Source: AGRICULTURAL RESEARCH SERVICE submitted to NRP
GENOMIC SELECTION IS LOOMING: BUILDING A ROBUST GENOTYPE-TO-PHENOTYPE PLATFORM TO REVOLUTIONIZE PUBLIC COTTON BREEDING
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1028133
Grant No.
2022-67013-36440
Cumulative Award Amt.
$589,522.57
Proposal No.
2021-07681
Multistate No.
(N/A)
Project Start Date
Dec 15, 2021
Project End Date
Dec 14, 2026
Grant Year
2022
Program Code
[A1141]- Plant Health and Production and Plant Products: Plant Breeding for Agricultural Production
Recipient Organization
AGRICULTURAL RESEARCH SERVICE
141 EXPERIMENT STATION RD
STONEVILLE,MS 38776
Performing Department
Genomics and Bioinformatics
Non Technical Summary
Cotton is the number one value-added crop in the United States. Annual business revenue stimulated by the US cotton industry is well over $120 billion. Public-sector cotton breeders underlie the current and future success of US cotton production, with an ultimate goal to provide humans with the best feeling, most affordable natural textile products. While distinct cotton types are available for farmers that have either great fiber quality or high yield, there are no available cotton varieties that bear high amounts of extra high quality fibers. In light of a changing climate, increasing agricultural input costs, and a changing world marketplace, plant breeders need tools today to deliver solutions for tomorrow's problems. Public-sector cotton breeders have achieved success historically by using the conventional plant breeding practices: use a high-yield type plant as a parent and cross-pollinate with high-fiber quality types. By examining thousands of the offspring plants over a period of many years, cotton breeders observe the traits and select the best individuals to move forward. With enough time and resources, they are able to deliver incremental progress to farmers, benefitting the families and businesses that clothe America as well as consumers who love the natural feeling of cotton textiles.Recent scientific advances will enable cotton breeders to conceptually tie together cutting-edge biotechnology and genomics with the hands-on art of plant breeding. By using both the old and the new, breeders will be able to combine beneficial traits into a package that is usable by cotton farmers. However, adoption of these technologies has been slow, primarily due to a serious shortfall in our ability to link theory to practice. Although more and more genetic information is becoming available, public-sector cotton breeders still rely primarily on laborious, expensive methods to directly observe the traits on adult plants. Moreover, it is difficult for breeders to work together because they all collect and save their data in different ways. We aim to close these gaps. First, using the latest available DNA sequencing technology, we will develop an inexpensive system to do genetic testing on tens of thousands of plants. By aggregating the DNA information and field data in a standardized database system, we will help breeders adopt new ways to make their data portable, shareable, and directly comparable between breeding programs. With our new tools in hand, we will use a combination of agricultural experiments and computational predictions to test different ways of identifying the gems in a breeder's field. This approach eliminates the need to wait multiple generations before knowing which plant is best. This new system of selecting plants will be tested and applied in the Georgia and South Carolina cotton breeding programs, and then shared with all other cotton breeding programs. This project will bring the most technologically advanced methods to public cotton breeding, increasing operational efficiency, decreasing time needed to improve and develop new cultivars, and freeing up breeders to address new challenges facing the future of cotton production.
Animal Health Component
75%
Research Effort Categories
Basic
20%
Applied
75%
Developmental
5%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2011710108190%
2011711108110%
Knowledge Area
201 - Plant Genome, Genetics, and Genetic Mechanisms;

Subject Of Investigation
1711 - Long fiber cotton; 1710 - Upland cotton;

