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eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of...

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Autores principales: Kerimov, Nurlan, Tambets, Ralf, Hayhurst, James D., Rahu, Ida, Kolberg, Peep, Raudvere, Uku, Kuzmin, Ivan, Chowdhary, Anshika, Vija, Andreas, Teras, Hans J., Kanai, Masahiro, Ulirsch, Jacob, Ryten, Mina, Hardy, John, Guelfi, Sebastian, Trabzuni, Daniah, Kim-Hellmuth, Sarah, Rayner, William, Finucane, Hilary, Peterson, Hedi, Mosaku, Abayomi, Parkinson, Helen, Alasoo, Kaur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538656/
https://www.ncbi.nlm.nih.gov/pubmed/37721944
http://dx.doi.org/10.1371/journal.pgen.1010932
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author Kerimov, Nurlan
Tambets, Ralf
Hayhurst, James D.
Rahu, Ida
Kolberg, Peep
Raudvere, Uku
Kuzmin, Ivan
Chowdhary, Anshika
Vija, Andreas
Teras, Hans J.
Kanai, Masahiro
Ulirsch, Jacob
Ryten, Mina
Hardy, John
Guelfi, Sebastian
Trabzuni, Daniah
Kim-Hellmuth, Sarah
Rayner, William
Finucane, Hilary
Peterson, Hedi
Mosaku, Abayomi
Parkinson, Helen
Alasoo, Kaur
author_facet Kerimov, Nurlan
Tambets, Ralf
Hayhurst, James D.
Rahu, Ida
Kolberg, Peep
Raudvere, Uku
Kuzmin, Ivan
Chowdhary, Anshika
Vija, Andreas
Teras, Hans J.
Kanai, Masahiro
Ulirsch, Jacob
Ryten, Mina
Hardy, John
Guelfi, Sebastian
Trabzuni, Daniah
Kim-Hellmuth, Sarah
Rayner, William
Finucane, Hilary
Peterson, Hedi
Mosaku, Abayomi
Parkinson, Helen
Alasoo, Kaur
author_sort Kerimov, Nurlan
collection PubMed
description The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.
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spelling pubmed-105386562023-09-29 eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs Kerimov, Nurlan Tambets, Ralf Hayhurst, James D. Rahu, Ida Kolberg, Peep Raudvere, Uku Kuzmin, Ivan Chowdhary, Anshika Vija, Andreas Teras, Hans J. Kanai, Masahiro Ulirsch, Jacob Ryten, Mina Hardy, John Guelfi, Sebastian Trabzuni, Daniah Kim-Hellmuth, Sarah Rayner, William Finucane, Hilary Peterson, Hedi Mosaku, Abayomi Parkinson, Helen Alasoo, Kaur PLoS Genet Research Article The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases. Public Library of Science 2023-09-18 /pmc/articles/PMC10538656/ /pubmed/37721944 http://dx.doi.org/10.1371/journal.pgen.1010932 Text en © 2023 Kerimov et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kerimov, Nurlan
Tambets, Ralf
Hayhurst, James D.
Rahu, Ida
Kolberg, Peep
Raudvere, Uku
Kuzmin, Ivan
Chowdhary, Anshika
Vija, Andreas
Teras, Hans J.
Kanai, Masahiro
Ulirsch, Jacob
Ryten, Mina
Hardy, John
Guelfi, Sebastian
Trabzuni, Daniah
Kim-Hellmuth, Sarah
Rayner, William
Finucane, Hilary
Peterson, Hedi
Mosaku, Abayomi
Parkinson, Helen
Alasoo, Kaur
eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs
title eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs
title_full eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs
title_fullStr eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs
title_full_unstemmed eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs
title_short eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs
title_sort eqtl catalogue 2023: new datasets, x chromosome qtls, and improved detection and visualisation of transcript-level qtls
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538656/
https://www.ncbi.nlm.nih.gov/pubmed/37721944
http://dx.doi.org/10.1371/journal.pgen.1010932
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