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Jacob Washburn
Plant Genetics Research
Research Geneticist

Phone: (573) 882-4305
Fax:

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Projects
Heirlooms of the United States, Southeast Evaluation
Cooperative Agreement (A)
  Accession Number: 445723
Heirlooms of the United States, Midwest Evaluation
Cooperative Agreement (A)
  Accession Number: 445724
Adaptation of Grain Crops to Varying Environments Including Climates, Stressors, and Human Uses
In-House Appropriated (D)
  Accession Number: 443892
Institutional Biological Safety Committee (IBC) Agreement - University of Missouri
Non-Funded Cooperative Agreement (N)
  Accession Number: 441686
Missouri Maize Center - Joint Administration of the Genetics Farm
Non-Funded Cooperative Agreement (N)
  Accession Number: 442031
Analysis of GxE in Diverse Maize Hybrids - Set 2
Trust Fund Cooperative Agreement (T)
  Accession Number: 444162

Publications (Clicking on the reprint icon Reprint Icon will take you to the publication reprint.)
Trait association and prediction through integrative K-mer analysis Reprint Icon - (Peer Reviewed Journal)
He, C., Washburn, J.D., Schleif, N., Hao, Y., Kaeppler, H., Kaeppler, S., Zhang, Z., Yang, J., Liu, S. 2024. Trait association and prediction through integrative K-mer analysis. The Plant Journal. 120(2): 833-850. https://doi.org/10.1111/tpj.17012.
High temporal resolution unoccupied aerial systems phenotyping provides unique information between flight dates Reprint Icon - (Peer Reviewed Journal)
Washburn, J.D., Adak, A., Desalvio, A., Arik, M.A., Murray, S.C. 2024. High temporal resolution unoccupied aerial systems phenotyping provides unique information between flight dates. The Plant Phenome Journal. 7. https://doi.org/10.1002/ppj2.20113.
Halophytes and heavy metals: a multi-omics approach to understand the role of gene and genome duplication in the abiotic stress tolerance of Cakile maritima Reprint Icon - (Peer Reviewed Journal)
Thomas, S.K., Vanden Hoek, K., Ogoti, T., Duong, H., Angelovici, R., Pires, C.J., Mendoza-Cozatl, D., Washburn, J.D., Schenck, C.A. 2024. Halophytes and heavy metals: a multi-omics approach to understand the role of gene and genome duplication in the abiotic stress tolerance of Cakile maritima. American Journal of Botany. 111. Article e16310. https://doi.org/10.1002/ajb2.16310.
Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations Reprint Icon - (Peer Reviewed Journal)
Adak, A., Murray, S.C., Washburn, J.D. 2024. Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations. New Phytologist. 242:121-136. https://doi.org/10.1111/nph.19575.
Leveraging data from the genomes-to-fields initiative to investigate genotype-by-environment interactions in maize in North America Reprint Icon - (Peer Reviewed Journal)
Lopez-Cruz, M., Aguate, F.M., Washburn, J.D., de Leon, N., Kaeppler, S.M., Lima, D., Tan, R., Thompson, A., De La Bretonne, L.W., de los Campos, G. 2023. Leveraging data from the genomes-to-fields initiative to investigate genotype-by-environment interactions in maize in North America. Nature Communications. 14. Article 6904. https://doi.org/10.1038/s41467-023-42687-4.
Ensemble of best linear unbiased predictor, machine learning and deep learning models predict maize yield better than each model alone Reprint Icon - (Peer Reviewed Journal)
Kick, D.R., Washburn, J.D. 2023. Ensemble of best linear unbiased predictor, machine learning and deep learning models predict maize yield better than each model alone. in silico Plants. 5(2). Article diad015. https://doi.org/10.1093/insilicoplants/diad015.