Field Of Science
1081 - Breeding;
Goals / Objectives
As genetic resources are developed, it becomes possible to revolutionize breeding methods using genetics as a way to more accurately calculate the potential of plants in a breeding program. Decades of research has built these genetic resources for upland cotton, a crop of worldwide importance with $123 billion yearly impact in the US, but technology for allowing application of these resources is needed. This effort lead by USDA-ARS, includes researchers at the University of Georgia and Washington State University, brings together a diverse group of breeders and informatics scientists to begin to enable genetic and phenotypic technology-directed breeding in public cotton breeding programs. We will do this through:Developing a standardized, publicly available, shared system to evaluate haplotypes via low-cost, high-throughput genotyping in cultivated upland cotton by synthesizing existing information regarding genetic diversity and trait architecture.Implementing a standardized phenotyping database and integrated informatics system that is breeder friendly for public cotton breeding programs.Initiating and testing genome-assisted selection in multiple public cotton breeding programs to develop published recommendations and online decision-support resources for public breeders to use immediately.This project will result in two cotton breeding programs using genomic selection and the needed resources for all other public breeding programs to begin using genomic selection. The results of genomic selection will have a profound effect on public cotton breeding programs and hopefully allow for replacing early generation field experiments, making faster genetic gain in fiber quality and development of better germplasm for stakeholders.
Project Methods
This project assembles the pieces of the genomic selection puzzle by leveraging research results from numerous previous projects, building an informatics system to combine genotype-to-phenotype data, and making selections based on genotypes reality for public cotton breeders.Objective 1 organizes the genetics side of the equation, first by identifying which genome regions are going to be most important for breeders to measure and then developing a truly cost-effective genotyping platform for use at breeding program scale.1.1. To gain a consensus view of chromosome segments important for fiber quality and yield traits, we will perform data mining of >100 previous QTL mapping and GWAS studies.1.2. Next, we will collate whole genome sequencing and other genotyping data from >2,900 individuals to identify conserved haplotype blocks across the cultivated germplasm.1.3. Lastly, we will run plant samples on each of four low-cost genotyping methods to test and evaluate performance (genome coverage and accuracy) for cotton breeding applications.This objective's success will be evaluated by completion of data generation, development of haplotyping strategy and new genotyping tool. As well as publication of data and accompanying methods.Objective 2 organizes the phenotypic side of the equation, making databases compatible with each other and giving breeders options for how to store and analyze their data.2.1. We will develop standardized phenotypic trait ontologies so databases can be initiated.2.2. CottonGen and Breeding Insight will be made to be fully cross-compatible.2.3. Breeders will be onboarded and set up for success in this digital, big data environment.This objective's outcomes will be evaluated by number of people trained and onboarded onto the digital system as well as responses from those stakeholders.Objective 3 puts these resources to the test, getting two breeding programs on their feet for directly testing and implementing genomic selection.3.1. We will assess the performance of various GS models for their applicability to important cotton fiber quality traits including fiber length, strength, micronaire, and uniformity, as well as yield parameters such as lint percent and boll weight. The prediction accuracy of the prediction models will be estimated using 300 selections culled at various stages (F3 to F6) in prior breeding cycles.3.2. Building on the breeders' existing infrastructure, we will carry forward a random subset of lines in parallel as a control against their normal phenotypic selections. We will develop a large dataset, including data from 2 breeding programs, that can be used for answering further practical and logistical questions. We will collect replicated field data across 6 location-x-year combinations of field trials (F5 and F6 years), including 4,320 plots with phenotypes assessed, plus 3,000 F3 plants with genotypes and phenotypes.3.3. Lastly, we will share the lessons learned from our experiment and provide recommendations that all breeders can apply to their own breeding situations.This objective's success will be evaluated by completion of field studies, movement of materials across breeding program stages, genotyping of all generations of breeding materials and evaluation of success of breeding using new methods. Success will include publication of downstream results and dissemination of theoretical results for impact of use in breeding.Overall project success will also be measured in the graduation of participating students.

