Literature DB >> 26808290

Reticulate evolutionary history and extensive introgression in mosquito species revealed by phylogenetic network analysis.

Dingqiao Wen1, Yun Yu1, Matthew W Hahn2,3, Luay Nakhleh1,4.   

Abstract

The role of hybridization and subsequent introgression has been demonstrated in an increasing number of species. Recently, Fontaine et al. (Science, 347, 2015, 1258524) conducted a phylogenomic analysis of six members of the Anopheles gambiae species complex. Their analysis revealed a reticulate evolutionary history and pointed to extensive introgression on all four autosomal arms. The study further highlighted the complex evolutionary signals that the co-occurrence of incomplete lineage sorting (ILS) and introgression can give rise to in phylogenomic analyses. While tree-based methodologies were used in the study, phylogenetic networks provide a more natural model to capture reticulate evolutionary histories. In this work, we reanalyse the Anopheles data using a recently devised framework that combines the multispecies coalescent with phylogenetic networks. This framework allows us to capture ILS and introgression simultaneously, and forms the basis for statistical methods for inferring reticulate evolutionary histories. The new analysis reveals a phylogenetic network with multiple hybridization events, some of which differ from those reported in the original study. To elucidate the extent and patterns of introgression across the genome, we devise a new method that quantifies the use of reticulation branches in the phylogenetic network by each genomic region. Applying the method to the mosquito data set reveals the evolutionary history of all the chromosomes. This study highlights the utility of 'network thinking' and the new insights it can uncover, in particular in phylogenomic analyses of large data sets with extensive gene tree incongruence.
© 2016 John Wiley & Sons Ltd.

Entities:  

Keywords:  Anopheles gambiae; hybridization; incomplete lineage sorting; introgression; phylogenetic networks

Mesh:

Year:  2016        PMID: 26808290      PMCID: PMC5146328          DOI: 10.1111/mec.13544

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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