Evidence map›Paper›PMID 21653565›Full record

ArticleBiology letters2011

Explaining the heritability of an ecologically significant trait in terms of individual quantitative trait loci.

Alison G Scoville, Young Wha Lee, John H Willis, John K Kelly

Abstract readEvaluation Study
In one paragraph

Article in Biology letters, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Article
  8. Centromere-associated meiotic drive and female fitness variation in Mimulus.Evolution; international journal of organic evolution · 2015
    Article
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  11. 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

4 authors.

Alison G ScovilleDepartment of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA.
Young Wha Lee
John H Willis
John K Kelly

Funding

U of Kansas/Haskell Indian Nations U.IRACDA ProjectK12GM063651 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI DE GUZMAN, ROBERTO N · 2002 to 2022
$10.0M
Genomic Analysis of Complex Trait Variation in MimulusR01GM073990 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI KELLY, JOHN K · 2006 to 2015
$2.6M
NIGMS NIH HHS GM063651NIGMS NIH HHS K12 GM063651NIGMS NIH HHS R01 GM073990NIGMS NIH HHS R01-GM073990
6 · The paper itself

Abstract

Most natural populations display substantial genetic variation in behaviour, morphology, physiology, life history and the susceptibility to disease. A major challenge is to determine the contributions of individual loci to variation in complex traits. Quantitative trait locus (QTL) mapping has identified genomic regions affecting ecologically significant traits of many species. In nearly all cases, however, the importance of these QTLs to population variation remains unclear. In this paper, we apply a novel experimental method to parse the genetic variance of floral traits of the annual plant Mimulus guttatus into contributions of individual QTLs. We first use QTL-mapping to identify nine loci and then conduct a population-based breeding experiment to estimate V(Q), the genetic variance attributable to each QTL. We find that three QTLs with moderate effects explain up to one-third of the genetic variance in the natural population. Variation at these loci is probably maintained by some form of balancing selection. Notably, the largest effect QTLs were relatively minor in their contribution to heritability.

Indexed as

Quantitative Trait LociBreedingChromosome MappingFlowersGenetic VariationMimulusOregonPhenotypeQuantitative Trait, HeritableSelection, Genetic

Identifiers

PMID21653565
PMCPMC3210669

What OpenQuestion holds

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Registered trials

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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.