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

Citation

Li, Jiang-Ni et al. (2020), A large-scale systematic framework of Chinese snakes based on a unified multilocus marker system, Dryad, Dataset, https://doi.org/10.5061/dryad.t9g44v3

Abstract

Snakes are one of the most diverse groups of terrestrial vertebrates, with approximately 3500 extant species, some of which are closely related to human life. A robust phylogeny and taxonomy of snakes is crucial for us to know, study, protect and make use of them. For a large group such as snakes, cross-study data utilization is important which can be facilitated by standardization of the loci used for systematic analyses. In this study, we combined 5 mitochondrial markers, 19 vertebrate-universal nuclear protein coding (NPC) markers and 72 snake-specific noncoding intron markers, and generated a unified multilocus marker system for studies of snake systematics. This marker system is an addition to the squamate conserved locus set compiled for large-scale sequence capture experiments. We applied this marker system to over 440 snake samples and constructed the currently most comprehensive systematics 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 our multilocus marker system and that based on only the mitochondrial loci, highlighting the necessity of using multiple marker types to better understand the snake evolutionary histories. The divergence times of different snake groups were estimated with the multilocus data set. Our comprehensive snake tree not only confirms many important nodes inferred in previous studies but also contributes new insights into the phylogenetic relationships among snakes. Suggestions are made for the current snake taxonomy.

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Funding

National Natural Science Foundation of China, Award: 31471968

National Natural Science Foundation of China, Award: 31601847

National Natural Science Foundation of China, Award: 31672266

Natural Science Foundation of Guangdong Province, Award: 2017A030313160

Natural Science Foundation of Guangdong Province, Award: 2019A1515010729

National Youth Talent Support Program, China, Award: W02070133