five

A genomic perspective on the evolutionary diversification of turtles

收藏
Mendeley Data2024-05-17 更新2024-06-27 收录
下载链接:
https://zenodo.org/records/5888715
下载链接
链接失效反馈
官方服务:
资源简介:
To examine phylogenetic heterogeneity in turtle evolution, we collected thousands of high-confidence single-copy orthologs from 19 genome assemblies representative of extant turtle diversity and estimated a phylogeny with multispecies coalescent and concatenated partitioned methods. We also collected next-generation sequences from 26 turtle species and assembled millions of biallelic markers to reconstruct phylogenies based on annotated regions from the western painted turtle (Chrysemys picta bellii) genome (coding regions, introns, untranslated regions, intergenic, and others). We then measured gene tree-species tree discordance, as well as gene and site heterogeneity at each node in the inferred trees, and tested for temporal patterns in phylogenomic conflict across turtle evolution. We found strong and consistent support for all bifurcations in the inferred turtle species phylogenies. However, a number of genes, sites, and genomic features supported alternate relationships between turtle taxa. Our results suggest that gene tree-species tree discordance in these datasets is likely driven by population-level processes such as incomplete lineage sorting. We found very little effect of substitutional saturation on species tree topologies, and no clear phylogenetic patterns in codon usage bias and compositional heterogeneity. There was no correlation between gene and site concordance, node age, and DNA substitution rate across most annotated genomic regions. Our study demonstrates that heterogeneity is to be expected even in well resolved clades such as turtles, and that future phylogenomic studies should aim to sample as much of the genome as possible in order to obtain accurate phylogenies for assessing conservation priorities in turtles.
创建时间:
2023-06-28
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作