic and CSR traits, analyzed, and entered into T3.	Identification of favorable alleles for WUE in elite barley germplasm.	Deployment of favorable alleles for WUE into variety development programs.
Wild barley introgression population (800 entries). Evaluation: MT, MN and ND.	Data collected for agronomic and CSR traits, analyzed, and entered into T3.	Identification of favorable alleles for WUE in elite barley germplasm.	Deployment of favorable alleles for WUE into variety development programs.

Table 4. Barley low temperature tolerance phenotyping (winter planting)

Activity	Outputs	Outcome	Impact
Winter LTT panel (1000 entries). Evaluation: OR and MN (LTT).	Data collected for LTT and agronomic traits, analyzed, and entered into T3.	Identification of favorable alleles for LTT in winter barleys.	Deployment of favorable alleles for LTT into winter barley breeding programs.
Six-row winter panel (300 entries). Evaluation: OR, MN, NE and UT (LTT).	Data collected for LTT and agronomic traits, analyzed, and entered into T3.	Identification of favorable alleles for LTT in winter barleys.	Deployment of favorable alleles for LTT into winter barley variety development programs.

A.1.2. Nitrogen use efficiency (NUE)

Table 5. Wheat nitrogen use efficiency phenotyping.

Activity	Outputs	Outcome	Impact
Hard red winter wheat and soft red winter wheat association mapping panels. Evaluation: Normal N many locations; N stress in two locations.	Data collected for agronomic, grain protein, and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for NUE in wheat.	Deployment of favorable alleles for NUE into variety development programs.

Table 6. Barley nitrogen use efficiency phenotyping.

Activity	Outputs	Outcome	Impact
Spring six row association mapping panel (256 entries). Evaluation: MN, ND and WA (high and low N conditions).	Data collected for agronomic, grain protein and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for NUE in barley.	Deployment of favorable alleles for NUE into variety development programs.
Spring two-row association mapping panel (256 entries). Evaluation: WA, MT, and ID (high and low N conditions).	Data collected for agronomic, grain protein and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for NUE in barley.	Deployment of favorable alleles for NUE into variety development programs.
Facultative six row association mapping panel (300 entries) Evaluation: OR, UT and MN (high and low N conditions).	Data collected for agronomic, grain protein and CSR traits, analyzed and entered into T3.	Identify favorable alleles for NUE in barley.	Deployment of favorable alleles for NUE into variety development programs.

A.1.3. Diseases

Table 7. Barley diseases

Activity	Outputs	Outcome	Impact
Six-rowed spring association mapping panel (256 entries). Evaluation: stem rust (adult stage in Africa), stripe rust (adult stage OR), spot blotch (seedling stage ND) & spot-form net blotch (seedling stage ND).	Data obtained for stem rust, stripe rust, spot blotch and spot-form net blotch, analyzed, and uploaded to T3.	Identification of favorable alleles for disease resistance in spring six row barleys.	Deployment of favorable alleles for disease resistance into variety development programs.
Two-rowed spring barleys association mapping panel (256 entries). Evaluation: stem rust (adult stage in Africa), stripe rust (adult stage OR), spot blotch (seedling stage in ND) and spot-form net blotch (seedling stage in ND).	Data obtained for stem rust, stripe rust, spot blotch and spot-form net blotch, analyzed, and uploaded to T3.	Identification of favorable alleles for disease resistance in spring two row barleys.	Deployment of favorable alleles for disease resistance into variety development programs.
Six-rowed winter association mapping panel (300 entries). Evaluation: stripe rust (adult stage in OR) & spot blotch (seedling stage in ND).	Data obtained for stripe rust and spot blotch, analyzed, and uploaded to T3.	Identification of favorable alleles for disease resistance in six-rowed winter barleys.	Deployment of favorable alleles for disease resistance into variety development programs.
Winter and facultative barleys (471 entries) from the NSGC core. Evaluation: stripe rust (adult stage OR) and spot blotch (seedling stage ND).	Data obtained for stripe rust and spot blotch, analyzed, and entered into T3.	Identification of favorable alleles for stripe rust and spot blotch resistance in winter and facultative barleys.	Deployment of favorable alleles for disease resistance into variety development programs.
NSGC core (1,050 entries). Evaluation: stem rust (adult stage in Africa).	Data obtained for stem rust, analyzed and uploaded to T3.	Identification of favorable alleles for stem rust resistance for spring barley.	Deployment of favorable alleles for disease resistance into variety development programs.
A pre-tested subset of the wild barley introgression lines. Evaluation: stem rust (adult stage in Africa and seedling stage in St. Paul).	Data obtained for stem rust, analyzed and entered into T3.	Identification of favorable alleles for stem rust resistance in spring two row barleys.	Deployment of favorable alleles for disease resistance into variety development programs.

Table 8. Wheat diseases

Activity	Outputs	Outcome	Impact
NSGC core (4400 entries). Evaluation: seedling stripe rust with 5 races in WA.	Seedling stripe rust data collected, analyzed, and entered into T3	Identification of favorable alleles and sources of seedling resistance to stripe rust.	Deployment of favorable alleles for disease resistance into variety development programs.
NSGC core (1500 Spring Entries). Evaluation: adult plant stripe rust in WA and CA.	Adult plant stripe rust data collected, analyzed, and entered into T3.	Identification of favorable alleles and effective sources of adult plant resistance to stripe rust.	Deployment of favorable alleles for disease resistance into variety development programs.
NSGC Core (2500 entries). Evaluation: seedling leaf and stem rust with 5 races in MN.	Seedling leaf and stem rust data collected, analyzed, and entered into T3.	Identification of favorable alleles and effective sources of seedling resistance and to leaf and stem rust.	Deployment of favorable alleles for disease resistance into variety development programs.
Leaf rust AM panel (384 entries). Evaluation: seedling and field leaf rust in MN.	Rust resistance data collected, analyzed, and entered into T3.	Identification of favorable alleles, and characterization of most documented sources of leaf rust resistance in wheat.	An improved system of rust resistance gene postulation and improved ability to characterize US breeding germplasm.
Winter wheat stripe rust AM panel (384 entries). Evaluation: seedling and field of stripe rust in WA.	Rust resistance data collected, analyzed, and entered into database.	Identification of favorable alleles and new sources of seedling and adult plant resistance to stripe rust.	Deployment of favorable alleles for disease resistance into variety development programs.
Hard winter wheat RIL mapping population (192 entries). Evaluation of adult plant resistance in KS & TX.	Rust resistance data collected, analyzed, and entered into T3.	Identification of favorable alleles and validation of adult plant resistance to all three rusts.	Deployment of favorable alleles for disease resistance into variety development programs.
Mini-NAM panel (384 entries). Evaluation: field stripe rust in CA.	Rust resistance data collected, analyzed, and entered into T3.	Identification of favorable alleles and validation of resistance to stripe rust.	Deployment of favorable alleles for disease resistance into variety development programs.
F3 mapping populations (several). Evaluation: seedling leaf and stem rust in MN.	Rust resistance data collected, analyzed, and bulk segregant analyzed and entered in T3.	Identification of favorable alleles and new sources of seedling resistance to leaf and stem rust.	Greater diversity of resistance to support strategic use of rust resistance in US wheat breeding.

A.1.4. Wheat and Barley National Small Grain Collection

Table 9. NSGC core phenotyping.

Activity	Outputs	Outcome	Impact
Winter wheat NSGC core (540 entries). Evaluation: three water & N conditions in ID.	Data collected for agronomic and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for WUE and NUE from NSGC winter wheat materials.	Deployment of favorable alleles for NUE and WUE into variety development programs.
Spring barley NSGC core (repeat 2012, 300 entries). Evaluation: contrasting water conditions in ID.	Data collected for agronomic and CSR traits, analyzed and entered into T3.	Identification of favorable alleles for WUE and NUE from NSGC spring barley materials.	Deployment of novel alleles into adapted varieties to address WUE and NUE for the changing climate.

A.1.5. Population development

Table 10. Population development in wheat and barley.

Activity	Outputs	Outcome	Impact
Development of NAM populations in spring wheat ~100 RILs for each of 30 crosses.	F₆ lines will be increased in the field for yield trials in following years.	Wheat NAM population completed.	Long-term resource for identifying favorable alleles for any trait of interest.
Development of NAM populations in HRWW and SRWW ~100 RILs for 30 crosses of HRWW and SRWW.	HRWW will advance to F4, SRWW will advance to F₄.	Wheat NAM population in progress.	Long-term resource for identifying favorable alleles for any trait of interest.
Development of NAM populations in barley (six-row populations – 93 RIL populations of 100 lines, 90 BC₁ populations of 1-40 lines; two-row populations – 115 BC₁ populations of 100 lines).	F₄ and BC₁S₃ lines for the six-row and two-row populations, preliminary heading date data, genotype data for 384 SNPs for each NAM line, preliminary results of association mapping of heading date.	Barley NAM population completed.	Long-term resource for identifying favorable alleles for any trait of interest.

A.1.6. Genotyping

Table 11. SNP genotyping of wheat and barley germplasm and populations.

Activity	Outputs	Outcome	Impact
Genotype 2500 spring wheat (NAM) lines using 90K SNP assay	Allele calls for 90K SNPs for 2500 NAM lines.	Genotype data for mapping traits.	Identification of favorable alleles for NUE and WUE.
Genotype 300 lines of hard red winter wheat association mapping panel using 90K SNP assay (collaborative effort with USDA wheat SNP project)	Allele calls for 90K SNPs for the hard red winter wheat mapping panel.	Genotype data for mapping traits.	Identification of favorable alleles for NUE and WUE.
Complete genotyping winter Barley LTT panel with 9,000 SNP assay.	Allele calls for 9K SNPs for the winter LLT panel.	Genotype data for mapping traits.	Identification of favorable alleles for LTT.
Genotype wheat AM panels and mapping populations (960 entries) segregating for disease resistance with 90K SNP assay.	Allele calls for 90K SNPs for 960 entries in association mapping and mapping populations.	Genotype data for mapping traits.	Identification of favorable alleles for disease resistance.

A.2. PLAN OF WORK FOR OBJECTIVE 2.

Accelerate breeding through marker-assisted selection and genomic selection. Two approaches to utilize SNP markers have been employed by the TCAP to accelerate breeding cycles including: marker-assisted selection and genomic selection. Marker-assisted selection is being performed in barley and wheat based on prior marker-trait associations identified through biparental and association mapping. Genomic selection is underway in barley based on prior data from the BarleyCAP, and is being evaluated in the winter wheat program, where longer breeding cycles make GS more attractive.

Table 12. Marker-assisted selection (MAS) in wheat and barley

Activity	Outputs	Outcome	Impact
Develop and validate SNP markers for MAS based on associations identified in bi-parental and AM populations	New SNPs developed that are targeted for agronomic, disease resistance and quality traits.	Efficient selection for agronomic, disease resistance and quality traits.	New wheat and barley varieties developed through MAS.
Genotype 2,000 barley samples and 4,000 wheat samples with panels of ~48 SNP markers linked to traits (agronomic, disease resistance and quality traits) for undergoing selection in breeding programs.	SNP alleles identified for 2,000 barley and 4,000 wheat samples.	Efficient selection for agronomic, disease resistance and quality traits.	New wheat and barley varieties developed through MAS.

Table 13. Genomic selection (GS) in barley and wheat.

Activity	Outputs	Outcome	Impact
Compare the gain from selection from GS, random and phenotypic selection in barley. Yield trials will be grown from the first cycle of selection.	Winter survival, yield, heading date, plant height, FHB, and lodging data from cycle 1 lines.	Assessment of accuracy of GS on multiple traits. Estimate of gain from first cycle of GS. Comparison of random, phenotypic and GS.	New facultative barley varieties that can be fall planted in a wide range of environments.
Conduct genomic selection in barley: advance cycle 2, 3 and cycle 4 lines; genotype and calculate genomic estimated breeding values (GEBV) for cycle 3, 4 and 5 lines; and conduct cycle 3, 4 and 5 selections.	Cycle 2 F4:5 seed for evaluation in 2013 fall planted field trials.GEBVs for cycle 3, 4, and 5 lines.Cycle 3 F3 seed.	Continue GS and advance lines for additional GS and evaluation.	New facultative barley varieties that can be fall planted in a wide range of environments.
Assess and implement GS in wheat HRWW and SRWW.	Data from HRWW and SRWW panels will be used to train GS models for yield, NUE and yield stability.	Assess effectiveness of GS.	New varieties developed using GS.
Assessing GS and association mapping in wheat uniform trials.	Yield data will be obtained from uniform trials.	Identify favorable alleles for yield and build GS prediction models.	New varieties developed using favorable alleles and GS prediction models.

A.3. PLAN OF WORK FOR OBJECTIVE 3

Implement sequence-based genotyping methodologies to discover new allelic diversity. This objective was focused on developing gene capture – resequencing and genotype-by-sequencing technologies for wheat and barley and using these technologies to genotype germplasm collections and populations. The basic idea behind this objective was to determine if the lower prices of sequencing were competitive with the iSelect SNP genotyping platforms. We have developed these technologies and are in the process of implementing them as described in the plans for year 3 in the Table 14 below.

Table 14. Gene capture and Genotyping-by-Sequencing (GBS).

Activity	Outputs	Outcome	Impact
Genotype 2500 spring wheat (NAM) lines using GBS.	Allele calls for thousands of polymorphic SNPs in wheat NAM lines.	SNP maps developed. Ability to conduct high resolution mapping of NUE, WUE, and disease resistance.	Identification of favorable alleles for NUE, WUE and disease resistance that will be deployed in breeding programs.
Integrate SNP and GBS data from the wheat NAM populations.	Increased markers for mapping.	Integrated SNP maps. Ability to conduct high resolution mapping of NUE, WUE and disease resistance.	Identification of favorable alleles for NUE, WUE and disease resistance that will be deployed in breeding programs.
Genotype 300 lines of hard red winter wheat association mapping panel using GBS (collaborative effort with USDA wheat SNP project).	Allele calls for tens of thousands of GBS markers.	Ability to conduct high resolution mapping of NUE, WUE and disease resistance	Identification of favorable alleles for NUE, WUE and disease resistance that will be deployed in breeding programs.
Perform exome capture (wheat – 110 Mb; barley 90 Mb) and resequencing 48 diverse wheat and barley lines.	Gene sequence diversity in diverse collections of wheat and barley.	Comprehensive analysis of allelic variation in gene space will help to better understand the genetic basis of agronomic traits.	New varieties developed based on allele-based breeding.
Optimize procedures for analysis of GBS and resequencing data in wheat and barley.	Pipeline for GBS and sequence capture data processing and variant analysis.	Efficient use of GBS and sequence capture data for assessing allelic variation.	Comprehensive analysis of allelic variation in gene space will help to better understand the genetic basis of agronomic traits.

A.4. PLAN OF WORK FOR OBJECTIVE 4.

Implement web-based tools to integrate marker-assisted selection and genomic selection strategies into breeding programs. The TCAP has developed The Triticeae Toolbox (T3) that stores all genotype and phenotype data from the project and provides easily queried data.

Activities: Various activities will be conducted to improve T3 In 2013. The T3 team will continue to curate and store all phenotypic data collected by the TCAP participants. In general, new database structures and interfaces will be developed for the phenotype, genotyping-by-sequencing (GBS) and gene capture sequence datasets. With regards to genotyping data, several improvements will be made including: (1) standards to code GBS nucleotide SNP; (2) differences in format across genotyping data from sequence-capture versus restriction site reduced representations will be accommodated for; (3) SNPs will be designated in a manner that allows revision as more sequence comes in and reference genomes are built; (4) improve storage and allele calling pipelines to provide regular allele calling; (5) improve database storage and efficiency to handle and manipulate 90K SNP data; and (6) develop database structure and interface to store, query, and present GBS data.

Improvements: Several improvements will be made to handle phenotype data including: (1) new database structures and interface for canopy spectral reflectance data; (2) create user interface to select training and prediction populations, visualize prediction outcomes and download results; and (3) collaborate with other interested parties on standards for phenotype storage. To facilitate use of T3 by the TCAP participants, tutorials will be conducted and improved documentation will be developed. A workshop will be organized with other interested database groups

Outputs: The outputs from these activities will include (1) a platform for TCAP data organization, curation, integration and exchange; (2) open-source T3 software and installation guides for non-TCAP installations; (3) new tools for users to analyze and interpret data; and (4) increased phenotype and genotype data content in T3.

Outcomes: The outcomes of these activities will be improved collaboration among TCAP participants working on multi-program objectives, and more powerful analyses for dissecting traits and training performance prediction models.

Impact: The impact of these activities will be an improved T3 that will facilitate virtually all other analyses, dissections, and discoveries taking place in TCAP. T3 will therefore catalyze efficient research in all TCAP objectives. Breeders may use T3 to manage their own program data, broadening the benefits of T3 and accelerating the use of high information DNA marker breeding methods.

A.5. PLAN OF WORK FOR OBJECTIVE 5

Develop and implement a Plant Breeding Education Network.

Table 15. Educational activities, outputs, outcomes and impact.

