Evidence map›Paper›PMID 30014850›Full record

ArticleeLife2018

Genetics of

Frank Wolfgang Albert, Joshua S Bloom, Jake Siegel, Laura Day, Leonid Kruglyak

Abstract read
In one paragraph

Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers.

0numbers the graph read from it
0cells of the map it votes in
126citing 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

126 citing papers in PubMed.

  1. Article
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  15. bioRxiv : the preprint server for biology · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

66 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

5 authors.

Frank Wolfgang Albert *Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, United States.ORCID http://orcid.org/0000-0002-1380-8063
Joshua S Bloom *Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States.ORCID http://orcid.org/0000-0002-7241-1648
Jake SiegelDepartment of Human Genetics, University of California, Los Angeles, Los Angeles, United States.
Laura DayDepartment of Human Genetics, University of California, Los Angeles, Los Angeles, United States.
Leonid KruglyakDepartment of Human Genetics, University of California, Los Angeles, Los Angeles, United States.ORCID https://orcid.org/0000-0002-8065-3057

Funding

Genomic approaches for dissecting regulatory variationR35GM124676 · NIGMS · UNIVERSITY OF MINNESOTA · PI Frank Wolfgang Albert · 2017 to 2026
$4.6M
Toward comprehensive genetic dissection of complex traits in yeastR01GM102308 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LEONID KRUGLYAK · 2012 to 2026
$3.3M
Howard Hughes Medical Institute InvestigatorNIGMS NIH HHS 1R35GM124676-01NIGMS NIH HHS R01 GM102308NIGMS NIH HHS R01GM102308NIGMS NIH HHS R35 GM124676
6 · The paper itself

Abstract

Heritable variation in gene expression forms a crucial bridge between genomic variation and the biology of many traits. However, most expression quantitative trait loci (eQTLs) remain unidentified. We mapped eQTLs by transcriptome sequencing in 1012 yeast segregants. The resulting eQTLs accounted for over 70% of the heritability of mRNA levels, allowing comprehensive dissection of regulatory variation. Most genes had multiple eQTLs. Most expression variation arose from

Indexed as

Gene Expression Regulation, FungalGenetic VariationQuantitative Trait LociGene Expression ProfilingGene Regulatory NetworksSaccharomyces cerevisiaechromosomeseQTLgene expressiongeneticsgenetic variationgenomicsregulatory variationS. cerevisiae

Identifiers

PMID30014850
PMCPMC6072440

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.