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QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes

Deciphering the fine-scale molecular mechanisms that shape the genetic effects at disease-associated loci from genome-wide association studies (GWAS) remains challenging. The key avenue is to identify the essential molecular phenotypes that mediate the causal variant and disease under particular bio...

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Autores principales: Huang, Dandan, Feng, Xiangling, Yang, Hongxi, Wang, Jianhua, Zhang, Wenwen, Fan, Xutong, Dong, Xiaobao, Chen, Kexin, Yu, Ying, Ma, Xin, Yi, Xianfu, Li, Mulin Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825467/
https://www.ncbi.nlm.nih.gov/pubmed/36330927
http://dx.doi.org/10.1093/nar/gkac1020
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author Huang, Dandan
Feng, Xiangling
Yang, Hongxi
Wang, Jianhua
Zhang, Wenwen
Fan, Xutong
Dong, Xiaobao
Chen, Kexin
Yu, Ying
Ma, Xin
Yi, Xianfu
Li, Mulin Jun
author_facet Huang, Dandan
Feng, Xiangling
Yang, Hongxi
Wang, Jianhua
Zhang, Wenwen
Fan, Xutong
Dong, Xiaobao
Chen, Kexin
Yu, Ying
Ma, Xin
Yi, Xianfu
Li, Mulin Jun
author_sort Huang, Dandan
collection PubMed
description Deciphering the fine-scale molecular mechanisms that shape the genetic effects at disease-associated loci from genome-wide association studies (GWAS) remains challenging. The key avenue is to identify the essential molecular phenotypes that mediate the causal variant and disease under particular biological conditions. Therefore, integrating GWAS signals with context-specific quantitative trait loci (QTLs) (such as different tissue/cell types, disease states, and perturbations) from extensive molecular phenotypes would present important strategies for full understanding of disease genetics. Via persistent curation and systematic data processing of large-scale human molecular trait QTLs (xQTLs), we updated our previous QTLbase database (now QTLbase2, http://mulinlab.org/qtlbase) to comprehensively analyze and visualize context-specific QTLs across 22 molecular phenotypes and over 95 tissue/cell types. Overall, the resource features the following major updates and novel functions: (i) 960 more genome-wide QTL summary statistics from 146 independent studies; (ii) new data for 10 previously uncompiled QTL types; (iii) variant query scope expanded to fit 195 QTL datasets based on whole-genome sequencing; (iv) supports filtering and comparison of QTLs for different biological conditions, such as stimulation types and disease states; (v) a new linkage disequilibrium viewer to facilitate variant prioritization across tissue/cell types and QTL types.
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spelling pubmed-98254672023-01-10 QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes Huang, Dandan Feng, Xiangling Yang, Hongxi Wang, Jianhua Zhang, Wenwen Fan, Xutong Dong, Xiaobao Chen, Kexin Yu, Ying Ma, Xin Yi, Xianfu Li, Mulin Jun Nucleic Acids Res Database Issue Deciphering the fine-scale molecular mechanisms that shape the genetic effects at disease-associated loci from genome-wide association studies (GWAS) remains challenging. The key avenue is to identify the essential molecular phenotypes that mediate the causal variant and disease under particular biological conditions. Therefore, integrating GWAS signals with context-specific quantitative trait loci (QTLs) (such as different tissue/cell types, disease states, and perturbations) from extensive molecular phenotypes would present important strategies for full understanding of disease genetics. Via persistent curation and systematic data processing of large-scale human molecular trait QTLs (xQTLs), we updated our previous QTLbase database (now QTLbase2, http://mulinlab.org/qtlbase) to comprehensively analyze and visualize context-specific QTLs across 22 molecular phenotypes and over 95 tissue/cell types. Overall, the resource features the following major updates and novel functions: (i) 960 more genome-wide QTL summary statistics from 146 independent studies; (ii) new data for 10 previously uncompiled QTL types; (iii) variant query scope expanded to fit 195 QTL datasets based on whole-genome sequencing; (iv) supports filtering and comparison of QTLs for different biological conditions, such as stimulation types and disease states; (v) a new linkage disequilibrium viewer to facilitate variant prioritization across tissue/cell types and QTL types. Oxford University Press 2022-11-04 /pmc/articles/PMC9825467/ /pubmed/36330927 http://dx.doi.org/10.1093/nar/gkac1020 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Huang, Dandan
Feng, Xiangling
Yang, Hongxi
Wang, Jianhua
Zhang, Wenwen
Fan, Xutong
Dong, Xiaobao
Chen, Kexin
Yu, Ying
Ma, Xin
Yi, Xianfu
Li, Mulin Jun
QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
title QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
title_full QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
title_fullStr QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
title_full_unstemmed QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
title_short QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
title_sort qtlbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825467/
https://www.ncbi.nlm.nih.gov/pubmed/36330927
http://dx.doi.org/10.1093/nar/gkac1020
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