Progress 01/01/24 to 12/31/24
Outputs
Target Audience:Audiences targeted by the research activities: 1) Wheat growers and wheat grower associations. WheatCAP breeding programs presented their results to state wheat commissions, grower associations, and individual growers during field days and annual meetings. Wheat growers are direct beneficiaries of the new varieties developed by the WheatCAP researchers. 2) Wheat milling and baking industry.WheatCAP results were presented to the Wheat Quality Council and other Quality Collaborative Programs across the USA. Presentations were also made to individual milling and baking companies. 3) Scientists working in basic and applied aspects of wheat research. Results from the WheatCAP were presented to other researchers in 28 papers published in peer-reviewed journals. WheatCAP PIs, coPIs and students gave presentations at national conferences including Plant and Animal Genome, ASA-CSSA meetings and the Internation Wheat Congress in Perth. 4) International wheat research community. WheatCAP researchers made presentations in different countries and published their results in internationally recognized scientific journals. WheatCAP participants sent improved wheat lines to the CIMMYT Hub in Mexico and the winter hub in Kansas. 5) Wheat breeders in the public and private sectors. Varieties and germplasm generated by WheatCAP breeders have been made available to all members of the WheatCAP team and to public and private breeding programs that requested seeds for crossing. As promised in the grant proposal, the datasets deposited the first years of the project in the section restricted to WheatCAP participant have been transferred to the public T3 database making the data available for all. 6) Markers for specific yield-enhancing genes are publicly accessible through the MASwheat website. TILLING mutants were distributed to wheat breeders and researchers in the US and abroad. All mutations are accessible and searchable in a public database and the seeds of the mutant lines are distributed without IP limitations. Audiences targeted by the educational activities: 1) Graduate and undergraduate students interested in plant breeding (including students outside the project). Education materials from the WheatCAP workshops have been uploaded to the WheatCAP website and are publicly available. 2) Educators interested in online tools for plant breeding and genetics. The results of educational surveys generated by WheatCAP are available through the WheatCAP website. 3) Breeding companies interested in the training of their workforce. There is a sustained demand for WheatCAP students from the private industry. 4) Extension specialists, farm advisors and growers. In addition to information related to the new wheat varieties, WheatCAP coPIs educate extension specialists, farm advisors, growers, and the seed industry about the opportunities and limitations of new technologies. This information has facilitated the wide acceptance of new marker and genomic technologies as well as the use of UAS for high-throughput phenotyping. These educational activities will be crucial to facilitate the adoption of CRISPR edited wheat varieties. Changes/Problems:There have been no changes in the original objectives of the grant and no changes in the total or individual budgets. The transfer of WheatCAP subaward from Utah State University to Oregon State University (Margaret Krause) mentioned in the previous report was completed smoothly. What opportunities for training and professional development has the project provided?Training opportunities A central objective of the WheatCAP project is to train PhD students in modern plant breeding including both traditional field activities, modern high-throughput genotyping and phenotyping technologies and data analyses. By leveraging funds from participating universities, the WheatCAP project was able to invite students from universities not funded by the project to participate in the educational activities. In 2024, 8 students successfully completed their PhD and another 50 participated in multiple educational activities organized by the project educational coordinator, including three in-person workshops and additional online activities. The number of trained students more than doubled the original target of 20 students proposed in the grant. In 2024, the project held four workshops and will host a fifth in November 2024 (Genomics and bioinformatic resources for wheat in the UK). In January, the WheatCAP Student Workshop was led by students Kyle Parker and Maria Rottersman at the Plant and Animal Genome conference (PAG). Twenty-three students gave short presentations with updates on their research projects to the group. Students also attended the Annual WheatCAP Meeting at PAG, where they presented posters on their research projects. At the WheatCAP Student Workshop and the Annual Meeting, students had time to discuss their projects with fellow students and WheatCAP CoPIs. In the Spring, twelve students in their 3rd or 4th year of their PhD program (Cohort 1) participated in one-on-one coaching and group workshops with BONSAI, a company specializing in leadership coaching and development of graduate students. WheatCAP students took the Gallup 34-strengths assessment and learned about their results during a one-on-one coaching session with a leadership coach. During these sessions, students learned about their unique strengths and how to utilize these talent themes to be more productive at work and better lead and collaborate. Students also participated in two workshops designed to build off their strengths. The first workshop focused on being more effective as individuals, appreciating their strengths, while learning about those that others possess. Understanding how one's strengths impact the ability to communicate and influence others was a key component of this session.A second workshop focused on utilizing strengths in teams. This helped students understand how to interact strategically with others, such as their PI or lab mates. Students learned how to predict and navigate team dynamics. A process for effective delegation was taught and practiced. In April, twenty-four WheatCAP students attended a two-day online course on hybrid breeding strategies offered by the UC-Davis Seed Biotechnology Center. Students were provided copies of all lectures for future reference. This course supplements the students' training on breeding self-pollinated crops, provided by their respective breeding programs. The Functional Genomics workshop was held in Manhattan, KS at Kansas State University August 5th-9th and attended by 26 WheatCAP students and 6 externally funded graduate students. The first day students learned about cytogenetics of wild wheat introgression, completing a genomic in situ hybridization laboratory to identify wild wheat introgressions via fluorescence microscopy. Next, the students created RNA-seq libraries in the lab and conducted RNA-seq data analyses. Students also learned about sequencing technologies, genotyping, practical haplotype imputation, and marker design, applying what they learned in hands-on computer exercises using R. Students toured the Kansas Wheat Innovation Center, the Wheat Genetics Resource Center, and the KSU Integrated Genomics Facility. In Spring 2024, Zachary King, a corn breeder at Syngenta, led a meeting talking about his experiences on finding, applying, and interviewing for industry breeding positions and advice for a successful career in plant breeding. Sarah Davidson Evanega, Vice President of External Relations at Okanagan Specialty Fruits and former Founding Executive Director at Alliance for Science, led a meeting discussing the current state of biotechnology uses in crops and public perception of genetically modified organisms and gene editing. Recordings of meetings were shared with students via e-mail. In 2024, the WheatCAP student mentorship program was created. The Education Coordinator identified and matched 19 professionals in industry (13), non-profit (1), and academic (5) careers in plant breeding and data science fields with interested students. Sixteen of the mentors work in the United States, two work in Canada, and one works in Germany. Mentors and mentees were matched based on their responses to an application with questions evaluating their expectations for mentorship and what they hope to gain from and contribute to the experience. This fall, students resumed monthly meetings with invited speakers. Jennifer Yates, the wheat breeding lead at Bayer, and Masha Trenhaile, Head of University Strategy and Outreach, led an information session about the Bayer co-op and internship programs for graduate students. Jennifer also shared her career journey. Cohort 1 will participate in mock interview panels where they will both be interviewed and interview others and receive feedback on their performance. Sara Tirado Tolosa, Global Precision Phenotyping Lead at Corteva Agriscience, will discuss the applications of machine learning and AI in trait discovery and plant breeding. In November, the students will attend the final workshop of 2024, "Genomics and bioinformatic resources for wheat in the UK" hosted by Designing Future Wheat. In December, students will have a monthly meeting focusing on effective networking, including having a positive presence on LinkedIn, prior to attending PAG in January 2025. In addition to the graduate student educational activities, the public wheat breeding programs provided training opportunities for many undergraduate students. The training of the undergrad students also provided the graduate students opportunities to learn mentorship skills. How have the results been disseminated to communities of interest?Results generated by WheatCAP researchers have been disseminated in multiple ways. First, results have been disseminated to the national and international research community in 28 peer-reviewed papers published in prestigious scientific journals including Development, The Plant Journal, Plant Biotechnology Journal, BMC Biology, and others. Tomeasure the impact of the WheatCAP publications, we keep track of the number of cross-citations of papers published by each WheatCAP project acknowledging USDA-NIFA support. Even though this program started in 2022, the papers published in this project have been already cited 1,149 times in Google Scholar (h index = 20). We also keep track of the impact of publications from the two previous WheatCAP: Publicationsfrom the TriticeaeCAP (2011-2016) were referenced 28,502 times (h index = 79) and those from the previous WheatCAP (2017-2021) were references 8,504 times (h index = 52). These numbers document the high impact of the WheatCAP publications. Results have also been presented in person at multiple scientific meetings in the US including the ASA-CSSA meeting, the Plant and Animal Genome Conference, and remotely by Zoom. Results from several groups were also presented at the Wheat International congress in Perth, Australia. Marker-assisted selection (MAS) protocols were distributed through the MASwheat website (http://maswheat.ucdavis.edu/). The WheatCAP coPIs also distribute their research results directly into seeds of adapted wheat germplasm carrying novel alleles or allele combinations. The 19 public WheatCAP breeding programs generate and share breeding lines and germplasm including different gene combinations, which can be used to tackle the different problems facing wheat production. More than 20,000 samples of seeds from the sequenced EMS mutant populations have been distributed worldwide in the last five years, documenting the impact of these resources. WheatCAP research results are also distributed as new DNA vectors. Until October 2024, the GRF4-GIF1 vectors for improved wheat transformation were distributed to more than 300 laboratories through Addgene. The new genomic resources generated by WheatCAP have been widely advertised through the GrainGenes list server, conferences, student workshops, and computer demos. Resources have been made widely available to the international wheat research community. The more applied results have been communicated directly to the growers attending the field days hosted by the 19 WheatCAP breeding programs. Results have been also shared with the state wheat commissions and other wheat grower associations. Results affecting quality have been presented in the Wheat Quality Council and in quality collaborative programs organized in the different states. These meetings include breeders, handlers, millers, and bakers. Educational tools and online resources have been distributed throughthe project web site https://www.triticeaecap.org/educational-activities/ and are also available through the online Plant Breeding Training Network. What do you plan to do during the next reporting period to accomplish the goals?Education priorities Y4 The education priorities for 2025 include several workshops, expanding the mentorship program for new students, and continuing writing groups and monthly meetings. One workshop will be in person, the other three will be online. The first workshop will behosted online by CIMMYT and will include topics such as the role of CGIAR and CIMMYT, the CIMMYT traditional breeding program, physiological breeding strategies and approaches, the integration of molecular technologies in breeding programs, and available genomic and germplasm resources. In the Spring, the second set of students in their 3rd or 4th year (Cohort 2) will participate in one-on-one leadership coaching with BONSAI, followed by two group workshops,one focused on being more effective as individualsand the other one focused on utilizing strengths in teams. In the fall, Cohort 2 will participate in mock interviews. Genomic Resources priorities Y4 In 2025, the KSU team will conduct analysis of tissue-specific eQTL data generated for a diverse panel of 200 wheat lines and wheat wild relatives. The relationship between marker-trait associations detected in the WheatCAP mapping experiments and eQTL will be investigated and used for building improved genomic prediction models. The deposition of RNA-seq and eQTL data to the T3 database will be completed in 2025. The new PHG based on whole-genome sequence alignments will be further expanded to include additional lines sequenced at intermediate levels of sequence coverage (5-6x) using PacBio technology. These lines will be selected from the set of 200 diverse wheat lines collected from the US wheat breeding programs and used for eQTL study. This dataset will be incorporated into the Wheat PHG taking full advantage of a new version of PHG that has higher imputation accuracy. In addition, the KSU team will integrate into new PHG genomic data generated using short-read technologies at 5-10x coverage for a subset of 200 diverse WheatCAP lines. This will permit more accurate imputation of genome-wide data generated for 200 WheatCAP lines and conduct more accurate eQTL mapping. The updated PHG will be used to impute all deposited genotyping data in the T3 database. The UCD team will explore the expansion of spatial transcriptomics resources by using the 10X Xenium platform. A new experiment with 240 genes is in preparation for early 2025 to characterize developing spikes of wildtype and mutant wheat lines and to expand the spike development expression atlas. Efforts are being coordinated internationally to test different spatial transcriptomics platforms and to generate a uniform nomenclature for genes involved in wheat spike development. T3/Breedbase priorities Y4 The T3 teamwill bring together assemblies that are not yet publicly available to populate a PHGv2 effective for North American germplasm. Theyexpect that next year we will have results from a PHGv2 that incorporates over 30 assemblies. In addition to anonymous genome-wide markers, the genotyping labs score many Known Informative Markers (KIMs), which are typically KASP markers. T3 is working with the labs to coordinate efforts so that common KIMs and inference algorithms are used to call Major Locus Alleles. Controlled vocabularies for the trait categories, the genes, and the known alleles at the genes are being defined. A new genotyping protocol will be defined on T3, the Major Locus Alleles genotyping protocol, for which the allele scores will be determined based on genotypes at the AgriSeq+KASP or Illumina 3K+KASP (from the Fargo Lab). Definition of that protocol will enable the following new functionality: a) Links to available literature on all genes through GrainGenes, which will be linked to the Major Locus detail pages on T3. b) Accession search based on major locus genotypes. Breeders will be able to seek among all genotyped accessions for those carrying specific alleles at those loci. c) Display accession's major locus profiles. The breeder will enter an accession's name in the interface and its genotype at relevant major loci will be displayed. UAS data from programs analyzing their own drone data. Over the coming year the T3 team will develop a system to capture data from programs that are not going through UAS-Hub. The D2S platform described below can be that option. UAS-hub priorities Y4 We plan to switch the UAV data management platform to Data to Science (D2S) to further enhance data accessibility and analysis tools. The D2S will provide a complete UAS data processing pipeline to breeding program so that they can perform all the UAS-based HTP feature extraction and submit the extracted features back to the T3 database without relying on other programs. We plan to train a smaller set of breeding programs in 2024 to test the new D2S platform and switch to the new platform starting in 2025. The switch will be announced in the PAG 2025 meeting with a live demonstration. A full training workshop (online training) will be provided in Q1 of 2025 to complete the transition. As the project enters its fourth additional efforts will be made to make the breeding programs more independent in the analysis of their own data, so they can continue their UAS programs beyond the WheatCAP project. The D2S platform will help with this transition. Challenges: So far, the TX group has successfully downloaded plot map information from T3 and uploaded spatially referenced plot maps and phenotypic information onto T3, but more datasets need to be uploaded. However, there are still communication challenges between the breeding programs and the UAS-hub, which results in late uploading of raw images, and delays in the submission of plot boundaries and upload of the plot map information to T3. These delays then limit the ability of the TX group to complete other tasks on time. The transition to the D2S platform is expected to reduce these delays. Genotyping labs priorities Y4 During year 4 of the grant, the genotyping labs will evaluate new versions of the AgriSeq and Illumina 3K genotyping platforms for genome-wide information content and reliability of trait related markers. The genotyping labs will share information across labs for automated generation of marker reports and add a process to calculate the concordance of new samples against those previously genotyped in the labs. The mid-density platforms will be broadly available for genotyping breeders' samples as requested. The genotyping labs will work with breeders to incorporate new genotyping platforms into their existing genomic selection pipelines. Their analyses indicate that using subsets of samples having overlapping marker datasets (i.e., GBS and AgriSeq markers) is an option for "bridging the gap" between genotyping platforms. Work will be done to utilize a Practical Haplotype Graph for US wheat in this effort. Imputation could allow breeders to use existing training populations for genomic prediction without the need for re-genotyping large numbers of lines. The labs will work to evaluate imputation accuracy and genomic prediction accuracy in breeding materials. Ongoing meetings involving the PI and staff for the four regional genotyping labs and the T3 database will continue in Year 4. The goal is to improve communications across regions, share new results and develop a standardized nomenclature for known informative markers for loci of major effect. This effort is particularly focused on loci evaluated with the targeted mid-density platforms. Standardization of protocols and data handling at the genotyping labs is aimed at uniform reporting for marker data that is conducive to inclusion of more information in T3.
