James Schnable

James Schnable

Professor

Research areas: Plant Genomics Phenomics Quantitative Genetics Maize Sorghum

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

In 2022, James was a visiting researcher at X (Google’s moonshot lab), where he worked on improving genotype-to-phenotype modeling and gene discovery—research that contributed to the spin-out Heritable Agriculture. He is a Fellow of the PhenoRob Cluster of Excellence and received The Plant Journal’s Outstanding Original Research Article award in 2024. As an assistant professor, he received the Marcus Rhoades Early Career Award (2018) and concurrent Early Career Awards from NAPPN and ASPB (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), which was acquired by CropX in 2024. 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 an NSF Plant Genome Fellowship-supported postdoctoral scholar at the Danforth Center in St. Louis and the Chinese Academy of Agricultural Sciences in Beijing, China.

In the News

  • James Schnable elected to National Academy of Inventors

    James Schnable has been elected a member of the National Academy of Inventors.

  • James Schnable speaks at Texas A&M Plant Breeding Symposium

    James Schnable was an invited speaker at the Texas A&M Plant Breeding Symposium in College Station, Texas.

  • James Schnable wins NAS Prize in Food and Agriculture

    James Schnable has been announced as the 2026 winner of the National Academy of Sciences Prize in Food and Agriculture Sciences. The prize recognizes researchers who have made extraordinary contributions to agriculture and food science.

  • PAG Lab Reunion

    Hit a new record for the number of lab alumni attended: L→R Sunil K. Kenchanmane Raju (now of UC Riverside), James Schnable, Zhikai Liang (now of NDSU), Ravi Mural (now of SDSU), and Vladimir Torres-Rodriguez (now a Scientist at Traits Company).

  • Prof. Schnable featured on The Crop Science Podcast

    In this episode of The Crop Science Podcast, James Schnable discusses how genetics, genomics, and machine learning are reshaping modern hybrid development—explaining how breeders use genomic prediction and high-throughput phenotyping to tackle climate variability, stress tolerance, and yield stability.

  • NCSU Genetics and Genomics Academy seminar

    James delivers a seminar for the North Carolina State Genetics and Genomics Academy. While there, he had the chance to catch up with two of our successful lab alumni: Nate Korth (now a postdoc with Joe Gage) and Lina Lopez (now a field manager with Jim Holland).

Recent Publications

  • Grzybowski M, Schnable JC (2026) Haplotype-rich cis-regulation underlies transcriptomic diversity across the breeding history of maize (Zea mays). doi: 10.64898/2026.02.19.706772 bioRxiv doi: 10.64898/2026.02.19.706772 Preprint
  • Adak A, DeSalvio AJ, Murray SC, de Leon N, Bohn M, Edwards J, Ertl D, Hirsch C, Holland J, Kaeppler S, Knoll JE, Lima DC, Minyo R, Schnable JC, Sekhon RS, Singh MP, Sparks EE, Thompson A, Tuinstra MR, Washburn JD, Weldekidan T (2026) Phenomics-derived temporal maize health signals and enviromics enhance physiology-informed prediction of yield across environments. Plant Physiology Accepted
  • Dias H, Sagawa G, Torres-Rodriguez V, Mural RV, Schnable JC, Van Sluys M-A (2026) A sorghum-anchored pan-grass syntenic gene set in grasses. NAR Genomics and Bioinformatics Accepted
  • Shrestha N, Ji Zhongjie, Dai X, Li P, Schnable JC (2025) A sequence-based classifier distinguishes phenotype-associated genes from other gene models in plants bioRxiv doi: 10.64898/2025.11.30.691407 Preprint
  • 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 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 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 Preprint
  • Chen Q, Washburn JD, Romay MC, ..., Schnable JC, ..., Weldekidan T, Xu W, de Leon N (2026) Genomes to Fields 2024 maize genotype by environment prediction competition. BMC Research Notes doi: 10.1186/s13104-026-07629-5 (Schnable JC is 27 of 36 authors)
  • 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