4.5 Article

Inferring population history and demography using microsatellites, mitochondrial DNA, and major histocompatibility complex (MHC) genes

期刊

EVOLUTION
卷 62, 期 6, 页码 1458-1468

出版社

WILEY
DOI: 10.1111/j.1558-5646.2008.00364.x

关键词

Ambystoma; effective population size; mismatch distribution; M-ratio; natural selection; neutral evolution

向作者/读者索取更多资源

Microsatellites and mitochondrial DNA (mtDNA) have traditionally been used in population genetics because of their variability and presumed neutrality, whereas genes of the major histocompatibility complex (MHC) are increasingly of interest because strong selective pressures shape their standing variation. Despite the potential for MHC genes, microsatellites, and mtDNA sequences to complement one another in deciphering population history and demography, the three are rarely used in tandem. Here we report on MHC, microsatellite, and mtDNA variability in a single large population of the eastern tiger salamander (Ambystoma tigrinum tigrinum). We use the mtDNA mismatch distribution and, on microsatellite data, the imbalance index and bottleneck tests to infer aspects of population history and demography. Haplotype and allelic variation was high at all loci surveyed, and heterozygosity was high at the nuclear loci. We find concordance among neutral molecular markers that suggests our study population originated from post-Pleistocene expansions of multiple, fragmented sources that shared few migrants. Differences in N-e estimates derived from haploid and diploid genetic markers are potentially attributable to secondary contact among source populations that experienced rapid mtDNA divergence and comparatively low levels of nuclear DNA divergence. We find strong evidence of natural selection acting on MHC genes and estimate long-term effective population sizes (N-e) that are very large, making small selection intensities significant evolutionary forces in this population.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据