Impacts
What was accomplished under these goals?
WheatCAP overall productivity: During the 3rd year, WheatCAP breeders and researchers released 28 commercial varieties and five improved germplasms, and published 28 new peer-reviewed papers (https://www.triticeaecap.org/publications-and-germplasm/). Phenotypic data was collected from 282 flights using Unmanned Aerial Systems (UAS) over 119 acres (35,376 plots), and genotypic data was collected from 48,9000 samples (>350M datapoints). Agronomic data was collected from 57,800 plots from 290 trials. These data are being entered into T3 and are being used by public breeders to advance their lines and implement genomic selection in their breeding programs. This large dataset is also a valuable research tool. Education: In 2024, eight students successfully completed their PhD and another 50 participated in multiple educational activities, including in-person workshops and additional online activities. Students' personal profiles and projects are available at https://www.triticeaecap.org/educational-activities/. A WheatCAP Student Workshop was led by two PhD students at the 2024 Plant and Animal Genome conference, (PAG), where all students gave short presentations. In the Spring, students participated in two BONSAI workshop focused on leadership coaching and development. In April, students attended a 2-day course on hybrid breeding provided by the UC Davis See Biotechnology Center, and in August a Functional Genomics workshop at KSU. In November, students will attend a two-days online workshop on Genomics and bioinformatic resources for wheat in the UK) T3 database: In this third year of WheatCAP, uploads of phenotypic data continue to be strong. T3 received high numbers of observations coming from drone-based phenotyping. Close to 2,260,000 phenotype observations in the increment from the 2023 report to the 2024 report came from high-throughput phenotyping. The remaining ~380,000 observations were of traditional traits. In the past year the number of phenotypic observations in T3 has more than doubled, reflecting the fact that each has an average of ~30 phenotypes. A large majority of genotyping datasets have now been imputed using a version 1 of the practical haplotype graph, and substantial progress was made towards the development of a second generation PHG (PHG v2). T3 also implemented a simplified form for genotype data submission and generated a more flexible phenotyping trial upload template. An annual submission summary page was developed https://wheatcap.triticeaetoolbox.org/guides/annual-summary. T3 is compliant with the Breeding Application Program Interface (BrAPI), and this has enabled rapid deposit of data into T3. As promised in the proposal, the WheatCAP data with >2 years in the project section of the database were moved to the public T3 database. Genomics resources: Structural genomics: In 2024, we used HiFi to generate genomic data for 10 diverse accessions of wheat. In these 10 new genomes, we detected ~100 M. SNPs, 2.9 M. insertions and 2.6 M deletions differentiating each of the 10 wheat genomes from the reference genome in both coding and regulatory regions. The new 10 wheat genomes were combined with 13 previously sequenced genomes to construct a diversity dataset that was used to build the improved practical haplotype graph version 2 (PHG2). Markers from different platforms present in T3 were integrated using imputation with the PHG v1. Functional genomics: We used quantitative multiplexed in situ hybridization and single-cell transcriptomics to identify distinct cell populations within the developing wheat spike and to construct a spike development expression atlas. We characterized the spatial expression of 99 genes using single-molecule fluorescence in situ hybridization (smFISH) across three stages of spike development. This was followed by single-cell RNA sequencing profiling of 13,660 cells at the late double ridge stage and 13,734 cells at the lemma primordia stage Through clustering analysis, we identified distinct cell types and investigated their functions. To investigate the role of regulatory variation in gene expression, we assembled a diverse panel of 200 lines including wheat, wild relative, and synthetic lines and performed RNA-seq across 5 different tissues. Genotyping laboratories: Regional genotyping labs supported breeding programs doing marker-assisted selection through genotyping samples using trait associated markers as requested. In addition, large numbers of samples were genotyped using non-targeted sequence-based approaches (GBS, MRASeq). In 2024,14,366 samples were submitted to the genotyping labs by WheatCAP breeding programs that were evaluated with 1 to 102 KASP, STS or SSR assays. Large numbers of samples were genotyped using genome-wide sequence-based approaches as part of ongoing genomic selection and gene mapping efforts. These included genotyping 12,892 samples by GBS, 670 samples by MRASeq, 11,808 samples with the Illumina 3K platform, 6,484 samples with the AgriSeq platform, 768 samples with the Allegro targeted genotyping platform and 702 samples with the Axiom 35K array. More than 40M datapoints were deposited in T3. UAS-Hub: The UAS-hub completed the processing of data from 2023 and deposited them into T3. In 2024, the UAS-hub received data from 130 UAV flights covering 30 acres. The initial step of Level 1 data processing--which includes generating orthomosaics and digital surface models--has been completed for all locations. Phenotypic features have been extracted from 85 flights covering 22 acres and the data will be submitted to T3. The TX group is waiting for plot boundary files from 6 wheat breeding programs. The number of breeding programs analyzing their own data has increased significantly (9 programs), which aligns well with the WheatCAP goal of increasing the breeding programs' independence in the use and analyses of UAV-based high-throughput phenotyping. The UAS-hub group in Purdue is developing a new analysis platform called Data to Science (D2S) that will increase the ability of the public breeding programs to complete their UAS data analysis independently. IWYP winter and spring hubs: In 2024, the WheatCAP collaborated with the IWYP winter-hub at KSU and spring-hub at CIMMYT to introgress and evaluate alleles controlling grain yield components. Experiments to evaluate high biomass lines with introgressions of genes for increased spikelet number per spike, grain weight, or number of fertile tillers were performed in collaboration between CIMMYT and WheatCAP collaborators in CO, MT and WA. In the NIFA IWYP Winter Wheat Breeding Innovation (WWBI) Hub at KSU, donor germplasm for eight yield component genes were used to initiate introgressions into winter wheat cultivars. In 2024, BC4F1 populations were developed for introgression of Elf3 and Tagw2 gene alleles. The QTL affecting heading (Vrn-B1 and Ppd-A1a.1) and yield (1AL: 472.2-531.6 Mb) from AGS 2000 were introgressed into top winter wheat cultivars from KS, OK, TX and NE to develop BC3F1 and BC3F2. Individual breeding programs: Finally, the 19 individual breeding programs reported the release of 28 varieties and 5 germplasms and good progress in the implementation of high-throughput genotyping and phenotyping technologies in their respective breeding programs. The genotyping and phenotyping information reported above was used to implement genomic selection in the public wheat breeding programs. The integration of the WheatCAP graduate students into the wheat breeding program activities provided them hands-on experience on the different activities required for the release of commercial wheat varieties.
Publications
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
Zhang, J., G.F. Burguener, F. Paraiso, J. Dubcovsky. 2024. Natural alleles of LEAFY and WAPO1 interact to regulate spikelet number per spike in wheat. bioRxiv https://www.biorxiv.org/content/10.1101/2024.08.17.608376v1 (accepted in Theoretical and Applied Genetics).
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
Zhang, C., J. Hegarty, M. Padilla, D.M. Tricoli, J. Dubcovsky, Juan M. Debernardi. 2024. Manipulation of the microRNA172 - AP2L2 interaction provides precise control of wheat and triticale plant height. bioRxiv https://doi.org/10.1101/2024.08.05.606718. Accepted in Plant Biotechnology Journal.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
Rottersman, M.G., W. Zhang, J. Zhang, G. Grigorian, G.F. Burguener, Carter C., T. Vang, J. Hegarty, X. Zhang, and J. Dubcovsky. 2024. Deletion of wheat alpha-gliadins from chromosome 6D improves gluten strength and reduces immunodominant celiac disease epitopes. bioRxiv. https://doi.org/10.1101/2024.07.19.604379
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Paraiso F., H. Lin, C. Li, D.P. Woods, T. Lan, C. Tumelty, J.M. Debernardi, A. Joe, J. Dubcovsky. 2024. LEAFY and WAPO1 jointly regulate spikelet number per spike and floret development in wheat. Development 151:dev202803. https://doi.org/10.1242/dev.202803 (in bioRxiv previous report).
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Li, C., H. Lin, J.M. Debernardi, C. Zhang, and J. Dubcovsky. 2024. GIGANTEA accelerates wheat heading time through gene interactions converging on FLOWERING LOCUS T1. The Plant Journal. 118, 519533. https://doi.org/10.1111/tpj.16622
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Winn, Z.J., E. Hudson-Arns, M. Hammers, N. DeWitt, J. Lyerly, G. Bai, P. St. Amand, P. Nachappa, S. Haley, R.E. Mason. 2024. HaploCatcher: An R package for prediction of haplotypes. The Plant Genome 17:e20412. https://doi.org/10.1002/tpg2.20412 .
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Wondifraw, M., Z.J. Winn, S.D. Haley, J.A. Stromberger, E.E. Hudson-Arns, R.E. Mason. 2024. Advancing water absorption capacity in hard winter wheat using a multivariate genomic prediction approach. Crop Science In press: https://doi.org/10.1002/csc2.21321.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Wondifraw, M.A., Z.J. Winn, S.D. Haley, J.A. Stromberger, E.E., R.E. Mason (2024) Elucidation of the genetic architecture of water absorption capacity in hard winter wheat through genome wide association study. The Plant Genome 17:e20500. https://doi.org/10.1002/tpg2.20500.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Joshi P, G.S. Dhillon, Y. Gao, A. Kaur, J. Wheeler, and J. Chen. 2024. An optimal model to improve genomic prediction for protein content and test weight in a diverse spring wheat panel. Agriculture, 14:347. https://doi.org/10.3390/agriculture14030347.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Zhao, L., A. Bernardo, F. Kong, W. Zhao, Y. Dong, H. Lee, H.N. Trick, J. Rupp Noller, G Bai. 2024. A glutathione S-transferase from Thinopyrum ponticum confers Fhb7 resistance to Fusarium head blight in wheat. Phytopathology 114 (7): 1458-1461 https://doi.org/10.1094/PHYTO-03-24-0106-SC.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Kumar, P., H.S. Gill, M. Singh, K. Kaur, D. Koupal, S. Talukder, A. Bernardo, P. St Amand, G. Bai, S.K. Sehgal. 2024. Characterization of flag leaf morphology identifies a major genomic region controlling flag leaf angle in the US winter wheat (Triticum aestivum L.). Theor Appl Genet 137: 1-17 https://doi.org/10.1007/s00122-024-04701-1
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Zhao, L., Y. Lu, X. Zhang, W. Zhao, X. Xu, H. Wang, G. Zhang, A.K. Fritz, J. Fellers, M. Guttieri, K.W. Jordan, G. Bai. 2024. Characterization of quantitative trait loci for leaf rust resistance from CI 13227 in three winter wheat populations. Phytopathology (First Look). https://doi.org/10.1094/PHYTO-03-24-0108-R.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Kaushal, S., H.S. Gill, M.M. Billah, S.N. Khan, J. Halder, A. Bernardo, P.S. Amand, G. Bai, K. Glover, M. Maimaitijiang, S.K Sehgal. 2024. Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning. Front Plant Sci 15, 1410249. https://doi.org/10.3389/fpls.2024.1410249.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Coombes B, Lux T, Akhunov E, Hall A. Introgressions lead to reference bias in wheat RNA-Seq analysis. BMC Biology. 2024, 22:56 https://doi.org/10.1186/s12915-024-01853-w (in bioRxiv in previous report).
