Mei Kong , Jingwen Dou , Hong Liu , Jing Xu , Zhuqing Zheng , Aishao Shangguan , Zhenshuang Tang , Xiaolong Qi , Saixian Zhang , Yue Xiang , Yuhua Fu , Xiaoyong Du , Xinyun Li , Liangliang Fu , Zhonglin Tang , Jingjin Li
{"title":"Identification of blacklist regions in cattle and pig genomes","authors":"Mei Kong , Jingwen Dou , Hong Liu , Jing Xu , Zhuqing Zheng , Aishao Shangguan , Zhenshuang Tang , Xiaolong Qi , Saixian Zhang , Yue Xiang , Yuhua Fu , Xiaoyong Du , Xinyun Li , Liangliang Fu , Zhonglin Tang , Jingjin Li","doi":"10.1016/j.ygeno.2025.111027","DOIUrl":null,"url":null,"abstract":"<div><div>Cattle and pigs are important farm animals and biomedical models for studying human development and diseases. Accurate annotation of their cis-regulatory elements is essential for advancing breeding strategies and biological research. Identifying these elements typically relies on ChIP-seq data, which profiles histone modifications and transcription factors. Although some large-scale ChIP-seq projects have decoded functional genomes in cattle and pigs, no comprehensive blacklist identification has been performed. In this study, we systematically identified and evaluated blacklist regions in cattle and pig genomes using the ENCODE pipeline. We annotated 126.8 Mb and 99.9 Mb of blacklist regions in cattle and pigs, respectively. We found that removing these blacklist regions is a critical quality control measure that can enhance the reliability of ChIP-seq analysis. Overall, our results provide a valuable resource for farm animal research, and we propose eliminating these problematic regions to reduce abnormally high signals and improve downstream analyses.</div></div>","PeriodicalId":12521,"journal":{"name":"Genomics","volume":"117 3","pages":"Article 111027"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0888754325000436","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Cattle and pigs are important farm animals and biomedical models for studying human development and diseases. Accurate annotation of their cis-regulatory elements is essential for advancing breeding strategies and biological research. Identifying these elements typically relies on ChIP-seq data, which profiles histone modifications and transcription factors. Although some large-scale ChIP-seq projects have decoded functional genomes in cattle and pigs, no comprehensive blacklist identification has been performed. In this study, we systematically identified and evaluated blacklist regions in cattle and pig genomes using the ENCODE pipeline. We annotated 126.8 Mb and 99.9 Mb of blacklist regions in cattle and pigs, respectively. We found that removing these blacklist regions is a critical quality control measure that can enhance the reliability of ChIP-seq analysis. Overall, our results provide a valuable resource for farm animal research, and we propose eliminating these problematic regions to reduce abnormally high signals and improve downstream analyses.
期刊介绍:
Genomics is a forum for describing the development of genome-scale technologies and their application to all areas of biological investigation.
As a journal that has evolved with the field that carries its name, Genomics focuses on the development and application of cutting-edge methods, addressing fundamental questions with potential interest to a wide audience. Our aim is to publish the highest quality research and to provide authors with rapid, fair and accurate review and publication of manuscripts falling within our scope.