QTL × environment interactions underlie adaptive divergence in switchgrass across a large latitudinal gradient.

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ID: 19179
2019
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Ranked #150 of 292 articles by views in Proceedings of the National Academy of Sciences of the United States of America

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Abstract
Local adaptation is the process by which natural selection drives adaptive phenotypic divergence across environmental gradients. Theory suggests that local adaptation results from genetic trade-offs at individual genetic loci, where adaptation to one set of environmental conditions results in a cost to fitness in alternative environments. However, the degree to which there are costs associated with local adaptation is poorly understood because most of these experiments rely on two-site reciprocal transplant experiments. Here, we quantify the benefits and costs of locally adaptive loci across 17° of latitude in a four-grandparent outbred mapping population in outcrossing switchgrass ( L.), an emerging biofuel crop and dominant tallgrass species. We conducted quantitative trait locus (QTL) mapping across 10 sites, ranging from Texas to South Dakota. This analysis revealed that beneficial biomass (fitness) QTL generally incur minimal costs when transplanted to other field sites distributed over a large climatic gradient over the 2 y of our study. Therefore, locally advantageous alleles could potentially be combined across multiple loci through breeding to create high-yielding regionally adapted cultivars.
Reference Key
lowry2019qtlproceedings Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lowry, David B;Lovell, John T;Zhang, Li;Bonnette, Jason;Fay, Philip A;Mitchell, Robert B;Lloyd-Reilley, John;Boe, Arvid R;Wu, Yanqi;Rouquette, Francis M;Wynia, Richard L;Weng, Xiaoyu;Behrman, Kathrine D;Healey, Adam;Barry, Kerrie;Lipzen, Anna;Bauer, Diane;Sharma, Aditi;Jenkins, Jerry;Schmutz, Jeremy;Fritschi, Felix B;Juenger, Thomas E;
Journal Proceedings of the National Academy of Sciences of the United States of America
Year 2019
DOI
10.1073/pnas.1821543116
URL
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