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Xu Y, Li Y, Bian R, Zhang G, Fritz AK, Dong Y, Zhao L, Xu Y, Ghori N, Bernardo A, Amand P, Rupp JLS, Bruce M, Wang W, Akhunov E, Carver B, Bai B. Genetic architecture of quantitative trait loci (QTL) for FHB resistance and agronomic traits in a hard winter wheat population. 2023. Crop Journal, 11:1836-1845. https://doi.org/10.1016/j.cj.2023.09.004 (accepted in previous report).
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Concepcion J.S., A.D. Noble, A.M. Thompson, Y. Dong, E.L. Olson. 2024. Genomic regions influencing the hyperspectral phenome of deoxynivalenol infected wheat. Sci Rep. 14: 19340. https://doi.org/10.1038/s41598-024-69830-5
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Anderson JA, Wiersma JJ, Reynolds SK, Conley EJ, Stuart N, Caspers R, Kolmer JA, Rouse MN, Jin Y, Dill-Macky R, Smith MJ, Dykes L (2024) Registration of 'MN-Torgy' spring wheat with moderate resistance to Fusarium head blight and adult plant resistance to Ug99 stem rust. Journal of Plant Registrations 18:122-133. https://doi.org/10.1002/plr2.20321
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Xu, Y., N. Ghori, S. Hussain, X. Xu, Z. Su, D. Zhang, L. Zhao, X. Liu, M.S. Chen, G.H. Bai. 2024. Evaluating a worldwide wheat collection for resistance to Hessian fly biotype Great Plains. Front Plant Sci 15, 1402218. https://doi.org/10.3389/fpls.2024.1402218
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Wang, W., Q. Pan, B. Tian, D. Davidson, G. Bai, A. Akhunova, H.N. Trick, E. Akhunov. 2024. Non-additive dosage-dependent effects of TaGS3 gene editing on grain size and weight in wheat. bioRxiv. https://doi.org/10.1101/2024.04.28.591550.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Rivera-Burgos L., C. VanGessel, M. Guedira, J. Smith, D. Marshall, Y. Jin, M. Rouse, G. Brown-Guedira. 2024. Fine mapping of stem rust resistance derived from soft red winter wheat cultivar AGS2000 to an NLR gene cluster on chromosome 6D. Theor Appl Genet 137:206. https://doi.org/10.1007/s00122-024-04702-0
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Li H., W. Men, C. Ma, Q. Liu, Z. Dong, X. Tian, C. Wang, C. Liu, H.S. Gill, P. Ma, Z. Zhang, B. Liu, Y. Zhao, S.K. Sehgal, W. Liu W. 2024. Wheat powdery mildew resistance gene Pm13 encodes a mixed lineage kinase domain-like protein. Nature Communications 15:2449 https://doi.org/10.1038/s41467-024-46814-7
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Zhang, F., H. Zhang, J. Liu, X. Ren, Y. Ding, F. Sun, Z. Zhu, X. He, Y. Zhou, G. Bai, Z. Ni, Q. Sun, Z Su. 2024. Fhb9, a major QTL for Fusarium head blight resistance improvement in wheat. J Integr Agric. https://doi.org/10.1016/j.jia.2024.03.045
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
Nyine M, Davidson D, Adhikari E, Clinesmith M, Wang H, Akhunova A, Fritz A, Akhunov E. Ecogeographic signals of local adaptation in a wild relative help to identify variants associated with improved wheat performance under drought stress. BioRxiv, 2024 doi: https://doi.org/10.1101/2024.03.20.585976 (accepted to Genome Biology).
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Thapa, S., H.S. Gill, J. Halder, A. Rana, S. Ali, M. Maimaitijiang, U. Gill, A. Bernardo, P. St. Amand, G. Bai, S.K Sehgal. 2024. Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blightrelated traits in winter wheat. The Plant Genome:e20470 https://doi.org/10.1002/tpg2.20470
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Zhao ,Y., Z. Dong, J. Miao, Q. Liu, C. Ma, X. Tian, J. He, H. Bi, W. Yao, T. Li, H. Gill, Z. Zhang, A. Cao, B. Liu, H. Li, S.K. Sehgal, W. Liu. 2024. Pm57 from Aegilops searsii encodes a tandem kinase protein and confers wheat powdery mildew resistance. Nature Communications 15:4796 https://doi.org/10.1038/s41467-024-49257-2
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Sangjan, W., A.H. Carter, M.O. Pumphrey, K. Hagemeyer, V. Jitkov, S. Sankaran. 2024 Effect of high-resolution satellite and UAV imagery plot pixel resolution in wheat crop yield prediction. Int J Remote Sens 45:1678-1698 https://doi.org/10.1080/01431161.2024.2313997
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Herr, A.W., P. Schmuker, A.H. Carter. 2024. Large-scale breeding applications of UAS enabled genomic prediction. Plant Phenome J 7:e20101 https://doi.org/10.1002/ppj2.20101
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Montesinos-Lopez, O.A., A.W. Herr, A. Montesinos-Lopez, J. Crossa, A.H. Carter. 2024. Enhancing winter wheat prediction with genomics, phenomics, and environmental data. BMC Genomics 25:544 https://doi.org/10.1186/s12864-024-10438-4
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Progress 01/01/23 to 12/31/23
Outputs
Target Audience:Audiences targeted by the research activities: 1) Wheat growers and wheat grower associations. WheatCAP breeding programs presented their results to state wheat commissions, grower associations and individual growers during field days and annual meetings. Wheat growers are direct beneficiaries of the new varieties developed by the WheatCAP researchers. 2) Wheat milling and baking industry.WheatCAP results were presented to the Wheat Quality Council and other Quality Collaborative Programs across the USA. Presentations were also made to individual milling and baking companies. 3) Scientist working in basic and applied aspects of wheat research. Results from the WheatCAP were presented to other researchers in 51 peer papers published in peer-reviewed journals. Presentations were made at national conferences including Plant and Animal Genome and ASA-CSSA meetings. A new database of 4.3 million mutations in the promoters of all the wheat genes and a new capture for wheat regulatory regions have been published and the wheat pangenome was expanded. 4) International wheat research community. WheatCAP researchers made presentations in different countries and published their results in internationally recognized scientific journals. WheatCAP participants sent improved wheat lines to the CIMMYT Hub in Mexico and the winter hub in Kansas. WheatCAP PIs, coPIs and students also made presentations at national and international meetings by ZOOM. 5) Wheat breeders in the public and private sectors. Varieties and germplasm generated by WheatCAP breeders have been made available to all members of the WheatCAP team and to public and private breeding programs that requested seeds for crossing. Markers for specific yield-enhancing genes are publicly accessible through the MASwheat website. TILLING mutants were distributed to wheat breeders and researchers in the US and abroad. All mutations are accessible and searchable in a public database and the seeds of the mutant lines are distributed without IP limitations. Audiences targeted by the educational activities: 1) Graduate and undergraduate students interested in plant breeding (including students outside the project). Education materials from the WheatCAP workshops have been uploaded into the WheatCAP website and are publicly available. 2) Educators interested in online tools for plant breeding and genetics. The results of educational surveys generated by WheatCAP are available through the WheatCAP website. 3) Breeding companies interested in the training of their workforce. There is a sustained demand for WheatCAP students from the private industry. 4) Wheat growers and grower organizations through field days and other venues conducted by participating breeders. In addition to information related to the new wheat varieties, WheatCAP coPIs educate growers, private breeders, and the seed industry about the opportunities and limitations of new technologies. This information has facilitated the wide acceptance of new marker and genomic technologies as well as the use of UAS for high throughput phenotyping. Changes/Problems:There have been no changes in the original objectives of the grant and no major changes in the budget: 1) $9000 were transferred from KS to TX to help the UAS-hub cover an unexpected cost for hosting the Oracle Cloud. 2) The supplies budget for UCD was reduced $3,969 for year 3 to accommodate the indirect rate adjustment at UCD. The Year 3 supplies total is $17,031 and is sufficient to cover all the planned activities at UCD. Change of PI at Texas A&M. Dr. Amir M. H. Ibrahim has been promoted to Texas A&M AgriLife Research associate director, chief scientific officer. In his new role he will provide leadership to Texas A&M College of Agriculture and Life Sciences. He will be replaced by Dr. Juan A. Landivar, from Texas A&M University, who is already listed as key personnel in the original WheatCAP grant application. Juan Landivar is a UAS high-throughput phenotyping (HTP) specialist and he was in charge of the UAS-HTP pipeline and image analyses from breeders, so he is very familiar with all the processes. Dr. Amir Ibrahim and Juan Landivar are overlapping during the months of November and December 2023 to facilitate the transition. Transfer of WheatCAP subaward from Utah State University to Oregon State University: Margaret Krause, the wheat breeder at Utah State University and coPI of the WheatCAP grant was recently hired as the new wheat breeder for Oregon State University. UC Davis will transfer the current subaward to Dr. Margaret Krause from Utah State University to Oregon State University starting from the start of the third year of the WheatCAP project (1/1/2024). The residual funding at Utah State University will remain there to continue paying WheatCAP graduate student Dalton Jones, who is expected to complete his MS by May 2024 at Utah State University, and then transfer to a PhD program at Oregon State University under the direction of Dr. Margret Krause. Dr. Paul Johnson at Utah State University will help Margaret Kraus to administer the residual WheatCAP funds for the completion of Dalton Jones graduation. Any residual funding after the graduation of Dalton Jones will be transferred to Margaret Krause at Oregon State University. What opportunities for training and professional development has the project provided?A central objective of the WheatCAP project is to train PhD students in modern plant breeding including both traditional field activities, modern high-throughput genotyping and phenotyping technologies and data analyses. By leveraging funds from participating universities, the WheatCAP project was able to invite students from universities not funded by the project to participate in the educational activities. During the second year of this grant, we trained 51 graduate students (including 10 that graduated in 2023), more than doubling the target of 20 students proposed in the original grant. The project held four workshops in 2023. The WheatCAP Student Workshop, was held in January at the Plant and Animal Genome conference (PAG). Twirty-two students met each other for the first time in-person and gave short presentations to introduce their research projects to the group. Students also attended the Annual WheatCAP Meeting at PAG and presented posters on their research projects after the meeting and discussed them with the WheatCAP CoPIs. The T3/Breedbase Online Workshop was held online over Zoom across four mornings in February. Between 12 and 17 students attended each day of the workshop, which covered information pertaining to the use of the of T3 and Breedbase, with the goal of increasing the number of trials uploaded to T3. Topics covered included databases, locations, accessions, field layouts, trait observations, lists, data aggregation, data sub-setting and downloading, accessing the PHG/Imputed data, use of the Android App "Field Book," seedlots, barcodes, and submission of genotyping data to T3. Each day of the workshop was recorded and both recordings and written instructions are available on the Plant Breeding Training Network. The UAS Workshop, was held in Amarillo, TX May 23rd-25th, 2023 and was attended by 25 WheatCAP students (1 as instructor). Students were provided with a manual to guide them in UAS data collection and analysis. The workshop covered how to plan a mission and prepare for a UAS flight followed by demonstration at the Conservation and Production Laboratory (Bushland, TX). The students learned how to complete all steps of data analysis from initial upload of UAS images to calculating vegetation indices. They attended a Small Grains Field Plot Tour at the Bushland field site and learned about analysis and interpretation of the UAS-generated data, focusing on practical applications in wheat breeding programs. The fourth workshop, the Genomic Selection Workshop, was held in Raleigh, NC July 21st - 23rd. A total of 23 graduate students and two Postdocs participated in the workshop. Topics covered included introductions to genotyping and data processing for genomic selection, mixed models, genomic prediction, breeding program design for genomic selection in wheat, and future directions in genomic selection. Students were led through many hands-on exercises using example datasets and R code, conducting imputation, cleaning and preparing phenotypic data, calculating BLUE values, and conducting genomic prediction. Four students gave presentations at the workshop on incorporating HTP and UAV data into predictions of genetic merit. Recordings from the workshop, datasets, and code are available on the Plant Breeding Training Network. In addition to the workshops, monthly meetings with invited speakers were held during the spring and fall semesters. Monthly meeting topics included wheat quality genes, data-driven participatory research in the Ethiopian wheat breeding program, physiological traits to breed for drought adaptation and climate resilience, and a panel with four wheat breeders. Recordings from monthly meetings were shared with students via email, or in the case of the breeders panel, on the Plant Breeding Training Network. Students connected with each other through Slack. Two student-writing groups met in both the spring and fall semester, each with 3-5 students. In the fall semester, one group was dedicated to students writing their thesis or dissertation. Students share written pieces and give each other feedback. Students have also taken on leadership roles, organizing a meeting, symposium, or workshop and a mentorship program is being set up. In addition to the graduate student educational activities, the public wheat breeding programs provided training opportunities for a large number of undergraduate students. The training of the undergrad students also provided the graduate students opportunities to learn