Evidence map›Paper›PMID 37873117›Full record

ArticlebioRxiv : the preprint server for biology2023

Allele biased transcription factor binding across human brain regions gives mechanistic insight into eQTLs.

Belle A Moyers, Jacob M Loupe, Stephanie A Felker, James M J Lawlor, Ashlyn G Anderson, Ivan Rodriguez-Nunez, William E Bunney, Blynn G Bunney, Preston M Cartagena, Adolfo Sequeira and 5 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 3 institutions in 1 country.

Belle A MoyersHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
Jacob M LoupeHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
Stephanie A FelkerHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
James M J LawlorHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
Ashlyn G AndersonHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
Ivan Rodriguez-NunezHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
William E BunneyDepartment of Psychiatry and Human Behavior, University of California, Irvine CA, USA.
Blynn G BunneyDepartment of Psychiatry and Human Behavior, University of California, Irvine CA, USA.
Preston M CartagenaDepartment of Psychiatry and Human Behavior, University of California, Irvine CA, USA.
Adolfo SequeiraDepartment of Psychiatry and Human Behavior, University of California, Irvine CA, USA.
Stanley J WatsonThe Michigan Neuroscience Institute, University of Michigan, Ann Arbor MI, USA.
Huda AkilThe Michigan Neuroscience Institute, University of Michigan, Ann Arbor MI, USA.
Eric M MendenhallHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
Gregory M CooperHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
Richard M MyersHudsonAlpha Institute for Biotechnology, Huntsville AL, USA.
HudsonAlpha Institute for Biotechnology · USUniversity of California, Irvine · USUniversity of Michigan · US

Funding

Transcription factor function in healthy and psychiatric disorder-affected brainsR01MH110472 · NIMH · HUDSON-ALPHA INSTITUTE FOR BIOTECHNOLOGY · PI COOPER, GREGORY MICHAEL, MYERS, RICHARD M · 2017 to 2021
$6.0M
NIMH NIH HHS R01 MH110472
6 · The paper itself

Abstract

Transcription Factors (TFs) influence gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because genomic localization of TFs is in part driven by TF recognition of DNA sequence, variation in TF binding sites can disrupt TF-DNA associations and affect gene regulation. To identify variants that impact TF binding in human brain tissues, we quantified allele bias for 93 TFs analyzed with ChIP-seq experiments of multiple structural brain regions from two donors. Using graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signal between alleles at heterozygous variants within each tissue sample from each donor. Comparison of results from different brain regions within donors and the same regions between donors provided measures of allele bias reproducibility. We identified thousands of DNA variants that show reproducible bias in ChIP-seq for at least one TF. We found that alleles that are rarer in the general population were more likely than common alleles to exhibit large biases, and more frequently led to reduced TF binding. Combining ChIP-seq with RNA-seq, we identified TF-allele interaction biases with RNA bias in a phased allele linked to 6,709 eQTL variants identified in GTEx data, 3,309 of which were found in neural contexts. Our results provide insights into the effects of both common and rare variation on gene regulation in the brain. These findings can facilitate mechanistic understanding of cis-regulatory variation associated with biological traits, including disease.

Identifiers

PMID37873117
PMCPMC10592666
OpenAlexW4387461801

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.