Somaieh Bakhshalizadeh, Saeed Zerehdaran, Karim Hasanpur, A. Javadmanesh
{"title":"鉴定与荷斯坦奶牛乳蛋白差异相关的潜在候选基因:整合 GWAS 和 RNA-Seq 转录组的元分析","authors":"Somaieh Bakhshalizadeh, Saeed Zerehdaran, Karim Hasanpur, A. Javadmanesh","doi":"10.1139/cjas-2023-0108","DOIUrl":null,"url":null,"abstract":"Despite the identification of candidate genes influencing milk protein, the connections between genes and regulatory pathways remains elusive. This study aimed integrate findings from genome wide association studies (GWAS) and RNA sequencing (RNA-Seq) through meta-analysis to pinpoint single nucleotide polymorphisms (SNPs) and genes responsible for high and low protein yield in cows. Previous GWAS and RNA-Seq analyses had identified 663 SNPs and 1,106 genes (P<0.05). 20 SNPs from GWAS, 10 genes from RNA-Seq, and 49 SNP/gene associations from both datasets, were identified using meta-analysis. Meta-analysis validated several SNPs previously identified through GWAS, such as rs135549651 (P=2.6×〖10〗^(-256)), rs109146371 (P=3.1×〖10〗^(-208)), rs109350371 (P=4.0×〖10〗^(-207)), and rs109774038 (P=8.6×〖10〗^(-587)). Genes identified in RNA-Seq experiments, including NR4A1 (P=3.2×〖10〗^(-7)), ATF3 (P=9.6×〖10〗^(-7)), CDH16 (P=9.9×〖10〗^(-7)), VEGFA (P=1.0×〖10〗^(-6)), and SAA3 (P=7.3×〖10〗^(-11)), were confirmed. The combined GWAS and RNA-Seq datasets highlighted CCND2 (P=8.9×〖10〗^(-111)), MAPK15 (P=1.3×〖10〗^(-151)), and CPSF1 (P=1.2×〖10〗^(-306)) as the most significant genes. Additionally, significant GO terms including ionizing radiation (P=1.5×〖10〗^(-4)), nuclear pore cytoplasmic filaments (P=9.4×〖10〗^(-5)), and phenylalanine 4-monooxygenase activity (P=1.4×〖10〗^(-5)) were identified. In conclusion, the integration of GWAS and RNA-Seq, coupled with GO enrichment, allowed identification of candidate SNPs and genes with higher accuracy. These findings improve our knowledge about genomic architecture of milk protein, and enhance evaluation of Holstein cows.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":"31 5","pages":""},"PeriodicalIF":16.4000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of potential candidate genes associated with milk protein differences in Holstein cows: A meta-Analysis integrating GWAS and RNA-Seq transcriptome\",\"authors\":\"Somaieh Bakhshalizadeh, Saeed Zerehdaran, Karim Hasanpur, A. Javadmanesh\",\"doi\":\"10.1139/cjas-2023-0108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite the identification of candidate genes influencing milk protein, the connections between genes and regulatory pathways remains elusive. This study aimed integrate findings from genome wide association studies (GWAS) and RNA sequencing (RNA-Seq) through meta-analysis to pinpoint single nucleotide polymorphisms (SNPs) and genes responsible for high and low protein yield in cows. Previous GWAS and RNA-Seq analyses had identified 663 SNPs and 1,106 genes (P<0.05). 20 SNPs from GWAS, 10 genes from RNA-Seq, and 49 SNP/gene associations from both datasets, were identified using meta-analysis. Meta-analysis validated several SNPs previously identified through GWAS, such as rs135549651 (P=2.6×〖10〗^(-256)), rs109146371 (P=3.1×〖10〗^(-208)), rs109350371 (P=4.0×〖10〗^(-207)), and rs109774038 (P=8.6×〖10〗^(-587)). Genes identified in RNA-Seq experiments, including NR4A1 (P=3.2×〖10〗^(-7)), ATF3 (P=9.6×〖10〗^(-7)), CDH16 (P=9.9×〖10〗^(-7)), VEGFA (P=1.0×〖10〗^(-6)), and SAA3 (P=7.3×〖10〗^(-11)), were confirmed. The combined GWAS and RNA-Seq datasets highlighted CCND2 (P=8.9×〖10〗^(-111)), MAPK15 (P=1.3×〖10〗^(-151)), and CPSF1 (P=1.2×〖10〗^(-306)) as the most significant genes. Additionally, significant GO terms including ionizing radiation (P=1.5×〖10〗^(-4)), nuclear pore cytoplasmic filaments (P=9.4×〖10〗^(-5)), and phenylalanine 4-monooxygenase activity (P=1.4×〖10〗^(-5)) were identified. In conclusion, the integration of GWAS and RNA-Seq, coupled with GO enrichment, allowed identification of candidate SNPs and genes with higher accuracy. 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Identification of potential candidate genes associated with milk protein differences in Holstein cows: A meta-Analysis integrating GWAS and RNA-Seq transcriptome
Despite the identification of candidate genes influencing milk protein, the connections between genes and regulatory pathways remains elusive. This study aimed integrate findings from genome wide association studies (GWAS) and RNA sequencing (RNA-Seq) through meta-analysis to pinpoint single nucleotide polymorphisms (SNPs) and genes responsible for high and low protein yield in cows. Previous GWAS and RNA-Seq analyses had identified 663 SNPs and 1,106 genes (P<0.05). 20 SNPs from GWAS, 10 genes from RNA-Seq, and 49 SNP/gene associations from both datasets, were identified using meta-analysis. Meta-analysis validated several SNPs previously identified through GWAS, such as rs135549651 (P=2.6×〖10〗^(-256)), rs109146371 (P=3.1×〖10〗^(-208)), rs109350371 (P=4.0×〖10〗^(-207)), and rs109774038 (P=8.6×〖10〗^(-587)). Genes identified in RNA-Seq experiments, including NR4A1 (P=3.2×〖10〗^(-7)), ATF3 (P=9.6×〖10〗^(-7)), CDH16 (P=9.9×〖10〗^(-7)), VEGFA (P=1.0×〖10〗^(-6)), and SAA3 (P=7.3×〖10〗^(-11)), were confirmed. The combined GWAS and RNA-Seq datasets highlighted CCND2 (P=8.9×〖10〗^(-111)), MAPK15 (P=1.3×〖10〗^(-151)), and CPSF1 (P=1.2×〖10〗^(-306)) as the most significant genes. Additionally, significant GO terms including ionizing radiation (P=1.5×〖10〗^(-4)), nuclear pore cytoplasmic filaments (P=9.4×〖10〗^(-5)), and phenylalanine 4-monooxygenase activity (P=1.4×〖10〗^(-5)) were identified. In conclusion, the integration of GWAS and RNA-Seq, coupled with GO enrichment, allowed identification of candidate SNPs and genes with higher accuracy. These findings improve our knowledge about genomic architecture of milk protein, and enhance evaluation of Holstein cows.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.