| Literature DB >> 33888874 |
Kelly Swarts1,2,3, Eva Bauer4, Jeffrey C Glaubitz5, Tiffany Ho6, Lynn Johnson5, Yongxiang Li7, Yu Li7, Zachary Miller5, Cinta Romay5, Chris-Carolin Schön4, Tianyu Wang7, Zhiwu Zhang8, Edward S Buckler6,9, Peter Bradbury9.
Abstract
Domesticates are an excellent model for understanding biological consequences of rapid climate change. Maize (Zea mays ssp. mays) was domesticated from a tropical grass yet is widespread across temperate regions today. We investigate the biological basis of temperate adaptation in diverse structured nested association mapping (NAM) populations from China, Europe (Dent and Flint) and the United States as well as in the Ames inbred diversity panel, using days to flowering as a proxy. Using cross-population prediction, where high prediction accuracy derives from overall genomic relatedness, shared genetic architecture, and sufficient diversity in the training population, we identify patterns in predictive ability across the five populations. To identify the source of temperate adapted alleles in these populations, we predict top associated genome-wide association study (GWAS) identified loci in a Random Forest Classifier using independent temperate-tropical North American populations based on lines selected from Hapmap3 as predictors. We find that North American populations are well predicted (AUC equals 0.89 and 0.85 for Ames and USNAM, respectively), European populations somewhat well predicted (AUC equals 0.59 and 0.67 for the Dent and Flint panels, respectively) and that the Chinese population is not predicted well at all (AUC is 0.47), suggesting an independent adaptation process for early flowering in China. Multiple adaptations for the complex trait days to flowering in maize provide hope for similar natural systems under climate change.Entities:
Mesh:
Year: 2021 PMID: 33888874 PMCID: PMC8178344 DOI: 10.1038/s41437-021-00422-z
Source DB: PubMed Journal: Heredity (Edinb) ISSN: 0018-067X Impact factor: 3.832