4.7 Article

Sequence differentiation in regions identified by a genome scan for local adaptation

期刊

MOLECULAR ECOLOGY
卷 17, 期 13, 页码 3123-3135

出版社

WILEY
DOI: 10.1111/j.1365-294X.2008.03755.x

关键词

AFLP; Littorina; population genomics; transposable element

资金

  1. Biotechnology and Biological Sciences Research Council [G18139] Funding Source: Medline
  2. Biotechnology and Biological Sciences Research Council [G18139] Funding Source: researchfish

向作者/读者索取更多资源

Genome scans using large numbers of randomly selected markers have revealed a small proportion of loci that deviate from neutral expectations and so may mark genomic regions that contribute to local adaptation. Measurements of sequence differentiation and identification of genes in these regions is important but difficult, especially in organisms with limited genetic information available. We have followed up a genome scan in the marine gastropod, Littorina saxatilis, by searching a bacterial artificial chromosome library with differentiated and undifferentiated markers, sequencing four bacterial artificial chromosomes and then analysing sequence variation in population samples for fragments at, and close to the original marker polymorphisms. We show that sequence differentiation follows the patterns expected from the original marker frequencies, that differentiated markers identify independent and highly localized sites and that these sites fall outside coding regions. Two differentiated loci are characterized by insertions of putative transposable elements that appear to have increased in frequency recently and which might influence expression of downstream genes. These results provide strong candidate loci for the study of local adaptation in Littorina. They demonstrate an approach that can be applied to follow up genome scans in other taxa and they show that the genome scan approach can lead rapidly to candidate genes in nonmodel organisms.

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

4.7
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