mentorship skills. How have the results been disseminated to communities of interest?Results generated by WheatCAP researchers have been disseminated in multiple ways. First, results have been disseminated to the national and international research community in 51 peer-reviewed papers published in prestigious scientific journals including PNAS, Nature Communications, PLOS Genetics, etc. To measure the impact of the WheatCAP publications, we keep track of the number of cross-citations of papers published by each WheatCAP project acknowledging USDA-NIFA support.Even though this program started in 2022, the papers published by the WheatCAP in 2022 and 2023 have been already cross-cited 569 times in Google Scholar (12/8/2023, h index = 13). We also keep track of the impact of publications from the two previous WheatCAP: Publicationsfrom the TriticeaeCAP (2011-2016) were cross referenced 26,598 times (h index = 78) and those from the previous WheatCAP (2017-2021) 7,343 times (h index = 48). These numbers document the high-impact of the WheatCAP publications. Results have also been presented in person at multiple scientific meetings in the US including the ASA-CSSA meeting, the Plant and Animal Genome Conference, and remotely by Zoom. Marker assisted selection (MAS) protocols were distributed through the MASwheat website (http://maswheat.ucdavis.edu/). The WheatCAP coPIs also distribute their research results directly into seeds of adapted wheat germplasm carrying novel alleles or allele combinations. The 19 public WheatCAP breeding programs generate and share breeding lines and germplasm including different gene combinations, which can be used to tackle the different problems facing wheat production. More than 20,000 samples of seeds from the EMS sequenced mutant populations have been distributed worldwide in the last five years, documenting the impact of these resources. WheatCAP research results are also distributed as new DNA vectors. In 2023, the GRF4-GIF1 vectors for improved wheat transformation were distributed to 50 new laboratories. In total, Addgene has distributed 264 GRF4-GIF1 vectors to different research groups worldwide, documenting the interest in this technology. New genomic resources generated by WheatCAP have been widely advertised through the GrainGenes list server, conferences, student workshops, and computer demos. Resources have been made widely available to the international wheat research community. The more applied results have been communicated directly to the growers attending the field days hosted by the 19 WheatCAP breeding programs. Results have been also shared with the state wheat commissions and other wheat grower associations. Results affecting quality have been presented in the Wheat Quality Council and in quality collaborative programs organized in the different states. These meetings include breeders, handlers, millers, and bakers. Educational tools and online resources have been distributed throughthe project web site https://www.triticeaecap.org/educational-activities/ and are also available through the online the Plant Breeding Training Network. What do you plan to do during the next reporting period to accomplish the goals?Education priorities for year 3:Education priorities for 2024 include four workshops, a hybrid-breeding course, and continuing writing groups, the mentorship program, and monthly meetings. While scientific monthly meetings will continue, students will also help select topics related to soft-skills and/or career prep. The first workshop will be the 2024 WheatCAP Student Workshop at PAG-2024. The second workshop will focus on functional genomics and the genomics/genetics/cytogenetics of wild relative introgression breeding, hosted in-person by Dr. Eduard Akhunov at Kansas State University. The third workshop will focus on genomic and bioinformatic resources for wheat in the UK, hosted on-line by Dr. Cristobal Uauy and Designing Future Wheat. The fourth workshop will focus on strengths-based leadership for students in their 3rd or 4th year. Prior to this workshop, students will complete Clifton-Strengths 2.0, the strengths-based leadership assessment and conduct one-on-one debriefing with Loriana and Patrick Sekarski, who are Gallup Certified Strengths Coaches and soft skills experts. In the one-on-one debriefing, students will identify their strengths, how they currently use them in work/life, how to apply their strengths to achieve their professional goals, and how to manage their weaknesses. In the strengths-based leadership workshop, students will practice applying their strengths in team-building activities designed to develop their interpersonal communication and teamwork skills. Twenty-five students indicated they were interested in the Hybrid Breeding Strategies course hosted by UC-Davis Seed Biotechnology Center. WheatCAP education funds will be used to cover the registration costs for interested students. The course will supplement the students' training in breeding for self-pollinated species within the wheat breeding programs. During the third year, students will take more leadership roles: Two students are planning the WheatCAP Student Workshop (January 2024), one student is planning a monthly meeting (Spring 2024), and 14 students are planning a graduate student plant science symposium for January 2025. The students have set up Program, Finance, Communication, and Registration Committees and identified Symposium Chairs and a Secretary. A WheatCAP mentorship program is being set up. Twenty students filled out a mentee application designed to identify what they were hoping to gain from the program to best match them with potential mentors. Students are looking for someone to ask questions about their experiences in graduate school and/or work, network with, give advice on soft-skill development, and/or talk with about their own future career plans. Genomic Resources priorities Y3: In 2024, the KSU team will finalize annotation of 10 wheat reference genomes assembled using long-read sequencing technologies. This genomic resource will be used to characterize structural variation in wheat genome and to develop a pan-genome reference. This reference will be useful for the wheat PHG to improve accuracy and completeness of genotype imputation. The updated PHG will be used to impute deposited genotyping data in the T3 database. The sequencing and analysis of RNA-seq data for a diverse panel of 200 lines and eQTL mapping in multiple wheat tissues will be finalized in 2024. The genome sequence variation data generated for this panel will be deposited into the T3 database, together with the RNA-seq expression values for this panel and wheat wild relatives. The UCD group will focus on transferring the 9M EMS sequenced mutations mapped to CS into the recently published Kronos genome. T3/Breedbase priorities Y3: The two main priorities for 2024 includethe automation of genotype uploads and the improved handling and search features for Known Informative Markers (KIMs). The first objective will take advantage of T3 BrAPI compliance, which means that external servers and computer scripts can both download and upload data to T3.This feature has been key to the rapid incorporation of hundreds of thousands of phenotypic measurements from UAS hub. Getting to this level of automation required sustained effort and communication with the UAS hub, in the form of monthly meetings to discuss bottlenecks and tasks' specifications. In 2024, the T3 team proposes to engage in the same effort with the USDA Small Grains Genotyping Labs so that results from new genotyping assays will more rapidly be incorporated into T3. For the improved handling and search features for KIMs the data storage structure that T3 uses for KIMs will be improved (this storage structure was initially developed for morphological markers). This new structure will be used to upload KIM data on lines in T3 and to implement searches to identify lines in T3 with specified combinations of KIM alleles. Breeders will benefit from such queries for the selection of parental lines in their crossing blocks. UAS-hub priorities for Y3:The UAS-hub will continue enhancing the website by adding functionalities that will enable users to push phenotypic information to T3. Moreover, the UAS-hub will develop QGIS plugins to expedite the plot map creation process. Quality assurance and quality check pipelines will be developed to ensure the integrity of data uploaded to T3 from the UAS- hub, focusing on preventing missing and duplicate data. The ban of DJI platforms has impacted routine data collection in year 2. The UAS-hub team will elaborate a list of suggested platforms to standardize UAV data collection and ameliorate this problem as programs update their equipment, Genotyping labs priorities for Y3: In 2024, the genotyping labs will further optimize mid-density genotyping platforms for the wheat community. They will collaborate to select SNP targets that enhance the level of overlap between the USDA-SoyWheOatBar-3K Illumina Infinium II and the Thermo Fisher AgriSeq platform. Discussion with Thermo Fisher will focus on synthesis of new, improved AgriSeq primer pools for use by the US wheat breeding programs. To reduce per sample costs, we will explore the development of primer pools targeted to growing regions. Research will be done with breeding programs to evaluate use of data from the new platforms to impute markers. Accuracy of genomic selection using existing training sets genotyped using other technologies (ie. GBS) will be assessed. Efforts will be made to increase the Known Informative Marker (KIM) content in the mid-density marker sets based on new research results. The Genotyping labs will work to improve the performance of problematic KIMs. The labs will also continue development of KASP assays for traits of interest to breeding programs. Pipelines will be developed to automatically process AgriSeq data for upload to T3, generate MAS reports that provide predicted alleles of the well-performing KIMs, and check the concordance of biological replicates. The labs will collaborate with T3 to improve handling of genotyping data.
Impacts
What was accomplished under these goals?
WheatCAP overall productivity: During the 2nd year, WheatCAP breeders and researchers released 32 commercial varieties and five improved germplasms, and published 51 new peer-reviewed papers (https://www.triticeaecap.org/publications-and-germplasm/). Phenotypic data was collected from 247 flights using Unmanned Aerial Systems (UAS) over 37 acres, and genotypic data was collected from 17,815 samples. Approximately 75,000 plots from 249 field trials with phenotypic data were deposited in T3 in 2023. This information was used by public breeders to advance their lines and implement genomic selection in their breeding programs. The combined genotypic and phenotypic datasets provide a valuable resource to investigate the effects of different alleles and their epistatic interactions across environments and germplasm. Education: In 2023, the WheatCAP team trained 51 students, 10 of which graduated this year (44% of current students are female). Six of the WheatCAP current students are funded by other sources, but were able to participate in the educational activities by leveraging funds available at their respective universities. In addition to the WheatCAP students, the project provided training to six PhD students and two postdocs at the Genomic Selection Workshop. Students' personal profiles and projects as well as links to project meetings and educational resources are available at the WheatCAP web site (https://www.triticeaecap.org/educational-activities/). T3 database: In the second year of the project, the WheatCAP team made good progress in automation, data sharing, and communication between the UAS-hub and the T3/Wheat database. In this second year, uploads of phenotypic data have strongly picked up: a total of 329 new field phenotyping trials were uploaded, including 14,191 new accessions with phenotypes and 923,173 new phenotypic data points. T3 is compliant with the Breeders Application Program Interface (BrAPI) and this has enabled rapid deposit of image-derived traits to T3, and accelerated pulling and pushing data to T3 without human intervention. Extensive efforts from both the UAS-hub and T3 teams enabled this success. T3 has improved the use of barcode labels for breeding programs. It has also expanded the use of lists (to aggregate information) to the use of datasets, which aggregates multiple lists and facilitates the specification of complete analyses (improving reproducibility). T3 has begun to impute genotyping projects generated with Illumina 90K, 9K and GBS using the practical haplotype graph. T3 held a data upload workshop with WheatCAP graduate students from Feb. 6th to 9th 2023 to train them in data submission and T3 data analyses tools. Genomics resources: In 2023 WheatCAP published three papers describing a wheat promoter capture including 4.3 M induced mutations, a new regulatory assay including both promoter and open chromatin regions, and new ATAC-seq data, which was incorporated into the Genome Browser in GrainGenes. Four new complete wheat genomes have been assembled to expand the wheat Pangenome. The KSU team developed a pan-genome reference to be used in the proposed transcriptome study. A paper has been submitted to bioRxiv demonstrated that this expanded reference is critical to generate unbiased estimates of gene expression. A panel of 200 lines including wheat, wild relatives and synthetic lines has been assembled, and RNA sampling and library construction has been completed for seedling root and vegetative tissues at one week and crown with axillary tillers and roots at four weeks. The RNA-seq libraries have been submitted for sequencing. The sampling of tissues from additional eight stages of wheat development will be completed by the summer of 2024. The WheatCAP project has acquired exome capture data for additional 25 lines from the CIMMYT's HiBAP panel as recommended by the Scientific Advisory Board. The data was aligned to the wheat reference genome and diversity data has been incorporated into the wheat PHG. Genotyping laboratories: large numbers of samples were genotyped using non-targeted sequence-based approaches (GBS, MRASeq) as part ofongoing genomic selection and gene mapping efforts. This includes 11,351 samples processed in the regional genotyping labs, in addition to 12,274 samples processed in-house by several breeding programs. Mid-density genotyping platforms(Allegro, AgriSeq, Illumina 