Evidence mapPaperPMID 21406540Full record

ArticleGenome research2011

Genetic analysis of complex traits in the emerging Collaborative Cross.

David L Aylor, William Valdar, Wendy Foulds-Mathes, Ryan J Buus, Ricardo A Verdugo, Ralph S Baric, Martin T Ferris, Jeff A Frelinger, Mark Heise, Matt B Frieman and 31 more

Abstract read
In one paragraph

Article in Genome research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 242 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
242citing papers in PubMed, 1 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

242 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  8. Article
  9. Machine vision based frailty assessment for genetically diverse mice.bioRxiv : the preprint server for biology · 2024
    Article
  10. Inter-strain variability in responses to a single administration of the cannabidiol-rich cannabis extract in mice.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2024
    Article
  11. Article
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  15. Review
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  20. Article

182 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

41 authors.

David L AylorDepartment of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, USA.
William Valdar
Wendy Foulds-Mathes
Ryan J Buus
Ricardo A Verdugo
Ralph S Baric
Martin T Ferris
Jeff A Frelinger
Mark Heise
Matt B Frieman
Lisa E Gralinski
Timothy A Bell
John D Didion
Kunjie Hua
Derrick L Nehrenberg
Christine L Powell
Jill Steigerwalt
Yuying Xie
Samir N P Kelada
Francis S Collins
Ivana V Yang
David A Schwartz
Lisa A Branstetter
Elissa J Chesler
Darla R Miller
Jason Spence
Eric Yi Liu
Leonard McMillan
Abhishek Sarkar
Jeremy Wang
Wei Wang
Qi Zhang
Karl W Broman
Ron Korstanje
Caroline Durrant
Richard Mott
Fuad A Iraqi
Daniel Pomp
David Threadgill
Fernando Pardo-Manuel de Villena
Gary A Churchill

Funding

UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · UNIV OF NORTH CAROLINA CHAPEL HILL · 1999 to 2025
$5.9M
NRSA IN GENETICST32GM007092 · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · 1985 to 2005
$1.5M
Integrative Genetics of Cancer SusceptibilityU01CA105417 · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · 2004 to 2005
$1.1M
QTL Analysis in Combined Inbred Line CrossesR01GM070683 · JACKSON LABORATORY · 2004 to 2005
$670k
Statistical Methods and Software for QTL MappingR01GM074244 · JOHNS HOPKINS UNIVERSITY · 2005 to 2005
$221k
UNC Predoc Training Progr in Bioinformatics/Comp BiologyT32GM067553 · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · 2005 to 2005
$112k
NCI NIH HHS U01 CA105417NCI NIH HHS U01CA105417NCI NIH HHS U01 CA134240NCI NIH HHS U01CA134240NIAID NIH HHS U54 AI081680NIDDK NIH HHS DK056350)NIDDK NIH HHS DK076050NIDDK NIH HHS P30 DK056350NIDDK NIH HHS R01 DK076050NIGMS NIH HHS F32 GM090667NIGMS NIH HHS F32GM090667NIGMS NIH HHS GM067553NIGMS NIH HHS GM070683NIGMS NIH HHS GM074244NIGMS NIH HHS GM076468NIGMS NIH HHS P50 GM076468NIGMS NIH HHS R01 GM070683NIGMS NIH HHS R01 GM074244NIGMS NIH HHS T32 GM007092NIGMS NIH HHS T32 GM067553NIGMS NIH HHS T32GM07092NIMH NIH HHS MH090338NIMH NIH HHS P50 MH090338NIMH NIH HHS T32 MH076694NIMH NIH HHS T32MH076694Wellcome Trust 090532
6 · The paper itself

Abstract

The Collaborative Cross (CC) is a mouse recombinant inbred strain panel that is being developed as a resource for mammalian systems genetics. Here we describe an experiment that uses partially inbred CC lines to evaluate the genetic properties and utility of this emerging resource. Genome-wide analysis of the incipient strains reveals high genetic diversity, balanced allele frequencies, and dense, evenly distributed recombination sites-all ideal qualities for a systems genetics resource. We map discrete, complex, and biomolecular traits and contrast two quantitative trait locus (QTL) mapping approaches. Analysis based on inferred haplotypes improves power, reduces false discovery, and provides information to identify and prioritize candidate genes that is unique to multifounder crosses like the CC. The number of expression QTLs discovered here exceeds all previous efforts at eQTL mapping in mice, and we map local eQTL at 1-Mb resolution. We demonstrate that the genetic diversity of the CC, which derives from random mixing of eight founder strains, results in high phenotypic diversity and enhances our ability to map causative loci underlying complex disease-related traits.

Indexed as

GenomeQuantitative Trait LociAnimalsCrosses, GeneticFemaleGene ExpressionGenetic Association StudiesHaplotypesMaleMicePhenotype

Identifiers

PMID21406540
PMCPMC3149489

What Socratic 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 Socratic graph.