Location: Plant, Soil and Nutrition Research
2023 Annual Report
Accomplishments
1. Natural and synthetic nitrogen is lost from our food systems before it reaches the consumer. Over 80% of natural and synthetic nitrogen is lost from our food systems before it reaches the consumer, contributing to 97% of US agricultural greenhouse gas emissions (nitrous oxide, methane) and over 60% of water pollution. The CERCA (Circular Economy for Reimaging Corn Agriculture) project being launched this year focuses on corn, the single largest player in the US agricultural nitrogen system. The goal of this project is to develop corn genetics in concert with agronomy that that reduces corn’s environmental impact by well over 50% by shifting the growing season earlier to capture natural soil nitrogen, reducing corn’s demand for nitrogen, and recycling nitrogen back to the soil at the end of season like perennials. The CERCA project lead by USDA scientists from across the country and university collaborators (27 total labs) have initiated integrated research covering modeling, agronomy, genetics, and physiology to accomplish these goals.
2. Specialty crops and livestock are central to human nutrition, wellbeing, and cultural preservation. Together their production is responsible for over $150 billion in cash receipts. The USDA-ARS and university partner breeder teams who work on these species develop outstanding biological and practical know-how but often lack specialized expertise in genomic DNA-based breeding or advanced information technologies. USDA-ARS Breeding Insight in collaboration with Cornell University centralizes that expertise and adds to it a flexibility to apply advanced genomic and information/automation technologies to these many idiosyncratic species across the country. This year, the project expanded to support 19 species including 32 breeding teams across 18 states. Genomic markers that accelerate breeding were developed for an additional 5 species (70% increase from last year). Nearly 40,000 potential new varieties were genomically evaluated (80% increase from last year). Information and machine learning technologies deployed to 18 species have integrated historical data and automated the collection of new field data resulting in a 190% increase in databased records from last year. Centralization and flexibility are working to enable a scaling not seen before within USDA specialty crops and livestock. Having more data, effectively organized, matters: In sugarcane, blueberry, citrus and sweet potato, ARS breeders are collecting data faster and with fewer errors while for the first time leveraging all aggregated historical datasets to improve precision in selection. In partnership with ARS breeders in St. Paul, Minnesota, and Prosser, Washington, working on alfalfa. Despite alfalfa's complex genome, the collaboration identified genomic markers for the key disease resistance that will accelerate the delivery of highly digestible feed alfalfa to farmers. Breeding Insight helps US breeders accelerate the delivery of nutritious and resilient crops and livestock.
Review Publications
Monier, B., Casstevens, T.M., Bradbury, P., Buckler IV, E.S. 2022. rTASSEL: An R interface to TASSEL for analyzing genomic diversity. Journal of Open Source Software. https://doi.org/10.21105/joss.04530.
Washburn, J.D., Cimen, E., Ramstein, G., Reeves, T., O'Briant, P., McLean, G., Cooper, M., Hammer, G., Buckler IV, E.S. 2021. Predicting phenotypes from genetic, environment, management, and historical data using CNNs. Theoretical and Applied Genetics. 134:3997–4011. https://doi.org/10.1007/s00122-021-03943-7.
Long, E.K., Romay, M., Ramstein, G., Buckler IV, E.S., Robbins, K.R. 2023. Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava. Frontiers in Plant Science. 13:1041925. https://doi.org/10.3389/fpls.2022.1041925.
Wrightsman, T., Marand, A.P., Crisp, P.A., Springer, N.M., Buckler IV, E.S. 2022. Modeling chromatin state from sequence across angiosperms using recurrent convolutional neural networks. The Plant Genome. 15(3):e20249. https://doi.org/10.1002/tpg2.20249.
Khaipho-Burch, M., Ferebee, T., Giri, A., Ramstein, G., Monier, B., Yi, E., Romay, M., Buckler IV, E.S. 2023. Elucidating the patterns of pleiotropy and its biological relevance in maize. PLoS Genetics. PLoS Genet 19(3): e1010664. https://doi.org/10.1371/journal.pgen.1010664.
Bradbury, P.J., Casstevens, T., Jensen, S.E., Johnson, L.E., Miller, Z.R., Monier, B., Romay, M., Song, B., Buckler IV, E.S. 2022. The practical haplotype graph, a platform for storing and using pangenomes for imputation. Bioinformatics. 38(15):3698-3702. https://doi.org/10.1093/bioinformatics/btac410.
Samayoa, L., Olukolu, B.A., Yang, C.J., Chen, Q., Stetter, M.G., York, A.M., Sanchez-Gonzalez, J., Glaubitz, J.C., Bradbury, P., Cinta Romay, M., Sun, Q., Yang, J., Ross-Ibarra, J., Buckler IV, E.S., Doebley, J.F., Holland, J.B. 2021. Domestication reshaped the genetic basis of inbreeding depression in a maize landrace compared to its wild relative, teosinte. PLoS Genetics. 2:1009797. https://doi.org/10.6084/m9.figshare.14750790.
Lima, D.C., Washburn, J.D., Varela, J.I., Chen, Q., Gage, J.L., Romay, M.C., Holland, J.B., Ertl, D., Lopez-Cruz, M., Aguate, F.M., De Los Campos, G., Kaeppler, S., Beissinger, T., Bohn, M., Buckler IV, E.S., Edwards, J.W., Flint Garcia, S.A., Gore, M.A., Hirsch, C.N., Knoll, J.E., Mckay, J., Minyo, R., Murray, S.C., Ortez, O.A., Schnable, J., Sekhon, R.S., Singh, M.P., Sparks, E.E., Thompson, A., Tuinstra, M., Wallace, J., Weldekidan, T., Xu, W., De Leon, N. 2023. Genomes to fields 2022 maize genotype by environment prediction competition. BMC Research Notes. 16: Article 148. https://doi.org/10.1186/s13104-023-06421-z.
