論文

査読有り
2013年9月6日

Genetic Structure of Pelagic and Littoral Cichlid Fishes from Lake Victoria

PLoS ONE
  • Miyuki Takeda
  • ,
  • Junko Kusumi
  • ,
  • Shinji Mizoiri
  • ,
  • Mitsuto Aibara
  • ,
  • Semvua Isa Mzighani
  • ,
  • Tetsu Sato
  • ,
  • Yohey Terai
  • ,
  • Norihiro Okada
  • ,
  • Hidenori Tachida

8
9
開始ページ
74088
終了ページ
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1371/journal.pone.0074088

The approximately 700 species of cichlids found in Lake Victoria in East Africa are thought to have evolved over a short period of time, and they represent one of the largest known examples of adaptive radiation. To understand the processes that are driving this spectacular radiation, we must determine the present genetic structure of these species and elucidate how this structure relates to the ecological conditions that caused their adaptation. We analyzed the genetic structure of two pelagic and seven littoral species sampled from the southeast area of Lake Victoria using sequences from the mtDNA control region and 12 microsatellite loci as markers. Using a Bayesian model-based clustering method to analyze the microsatellite data, we separated these nine species into four groups: one group composed of pelagic species and another three groups composed mainly of rocky-shore species. Furthermore, we found significant levels of genetic variation between species within each group at both marker loci using analysis of molecular variance (AMOVA), although the nine species often shared mtDNA haplotypes. We also found significant levels of genetic variation between populations within species. These results suggest that initial groupings, some of which appear to have been related to habitat differences, as well as divergence between species within groups took place among the cichlid species of Lake Victoria. © 2013 Takeda et al.

リンク情報
DOI
https://doi.org/10.1371/journal.pone.0074088
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/24040175
ID情報
  • DOI : 10.1371/journal.pone.0074088
  • ISSN : 1932-6203
  • PubMed ID : 24040175
  • SCOPUS ID : 84883638253

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