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Deciphering the Genetic Landscape: Insights Into the Genomic Signatures of Changle Goose.

Authors :
Chen, Hao
Wu, Yan
Zhu, Yihao
Luo, Keyi
Zheng, Sumei
Tang, Hongbo
Xuan, Rui
Huang, Yuxuan
Li, Jiawei
Xiong, Rui
Fang, Xinyan
Wang, Lei
Gong, Yujie
Miao, Junjie
Zhou, Jing
Tan, Hongli
Wang, Yanan
Wu, Liping
Ouyang, Jing
Huang, Min
Source :
Evolutionary Applications. Aug2024, Vol. 17 Issue 8, p1-12. 12p.
Publication Year :
2024

Abstract

The Changle goose (CLG), a Chinese indigenous breed, is celebrated for its adaptability, rapid growth, and premium meat quality. Despite its agricultural value, the exploration of its genomic attributes has been scant. Our study entailed whole‐genome resequencing of 303 geese across CLG and five other Chinese breeds, revealing distinct genetic diversity metrics. We discovered significant migration events from Xingguo gray goose to CLG and minor gene flow between them. We identified genomic regions through selective sweep analysis, correlating with CLG's unique traits. An elevated inbreeding coefficient in CLG, alongside reduced heterozygosity and rare single nucleotide polymorphisms (RSNPs), suggests a narrowed genetic diversity. Genomic regions related to reproduction, meat quality, and growth were identified, with the GATA3 gene showing strong selection signals for meat quality. A non‐synonymous mutation in the Sloc2a1 gene, which is associated with reproductive traits in the CLG, exhibited significant differences in allelic frequency. The roles of CD82, CDH8, and PRKAB1 in growth and development, alongside FABP4, FAF1, ESR1, and AKAP12 in reproduction, were highlighted. Additionally, Cdkal1 and Mfsd14a may influence meat quality. This comprehensive genetic analysis underpins the unique genetic makeup of CLG, providing a basis for its conservation and informed breeding strategies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17524563
Volume :
17
Issue :
8
Database :
Academic Search Index
Journal :
Evolutionary Applications
Publication Type :
Academic Journal
Accession number :
179320891
Full Text :
https://doi.org/10.1111/eva.13768