GWAS analysis of maize host plant resistance to western corn rootworm (Coleoptera: Chrysomelidae) reveals candidate small effect loci for resistance breeding Reprint Icon - (Peer Reviewed Journal)
Washburn, J.D., LaFond, H.F., Lapadatescu, M.C., Pereira, A.E., Erb, M., Hibbard, B.E. 2023. GWAS analysis of maize host plant resistance to western corn rootworm (Coleoptera: Chrysomelidae) reveals candidate small effect loci for resistance breeding. Journal of Economic Entomology. 116(6):2184–2192. https://doi.org/10.1093/jee/toad181.
Synthetically labeled images for maize plant detection in UAS images - (Book / Chapter)
Piyush, P., Best, N.B., Washburn, J.D. 2023. Synthetically labeled images for maize plant detection in UAS images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2023. Lecture Notes in Computer Science, vol 14361. Springer, Cham. p. 543–556.
Genomes to fields 2022 maize genotype by environment prediction competition Reprint Icon - (Peer Reviewed Journal)
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.
2018-2019 field seasons of the maize genomes to fields (G2F) G x E project Reprint Icon - (Peer Reviewed Journal)
Lima, D., Castro Aviles, A., Alpers, T., Mcfarlan, B., Kaeppler, S., Ertl, D., Romay, C., Gage, J., Holland, J.B., Beissinger, T., Bohn, M., Buckler, E., Edwards, J., Flint-Garcia, S., Hirsch, C., Hood, E., Hooker, D., Knoll, J., Kolkman, J., Liu, S., Mckay, J., Minyo, R., Moreta, D.E., Murray, S., Nelson, R., Schnable, J., Sekhon, R., Singh, M., Thomison, P., Thompson, A., Tuinstra, M., Wallace, J., Washburn, J.D., Weldekidan, T., Wisser, R., Xu, W. 2023. 2018-2019 field seasons of the maize genomes to fields (G2F) G x E project. BMC Genomic Data. 24:29. https://doi.org/10.1186/s12863-023-01129-2.
RootBot: high-throughput root stress phenotyping robot Reprint Icon - (Peer Reviewed Journal)
Ruppel, M., Nelson, S., Sidberry, G., Mitchell, M., Kick, D.R., Thomas, S., Guill, K., Oliver, M., Washburn, J.D. 2023. RootBot: high-throughput root stress phenotyping robot. Applications in Plant Sciences. 11(6): Article e11541. https://doi.org/10.1002/aps3.11541.
Ensemble of BLUP, machine learning, and deep learning models predict maize yield better than each model alone Reprint Icon - (Pre-print Publication)
Kick, D.R., Washburn, J.D. 2023. Ensemble of BLUP, machine learning, and deep learning models predict maize yield better than each model alone. bioRxiv. Article bioRxiv 2023.03.30.532932. https://doi.org/10.1101/2023.03.30.532932.
Inclusive collaboration across plant physiology and genomics: now is the time! Reprint Icon - (Other)
Baxter, I., Ainsworth, E.A., Brooks, M.D., Castano-Duque, L.M., Londo, J.P., Washburn, J.D., McElrone, A.J., Coyne, C.J., et al. 2023. Inclusive collaboration across plant physiology and genomics: now is the time! Plant Direct. 7(5). Article e493. https://doi.org/10.1002/pld3.493.
Enhancing the resilience of plant systems to climate change Reprint Icon - (Other)
Braun, D., Washburn, J.D., Wood, J.D. 2023. Enhancing the resilience of plant systems to climate change. Journal of Experimental Botany. 74(9): 2787-2789. https://doi.org/10.1093/jxb/erad090.
Yield prediction through integration of genetic, environment, and management data through deep learning Reprint Icon - (Peer Reviewed Journal)
Kick, D.R., Wallace, J.G., Schnable, J.C., Kolkmann, J.M., Alaca, B., Beissinger, T.M., Edwards, J.W., Ertl, D., Flint-Garcia, S.A., Gage, J.L., Hirsch, C.N., Knoll, J.E., de Leon, N., Lima, D.C., Moreta, D., Singh, M.P., Thompson, A., Weldekidan, T., Washburn, J.D. 2023. Yield prediction through integration of genetic, environment, and management data through deep learning. G3, Genes/Genomes/Genetics. 13(4). Article jkad006. https://doi.org/10.1093/g3journal/jkad006.
