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From genetic associations to genes: methods, applications, and challenges.
Qi, Ting; Song, Liyang; Guo, Yazhou; Chen, Chang; Yang, Jian.
Afiliação
  • Qi T; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China. Electronic address: qiting@westlake.edu.cn.
  • Song L; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
  • Guo Y; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
  • Chen C; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
  • Yang J; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China. Electronic address: jian.yang@westlake.edu.cn.
Trends Genet ; 40(8): 642-667, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38734482
ABSTRACT
Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Locos de Características Quantitativas / Estudo de Associação Genômica Ampla Limite: Humans Idioma: En Revista: Trends Genet Assunto da revista: GENETICA Ano de publicação: 2024 Tipo de documento: Article País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Locos de Características Quantitativas / Estudo de Associação Genômica Ampla Limite: Humans Idioma: En Revista: Trends Genet Assunto da revista: GENETICA Ano de publicação: 2024 Tipo de documento: Article País de publicação: Reino Unido