DESCRIPTION:

QTL associated with ethanol induced loss of righting response 1. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (135259675)

LABEL:

QTL-Elorr1-Mouse-Chr 1

SCORE TYPE:

Binary

DATE ADDED:

2012-04-02

DATE UPDATED:

2020-05-06

SPECIES:

URI:

http://www.informatics.jax.org/searches/accession_report.cgi?id=MGI:3688590

AUTHORS:

Bennett B, Carosone-Link P

TITLE:

Replication of small effect quantitative trait loci for behavioral traits facilitated by estimation of effect size from independent cohorts.

JOURNAL:

Genes, brain, and behavior Jul 2006, Vol 5, pp. 404-12

ABSTRACT:

Quantitative trait locus (QTL) mapping is often done in a single segregating population, such as a backcross or an intercross. Both QTL location and effect size are then estimated from the same dataset. This approach results in an over-estimate of effect size for two reasons: (1) LOD scores, which are maximized over numerous point-wise tests, are correlated with estimated effect size and (2) small effect QTLs are often undetected in underpowered experiments, yielding inflated effect sizes for detected QTLs (the Beavis effect). When it is impractical to maintain or generate large population sizes, an alternative is to use two populations, one for initial detection and localization and a second for a locus-matched estimate of effect size, not conditioned on significance. Recombinant inbred (RI) panels are eminently suitable for this approach, as each strain genotype can be sampled repeatedly. We present mapping results from the LXS RI panel for two behavioral phenotypes relating to ethanol response: low-dose ethanol activation and loss of righting following high-dose injection. Both the phenotypes were measured in two or three independent cohorts, which were then used to re-estimate effect size. Many small-effect QTLs replicated using this approach, but in all cases, effect size, in the replicate cohorts, was reduced from the initial estimate, often substantially. Such a reduction will have important consequences for power analyses in which sample sizes are determined for subsequent confirmation studies. PUBMED: 16879634
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