Whole-genome sequencing resources of 301 indigenous Tibetan sheep from the Himalayan region
Compared to commercial sheep breeds, Tibetan sheep are exceptionally productive in high-altitude environments. Whole-genome sequencing can elucidate the genetic markers and candidate genes related to such economic traits, greatly accelerating the breeding progress. However, a lack of genome sequence data has hindered the functional gene dissection and genetic improvement of Tibetan sheep. This study presents whole-genome sequencing data from 301 Gamba sheep, a Tibetan national breed raised in extremely high-altitude regions. The data represents 12.3 Tb paired-end sequences generated on a BGI-T7 platform. An average sequencing depth of 13.8X, an average mapping ratio of 94.0%, and an average genome coverage of 99.6% illustrated the high quality of the sequence data. By aligning the sequence data to the sheep reference genome ARS-UI_Ramb_v3.0 with variants filtration, 39,718,985 single nucleotide polymorphisms (SNPs) and 5,275,473 insertions-deletions (InDels) were obtained. Genetic kinship analysis indicated the sample independence and high quality of the selected individuals. This whole-genome dataset significantly enriches public resources for studying the genetic diversity, genomic selection, and environmental adaptations of sheep.
Authors
- Yongju Zhao (ORCID: https://orcid.org/0000-0001-9256-8856)
- Luobu Gesang (ORCID: https://orcid.org/0009-0008-3269-3362)
- Hong Miao (ORCID: https://orcid.org/0000-0003-4590-6781)
- Jikang Zheng
- Pubu Ciren (ORCID: https://orcid.org/0000-0002-9100-7341)
- Jipan Zhang (ORCID: https://orcid.org/0000-0002-3562-4118)
- Mengying Wang (ORCID: https://orcid.org/0000-0001-7591-522X)
- Yangshen Zhang
- Zhaxi Duoji
Institutions
- Tibet University (CN)
- Southwest University (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2025-08-04
- DOI
- https://doi.org/10.1038/s41597-025-05650-0
- Citations
- 1
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.81