Progress 12/15/23 to 12/14/24

Outputs
Target Audience: Right now, public cotton breeders must go in DNA-blind when trying to combine target traits from parental lines. Since most public-sector cotton breeders use the pedigree method to select parents for new crosses, crosses may wind up being far wider or narrower than anticipated, yielding unexpected results due to ancestral genetic drift. Choosing genetic markers is difficult since each individual marker is unlikely to be close to QTL underlying a trait of interest or to be segregating in a cross between two random individuals. There are innumerable considerations in planning a genotyping scheme and connecting this information back to program-specific or global haplotype blocks is infeasible for each individual breeder. Our team has developed genotyping systems for multiple crops and knows what it takes to make useful genomics tools. Breeders have identified a haplotype-based genotyping strategy as a top priority and agree that availability of such a system will greatly improve the reach of their programs. Research has been communicated with public cotton researchers at multiple venues during the project reporting period, including through dissemination of the CottonGen database. Research has also been communicated with cotton stakeholders, Cotton Incorporated. Changes/Problems: Hurricane Helene affected the field trials in Tifton, GA, upon landfall September 27, 2024. Plots were unevenly affected by wind damage, reducing the reliability of plot yield measurements. As a result, a subset of lines that were most severely affected by wind damage may be re-planted in field season 2025 for additional data collection focussed on high-throughput phenotyping method development. What opportunities for training and professional development has the project provided? Both graduate students attended the National Association of Plant Breeding conference in St. Louis, MO and participated in professional development training. One student attended the Cotton Beltwide Conference in Fort Worth, TX. Graduate student (Sam Wan) obtained leadership experience by managing the maintenance and harvesting of last year of field trials at the GA location. Outreach activities include 1 peer-reviewed publication, two training workshops at two conferences: "Database Resources for Crop Genomics, Genetics and Breeding Workshop" at the Plant and Animal genome Conference (January, 2024) , and a "Breeding Tools Workshop" at the National Association for Plant Breeding Annual Meeting (July, 2024), delivery of 4 newsletters, 7 video tutorials on how to use specific data and tools. How have the results been disseminated to communities of interest? PI Hulse-Kemp, and Co-PIs Chee and Campbell, attended the Cotton Breeders Meeting at Cotton Incorporated, Cary, NC, to interact with the cotton breeding and genetics community. PI Hulse-Kemp gave an invited presentation related to genomic selection at the meeting. CottonGen circulated a year in review flyer, gave ten oral presentations at 4 confereces (PAG, January 2024; Cotton Beltwide, January 2024, Annual Plant Biology Conference, June 2024; World Cotton Research Conference, October 2024) and one poster presentation, and a BIMS webinar. In this reporting period, CottonGen was cited in 126 peer-reviewed publications, had 54K users, 97K visits with 1.1M pages accessed (twice numbers of last reporting period). What do you plan to do during the next reporting period to accomplish the goals? Complete genotyping and cluster file development for automated genotyping of CottonSNP27K array. Complete whole genome sequencing on the 4 remaining parental lines from the Georgia breeding program. In the next reporting period we plan to (1) Continue to add high-quality cotton genomics, genetics, breeding data; (2) Continue to improve or add new functionality to CottonGen and BIMS as needed by the cotton research and breeding community; (3) Provide in-person and virtual training to public cotton breeders and researchers to promote efficient use of CottonGen for discovery and decision-making; and (4) continue to collaborate to ensure an efficient and seamless system to incorporate and promote cotton micropublications in CottonGen.

Impacts
What was accomplished under these goals? The new CottonSNP27K has been manufactured and provided to service providers to initiate development of automated clustering file. Initial samples for the 27K SNP array were successfully processed at Texas A&M University. Coordinated submission of additional samples from national and international cotton community members. Completed PacBio HiFi sequencing and draft (contig) genome assembly on 29 parental lines for the SC and GA breeding programs. Conducted final year (F6 - GA program) and second-to-last year (SC program) of field trials. Major data added to CottonGen included 25 genomes, 1,829,867 genes, 88 germplasm, 10 genetic maps; 16,856 markers; 4514 GWAS; 385,135 phenotypes and 558 QTLS.. Continued to add CottonGen generated gene function and synteny analysis and added five Cyc pathway database, gene annotation data from Gene microPublication biology, updated the US State Cotton Variety Test Results and updated the USDA ARS National Cotton Germplasm Characterization. New functionality in CottonGen included the addition of (1) Protein sequences searchable, (2) Hosting Public Phenotype and Genotype Data in BIMS - Enabled functionality for program owners to make their private data public, added URL links to BIMS pages, including Program, Trial, and Stock pages, and enabled functionality for public users to download all phenotype data for a specific trial, (3) Importing Data from BreedBase to BIMS - Using BrAPI - Matched BrAPI specifications between BreedBase and BIMS to enable data transfer, and built functionality in BIMS for users to view the list of studies available in BreedBase for import.