Activity	Outputs	Outcomes	Impacts
Association analysis and genomic selection course taught by experts.	30 graduate students attend course, utilizing data from T3.	Students better trained in association analysis and genomic selection, develop analytical and problem solving skills of students.	Better-trained plant breeders through collaborative training.
TCAP seminar series/student organized.	Six archived seminars.	Students learn about current research topics from experts and have leadership opportunity.	PBTN more accepted as venue for sharing information and education tool.
Group meeting at PAG.	All TCAP participants communicate between each other and stakeholders.	Increased integration of TCAP participants and stakeholders.	Stakeholders have a better understanding of the project. PIs and students are better coordinated.
Conduct human capital workshop.	30 students attend pilot of human capital training workshop.	Pilot human capital training workshop for future use, support development of student communication, collaboration & leadership skills.	Better trained more employable plant breeders.
Graduate student poster session.	30 students communicate research projects supported by TCAP to participants and stakeholders.	Support development of student communication skills, increased integration of project.	Better trained more employable plant breeders.
Online collaborative research/writing project.	Five students prepare paper in collaborative fashion from data on T3, test collaborative online project.	Provide students with opportunity to mine TCAP data, prepare a paper in a collaborative fashion fully developing plant breeder human capital.	Better trained more employable plant breeders.
Support attendance of 50 students at the National Association of Plant Breeders (NAPB) meeting.	50 students attend the NAPB meeting.	Provide exposure of students to other plant breeders and students working on a variety of crops in both private and public sector.	Better trained more employable plant breeders.
Support 10 students to visit CIMMYT.	10 Students visit CIMMYT.	Broaden student exposure and awareness of international research.	Better trained more employable plant breeders.
Continue supporting research collaborations with faculty and students at Minority Serving Institution (MSI).	Seven TCAP faculty and seven MSI faculty and their students collaborate on research.	Faculty develop deep collaboration to better build bridge for students from MSIs to plant breeding. Students attracted to internships at TCAP institution or industry.	Recruit more diverse students into plant breeding careers.
Recruit students from underrepresented groups to the plant breeding profession.	TCAP PIs visit three MSI institutions, utilizing materials created by TCAP.	Increase awareness and interest in plant breeding, strengthen bridge and research collaboration with MSI faculty.	Recruit more students from underrepresented groups into plant breeding careers.
Support undergraduate research internships at TCAP institutions	30 undergraduates mentored by TCAP PIs/Graduate students.	Increase undergraduate student confidence in research and interest in graduate studies.	Recruit more diverse students into plant breeding careers.
Support mentors of undergrads through entering mentoring program.	Provide supportive information and training opportunity for mentors.	Improved undergraduate research experience.	Improve plant breeders as mentors.
Undergraduate online synchronous and asynchronous support.	Students interact with each other and professionals in the field, students are provided with career information.	Support undergraduate research experience and expose undergrads to other students and others working in the field.	Help recruit students into plant breeding careers.
Create two inquiry-based lessons focused on TCAP-related research.	Create tools that will be demonstrated at a workshop and shared broadly with faculty	Support faculty in adopting inquiry-based learning.	Improve training of students.
Conduct inquiry-based learning workshop.	Host 10 to 20 faculty at an inquiry based learning workshop	Support faculty in adopting inquiry-based learning.	Improve training of students.
PBTN improvement and support.	Develop a list of improvements from users.	Prioritize list and implement changes and support.	Ensure continued use of PBTN.
In depth interview of PIs, students and MSIs.	Further explore survey results.	Gain a better understanding of expectations of PIs and students, development of publications.	Improvement of project.
Survey PIs, students and MSIs.	Compile surveys.	Compare and contrast between groups and years.	Improvement of project.
Evaluation report	Summarize evaluation findings.	Report findings in publications to broad audience.	Improve TCAP education impact.
Advisory panel meeting.	Solicit advice from advisory panel.	Improve education component.	Improve TCAP education impact.
PI focus group.	Solicit advice from TCAP PIs.	Improve education component.	Broaden TCAP PI support and project impact.

B. OUTCOMES & IMPACTS (year 2, 2012)

B.1. OUTCOMES & IMPACTS OBJECTIVE 1.

Discover and deploy beneficial alleles from diverse wheat and barley germplasm.

B.1.1. High-throughput phenotyping using Canopy Spectral Reflectance (CSR): The implementation of CSR technology has provided breeders a new tool to evaluate the response of barley and wheat accessions to water stress quickly (less than a minute per plot) and without having to destroy the material. This has positively impacted breeder’s ability to conduct research on drought tolerance and is expected to accelerate the release of varieties with improved WUE.

B.1.2. Water use efficiency: The favorable alleles for WUE identified in wild species of wheat and barley have expanded the genetic diversity that breeders can use to improve this trait. The development of WUE association mapping panels in barley and wheat has provided additional tools to identify favorable alleles for dry conditions in a wide range of germplasm. The increased diversity of WUE alleles discovered in these studies is expected to have a positive impact in the rate of improvement of this trait.

The results from the evaluation of dedicated sets of isogenic wheat lines for photoperiod sensitivity, semi-dwarf growth habit, and solid stem under water limited conditions provided additional information for WUE improvement. The 2012 results showed a positive effect of the solid stem trait for wheat improvement under dry conditions. The solid-stem variety ‘SY Tyra’ is being marketed in Montana and North Dakota. The 2012 results also showed that Rht-B1b and Rht-D1b alleles are superior to Rht8 as a source for height-reduction for spring wheat in environments characterized by terminal drought stress. We also found that photoperiod sensitive lines are superior to photoperiod insensitive lines for the northern Great Plains; a difference that is likely to be enhanced as planting date becomes earlier due to increasing spring temperatures. This information will be useful to select better parental lines for the breeding crossing blocks.

The identification of the distal region of the 1RS chromosome as the one responsible for drought tolerance in the rye-wheat translocation demonstrated that the rye Sec1 locus (associated to sticky dough) can be removed without affecting drought tolerance. A direct impact of this result is the engineering of a 1B chromosome combining the 1RS distal region for drought tolerance, the Yr15 gene for stripe rust resistance, and the high molecular weight glutenin allele Glu-B1 7Bx-over-expressor for strong gluten.

The study of root architecture in a selected set of germplasm has provided practical knowledge of the relationships among root characters and agronomic traits under drought stress. This information will impact the development of new varieties with root characteristics appropriate for dryland production.

B.1.3. Nitrogen use efficiency: The deployment of the high grain protein content allele Gpc-B1 allele from T. turgidum ssp. dicoccoides in four commercial wheat varieties is a tangible outcome of our efforts to improve NUE. These varieties have 5 to 10% higher grain protein content (GPC) than isogenic lines without the functional Gpc-B1 due to a more efficient N remobilization and therefore require less N fertilization to achieve similar levels of GPC.

The development of NUE association mapping panels in barley and wheat has provided breeders a powerful tool to identify additional alleles for NUE in a wide range of germplasm. This information will positively impact the deployment of favorable alleles for NUE into variety development programs.

B.1.4. Diseases resistance: The evaluation of the NSGC and dedicated association mapping panels for resistance to the current races of the major pathogens of barley and wheat has provided breeders with a larger set of resistance genes to deploy in their breeding programs and to anticipate changes in pathogen distribution due to climate change.

The outcomes in barley include the identification of accessions containing resistance to stripe rust, stem rust, spot blotch, spot form net blotch and the cereal yellow dwarf virus (CYDV). During this year, we also identified 17 accessions resistant to the highly virulent isolate ND4008 of the spot blotch pathogen (Cochliobolus sativus). Nine barley lines were also identified with broad resistance to four diverse isolates of the spot form net blotch pathogen (Pyrenophora teres f. maculata) from North Dakota, Australia, New Zealand, and Denmark.

The outcomes in wheat include the results of the first association mapping studies for rust resistance. In total, 35 significant stem rust resistance loci were detected with races BCCBC, TTTTF, a bulk of North American isolates, TTKSK, and TRTT; 2 loci were identified in the screen with leaf rust Race 1; and 14 loci significantly linked to resistance to stripe rust were identified in the field nurseries in CA and WA (2011 and 2012).

The high-density mapping projects have resulted in more precise markers for stem rust resistance genes Sr13, Sr21, Sr25, and Sr35; leaf rust resistance gene Lr21; and the stripe rust resistance genes Yr48 and the 2BS QTL from Louise, that will have a favorable impact in the precision of the marker-assisted selection programs using these markers. Additional outcomes include new markers and QTL identified for fusarium head blight.

The availability of a greater diversity of resistance alleles impacts the deployment strategies for disease resistance alleles in the US wheat and barley breeding programs. In addition, the wheat and barley breeders are incorporating the resistant germplasm identified in the disease screens described above in their crossing blocks.

A concrete outcome for this year is the release of new varieties and germplasm incorporating and combining different disease resistance alleles. These include the wheat cultivars UI Stone (ID, Fhb1), Rollag (MN, Fhb1 & Lr34), Norden (MN, Fhb1 & Lr34); Patwin 515 (CA, Yr5 & Yr15), 5187J (VA, Sr24 1RS-1A translocation) and 12V51 (VA, Lr29); and PI 656793 and PI 664549 germplasm (CA, Yr36). The improved resistance of the varieties with these resistance genes has a positive impact in the reduction of fungicide applications, with the associated positive impacts on production costs and environmental impact.

B.1.5. Enhanced value of the National Small Grain Collection. An additional outcome of the TCAP activities is the renewed interest in the wheat and barley core germplasm collections. The detailed genotyping and phenotyping for WUE, NUE and disease resistance has increased the value of the US wheat and barley NSGC core germplasm collections. This added value is attracting breeders to utilize this germplasm in their breeding programs.

B.1.6. Population development. An important outcome of this project is the development of publicly available association mapping (AM) panels and nested association mapping populations (NAM). The genotypic and phenotypic characterization of the AM panels started in 2012 has greatly increased their value. The NAM populations incorporate a wide sample of the NSGC diversity and deploy it in more adapted genetic backgrounds, which facilitate its utilization by public and private breeding programs.

The availability of fully genotyped AM and NAM populations will have a long term impact in wheat and barley research by providing a valuable public resource for the rapid identification of linkage between traits and genotypes. Since lines will be fully genotyped, the cost of future experiments will be limited to phenotyping costs, encouraging breeders and researchers to initiate new projects to dissect novel traits.

An additional outcome of the population development activities is the increased interest in wild barley germplasm. The wild barley introgression-lines have expanded the genetic diversity available to barley breeders and, by incorporating it into a more adapted genetic background, facilitated its deployment into new commercial varieties.

B.1.7. Genotyping. A central outcome of this project is the increased interest in genetic studies in barley and wheat that are now easier and faster to complete using the new iSelect SNP platforms. The impact of these platforms on wheat breeding programs world-wide is documented by the order of 46,000 assays for the first round of experiments using the wheat iSelect 90,000 SNP platform.

An outcome of the improved SNP maps developed this year is the improved ability of breeders and researchers to directly connect the barley and wheat information with information available for sequenced grass species. In addition, the mapping information provides a powerful tool for haplotype analyses, and a scaffold to assemble the incoming wheat sequences coming from next generation sequencing technologies.

The improved barley SNP metadata is accelerating the identification of the functional consequences of individual SNPs and the ancestral state of mutations. This information has a positive impact on population and evolutionary studies performed with these data.

An outcome of the genotyping of the NSGC core barley and wheat collections is the increased value of this germplasm collections and the renewed interest in its utilization. This deep genotyping also has an impact in the re-organization of the core collection, the elimination of duplicate accessions, and the generation of sub-collections based on genotyping information.

B.2. OUTCOMES & IMPACTS OBJECTIVE 2

Accelerate breeding through marker-assisted selection and genomic selection.

A direct outcome of the improved genotyping capability is the improved ability to select for multiple agronomic, disease resistance and quality traits. These new selection tools have the potential to accelerate the development of new wheat and barley varieties through MAS.

The development of cheaper SNP platforms has made possible the implementation of genomic selection (GS) strategies in barley and wheat. An outcome from these studies is the assessment of the accuracy of GS on multiple traits and an estimate of potential gain from the GS. An additional outcome of these studies is the ability to compare random, phenotypic and GS strategies on the resistance of facultative barley varieties to low temperatures. These activities will have a positive impact on the development of facultative barley varieties that can be planted in the fall, expanding the range of environments relative to the current varieties.

B.3. OUTCOMES & IMPACTS OBJECTIVE 3

Implement sequence-based genotyping methods to discover new allelic diversity.

The integration of GBS and SNP mapping data will increase the ability of barley and wheat breeders and researchers to conduct high resolution mapping of NUE, WUE, and disease resistance genes. More precise markers will benefit current MAS efforts to develop new varieties that can ameliorate the negative impacts of climate change.

An important outcome of the first exome capture experiments in barley and wheat is the demonstration that this technique is feasible in species with very large genomes. A likely impact of these results will be the initiation of large resequencing projects of the gene space in barley and wheat. The exome capture technology will also have a positive impact on the identification of mutated genes in barley and wheat. Finally, the comprehensive analysis of allelic variation in the gene space will help us to understand the genetic basis of agronomic traits and accelerate the development of new varieties through allele-based breeding.

B.4. OUTCOMES & IMPACTS OBJECTIVE 4

Implement web-based tools to integrate marker-assisted selection and genomic selection strategies into breeding programs.

Activities in 2012 made T3 easier to use, particularly for upload of data. An outcome of this activity is that more TCAP participants from more institutions contributed data to T3. Increased contact of participants with T3 has a positive impact on TCAP as it ensures timelier sharing of data and greater education to the use of databases that are becoming essential tools in plant breeding.

Use of T3 has promoted dialogue toward the standardization of phenotyping methods and data storage. This process of standardization is ongoing but has the important impact of facilitating collaboration between programs that are part of TCAP. For example, TCAP is moving forward with protocols for canopy spectral reflectance measurement, and T3 is playing a role in coordinating a uniform format for the storage of these data.

Data content in T3 has expanded dramatically, with the impact that data acquisition for analyses is facilitated. For example, T3 store 9K genotype data on wheat accessions of the core collection of the National Small Grains Collection (NSGC). We took the initiative to also store phenotypes that have been evaluated by NSGC. A single visit to T3 now makes it possible to run association analyses on any trait evaluated by NSGC. Similar synergy will make it possible to analyze data gathered from across programs for a single objective much more easily than in the absence of T3.

B.5. OUTCOMES & IMPACTS OBJECTIVE 5

B.5.1. Change participants’ views of innovative recruitment and education

The Plant Breeding Training Network (PBTN) has provided an efficient way of communication among the US wheat and barley breeding and research programs and facilitated nation-wide rapid implementation of technological advances. Participants of the project use the TCAP seminar series in the same online environment to get updates on the latest developments in different breeding areas as documented by large participation in these seminars. Participants view the seminar series as an important tool that will help ensure the success of the project. The seminar series has served as an entry point for other online activities. The PIs and coPIs are realizing that the PBTN is a valuable tool to expand the training of their graduate and undergraduate students. An important impact of the PBTN is a cohort of plant breeding students that are better integrated into breeding and research activities and that understand better the collaborative nature of the plant breeding projects.

The PBTN collaborative problem solving activities were instrumental to solve the technical difficulties of the CSR equipment. This and other success stories are improving the perception of project participants about the effectiveness of distance collaboration tools. The communication network established by the PBTN has provided a rapid way to share information within the TCAP and has facilitated the adoption of new technologies (e.g. CSR and T3).

B.5.2. Change undergraduate students’ views of plant breeding and allied fields

TCAP recruitment efforts have raised minority student interest. Ten students have contacted Sherman with interest in internships and are being connected to industry opportunities. Two minority students from University of Arkansas, Pine Bluff (UAPB) have applied to graduate school and 1 student from Woodland Community College (CA) has begun an internship in drought tolerance at UC Davis. The success of MSI faculty in attracting students to our program indicates the importance of intentional mentoring. MSI faculty not only provided research guidance, but also helped students prepare presentations as well as graduate applications. The “Entering Mentoring” seminar had a positive impact in the mentoring skills of the participating graduate students.

C. OUTPUTS (year 2, 2012)

C.1. OUTPUTS OBJECTIVE 1.

Discover and deploy beneficial alleles from diverse wheat and barley germplasm.

C.1.1. High-throughput phenotyping using Canopy Spectral Reflectance (CSR)

Output: Improved CSR methods

The previous configuration of the Jaz spectrometer resulted in limited efficiency in the NIR wavelengths (970 nm rectangle in the figure). The problem was corrected by replacing grating number #4 by grating #14 and using improved silver mirrors (see figure) for those projects focused on WUE. Grating #14 provided improved efficiency in the NIR wavelength used in the water indexes (970 nm). We introduced a new scanning protocol that improved the precision of measurements by “scanning” along the plot, integrating 400 images into a single plot reading. This method also saves time when collecting and analyzing data, as the scanning method saves only one file per channel. The use of 400 subsamples instead of 4, greatly improved the precision of the measurements of individual plots. A Perl script has been written to expedite processing of the CSR data. A web seminar was organized to update the TCAP users of CSR of these improvements (April 26, 2012, 30 participants).

The TCAP coPI from the University of Nebraska has established a collaboration with the Center for Agricultural Land Management and Information Technology (CALMIT) for collecting canopy spectral reflectance (CSR) of their NUE trial using field equipment and to explore aerial spectral monitoring by a small aircrafts.

C.1.2. Water use efficiency

Output: barley populations evaluated for WUE

C.1.2.1. Spring 2-row (SP2) and 6-row (SP6) panels: Seed for the spring 2-row (256 lines) was planted at four locations: Fort Collins, CO (dry and normal), Aberdeen, ID (dry and normal) Bozeman, MT (dry) and Huntley, MT (normal). The SP6 panel was planted at Fort Collins, CO (dry and normal). WUE was determined by comparing phenotypes under a normal/full irrigation schedule and limited irrigation schedule (50-60% of normal). Genotyping was completed.

C.1.2.2. Winter 6-row (WN-6): Seed for the winter 6-row panel (300 lines) was planted at Corvallis, OR. WUE was determined by comparing phenotypes under a normal/full irrigation schedule and limited irrigation schedule (50-60% of normal). The panel will be genotyped with the 9K iSELECT SNP chip in 2012.

C.1.2.3. The Barley World Core evaluated for low temperature tolerance (LTT): Fall planting is a valid strategy to improve WUE, but it requires genotypes tolerant to low temperatures. A set of 400 accessions from the barley World Core was planted at St. Paul, MN and Pendleton, OR in the fall of 2011. Differential winter injury was rated as the % of the plot surviving and differential yellowing. Data are being analyzed. Genotyping with the 9K SNP chip is completed and data are in T3.

C.1.2.4. LTT Panel: Germplasm (384 lines) with potential LTT will be genotyped with the 9K SNP chip in 2012. The James Hutton Institute provided an additional 344 accessions, already genotyped with the 9K iSELECT SNP chip. The winter 6-row panel (300) will be added to this set; it will have been genotyped with the 9K SNP chip for the purposes of NUE and WUE. The final panel will be reduced to 1,000 accessions. This panel will be tested for LTT in MN and increased for seed in OR starting fall, 2012. An international consortium has been formed to test the panel for LTT in 2012-2013.

Output: wheat populations evaluated for WUE.

C.1.2.5. Hard winter wheat association mapping population for WUE: The population was planted in Greeley, CO under drip irrigation. Two very distinct soil moisture environments were generated, which showed large differences in leaf area, tiller number, CSR, relative water content and biomass. The panel has also been planted under dryland and irrigated conditions in Kansas. All traditional yield component data and CSR data have been obtained. Two field trials of the same population are also growing in Etter and Bushland, TX. Data is being recorded at those sites for maturity, plant height, and yield components.

Analysis of root traits in the Hard Winter Wheat Association Mapping Panel included evaluation of the 30 cultivars and advanced lines in a replicated greenhouse trial. Plants were grown in PVC tubes 1 m deep. Starting at the four-leaf growth stage, water was withheld from plants for three weeks, followed by harvest of above- and below-ground plant parts. Roots were cleaned, stained with methylene blue for better contrast, scanned for digital analysis, dried, and weighed. WinRhizo root analysis software (Regent Instruments, Quebec, QC) is being used to analyze digital scans of root biomass from each of three depths in the tubes (top, middle, and bottom thirds). Measurements of root diameter, root length per diameter class, and root volume are being compared among rooting depths and genotypes and correlated with WUE measurements.

