Location: Corn Insects and Crop Genetics Research
2022 Annual Report
Accomplishments
1. Development of a pan-genomic approach to explore the diversity of maize. The development of high-yielding resilient germplasm continues to be of paramount importance to reduce global food insecurity, improve access to proper nutrition, and curtail economic impacts from destructive diseases, pests, and environmental extremes. Breeders and farmers have taken advantage of the rich diversity of the maize genome to develop better varieties to meet these demands. ARS researchers at Ames, Iowa, developed an approach to represent the genetic and genomic relationships (pan-genome) of multiple diverse maize genomes (published in BMC Plant Biology) to facilitate the exploration of the maize genome and allow maize breeders and researchers to connect traits to genes. Resources are available for over 40 genomes representing distinct maize cultivars. An example tool is qTeller, a platform to compare how, when, where, and under what conditions genes are expressed across different cultivars. The pan-genomic resource allows researchers to understand basic plant biology, accelerate the pace of genetic enhancement and breeding, and translate those findings into products that increase crop quality and production.
Review Publications
Woodhouse, M.H., Cannon, E.K., Portwood II, J.L., Harper, E.C., Gardiner, J.M., Schaeffer, M.L., Andorf, C.M. 2021. A pan-genomic approach to genome databases using maize as a model system. Biomed Central (BMC) Plant Biology. 21. Article 385. https://doi.org/10.1186/s12870-021-03173-5.
Hufford, M.B., Seetharam, A.S., Woodhouse, M.H., Chougle, K.M., Ou, S., Liu, J., Ricci, W.A., Guo, T., Olson, A., Qiu, Y., Portwood II, J.L., Cannon, E.K., Andorf, C.M., Ware, D., Dawe, K.R. et al. 2021. De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science. 373(6555):655-662. https://doi.org/10.1126/science.abg5289.
Woodhouse, M.H., Sen, S., Schott, D., Portwood II, J.L., Freeling, M., Walley, J.W., Andorf, C.M., Schnable, J.C. 2021. qTeller: A tool for comparative multi-genomic gene expression analysis. Bioinformatics. 38(1): 236-242. https://doi.org/10.1093/bioinformatics/btab604.