Publications

  • Type: Peer Reviewed Journal Articles Status: Published Year Published: 2024 Citation: Graffam, D., Cutlan, M., Storm, A.R., Hulse-Kemp, A.M., and Stoeckman, A.K.. Gossypium hirsutum gene of unknown function Gohir.A02G161000 encodes a potential transmembrane Root UVB Sensitive 4 Protein with a putative protein-protein interaction interface. Micropublication Biology. (2024). doi: 10.17912/micropub.biology.000869.
  • Type: Peer Reviewed Journal Articles Status: Published Year Published: 2024 Citation: Hernandez, G., Hulse-Kemp, A.M., and Storm, A.R.. Gossypium hirsutum gene of unknown function Gohir.A02G131900 encodes a potential plant-specific, dual-domain exo-1,3-?-glucosidase. Micropublication Biology. (2024). doi: 10.17912/micropub.biology.000868.
  • Type: Peer Reviewed Journal Articles Status: Published Year Published: 2024 Citation: Jung, S., Cheng, C. H., Lee, T., Buble, K., Humann, J., Zheng, P., ... & Main, D. (2024). Building resource-efficient community databases using open-source software. Database, 2025, baaf005. https://doi.org/10.1093/database/baaf005


Progress 12/15/22 to 12/14/23

Outputs
Target Audience:Right now, public cotton breeders must go in DNA-blind when trying to combine target traits from parental lines. Since most public-sector cotton breeders use the pedigree method to select parents for new crosses, crosses may wind up being far wider or narrower than anticipated, yielding unexpected results due to ancestral genetic drift. Choosing genetic markers is difficult since each individual marker is unlikely to be close to QTL underlying a trait of interest or to be segregating in a cross between two random individuals. There are innumerable considerations in planning a genotyping scheme and connecting this information back to program-specific or global haplotype blocks is infeasible for each individual breeder. Our team has developed genotyping systems for multiple crops and knows what it takes to make useful genomics tools. Breeders have identified a haplotype-based genotyping strategy as a top priority and agree that availability of such a system will greatly improve the reach of their programs.Research has been communicated with public cotton researchers at multiple venues during the project reporting period, including through dissemination of CottonGen database. Research has also been communicated with cotton stakeholders, Cotton Incorporated. Changes/Problems: The CottonSNP11K (now CottonSNP18K) that was initially tested, required a round of technical improvement before being able to genotype additional materials. This round of technical improvement is near complete and will enable downstream genotyping of the remaining F3 individuals in 2024. We consulted with multiple other cotton breeding and genetics groups on navigating choices in genotyping technology for cotton, which is a continual process. The knowledge gained in this project is already being shared with relevant community stakeholders. It is likely the work proposed in UGA breeding program will be shifted towards support of the graduate student that is working on the project. What opportunities for training and professional development has the project provided? Both graduate student's attended the Plant and Animal Genome conference and participated in multiple workshops. Both graduate students attended the National Association of Plant Breeding conference in Greenville, SC, and participated in professional development training. Outreach activities included three workshops at two conferences: "Database Resources for Crop Genomics, Genetics and Breeding Workshop" and "Lessons Learned While Integrating New Tools into Breeding Programs" at the Plant and Animal genome Conference (January, 2023) , and a "Breeding Tools Workshop" at the National Association of Plant Breeding Annual Meeting (July, 2023). How have the results been disseminated to communities of interest? Both graduate students were invited to give talks at the International Cotton Genome Initiative workshop at PAG. A graduate student presented at the NCSU Graduate Student Research Symposium and won 2nd place in the Life Sciences division. A graduate student presented at the National Association of Plant Breeders Annual Meeting. In relation to CottonGen efforts, 4 newsletters were delivered, 7 video tutorials on how to use specific data and tools, a year in review flyer, 2 poster presentations, and a BIMS webinar. In this reporting period, CottonGen was cited in 128 peer-reviewed publications, had 27K users, 63K visits with 657K pages accessed. It was cited in. Since its inception in 2012, CottonGen has now been cited in 958 publications, with 18,975 secondary citations. What do you plan to do during the next reporting period to accomplish the goals? In the next reporting period we plan to (1) Continue to add high-quality cotton genomics, genetics, breeding data; (2) Continue to improve or add new functionality to CottonGen as needed by the cotton research community. This will include better connection of BIMS to other BrAPI compliant breeding resources and tools; (3) Provide in-person and virtual training to public cotton breeders and researchers to promote efficient use of CottonGen for discovery and decision-making; and (4) continue to collaborate to ensure an efficient and seamless system to incorporate and promote cotton micropublications in CottonGen; (5) Complete work to allow USDA ARS cotton breeders to easy transfer their phenotypic and genotypic data from Breeding Insight to BIMS, thus enabling them to be compliant with public data requirements. Complete further technical evaluation of the new SNP arrays (30K and 11K). Submit additional F3 breeding samples for genotyping using the selected technology. Test imputation software within- and between-breeding programs to improve the number and accuracy of molecular marker data.