3K and GBMAS) were also implemented to genotype 10,151 samples in total. Regional genotyping labs supported breeding programs doing marker assisted selection by genotyping samples with known informative markers (KIMs) using KASP and STS assays. A total of 6,990 samples were submitted to the genotyping labs by WheatCAP breeding programs that were evaluated with 1 to 102 KASP or STS assays. Several genotyping platforms were compared for cost and umber of SNPs. Promising results were obtained using the Illumina Infinium II array developed by the Northern Genotyping lab that simultaneously targets 3,000 SNPs in each wheat, oat, and barley. Extensive validation indicated good technical performance and high concordance results with wheat data from other platforms. The Allegro platform targeting 3,680 loci produced good results when libraries were sequenced in pools of 768 (2,158 variants) than when the pools included,536 samples (1,621 variants MAF>0.05 and <20% missing data). The AgriSeq platform targeting 5000 loci developed as a collaboration between the Genotyping labs and Thermo Fisher generated 3,284 and 3,636 markers that passed the quality thresholds for the North and West panels respectively. UAS-Hub: In Year 2, the UAS-hub received raw UAS images from 142 flights coming from 15 wheat programs. The UAS team has completed data analyses for 88 flights and submitted the data back to the breeders. Orthomosaics and Digital Surface Models (DSMs) for feature extraction were completed for additional 54 flights. The UAS-hub accessed plot-level data uploaded to the T3 Database by the different breeding program using several breeding application programming interfaces (BrAPI) calls within a Python programming environment. This 'data pull' feature can retrieve plot map information from T3 and accommodate the diverse formats used by the different breeding programs. Additionally, The UAS-hub developed a pipeline for pushing phenotypic information back to T3. This pipeline is fully operational and has been successfully used to upload the 2022 phenotypic data to the T3/Breedbase database. The UAS-hub is currently working on pushing phenotypic information generated in 2023. IWYP winter and spring hubs: In 2023, the WheatCAP collaborated with the IWYP winter-hub at KSU and spring-hub at CIMMYT to introgress and evaluate alleles controlling grain yield components. The donor germplasm for seven yield component genes were provided by the WheatCAP to the WWBI hub for introgression into winter wheat cultivars. The Elf3 and Tagw2 genes were advanced to BC3F2, while TaGW7, TaGW2, TaCKX2-1, TaCKX2-2 and TaARF4 were advanced to BC2F. Four WheatCAP experiments were performed at CIMMYT, three at the common wheat spring-hub, and one in collaboration with the CIMMYT durum breeding program. Individual breeding programs:Finally, the 19 individual breeding programs reported the release of 32 varieties and 5 germplasms and good progress in the implementation of high-throughput genotyping and phenotyping technologies in their respective breeding programs. The genotyping and phenotyping information was used to implement genomic selection in the public wheat breeding programs. The integration of the WheatCAP graduate students into the wheat breeding program activities provided them hands-one experience on the different activities required for the release of commercial wheat varieties.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Yu S, Li M, Dubcovsky J, Tian L (2022). Mutant combinations of lycopene epsilon-cyclase and beta-carotene hydroxylase 2 homoeologs increased beta-carotene accumulation in endosperm of tetraploid wheat (Triticum turgidum L.) grains. Plant Biotech. J. 20:564576. https://doi.org/10.1111/pbi.13738
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Zhang J, Nirmala J, Chen S, Jost M, Steuernagel B, Karafiatova M, Hewitt T, Li H, Edae E, Sharma K, Hoxha S, Bhatt D, Antoniou-Kourounioti R, Dodds P, Wulff BBH, Dolezel J, Ayliffe M, Hiebert C, McIntosh R, Dubcovsky J, Zhang P, Rouse MN, Lagudah E (2023) Single amino acid change alters specificity of the multi-allelic wheat stem rust resistance locus SR9. Nature Communications 14:7354. https://doi.org/10.1038/s41467-023-42747-9
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Li H, Hua L, Zhao S, Hao M, Song R, Pang S, Liu Y, Chen H, Zhang W, Shen T, Gou J-Y, Mao H, Wang G, Hao X, J. L, Song B, C. L, Li Z, Wang Deng X, Dubcovsky J, Wang X, Chen S (2023) Cloning of the wheat leaf rust resistance gene Lr47 introgressed from Aegilops speltoides. Nature Communications:6072. https://doi.org/10.1038/s41467-023-41833-2
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Debernardi JM, Burguener G, Bubb K, Liu Q, Queitsch C, Dubcovsky J (2023) Optimization of ATAC-seq in wheat seedling roots using INTACT-isolated nuclei. BMC Plant Biology 23:270. https://doi.org/10.1186/s12870-023-04281-0
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Zhang J, Li C, Zhang W, Zhang X, Mo Y, Tranquilli GE, Vanzetti LS, Dubcovsky J (2023) Wheat plant height locus RHT25 encodes a PLATZ transcription factor that interacts with DELLA (RHT1). Proc. Natl. Acad. Sci. USA. 120:e2300203120. https://doi.org/10.1073/pnas.2300203120
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Boden SA, McIntosh RA, Uauy C, Krattinger SG, Dubcovsky J, Rogers WJ, Xia XC, Badaeva ED, Bentley AR, Brown-Guedira G, Caccamo M, Cattivelli L, Chhuneja P, Cockram J, Contreras-Moreira B, Dreisigacker S, Edwards D, Gonzalez FG, Guzman C, Ikeda TM, Karsai I, Nasuda S, Pozniak C, Prins R, Sen TZ, Silva P, Simkova H, Zhang Y, Wheat I (2023) Updated guidelines for gene nomenclature in wheat. Theor. Appl. Genet. 136:72 https://doi.org/10.1007/s00122-023-04253-w
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Alvarez MA., Li C, Lin H, Joe A, Padilla M, Woods DP, Dubcovsky J. (2023). EARLY FLOWERING 3 interactions with PHYTOCHROME B and PHOTOPERIOD1 are critical for the photoperiodic regulation of wheat heading time. PLoS Genetics 19:e1010655. https://doi.org/10.1371/journal.pgen.1010655
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Gabay G, Wang HC, Zhang JL, Moriconi JI, Burguener GF, Gualano LD, Howell T, Lukaszewski A, Staskawicz B, Cho MJ, Tanaka J, Fahima T, Ke HY, Dehesh K, Zhang GL, Gou JY, Hamberg M, Santa-Mar�a GE, Dubcovsky J (2023) Dosage differences in 12-OXOPHYTODIENOATE REDUCTASE genes modulate wheat primary root growth. Nature Communications 14:539. https://doi.org/10.1038/s41467-023-36248-y.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Chen Z, Debernardi JM, Dubcovsky J, Gallavotti A (2022). Recent advances in crop transformation technologies. Nature Plants. 8:13431351. https://doi.org/10.1038/s41477-022-01295-8
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Zhang J, Debernardi JM, Burguener GF, Choulet F, Paux E, O'Connor L, Enk J, Dubcovsky J (2023) A second generation capture panel for cost-effective sequencing of genome regulatory regions in wheat and relatives. The Plant Genome. 16:e20296 https://doi.org/10.1002/tpg2.20296
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Wong ML, Bruckner PL, Berg JE, Lamb PF, Hofland ML, Caron CG, Heo H-Y., Blake NK, Weaver DK, Cook JP (2023). Evaluation of wheat stem sawfly-resistant solid stem Qss.msub-3BL alleles in hard red winter wheat. Crop Science, 63:556567. https://doi.org/10.1002/csc2.20866
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Bian R, Liu N, Xu Y, Su Z, Chai L, Bernardo A, St. Amand P, Fritz A, Zhang G, Rupp J, Akhunov E, Jordan KW, Bai G (2023) Quantitative trait loci for rolled leaf in a wheat EMS mutant from Jagger. Theor Appl Genet 136(3):52. https://doi.org/10.1007/s00122-023-04284-3
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Chen J, Wheeler JJ, Marshall JM, Chen X, Windes S, Wilson C, Su M, Yimer B, Schroeder K, Jackson C (2023) Release of UI Gold hard white spring wheat. Journal of Plant Registrations. https://doi.org/10.1002/plr2.20309
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Crutcher FK, Lamb PF, Nash D, Fiedler JD, Eberly J, Kephart KD, McVay K, Torrion J, Beiermann CW, Vetch JM, Chen C, Holen D, Blake NK, Heo H-Y, Cook JP (2023) Registration of MT Sidney hard red spring wheat. Journal of Plant Registrations 17(2):368375. https://doi.org/10.1002/plr2.20268
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Dixon L, Bellinger B, Carter AH (2023) A gravimetric method to monitor transpiration under water stress conditions in wheat. The Plant Phenome Journal 6(1):e20078. https://doi.org/10.1002/ppj2.20078
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Dogan M, Wang Z, Cerit M, Valenzuela-Antelo JL, Dhakal S, Chu C, Xue Q, Ibrahim AMH, Rudd JC, Bernardo A, St. Amand P, Bai G, Zhang H, Liu S (2023) QTL analysis of yield and end-use quality traits in Texas Hard Red Winter Wheat. Agronomy 13(3):689. https://doi.org/10.3390/agronomy13030689
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Garst N, Belamkar V, Easterly A, Guttieri MJ, Stoll H, Ibrahim AMH, Baenziger PS (2023) Evaluation of pollination traits important for hybrid wheat development in Great Plains germplasm. Crop Science 63(3):11691182. https://doi.org/10.1002/csc2.20926
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Halder J, Gill HS, Zhang J, Altameemi R, Olson E, Turnipseed B, Sehgal SK (2023) Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat. The Plant Genome 16(1):e20300. https://doi.org/10.1002/tpg2.20300
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Hammers M, Winn ZJ, Ben-Hur A, Larkin D, Murry J, Mason RE (2023) Phenotyping and predicting wheat spike characteristics using image analysis and machine learning. The Plant Phenome Journal 6(1):e20087. https://doi.org/10.1002/ppj2.20087
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Herr AW, Adak A, Carroll ME, Elango D, Kar S, Li C, Jones SE, Carter AH, Murray SC, Paterson A, Sankaran S, Singh A, Singh AK (2023) Unoccupied aerial systems imagery for phenotyping in cotton, maize, soybean, and wheat breeding. Crop Science 63(4):17221749. https://doi.org/10.1002/csc2.21028
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Liu Z, Li Y, Bernardo A, Amand PSt, Zhang P, Sehgal S, Bai G (2023) Development of diagnostic SNP markers for identification of rye 1RS translocations in wheat. Crop Science 63(1):255265. https://doi.org/10.1002/csc2.20841
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Montesinos-L�pez OA, Herr AW, Crossa J, Carter AH (2023) Genomics combined with UAS data enhances prediction of grain yield in winter wheat. Frontiers in Genetics 14. https://doi.org/10.3389/fgene.2023.1124218
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Mustahsan W, Guttieri MJ, Bowden RL, Garland-Campbell K, Jordan K, Bai G, Zhang G (2023) Mapping the quantitative field resistance to stripe rust in a hard winter wheat population Overley � Overland. Crop Science 63(4):20502066. https://doi.org/10.1002/csc2.20977
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Gill HS, Brar N, Halder J, Hall C, Seabourn BW, Chen YR, St. Amand P, Bernardo A, Bai G, Glover K, Turnipseed B, Sehgal SK (2023) Multi-trait genomic selection improves the prediction accuracy of end-use quality traits in hard winter wheat. The Plant Genome:e20331. https://doi.org/10.1002/tpg2.20331
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Guttieri MJ, Bowden RL, Zhang G, Haley S, Frels K, Hein GL, Jordan KW (2023) Agronomic and quality impact of a shortened translocation for wheat streak mosaic virus resistance. Crop Science 63(2):622634. https://doi.org/10.1002/csc2.20876
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Peters Haugrud AR, Sharma JS, Zhang Q, Green AJ, Xu SS, Faris JD (2023) Identification of robust yield quantitative trait loci derived from cultivated emmer for durum wheat improvement. The Plant Genome:e20398. https://doi.org/10.1002/tpg2.20398
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Wang H, Bernardo A, St. Amand P, Bai G, Bowden RL, Guttieri MJ, Jordan KW (2023) Skim exome capture genotyping in wheat. The Plant Genome:e20381. https://doi.org/10.1002/tpg2.20381
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Winn ZJ, Amsberry AL, Haley SD, DeWitt ND, Mason RE (2023) Phenomic versus genomic prediction-A comparison of prediction accuracies for grain yield in hard winter wheat lines. The Plant Phenome Journal 6(1):e20084. https://doi.org/10.1002/ppj2.20084
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Winn ZJ, Larkin DL, Lozada DN, DeWitt N, Brown-Guedira G, Mason RE (2023) Multivariate genomic selection models improve prediction accuracy of agronomic traits in soft red winter wheat. Crop Science 63(4):21152130. https://doi.org/10.1002/csc2.20994
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Winn ZJ, Lyerly JH, Brown-Guedira G, Murphy JP, Mason RE (2023) Utilization of a publicly available diversity panel in genomic prediction of Fusarium head blight resistance traits in wheat. The Plant Genome 16(3):e20353. https://doi.org/10.1002/tpg2.20353
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Wu J, Jia H, Qiao L, Fu B, Brown-Guedira G, Nagarajan R, Yan L (2023) Genetic basis of resistance against powdery mildew in the wheat cultivar Tabasco . Mol Breeding 43(7):56. https://doi.org/10.1007/s11032-023-01402-3
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Xu Y, Li Y, Bian R, Zhang G, Fritz AK, Dong Y, Zhao L, Xu Y, Ghori N, Bernardo A, St. Amand P, Rupp JLS, Bruce M, Wang W, Akhunov E, Carver B, Bai G (2023) Genetic architecture of quantitative trait loci (QTL) for FHB resistance and agronomic traits in a hard winter wheat population. The Crop Journal. https://doi.org/10.1016/j.cj.2023.09.004
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Rebollo I, Aguilar I, P�rez de Vida F, Molina F, Guti�rrez L, Rosas JE (2023) Genotype by environment interaction characterization and its modeling with random regression to climatic variables in two rice breeding populations. Crop Science 63(4):22202240. https://doi.org/10.1002/csc2.21029
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Bhandari M, Chang A, Jung J, Ibrahim AM, Rudd JC, Baker S, Landivar J, Liu S, Landivar J (2023) Unmanned aerial system?based high?throughput phenotyping for plant breeding. The Plant Phenome Journal 6: e20058. https://doi.org/10.1002/ppj2.20058
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Rooney TE, Sweeney DW, Kunze KH, Sorrells ME, Walling JG (2023) Malting quality and preharvest sprouting traits are genetically correlated in spring malting barley. Theor Appl Genet 136(3):59. https://doi.org/10.1007/s00122-023-04257-6
