A large-scale systematic framework of Chinese snakes based on a unified multilocus marker system.

Abstract:

:Snakes are one of the most diverse groups of terrestrial vertebrates, with approximately 3500 extant species. A robust phylogeny and taxonomy of snakes is crucial for us to know, study and protect them. For a large group such as snakes, broad-scale phylogenetic reconstructions largely rely on data integration. Increasing the compatibility of the data from different researches is thus important, which can be facilitated by standardization of the loci used in systematic analyses. In this study, we proposed a unified multilocus marker system for snake systematics by conflating 5 mitochondrial markers, 19 vertebrate-universal nuclear protein coding (NPC) markers and 72 snake-specific noncoding intron markers. This marker system is an addition to the large squamate conserved locus set (SqCL) for studies preferring a medium-scale data set. We applied this marker system to over 440 snake samples and constructed the currently most comprehensive systematic framework of the snakes in China. Robust snake phylogenetic relationships were recovered at both deep and shallow evolutionary depths, demonstrating the usefulness of this multilocus marker system. Discordance was revealed by a parallel comparison between the snake tree based on the multilocus marker system and that based on only the mitochondrial loci, highlighting the necessity of using multiple types of markers to better understand the snake evolutionary histories. The divergence times of different snake groups were estimated with the nuclear data set. Our comprehensive snake tree not only confirms many important nodes inferred in previous studies but also contributes new insights into many snake phylogenetic relationships. Suggestions are made for the current Chinese snake taxonomy.

journal_name

Mol Phylogenet Evol

authors

Li JN,Liang D,Wang YY,Guo P,Huang S,Zhang P

doi

10.1016/j.ympev.2020.106807

subject

Has Abstract

pub_date

2020-07-01 00:00:00

pages

106807

eissn

1055-7903

issn

1095-9513

pii

S1055-7903(20)30079-8

journal_volume

148

pub_type

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