five

Brooding phylogenomics: Target-capture probe sets for the analysis of ultraconserved elements in the Peracarida

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.4xgxd25nf
下载链接
链接失效反馈
官方服务:
资源简介:
Sequencing via target capture is becoming an important phylogenetic tool that has been used to great effect with organisms such as insects, arachnids, and various vertebrate taxa. However, other taxa, such as the Crustacea, have received limited genomic attention despite the amount of diversity present within the taxon and the intensity of research on this group. Here we describe generalized probe sets targeting ultraconserved elements (UCEs) for members of the crustacean orders Amphipoda and Isopoda in the superorder Peracarida. These probe sets employ 50-100,000 probes targeting up to 10,000 UCE loci. In-silico analysis of these probe sets recovered an average of 5,087 UCE loci; an average of 4,633 unique loci were retained post-filtering. Phylogenetic analysis of this dataset resulted in well-supported trees that align with previously reconstructed relationships among the taxa selected, while also providing resolution of previously uncertain nodes. Following the in-silico analysis, an in vitro analysis targeting members of the amphipod families Crangonyctidae and Gammaridae was conducted. This analysis extracted up to 4,864 unique loci from the taxa sequenced, with an average of 1,897 loci among all taxa. Phylogenetic analysis of the data generated in vitro resulted in well-supported trees that were resolved at both shallow and deep taxonomic levels. Both analyses demonstrate the utility of these probe sets for phylogenomic research within the Peracarida. Additional attention to members of the superorder using target enrichment will doubtlessly assist in resolving poorly understood aspects of their evolutionary history and expand current knowledge of this group.
创建时间:
2025-11-26
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