C.1.2.6. Hard spring wheat association mapping population for WUE: 250 elite spring wheat lines from 12 breeding programs are being genotyped with the iSelect 90,000 SNP wheat array. Data from the 2011 WUE trial in Montana was entered into the T3 database. The panel was evaluated in 2012 in WA (two locations), CA (dry and irrigated), MT (two locations), KS (dry and irrigated) and ID. Seed was provided to a cooperator in Saskatchewan, Canada (one location) and for seed production for additional Canadian locations in 2013. A cooperator in North Dakota has planted the panel to obtain cereal quality data for association analysis. The Spring Wheat AM Panel is also being measured for root traits (Kansas) using plants grown in 1.5 m columns in a greenhouse. Data on plant height, number of tillers, and rooting depth is currently being analyzed. Roots of selected genotypes with maximum, minimum, and intermediate rooting depth will be subjected to complete image analysis (WinRHIZO software). Vegetative growth has been monitored by taking early vigor scores, number of elongated nodes, heading dates, and plant height at three consecutive dates. SPAD leaf greenness and CSR have been taken at three consecutive stages.

C.1.2.7. Mapping of the 1RS drought tolerance gene(s): The drought tolerance gene present in the rye 1RS.1BL translocation was mapped using four sets of near-isogenic lines (NIL). Water index NWI3 was determined by CSR and yield components were measured. The rye gene(s) for drought tolerance were mapped within the distal rye segment. Recombinant lines are being developed to dissect this distal segment.

C.1.2.8. Evaluation of three genes for semi-dwarf growth habit: The objective of this experiment was to assess the impact of the height-reducing gene Rht8 relative to the standard Rht-B1b and Rht-D1b alleles on performance of spring wheat in MT, WA and CA environments characterized by terminal drought stress. Evaluation of NILs developed in four genetic backgrounds showed that Rht-B1b, Rht-D1b, and Rht8 caused height reduction of 19, 20, and 6.5%, respectively, relative to wild-type NILs. Significant increases in grain yield were associated with the Rht-B1b and Rht-D1b genes. Lines with Rht8 yielded less than wild-type. Lines with Rht-B1b and Rht-D1b tended to have a higher harvest index and more seed per spike than wild-type lines and reduced height lines with Rht8. In summary, our results suggest that Rht-B1b and Rht-D1b are superior to Rht8 as a source for height-reduction for spring wheat in environments characterized by terminal drought stress.

C.1.2.9. Relationship of photoperiod response and adaptation to a changing climate:

Spring wheat lines are divided into photoperiod insensitive (PI) or photoperiod sensitive (PS), the latter requiring long days for flower initiation. To assess the impact of earlier spring wheat plantings due to climate change, sets of NILs for photoperiod sensitivity were tested at three planting dates in 15 environments in MT, WA, Saskatchewan and Alberta. Grain yield was significantly greater for PS lines at the first two planting dates, though no difference between PS and PI lines occurred for the latest planting date. These results suggest that PS lines are superior to PI lines for the northern Great Plains.

C.1.2.10. Evaluation of near-isogenic lines for stem solidness and stay-green phenotypes: Previous experiments with recombinant inbred line populations allowed identification of QTL for major genes for stem solidness and long green leaf duration after heading. Both traits have shown association with drought tolerance in previous studies. NILs for these QTL alleles were evaluated at two MT locations in 2011. Results confirmed the impact of the solid stem QTL, but did not confirm the stay-green QTL. Larger experiments were planted at two locations in MT and two locations in WA to determine the impact of physiological traits stem solidness and stay-green leaves on drought tolerance.

C.1.2.11. Evaluation of hexaploid and tetraploid RIL populations from a hexaploid / tetraploid cross: The goal of this experiment is to identify QTL for drought tolerance that may be exchanged between hexaploid spring wheat and tetraploid durum wheat. A RIL population containing ~100 lines for each ploidy level was developed by crossing hexaploid Choteau with tetraploid Mountrail. The hexaploid RILs tended to be superior to the tetraploid ones, suggesting that A and B genome genes from the hexaploid had a deleterious impact on performance of the tetraploid RIL. All tetraploid RIL yielded significantly less than the tetraploid parent. Conversely, genes from the tetraploid were not deleterious to the hexaploid RILs. In fact, several hexaploid RIL yielded significantly more than the hexaploid parent Choteau. These results suggest that favorable genes from tetraploid wheat will be identified for improvement of hexaploid spring wheat. The population is being genotyped with the 90,000 SNP array.

C.1.2.12. Evaluation of wheat chromosomal translocation lines for high temperature tolerance: Dasypyrum villosum and Aegilops geniculata are diploid wild relatives of bread wheat that have agronomically-important genes for wheat improvement. The objective of this research was to evaluate selected chromosomal translocation lines for high temperature (HT) tolerance. Sixteen wheat chromosomal translocation lines and four bread wheat varieties were grown at optimum temperature (OT) of 22/14°C day/night and full irrigation in a greenhouse in Kansas. Ten days after anthesis half of the plants were exposed to HT stress of 34/26°C, and the other half remained at OT. The stress period was for 16 d; plants were then returned back to OT. High temperature decreased leaf chlorophyll content by 22%, maximum quantum yield of photosystem II (Fv/Fm) by 39%, individual grain weight by 44% and grain yield by (45%), when averaged across the genotypes. There was genetic variability among chromosomal translocation lines for yield traits. The tolerant genotype TA 5608, identified in this study can be utilized in improving high temperature tolerance of bread wheat cultivars.

C.1.2.13. Evaluation of Asian spring wheat lines for high temperature tolerance: Kansas State University evaluated heat tolerance of 161 Asian Spring wheat lines and 6 checks. These Asian lines were mainly from China and Japan, and the checks were Excalibur, Krichauff, Halberd, Kukri, Len and Siete Cerros. Phenotypic data were collected from plants grown in a controlled environment. Plants of each line were grown in non-stress condition in growth chambers. At the post-anthesis stage, 50% of the plants from each line were used for heat treatment. Heat tolerance-related traits including chlorophyll degradation rate and grain yield were measured. The results showed that heat stress decreased grain yield by 42% when averaged across all genotypes. Average heat susceptible index (HSI) of all genotypes is 0.937. Seven Asian Spring lines produced greater grain yields in both heat stress and non-stress conditions, and showed lower HSI than the heat tolerant checks. These experiments are being repeated in 2012, and the best lines will be transferred to the breeding programs.

C.1.3. Nitrogen use efficiency

Output: barley populations evaluated for NUE

C.1.3.1. Barley: NUE is being evaluated using the spring six-row (SP6), spring two-row (SP2), and winter six-row (WN6) association mapping panels in a low (70%) nitrogen and normal (100%) nitrogen environment. In 2011, the SP6 and SP2 AM panels were evaluated in MN and MT and agronomic data was collected in both locations. CSR data was collected only at MT. Data was uploaded in T3.

In 2012, the SP6 AM panel was planted in MN, ND, and WA. The SP2 AM panel was planted in MT, WA, and ID. The WN6 AM panel was planted last fall in Crookston, MN, Corvallis OR, and Logan UT. The MN location was lost to complete winterkill of the plots. The OR location (Corvallis) was planted in 2011. There was complete winter survival. Based on soil tests, N was applied in fall and spring. CSR measurements were obtained. The UT location was planted in 2011. Winter survival and heading notes have been taken and CSR measurements have been completed.

Output: wheat populations evaluated for NUE

C.1.3.2. Hard Winter Wheat Elite panel: The field experiment for NUE and yield evaluation was planted in the fall of 2011 at OK and NE. This panel is also being used for WUE and irrigated, normal N trials were also established for that purpose in KS and CO. Thus, there are two locations for NUE and four for yield. The NE and OK sites were planted in a split-plot design for moderate N and low N treatment. Above-ground tissue samples were collected from two 30 cm sections of row from each plot as plots reach anthesis. Dried tissue samples are being analyzed for N and mineral concentration. The complete panel has been submitted for genotyping and line information has been uploaded to the T3 database. The second year data will be collected in 2013.

C.1.3.3. Soft Winter Wheat Elite Panel: This panel was planted for yield and NUE evaluation in the fall of 2011 in Wooster, OH, and Warsaw, VA. The panel was also planted for yield using normal N rates in Columbia, MO, KY, and MD. The OH and VA sites were planted in a split-plot design for high N and low N treatment. N levels were determined based on yield goals and soil N for each location. An equal N amount was applied in the fall at planting and the differential N rates were applied in the spring. Dried tissue samples are being collected and analyzed for N and mineral concentration. The complete panel has been submitted for genotyping and line information has been uploaded to the T3 database.

Most program locations (OK, MO, KY, OH, MD, and VA) collected CSR readings using the JAZ spectrophotometer. OK and OH collected data at flag leaf and boot stages, VA at Zadoks 31, 41, and 51. In OK at anthesis, whole plant samples were collected from each plot to document biomass and nutrient uptake. VA has conducted an additional field experiment with five soft red winter wheat and 16 sampling patterns as treatments. CSR data was collected 50 cm above the canopy level in eight treatments and at 100 cm for the other eight. Spectral readings are being collected at Zadoks stages 35, 45, 55, and 75.

C.1.3.4. Genetic variability for root traits in a sample of the world collection: A study was conducted at Kansas State to quantify genetic variability for root traits in 296 spring wheat genotypes from the Washington State University (WSU) World Wheat Collection. Single plants of all genotypes were grown in 1.5 m columns in a green house. Data on plant height, number of tillers, and rooting depth are currently being analyzed. Roots of selected genotypes with maximum, minimum, and intermediate rooting depth were subjected to complete image analysis (WinRHIZO software) for quantifying traits such as total length, surface area, and volume of total root mass and of roots of various size classes. Partial results indicate that considerable genetic variability exists in WSU World Wheat Collection for root traits that can be exploited to improve drought tolerance and/or resource capture in wheat.

Output: new wheat varieties with improved NUE

C.1.3.5. Deployment of the Gpc-B1 allele. The functional Gpc-B1 allele from T. turgidum ssp. dicoccoides increases grain protein content (GPC) by 5 to 10%. This allele has already been incorporated in the durum wheat varieties Desert King-High Protein and Westmore (CA) and in the common wheat varieties Lassik (CA) and Farnum (WA) and is being extensively used in several MAS programs.

C.1.4. NSGC core collection evaluated for WUE and NUE

Output: NSGC core collection evaluated for yield, NUE and WUE.

C.1.4.1. Barley: The focus for year two is spring barley (year one was focused in spring wheat). Over 500 six-row spring barley accessions from the NSGC core collection and five checks used in the elite panel were planted in an augmented complete block design in a drip irrigation nursery at Aberdeen, ID. The design was replicated under three different water/nitrogen treatments: normal water and normal nitrogen, terminal drought and normal nitrogen, terminal drought and low nitrogen. Data has been collected and is being analyzed

C.1.4.2. Spring wheat: Although not planned in the original TCAP proposal, we decided to retest the 540 spring wheat NSGC accessions evaluated in 2011 to obtain a more precise evaluation of the phenotypes and to test the reproducibility of the WUE results across years. The 540 wheat lines are being tested under two treatments: normal water and terminal drought (both with normal nitrogen). All wheat and barley accessions are being evaluated for water and N use efficiency (WUE and NUE) using Canopy Spectral Reflectance (CSR) equipment upgraded with a #14 grating system and silver mirrors. In addition, 256 elite spring wheat lines were planted under limited water conditions in Aberdeen and will be evaluated for yield and WUE.

C.1.4.3. Winter Wheat: Over 600 winter wheat accessions from the NSGC were planted in a rain-fed environment in Rockland for a preliminary evaluation of yield and agronomic performance and for a seed increase for the 2013 evaluation.

C.1.4.4. Breeding applications of the 2011 NSGC data: Data collected from 2011 were submitted to T3 and is being used to development a Mini Core Collection for wheat. The 2011 evaluation also yielded useful materials for the breeding programs. Out of the 540 spring wheat accessions evaluated in 2011, thirty were selected and used in crossing in several breeding programs. A set of 123 hard white spring wheat accessions has been used in association analysis to identify QTL associated with late maturity alpha amylase, an important quality defect that is widespread in hard spring wheat varieties in the western USA. Three chromosome regions were identified. This set of materials has also been used in association mapping for fusarium head blight and baking quality.

C.1.5. Diseases

Output: Barley NSGC core evaluated for multiple diseases

C.1.5.1. Stem rust resistance: The first half of the barley NSGC core (1,050 accessions) was sent to Greytown, South Africa for adult plant phenotyping to African stem rust. These lines were sown in mid-June and inoculated three times with stem rust. Disease severity assessments were made in mid-November, but rust infection was low and not evenly distributed in the nursery, making the data of little value for association mapping. Only the first half of the barley core collection was shipped to Njoro, Kenya for rust evaluation due to a quota on the number of barley lines allowed in the main season nursery. Disease assessments will be taken in mid-October. The second half of the barley core collection will be sent to Kenya in November 2012 for the off-season nursery. This material will be scored for rust reaction in late March 2013.

C.1.5.2. Stripe rust resistance: The entire barley core collection (2,062 entries) was planted at the Hyslop farm in Corvallis. All of the accessions survived the winter and were evaluated for leaf scald and stripe rust. Data are being uploaded into T3.

C.1.5.3. Spot blotch resistance: The second half set of the NSGC Barley Core Collection (total of 1,012 accessions) was evaluated for seedling reactions to the spot blotch pathogen (Cochliobolus sativus) in the greenhouse using the highly virulent isolate ND4008. Three experiments (replicates) were conducted. Assessments for disease were made according to the 1-9 scale developed by Fetch and Steffenson (1999), with 1 being most resistant and 9 being most susceptible. Susceptible controls showed readings ranging from 6-8, while moderately resistant controls had readings ranging from 4-5. Among the 1,012 accessions tested, 17 (1.7%) were resistant with readings ranging from 2-4 and 187 (18.5%) showed moderate resistance with readings ranging from 4-5. The remaining accessions (808/79.8%) were susceptible with readings from 6-9. Data are being uploaded into T3.

C.1.5.4. Spot form net blotch resistance: Seedling screening for resistance to the spot form net blotch pathogen (Pyrenophora teres f. maculata) was completed on the first half of the barley core collection (1,050 accessions). Phenotyping was completed on the 1,050 line set with a highly virulent local North Dakota isolate (FGOB10Ptm1). Lines were scored on a 1-5 reaction type scale. Barley lines showing an average disease reaction of 2 or less (81) to isolate FGOB10Ptm1 were evaluated with three additional isolates including SG1 (from Australia), NZKF2 (New Zealand), and Den2.6 (Denmark). Of the 81 lines that showed good levels of resistance (≤2) to ND isolate FGOB10Ptm1, only nine lines showed the same level of resistance to the other three isolates indicating high levels of diversity in both resistance and virulence. Currently, the second half of the barley NSGC is being phenotyped in the same manner to identify additional barley accessions with the highest potential for durable resistance. These evaluations will be completed by December 2012. Using single seed descent, we developed genetically clean stocks of several of the resistance sources for use in future crosses. The crossing block has been established and TCAP students will assist in the development of genetic materials for resistance characterization.

Output: wheat NSGC core collection evaluated for multiple diseases

C.1.5.5. Analysis of the NSGC wheat core 2011 data: Preliminary association mapping analyses have been conducted using the leaf, stem, and stripe rust data collected in 2011, on 1000 spring wheat lines from the NSGC core collection. These lines have been genotyped with the iSelect 9000 SNP wheat chip. In total, ~35 resistance loci that are significant after accounting for experiment-wide error rates have been detected with wheat stem rust races BCCBC, TTTTF, a bulk of North American isolates, TTKSK, and TRTT. Association mapping with data from stem rust evaluation of adult plants in the field in Minnesota resulted in the identification of 2 SNP markers that represent a single locus. Association mapping of leaf rust resistance in the seedling stage with Race 1 resulted in the identification of 2 loci. Association mapping of stripe rust reaction in field nurseries in CA and WA (2 locations) under conditions of natural infection resulted in the identification 14 significant resistance loci linked to ~30 SNP markers. A second year of data has been collected in 2012 in both locations and is being analyzed.

C.1.5.6. Selection of promising lines from the NSGC wheat core collection: From the first 1,000 NSGC spring wheat core accessions evaluated in 2011, 29 were selected that showed low (≤10%) severity to leaf rust. The 29 lines were screened with 10 leaf rust races to postulate major leaf rust resistance genes and were crossed to the susceptible line Thatcher to develop bi-parental mapping populations. The 29 lines were also screened for adult plant resistance in the greenhouse using a mixture of races. DNA was collected from each line and screened with SSR markers for nine known leaf rust resistance genes (Lr16, Lr19, Lr21, Lr24, Lr26, Lr32, Lr34, Lr37, and Lr46). Fifteen of the 29 crosses were selected based on adult plant, seedling, and marker screenings to be planted in the field in 2012 as F₂’s for advancement. Ten populations will be evaluated in the fall for seedling resistance and 5 for adult plant resistance and advanced by the SSD.

From the same 1,000 NSGC core lines, 30 were selected based on their resistance to stem rust, and other agronomic traits and were crossed with susceptible parent LMPG-6 in fall 2011. Seedlings of all lines were screened with stem rust races from North America (10), East African (3, Ug99 complex), Yemen (1), and Pakistan (1). These selected lines were also screened with available SSR markers for 17 Sr genes. Based on the information gathered from seedling screening, marker screening and their parental pedigrees, we identified four lines as potential new sources of resistance to North American stem rust races, two lines resistant to the East Africa races (Ug99) and 2 lines resistant to Yemeni and Pakistani races. Bulk segregant analysis will be carried out on F_2:3 families of all 8 populations in fall 2012. Also, RIL populations will be generated from 15 F₂ populations with potential novel APR genes. These 15 F₂ populations were planted in St Paul in summer 2012 and subsequent generations will be advanced via SSD. After additional evaluation, one or two RIL populations (F₆ or further inbred) will be selected for extensive phenotyping and genotyping.

Similarly, development of validation and mapping populations is underway for stripe rust resistance loci identified by association mapping results obtained in 2011. Depending on polymorphism at specific SNP loci, new resistance donors are being crossed to Avocet S, or another susceptible parent. Loci on chromosomes 1BS, 2BS, 2BL, 3BS, 4BL, 4DL, 5AL, 6BS, 6D, and 7B were initially selected.

C.1.5.7. 2012 phenotypic evaluations of the NSGC collection: Additional phenotypic evaluation is currently underway on the complete NSGC Core. All 1,417 winter wheat core accessions were evaluated for seedling leaf rust resistance with two different races and are currently being evaluated for seedling stem rust resistance with three races. These lines were recently evaluated in the field in TX and KS (3 locations) and as adult plants in a greenhouse test for adult plant leaf rust resistance. The lines will be evaluated for field stem rust resistance in MN this summer, and were evaluated at two locations in WA and one in CA for stripe rust resistance. All 1,000 spring wheat accessions evaluated in 2011 were re-evaluated in 2012 in CA and WA for stripe rust resistance in the field. In addition, the final 2000 spring wheat core accessions are currently being screened for leaf, stem and stripe rust under field conditions in MN (2 locations), CA and WA (2 locations). Seedling leaf, stem, and stripe rust screening on the complete core collection will be completed by the end of 2012.

