Joseph Gage

Lima, D. C., Aviles, A. C., Alpers, R. T., McFarland, B. A., Kaeppler, S., Ertl, D., … Leon, N. (2023). 2018-2019 field seasons of the Maize Genomes to Fields (G2F) G x E project. BMC GENOMIC DATA, 24(1). https://doi.org/10.1186/s12863-023-01129-2

Lima, D. C., Aviles, A. C., Alpers, R. T., Perkins, A., Schoemaker, D. L., Costa, M., … Leon, N. (2023, September 14). 2020-2021 field seasons of Maize GxE project within the Genomes to Fields Initiative. BMC RESEARCH NOTES, Vol. 16. https://doi.org/10.1186/s13104-023-06430-y

Lima, D. C., Washburn, J. D., Varela, J. I., Chen, Q., Gage, J. L., Romay, M. C., … Leon, N. (2023, July 17). Genomes to Fields 2022 Maize genotype by Environment Prediction Competition. BMC RESEARCH NOTES, Vol. 16. https://doi.org/10.1186/s13104-023-06421-z

Kick, D. R., Wallace, J. G., Schnable, J. C., Kolkman, J. M., Alaca, B., Beissinger, T. M., … Washburn, J. D. (2023). Yield prediction through integration of genetic, environment, and management data through deep learning. G3-GENES GENOMES GENETICS, 13(4). https://doi.org/10.1093/g3journal/jkad006

Gage, J. L., Mali, S., McLoughlin, F., Khaipho-Burch, M., Monier, B., Bailey-Serres, J., … Buckler, E. S. (2022). Variation in upstream open reading frames contributes to allelic diversity in maize protein abundance. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 119(14). https://doi.org/10.1073/pnas.2112516119

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning. (2022, July 30). [], Vol. 7. https://doi.org/10.1101/2022.07.29.502051

Feldmann, M. J., Gage, J. L., Turner-Hissong, S. D., & Ubbens, J. R. (2021). Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants. The Plant Phenome Journal, 4(1). https://doi.org/10.1002/ppj2.20023

Franco, J. A. V., Gage, J. L., Bradbury, P. J., Johnson, L. C., Miller, Z. R., Buckler, E. S., & Romay, M. C. (2020, August 31). A Maize Practical Haplotype Graph Leverages Diverse NAM Assemblies. [], Vol. 8. https://doi.org/10.1101/2020.08.31.268425

McFarland, B. A., AlKhalifah, N., Bohn, M., Bubert, J., Buckler, E. S., Ciampitti, I., … Leon, N. (2020). Maize genomes to fields (G2F): 2014–2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets. BMC Research Notes, 13(1). https://doi.org/10.1186/s13104-020-4922-8

Gage, J. L., Monier, B., Giri, A., & Buckler, E. S. (2020). Ten Years of the Maize Nested Association Mapping Population: Impact, Limitations, and Future Directions. The Plant Cell, 32(7), 2083–2093. https://doi.org/10.1105/tpc.19.00951

Genome-wide association analysis of stalk biomass and anatomical traits in maize. (2019). BMC Plant Biology. https://doi.org/10.1186/s12870-019-1653-x

Gage, J. L., Richards, E., Lepak, N., Kaczmar, N., Soman, C., Chowdhary, G., … Buckler, E. S. (2019). In‐Field Whole‐Plant Maize Architecture Characterized by Subcanopy Rovers and Latent Space Phenotyping. The Plant Phenome Journal, 2(1), 1–11. https://doi.org/10.2135/tppj2019.07.0011

LiDar Point Clouds of Hybrid Maize [Data set]. (2019). CyVerse Data Commons. https://doi.org/10.25739/zxp6-g188

Multiple Maize Reference Genomes Impact the Identification of Variants by Genome-Wide Association Study in a Diverse Inbred Panel. (2019). The Plant Genome. https://doi.org/10.3835/plantgenome2018.09.0069

Residual Heterozygosity and Epistatic Interactions Underlie the Complex Genetic Architecture of Yield in Diploid Potato. (2019). Genetics. https://doi.org/10.1534/genetics.119.302036

Gage, J. L., de, L. N., & Clayton, M. K. (2018). Comparing Genome-Wide Association Study Results from Different Measurements of an Underlying Phenotype. G3 (Bethesda, Md.), 9. https://doi.org/10.1534/g3.118.200700

Gage, J. L., White, Edwards, J. W., Kaeppler, S., & de, L. N. (2018). Selection Signatures Underlying Dramatic Male Inflorescence Transformation During Modern Hybrid Maize Breeding. Genetics, 9. https://doi.org/10.1534/genetics.118.301487

Gage, J. L., Miller, N. D., Spalding, E. P., Kaeppler, S. M., & Leon, N. (2017). TIPS: a system for automated image-based phenotyping of maize tassels. Plant Methods, 13(1), 21. https://doi.org/10.1186/s13007-017-0172-8

Gage, J. L., Jarquin, D., Romay, C., Lorenz, A., Buckler, E. S., Kaeppler, S., … Leon, N. (2017). The effect of artificial selection on phenotypic plasticity in maize. NATURE COMMUNICATIONS, 8(1). https://doi.org/10.1038/s41467-017-01450-2

Spindel, J., Wright, M., Chen, C., Cobb, J., Gage, J., Harrington, S., … McCouch, S. (2013). Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations. TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik, 8. https://doi.org/10.1007/s00122-013-2166-x