Haplotype-phased genome assemblies and annotation of the northern white-cheeked gibbon (Nomascus leucogenys).

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-11-25 DOI:10.1038/s41597-024-04073-7
Zhonglai Luo, Libo Jiang, Jianing Xu, Jinhuan Wang, Wenhui Nie, Zemin Ning, Fengtang Yang
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Abstract

Nomascus leucogenys is a critically endangered species of small apes. Here, we sequenced and assembled the male genome of N. leucogenys, using PacBio and Hi-C datasets, with a particular focus on its Y-chromosome. The resulting high-quality haplotype-phased assemblies are at chromosome-scale, with scaffold/contig N50 values of 124.2/102.2 Mb for Haplotype 1 and 121.2/85.67 Mb for Haplotype 2. The assembled Y-chromosome spans 16.06 Mb. BUSCO assessment indicated completeness scores exceeding 95%. We predicted 18,925 protein-coding genes (23,783 mRNAs), including 58 genes on the Y-chromosome. Approximately 50% of the genome comprises repetitive elements. These comprehensive genome datasets will serve as a valuable resource for future studies on the genetics and protection of gibbons and improve our understanding on the evolution of Y-chromosome-related genes in primates.

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Nomascus leucogenys是一种极度濒危的小型类人猿物种。在这里,我们利用 PacBio 和 Hi-C 数据集对 N. leucogenys 的雄性基因组进行了测序和组装,并特别关注其 Y 染色体。所得到的高质量单倍型分阶段组装结果达到了染色体规模,单倍型1的支架/连接体N50值为124.2/102.2 Mb,单倍型2的支架/连接体N50值为121.2/85.67 Mb。组装的 Y 染色体跨度为 16.06 Mb。BUSCO 评估显示完整性得分超过 95%。我们预测了 18,925 个编码蛋白质的基因(23,783 个 mRNA),包括 Y 染色体上的 58 个基因。约50%的基因组由重复元件组成。这些全面的基因组数据集将成为今后研究长臂猿遗传学和保护的宝贵资源,并将提高我们对灵长类动物Y染色体相关基因进化的认识。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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