Output: wheat mapping populations for AM and high density mapping

C.1.5.8. Evaluation of Winter Wheat Association Mapping panels: 310 hard winter wheat lines from the Winter Wheat Association Mapping Panel were evaluated for leaf rust resistance at the adult stage in the greenhouse, and in Castroville, TX, Hutchinson, KS, and Manhattan, KS in 2012. These data will be added to data collected in 2011 in Manhattan, KS. The panel has been genotyped with the iSelect 9,000 SNP wheat chip and data will be analyzed to identify resistance loci for leaf rust.

Approximately 160 additional elite breeding lines from another winter wheat panel were phenotyped for leaf rust resistance in the greenhouse, Castroville, and Manhattan, KS. These lines have also been phenotyped and will be used to augment the analysis of the main AM panel. The Winter Wheat AM panel was phenotyped for resistance to the new race of stripe rust identified at Hays and Hutchinson in 2012.

C.1.5.9. Lakin/Heyne RIL mapping population: This population was analyzed for resistance to stripe rust and QTL were found on 2AS (Yr17), 2BS, and 1A in Heyne as well as a QTL on 3A for Lakin.

C.1.5.10. KS05HW14*2/Kingbird: A BC₁F₅population of KS05HW14*2/Kingbird was scored for resistance to a new race of stripe rust at Manhattan, KS. The resistance of KS05HW14 was substantially defeated by the new race, but resistance derived from Kingbird segregated in the progeny. This population will be genotyped in the coming year. This population was also scored for resistance to the QFCSC race of stem rust at Manhattan, KS. KS05HW14 was partially resistant to QFCSC, possibly due to Sr7b. Resistance derived from Kingbird segregated in the progeny as well.

C.1.5.11. Spring wheat stripe rust resistance AM panel:
This panel, which includes 510 entries, is currently being evaluated in field nurseries in WA. This panel is a collection of various sources of resistance identified over the past 30+ years of germplasm evaluation at Washington State University. DNA of this panel has been prepared, and it will be SNP genotyped to identify favorable alleles associated with resistance. Avocet S was crossed to 70 spring wheat accessions with unknown resistance to stripe rust. F₂and BC₁F₁ populations for all accessions were advanced in 2012 field nurseries in WA.

C.1.5.12. Winter wheat stripe rust AM panel: This panel, which includes 486 entries, was planted in the field for stripe rust evaluation at two WA locations in 2012. Stripe rust has been evaluated. This panel will be genotyped with the iSelect 90K SNP wheat chip in 2012/2013 for association mapping.

C.1.5.13. Yr48 high density mapping: Yr48 was mapped in the distal region of 5AL 0.03 cM distal to AK336105 and completely linked to markers cfa2149 and gpw2149. A region of reduced recombination was identified in the distal part of 5AL and is being investigated by multiple crosses of both parental lines. A Yr48 EMS mutagenized population was grown in the field and 5 putative susceptible mutants have been identified and are being crossed to validate segregation.

C.1.5.14. YrLouise high density map: This locus on chromosome 2BS is a strong and consistent source of adult plant stripe rust resistance. Two populations of 1,536 progeny each have been advanced (Avocet S*2/Louise and Penawawa*3/Louise). Backcrossed-derived plants heterozygous for the QTL region were identified and self-pollinated, and over 3,000 F₃ families produced. We have completed SNP-based genotyping of 1,536 Avocet S*2/Louise F₂‘s, and detected ~170 recombinants in the QTL region. These 170 recombinant families along with 1,536 Penawawa*3/Louise BC₂F₃‘s are currently growing in a field stripe rust screening nursery.

C.1.6. Population development

Output: Advanced barley spring NAM populations

C.1.6.1. Barley Six-row NAM population: Kevin Smith (UMN) is developing the 6-row NAM population. A total of 93 crosses were made between the NSGC parents and Rasmusson. The F₁’s from these crosses were planted in January in the greenhouse and backcrosses were made to Rasmusson and each F₁ was self-pollinated. The 93 F₂ populations are comprised of approximately 100 individuals and the 93 BC₁ populations are comprised of 1-40 individuals. The populations will be advanced by single seed descent beginning in the fall of 2012 in the greenhouse.

C.1.6.2. Barley two-row NAM population: Rich Horsley (NDSU) is developing the 2-row NAM population. A total of 128 crosses were made between the NSGC parents and Conlon. The F₁’s from these crosses were planted in January in the greenhouse and 115 backcrosses were made to Conlon. Each BC1 population is comprised of approximately 100 individuals. The BC₁ populations will be advanced by single seed decent beginning in the fall of 2012 in the greenhouse.

Output: Advanced wheat NAM populations

C.1.6.3. Soft and hard winter wheat NAM populations: Thirty F₁ hybrids between accessions from the NSGC Core collection and ‘Overland’ have been made in the greenhouse to initiate the Hard Winter Wheat NAM population. Thirty-six F₁ hybrids between accessions from the NSGC Core collection and ‘Branson’ have been made in the greenhouse to initiate the Soft Winter Wheat NAM population. Crosses toward development of an NUE male-sterile facilitated Hard Winter Wheat recurrent selection population utilizing the NAM donor parents also have been made.

C.1.6.4. Spring wheat NAM populations: A total of 38 land-race accessions from around the world and 15 elite spring wheat lines from Montana, California, CIMMYT and Australia were crossed to the common parent Berkut. From initial populations of about 800 F₂ individuals for each landrace cross, approximately 300 F₄ individuals with semidwarf growth habit have been selected. These are currently being grown in a growth chamber under 12 hour days to select for photoperiod insensitivity. The goal is to develop ~75-100 semidwarf photoperiod insensitive RILs per cross (total 2500-3000 lines). These will have suitable agronomic properties for evaluation for WUE throughout our growing region. The seven elite populations from California are one generation behind and are being advanced at Tulelake as F₃ progenies, and will be ready for evaluation in 2014.

Output: Completed wild barley introgression population

C.1.6.5. Wild barley introgression population: TCAP graduate student Liana Nice (UMN) has developed a wild barley introgression population consisting of 25 wild barleys that represent 90% of the diversity in the 318 individuals of the wild barley diversity collection. These 25 wild barleys have been backcrossed twice to the elite six-row malting barley Rasmusson. On average, 32 BC₂ individuals have been derived from each of the 25 wild barleys for a total of 803 lines. Four generations of single seed descent have been conducted to derive inbred lines. A customized 384 SNP VeraCode assay has been designed and was used to genotype the population.

A total of 798 individuals of the population were grown in Crookston and St. Paul, MN in a type II augmented design. There are 60 entries of the primary check (Rasmusson) and 16 secondary checks (Harrington and Conlon, late and early heading, respectively) randomly arranged in the field as well as 26 repeated line entries to fill in the field design. To permit maturity-appropriate harvesting, the field was blocked using heading date (early, mid, late, and unknown). Multiple traits were scored on the population including: height, heading date, yield, and productive tiller number. Grain protein and spike phenotypes (seed/hull color, awn texture, shattering, nodes per spike, etc.) data will be obtained.

C.1.7. Genotyping

Output: improved barley SNP genotyping platform and maps

C.1.7.1. Integration of new and old SNP platforms: To integrate previous barley SNP genotyping with the new iSelect 9,000 SNP barley chip, the Tim Close lab used the information from the design of the SNP Illumina iSelect assay to generate a cross-reference to previous Illumina assays (Close et al. 2009 and HarvEST:Barley assembly #35 unigenes). A new master table of BarleyCAP Core SNP calls in ACGT format using Illumina TopStrand was generated and provided to collaborators and to the T3 database.

C.1.7.2. Improved barley SNP map: A new barley SNP map containing 2,994 SNPs was published and disseminated through GrainGenes and T3. The new map has higher marker density than the previous map, 19% higher resolution, improved marker order, and it allocates 300 additional SNPs to chromosome arms.

C.1.7.3. Improved automated SNP annotation: The project has made advances in the area of automated SNP annotation and automated SNP calling, particularly for barley. In an effort to improve consistency and repeatability of SNP calls in Illumina genotype data, Peter Morrell’s lab (UMN) worked with a number of collaborators to implement automated SNP calling. The approach used is implemented in the program Alchemy (Wright et al. 2010). The program was designed by the rice community, and is able to incorporate prior information to improve SNP calls. This information includes inbreeding coefficients for individual samples (to deal with expected heterozygosity), use of known genotypes, and a list of ‘bad SNPs’. The accuracy of the SNPs called with Alchemy was tested using multiple approaches, including comparison to genotypes from genetic mapping populations, comparisons to variant calls from Illumina RNASeq data, and comparison to existing SNP calls that were manually curated in the Illumina Genome Studio software. These comparisons suggest that Alchemy SNP calls are comparable to those from manual curation, but that calls are slightly more conservative, resulting in more ‘no calls’ from ambiguous SNPs. Alchemy SNP calling can be completed in minutes, and results are machine-scored and thus completely reproducible. It will be possible to design future genotyping efforts to include individuals with known genotypes that further improve SNP genotyping accuracy. Barley experience with automated SNP annotation will be very valuable for the analysis of the new wheat 90,000 SNP chip.

C.1.7.4. Improved SNP metadata: Without a complete reference genome, it is difficult to determine the potential functional consequences of individual SNPs. Potentially, many types of information could be collected for each SNP, including whether the variant is in a genic or non-genic region, in coding or noncoding sequence, and for exon variants, whether the change is synonymous or non-synonymous. This metadata is being compiled for all barley SNPs currently being genotyped including GBS data, with the goal of submitting all information both to T3 and the GenBank resource dbSNP. The Python tool was used to extract barley annotation from GenBank results for barley SNP contextual sequence compared to barley and wheat BLAST hits and for BLAST hits against the Brachypodium distachyon genome. For barley BOPA1 and BOPA2, a total of 2,457 SNPs could be annotated, with 91 SNPs annotated using Brachypodium BLAST results. The annotations identified 15% of SNPs as non-synonymous. The ancestral state of mutations can also be inferred relative to an out-group. SNP contextual sequence was compared to Hordeum bulbosum RNASeq data, identifying the putative ancestral state at half of BOPA SNPs. The balance of SNPs will be compared to Brachypodium to infer ancestral state. A manuscript reporting the SNP annotation tool is in preparation.

C.1.7.5. Preparation of barley samples for genotyping with 9000 SNP chip: A total of 960 barley lines are being genotyped using the improved barley custom iSelect 9,000 SNP chip. The barley lines to be genotyped include the 384 low-temperature-tolerance AM panel (LTT-AM) and 576 TCAP spring and winter lines from various barley breeding programs. The leaf tissues for the rest of 576 lines were collected at the University of Minnesota and were sent to Fargo. The seeds for the LTT panel became available in July and were sent to Fargo.

Output: improved wheat SNP genotyping platform and maps

C.1.7.6. 7,500 mapped wheat SNPs: SNPs were mapped in multiple U.S. and Australian segregating populations and a consensus map including 7,517 SNPs has been developed and has been distributed among TCAP participants. A publication including this map is in preparation and the data will be publicly released as soon as the paper is accepted.

C.1.7.7. 90,000 iSelect wheat chip: We have updated all the genotyping of the wheat association mapping panels previously planned for the 3072-SNP platform to the new 90,000 SNP iSelect wheat chip. A total of 2,500 lines from the spring and winter wheat association mapping panels are being genotyped with the custom iSelect 90,000 SNP wheat chip. Through a coordinated international effort with wheat programs in several countries, we were able to increase the initial order of iSelect wheat chips to 46,000 assays, with a dramatic reduction in costs for wheat genotyping. This reduction in cost allowed us to deliver 30-fold more markers than planned in the initial proposal. The Fargo lab is responsible for the genotyping with the iSelect 90,000 SNP wheat chip, which will be completed within 2012. Seeds or leaf tissues for these populations have been sent to the various genotyping labs for DNA extractions.

C.2. OUTPUTS OBJECTIVE 2

Accelerate breeding through marker-assisted selection and genomic selection.

Output: accelerated breeding through Marker assisted selection (MAS)

C.2.1. Barley GS, 4,032 samples (384 SNP chip): Barley Genomic Selection is scheduled for fall due to unusually warm spring weather and high greenhouse temperatures in MN.

C.2.2. Barley mapping populations, 4032 samples (384 SNP chip): Reagents from Illumina for a 384 SNP barley mapping OPA were received in April 2012. DNA was isolated from 803 wild barley introgression lines and 192 RILs from the Madre Selva/Butta-12 mapping population for CYDV and stem rust resistance. Genotyping and map construction has been completed. Four QTL for CYDV resistance were identified.

C.2.3. Barley and wheat MAS, 9,546 samples (48 SNP – Sequenom): Analysis of the 9,000 SNP results on multiple wheat mapping populations and association mapping panels is providing the information required for the genotyping labs to incorporate SNP assays into the marker-assisted selection programs. Considerable progress has been made developing SNP marker assays for the Sequenom MassArray for low to mid-level SNP genotyping of both wheat and barley samples. The Sequenom platform is cost-effective and provides greater flexibility than the Illumina BeadXpress since labs can vary the content and numbers of markers assayed on each sample. The list of the lines genotyped by the smaller SNP chips and by individual STS and SSR markers is included below.

Barley – 192 samples completed

OR, Pat Hayes. = 96 samples, 35 SNP
MN, Kevin Smith = 96 samples, 48 SNP

Wheat – 6,126 samples completed or in progress with varying numbers of SNP.

Louise stripe rust HTAP AM validation = 384 samples, 16 SNP
Spring wheat quality QTL’s validation = 384 samples, 15 SNP
Winter wheat MAS = 192 samples, 56 SNP
Yr48 high resolution MAS = 3840 samples, 4 SNP
Yellowstone X Choteau mapping population = 182 samples, 248 SNP
1,728 eastern and central winter wheat samples genotyped with 72 SNP
Seven sets of 200 SNP from known FHB resistance QTL regions were assembled to increase our ability to determine haplotypes in the elite breeding lines. 5 mapping populations segregating for FHB resistance were analyzed.
Low cadmium allele durum lines from CA= 1000 samples

Output: first cycles of crosses for genomic selection completed

C.2.4. Barley GS: Barley lines from Cycle 1 were generated for seed increase and future evaluation and crossing parents for Cycle 2. The six-row winter barley genomic selection project is based on forty-seven facultative parents tracing to Oregon, Nebraska, Idaho and Minnesota breeding programs. In the fall of 2011, 768 F₃ plants tracing to 48 crosses were genotyped by the NC Genotyping Lab with a custom 384 SNP VeraCode assay optimized for polymorphism among the parents and genome distribution. All of this cycle 1 genotyping data has been uploaded to T3.

A training population was assembled using phenotype and genotype data from the Barley CAP. Jean Luc Jannink trained a prediction model using the RKHS method with a Gaussian kernel for the traits: yield, malt extract, low temperature tolerance (LTT), height, heading date, Fusarium head blight, and stripe rust. Little to no negative correlation among the traits was observed and a selection index primarily weighting yield, LTT and malt extract was used to select the best 100 lines to advance to the next generation and to be used as parents in the next cycle of crossing. A random set of 100 lines was also selected. The remnant seed from all 768 F₃ plants was planted in single row plots in St. Paul in the fall of 2011 to assess LTT. The correlation between the genomic estimated breeding value (GEBV) for LTT and observed winter survival was 0.6. In the winter greenhouse, crosses among the selected F₄ parents were made to generate over 900 F₁’s for the next round of selection. A slightly delayed planting and a very unseasonably warm spring created a situation where we determined that it would be too risky to make crosses for cycle 2 in the greenhouse. Therefore, we planted the F₁ generation in the field in May and genotype 768 F₂’s in the fall for cycle 2 selections. We have planted the 100 selected and 100 random F_4:5 lines from cycle 1 as two row plots in Crookston to generate seed for preliminary yield trials that will be conducted in MN and OR in the fall of 2012.

C.2.5. Wheat GS: For wheat, two GS programs were initiated using the hard (HRWW) and soft (SRWW) winter panels. The HRWW panel has 300 entries and was evaluated for yield under high N and water in four environments, low N in two environments, and low water in two environments. The SRWW panel has 280 entries and was evaluated for yield in five high N environments and two low N environments. In addition to yield, lines were evaluated for agronomic traits, CSR, grain protein, and mineral content. From that data, we will calculate NUE, WUE, and trait stability. Each panel has been submitted for genotyping with 90K SNP.

To compare GS to phenotypic selection, the NE`s wheat breeding program used two F_3:6 nurseries (276 lines, 1900 DArT markers) in two successive seasons. Phenotypic selection and GS prediction accuracy were compared for five traits. A cross-validation approach that trained and validated prediction accuracy across years was used to evaluate effects of model selection and training population size. The comparison of the prediction accuracy for phenotypic selection with that from GS indicated that GS was 94, 64, 84, 85 and 79% as accurate as phenotypic selection for grain yield, grain volume weight, plant height, anthesis date and leaf rust resistance, respectively.

The group at Ohio State University has genotyped 470 SRWW lines with ~1900 DArT markers and will soon add GBS markers to increase genome coverage. The lines have been phenotyped for yield (6 environments), resistance to Fusarium Head Blight (2 environments), and several quality traits (4 environments). The relative efficiency of GS versus phenotypic selection was assessed by cross-validation. To date, the relative efficiency of GS on a per cycle basis was 0.50 for yield, 0.65 for FHB, and ~0.75 for quality traits.

The winter wheat breeders are also assessing GS and association analyses in the regional uniform yield trials. About 2/3 of the entries in the SRWW elite panel have been evaluated for yield in various uniform trials. We will compile the data from those trials and use it in conjunction with the direct elite panel data in the analyses. Twenty entries of the 2013 Southern Regional Performance Nursery will be included in the 2013 elite panel grown in Nebraska, and these entries will be genotyped. The association analyses and GS performed on the elite panel will be used to identify QTL and build prediction models. The results will be validated and/or extended using the data from the uniform trials. The results will validate outputs, assess the frame of inference of the elite panel results, and develop approaches to use the vast amount of data collected annually in uniform trials.

C.3. OUTPUTS OBJECTIVE 3

Implement sequence-based genotyping methods to discover new allelic diversity.

Output: gene-capture technology evaluated in barley and wheat.

