Evidence map›Paper›PMID 17474878›Full record

ArticleStatistical applications in genetics and molecular biology2007

Sequential quantitative trait locus mapping in experimental crosses.

Jaya M Satagopan, Saunak Sen, Gary A Churchill

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in Statistical applications in genetics and molecular biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 28% of its field
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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. A genome-wide association study identifies major loci affecting the immune response against infectious bronchitis virus in chicken.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2014
    Article
  3. 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

3 authors at 3 institutions in 1 country.

Jaya M SatagopanMemorial Sloan-Kettering Cancer Center, USA. satagopj@mskcc.org
Saunak Sen
Gary A Churchill
Jackson Laboratory · USMemorial Sloan Kettering Cancer Center · USUniversity of California, San Francisco · US

Funding

Systems Genetic Analysis of Multi-parent CrossesR01GM070683 · NIGMS · JACKSON LABORATORY · PI BROMAN, KARL W, CHURCHILL, GARY A · 2004 to 2022
$6.8M
Statistical Methods and Software for QTL MappingR01GM074244 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BROMAN, KARL W · 2005 to 2013
$2.3M
STUDY OF EXPOSURES, BEHAVIORS, AND BIOMARKERS IN CANCER EPIDEMIOLOGYR01CA137420 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI SATAGOPAN, JAYA M · 2009 to 2012
$1.6M
TWO STAGE DESIGNS FOR LINKAGE DISEQUILIBRIUMR01GM060457 · NIGMS · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SATAGOPAN, JAYA M · 2000 to 2002
$413k
NCI NIH HHS R01 CA137420NIGMS NIH HHS GM060457NIGMS NIH HHS GM070683NIGMS NIH HHS GM074244NIGMS NIH HHS R01 GM070683NIGMS NIH HHS R01 GM074244
6 · The paper itself

Abstract

The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by systematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

Indexed as

Crosses, GeneticQuantitative Trait LociChromosome MappingGenotypeHumansModels, GeneticQuantitative Trait, HeritableResearch Design

Identifiers

PMID17474878
PMCPMC11980321
OpenAlexW2037467079

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.