Evidence map›Paper›PMID 18845850›Full record

ArticleGenetics2008

Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci.

Sarah L Burgess-Herbert, Allison Cox, Shirng-Wern Tsaih, Beverly Paigen

Abstract read
In one paragraph

Article in Genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Epidermal growth factor receptor restoration rescues the fatty liver regeneration in mice.American journal of physiology. Endocrinology and metabolism · 2017
    Article
  5. Article
  6. Article
  7. Article
  8. Collaborative Cross and Diversity Outbred data resources in the Mouse Phenome Database.Mammalian genome : official journal of the International Mammalian Genome Society · 2015
    Article
  9. Genetic Regulation of Female Sexual Maturation and Longevity Through Circulating IGF1.The journals of gerontology. Series A, Biological sciences and medical sciences · 2015
    Article
  10. Genetic regulation of life span, metabolism, and body weight in Pohn, a new wild-derived mouse strain.The journals of gerontology. Series A, Biological sciences and medical sciences · 2013
    Article
  11. Article
  12. A major X-linked locus affects kidney function in mice.Molecular genetics and genomics : MGG · 2012
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. The search for longevity and healthy aging genes: insights from epidemiological studies and samples of long-lived individuals.The journals of gerontology. Series A, Biological sciences and medical sciences · 2012
    Review
  18. Article
  19. Article
  20. Forward genetic approaches to understanding complex behaviors.Current topics in behavioral neurosciences · 2012
    Review
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.

Sarah L Burgess-HerbertThe Jackson Laboratory, Bar Harbor, Maine 04609, USA.
Allison Cox
Shirng-Wern Tsaih
Beverly Paigen

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI William Carl Skarnes · 1985 to 2026
$61.9M
UNC and PERLEGEN, IncP50GM076468 · NIGMS · JACKSON LABORATORY · PI PETKOV, PETKO M · 2006 to 2015
$31.0M
From QTL to Gene for HDL CholesterolR37HL077796 · NHLBI · JACKSON LABORATORY · PI PAIGEN, BEVERLY J · 2009 to 2018
$4.3M
Cloning QTL Genes for Plasma HDL CholesterolR01HL081162 · NHLBI · JACKSON LABORATORY · PI KORSTANJE, RONNY · 2006 to 2013
$3.3M
From QTL to Gene for HDL CholesterolR01HL077796 · NHLBI · JACKSON LABORATORY · PI PAIGEN, BEVERLY J · 2004 to 2008
$2.1M
Identifying Genes Regulating HDL Cholesterol LevelsR01HL074086 · NHLBI · JACKSON LABORATORY · PI PAIGEN, BEVERLY J · 2004 to 2007
$994k
NCI NIH HHS CA-34196NCI NIH HHS P30 CA034196NHLBI NIH HHS HL-74086NHLBI NIH HHS HL-77796NHLBI NIH HHS HL-81162NHLBI NIH HHS R01 HL074086NHLBI NIH HHS R01 HL077796NHLBI NIH HHS R01 HL081162NHLBI NIH HHS R37 HL077796NIGMS NIH HHS GM-76468NIGMS NIH HHS P50 GM076468
6 · The paper itself

Abstract

Dissecting the genes involved in complex traits can be confounded by multiple factors, including extensive epistatic interactions among genes, the involvement of epigenetic regulators, and the variable expressivity of traits. Although quantitative trait locus (QTL) analysis has been a powerful tool for localizing the chromosomal regions underlying complex traits, systematically identifying the causal genes remains challenging. Here, through its application to plasma levels of high-density lipoprotein cholesterol (HDL) in mice, we demonstrate a strategy for narrowing QTL that utilizes comparative genomics and bioinformatics techniques. We show how QTL detected in multiple crosses are subjected to both combined cross analysis and haplotype block analysis; how QTL from one species are mapped to the concordant regions in another species; and how genomewide scans associating haplotype groups with their phenotypes can be used to prioritize the narrowed regions. Then we illustrate how these individual methods for narrowing QTL can be systematically integrated for mouse chromosomes 12 and 15, resulting in a significantly reduced number of candidate genes, often from hundreds to <10. Finally, we give an example of how additional bioinformatics resources can be combined with experiments to determine the most likely quantitative trait genes.

Indexed as

Quantitative Trait LociAnimalsComputational BiologyCrosses, GeneticDatabases, GeneticHaplotypesLipoproteins, HDLMiceLipoproteins, HDL

Identifiers

PMID18845850
PMCPMC2600954

What OpenQuestion holds

Textmetadata
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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.