five

Genome, annotations and SNPs for the green peafowl and associated scripts

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.ffbg79ctc
下载链接
链接失效反馈
官方服务:
资源简介:
Both anthropogenic impacts and historical climate change could contribute to population decline and species extinction, but their relative importance has yet to be determined. Emerging approaches based on genomic, climatic and anthropogenic data provide a promising analytical framework to address this question. This study applied such an integrative approach to examine potential drivers for endangerment of the green peafowl (Pavo muticus). Several demographic reconstructions based on population genomes congruently retrieved a drastic population declination since the mid-Holocene. Furthermore, comparison between historical and modern genomes suggested genetic diversity decrease during the last 50 years. However, climate-based ecological niche models predicted general range stationarity during these periods and imply little impact of climate change. Further analyses suggested that human activity intensities were negatively correlated with the green peafowl’s effective population sizes and significantly associated with its survival statuses (extirpation or persistence). Archaeological and historical records corroborate the critical role of humans, leaving the footprint of low genomic diversity and high inbreeding in the surviving populations. This study sheds light on the potential deep-time effects of human disturbance on species endangerment and on the whole, offers immediately a multi-evidential approach in examining underlying forces for population declines. Methods The pseudo-chromosomes were generated by mapping assembled scaffolds of the green peafowl's genome assembly (GenBank accession: JACDJE000000000) into of the chicken assembly (GenBank accession: GCA_000002315.5, hereafter the chicken genome) via synteny using Chromosemble in Satsuma v2.0. The annotations were obtained using MAKER v2.31.10.
创建时间:
2021-03-03
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