Evidence map›Paper›PMID 23393305›Full record

ArticleJournal of lipid research2013

Recalculation of 23 mouse HDL QTL datasets improves accuracy and allows for better candidate gene analysis.

Cheryl Ackert-Bicknell, Beverly Paigen, Ron Korstanje

Abstract read
In one paragraph

Article in Journal of lipid research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Genetic determinants of atherosclerosis, obesity, and energy balance in consomic mice.Mammalian genome : official journal of the International Mammalian Genome Society · 2014
    Article
  4. Article
  5. 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

3 authors.

Cheryl Ackert-BicknellThe Jackson Laboratory, Bar Harbor, ME.
Beverly Paigen
Ron Korstanje

Funding

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
REPRODUCTIVE BIOLOGYT32HD007065 · NICHD · JACKSON LABORATORY · PI BRAUN, ROBERT E · 1985 to 2020
$2.6M
Mapping Gene Mutations That Alter HDL Cholesterol Levels in MiceR01HL095668 · NHLBI · JACKSON LABORATORY · PI KORSTANJE, RONNY · 2009 to 2013
$2.4M
From QTL to Gene for HDL CholesterolR01HL077796 · NHLBI · JACKSON LABORATORY · PI PAIGEN, BEVERLY J · 2004 to 2008
$2.1M
Co-localizing Quantitative Trait Loci for Bone Mineral Density and HDL in MiceR01AR060234 · NIAMS · UNIVERSITY OF ROCHESTER · PI ACKERT-BICKNELL, CHERYL LYNNE · 2010 to 2014
$1.5M
NHLBI NIH HHS R01 HL-077796NHLBI NIH HHS R01 HL077796NHLBI NIH HHS R01 HL-081162NHLBI NIH HHS R01 HL081162NHLBI NIH HHS R01 HL-095668NHLBI NIH HHS R01 HL095668NHLBI NIH HHS R37 HL077796NIAMS NIH HHS R01 AR-060234NIAMS NIH HHS R01 AR060234NICHD NIH HHS T32 HD007065
6 · The paper itself

Abstract

In the past 15 years, the quantitative trait locus (QTL) mapping approach has been applied to crosses between different inbred mouse strains to identify genetic loci associated with plasma HDL cholesterol levels. Although successful, a disadvantage of this method is low mapping resolution, as often several hundred candidate genes fall within the confidence interval for each locus. Methods have been developed to narrow these loci by combining the data from the different crosses, but they rely on the accurate mapping of the QTL and the treatment of the data in a consistent manner. We collected 23 raw datasets used for the mapping of previously published HDL QTL and reanalyzed the data from each cross using a consistent method and the latest mouse genetic map. By utilizing this approach, we identified novel QTL and QTL that were mapped to the wrong part of chromosomes. Our new HDL QTL map allows for reliable combining of QTL data and candidate gene analysis, which we demonstrate by identifying Grin3a and Etv6, as candidate genes for QTL on chromosomes 4 and 6, respectively. In addition, we were able to narrow a QTL on Chr 19 to five candidates.

Indexed as

Quantitative Trait LociAnimalsChromosome MappingHumansLipoproteins, HDLMeta-Analysis as TopicMiceLipoproteins, HDL

Identifiers

PMID23393305
PMCPMC3606003

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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.