Impacts
What was accomplished under these goals? Leaf samples from 1,551 F3 plants have been collected from the USDA-SC breeding program. Collected lint percent and HVI fiber quality data on 1,551 F3 plants from the USDA-SC breeding program. The final design for the 30K SNP array design was submitted for production. Community members contributed 100+ markers associated with fiber and plant health traits, and they were incorporated into the probe set (pending validation). Major data added to CottonGen included 14 genomes, 691,522 genes, 175 germplasm, 1 genetic map, 26,424 markers, 181,500 genotypes, 26,428 phenotypes and 330 QTLS. Added new data types to CottonGen, including 4,122 GWAS and expression data for 67,721 genes from 5 publications. Continued to add gene annotation data from Gene microPublication biology, and updated the US State Cotton Variety Test Results, and the UZ and CN germplasm evaluation data. New functionality implemented in the CottonGen included the addition of (1) an ortholog page in the gene/mRNA page, (2) New Trait page and 'Search Trait', (3) Tripal Loaders for gene expression added, (4) Updating MegaSearch to include GWAS search, (5) New data templates were created for GWAS data submission, (6) Updated MapViewer to display GWAS data, (7) Image upload added to the Breeding Information Management system, (8) Collaboration initiated with Breeding Insight OnRamp to allow USDA ARS breeders breeding data to be made publicly available through BIMS, and the CottonGen database server systems were upgraded to Ubuntu 20.04, Drupal 7.95, PHP 8.1.18, postgres 12