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Jordan KW, Fernandez-de Soto M, Korol A, Akhunova A, Akhunov E (2023). Allelic variation in the wheat homolog of topoisomerase II is associated with crossover rate. BioRxiv, https://doi.org/10.1101/2023.07.06.548017
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Coombes B, Lux T, Akhunov E, Hall A. Introgressions lead to reference bias in wheat RNA-Seq analysis. BioRxiv, 2023, https://doi.org/10.1101/2023.10.04.560829
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Glenn P, Woods DP, Zhang J, Gabay G, Odle N, Dubcovsky J (2023) Wheat bZIPC1 interacts with FT2 and contributes to the regulation of spikelet number per spike. Theoretical and Applied Genetics 136:237. https://doi.org/10.1007/s00122-023-04484-x
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Zhang J, Xiong H, Burguener GF, Vasquez-Gross H, Liu Q, Debernardi JM, Akhunova A, Garland-Campbell K, Kianian SF, Brown-Guedira G, Pozniak C, Faris JD, Akhunov E, Dubcovsky J (2023) Sequencing 4.3 million mutations in wheat promoters to understand and modify gene expression. Proceedings of the National Academy USA 120:e2306494120. https://doi.org/10.1073/pnas.2306494120
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Bekkering CS, Yu S, Isaka NN, Sproul BW, Dubcovsky J, Tian L (2023) Genetic dissection of the roles of beta-hydroxylases in carotenoid metabolism, photosynthesis, and plant growth in tetraploid wheat (Triticum turgidum L.). Theor Appl Genet 136:8. https://doi.org/10.1007/s00122-023-04276-3
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Li H, Luo J, Zhang W, Hua L, Li K, Wang J, Xu B, Yang C, Wang G, Rouse MN, Dubcovsky J, Chen S (2023) High-resolution mapping of SrTm4, a recessive resistance gene to wheat stem rust. Theor. Appl. Genet. 136:120. https://doi.org/10.1007/s00122-023-04276-3
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
DeWitt N, Lyerly J, Guedira M, Holland JB, Murphy JP, Ward BP, Boyles RE, Mergoum M, Babar MA, Shakiba E, Sutton R, Ibrahim A, Tiwari V, Santantonio N, Van Sanford DA, Howell K, Smith JH, Harrison SA, Brown-Guedira G (2023) Bearded or smooth? Awns improve yield when wheat experiences heat stress during grain fill in the southeastern United States. Journal of Experimental Botany 74(21): 6749-6759.erad318. https://doi.org/10.1093/jxb/erad318
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Herr AW, Carter AH (2023) Remote sensing continuity: a comparison of HTP platforms and potential challenges with field applications. Frontiers in Plant Science 14:1233892. https://doi.org/10.3389/fpls.2023.1233892
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Kaur S, Gill HS, Breiland M, Kolmer JA, Gupta R, Sehgal SK, Gill U (2023) Identification of leaf rust resistance loci in a geographically diverse panel of wheat using genome-wide association analysis. Frontiers in Plant Science 14:1090163. https://doi.org/10.3389/fpls.2023.1090163
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Merrick LF, Herr AW, Sandhu KS, Lozada DN, Carter AH (2022) Optimizing plant breeding programs for genomic selection. Agronomy 12(3):714. https://doi.org/10.3390/agronomy12030714
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Merrick LF, Burke AB, Zhang Z, Carter AH (2022) Comparison of single-trait and multi-trait genome-wide association models and inclusion of correlated traits in the dissection of the genetic architecture of a complex trait in a breeding program. Frontiers in Plant Science 12:772907. https://doi.org/10.3389/fpls.2021.772907
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Merrick LF, Herr AW, Sandhu KS, Lozada DN, Carter AH (2022) Utilizing genomic selection for wheat population development and improvement. Agronomy 12(2):522. https://doi.org/10.3390/agronomy12020522
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Merrick LF, Lozada DN, Chen X, Carter AH (2022) Classification and regression models for genomic selection of skewed phenotypes: A case for disease resistance in winter wheat (Triticum aestivum L.). Frontiers in Genetics 13:835781. https://doi.org/10.3389/fgene.2022.835781
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Wold-McGimsey F, Krosch C, Alarc�n-Reverte R, Ravet K, Katz A, Stromberger J, Mason RE, Pearce S (2023) Multi-target genome editing reduces polyphenol oxidase activity in wheat (Triticum aestivum L.) grains. Frontiers in Plant Science 14: 1247680 https://doi.org/10.3389%2Ffpls.2023.1247680
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Cerit M, Wang Z, Dogan M, Yu S, Valenzuela-Antelo JL, Chu C, Wang S, Xue Q, Ibrahim AMH, Rudd JC, Metz R, Johnson CD, Liu S (2023) Mapping QTL for Yield and Its Component Traits Using Wheat (Triticum aestivum L.) RIL Mapping Population from TAM 113 x Gallagher. Agronomy 13:2402. https://doi.org/10.3390/agronomy13092402
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Wang Z, Dhakal S, Cerit M, Wang S, Rauf Y, Yu S, Maulana F, Huang W, Anderson JD, Ma X-F, Rudd JC, Ibrahim AMH, Xue Q, Hays DB, Bernardo A, St. Amand P, Bai G, Baker J, Baker S, Liu S (2022) QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster. Frontiers in Plant Science 1313:1057701. https://doi.org/10.3389/fpls.2022.1057701
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Progress 01/01/22 to 12/31/22
Outputs
Target Audience:Audiences targeted by the research activities: 1) Wheat growers and wheat grower associations. WheatCAP breeding programs presented their results to state wheat commissions, grower associations and individual growers during field days and annual meetings. Wheat growers are direct beneficiaries of the new varieties developed by the WheatCAP researchers. 2) Wheat milling and baking industry.WheatCAP results were presented to the Wheat Quality Council and other Quality Collaborative Programs across the USA. Presentations were also made to individual milling and baking companies. 3) Scientist working in basic and applied aspects of wheat research. Results from the WheatCAP were presented to other researchers in 47 peer papers published in peer-reviewed journals. Presentations were made at national conferences including Plant and Animal Genome and ASA-CSSA meetings. A new database of 4.3 million mutations in the promoters of all the wheat genes has been made available through GrainGenes and the Dubcovsky's Lab website. Vectors for the new GRF4-GIF1 wheat transformation technology were distributed through 'Addgene' to 214 laboratories in the USA and abroad. 4) International wheat research community. WheatCAP researchers made presentations in different countries and published their results in internationally recognized scientific journals. WheatCAP participants sent improved wheat lines to the CIMMYT Hub in Mexico. WheatCAP PIs, coPIs and students made presentations at international meetings by ZOOM and in person. 5) Wheat breeders in the public and private sectors. Varieties and germplasm generated by WheatCAP breeders have been made available to all members of the WheatCAP team and to public and private breeding programs that requested seeds for crossing. Markers for specific yield-enhancing genes are publicly accessible through the MASwheat website. TILLING mutants were distributed to wheat breeders and researchers in the US and abroad. All mutations are accessible and searchable in a public database and the seeds of the mutant lines are distributed without IP limitations. Audiences targeted by the educational activities: 1) Graduate and undergraduate students interested in plant breeding (including students outside the project). Education materials from the WheatCAP workshops have been uploaded into the WheatCAP website and are publicly available. 2) Educators interested in online tools for plant breeding and genetics. The results of educational surveys generated by WheatCAP are available through the WheatCAP website. 3) Breeding companies interested in the training of their workforce. 4) Wheat growers and grower organizations through field days and other venues conducted by participating breeders. In addition to information related to the new wheat varieties, we educate growers, private breeders, and the seed industry about the opportunities and limitations of new technologies. This information has facilitated the wide acceptance of new marker technologies. Changes/Problems:There have been no changes in the budgets or original objectives. The budget of USDA-ARS Ithaca will continue to be transferred to Cornell University to provide T3 with more hiring flexibility. The only change in personnel is in the educational coordinator. Amand Peters was selected for the Research Geneticist position at the USDA-ARS in Fargo in the Cereals Crops Research Unit. She will be replaced by Katherine Running, who is also from ND and participated in previous WheatCAP projects. She is already overlapping with Amanda to facilitate the transition and both will attend the WheatCAP student workshop in PAG in 2023. This change will not alter any of the Educational objectives and activities or the overall ND WheatCAP budget. However, to accommodate the different sources of funding for the educational coordinator, an internal redistribution of $37,698 from ORISE to ARS was implemented for the second year of the WheatCAP project. Besides this change, there are no other changes in the budget, objectives, or proposed activities in the WheatCAP proposal for the second year of the project. What opportunities for training and professional development has the project provided?A central objective of the WheatCAP project is to train PhD students in molecular plant breeding. By leveraging funds from participating universities, along with inviting students from universities not funded by the project (e.g. Purdue University, University of Maryland-College Park) to participate in educational activities, the WheatCAP have exceeded the proposed target of 20 students. During the first year of this grant we trained 49 graduate students, including 7 that started in the previous WheatCAP and graduated this year and 42 current students (Appendix 4). Of these students, 47% are female, indicating a good balance, in a profession that was previously male-dominated. All students were surveyed in September 2022 to assess their education level on topics related to plant breeding and to evaluate the needs for their research projects and for a future career in plant breeding. The 2022 annual survey results are posted on the WheatCAP website (https://www.triticeaecap.org/2022-graduate-student-suvey/). Annual surveys are being used to track WheatCAP student education progress. This information helps the educational team to design workshops and meetings targeted to the needs of the students. A 'slack' work page was created for WheatCAP students to connect and discuss their research projects. Monthly meetings over Zoom occurred in the spring and fall of 2022, with a break during the summer for the field season. Monthly meeting topics included an introduction to the grant objectives and scope and a workshop on the use of T3 and BreedBase provided by T3 personnel. During the fall, students participated in a workshop on Equity in Plant Breeding, which included a panel discussion including three breeders working for private companies. Bi-weekly writing groups discussing student writing (manuscripts and dissertations) were formed with 14 students currently participating. A full-day workshop is planned for this January at PAG where students will present and discuss their research projects. The WheatCAP leadership will attend the student workshop to provide advice on genomic resources and academic expertise available to the WheatCAP students. The educational activities included an update of the online education delivery platform Plant Breeding Training Network (PBTN) (https://passel2.unl.edu/view/community/b6721f4789d7). This included the identification and recovery of lost links and the update of out-of-date information. New lectures will be added on the areas in which students feel less confident based on the educational survey. These areas include genomics, selection theory and practice, methods for breeding in selfing and outcrossing systems, plant breeding strategies, genomic selection, and UAS-Hub data utilization. How have the results been disseminated to communities of interest?Results generated by WheatCAP researchers have been disseminated in multiple ways. First, results have been disseminated to the national and international research community in 47 peer-reviewed papers published in prestigious scientific journals including Science, Nature Communications, Genetics and PLOS Genetics. To measure the impact of the WheatCAP publications, we keep track of the number of cross-citations of papers published by each WheatCAP project acknowledging USDA-NIFA support. Since it is too early to measure the impact of the publications for this grant (year 1), we provide the impact from the two previous WheatCAP projects in Google Scholar (11/29/2022). Publications from the previous WheatCAP (2017-2021) have been cross-referenced 5,762 times (h index = 42) in spite of the short term since their publication; and those from the TriticeaeCAP (2011-2016) 24,194 times (h index = 75), documenting the high-impact of the WheatCAP publications. Results have also been presented at multiple scientific meetings in the US including the ASA-CSSA meeting, the American Society of Plant Biology (ASPB), and the Plant and Animal Genome Conference. The WheatCAP PDs and students presented multiple Zoom conferences remotely due to the pandemic. The WheatCAP PD made a zoom presentation to an audience of 12,000 researchers in China and recently received the Frank N. Meyer Award for the contribution of the WheatCAP to the National Plant Germplasm System, including the WheatCAP genotyping of the wheat and barely core collections. This genotypic information increased the value of the core collections and reached a very wide audience in the wheat and barley research and breeding communities. Marker assisted selection (MAS) protocols were distributed through the MASwheat website (http://maswheat.ucdavis.edu/), and the 15,000,000 sequenced mutations in all wheat genes and promoters were available at https://dubcovskylab.ucdavis.edu/wheat_blast and at GrainGenes and ENSEMBL. More than 10,000 seeds from these mutant lines have been distributed world-wide so far. The new vectors for improved wheat transformation using the GRF4-GIF1 technology published in Nature Biotechnology and reported by the WheatCAP are