Genome-wide DNA methylation analysis reveals different methylation patterns in Chinese indigenous sheep with different type of tail

Frontiers in Veterinary Science

Veterinary Science

Minna Li¹  Suli Fang¹  Xaioyu Huang¹  Zhu Caiye¹  Yan Luo²  Shuzhen Song³ 

[1] College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China;Gansu Institute of Animal Science and Veterinary Medicine, Pingliang, China;Institute of Animal and Pasture Science and Green Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu, China;

关键词: sheep;    tail type;    tail fat deposition;    DNA methylation;    genome;   

DOI  :  10.3389/fvets.2023.1125262

 received in 2022-12-16, accepted in 2023-04-13,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundThe study was aimed to analyze the difference of genome-wide DNA differential methylation in Lanzhou Large-tailed sheep, Altay sheep and Tibetan sheep, which the typical breeds with different type tails, as to screen the differentially methylated genes (DMGs) that affect the type of tails.MethodsIn this study, three Lanzhou Large-tailed sheep, three Altay sheep and three Tibetan sheep were detected by whole genome bisulfite sequencing (WGBS). The degree of genome-wide DNA methylation, differentially methylated regions (DMRs) and DMGs were analyzed. The candidate genes affecting the tail type of sheep were identified by GO and KEGG pathway enrichment analysis of DMGs.Resultswe identified 68,603 different methylated regions (DMCs) and 75 differentially methylated genes (DMGs) associated with these DMCs. Functional analysis showed that these DMGs were mainly enriched in biological process, cellular component and molecular function, Some of the genes in these pathways are involved in fat metabolism: NFATC4, LPIN2, MGAT2 and MAT2B.ConclusionOur results may help to further understand the epigenetic regulation mechanisms of deposition of fat in the tail of sheep and provide new basic data for the study of local sheep.

【 授权许可】

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Copyright © 2023 Caiye, Song, Li, Huang, Luo and Fang.