首页|An overview of detecting gene-trait associations by integrating GWAS summary statistics and eQTLs

An overview of detecting gene-trait associations by integrating GWAS summary statistics and eQTLs

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Detecting genes that affect specific traits(such as human diseases and crop yields)is important for treating complex diseases and improving crop quality.A genome-wide association study(GWAS)provides new insights and directions for understanding complex traits by identifying important single nucleotide polymorphisms.Many GWAS summary statistics data related to various complex traits have been gathered recently.Studies have shown that GWAS risk loci and expression quantitative trait loci(eQTLs)often have a lot of overlaps,which makes gene expression gradually become an important intermediary to reveal the regulatory role of GWAS.In this review,we review three types of gene-trait association detection methods of integrating GWAS summary statistics and eQTLs data,namely colocalization methods,tran-scriptome-wide association study-oriented approaches,and Mendelian randomization-related methods.At the theoretical level,we dis-cussed the differences,relationships,advantages,and disadvantages of various algorithms in the three kinds of gene-trait association detection methods.To further discuss the performance of various methods,we summarize the significant gene sets that influence high-density lipoprotein,low-density lipoprotein,total cholesterol,and triglyceride reported in 16 studies.We discuss the performance of various algorithms using the datasets of the four lipid traits.The advantages and limitations of various algorithms are analyzed based on experi-mental results,and we suggest directions for follow-up studies on detecting gene-trait associations.

gene-trait associationGWASeQTLcolocalizationtranscriptome-wide association study(TWAS)Mendelian randomization(MR)

Yang Zhang、Mengyao Wang、Zhenguo Li、Xuan Yang、Keqin Li、Ao Xie、Fang Dong、Shihan Wang、Jianbing Yan、Jianxiao Liu

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National Key Laboratory of Crop Genetic Improvement,Huazhong Agricultural University,Wuhan 430070,China

Key Laboratory of Smart Farming for Agricultural Animals,Huazhong Agricultural University,Wuhan 430070,China

Hubei Key Laboratory of Agricultural Bioinformatics,Huazhong Agricultural University,Wuhan 430070,China

College of Informatics,Huazhong Agricultural University,Wuhan 430070,China

College of Life Sciences,Nankai University,Tianjin 300071,China

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National Key Research and Development Program of ChinaFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesMajor Project of Hubei Hongshan LaboratoryMajor Science and Technology Project of Hubei ProvinceYingzi Tech & Huazhong Agricultural University Intelligent Research Institute of Food Health

2022YFD12015042662022YLYJ0102021ZKPY0182662021JC008SZYJY20210032022HSZD0312021AFB002IRIFH202209

2024

10.1007/s11427-023-2522-8

中国科学:生命科学(英文版)
中国科学院

中国科学:生命科学(英文版)

CSTPCD
影响因子：0.806
ISSN：1674-7305
年,卷(期)：2024.67(6)
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