being distributed through 'Addgene'. Until November 2022, 'Addgene' has distributed the GRF4-GIF1 vectors to 214 different research groups. This is in addition to multiple distributions made directly from UCD. The vectors are distributed without restrictions for research but are licensed to companies for commercial purposes. Four companies have obtained licenses for these vectors documenting their value. New genomic resources generated by WheatCAP have been widely advertised through the GrainGenes list server, conferences, and computer demos. Resources have been made widely available to the international wheat research community. Results have been communicated directly to growers attending field days hosted by the 19 breeding programs that participate in WheatCAP. Results have been also shared with the state wheat commissions and other wheat grower associations. Results affecting quality have been presented in Wheat Quality Council and in the quality collaborative programs in different states. These meetings include breeders, handlers, millers, and bakers. Educational tools have been distributed throughonline resources and courses are accessible through PBTN. What do you plan to do during the next reporting period to accomplish the goals?Plans and priorities for the second year of the project Education: The educational priorities for 2023 include training on the utilization of T3/Breedbase database resources, on the standardization of data entry into the UAS-Hub, and on genomic selection. Online and in-person workshops focused on these topics will be held during the spring, summer, and fall of 2023. Monthly student meetings and writing groups will continue as during the first year. Topics for monthly meetings will include presentations and discussions with early-career public plant breeders and meetings with the directors of the different genotyping labs to discuss the specialized services offered by each lab. Additionally, one monthly meeting will include a Strengths-Based leadership training where students identify their leadership strengths and potential strategies to best use those strengths to be successful graduate students, researchers, and collaborators. Training on soft-skills valued by industry and internships will increase in the last years of the grant as the students get close to graduation. Genomic Resources: The panel of diverse lines including bread wheat, wild relatives and synthetic wheat will be assembled for sampling multiple tissues across different developmental stages. The genotyping of these lines will be performed using whole-genome low-pass sequencing to create a dense diversity map for downstream eQTL and trait mapping analyses. RNA-seq analyses of these samples will be performed to develop a more comprehensive tissue-specific eQTL map of wheat. This resource will be combined with the diversity datasets hosted by the T3 Breedbase. By combining eQTL maps with the phenotyping and genotyping data generated in the WheatCAP projects, we will improve our ability to interpret the functional significance of trait-associated SNPs and prioritize the best ones for developing new functional markers for MAS and genomic selection. The second version of the PHG will be integrated into the T3 Breedbase to improve the accuracy and coverage of genotype imputation. We will continue the expansion of the PHG using the PanGenome data by combining variant calling data generated by mapping the existing wheat NGS datasets to the expanded panel of wheat reference lines developed by WheatCAP and the wheat community. During the second year of the project we will complete the publications for the promoter sequencing of the Kronos EMS mutations (4.3 M mutations), the description of the new regulatory capture in collaboration with Arbor-Biosciences (submitted to The Plant Genome), and the INTACT-ATAC results for wheat roots. We will also continue the distribution of seeds of the sequenced EMS mutant lines and of the vectors for the GRF4-GIF1-CRISPR-Cas9 improved transformation in wheat. T3/Breedbase: During the second year, we will hire a postdoc to work with individual WheatCAP programs to develop genomic prediction models. As the pace of data upload continues to increase we will continue working with WheatCAP PIs to ensure proper data upload and curation. Some non-breeding trial data, such as the methylation sequences from the Akhunov lab and ATAC-Seq data from the Dubcovsky's lab, will also be uploaded. T3 has a good user interface for uploading trials and associated metadata, with functionality to improve data validity (e.g., avoiding breeding line name duplications in the system, ensuring valid plot coordinates, etc.). WheatCAP breeders will upload their trial metadata to T3 and their images to UAS-Hub. UAS-Hub will pull the trial field layout from T3, analyze the images, associate phenotypes (Level 2 data) with the plots, and push those phenotypes back to T3. Most components of this server-to-server connectivity are in place and during the second year we will ensure full functionality. Accidental mislabeling or switch errors could happen during the submission of samples to a genotyping lab. Industry reduces errors by extensive use of barcodes. In collaboration with the genotyping labs, we will continue developing processes whereby WheatCAP breeders design genotyping plates on T3, T3 creates the templates needed by the labs, templates are sent with the samples to the labs accompanied with barcodes, the labs generate the data and upload them, tagged by the barcodes back to T3. All samples then are accompanied point to point by digital identifiers, reducing mislabeling or switch errors. In Year 2, T3 will complete integration of the Practical Haplotype Graph version 2 (PHG2). There are two components to this integration: First, we will complete the software integration of the PHG2 into T3. PHG2 generates marker score calls in a different way and at a much higher density than standard genotyping platforms. Integrating the PHG2 so that its outputs are easily available through the same interface presents a challenge that will be tackled in Year 2. Second, we will work on improving imputation accuracy validation. Different wheat market classes (subpopulations) need to be validated for imputation accuracy independently. We will identify the per-market class validation sets to test the PHG2. These sets will allow us to swap in new PHG2 builds as they become available. We will also build out the spatial analysis capabilities of T3. Because of the use of UAS-Hub, trials now systematically have field layout data associated with them. This information can also be used for spatial analysis of the trials.Finally, we plan to provide a two to three-day workshop covering data upload and trial aggregation features of T3 in early spring 2023. UAS-Hub: To accelerate communication between the UAS-Hub and T3/Breedbase, we have already developed a feature to pull data from the T3 database using BrAPI and integrated this feature into the UAS-Hub. During the second year, we will focus on developing a feature to push extracted phenotypic features from the UAS-Hub back to T3/Breedbase. We will test this feature on a sandbox instance before streamlining it for automated data push from the UAS-Hub to T3. With the UAS-Hub platform equipped for full implementation, our team will continue its focus on the timely processing and delivery of processed data products and their upload into T3. During the second year, we will add canopy cover, height, volume, and vegetation indices to the outputs of the pipeline. Finally, we will develop new training modules and train graduate students on plot boundary delineation for feature extraction. An in-person workshop is being organized in Amarillo, TX for the WheatCAP students. Genotyping labs: During the second year of the WheatCAP, the four Regional Genotyping Labs will continue working on the development and testing of an AmpliSeq highly multiplexed PCR platform targeting 5,000 loci. Sequences flanking 1,500 exome capture SNPs from each wheat market class and even distribution throughout the genome have been already submitted to ThermoFisher (October, 2022) and the first design will be tested in 2023. ThermoFisher will synthesize the primer pool and validate the pool on 384 samples selected to represent US germplasm. The objective is to have a unified medium throughput genotyping platform available to the US wheat community for $10 per sample.
Impacts
What was accomplished under these goals?
WheatCAP overall productivity: During the 1st year, WheatCAP breeders have released 33 commercial varieties and 7 improved germplasm and published 47 peer-reviewed papers. Data was collected from 173 Unmanned Aerial Systems (UAS) flights over 23.8 acres and a total of 25,400 samples were sent for genotyping. Approximately 55,000 plots from 175 trials were entered in T3, with data already incorporated in 167 trials. This information was used by public breeders to advance their lines and implement genomic selection in their breeding programs. The combined genotypic and phenotypic datasets provide a valuable resource to investigate the effects of different alleles and their epistatic interactions across environments and germplasm. Education: By leveraging funds from participating universities, we were able to train almost twice as the students indicated in the proposal. This year 7 students completed their PhD and 42 participated in multiple educational activities organized by the project. Students' personal profiles and projects and links to the project meetings and educational resources are available at the WheatCAP web site (https://www.triticeaecap.org/). WheatCAP students have been recognized for their leadership and have been invited to make presentations in large meetings. A student survey was completed to establish a baseline and determine students' needs (https://www.triticeaecap.org/2022-graduate-student-suvey/). T3 database: The T3 team completed migrating all the data into the new Breedbase platform. A total of 281 new field phenotyping trials were uploaded, of which 167 have phenotypic data. This data includes 11,729 new accessions with phenotypes and 239,423 new phenotypic data points. To facilitate UAS data management, T3 improved features to upload, display, and operate on field layouts with different orders (e.g. serpentine or zigzag). T3 has also improved breeder functionality and developed genotyping plate sample tracking. T3 has expanded functionality to manage seedlots, including tracking seed origin, storage location, and transactions that change the amount of seed in the lot. T3 has implemented automated synonym searching to prevent the duplication of accessions with slightly different names. T3 is working on establishing a server-to-server communication between the Texas A&M UAS-Hub and T3. Currently, the UAS-Hub is able to download field layouts from T3 so that it can tie images submitted by users to specific plots. T3 is also working on the integration of the Practical Haplotype Graph (PHG) version 2 into T3. This new version has 472 wheat lines and represents a significant improvement over version 1. The outreach and educational activities of T3 included two online workshops on data upload and utilization for WheatCAP graduate students on April and November, 2022. In addition, T3 developed tutorial YouTube videos for training T3 users and students. Genomics resources: WheatCAP has provided access to sequenced mutant populations of tetraploid and hexaploid wheat including more than 10,000,000 mutations in the coding regions, 4.3 million sequenced mutations in the promoters of high-confidence genes (added in 2022). Results are available through GrainGenes. A new regulatory regions capture was developed in collaboration with Arbor BioSciences including promoter region for all wheat genes and additional 23.5 Mb of open chromatin detected by ATAC-seq from wheat leaf and root samples. The new design showed increased specificity and coverage of targeted sequences relative to the previous design. Gene expression variation: We completed the first study on the natural variation in gene expression in wheat based on RNA-seq data from 2-week-old seedlings of 198 diverse accessions and published the results. Developing multi-OMICs data: We used whole-genome methylation profiling of 96 hard red winter wheat lines from the US Great Plains that were also characterized for major agronomic traits in multi-year field trials. Second-generation Practical Haplotype Graph (PHG): The second-generation PHG was developed based on 472 lines from all over the US. It has >5 million SNPs and has been transferred to the T3 database to be used for imputation. Expanding the Wheat PanGenome: To improve the detection of genetic variants and the accuracy of imputation, we expanded the set of reference genomes by sequencing a set of six diverse wheat lines from a world-wide collection. This information will be valuable to update future versions of PHG. Wild relative introgressions: We characterized the wild-wheat introgression populations developed by crossing wheat with wild emmer wheat and Aegilops tauschii by deep sequencing of parental lines and low-pass sequencing of introgression lines. Genotyping laboratories: Large numbers of samples were evaluated with non-targeted genotyping by sequencing approaches (GBS, MRASeq) to support WheatCAP participants genomic selection and mapping efforts. This includes 9,856 samples processed in the regional genotyping labs, in addition to 8,779 samples processed by the breeding programs. In addition, regional genotyping labs provided support to the breeding programs through the evaluation of submitted materials with known informative markers (KIMs) using KASP and STS assays or with amplicon sequencing approaches (GBMAS). The genotyping lab at Fargo developed a new genotyping platform based on the Illumina Infinium II array technology that simultaneously targets approximately 3,000 SNPs in each wheat, oat, and barley. The Allegro platform was tested by the genotyping lab at Raleigh. Evaluation of 1,536 samples using a probe pool targeting 3,680 loci recovered data for 2,845 loci, leading to an 84% success rate in probe design for bi-allelic genome-wide markers. Together the four regional genotyping labs are collaborating in the development of an AmpliSeq highly multiplexed PCR platform targeting 5,000 loci. Sequences flanking 1,500 exome capture SNPs with high information content in each market class and even distribution across the genome have already been selected. UAS-Hub: 19 wheat breeding programs submitting data to the UAS-Hub and another four submitted their data directly to the T3/Breedbase database. Data was collected from 173 UAS flights over 23.8 acres. A survey conducted by the UAS-Hub revealed different levels of expertise and access to UAS resources among WheatCAP breeding programs. The Texas A&M/Purdue team dedicated more time to programs new to the UAS technology to help them identify the best platforms for their needs. The UAS-Hub made use of the breeding application programming interface (BrAPI) calls within the python environment and got the data of each plot uploaded by each breeding program directly from the T3 database. Spring and winter Hubs: Spring Hub: Five WheatCAP experiments were performed at the CIMMYT Spring-Hub. QTLs mapped and genes cloned in the previous WheatCAP by programs in CA, CO, MT and WA were introgressed into high-yield and high-biomass breeding lines and were evaluated in the CIMMYT spring wheat Hub in Obregon, Mexico. Winter Hub: Wheat CAP collaborated with the WWBI Hub on the introgression of alleles of genes controlling yield component traits.The donor germplasm of 8 genes identified in the WheatCAP projects have been provided to the WWBI Hub for introgression into 11 winter wheat cultivars. Incorporated genes include gw2, elf-Am3, and CRISPR-Cas9-edited alleles of TaGW7, TaGW2, TaCKX2-1, TaCKX2-2 and TaARF4 developed in collaboration with WheatCAP. Lines carrying these genes were used to generate BC1 or F1 crosses.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Alarc�n-Reverte R, Xie Y, Stromberger J, Cotter JD, Mason RE, Pearce S (2022) Induced mutations in ASPARAGINE SYNTHETASE-A2 reduce free asparagine concentration in the wheat grain. Crop Science 62:14841496. https://doi.org/10.1002/csc2.20760
