Evidence map›Paper›PMID 27197214›Full record

ArticleGenome research2016

Impact of the X Chromosome and sex on regulatory variation.

Kimberly R Kukurba, Princy Parsana, Brunilda Balliu, Kevin S Smith, Zachary Zappala, David A Knowles, Marie-Julie Favé, Joe R Davis, Xin Li, Xiaowei Zhu and 9 more

Abstract read
In one paragraph

Article in Genome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed, 3 pooled it
–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

68 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Review
  20. Article

8 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Kimberly R KukurbaDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA;
Princy ParsanaDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA;
Brunilda BalliuDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA;
Kevin S SmithDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA;
Zachary ZappalaDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA;
David A KnowlesDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA;
Marie-Julie FavéSainte-Justine University Hospital Research Centre, Department of Pediatrics, University of Montreal, Montreal, Québec H3T 1J4, Canada;
Joe R DavisDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA;
Xin LiDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA;
Xiaowei ZhuDepartment of Psychiatry, Stanford University School of Medicine, Stanford, California 94305, USA;
James B PotashDepartment of Psychiatry, University of Iowa Hospitals & Clinics, Iowa City, Iowa 52242, USA;
Myrna M WeissmanDepartment of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, New York 10032, USA;
Jianxin ShiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland 20892, USA;
Anshul KundajeDepartment of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA; Department of Computer Science, Stanford University, Stanford, California 94305, USA;
Douglas F LevinsonDepartment of Psychiatry, Stanford University School of Medicine, Stanford, California 94305, USA;
Philip AwadallaSainte-Justine University Hospital Research Centre, Department of Pediatrics, University of Montreal, Montreal, Québec H3T 1J4, Canada;
Sara MostafaviDepartment of Statistics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
Alexis BattleDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA; ajbattle@cs.jhu.edu smontgom@stanford.edu.
Stephen B MontgomeryDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA; Department of Computer Science, Stanford University, Stanford, California 94305, USA; ajbattle@cs.jhu.edu smontgom@stanford.edu.

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
Methods for high-resolution analysis of genetic effects on gene expressionR01MH101814 · NIMH · UNIVERSITY OF GENEVA · PI BUSTAMANTE, CARLOS DANIEL, DERMITZAKIS, EMMANOUIL · 2013 to 2016
$2.3M
Predicting causal non-coding variants in a founder populationR01HG008150 · NHGRI · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2015 to 2017
$1.4M
NHGRI NIH HHS R01 HG008150NIMH NIH HHS R01 MH101814
6 · The paper itself

Abstract

The X Chromosome, with its unique mode of inheritance, contributes to differences between the sexes at a molecular level, including sex-specific gene expression and sex-specific impact of genetic variation. Improving our understanding of these differences offers to elucidate the molecular mechanisms underlying sex-specific traits and diseases. However, to date, most studies have either ignored the X Chromosome or had insufficient power to test for the sex-specific impact of genetic variation. By analyzing whole blood transcriptomes of 922 individuals, we have conducted the first large-scale, genome-wide analysis of the impact of both sex and genetic variation on patterns of gene expression, including comparison between the X Chromosome and autosomes. We identified a depletion of expression quantitative trait loci (eQTL) on the X Chromosome, especially among genes under high selective constraint. In contrast, we discovered an enrichment of sex-specific regulatory variants on the X Chromosome. To resolve the molecular mechanisms underlying such effects, we generated chromatin accessibility data through ATAC-sequencing to connect sex-specific chromatin accessibility to sex-specific patterns of expression and regulatory variation. As sex-specific regulatory variants discovered in our study can inform sex differences in heritable disease prevalence, we integrated our data with genome-wide association study data for multiple immune traits identifying several traits with significant sex biases in genetic susceptibilities. Together, our study provides genome-wide insight into how genetic variation, the X Chromosome, and sex shape human gene regulation and disease.

Indexed as

TranscriptomeChromosomes, Human, XFemaleGene Expression ProfilingGene Expression RegulationGenetic Predisposition to DiseaseGenome, HumanHumansMalePolymorphism, Single NucleotideQuantitative Trait LociSex Characteristics

Identifiers

PMID27197214
PMCPMC4889977

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.