James Schnable

Prof. James Schnable the Nebraska Corn Checkoff Presidential Chair at the University of Nebraska. His research group focuses on integrating new technologies and capabilities from engineering, computer science, and statistics into maize and sorghum genetic and genomic research.

James received the Marcus Rhoades Early Career Award for Maize Genetics in 2018, the North American Plant Phenotyping Network Early Career Award in 2019, and the American Society of Plant Biologists Early Career Award in 2019.

James has founded three companies: Data2Bio (focused on genotyping and breeding decision support), Dryland Genetics (breeding naturally water use efficient crops), and EnGeniousAg (low cost nondestructive nutrient and water sensors for farmers), and he serves as a consultant or advisor to the scientific advisory boards of a number of larger companies in the agricultural and genomics sectors.

James holds a BA in Biology from Cornell University (2008) and a PhD in Plant Biology from UC-Berkeley (2012). From 2013 to 2014 he was NSF Plant Genome Fellowship supported postdoctoral scholar at the Danforth Center in St. Louis and the Chinese Academy of Agricultural Sciences in Beijing China.

Complete CV

Conflict of Interest Disclosure

Recent Publications

Creach M, Webster B, Newton L, Turkus J, Schnable JC, Thompson AM, VanBuren R (2025) Predicting complex phenotypes using multi-omics data in maize. bioRxiv doi: 10.1101/2025.09.30.679283 bioRxiv doi: 10.1101/2025.09.30.679283 Preprint
Zaremehrjerdi H, Coffey L, Jubery T, Liu H, Turkus J, Linders K, Schnable JC, Schnable PS, Ganapathysubramanian B (2025) MaizeEar-SAM: Zero-shot maize ear phenotyping. arXiv doi: 10.48550/arXiv.2502.13399 Preprint
Ji Zhongjie, Ge Y, Schnable JC (2025) Scalable methods for quantifying the stay green ability of corn for yield prediction by using satellite images. agriRxiv doi: 10.31220/agriRxiv.2025.00339 agriRxiv doi: 10.31220/agriRxiv.2025.00339 Preprint
Tross MC, Duggan G, Shrestha N, Schnable JC (2024) Models trained to predict differential expression across plant organs identify distal and proximal regulatory regions. doi: 10.1101/2024.06.04.597477 bioRxiv doi: 10.1101/2024.06.04.597477 Preprint
Engelhorn J, Snodgrass S, Kok A, Seetharam A, Schneider M, Kiwit T, Singh A, Banf M, Khaipho-Burch M, Runcie D, Camargo V, Torres-Rodriguez JV, Sun G, Stam M, Fiorani F, Schnable JC, Bass H, Hufford M, Stich B, Frommer W, Ross-Ibarra J, Hartwig T (2025) Phenotypic variation in maize can be largely explained by genetic variation at transcription factor binding sites. Nature Genetics doi: 10.1038/s41588-025-02246-7 bioRxiv doi: 10.1101/2023.08.08.551183
Singh A, Newton L, Schnable JC, Thompson AM (2025) Unveiling shared genetic regulators for plant architectural and biomass yield traits in sorghum. Journal of Experimental Botany doi: 10.1093/jxb/eraf012 bioRxiv doi: 10.1101/2024.03.13.584802
Izere P, Zhao B, Schnable JC, Ge Y, Shi Y (2025) Positioning accuracy of RTK-GNSS-enabled drones and their performance in agricultural crop sensing. Journal of the ASABE doi: 10.13031/ja.16306
Ozair F, Adak A, Murray S, ..., Schnable JC, ..., Thompson A, Weldekidan T, Xu W (2025) Phenotypic plasticity in maize grain yield: genetic and environmental insights of response to environmental gradients. The Plant Genome doi: 10.1002/tpg2.70078 (Schnable JC is 11 of 16 authors)