C.3.1. Gene Capture: An international collaboration was formed to develop gene capture technologies in barley and wheat. The Nimblegen whole exome capture assay targeting 110 Mb of sequence in the wheat genome and 90 Mb of sequence in the barley genome have been designed and tested by resequencing the coding regions of 32 accessions of hexaploid wheat and 12 accessions of barley. Paired-end sequencing was performed using the Illumina HiSeq2000 and MiSeq instruments to generate an average of 40x coverage of the targeted exonic regions. The latter platform was mostly used for quick testing and optimizing the conditions of the capture protocol. The capture reactions were performed either with genomic libraries prepared from a single sample or by pooling four to eight barcoded samples in equimolar proportions. All levels of multiplexing produced similar results. From 22% to 26% of reads in a pool of four genomic libraries could be assigned to individual accessions suggesting the similar levels of enrichment achieved for each accession.

Up to 77% of sequence reads could be mapped to a reference using the program bowtie and bwa. More than 90% of targeted exonic regions were represented in enriched genomic libraries. The average depth of target coverage after removal of duplicated reads was 40x. The distribution of the depth of read coverage at variable sites differentiating wheat genomes from each other suggested that duplicated genes in a polyploid genome can be captured with similar efficiency using the Nimblegen capture assay. The results obtained were used to design a rebalanced beta version of the capture assays that is currently being evaluated. The capture experiment will be scaled up to perform targeted exome resequencing of diverse panels of wheat and barley landraces and cultivars.

Output: first GBS maps generated for barley and wheat

C.3.2. GBS: GBS was used to generate sequence data for one segregating population for barley and two double haploid populations for wheat. Two of these populations have been already published in Poland et al. (2012).

Barley: GBS was used to genotype the Steptoe x Morex double haploid population consisting of 129 DH lines and the two parents. A 136-plex library was constructed and sequenced at 2x coverage on the Illumina HiSeq. We identified 19,700 SNPs segregating in this population. In collaboration with the IBSC, the SxM mapping data is being combined with other reference populations to develop a barley consensus map of SNPs and GBS markers.

Wheat: The first double haploid population includes 268 individuals from the cross between common wheat varieties Duster and Billings (DxB); the second one 192 individuals from the cross of Synthetic wheat with Opata (SynOp), and the third one a slow rusting population derived from CI13227. GBS libraries were constructed using PstI / MspI, PstI / MluI and PstI / MseI restriction enzyme combinations. Ninety-two barcoded libraries were pooled to sequence in a single lane of HiSeq2000 instrument. A total of 440 million 100 bp-long reads were obtained for the DxB population with an average of 1.6 million reads per individual and 408 million reads were obtained for SynOp mapping population with an average of 2.1 million reads per individual. The data was processed to generate genotype calls using a custom pipeline. The Illumina read clustering performed with CD-HIT program was used to obtain unique reference tags. A total of 1.1 million unique tags were obtained for DxB population. Similar results were obtained for SynOp mapping population. These clusters have been used as a reference sequence for mapping Illumina reads using the bowtie program. SNP genotype calling in the Illumina alignments was performed using the SAMtools program. The presence/absence and SNP variations identified between the parents of mapping populations were scored in the mapping populations to call individual genotypes. Both types of variation were tested for 1:1 allele ratio using the binomial distribution.

By allowing up to 80% of missing data, 59,907 potential SNP sites have been identified in the DxB population. Among these variable sites, 1,690 SNPs that showed high quality and low proportion of missing data were selected for constructing the genetic map. The GBS tags generated for SynOp mapping population were mapped to recombination intervals of the SynOp genetic map constructed using DArT, SSR and SNP markers. Mapping to recombination intervals was based on testing of two-marker configurations for independence using binomial distribution with the p-value < 0.001. A total of ~60,000 SNP and 390,000 PAV GBS-tags were integrated with the SynOp genetic map.

C.4. OUTPUTS OBJECTIVE 4

Implement web-based tools to integrate marker-assisted selection and genomic selection strategies into breeding programs.

Output: improved T3 database

C.4.1. New data released: New datasets uploaded to T3 since the beginning of 2012 have been primarily new barley allele calls on the University of Minnesota breeding program, and agronomic data spanning three years on a series of height allele NILs in wheat. Wheat disease data on the NSGC core collection and barley elite association mapping panel data are expected in the coming quarter. A schedule for phenotypic data delivery has been assembled to provide milestones for each expected dataset from TCAP participants (http://bit.ly/I9plRt). This schedule will be regularly updated to help ensure timely data submission to T3 and therefore delivery of TCAP data to participants and stakeholders.

C. 4.2. Improved user interface: Several improvements in the user interface have been made to enable more intuitive searching of the data in T3 and the integration of multiple datasets. Users can now identify data of interest starting from a focus on the breeding program generating the data; from locations from where the data were collected; from traits measured; or from the identities of the lines themselves. Each initial focus leads in an intuitive way to search restrictions based on other criteria until the user has narrowed the search to a precise combination or union of criteria. A connection to the analysis software TASSEL has been added, which allow users to jump directly into TASSEL with the selected data. Users may define panels of lines that they expect to work with on a regular basis. Upon login, data for user-defined panels can be queried directly. A BLAST search feature has been implemented allowing users to identify barley or wheat markers with sequence similarity to arbitrary input sequence.

C. 4.3. T3 training: Three online tutorials explaining data submission to T3 have been developed for submitting line names and properties; experiment annotations; and genotype data. In conjunction with the tutorials, we created a YouTube channel to show tutorial videos. The line submission video has had 13 views.

A poster and a computer demonstration were presented at the 2012 Plant and Animal Genome Conference. A seminar on uploading data to T3 was presented to the Plant Breeders Training Network on April 12^th, 2012. The “sandbox” versions of T3, developed during the fourth quarter of 2011 have been successful in enabling users to test-run data submission prior to transmitting the data to the curator. Seven TCAP participants from five programs have submitted data to T3 via the sandboxes.

C. 4.4. Coordination and hyperlinks with other databases: Hyperlinks to other databases can facilitate users tracking down information about lines or markers of interest. The following hyperlinks to other databases now exist in T3: Marker name query on GrainGenes; Rice homologous gene on Gramene; Affymetrix probeset query on PLEXdb; UnigeneID query on HarvEST; Line query to PI number in GRIN

T3’s trait descriptions have links to the corresponding Trait Ontology records at www.gramene.org/db/ontology, to allow users to access data about those traits from other sources. We are working with Laurel Cooper of the Plant Ontology Consortium to create links from the Trait Ontology back to T3’s data about each trait. For example, the link for “beta glucan” would jump to T3’s page with all the trials in which that trait has been evaluated. We are organizing a workshop entitled “Managing crop phenotype data” targeted at other database developers for PAG in 2013.

C. 4.5. Solutions to the “Big Data” problem: T3 now uses two-dimensional “materialized view” tables to access genotype data. This approach provides quicker access to large blocks of data as well as more compact storage. These tables have dramatically decreased query times for retrieval of genotype data used both for internal analyses (e.g., clustering lines by genotype) and for download to external analyses.

T3 developers are maintaining contact with other databases confronted by the “Big Data” problem, in particular with Panzea and MaizeGDB.

A new server dedicated to T3 is online. This server was designed with TCAP datasets in mind, in particular aiming to be able to maintain the complete table of allele calls in random-access memory to increase the speed of genotype queries.

C. 4.6. Expanded use of T3 beyond TCAP: The T3 database schema and web interface software are potentially useable by any project that generates genotype and/or phenotype data for wheat or barley. With funding from the US Wheat and Barley Scab Initiative, we have created a T3 instance called The Breeders Database, http://malt.pw.usda.gov/t3/bd/, to hold the results of current and historical Uniform Regional Scab Nurseries. USWBSI participants Dave Van Sanford and Paul Murphy are taking the lead on populating this database, and Dave’s student Sandy Swanson has begun adding data.

Efforts have begun in individual breeding programs to use T3 itself for their own data management. The University of Minnesota breeding program has been particularly active, submitting line names and properties for over 5,000 lines to T3 Barley. Wheat programs at the University of Nebraska, Lincoln and at Cornell University are also making steps in this direction.

We have packaged T3 and added installation instructions to make it “portable” for installation on any Unix computer, including Mac OS X. It is available for downloading from GitHub (a service similar to Source Forge). A student of Hermann Buerstmayr found it there and has successfully installed it at University of Natural Resources and Life Sciences, Vienna, Austria, for a database of Fusarium Head Blight disease reactions. The modifications necessary to make T3 easily customized for any crop are relatively small, and we are planning to make them.

C.5. OUTPUTS OBJECTIVE 5

Output: Integrated Education and Research programs

C.5.1. Annual meeting at PAG: The TCAP held its annual meeting in San Diego, CA on January 15, 2012. TCAP co-PIs, students, stakeholders, the scientific advisory board and USDA administrators attended the meeting (~100 participants). This meeting provided students the opportunity to interact with all project participants and to gain an integrated view of the project. The morning was devoted to reporting progress and the afternoon was devoted to planning future activities. Input was received from SAB and a response indicating implementation of these suggestions was prepared and submitted to USDA.

C.5.2. PAG Graduate Student meeting: To help build a graduate student community, 19 graduate students, six faculty (including a MSI representative) and an industry representative met at the PAG meeting. A brainstorming session was implemented to discuss the skills needed by breeding professionals. Next, the group broke into small groups and the students discussed their specific research topics. Graduate students expressed an interest in organizing the meeting next year.

C.5.3. Newsletters: The winter and spring 2012 Newsletter were produced and distributed among TCAP participants, stakeholders and members of the scientific advisory board. Stakeholder comments were integrated into a more stakeholder friendly format.

C.5.4. TCAP seminar series: To encourage communication about the TCAP project a seminar series was held online. Six seminars were presented by TCAP faculty, students and collaborating faculty from minority serving institutions (see below) and have been archived at http://passel.unl.edu/communities/pbtn.

Table 16. Seminar series

Presenter	Title	Date	Part.
Stephen Baenziger	Understanding Grain Yield: It’s a journey, not a destination	2/23/12	47
Deana Namuth-Covert	Cyberspace: New Frontiers in Learning and Networking	3/15/12	15
Eduard Akhunov	Usage of genome wide genotyping approaches to understand the genetics of agronomically important traits in wheat.	3/29/12	41
JeanLuc Jannink, Vic Blake, Clay Birkett & Dave Matthews	Introduction to T3	4/12/12	31
Tyson Howell and Jorge Dubcovsky	TCAP Canopy Spectral Reflectance updated methods for 2012	4/26/12	30
Martin Matute	Plant Parasitic Nematodes- The Farmer’s Hidden Enemy	5/3/12	16

C.5.5. Use of online environment: A total of 86 people are now members of the Plant Breeding Training Network (http://passel.unl.edu/communities/pbtn), including some members outside of the TCAP group. The online environment is being used as a communication tool for project management as well as to provide educational opportunities through classes and seminars (see Table below). Other groups are using the site for communication e.g. Ag*Idea Plant Breeding Program design committee (meets monthly), UNL Graduate Student Plant Breeding Symposium (80+ attendees) and NAPB Student committee (met monthly to plan student activities at 2012 NAPB).

Table 17. Use of the online environment.

	Dates	Total Visits	Aver. Time on site	Pages/visit
Entering mentoring (Spring class)	2/1/12-4/30/12	35	19 m 10 s	4
PBTN (entry into all offerings)	2/1/12-4/30/12	527	5 m 9 s	3
PBTN (entry into all offerings)	9/1/11-11/30/11	758	5 m 37 s	4
PB Grad Student community (available for use fall & spring)	2/1/12-4/30/12	35	19 m 10 s	4
PB Grad Student community (available for use fall & spring)	9/1/11-11/30/11	3	3 m 43 s	16
Plant Breeding Strategies(Fall class)	9/1/11-11/30/11	124	10 m 6 s	6
Quantitative genetics (Spring class)	2/1/12-4/30/12	95	9 m 36 s	37
TCAP Graduate courses (offerings)	2/1/12-4/30/12	24	8 m 43 s	11
TCAP MSI Faculty	1/1/11–12/31/111/1/12–4/30/12	64 3	13 m 51 s 3 m 43 s	4 15
TCAP Undergrad Community	1/1/11–12/31/111/1/12 – 4/30/12	66 5	14 m 2 m 41 s	6 18

Output: Recruit a diverse group of undergraduates to plant breeding

C.5.6. Education/recruitment films: The TCAP film, “Holding the future in the palm on your hand”, was finished and posted at http://passel.unl.edu/communities/pbtn. A film on Plant breeding for disease and pest resistance and a short film about the wheat stem sawfly were completed over the summer, posted online and will be used this fall.

The film, “Holding the future in the palm on your hand”, was used successfully in recruitment by Jamie Sherman at University of Arkansas Pine Bluff, Rust College and Chicago State University to about 200 students.

C.5.7. Brochure: A recruitment brochure was created as a companion to the film and 200 copies were distributed in spring 2012 during recruitment trips. It has also been posted at http://passel.unl.edu/communities/pbtn. Participants are encouraged to print and use in recruitment efforts.

C.5.8. MSI / TCAP bridge: Eight MSI faculty/TCAP faculty collaborations were established in fall of 2011. Sixteen undergraduates and one graduate student have been engaged in research with these eight faculty. Each MSI faculty reported on first year progress by the end of May. Seven of the relationships were renewed with additional funds given to two particularly successful programs.

C.5.9. MSI student visits to TCAP facilities: Four minority students from UAPB traveled to Washington State University for a six week research experience in Arron Carter’s lab. Students conducted research related to disease and drought tolerance in wheat, participated in field days and visited additional labs. The TCAP contributed to travel and housing costs. Rust College student Lolley Ceesay interned at CSU. She and her MSI mentor Dr. Zhu attended the CSU Drought tolerance symposium. Yaleaka Currie interned at KSU with Dr Bai and Michael Tavarez from Lehman College interned with Dr Brian Waters at UNL. Jorge Dubcovsky visited Woodland Community College and gave a class on modern plant breeding. One of the students from this class Wes Nelms, initiated an internship at the UC Davis program and decided to transfer to UC Davis to continue work in the TCAP project.

In addition to providing research experience in plant improvement for undergraduate students, these opportunities serve as pilots for collaborative research/training activities between TCAP and minority serving institutions.

Output: trained students in plant breeding

C.5.10. Graduate student training: A total of 69 graduate students have participated in the plant breeding training network. 62 of these are directly mentored by a TCAP PI with 38 students being fully or partially funded by TCAP. Several students have participated in TCAP classes and have no affiliation with TCAP. A complete list of graduate students is provided in Appendix H3.

C.5.11. Graduate courses: Three courses that have been offered through the TCAP are listed below. Participants were surveyed to determine needed improvements. Theory and Application of Association Analysis taught by Jeff Endelman, Jean-Luc Jannink, Clay Sneller, and Mark Sorrells will be offered this fall.

Table 18. Graduate courses.

	Semester	Total Registered	Total completed
Plant Breeding Strategies	Fall 2011	26	14
Entering Mentoring	Winter 2012	10	5
Quantitative Genetics	Spring 2012	33	9

C.5.12. Undergraduate students: A total of 55 undergraduates have participated in the TCAP with 37 being mentored by TCAP faculty and graduate students, 17 by MSI PIs. Five graduate students completed Entering Mentoring to support their undergraduate mentoring efforts. A complete list of undergraduate students is provided in Appendix H4.

C.5.13. Undergraduate online meeting: An online community was established to support undergraduate students through meetings in which students interact with plant breeding scientists in academia and industry and discuss their own research experiences with other undergraduate students. Jamie Sherman met with students in January and provided background on the TCAP. Donn Cummings (Monsanto) discussed the future of biotechnology in plant improvement and careers in that field in March. Kevin Smith discussed preparation for, and application to, graduate school in the area of plant sciences on May 9.

C.5.14. Workshops and symposium: TCAP supported student attendance this summer at two workshops and the National Association of Plant Breeders meeting. The first Plant Breeding for Drought Tolerance from June 11^th through 22^nd was led by Pat Byrne at Colorado State University with 15 participants. Sixty-five participants attended the Drought tolerance symposium that was held in conjunction with the short course at CSU. The second, Rust Research Methodology, July 8‐July 10, 2012 at University of Minnesota, was led by Brian Steffenson and Pablo D. Olivera with 8 participants. The 2012 NAPB annual meeting was held August 6-8^th in Indianapolis, IN and was hosted by Dow AgroSciences. This year’s meeting theme was “Sustaining Life through Plant Improvement” with over 200 in attendance and TCAP supporting attendance of 69 graduate students.

C.5.15. Publications by the education team: One peer reviewed article and five presentations in the area of education were presented by TCAP participants

Publications:

Kohmetscher, A., Lee, D. and D. Namuth-Covert. (2012) Introduction to Plant Breeding Learning Activity: Wheat . Journal of Natural Resources and Life Sciences Education (in press). http://passel.unl.edu/animation/JNRLSEWheatBreedingActivityWithNotebook/WheatBreedingActivity2.swf

Presentations

Sherman, J. 2012. Plant Breeding the Future is in your Hands to 200 students at University of Chicago Pine Bluff, Rust College and Chicago State University.

Sherman, J. Mary Brakke, Don Lee and Deana Namuth-Covert. 2012. Visioning online plant breeder education. National Association of Plant Breeders, Indianapolis IN.

Kohmetscher, A., Leingang, D., Speth, C., Namuth-Covert, D., and Sherman, J., 2012. What Does It Take to Get From Technology to Community? 18^th Annual Sloan Consortium International Conference on Online Learning, Orlando, FL, Oct 10- 12, 2012.

Don Lee and Amy Kohmetscher . 2012. A presentation about plant breeding was given to about 45 FFA students March 30^th at the University of Nebraska Lincoln East Campus.

Namuth-Covert, D., Guru, A., and M. Fairchild. 2012. Learning Object Repository Becomes of Age – Reflecting on 13 Years of Faculty Development & Technology Applications. 18^th Annual Sloan Consortium International Conference on Online Learning, Orlando, FL, Oct 10- 12, 2012.

C.5.16. Publications and presentations of TCAP students: Five peer reviewed papers were published by TCAP graduate students and are listed in Appendix H3 under general publications. In addition TCAP students made 18 presentations in scientific meetings (14 from graduate students and 4 from undergraduate students, Appendix H5).

Output: open source online education resources

C.5.17. Educational materials: The Wheat Breeding Activity was accepted to the Journal of Natural Resource and Life Science Education. Introduction to Plant Breeding Learning Activity: Wheat By Amy Kohmetscher, Don Lee, and Deana Namuth-Covert* Available at: http://passel.unl.edu/animation/JNRLSEWheatBreedingActivityWithNotebook/WheatBreedingActivity2.swf

The lesson on Nitrogen Use Efficiency is in a third draft stage and under peer review. Discussion of additional inquiry-based activities connected to nitrogen use and nitrogen use efficiency in crop plants are in progress. An interactive quantitative traits lesson has been initiated that will utilize data from the Oregon Wolfe Barley population.