Publications

  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Schoonmaker, A.N., Hulse-Kemp, A.M., Youngblood, R.C., Rahmat, Z., Atif Iqbal, M., Rahman, M.U., Kochan, K.J., Scheffler, B.E. and Scheffler, J.A.. Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping. Plants, 12(5), p.1153. (2023).
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Zirkel, J., Hulse-Kemp, A.M. and Storm, A.R.. Gossypium hirsutum gene of unknown function, Gohir. A02G039501. 1, encodes a potential DNA-binding ALOG protein involved in gene regulation. Micropublication Biology. (2023).
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Osborne, A.N., Osagiede, A., Storm, A.R., Hulse-Kemp, A.M. and Stoeckman, A.K.. Gossypium hirsutum gene of unknown function Gohir. A03G0737001 encodes a potential Chaperone-like Protein of protochlorophyllide oxidoreductase (CPP1). microPublication Biology. (2023).
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Smith, E.R., Caulley, L.R., Storm, A.R., Hulse-Kemp, A.M. and Stoeckman, A.K.. Gossypium hirsutum gene of unknown function Gohir. A03G007700. 1 encodes a potential VAN3-binding protein with a phosphoinositide-binding site. Micropublication Biology. (2023).
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: M Deng, C. H., Naithani, S., Kumari, S., Cobo-Sim�n, I., Quezada-Rodr�guez, E. H., Skrabisova, M., ... & Jung, S. (2023). Genotype and phenotype data standardization, utilization, and integration in the big data era for agricultural sciences. Database, 2023, baad088.https://doi.org/10.1093/database/baad088
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Clarke, J. L., Cooper, L. D., Poelchau, M. F., Berardini, T. Z., Elser, J., Farmer, A. D., ... & Sen, T. Z. (2023). Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium. Database, 2023, baad076. https://doi.org/10.1093/database/baad076
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Yu J, Jung S, Cheng CH, Lee T, Zheng P, Buble K,. & Main D. 2023. CottonGen: Updates to the Cotton Community Database for Genomics, Genetics and Breeding Research. Cotton Beltwide Conference, January 10-12, 2023, New Orleans, USA. Poster Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Yu J, Jung S, Cheng CH, Lee T, Zheng P, Buble K,. & Main D. 2023. CottonGen: Updates to the Cotton Community Database for Genomics, Genetics and Breeding Research. Plant and Animal Genome Conference, January 13-18, 2023, San Diego, USA. Poster Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Humann J, Jung S, Lee T, Cheng CH, Zheng P, Buble K,. & Main D. 2023. Updates on Genomic Data and Tools in Rosaceae, Cotton, Citrus, Vaccinium and Pulse Crop Databases. Plant and Animal Genome Conference, January 13-18, 2023, San Diego, USA. Oral Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Bassil N, Jung S, Cheng CH, Lee T, Yu J, Humann J,. & Main D. 2023. Updates on Germplasm and Diversity Data and Tools in Rosaceae, Cotton, Citrus, Vaccinium and Pulse Crop Databases. Plant and Animal Genome Conference, January 13-18, 2023, San Diego, USA. Oral Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Jung S, Buble K, Cheng CH, Lee T, Yu J, Humann J,. & Main D. 2023. Updates on Genetics Data and Tools in Rosaceae, Cotton, Citrus, Vaccinium and Pulse Crop Databases. Plant and Animal Genome Conference, January 13-18, 2023, San Diego, USA. Oral Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Jung S, Lee T, Gasic K, and Main D. 2023. Breeding Information Management System Demonstration. Breeding Tools Workshop part 1. NAPB 2023 Annual Meeting, July 16-August 20, 2023, Greenville, SC, USA. Oral Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Jung S, Lee T, Gasic K, and Main D. 2023. Breeding Information Management System Hands on Training and Discussion. Breeding Tools Workshop part 2. NAPB 2023 Annual Meeting, July 16-August 20, 2023, Greenville, SC, USA. Oral Presentation.
  • Type: Other Status: Published Year Published: 2023 Citation: CottonGen Brochure. 2023. Cotton Beltwide Conference, January 10-12, 2023, New Orleans, USA.
  • Type: Other Status: Published Year Published: 2023 Citation: Breeding Information Management Brochure. 2023. Cotton Beltwide Conference, January 10-12, 2023, New Orleans, USA.
  • Type: Other Status: Published Year Published: 2023 Citation: CottonGen Brochure, 2023. Plant and Animal Genome Conference AgBioData Booth, January 13-18, 2023, San Diego, USA.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Naithani S, Deng C, Kumari S, Cobo-Simon I, Quezada EH, Skrabisova M, Gladman N, Correll M, Sikiru A, Afuwape O, Rebollo I, Zhang W, and Jung S. Challenges and Opportunities in Connecting Genotype Data to Phenotype Data, International Plant & Animal Genome Conference 30, Jan. 13-18, 2023.
  • Type: Other Status: Published Year Published: 2023 Citation: Breeding Information Management Brochure. 2023. Plant and Animal Genome Conference AgBioData Booth, January 13-18, 2023, San Diego, USA
  • Type: Other Status: Published Year Published: 2023 Citation: Breeding Information Management Brochure. 2023. NAPB 2023 Annual Meeting, July 16-August 20, 2023, Greenville, SC, USA.
  • Type: Other Status: Published Year Published: 2023 Citation: CottonGen Brochure. 2023. NAPB 2023 Annual Meeting, July 16-August 20, 2023, Greenville, SC, USA.
  • Type: Other Status: Published Year Published: 2023 Citation: CottonGen (www.cottongen.org) - Database
  • Type: Other Status: Published Year Published: 2023 Citation: 4 CottonGen Newsletters - Describing new data, tools, and cotton community news.
  • Type: Websites Status: Published Year Published: 2023 Citation: How to Overlay Omics Data in PathwayCyc video tutorial - https://www.youtube.com/watch?v=qhSTmzBZCLQ
  • Type: Websites Status: Published Year Published: 2023 Citation: How to search markers using MegaSearch video tutorial - https://us20.campaign-archive.com/?u=0c70f89852999c0ed137acc7d&id=a2a286cfb9
  • Type: Websites Status: Published Year Published: 2023 Citation: How to view genomes linked to genetic maps video tutorial - https://www.youtube.com/watch?v=dFMn9g5NsTw
  • Type: Websites Status: Published Year Published: 2023 Citation: How to Use MegaSearch for Genes and Transcripts video tutorial - https://www.youtube.com/watch?v=Ia3v650TZAg
  • Type: Websites Status: Published Year Published: 2023 Citation: How to search traits and see all the linked data video tutorial - https://www.youtube.com/watch?v=nKo8c7s5pHc
  • Type: Websites Status: Published Year Published: 2023 Citation: How to Search and View GWAS data video tutorial - https://www.youtube.com/watch?v=jz-8ePzuiTI
  • Type: Websites Status: Published Year Published: 2023 Citation: CottonGen in Review 2022 - Email with links to new data, tools, outreach information. - https://mailchi.mp/6b7d83a13a9b/whats-new-on-cottongen-9273363?e=c8d6ef3065


