Evidence map›Paper›PMID 24326347›Full record

ReviewPhysiological genomics2014

QTL mapping in outbred populations: successes and challenges.

Leah C Solberg Woods

Abstract readReview
In one paragraph

Review in Physiological genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Beyond Resistance Genes: Silencing Susceptibility.International journal of molecular sciences · 2026
    Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Identification of novel genetic loci and candidate genes for progressive ethanol consumption in diversity outbred mice.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Bisphenol F Exposure in Adolescent Heterogeneous Stock Rats Affects Growth and Adiposity.Toxicological sciences : an official journal of the Society of Toxicology · 2021
    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

1 author.

Leah C Solberg WoodsDepartment of Pediatrics, Human and Molecular Genetics Center and Children's Research Institute, Medical College of Wisconsin, Milwaukee, Wisconsin.

Funding

Systems Genetics of Adiposity Traits in Outbred RatsR01DK106386 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI SOLBERG WOODS, LEAH CATHERINE · 2015 to 2018
$2.6M
Genome-wide fine-mapping of metabolic traits in heterogeneous stock ratsR01DK088975 · NIDDK · MEDICAL COLLEGE OF WISCONSIN · PI SOLBERG WOODS, LEAH CATHERINE · 2010 to 2014
$1.9M
NIDDK NIH HHS R01 DK088975NIDDK NIH HHS R01 DK106386
6 · The paper itself

Abstract

Quantitative trait locus (QTL) mapping in animal populations has been a successful strategy for identifying genomic regions that play a role in complex diseases and traits. When conducted in an F2 intercross or backcross population, the resulting QTL is frequently large, often encompassing 30 Mb or more and containing hundreds of genes. To narrow the locus and identify candidate genes, additional strategies are needed. Congenic strains have proven useful but work less well when there are multiple tightly linked loci, frequently resulting in loss of phenotype. As an alternative, we discuss the use of highly recombinant outbred models for directly fine-mapping QTL to only a few megabases. We discuss the use of several currently available models such as the advanced intercross (AI), heterogeneous stocks (HS), the diversity outbred (DO), and commercially available outbred stocks (CO). Once a QTL has been fine-mapped, founder sequence and expression QTL mapping can be used to identify candidate genes. In this regard, the large number of alleles found in outbred stocks can be leveraged to identify causative genes and variants. We end this review by discussing some important statistical considerations when analyzing outbred populations. Fine-resolution mapping in outbred models, coupled with full genome sequence, has already led to the identification of several underlying causative genes for many complex traits and diseases. These resources will likely lead to additional successes in the coming years.

Indexed as

Quantitative Trait LociAllelesAnimalsAnimals, CongenicChromosome MappingCrosses, GeneticGenetics, PopulationGenomeGenotypeHaplotypesLinkage DisequilibriumMiceMice, CongenicMice, KnockoutPhenotypediversity outbredgenetic mappingheterogeneous stockhigh resolution mappingintercross

Identifiers

PMID24326347
PMCPMC4073892

What OpenQuestion holds

Textmetadata
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.