Yield prediction through integration of genetic, environment, and management data through deep learning Reprint Icon - (Pre-print Publication)
Kick, D.R., Wallace, J.G., Schnable, J.C., Kolkmann, J.M., Boris, A., Beissinger, T.M., Irtl, D., Flint Garcia, S.A., Gage, J.L., Hirsch, C.N., Knoll, J.E., De Leon, N., Lima, D.C., Moreta, D., Singh, M.P., Weldekidan, T., Washburn, J.D. 2022. Yield prediction through integration of genetic, environment, and management data through deep learning. bioRxiv. Article bioRxiv 2022.07.29.502051. https://doi.org/10.1101/2022.07.29.502051.
Distinct C4 sub-types and C3 bundle sheath isolation in the Paniceae grasses Reprint Icon - (Peer Reviewed Journal)
Washburn, J.D., Strable, J., Dickinson, P., Kothapalli, S.S., Brose, J.M., Covshoff, S., Conant, G.C., Hibberd, J.M., Pires, C.J. 2021. Distinct C4 sub-types and C3 bundle sheath isolation in the Paniceae grasses. Plant Direct. 5(12): Article e373. https://doi.org/10.1002/pld3.373.
Trait association and prediction through integrative K-mer analysis Reprint Icon - (Pre-print Publication)
He, C., Washburn, J.D., Hao, Y., Zhang, Z., Yang, J., Liu, S. 2021. Trait association and prediction through integrative K-mer analysis. bioRxiv. https://doi.org/10.1101/2021.11.17.468725.
Predicting phenotypes from genetic, environment, management, and historical data using CNNs Reprint Icon - (Peer Reviewed Journal)
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.
The contributions from the progenitor genomes of the mesopolyploid brassiceae are evolutionarily distinct but functionally compatible Reprint Icon - (Peer Reviewed Journal)
Hao, Y., Mabry, M.E., Edger, P.P., Freeling, M., Zheng, C., Jin, L., VanBuren, R., Colle, M., An, H., Abrahams, R.S., Washburn, J.D., Qi, X., Barry, K., Daum, C., Shu, S., Schmutz, J., Sankoff, D., Barker, M.S., Lyons, E., Pires, C.J., Conant, G.C. 2021. The contributions from the progenitor genomes of the mesopolyploid brassiceae are evolutionarily distinct but functionally compatible. Genome Research. 31(5):799-810. https://doi.org/10.1101/gr.270033.120.
Cytogenetics and fertility of an induced tetraploid Sorghum bicolor x S. propinquum hybrid Reprint Icon - (Peer Reviewed Journal)
Porter, N.T., Burson, B.L., Washburn, J.D., Klein, R.R., Jessup, R.W. 2021. Cytogenetics and fertility of an induced tetraploid Sorghum bicolor x S. propinquum hybrid. Crop Science. 61(3):1881-1889. https://doi.org/10.1002/csc2.20482.
Phylogeny and multiple independent whole-genome duplication events in the brassicales Reprint Icon - (Peer Reviewed Journal)
Mabry, M.E., Brose, J.M., Blischak, P.D., Sutherland, B., Dismukes, W.T., Bottoms, C.A., Edger, P.P., Washburn, J.D., An, H., Hall, J.C., McKain, M.R., Al-Shehbaz, I., Barker, M.S., Schranz, E.M., Conant, G.C., Pires, C.J. 2020. Phylogeny and multiple independent whole-genome duplication events in the brassicales. American Journal of Botany. 107(8):1148-1164. https://doi.org/10.1002/ajb2.1514.