Progress 12/15/21 to 12/14/22

Outputs
Target Audience:Right now, public cotton breeders must go in DNA-blind when trying to combine target traits from parental lines. Since most public-sector cotton breeders use the pedigree method to select parents for new crosses, crosses may wind up being far wider or narrower than anticipated, yielding unexpected results due to ancestral genetic drift. Choosing genetic markers is difficult since each individual marker is unlikely to be close to QTL underlying a trait of interest or to be segregating in a cross between two random individuals. There are innumerable considerations in planning a genotyping scheme and connecting this information back to program-specific or global haplotype blocks is infeasible for each individual breeder. Our team has developed genotyping systems for multiple crops and knows what it takes to make useful genomics tools. Breeders have identified a haplotype-based genotyping strategy as a top priority and agree that availability of such a system will greatly improve the reach of their programs.Research has been communicated with public cotton researchers at multiple venues during the project reporting period, including through dissemination of CottonGen database. Research has also been communicated with cotton stakeholders, Cotton Incorporated. Changes/Problems: The proposed timeline for field materials have been adjusted slightly for the South Carolina program as F3 generation was not initially available. The F3 will be going into the field in 2023. Work proposed in the UGA breeding program will be shifted to including training a graduate student and will require a rebudget of current funding in technical support. What opportunities for training and professional development has the project provided? Outreach activities included delivery of 4 newsletters, 8 video tutorials on how to use specific data and tool, a peer-reviewed CottonGen publication, an updated BIMS user manual, and collaboration with micropublications to add cotton micropubs to CottonGen. How have the results been disseminated to communities of interest? A graduate student presented at the National Association of Plant Breeders Annual Meeting. A graduate student presented a seminar with INTRINSyC plant biology research group. The PI (Hulse-Kemp) presented the research project as a part of the International Plant Breeding Seminar Series at North Carolina State University. Providing access to high-quality, curated and integrated genomic, genetic and breeding data, and query/analysis tools, CottonGen continues to enable basic discovery and crop improvement in cotton. In year 1 of this project CottonGen was cited in 114 peer-reviewed journal articles, and was used by 31,855 users from 178 countries, with 414.354 pages accessed over 64,485 sessions. Of these users 22% were from the US. What do you plan to do during the next reporting period to accomplish the goals? In the next reporting period we plan to (1) Continue to add high-quality cotton genomics, genetics, breeding data; (2) Continue to improve or add new functionality to CottonGen as needed by the cotton research community. This will include better connection of BIMS to other BrAPI compliant breeding resources and tools; (3) Provide in-person and virtual training to public cotton breeders and researchers to promote efficient use of CottonGen for discovery and decision-making; and (4) Collaborate to ensure an efficient and seamless system to incorporate and promote cotton micropublications in CottonGen. Next generation of plant materials will be planted/trialed at multiple locations for each of the two cotton breeding programs. Additional materials will be genotyped utilizing a newly developed genotyping technology that will be validated in the process and made available to the public.

