Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds

文献类型： 外文期刊

第一作者： Ren, Pengwei

作者： Ren, Pengwei;Peng, Yongdong;Yang, Liu;Khan, Muhammad Zahoor;Jing, Yadi;Zhang, Meixia;Liu, Xiang;Zhu, Mingxia;Qi, Chao;Liu, Zhansheng;Zhang, Shuer;Zheng, Nenzhu;Zhu, Zhiming

作者机构：

关键词： Breed identification; Duck; Population genetic structure; Whole genome resequencing; Selection signals

期刊名称：BMC GENOMICS （ 影响因子：3.7； 五年影响因子：4.2 ）

ISSN： 1471-2164

年卷期： 2025 年 26 卷 1 期

页码：

收录情况： SCI

摘要： BackgroundShandong's local duck breeds are renowned for their outstanding egg-laying performance and are regarded as valuable assets within China's waterfowl germplasm. Understanding the genetic characteristics of these populations, along with monitoring and conserving their genetic diversity, is of paramount importance. In this study, we analyzed the genetic diversity, population structure, and genetic characteristic of 89 ducks, including the Weishan Partridge (WS, n = 30), Matahu (MT, n = 29), and Wendeng Black (WD, n = 30), using genome resequencing data. We also used a random forest model algorithm to identify specific breed-identification SNPs, ensuring accurate differentiation of the three breeds.ResultsThe findings of this study revealed that WS ducks exhibited higher genetic diversity compared to the other two breeds. This may be related to their larger group size and level of inbreeding. Notice that HO values larger than HE values for all three species are associated with random mating patterns, reduced selection pressure, or recovery from historical bottleneck events. Additionally, the WS and MT breeds were found to be closely related, possibly sharing a common ancestral group, while both breeds were genetically distinct from the WD breed. After comparing with meat duck breeds (BJ, CV, ML), we identified several potential functional genes (notably TP63, BMP3, and ACACA) associated with key economic traits, including growth and development, muscle quality, reproductive performance, and disease resistance. Using top 60 feature selected SNPs, the random forest classification model successfully identified different breeds of ducks under the study with 96.2% accuracy.ConclusionsThis study, utilizing genome sequencing data and machine learning algorithms, provides a comprehensive evaluation of the genetic resources of Shandong's local duck breeds. It highlights the distinct genetic characteristics of the three breeds, providing valuable insights and a theoretical foundation for the conservation and sustainable utilization of Shandong's local duck genetic resources.

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