A video on wheat resistance to sawfly was completed and uploaded in Vimeo.

C.5.18. Improvements to online environment: Several improvements have been implemented. Auto-generated members list was created so each community now has a tab, with lists of members who wish their profiles to be public. The objective of these lists is to help people in contacting each other for collaborations.

In collaboration with NSF project (Namuth-Covert), computer programming was added to generate reports of how often materials, communities, etc. are being accessed. Summaries generated by these tools are presented in this document.

A major overhaul of the quizzing system has been initiated using code from Moodle. We will also switch to Moodle’s discussion forum platform, which appears to be more user friendly than the one we have in place. Quizzing using this platform will allow for more types of questions than the current multiple-choice format.

We have researched the best option for long-term storage of large video files, such as narrated power points and archived webinars. Vimeo is our best option, providing cost efficient storage of videos, plus good accessibility for clientele with tighter firewalls.

Output: an independent evaluation of the education activities

C.5.19. Evaluation of educational tools: Evaluation approaches include annual surveys and interviews of TCAP PIs, graduate students and collaborating faculty at minority serving institutions (MSI), and participant observation of online courses and webinars. Additional evaluation of the impact of TCAP educational materials (online learning objects and videos) on undergraduate student understanding and perceptions of plant breeding is currently being conducted by individuals who created materials, including Don Lee, Carol Speth and Jamie Sherman.

Results of evaluation work to date are being used to 1) identify and address factors that affect realization of TCAP education goals, 2) characterize baseline perceptions, confidence levels and professional networks and 3) measure changes in perceptions, confidence levels and professional networks.

Matched analyses of 2011 and 2012 TCAP PI and graduate survey responses were performed and are reported. Matched analyses of MSI collaborating faculty responses were not possible due to small sample sizes. Responses in key areas of TCAP programming and graduate education, collaborative research, and networking are described below. In each area, the significance of responses is discussed.

C.5.19.1. Evaluation of TCAP Graduate Education – PI responses

In 2012, “Faculty mentoring” and “Research” were rated as “Extremely important” by 82% and 75% of respondents, respectively. In matched analysis of 2011 and 2012 responses, ratings of “Extremely important” for faculty mentoring of graduate students increased by 20% and remained unchanged for the research component.

In 2012, one-on-one mentoring, experience presenting results, and field experiences were rated as “Extremely important” by 93%, 75% and 71% of respondents, respectively. In matched analyses of 2011 and 2012 responses, there was an increase of 16% of respondents who viewed one-on-one mentoring as “Extremely important” and an increase of 8% who viewed field experience as “Extremely important.”

In 2012, TCAP education components of recruiting underrepresented groups to plant breeding, understanding challenges to recruiting underrepresented groups and relationship development with faculty from MSIs were rated as “Extremely important” by only 22%, 4%, and 4% of respondents, respectively. Matched analysis suggests that the importance of these components remained unchanged from 2011 to 2012.

In other matched analysis of the importance of TCAP education components, there was an increase of 12% in the number of PIs who regarded inquiry-based learning approaches to be “Extremely important” in 2012 compared to 2011 and 8% more PIs who viewed group interactions at the Plant and Animal Genome meeting to be “Extremely important” in 2012 compared to 2011 (32% vs 24%, respectively). Four items showed a decrease in the percentage of TCAP PIs who viewed them to be “Extremely important”: graduate student mentoring of undergraduates (16% vs. 28%), developing relationships with MSI faculty (4% vs. 16%), skill workshops (45% vs. 25%), and recruiting more American-born underrepresented minorities to plant breeding programs (32% vs. 16%).

C.5.19.2. Evaluation of TCAP Graduate Education – Graduate Student Responses

In 2012, 76% of respondents rated ‘field experience” as “Extremely important” (similar to 2011) followed by “laboratory experience” (72%), “exposure to diverse research methods” (68%), and “one-on-one mentoring” (65%). %). “Exposure to plant breeding students from different ethnic backgrounds” was rated as “Extremely important” by 32% of respondents, representing a large increase from 2011.

In the 2012 survey, conducting research, problem solving, planning research, conducting research and gathering, analyzing and managing data were rated as “very valuable” important by more 90% of respondents (similar high percentages as 2011).

In 2012 the online community was the activity in which the fewest students participated (29% did not participate at all) and was the least valued (13% rated it as “very” valuable), similar values as those reported in 2011.

In 2012, the top knowledge areas in which students felt confident were experimental design (28%), genetics (24%) and factors in crop plants that impact productivity (16%). In both 2011 and 2012, methods of breeding in self- and cross-pollinated species and selection theory and techniques were not listed as top knowledge area in which students felt confident.

In 2012, the top skill areas in which students felt confident were work cooperatively (28%), design experiments (16%), and molecular techniques (12%).

In 2012, 83% of respondents indicated they were highly interested in the plant breeding field (4 or 5 on a scale of 1 to 5), and increase of 10% from 2011.

C.5.19.3. Evaluation of Minority Serving Institutions (MSI). TCAP PI responses

In matched analysis between 2012 and 2011, there was a decrease of 12% in number of PIs who rated “developing relationships with faculty from MSIs” as “Extremely important” (17% to 5%) and a decrease of 16% in PIs who rated “recruiting more American-born underrepresented minorities to plant breeding programs” as “Extremely important”.

In matched analysis between 2012 and 2011, there was a 12% decrease in the PIs who responded reported having “no strong relationship at all” with minority serving institutions (MSIs) (58% to 46%). There was also a 6% decrease in 2012 in the percent of PIs who reported having “no strong relationship” with MSI institutions.

In 2012, the highest number of PIs also indicated that the lack of mutual goals and fit was the top barrier to collaborating with MSI faculty (similar to 2011). Lack of funding was the second top barrier.

In 2012, lack of interest in, or awareness of plant breeding was the most cited top barrier to increasing the number of underrepresented minorities in plant breeding, a similar result to the 20111 survey. Lack of adequate preparation was listed as a top barrier by 5% of PIs in 2011 and by 7% of PIs in 2012.

Interviews with PIs generated a wide range of ideas regarding recruitment of undergraduates to programs in plant breeding although none were described as specific to underrepresented groups.

C.5.19.4. Evaluation of Minority Serving Institutions (MSI). MSI faculty responses

In 2011 and 2012, enhanced interaction of MSI and TCAP faculty was listed in 3/16 responses as among the two most important things the education component of TCAP could accomplish.

In 2011 only one in eight MSI faculty rated their relationship with TCAP institutions as “very strong” while in 2012, all six MSI faculty who completed the survey rated them as “very strong.”

In 2012, funding was cited as the top barrier by four of the six MSI PIs. Other barriers cited include lack of graduate students, communication, common interests and human resources. This response differed from 2011, when teaching load/time for research and distance were each listed as top barriers to collaborating on research with TCAP faculty by two of seven MSI faculty.

In 2012, the top barrier to increasing the number of underrepresented groups in the field of plant breeding with the most responses was funding (2/6). Other responses included lack of awareness, lack of interest, historical issues and lack of plant breeding programs.

Site visits to MSIs resulted in additional information and insights, including

The importance of connecting MSI students with TCAP students and of recruiting sophomore and junior level students to internships to ensure that the experience will be impactful and will provide multiple years of funding to the students.
A lack of awareness and understanding among minority students in areas of plant breeding and agriculture
The importance of personal relationships to recruitment and the effectiveness of peer recruiting.
The importance of authentic relationships built on understanding one another in which research interests and goals are mutually shared
The importance of TCAP faculty visits to MSIs to enhance communication.

C.5.19.5. Evaluation of TCAP networking activities.

The percentage of PIs who reported interacting with advisees more than once a week in 2012 was 79% (similar to 75% in 2011). Interactions were focused on trouble shooting research (48%) and collaborating (24%) in 2012.

The percentage of PIs who reported interacting with researchers at their own institutions more than once a week in 2012 was 75%, a sharp increase from the 3% reported in 2011.

The percentage of students who reported interacting with their advisor more than once a week in 2012 was 55%. This is a decrease from 80% in 2011, but the interactions were mostly social in 2011 and about collaborations or being mentored in 2012. Student interactions with researchers from industry and outside the U.S. were limited in 2012.

Student interactions with students at other institutions occurred on average once a month or less in 2012. Students in 2012 reported communicating more frequently with students outside their institution than in 2011. Interactions with students at MSIs were low.

Graduate students indicated the most important aspect of TCAP was the opportunity to network with faculty and students from across the nation.

MSI PIs interacted most frequently with their advisees. Other interactions were with other students and other researchers at their own institutions. Interactions revolved around trouble-shooting research and collaborations.

C.5.19.6. Evaluation of undergraduate research in laboratory settings

Research in a laboratory setting was the activity in which most (9/13) students in research internships participated while research at another institution and the online research community were the activities in which the fewest students participated. When asked what they liked about their research experience students referred to learning new techniques, how to interpret data, and what it’s like to be a scientist. When asked what could be done to improve their research experiences two MSI students referred to collaborating with other labs or universities. TCAP students referred to interacting with a professor, learning more lab techniques or doing more data analysis.

Nearly all (10/12) students reported that there is someone involved in their research experience that they consider a mentor. Most (10/13) students reported being mentored “moderately often” or “very often.” Being mentored was the activity that the most (9/12) students reported as “very valuable.” For all MSI students, their mentor is a faculty member. For most TCAP students (4/6), their mentor is a graduate student.

All 13 students reported being at least “somewhat” interested in graduate school and six of those indicated being “extremely” interested in graduate school. Nearly half (5/11) of all students felt their research experience had influenced their interest in graduate school. Seven of ten students indicated they felt their research experience had contributed to some extent to their ability to succeed in graduate school.

Before participating in their research experience, most students knew very little about plant breeding as a career and only a couple students reported being very interested in plant breeding. Ten of thirteen students indicated their perception of plant breeding had changed since beginning their research experience. Ways in which perceptions had changed included better understanding of what is involved in conducting plant breeding research and positive perceptions of the impacts of plant breeding. Nearly half (6/13) of all students indicated they were either moderately or extremely motivated to pursue a career in plant breeding.

D. Milestones and Deliverables (year 2, 2012)

During 2012 the TCAP participants have completed (and in many cases exceeded) the milestones proposed in the initial project proposal. Below we provide a detailed description of the progress made towards to the milestones proposed to each of the five central objectives of the TCAP project. Publications are listed in Appendix H1 and varieties and germplasm releases in Appendix H2.

D.1. MILESTONES & DELIVERABLES OBJECTIVE 1.

Discover and deploy beneficial alleles from diverse wheat and barley germplasm.

D.1.1. Develop field based high-throughput phenotyping technologies: During the first year of the project we had some technical problems with the field operation of the JAZ spectrophotometers selected for the Canopy Spectral Reflectance (CSR) measurements. During the second year these problem were solved by changing the grating and the mirrors of the equipment (for those working on WUE), developing a new strategy that integrates hundreds of measurements in a continuous scan of the plots, and developing Perl scripts to facilitate data analysis. Solutions were shared with the whole TCAP group through a web seminar. Analysis of the 2012 data with the modified JAZ equipment confirmed the utility of CSR measurements to determine plants’ water status. The technology is now in place for the evaluation of the AM panels in 2013.

D.1.2. Water use efficiency: The second year milestones in this objective for barley included the evaluation of the spring two- and six-row, and the winter six-row AM panels for WUE. These milestones were completed and exceeded by including a fourth location for the spring two-row barley (see output sections C.1.2.1 and C.1.2.2). This objective also included the development of low temperature tolerant (LTT) barley varieties for fall plantings to increase WUE. The proposed evaluation of the Barley Word Core for LTT (2 locations, 400 accessions) was completed (see output sections C.1.2.3). The six-row winter AM panel for LTT was expanded from 256 to 1000 lines and the evaluation was postponed for 2013 to allow for seed increases of the added lines, which are part now of an international consortium (see output sections C.1.2.4).

The proposed milestones for wheat for 2012 included the evaluation of the AM spring and winter panels for WUE. These milestones were completed and exceeded (see output sections C.1.2.5 and C.1.2.6). An additional location was added for the winter panel (TX) and the spring panel was planted in eight locations instead of the three proposed in the initial proposal. The evaluation of all the proposed special mapping populations for WUE was completed as described in the output sections C.1.2.7 to C.1.2.13.

The evaluation of the spring panel in CA showed that 144 photoperiod sensitive lines were too late in this environment. Although measurements were taken for all lines in 2012, the decision was made to replace the photoperiod sensitive lines for 144 photoperiod insensitive lines. New lines were requested from the NSGC, CIMMYT and Italy and the seed was increased in Tulelake and is ready for planting in November 2013 in two locations. The lines will be evaluated also in 2014 to have 2 years of data for all lines.

D.1.3. Nitrogen use efficiency: The second year milestones in this objective for barley included the evaluation of the spring two- and six-row and winter six-row AM panels for NUE. All locations were planted and evaluated as planned with the exception of the MN location that was lost to complete winterkill of the plots (see outputs section C.1.3.1.). The proposed milestones for wheat for 2012 included the evaluation of the AM winter panels for NUE. This milestone was completed as described in output sections C.1.3.2 and C.1.3.3.

D.1.4. Diseases resistance: The 2012 disease resistance milestones for barley included the screening of the NSGC core collection for stem rust, stripe rust, spot botch, spot form net blotch. These milestones were completed for stripe rust, spot botch, spot form net blotch (outputs sections C1.5.1, C1.5.3 and C.1.5.4). However, completion of the stem rust evaluations has been delayed by low rust infection levels in the South African nursery. The first half of the barley core collection has now been shipped to Njoro, Kenya for disease assessments in mid-October. The rest of the collection will be evaluated for stem rust in 2013.

For wheat, the 2012 milestones included the evaluation of the spring and winter NSGC core collections for leaf rust, stripe rust and stem rust. These milestones were completed as described in the outputs sections C.1.5.6. and C.1.5.7. Data has been analyzed for the stripe rust and stem rust AM panels (C.1.5.5.). Even though the evaluation of the wheat AM panels for the three rust species was initially planned for 2013, studies were started in 2012 ahead of schedule (see output sections C.1.5.8 and C.1.5.11).

The high density mapping populations yielded markers closer to the target genes that will be useful in the MAS programs. One unexpected difficulty was the lack of recombination detected in the Yr48 region in the distal 5 cM of the 5AL arm. New crosses were initiated to bypass this limitation.

D.1.5. Enhanced value of the National Small Grain Collection: The milestone for the second year was to phenotype the NSGC barely spring collection for WUE and NUE in three environments. This milestone was completed. Although it was not part of the original milestones, we considered it valuable to replicate in 2012 the WUE and NUE measurements for the wheat lines evaluated in 2011. Both wheat and barley sets were successfully evaluated for both traits in 2012 exceeding the milestones for this objective.

D.1.6. Population development. The AM panels were established and their seeds increased and the NAM and wild barley introgression populations were advanced as planned (see output sections C.1.6.1 to C.1.6.4). For the wheat NAM, the original number of populations was 25 (Berkut x land-races), but we advanced 38 populations from crosses with land-races and 15 from crosses with adapted spring lines, greatly exceeding the original milestone.

D.1.7. Genotyping. The development of improved SNP technologies allowed us to greatly exceed the original milestones in this objective. All the wheat AM and NAM that were planned originally and were to be genotyped with the 3,072 wheat iSelect SNP platform are now being genotyped with the 90,000 chip, which will result in a 30-fold increase in the number of markers that will be produced for these lines. The integration of a larger number of maps that originally planned in the grant resulted in the mapping of 7,517 SNPs in wheat, greatly exceeding the original milestones of the project. The barley SNP maps are also being improved by the inclusion of additional metadata that was not planned in the original proposal (see outputs sections C.1.7.1 to C.1.7.7.). In summary, the TCAP project has largely exceeded the original milestones proposed for this objective.

D.2. MILESTONES & DELIVERABLES OBJECTIVE 2

Accelerate breeding through marker-assisted selection and genomic selection.

During 2012, marker-assisted selection projects continued as planned in the original project. The USDA-ARS Genotyping laboratories provided valuable marker information to the breeding programs. The development of different SNP platforms, including small SNP chips accelerated the selection for agronomic, disease resistance and quality traits and the genotyping of dedicated mapping populations. The release of new varieties and germplasm developed by marker technologies (See Appendix H2) represent an important milestone for this project and for the previous CAP projects where the initial crosses were initiated.

In the area of genomic selection (GS), the objective described in the original TCAP project was to explore the potential of this technology and test its value in barley and winter wheat. The activities described in output sections C.2.4. and C.2.5. show concrete progress towards this broadly defined long term milestone.

D.3. MILESTONES & DELIVERABLES OBJECTIVE 3

Implement sequence-based genotyping methods to discover new allelic diversity.

D.3.1. Gene capture: The first milestone in this sub-objective for 2012 was the design of the capture assay, which was completed in 2012. The second milestone is the evaluation of this array, which was also completed in 2012. This information was used to design a beta version that is currently being evaluated (see output section C.3.1).

D.3.2. Genotyping by sequencing: The first milestone in this sub-objective was to anchor GBS polymorphisms to bi-parental populations in both wheat and barley, and to apply this technology to the barley and wheat founders of the NAM populations. During 2012, this milestone was completed and GBS was used to generate sequence data for one segregating population for barley and two double haploid populations for wheat. Two of these populations have been already published in Poland et al. (2012) (see output section C.3.2 and Publication Appendix H1).

D.4. MILESTONES & DELIVERABLES OBJECTIVE 4

Implement web-based tools to integrate marker-assisted selection and genomic selection strategies into breeding programs.

An important milestone for 2012 was the completion of the expansion of the original “The Hordeum Toolbox” to wheat. Protocols are now available for depositing and analyzing phenotypic and genotypic data and to download data directly to Tassel. During 2012, phenotypic datasets were curated and uploaded and a schedule for phenotypic data delivery has been established (see output section C.4.1).

Progress in 2012 towards the improvement of the user interface is described in the output section C.4.2., which include more intuitive searching and a BLAST search feature. To facilitate the use of T3, we generated three online tutorials as well as a YouTube video (see output section C.4.3). Several other activities also contributed to the training milestone. Deliverables for the coordination with other databases are detailed in output section 4.4 and include hyperlinks to 5 other databases and links to trait ontology.

Progress on addressing the big data problem is described in output section 4.5. Solutions to managing large datasets will continue to evolve and T3 is communicating with other groups dealing with similar problems. T3 is now being used by other groups as well as individual breeding programs (see output section C.4.6). This activity will likely expand substantially in the coming year.

D.5. MILESTONES & DELIVERABLES OBJECTIVE 5

D.5.1. Ensure project integration and improvement: This milestone has been accomplished through a well-attended annual meeting at PAG, publication of two newsletters, organization of a seminar series, and evaluation reports from advisory panels (see output sections C.5.1. to C.5.5). In fall of 2012, Brakke and Sherman will host a focus group of TCAP coPIs led by education evaluators to obtain advice and further build support and integration of education and research components.