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Baenziger PS, Frels KA, Boehm J, Belamkar V, Rose DJ, Xu L, Wegulo SN, Regassa T, Easterly AC, Creech CF, Santra DK, Klein RN, Jin Y, Kolmer J, Chen MS, Guttieri MJ, Bai G, El-Basyoni Salah I, Masterson SD, Poland J (2022) Registration of Epoch hard red winter wheat. Journal of Plant Registrations 16:613621. https://doi.org/10.1002/plr2.20247
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
DeWitt N, Guedira M, Murphy JP, Marshall D, Mergoum M, Maltecca C, Brown-Guedira G (2022) A network modeling approach provides insights into the environment-specific yield architecture of wheat. Genetics 221(3) iyac076. https://doi.org/10.1093/genetics/iyac076
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Fan M, Zhang X, Nagarajan R, Fan M, Zhang X, Nagarajan R, Zhai W, Rauf Y, Jia H, Ma Z, Yan LL (2022) Natural variants and editing events provide insights into routes for spike architecture modification in common wheat. The Crop Journal. https://doi.org/10.1016/j.cj.2022.04.009
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Gill HS, Halder J, Zhang J, Rana A, Kleinjan J, St. Amand P, Bernardo A, Bai G, Sehgal SK (2022) Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits. Theor Appl Genet 135:29532967. https://doi.org/10.1007/s00122-022-04160-6
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Glenn P, Zhang J, Brown-Guedira G, DeWitt N, Cook JP, Li K, Akhunov E, Dubcovsky J (2022) Identification and characterization of a natural polymorphism in FT-A2 associated with increased number of grains per spike in wheat. Theor Appl Genet 135:679-692. https://doi.org/10.1007/s00122-021-03992-y
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
He F, Wang W, Rutter WB, KW Jordan, Ren J, Taagen E, DeWitt N, Sehgal D, Sukumaran S, Dreisigacker S, Reynolds M, Liu S, Chen J, Fritz A, Cook J, Brown-Guedira G, Pumphrey M, Carter A, Sorrells M, Dubcovsky J, Hayden MJ, Akhunova A, Morrell PL, Szabo L, Rouse M, Akhunov E (2022) Genomic variants affecting homoeologous gene expression dosage contribute to agronomic trait variation in allopolyploid wheat. Nat Commun 13:826. https://doi.org/10.1038/s41467-022-28453-y
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Chen H, Su Z, Tian B, Liu Y, Pang Y, Kavetskyi V, Trick HN, Bai G (2022) Development and optimization of a Barley stripe mosaic virus-mediated gene editing system to improve Fusarium head blight resistance in wheat. Plant Biotechnology Journal 20:10181020. https://doi.org/10.1111/pbi.13819
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Chen H, Su Z, Tian B, Hao G, Trick HN, Bai G (2022) TaHRC suppresses the calcium-mediated immune response and triggers wheat Fusarium head blight susceptibility. Plant Physiology 190:15661569. https://doi.org/10.1093/plphys/kiac352
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Chen Y, Liu Y, Zhang J, Torrance A, Watanabe N, Adamski NM, Uauy C (2022) The Triticum ispahanicum elongated glume locus P2 maps to chromosome 6A and is associated with the ectopic expression of SVP-A1. Theor Appl Genet 135:23132331. https://doi.org/10.1007/s00122-022-04114-y
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Chu C, Wang S, Rudd JC, Ibrahim AMH, Xue Q, Devkota RN, Baker JA, Baker S, Simoneaux B, Opena G, Dong H, Liu X, Jessup KE, Chen MS, Hui K, Metz R, Johnson CD, Zhang ZS, Liu S (2022) A new strategy for using historical imbalanced yield data to conduct genome-wide association studies and develop genomic prediction models for wheat breeding. Mol Breeding 42:18. https://doi.org/10.1007/s11032-022-01287-8
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Dang C, Zhang J, Dubcovsky J (2022) High-resolution mapping of Yr78, an adult plant resistance gene to wheat stripe rust. The Plant Genome, 15: e20212. https://doi.org/10.1002/tpg2.20212 .
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Debernardi JM, Woods DP, Li K, Li C, Dubcovsky J (2022) MiR172-APETALA2-like genes integrate vernalization and plant age to control flowering time in wheat. PLoS Genetics, 18: e1010157. https://doi.org/10.1371/journal.pgen.1010157
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Jiang D, Hua L, Zhang C, Li H, Wang Z, Li J, Wang G, Song R, Shen T, Li H, Bai S, Liu Y, Wanga J, Li H, Dubcovsky J, Chen S 2022. Mutations in the miRNA165/166 binding site of the HB2 gene result in pleiotropic effects on morphological traits in wheat. The Crop Journal. Online first. https://doi.org/10.1016/j.cj.2022.05.002.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Peters Haugrud AR, Zhang Q, Green AJ, Xu SS, Faris JD (2022) Identification of stable QTL controlling multiple yield components in a durum � cultivated emmer wheat population under field and greenhouse conditions. G3 Genes|Genomes|Genetics jkac281. https://doi.org/10.1093/g3journal/jkac281
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Moriconi JI, Silva M, Zhang J, Tranquilli GE, Santa-Mar�a GE (2022) A genome-wide association study unveils key chromosome regions involved in determining sodium accumulation in wheat under conditions of low potassium supply. Journal of Plant Physiology 275:153739. https://doi.org/10.1016/j.jplph.2022.153739
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Kuzay S, Lin H, Li C, Chen S, Woods D, Zhang J, Dubcovsky J (2022) WAPO-A1 is the causal gene of the 7AL QTL for spikelet number per spike in wheat. PLOS Genetics 18:e1009747. https://doi.org/10.1371/journal.pgen.1009747
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Morales N, Ogbonna AC, Ellerbrock BJ, Bauchet GJ, Tantikanjana T, et al. (57 co-authors including Jean-Luc Jannink, Clay Birkett, and David Waring) 2022. Breedbase: a digital ecosystem for modern plant breeding. G3. https://doi.org/10.1093/g3journal/jkac078
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Li H, Zhang F, Zhao J, Bai G, St. Amand P, Bernardo A, Ni Z, Sun Q, Su Z (2022) Identification of a novel major QTL from Chinese wheat cultivar Ji5265 for Fusarium head blight resistance in greenhouse. Theor Appl Genet 135:18671877. https://doi.org/10.1007/s00122-022-04080-5
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Lopez SR, Wiersma AT, Strauss NM, Watkins T, Baik BK, Zhang G, Sehgal SK, Kolb FL, Poland JA, Mason RE, Carter AH, Olson EL (2022) Description of U6719-004 wheat germplasm with YrAS2388R stripe rust resistance introgression from Aegilops tauschii. Journal of Plant Registrations: https://doi.org/10.1002/plr2.20226
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Luo J, Rouse MN, Hua L, Li H, Li B, Li T, Zhang W, Gao C, Wang Y, Dubcovsky J, Chen S (2022). Identification and characterization of Sr22b, a new allele of the wheat stem rust resistance gene Sr22 effective against the Ug99 race group. Plant Biotechnology Journal. 20: 554563. https://doi.org/10.1111/pbi.13737.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Prather S, Schneider T, Gaham Godoy J, Odubiyi S, Bosque-Perez NA, Rashed A, Rynearson S, Pumphrey MO (2022) Reliable DNA Markers for a Previously Unidentified, Yet Broadly Deployed Hessian Fly Resistance Gene on Chromosome 6B in Pacific Northwest Spring Wheat Varieties. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.779096
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Rivera-Burgos LA, Brown-Guedira G, Johnson J, Mergoum M, Cowger, C (2022) Accounting for heading date gene effects allows detection of small-effect QTL associated with resistance to Septoria nodorum blotch in wheat. PloS one 17(5) e0268546.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Rooney TE, Kunze KH, Sorrells ME (2022) Genome-wide marker effect heterogeneity is associated with a large effect dormancy locus in winter malting barley. The Plant Genome:e20247. https://doi.org/10.1002/tpg2.20247
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Rooney TE, Sweeney DW, Sorrells ME (2022) Time series barley germination is predictable and associated with known seed dormancy loci. Crop Science 62:100119. https://doi.org/10.1002/csc2.20638
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Sandhu KS, Merrick LF, Sankaran S, Zhang Z, Carter AH (2022) Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs. Frontiers in Genetics 12. https://doi.org/10.3389/fgene.2021.829131
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Sandhu KS, Patil SS, Aoun M, Carter AH (2022) Multi-Trait Multi-Environment Genomic Prediction for End-Use Quality Traits in Winter Wheat. Frontiers in Genetics 13. https://doi.org/10.3389/fgene.2022.831020
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Sandro P, Kucek LK, Sorrells ME, Dawson JC, Gutierrez L (2022) Developing high-quality value-added cereals for organic systems in the US Upper Midwest: hard red winter wheat (Triticum aestivum L.) breeding. Theor Appl Genet. https://doi.org/10.1007/s00122-022-04112-0
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Sweeney DW, Kunze KH, Sorrells ME (2022) QTL x environment modeling of malting barley preharvest sprouting. Theor Appl Genet 135:217232. https://doi.org/10.1007/s00122-021-03961-5
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Sweeney DW, Rooney TE, Walling JG, Sorrells ME (2022) Interactions of the barley SD1 and SD2 seed dormancy loci influence preharvest sprouting, seed dormancy, and malting quality. Crop Science 62:120138. https://doi.org/10.1002/csc2.20641
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Taagen E, Jordan K, Akhunov E, Sorrells ME, Jannink JL (2022) If It Aint Broke, Dont Fix It: Evaluating the Effect of Increased Recombination on Response to Selection for Wheat Breeding. G3 Genes|Genomes|Genetics jkac291. https://doi.org/10.1093/g3journal/jkac291
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Venegas J, Guttieri MJ, Boehm Jr. JD, Graybosch R, Bai G, St. Amand PC, Palmer N, Hussain W, Blecha S, Baenziger PS (2022) Genetic architecture of the high-inorganic phosphate phenotype derived from a low-phytate mutant in winter wheat. Crop Science 62:12281241. https://doi.org/10.1002/csc2.20738
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Wu J, Qiao L, Liu Y, Fu B, Nagarajan R, Rauf Y, Jia H, Yan LL (2022) Rapid identification and deployment of major genes for flowering time and awn traits in common wheat. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.992811
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhang G, Martin TJ, Fritz AK, Li Y, Seabourn BW, Chen RY, Bai G, Bowden RL, Chen M-S, Rupp J, Jin Y, Chen X, Kolmer JA, Marshall DS (2022) Registration of KS Hamilton hard red winter wheat. Journal of Plant Registrations 16:7379. https://doi.org/10.1002/plr2.20190
- Type:
Book Chapters
Status:
Published
Year Published:
2022
Citation:
Zhang J (2022) Check CRISPR editing events in transgenic wheat with next-generation sequencing. In: Wani SH, Kumar A (eds) Genomics of Cereal Crops. Springer US, New York, NY, pp 95106
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhang J, Gill HS, Brar NK, Halder J, Ali S, Liu X, Bernardo A, St. Amand P, Bai G, Gill US, Turnipseed B, Sehgal SK (2022) Genomic prediction of Fusarium head blight resistance in early stages using advanced breeding lines in hard winter wheat. The Crop Journal. https://doi.org/10.1016/j.cj.2022.03.010
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhang J, Gill HS, Halder J, Brar NK, Ali S, Bernardo A, St. Amand P, Bai G, Turnipseed B, Sehgal SK (2022) Multi-locus genome-wide association studies to characterize Fusarium Head Blight (FHB) resistance in Hard Winter Wheat. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.946700
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhang L, Xu Y, Chen M-S, Su Z, Liu Y, Xu Y, La G, Bai G (2022) Identification of a major QTL for Hessian fly resistance in wheat cultivar Chokwang. The Crop Journal 10:775782. https://doi.org/10.1016/j.cj.2021.08.004
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhang XY, Jia HY, Li T, Wu JZ, Nagarajan R, Lei L, Powers C, Kan CC, Hua W, Liu ZY, Chen C, Carver BF, Yan LL (2022) TaCol-B5 modifies spike architecture and enhances grain yield in wheat. Science 376:180183. https://doi.org/10.1126/science.abm0717
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhao L, Ge W, Lyu Z, Xu S, Xu Y, Bernardo A, Zhang Q, Xu S, Wang H, Kong L, Bai G (2022) Development and validation of diagnostic markers for the wheat Fusarium head blight resistance gene Fhb7. Crop Science 62:19031911. https://doi.org/10.1002/csc2.20754
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Zhao L, Su P, Hou B, Wu H, Fan Y, Li W, Zhao J, Ge W, Xu S, Wu S, Ma X, Li A, Bai G, Wang H, Kong L (2022) The Black Necrotic Lesion Enhanced Fusarium graminearum Resistance in Wheat. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.926621
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