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Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain

Dense genotyping approaches have revealed much about the genetic architecture both of gene expression and disease susceptibility. However, assigning causality to genetic variants associated with a transcriptomic or phenotypic trait presents a far greater challenge. The development of epigenomic reso...

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Autores principales: Handel, Adam E., Gallone, Giuseppe, Zameel Cader, M., Ponting, Chris P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351933/
https://www.ncbi.nlm.nih.gov/pubmed/27798116
http://dx.doi.org/10.1093/hmg/ddw369
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author Handel, Adam E.
Gallone, Giuseppe
Zameel Cader, M.
Ponting, Chris P.
author_facet Handel, Adam E.
Gallone, Giuseppe
Zameel Cader, M.
Ponting, Chris P.
author_sort Handel, Adam E.
collection PubMed
description Dense genotyping approaches have revealed much about the genetic architecture both of gene expression and disease susceptibility. However, assigning causality to genetic variants associated with a transcriptomic or phenotypic trait presents a far greater challenge. The development of epigenomic resources by ENCODE, the Epigenomic Roadmap and others has led to strategies that seek to infer the likely functional variants underlying these genome-wide association signals. It is known, for example, that such variants tend to be located within areas of open chromatin, as detected by techniques such as DNase-seq and FAIRE-seq. We aimed to assess what proportion of variants associated with phenotypic or transcriptomic traits in the human brain are located within transcription factor binding sites. The bioinformatic tools, Wellington and HINT, were used to infer transcription factor footprints from existing DNase-seq data derived from central nervous system tissues with high spatial resolution. This dataset was then employed to assess the likely contribution of altered transcription factor binding to both expression quantitative trait loci (eQTL) and genome-wide association study (GWAS) signals. Surprisingly, we show that most haplotypes associated with GWAS or eQTL phenotypes are located outside of DNase-seq footprints. This could imply that DNase-seq footprinting is too insensitive an approach to identify a large proportion of true transcription factor binding sites. Importantly, this suggests that prioritising variants for genome engineering studies to establish causality will continue to be frustrated by an inability of footprinting to identify the causative variant within a haplotype.
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spelling pubmed-53519332017-03-21 Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain Handel, Adam E. Gallone, Giuseppe Zameel Cader, M. Ponting, Chris P. Hum Mol Genet Articles Dense genotyping approaches have revealed much about the genetic architecture both of gene expression and disease susceptibility. However, assigning causality to genetic variants associated with a transcriptomic or phenotypic trait presents a far greater challenge. The development of epigenomic resources by ENCODE, the Epigenomic Roadmap and others has led to strategies that seek to infer the likely functional variants underlying these genome-wide association signals. It is known, for example, that such variants tend to be located within areas of open chromatin, as detected by techniques such as DNase-seq and FAIRE-seq. We aimed to assess what proportion of variants associated with phenotypic or transcriptomic traits in the human brain are located within transcription factor binding sites. The bioinformatic tools, Wellington and HINT, were used to infer transcription factor footprints from existing DNase-seq data derived from central nervous system tissues with high spatial resolution. This dataset was then employed to assess the likely contribution of altered transcription factor binding to both expression quantitative trait loci (eQTL) and genome-wide association study (GWAS) signals. Surprisingly, we show that most haplotypes associated with GWAS or eQTL phenotypes are located outside of DNase-seq footprints. This could imply that DNase-seq footprinting is too insensitive an approach to identify a large proportion of true transcription factor binding sites. Importantly, this suggests that prioritising variants for genome engineering studies to establish causality will continue to be frustrated by an inability of footprinting to identify the causative variant within a haplotype. Oxford University Press 2017-01-01 2016-10-26 /pmc/articles/PMC5351933/ /pubmed/27798116 http://dx.doi.org/10.1093/hmg/ddw369 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Handel, Adam E.
Gallone, Giuseppe
Zameel Cader, M.
Ponting, Chris P.
Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain
title Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain
title_full Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain
title_fullStr Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain
title_full_unstemmed Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain
title_short Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain
title_sort most brain disease-associated and eqtl haplotypes are not located within transcription factor dnase-seq footprints in brain
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351933/
https://www.ncbi.nlm.nih.gov/pubmed/27798116
http://dx.doi.org/10.1093/hmg/ddw369
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