Impacts
What was accomplished under these goals? Leaf samples from 2000 plants were collected from the Georgia breeding program. 900 of 2000 plants for the Georgia breeding program F3 were genotyped with the 11K SNP array. A database of genetic variants from 170 historical cotton cultivars was created for in-house use until additional genotypes can be added. Three existing genotyping technologies were tested: CottonSNP63K array, CottonSNP11K, and DArTag amplicon sequencing. Additional work was done in house to create a medium-density option for genotyping, the CottonSNP30K array, expected to be available to the public in 2023. DNA extraction was tested in-house and with two service providers. Protocol for freeze-drying field collected leaf samples was created. A trait meta-analysis was performed on 20 QTL mapping studies and 28 GWAS publications (total of 890 publications screened for inclusion). No major QTL clusters in the cotton genome were identified. Major data added to CottonGen included 11 genomes, 549,720 genes, 350 germplasm, 3 genetic maps, 103,382 markers, 5,997,856 genotypes, 6,662 phenotypes and 456 QTLS. New functionality in CottonGen included addition of (1) germplasm, Genes/Transcripts, Map, Publication and QTLs searches through the new MegaSearch Tool, offering faster querying and more customization of fields in the result table and download file; (2) A new Ortholog/Paralog Search tool allowing retrieval of orthologs/paralogs for gene sets filtered through the query form or uploaded file, and provides access to corresponding genes in different genome assemblies within the same species; (3) MapViewer was updated to have corresponding matrices between genome sequences and genetic maps, and between different genetic maps; (4) Genotype upload and search capability added to the Breeding Information Management System (BIMS); (5) A BIMS program was created for this project with GRIN Cotton data uploaded for testing of this breeding resource.

Publications

  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Allen, M., Hulse-Kemp, A.M., and Storm, A.R. Gossypium hirsutum gene of unknown function, Gohir.A02G044702.1, encodes a potential B3 Transcription Factor of the REM subfamily. microPublication Biology. (2022).
  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Billings, G.T., Jones, M.A., Rustgi, S., Bridges Jr., W.C., Holland, J.B., Hulse-Kemp, A.M., and Campbell, B.T.. Outlook for Implementation of Genomics-Based Selection in Public Cotton Breeding Programs. Plants, 11(11), 1446. (2022).
  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Graham, B.P., Park, J., Billings, G.T., Hulse-Kemp, A.M., Haigler, C.H., and Lobaton, E.. Efficient imaging and computer vision detection of two cell shapes in young cotton fibers. Applications in Plant Sciences. E11503. (2022).