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eQTL Studies: from Bulk Tissues to Single Cells
An expression quantitative trait locus (eQTL) is a chromosomal region where genetic variants are associated with the expression levels of certain genes that can be both nearby or distant. The identifications of eQTLs for different tissues, cell types, and contexts have led to better understanding of...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980190/ https://www.ncbi.nlm.nih.gov/pubmed/36866231 |
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author | Zhang, Jingfei Zhao, Hongyu |
author_facet | Zhang, Jingfei Zhao, Hongyu |
author_sort | Zhang, Jingfei |
collection | PubMed |
description | An expression quantitative trait locus (eQTL) is a chromosomal region where genetic variants are associated with the expression levels of certain genes that can be both nearby or distant. The identifications of eQTLs for different tissues, cell types, and contexts have led to better understanding of the dynamic regulations of gene expressions and implications of functional genes and variants for complex traits and diseases. Although most eQTL studies to date have been performed on data collected from bulk tissues, recent studies have demonstrated the importance of cell-type-specific and context-dependent gene regulations in biological processes and disease mechanisms. In this review, we discuss statistical methods that have been developed to enable the detections of cell-type-specific and context-dependent eQTLs from bulk tissues, purified cell types, and single cells. We also discuss the limitations of the current methods and future research opportunities. |
format | Online Article Text |
id | pubmed-9980190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cornell University |
record_format | MEDLINE/PubMed |
spelling | pubmed-99801902023-03-03 eQTL Studies: from Bulk Tissues to Single Cells Zhang, Jingfei Zhao, Hongyu ArXiv Article An expression quantitative trait locus (eQTL) is a chromosomal region where genetic variants are associated with the expression levels of certain genes that can be both nearby or distant. The identifications of eQTLs for different tissues, cell types, and contexts have led to better understanding of the dynamic regulations of gene expressions and implications of functional genes and variants for complex traits and diseases. Although most eQTL studies to date have been performed on data collected from bulk tissues, recent studies have demonstrated the importance of cell-type-specific and context-dependent gene regulations in biological processes and disease mechanisms. In this review, we discuss statistical methods that have been developed to enable the detections of cell-type-specific and context-dependent eQTLs from bulk tissues, purified cell types, and single cells. We also discuss the limitations of the current methods and future research opportunities. Cornell University 2023-02-22 /pmc/articles/PMC9980190/ /pubmed/36866231 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Zhang, Jingfei Zhao, Hongyu eQTL Studies: from Bulk Tissues to Single Cells |
title | eQTL Studies: from Bulk Tissues to Single Cells |
title_full | eQTL Studies: from Bulk Tissues to Single Cells |
title_fullStr | eQTL Studies: from Bulk Tissues to Single Cells |
title_full_unstemmed | eQTL Studies: from Bulk Tissues to Single Cells |
title_short | eQTL Studies: from Bulk Tissues to Single Cells |
title_sort | eqtl studies: from bulk tissues to single cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980190/ https://www.ncbi.nlm.nih.gov/pubmed/36866231 |
work_keys_str_mv | AT zhangjingfei eqtlstudiesfrombulktissuestosinglecells AT zhaohongyu eqtlstudiesfrombulktissuestosinglecells |