Evidence map›Paper›PMID 35147078›Full record

ArticleeLife2022

Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast.

Alex N Nguyen Ba, Katherine R Lawrence, Artur Rego-Costa, Shreyas Gopalakrishnan, Daniel Temko, Franziska Michor, Michael M Desai

Open access · goldAbstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
13.5field-weighted citation impact, top 1% of its field
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

50 citing papers in PubMed, 79 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Evolutionary cell biology comes of age.Journal of cell science · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

7 authors at 1 institution in 2 countries.

Alex N Nguyen Ba *Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.ORCID 0000-0003-1357-6386
Katherine R Lawrence *NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States.
Artur Rego-Costa *Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.ORCID 0000-0001-9604-4208
Shreyas GopalakrishnanDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.
Daniel TemkoDepartment of Data Science, Dana-Farber Cancer Institute, Boston, United States.
Franziska MichorDepartment of Data Science, Dana-Farber Cancer Institute, Boston, United States.
Michael M DesaiDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States.ORCID 0000-0002-9581-1150
Harvard University · US

Funding

Project 3: Single Cell Measures of Intratumor Diversity for Optimal Breast Cancer TherapyU54CA193461 · NCI · DANA-FARBER CANCER INST · PI MICHOR, FRANZISKA · 2015 to 2020
$11.2M
Microbial Adaptation and the Statistics of Epistasis and PleiotropyR01GM104239 · NIGMS · HARVARD UNIVERSITY · PI DESAI, MICHAEL M · 2013 to 2025
$4.5M
NCI NIH HHS U54 CA193461NIGMS NIH HHS R01 GM104239
6 · The paper itself

Abstract

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.

Indexed as

Genome-Wide Association StudyMultifactorial InheritanceChromosome MappingEpistasis, GeneticGenotypePhenotypeQuantitative Trait LociSaccharomyces cerevisiaeepistasisevolutionary biologygeneticsgenomicspleiotropypolygenic traitsquantitative trait lociS. cerevisiae

Identifiers

PMID35147078
PMCPMC8979589
OpenAlexW4225472713

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.