Genomics of isolation in hybrids
Author(s) -
Zachariah Gompert,
Thomas L. Parchman,
C. Alex Buerkle
Publication year - 2011
Publication title -
philosophical transactions of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.753
H-Index - 272
eISSN - 1471-2970
pISSN - 0962-8436
DOI - 10.1098/rstb.2011.0196
Subject(s) - introgression , reproductive isolation , biology , evolutionary biology , genetic algorithm , genetic architecture , hybrid , genomics , isolation (microbiology) , isolation by distance , genome , population genomics , population , genetics , quantitative trait locus , gene flow , genetic variation , gene , bioinformatics , demography , botany , sociology
Hybrid zones are common in nature and can offer critical insights into the dynamics and components of reproductive isolation. Hybrids between diverged lineages are particularly informative about the genetic architecture of reproductive isolation, because introgression in an admixed population is a direct measure of isolation. In this paper, we combine simulations and a new statistical model to determine the extent to which different genetic architectures of isolation leave different signatures on genome-level patterns of introgression. We found that reproductive isolation caused by one or several loci of large effect caused greater heterogeneity in patterns of introgression than architectures involving many loci with small fitness effects, particularly when isolating factors were closely linked. The same conditions that led to heterogeneous introgression often resulted in a reasonable correspondence between outlier loci and the genetic loci that contributed to isolation. However, demographic conditions affected both of these results, highlighting potential limitations to the study of the speciation genomics. Further progress in understanding the genomics of speciation will require large-scale empirical studies of introgression in hybrid zones and model-based analyses, as well as more comprehensive modelling of the expected levels of isolation with different demographies and genetic architectures of isolation.
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