Quach TN, Guo M, Nazarenus T, Sato SJ, Wang M, Zhang T, Nersesian N, Ge Z, Ullagaddi C, Yu B, Schnable JC, Clemente TE (2025) In context promoter bashing of the Sorghum bicolor gene models functionally annotated as bundle sheath cell preferred expressing phosphoenolpyruvate carboxykinase and alanine aminotransferase. Crop Science doi: 10.1002/csc2.70039
Shrestha K, Thapa K, Kaler E, Taniguchi M, Sattler S, Schnable JC, Louis J (2025) Employing spectral features to accelerate sorghum phenotyping against sap-feeding aphids. Plant Direct doi: 10.1002/pld3.70092
Ojeda-Rivera JO, Barnes A, Ainsworth EA, ..., Schnable JC, ..., Zou J, Buckler ES (2025) Designing a nitrogen efficient cold tolerant maize for modern agricultural systems. The Plant Cell doi: 10.1093/plcell/koaf139 (Schnable JC is 48 of 56 authors)
Powadi A, Jubery T, Tross M, Shrestha N, Coffey L, Schnable JC, Schnable PS, Ganapathysubramanian B (2025) Enhancing yield prediction from plot-level satellite imagery through genotype and environment feature disentanglement. Frontiers in Plant Science doi: 10.3389/fpls.2025.1617831
Jin H, Park A, Sreedasyam A, Li G, Ge Y, Swaminathan K, Schmutz J, Clemente TE, Schnable JC, Yang J (2025) Nitrogen response and growth trajectory of sorghum CRISPR-Cas9 mutants using high-throughput phenotyping. Genomics Communications doi: 10.48130/gcomm-0025-0011 bioRxiv doi: 10.1101/2024.12.13.624727
Torres-Rodriguez JV, Li D, Schnable JC (2025) Evolving best practices for transcriptome-wide association studies accelerate discovery of gene-phenotype links. Current Opinion in Plant Biology doi: 10.1016/j.pbi.2024.102670
Li F, Grzybowski M, Roston RL, Schnable JC (2025) Nighttime fluorescence phenotyping reduces environmental variability for photosynthetic traits and enables the identification of candidate loci in maize. Frontiers in Plant Science doi: 10.3389/fpls.2025.1595339
Davis JM, Gaillard M, Tross MC, Shrestha N, Ostermann I, Grove RJ, Li B, Benes B, Schnable JC (2025) 3D reconstruction enables high-throughput phenotyping and quantitative genetic analysis of phyllotaxy. Plant Phenomics doi: 10.1016/j.plaphe.2025.100023 bioRxiv doi: 10.1101/2024.10.03.616344
Mathivanan RK, Pedersen C, Turkus J, Shrestha N, Ali W, Torres-Rodriguez JV, Mural RV, Obata T, Schnable JC (2025) Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions. BMC Genomics doi: 10.1186/s12864-025-11580-3 bioRxiv doi: 10.1101/2024.08.26.609532
Davis JM, Coffey LM, Turkus J, López-Corona L, Linders K, Ullagaddi C, Santra DK, Schnable PS, Schnable JC (2025) Assessing the impact of yield plasticity on hybrid performance in maize. Physiologia Plantarum doi: 10.1111/ppl.70278 bioRxiv doi: 10.1101/2025.01.21.634104
Shrestha N, Powadi A, Davis J, Ayanlade TT, Liu H, Tross MC, Mathivanan RK, Bares J, Lopez-Corona L, Turkus J, Coffey L, Tubery TZ, Ge Y, Sarkar S, Schnable JC, Ganapathysubramanian B, Schnable PS (2025) Plot-level satellite imagery can substitute for UAVs in assessing maize phenotypes across multistate field trials. Plants Planet People doi: 10.1002/ppp3.10613 agriRxiv doi: 10.31220/agriRxiv.2024.00251
Istipliler D, Tross MC, Bouwens B, Jin H, Yufeng Ge, Yang J, Mural RV, Schnable JC (2025) Heritability, heterosis, and hybrid/inbred classification ability of maize leaf hyperspectral signals under changing soil nitrogen. Crop Science doi: 10.1002/csc2.70073