Abstract：
:The degree to which genomic architecture varies across space and time is central to the evolution of genomes in response to natural selection. Bulked-segregant mapping combined with pooled sequencing provides an efficient means to estimate the effect of genetic variants on quantitative traits. We develop a novel likelihood framework to identify segregating variation within multiple populations and generations while accommodating estimation error on a sample- and SNP-specific basis. We use this method to map loci for flowering time within natural populations of Mimulus guttatus, collecting the early- and late-flowering plants from each of three neighboring populations and two consecutive generations. Structural variants, such as inversions, and genes from multiple flowering-time pathways exhibit the strongest associations with flowering time. We find appreciable variation in genetic effects on flowering time across both time and space; the greatest differences evident between populations, where numerous factors (environmental variation, genomic background, and private polymorphisms) likely contribute to heterogeneity. However, the changes across years within populations clearly identify genotype-by-environment interactions as an important influence on flowering time variation.
journal_name
Geneticsjournal_title
Geneticsauthors
Monnahan PJ,Kelly JKdoi
10.1534/genetics.117.201483subject
Has Abstractpub_date
2017-07-01 00:00:00pages
1621-1635issue
3eissn
0016-6731issn
1943-2631pii
genetics.117.201483journal_volume
206pub_type
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