D.5.2. Improved Recruitment: During 2012, we exceeded this milestone by recruiting and supporting more than the expected number of graduate and undergraduate students. The renewal of 7 of the 8 MSI Bridge collaborations with TCAP represented an important milestone for 2012, and resulted in numerous interns and graduate applications in plant breeding. To improve communication and awareness, we will financially support TCAP PIs travel to MSIs. We will identify ways to support MSI student and faculty visits to TCAP institutions. We will ask TCAP PIs to share successful MSI collaborations with their colleagues to increase TCAP PI awareness. To increase impact of the MSI, we are going to shift some funding from the development of materials online to the MSI grants.

The first year of MSI collaborative research projects have provided us a better understanding of the barriers that limit the number of students from underrepresented groups in plant breeding. These barriers include lack of funding and access to programs in plant breeding. Awareness of, and interest in, plant breeding are other top barriers. Three recruitment/educational films have been created and housed online and the first was shown and discussed at 3 MSIs to over 200 students. Student feedback indicates changes in awareness of plant breeding as a career and groups outside TCAP are using the films. Educational materials that use examples of plant breeding to teach principles of genetics are also being created to promote awareness of plant breeding as a career.

D.5.3. Improved Faculty Support: To improve student educational experience, a module involving active learning is planned for the 2012 fall. We postponed the active learning workshop for faculty from 2012 to 2013 until more materials are generated and tested.

D.5.4. Online Environment: The online environment continued to be tested and developed. The online environment was used for project planning within and outside the TCAP. TCAP seminar series was hosted in the online environment with 180 participants. Three graduate level courses have been created, implemented and tested online. Faculty and students indicated an appreciation for the enlarged network for collaboration empowered by the PBTN.

D.5.5. Increased Student Participation: Two TCAP undergraduates and three MSI undergraduates gave research presentations. We will emphasize importance of presenting to mentors so that presentation numbers will increase. Entering Mentoring was offered to all graduate students, but only five were able to complete due to conflicts in schedules. Student perception of Entering Mentoring was positive, but some students felt that waiting a year would have improved their experience. We will continue to offer Entering Mentoring yearly to graduate students to ensure all have an opportunity to improve as mentors. The undergraduate online community will be strengthened through asynchronous discussions and self-guided reflections and evaluation materials. We believe that one reason for low completion rate of graduate courses is that this program is an additional commitment for a graduate student with no additional credit. To mitigate this problem, Namuth-Covert, Baenzinger, Sherman (Co-Chair) and others outside the TCAP project are meeting regularly to design a plant breeding program through Ag*Idea, an online course sharing consortium. Ag*Idea officials have accepted the letter of intent to create a Plant Breeding program and the group is working on a business plan. In the meantime, we ask PIs to enroll students in special problems at home institutions to provide credit incentive. Students getting such credit have proven to have a higher completion rate.

D.5.6. Improved Course Content: This milestone was completed by the development of two courses in 2012 (see output section C.5.11). A third course has been developed for fall 2012- Theory and Application of Association Analysis. Industry representatives on the educational advisory panel are very supportive of these online courses. Student reviews indicated that too much was covered in a short time frame in the Q genetics course so we will revise the approach and determine if a combination of theory and practice works better for the coming fall course.

D.5.7. Organization of Workshops and Symposium: This milestone was addressed by the support of students’ attendance to the National Association of Plant Breeders meeting, the organization of the first Plant Breeding workshop for Drought Tolerance, and the Rust Research Workshop. In addition, conversations with industry were initiated to organize a workshop at PAG for developing communication and leadership skills.

E. Broad Impacts

Research: The TCAP project has enabled integration of modern genotyping capabilities with applied wheat and barley breeding programs, providing a unique opportunity to address climate variability by identification and deployment of favorable alleles for drought tolerance, nitrogen use efficiency, and disease resistance The new iSelect SNP platforms for barley and wheat have greatly accelerated the mapping of important agronomic traits are making possible the implementation of genome wide association studies in wheat. The detailed SNP maps developed this year have enabled breeders to connect information in barley and wheat with the sequenced model grass species, provided a powerful tool for haplotype analyses, and generated a useful scaffold to anchor the incoming wheat sequence from next generation sequencing technologies. The TCAP has also provided the resources to develop and test gene capture and genotyping by sequencing technologies, which are providing a huge number of markers. The increased genotyping capabilities have been complemented with novel high-throughput phenotyping technologies. The implementation of canopy spectral reflectance technologies has provided an expanded vision of the plant status allowing breeders to see the barley and wheat plants in the infrared range and determine both water and nitrogen status of the plants quickly and nondestructively. This has positively impacted breeder’s ability to conduct research on drought tolerance and NUE.

The identification of favorable chromosome segments for WUE and NUE in wild species of wheat and barley has expanded the genetic diversity that breeders can use to improve these traits. Favorable alleles for growth under more limited water availability are being identified helping breeder’s to develop new varieties with increased productivity in hot and dry conditions. The deployment of the high grain protein content allele Gpc-B1 allele in commercial wheat varieties resulted in a 5 to 10% higher grain protein content (GPC) due to a more efficient nutrient remobilization. The development of NUE association mapping panels in barley and wheat has provided breeders a powerful tool to identify additional alleles for NUE in a wide range of germplasm. This information will positively impact the deployment of favorable alleles for NUE and reduce the need for N fertilizers per unit of grain production while maintaining end-use quality, and compensate for the expected reduction of wheat to assimilate nitrates under increasing CO₂ concentrations. The evaluation of the NSGC and dedicated AM panels for resistance to the current races of the major pathogens of barley and wheat has provided breeders with a larger set of resistance genes to deploy in their breeding programs. This information is critical to be prepared for changes in pathogen populations predicted by changes in the environment. In summary, the research generated by the TCAP project will help ameliorate the negative impacts of climate change in cereal production in the US.

The new genotyping capabilities have improved the ability of the USDA Genotyping centers to deliver marker information to the public breeding programs. These marker platforms have also made possible the assessment of the accuracy of genomic selection for multiple traits and open the way for faster and more efficient breeding cycles. All this wealth of genotypic and phenotypic information has been organized in the T3 database that is also providing tools to analyze these complex datasets. The improved T3 database will impact virtually all other analyses by facilitating the dissection and gene discoveries taking place in TCAP.

Education: During the first two years changes in student recruitment and training were implemented creating a more diverse and better trained plant breeding professionals. Approximately 400 people have participated in TCAP workshops and training activities documenting an active participation. The online communication tools have greatly reduced the isolation of breeding students in smaller institutions and formed an integrated cohort of graduate students interested in plant breeding, including students outside the TCAP project. These students have a broader perspective of plant breeding and are trained from the beginning of their careers in the collaborative and modern approaches required for successful breeding projects. The educational activities have accelerated the adoption of modern phenotyping and genotyping technologies in wheat and barley breeding programs nationwide. The education component of the grant has served as an integrative force within the TCAP and has helped coordinate research and education activities. In summary, a large cohort of plant breeders are being trained in traditional and modern breeding strategies that will provide the continuity required for sustainable cereal breeding activities in the US.

F. Training

Two hundred and ninety three people (undergraduates, graduate students, postdocs, visiting scientists and PIs) have participated in training through the TCAP including courses and seminars on the PBTN as well as face to face workshops, trainings and collaborative research. This number does not include those supported by TCAP to attend NAPB meeting (78) or CSU Drought Symposium (65).

Graduate student training: A total of 69 graduate students have participated in the plant breeding training network. 62 of these are directly mentored by a TCAP PI with 38 students being fully or partially funded by TCAP. Several students have participated in TCAP classes and have no affiliation with TCAP. A complete list of graduate students is provided in Appendix H3.

Undergraduate students: A total of 55 undergraduates have participated in the TCAP with 37 being mentored by TCAP faculty and graduate students, 17 by MSI PIs. Five graduate students completed Entering Mentoring to support their undergraduate mentoring efforts. A complete list of undergraduate students is provided in Appendix H4.

G. Concluding statement (year 2, 2012)

The TCAP has made tremendous progress on all of the original objectives of the grant and in many cases we are exceeding the original objectives. In brief, we have phenotyped and genotyped large collections of wheat and barley germplasm, developed or are in the process of developing novel mapping populations, implemented nation-wide MAS approaches for wheat and barley improvement, initiated GS projects, developed GBS and gene capture technologies for assessing and using variation in wheat and barley, established T3 as the project database, and established the Plant Breeding Training Network (PBTN). The PBTN is delivering on its dual role of training students in plant breeding and attracting new students into plant breeding. The mapping and association mapping activities are yielding the first favorable alleles for NUE, WUE, and disease resistance for use in developing new varieties that can ameliorate the negative impacts of climate change. High-throughput marker-based breeding approaches are being implemented nation-wide and the first commercial varieties and improved germplasm using marker assisted selection are being released. The precise genotypic and phenotypic characterization of the large US core collections of wheat and barley, and the organization of this information in a breeding database (T3) will serve current and future generations of barley and wheat breeders, and can serve as a footprint for other crop species.

H. Appendices (year 2, 2012)

H1. Publications 2012

H2. Germplasm Release 2012

H3. Trained Graduate students

H4. Trained Undergraduate students

Appendix H1. Peer Reviewed Publications 2012 (35 publications)

1.- Anderson, J.A., J.J. Wiersma, G.L. Linkert, J.A. Kolmer, Y. Jin, R. Dill-Macky, J.V. Wiersma, G.A. Hareland, and R. H. Busch. 2012. Registration of ‘Tom’ Wheat. J. Plant Registrations. 6: 2: 180-185

2.- Anderson, J.A., J.J. Wiersma, G.L. Linkert, J.A. Kolmer, Y. Jin, R. Dill-Macky, J.V. Wiersma, G.A. Hareland, and R. H. Busch. 2012. Registration of ‘Sabin’ Wheat. J. Plant Registrations. 6: 2: 174-179

3.- Baenziger, P.S., R. A. Graybosch, t. Regassa, L.A. Nelson, R. N. Klein, D. K. Santra, D.D. Baltensperger, L. Xu, S. N. Wegulo, Y. Jin, J. Kolmer, Ming-shun Chen, and Guihua Bai. 2012. Registration of ‘NE01481’ hard red winter wheat. J. Plant Reg. 6:49-53.

4.- Baenziger, P.S., R. A. Graybosch, T. Regassa, L.A. Nelson, R. N. Klein, D. K. Santra, D.D. Baltensperger, J. M. Krall, S. N. Wegulo, Y. Jin, J. Kolmer, Ming-shun Chen, and Guihua Bai. 2012. Registration of ‘NI04421’ hard red winter wheat. J. Plant Reg. 6:54-59.

5.- Bernardo A. N., H. Ma, D. Zhang, and G. Bai. 2012. Single Nucleotide Polymorphism in wheat chromosome region harboring Fhb1 for Fusarium Head Blight resistance. Mol Breed. 29:477–488.

6.-Blake, V.C., J.G. Kling, P.M. Hayes, J.-L. Jannink, S.R. Jillella, J. Lee, D.E. Matthews, S. Chao, T.J. Close, G.J. Muehlbauer, K.P. Smith, R.P. Wise and J.A. Dickerson. 2012. The Hordeum Toolbox – The barley coordinated agricultural project genotype and phenotype resource. The Plant Genome 5:81-91.

7.- Chen, J. L. ; C. G. Chu; E. J. Souza; M. J. Guttieri; X.M. Chen; S. Xu; D. Hole; R. Zemetra. 2012. Genome-wide identification of QTL conferring high-temperature adult-plant (HTAP) resistance to stripe rust (Puccinia striiformis f. sp. tritici) in wheat. Mol. Breeding 3:791-800.

8.- Edwards, J.T., R.M. Hunger, E.L. Smith, G.W. Horn, M.-S. Chen, L. Yan, G. Bai, R.L. Bowden, A.R. Klatt, P. Rayas-Duarte, R.A. Osburn, J.A. Kolmer, Y. Jin, D.R. Porter, K.L. Giles, B.W. Seabourn, M.B. Bayles, and B.F. Carver. 2012. ‘Duster’ wheat: A durable, dual-purpose cultivar adapted to the southern Great Plains of the USA. J. Plant Reg. 6:1-12.

9.- Haley, S.D., Johnson, J., Peairs, F., Stromberger, J., Hudson, E., Seifert, S., Kottke, R., Valdez, V., Rudolph, J., Bai, G., Chen, X., Bowden, R.L., Jin, Y., Kolmer, J.A., Chen, M., Seabourn, B.W. 2012. Registration of ‘Byrd’ wheat. Journal of Plant Registrations. 6:302-305.

10.- Haley, S.D., Johnson, J., Westra, P., Peairs, F., Stromberger, J., Hudson, E., Seifert, S., Kottke, R., Valdez, V., Rudolph, J., Bai, G., Chen, X., Bowden, R.L., Jin, Y., Kolmer, J.A., Chen, M., Seabourn, B.W. 2012. Registration of ‘Brawl CL Plus’ wheat. Journal of Plant Registrations. 6:306-310.

11.- Haley, S.D., Johnson, J., Peairs, F., Stromberger, J., Hudson, E., Seifert, S., Kottke, R., Valdez, V., Rudolph, J., Martin, T.J., Bai, G., Chen, X., Bowden, R.L., Jin, Y., Kolmer, J.A., Chen, M., Seabourn, B.W. 2012. Registration of ‘Denali’ wheat. Journal of Plant Registrations. 6:311-314.

12.- Hazard B., X. Zhang, P. Colasuonno, C. Uauy, D.M. Beckles, and J. Dubcovsky. 2012. Induced mutations in the Starch Branching Enzyme II (SBEII) genes increase amylose and resistant starch content in pasta wheat. Crop Sci. 52: 1754-1766.

13.- Heslot, N., H.-P. Yang, M.E. Sorrells, and J-L. Jannink. 2012. Genomic selection in plant breeding: A comparison of models. Crop Sci. 52:146-160.

14.- Lanning, S. P., P. Hucl, M. Pumphrey, A. H. Carter, P. F. Lamb, G. R. Carlson, D. M. Wichman, K. D. Kephart, D. Spaner, J. M. Martin and L. E. Talbert. 2012. Agronomic performance of spring wheat as related to planting date and photoperiod response. Crop Sci. 52:1633-1639.

15.- Lanning, S. P., J. M. Martin, R. N. Stougaard, F. R. Guillen-Portal, N. K. Blake, J. D. Sherman, A. M. Robbins, K. D. Kephart, P. Lamb, G. R. Carlson, M. Pumphrey, and L. E. Talbert. 2012. Evaluation of near-isogenic lines for three height-reducing genes in hard red spring wheat. Crop Sci. 52:1145-1152.

16.- Leng, Y. and S. Zhong. 2012, Sfp-type 4′-phosphopantetheinyl transferase is required for lysine synthesis, tolerance to oxidative stress and virulence in the plant pathogenic fungus Cochliobolus sativus. Mol. Plant Path. 13: 375–387.

17.- Liu, Z.-H., Zhong, S., Edwards, M.C., and Friesen, T.L. 2012. Virulence profile and genetic structure of a North Dakota population of Pyrenophora teres f. teres, the causal agent of net form net blotch of barley. Phytopath. 102:539-546.

18.- Lorenz, A.J., K.P. Smith, and J.-L. Jannink. 2012. Potential and optimization of genomic selection for Fusarium head blight resistance in six-row barley. Crop Sci. Vol. 52 No. 4, p. 1609-1621.

19.- Mengistu, N., P. S. Baenziger, K. M. Eskridge, I. Dweikat, S. N. Wegulo, K. S. Gill, and A. Mujeeb-Kazi. 2012. Validation of QTL for grain yield-related traits on wheat chromosome 3A using recombinant inbred chromosome lines. Crop Sci.: 52:1622-1632.

20.- Morrell, P.L., Buckler, E.S., Ross-Ibarra, J. 2012. Crop genomes: advances and applications. Nat. Rev. Genet. 13:85-96

21.- Naruoka, Y., J. D. Sherman, S. P. Lanning, N. K. Blake, J. M. Martin, and L. E. Talbert. 2012. Genetic analysis of long green leaf duration in spring wheat. Crop Sci. 52: 1: 99-109.

22.- Pradhan G.P., P.V.V. Prasad, A.K. Fritz, M.B. Kirkham, and B.S. Gill. 2012. Response of Aegilops species to drought stress during reproductive stages of development. Functional Plant Biology. 39:51-59.

23.- Pradhan G.P., P.V.V. Prasad, A.K. Fritz, M.B. Kirkham, and B.S. Gill. 2012. Effect of drought and high temperature stress on synthetic hexaploid wheat. Functional Plant Biology. 39:190-198.

24.- Pradhan G.P., P.V.V. Prasad, A.K. Fritz, M.B. Kirkham, and B.S. Gill. 2012. High temperature tolerance in Aegilops species and its potential transfer to wheat. Crop Sci. 52: 292-304.

25.- Poland J.A., P.J. Brown, M.E. Sorrells, and J.-L. Jannink. 2012. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PloS ONE 7:e32253.

26.- Yu, L-X, A. Morgounov, R. Wanyera, M. Keser, S. Kumar Singh, and M.E. Sorrells. 2012. Identification of Ug99 stem rust resistance loci in winter wheat germplasm using genome-wide association analysis. Theor. Appl. Genet. 125:495-502.

27.- Zhang X.H., H.Y. Pan and G.H. Bai. 2012. Quantitative trait loci for fusarium head blight resistance in U.S. hard winter wheat cultivar ‘Heyne’. Crop Sci. 52:1187–1194.

Published on line

28.- Kulwal, P., G. Ishikawa, D. Benscher, Z. Feng, L-X Yu, A. Jadhav, S. Mehetre, and M. E. Sorrells. 2012. Association mapping for pre-harvest sprouting resistance in white winter wheat. Theor Appl Genet. DOI 10.1007/s00122-012-1872-0

29.- Kumar S., S.K. Sehgal, U. Kumar, P.V.V. Prasad, A.K. Joshi, B.S. Gill. 2012. Genomic characterization of drought tolerance-related traits in spring wheat. Euphytica. DOI:10.1007/s10681-012-0675-3

30.- Rutkoski, J., J. Benson, Y. Jia, G. Brown-Guedira, J.-L. Jannink, and M.E. Sorrells. 2012. Evaluation of genomic prediction methods for Fusarium head blight resistance in wheat. The Plant Genome. DOI: 10.3835/plantgenome2012.02.0001

31.- Tao Li, Guihua Bai, Shuangye Wu and Shiliang Gu. 2012. Quantitative trait loci for resistance to fusarium head blight in a Chinese wheat landrace Huangfangzhu. Euphytica. DOI 10.1007/s10681-012-0631-2

32.- Zhang X.H., H.Y. Pan and G.H. Bai. 2012. Quantitative trait loci responsible for fusarium head blight resistance in Chinese wheat landrace Baishanyuehuang. Theor. Appl. Genet. DOI: 10.1007/s00122-012-1848-0

33.- Neelam K., G. Brown-Guedira, L. Haung. 2012. Development and validation of a breeder-friendly KASPar marker for wheat leaf rust resistance locus Lr21. Mol Breeding DOI 10.1007/s11032-012-9773-0

In press (2)

34.- Hale I., X. Zhang, D. Fu, and J. Dubcovsky. 2012. Registration of wheat lines carrying the partial stripe rust resistance gene Yr36 without the Gpc-B1 high grain protein content allele. J. Plant Reg. In press.

