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Whole-genome resequencing reveals genetic diversity and selection signatures of Tongjiang and five goat breeds.

Siyuan Zhan | Jing Luo | Ruiyang Li | Guangyao Li | Linxiang Li | Dandan Li | Tao Zhong | Linjie Wang | Jiazhong Guo | Jiaxue Cao | Hongping Zhang | Li Li
Frontiers in veterinary science | 2025

One of the first livestock that humans domesticated was the goat. They give people access to vital supplies. However, the exploration and conservation of the genetic resources of goats are not comprehensive enough. Here, we generated whole-genome sequencing data for 35 samples from three populations (Tongjiang, Banjiao, and Chuandong white) and downloaded the genome sequence data of 30 individuals from three breeds (Jintang black, Chengdu grey, and Tibetan cashmere) to characterize the genomic variations of Tongjiang and other goat breeds. Among the six goat populations studied, the Tongjiang goat exhibits the highest levels of observed heterozygosity and runs of homozygosity, alongside the lowest inbreeding coefficient. The nucleotide diversity and linkage disequilibrium in this population were observed to be at intermediate levels. The population genetic structure analysis showed that significant differentiation of Tongjiang goats from other goat breeds, as evidenced by their distinct clustering and considerable genetic distance from other groups. Furthermore, based on selective sweeps, we identified positive selection genes in Tongjiang goats, which were probably related to important traits such as development (BMP4), reproduction (HTR1E), meat quality (HDAC9, PITX2, and PDGFD), and immune response (IKBKB and DLG1). Our findings indicate that Tongjiang goats possess elevated genomic diversity and exhibit minimal inbreeding. The unique genetic structure of Tongjiang goats can be partly attributed to the specific geographic conditions of the region. We have identified several selection signatures within the genomic regions of Tongjiang goats, which may play a role in their meat quality and environmental adaptation. All of our findings have the potential to provide an invaluable genomic resource for future genetic research and conservation efforts.

Pubmed ID: 40496916

Research resources used in this publication

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Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


VCFtools (tool)

RRID:SCR_001235

Software package for working with VCF files. Used to provide easily accessible methods for working with complex genetic variation data in the form of VCF files.Implements various utilities for processing Variant Call Format files, including validation, merging, comparing. Provides general Perl API.

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RRID:SCR_001757

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RRID:SCR_001881

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RRID:SCR_002105

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RRID:SCR_006350

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ANNOVAR (tool)

RRID:SCR_012821

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TreeBeST (tool)

RRID:SCR_018173

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RRID:SCR_025825

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