35.- X. Wang, J. Richards, T. Gross, A. Druka, A. Kleinhofs, B. Steffenson, M. Acevedo and R. Brueggeman (2012) The rpg4-mediated resistance to wheat stem rust (Puccinia graminis) in barley (Hordeum vulgare) requires Rpg5, a second NBS-LRR gene and an actin depolymerization factor. MPMI. In Press.

Appendix H2. Varieties and Germplasm Release 2012

Most of the varieties reported below were initiated during the WheatCAP and BarleyCAP projects and were completed during the TCAP.

2012 Variety releases

UI Stone (IDO599) soft white spring wheat released by Jianli Chen at the University of Idaho has high yield under both irrigation and water limited conditions as well as excellent end-use quality. UI Stone has good resistance to FHB and FHB1 gene based on molecular marker UMN10. Two additional lines are in the process of being released: IDO671 (SWS), IDO694 (HWS)
Hard red spring variety ‘Rollag’. Jim Anderson, MN. Rollag has a unique combination of highest available resistance to Fusarium head blight and strong straw. Rollag contains the Fhb1 QTL for Fusarium head blight resistance and Lr34.
Hard red spring variety ‘Norden’, Jim Anderson, MN. Norden is a competitive yielder with high test weight, good straw strength and leaf rust resistance not based on Lr21. Norden contains the Fhb1 QTL for Fusarium head blight resistance and Lr34.
WB9879CLP is a two-gene Clearfield variety with resistance to imidazolinone herbicides developed by Montana State University and licensed to Westbred LLC for commercialization. The genes for herbicide resistance were backcrossed into the widely grown variety Choteau using marker-assisted selection. WB9879CLP is being grown in areas of Montana and North Dakota with wheat stem sawfly pressure.
Patwin-515 hard white spring wheat released by J. Dubcovsky (University of California, Davis) which includes stripe rust resistance genes Yr5 and Yr15.
Three SRW wheat cultivars (5187J, 12V51, and Yorktown) were developed and released by Carl Griffey at Virginia Tech. Cultivar 5187J has Sr24 + 1A.1R translocation conferring resistance to Ug99; cultivar 12V51 is highly resistant to glume blotch (S. nodorum) and has the Lr9 gene contributing to leaf rust resistance and cultivar Yorktown has the 1A.1R translocation and Lr9.

2012 Germplasm releases

Recombinant inbreed lines with Yr36 but without the closely linked gene GPC-B1 in both tetraploid (PI 656793) and hexaploid wheat (PI 664549). The hexaploid recombinant line is particularly useful for soft wheat breeding programs.

Appendix H3. Trained Graduate students

A total of 69 graduate students have participated in the plant breeding training network (listed below). 62 of these are directly mentored by a TCAP PI with 38 students being funded by TCAP.

Graduate Student	Mentor	Funding TCAP	Institution
Ando, Kaori	Mike Pumphrey	–	Washington State University
Bajgain, Prabin	James Anderson	Full	University of Minnesota
Becker, Steve	Pat Byrne	–	Colorado State University
Belcher, Araby	Patrick Hayes, Alfonso Cuesta-Marcos	Full	Oregon State University
Bowman, Brian	Jianli Chen	Full	University of Idaho
Cai, Jin	Guihua Bai	–	Kansas State University
Case, Austin	Brian Steffenson	Partial	University of Minnesota
Chappell, David	Anne McKendry	–	Missouri State University
Cobo, Nicolas	Jorge Dubcovsky	–	UC Davis
Cooper , Jessica	Scott Haley		Colorado State University
Dwoney, Samantha	Mike Pumphrey	–	Washington State University
Edae, Erena	Pat Byrne/Scott Haley	–	Colorado State University
Falcon, Celeste	Kevin Smith	Full	University of Minnesota
Fang, Tilin	Liuling Yan	Partial	Oklahoma State University
Frels, Katherine	P. Stephen Baenziger	Full	University of Nebraska, Lincoln
Gizaw, Shiferaw	Arron Carter	Full	Washington State University
Godoy, Jayfred Gaham	Michael O. Pumphrey	Full	Washington State University
Gonzales, Ana	Peter L. Morrell	Full	University of Minnesota
Green, Andrew	Carl Griffey	–	Virginia State
Grogan, Sarah	Dr. Pat Byrne	Full	Colorado State University
Guttieri, Mary	Brian Waters/Stephen Baenziger	Partial	University of Nebraska, Lincoln
Harrington, Judy	Pat Byrne	–	Colorado State University
Hazard, Brittany	Jorge Dubcovsky	Partial	UC Davis
Hegarty, Josh	Jorge Dubcovsky	Partial	UC Davis
Hoffstetter, Amber	Clay Sneller	Partial	Ohio State University
Hofstad, Anna	Gary Muehlbauer	–	University of Minnesota
Howell, Tyson	Jorge Dubcovsky	Partial	UC Davis
Johnson, Brittney	Prabin Baijgan	Full	University of Minnesota
Kalous, Jay	Luther Talbert	Full	Montana State University
Larrea-Bueno, Alejandra	David VanSanford	Full	University of Kentucky
Latshaw, Sue	Scott Haley	–	Colorado State University
Lei, Lei	Liuling Yan	Full	Oklahoma State University
Lin, Meng	Guihua Bai	–	Kansas State University
Liu, Shubing	Guihua Bai	–	Kansas State University
Liu, Weizhen	Mike Pumphrey	–	Washington State University
Lu, Yue	Guihua Bai	Partial	Kansas State University
Mahmoud, Wahid	Pat Byrne	–	Colorado State University
Mekonnen, Melaku	Pat Byrne	–	Colorado State University
Merrill, Keith	Gina Brown-Guedira	Full	North Carolina State University
Muleta, Kebede Tadesse	Mike Pumphrey	–	Washington State University
Nair, Sindhu Gopalkrishnan	Mike Pumphrey	–	Washington State University
Narayanan, Sruthi	P.V. Vara Prasad	Full	Kansas State University
Nayak, Santosh	Jianli Chen	–	University of Idaho
Nazarov, Taras	Deven See	Full	Washington State University
Neupane, Anjan	T.L. Friesen & Dr. R. Bruggaman	Full	North Dakota State
Nice, Liana	Gary Muehlbauer	Full	University of Minnesota
Nitcher, Rebecca	Jorge Dubcovsky	–	UC Davis
Onweller, Kayse	Stephen Baenziger	–	University of Nebraska
Pauli, Duke	Tom Blake	Full	Montana State University
Pavuluri, Kiran	Wade Thomason	Partial	Virginia State
Rife, Trevor	Jesse Poland	Full	Kansas State University
Salcedo, Andres	Eduard Akhunov	–	Kansas State University
Sharma Poudyal, Dipak	Xianming Chen	–	Washington State University
Shroyer, Kyle	P.V.V. Prasad	–	Kansas State University
Singh, Arti	Ron Knox	–	AAFC-SPARC Canada
Sthapit, Jinita	Deven See	Partial	Washington State University
Su, Yuanjie	Dave Douches	–	Michigan State University
Tamang, Prabin	Robert Bruggeman	Full	North Dakota State University
Tavarez, Michael (MSI Student)	Renuka Sankaran/Waters	Partial	Lehman College
Turner, M Kathryn	Jim Anderson	Full	University of Minnesota
Varella, Andrea	Jamie Sherman	Partial	Montana State University
Veenstra, Lynn	Jean-Luc, Mark Sorrells	Partial	Cornell
Wang, Rui	Shaobin Zhong	Full	North Dakota State University
Ward, Brian	Carl Griffey		Virginia State University
Xiong, Mai	Gina Brown-Guedira	Partial	North Carolina State University
Yang, Xiping	Guihua Bai		Kansas State University
Zhang, Junli	Jianli Chen	Partial	University of Idaho
Zia Ullah Zia	David Hole		Utah State University

Appendix H4. Trained Undergraduate students

A total of 55 undergraduates have participated in the TCAP with 37 being mentored by TCAP faculty and graduate students, 17 by MSI PIs.
Undergrad Student	Mentor	Funding	Institution
Amole, Oyejare	Marceline Egnin	MSI	Tuskegee University
Barnes, Ryan	Anne McKendry	TCAP	Missouri State University
Bickford, Aidan	Tom Blake	TCAP	Montana State University
Brown, Stephanie	JiaQian Zhu	MSI	Rust College
Burgess, Brandon	Brian Arnall	TCAP	Oklahoma State
Calister, Maddie	Baenzinger or Waters	TCAP	University of Nebraska
Ceesay, Lolley (MSI Student)	S. Grogan (Mentor) – P. Byrne – Zhu	MSI	University of Nebraska
Clawson, Ryan	David Hole	TCAP	Utah State University
Cooper, Jessica	Scott Haley	–	Colorado State University
Currie, Yaleaka (MSI Student)	Zhu/Bai	MSI	Fayetteville St. Univ., North Carolina
Elmore, Elizabeth	Robert Bowden	TCAP	Kansas State University
England, Serina	Liu/Chen	MSI	Texas A&M
Gamble, Devona	Botanga/Anderson	MSI	Chicago State University
Gaston, Jasmine	Matute/Arron Carter	MSI	University of Arkansa, Pine Bluff
Goldsby, Kaitlin	Guihua Bai	TCAP	Kansas State University
Grabbe, Reagan	Jamie Sherman	TCAP	Montana State University
Graebner, Ryan	Pat Hayes	TCAP	Oregon State
Graham, Anthony	Arron Carter	MSI	University of Arkansa, Pine Bluff
Hole, Chelsea	David Hole	TCAP	Utah State University
Hughes, Austin	P.V.V. Prasad	TCAP	Kansas State University
Hulbert, Bryn	Mike Pumphrey	TCAP	Washington State University
Johnson, Brittney	Jim Anderson	TCAP	University of Minnesota
Johnson, Isiah	Jose Costa	TCAP	University of Maryland
Johnson, Whetney	Onyilagha/Talbert	MSI	University of Arkansa, Pine Bluff
Kellem, Mariam	Matute/Arron Carter	MSI	University of Arkansa, Pine Bluff
Lowry, Elizabeth	Eduard Akhunov	TCAP	Kansas State University
Manning, Yvonne	Matute/Arron Carter	MSI	University of Arkansa, Pine Bluff
McCabe, Matt	Luther Talbert	TCAP	Montana State University
McCauley, Cara	Mark Sorrells	TCAP	Cornell
Miller, Daniela	Jose Costa	TCAP	University of Maryland
Amanda McClendon	Onyilagha/Talbert	MSI	Arkansas Pine Bluff
Cody Shatcher	Liu/Chen	MSI	Texas A&M
Nazar, Aneesh	Jorge Dubcovsky/Josh Hegarty	TCAP	UC Davis
Nelms, Eric ‘Wes’	Jorge Dubcovsky/Marco Maccaferri	TCAP	UC Davis
Nevarez, Martha	Botanga/Anderson	MSI	Chicago State University
Neyhart, Jeffrey	Mark Sorrells	TCAP	Cornell
Ngu, Ester	Shaobin Zhong	Partial	North Dakota State University
Oliver, Brian	David Van Sanford	TCAP	University of Kentucky
Prayer, Jeffrey	Gina Brown-Guedira	TCAP	North Carolina State University
Ray, Erin	Mary Guttieri	TCAP	University of Nebraska
Reese, Angela	Botanga/Anderson	MSI	Chicago State University
Roberson, Heather	Tim Close	TCAP/MSI	University of California, Riverside
Rodriguez, Jose	Tim Close	TCAP/MSI	University of California, Riverside
Sallee, Katie	Liuling Yan	–	Oklahoma State University
Salvo, Kelsey	Patrick Byrne	TCAP	Colorado State University
Shekleton, Joe	Jim Anderson	TCAP	University of Minnesota
Skinner, Avarie	Arron Carter	TCAP	Washington State University
Sleper, Joshua	Gary Muehlbauer	Other	University of Minnesota
Smith, Gabe	Brian Steffenson	TCAP	University of Minnesota
Stevens, Mary	P.V.V. Prasad	TCAP	Kansas State University
Sun, Tianqi	Kevin Smith	TCAP	University of Minnesota
Underwood, Josh	Zhu/Bai	MSI	Fayetteville St.e Univ., North Carolina
Van De Weghe, Michael	Gary Muehlbauer	TCAP	University of Minnesota
Wagner, Secret	Marceline Egnin	MSI	Tuskegee University
Wanza Ngao, Shiela	P.V. Vara Prasad	TCAP	Kansas State University

Appendix H5. Presentations by TCAP students

Graduate students underlined

1.- Bowman B,. J. M. Bonman, J. Zhang, E. Jackson, H. Bockelman, S. Chao, N. Heslot, M. Sorrells, J. Wheeler, and J. Chen. 2012. Mining high WUE and NUE in wheat (T. aestivum L.) genotypes in the USDA-ARS NSGC. 2012 PAG, San Diego, California, Jan. 14 – 18, 201.

2.- Bowman^,B. J. Zhang, J. Wheeler, J. M. Bonman, H. Bockelman and J. Chen. 2012. Agronomic Characteristics of spring wheat accessions from the USDA NSGC evaluated under drought and low nitrogen environments. Western Society of Crop Science (July 1113, 2012), Washington State University, Pullman, WA. (Oral Presentation)

3.- Cobo N., L. Tomar, A. Alvarez, F. Paraiso, L. Pflüger and J. Dubcovsky. QTL analysis for high yield protein content genes in a Triticum aestivum RIL mapping population. ASA, CSSA and SSSA Annual Meeting, Cincinnati, OH- Oct. 21 – Oct. 24, 2012.

4.- Gonzales, A.M. and P.L. Morrell. Genetic provenance and genetic providence in a diverse crop. 22^nd ITMI & 4^th National Wheat Genomics Committee Joint Workshop, Fargo, ND, 25 – 29 June 2012.

5.- Hazard B., X. Zhang, P. Colasuonno, C. Uauy, D.M. Beckles, and J. Dubcovsky. 2012. Induced mutations in the starch branching enzyme II (SBEII) genes increase amylose and resistant starch content in durum wheat. ASA, CSSA and SSSA Annual Meeting, Cincinnati, OH- Oct. 21 – Oct. 24, 2012.

6.- Howell T., I. Hale, A. Lukaszewski, and J. Dubcovsky. 2012. A recombinant 1RS.1BL chromosome with interstitial wheat segments in the Sec1 and Glu-B3 regions is more susceptible to drought than the intact 1RS.1BL chromosome. ASA, CSSA and SSSA Annual Meeting, Cincinnati, OH- Oct. 21 – Oct. 24, 2012.

7.- Kalous, J., McCabe, M. 2012. Marker Trait Associations in Recombinant Inbred Wheat Lines. Plant Science Department Biotechnology Seminar

8.- Kippes, N., J. Zhu, A. Chen, H. Nishida, L. Vanzetti, K. Kato, M. Helguera, J. Dubcovsky. 2012. Fine mapping and epistatic interactions of Vrn-D4 in common wheat (Triticum aestivum L.). PAG XX, January 14-18, San Diego, CA. P306.

9.- Nice, L. M., Steffenson, B., Schwarz, P., Smith, K.P., Muehlbauer, G. January 2012. Advanced backcross QTL mapping of yield and malt quality in a wild x cultivated barley mapping population. PAG XX San Diego, CA (Abstract and Poster Presentation)

10.- Nitcher, R., A. Distelfeld, and J. Dubcovsky. Characterization of barley natural variation at the HvFT1 locus affecting flowering time. ASA, CSSA and SSSA Annual Meeting, Cincinnati, OH- Oct. 21 – Oct. 24, 2012.

11.- Wang, R., Leng, Y., and *Zhong, S. 2012. The role of a velvet-like complex in fungal development and virulence of the cereal pathogen Cochliobolus sativus. P0848 PAG XX, San Diego, CA. (Poster).

12.- Zhang, J., J. Chen, W, Zhao, J. Wheeler, E. Souza, and R. Zemetra. 2012. Quantitative Trait Loci Associated with Canopy Temperature, Chlorophyll Content Index, and Flag Leaf Senescence in a Recombinant Inbred line Population of Winter Wheat (Triticum aestivum L.). PAG XX, San Diego, California, Jan. 14 – 18, 2012.

13.- Zhang, J., J. Chen, Y. Wang, B. Bowman, J. Wheeler, W. Zhao, K. O’Brien, J. Marshall, H. Bockelman and J. M. Bonman. Association Mapping of Hagberg Falling Number in Hard White Spring Wheat Accessions. Western Society of Crop Science (July 1113, 2012), Washington State University, Pullman, WA. (Oral Presentation)

14.- Zhang, J. Chen, J., Y. Wang, B. Bonman, J. Wheeler, W, Zhao, K. O’Brien, J.M. Marshall, H. Bockelman, and J. Bonman. 2012. Association mapping of low falling number in hard white spring wheat collection materials. Poster presentation and abstract in the proceedings of 2012 ASA, CSSA and SSSA Int’l Annual meeting, Cincinnati, OH, Oct.21-24.

Presentations by undergraduate students (underlined)

15.- Kelsey Salvo and Sarah Grogan. Characterizing glaucousness in wheat. Celebrate Undergraduate Research and Creativity Symposium, Poster 170. Colorado State University, April 17, 2012.

16.- Mariam Kaleem and Yvonne Manning presented Initial soil profiling for plant-parasitic nematodes before a Triticum aestivum crop on March 7, 2012 at 25^th Annual Student and Faculty Research Forum, University of Arkansas, Pine Bluff, Arkansas, winning Overall Winner for Best undergraduate presentation and First Place Award in Undergraduate Level in Scholarly Research in the Area of Biology.

17.- Jasmine Gaston presented Potential plant-parasitic nematode constraint to profitable Triticum aestivum production on April 20, 2012 at Twentieth Annual Arkansas Space Grant Symposium, The Winthrop Rockefeller Institute, U of A System, Morrilton, Arkansas.

18.- Ryan Graevbner (TCAP undergrad) and Araby Belcher (TCAP grad) at Oregon State explain the principle of CSR at a field day held for “Leadership Corvallis”.

Annual Report – September 2012

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