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A genomewide linkage screen for relative hand skill in sibling pairs.

ABSTRACT: Genomewide quantitative-trait locus (QTL) linkage analysis was performed using a continuous measure of relative hand skill (PegQ) in a sample of 195 reading-disabled sibling pairs from the United Kingdom. This was the first genomewide screen for any measure related to handedness. The mean PegQ in the sample was equivalent to that of normative data, and PegQ was not correlated with tests of reading ability (correlations between minus sign0.13 and 0.05). Relative hand skill could therefore be considered normal within the sample. A QTL on chromosome 2p11.2-12 yielded strong evidence for linkage to PegQ (empirical P=.00007), and another suggestive QTL on 17p11-q23 was also identified (empirical P=.002). The 2p11.2-12 locus was further analyzed in an independent sample of 143 reading-disabled sibling pairs, and this analysis yielded an empirical P=.13. Relative hand skill therefore is probably a complex multifactorial phenotype with a heterogeneous background, but nevertheless is amenable to QTL-based gene-mapping approaches.

SUBMITTER: Francks C

PROVIDER: S-EPMC384959 | biostudies-literature | 2002 Mar

REPOSITORIES: biostudies-literature

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A genomewide linkage screen for relative hand skill in sibling pairs.

Francks Clyde C Fisher Simon E SE MacPhie I Laurence IL Richardson Alex J AJ Marlow Angela J AJ Stein John F JF Monaco Anthony P AP

American journal of human genetics 20020103 3

Genomewide quantitative-trait locus (QTL) linkage analysis was performed using a continuous measure of relative hand skill (PegQ) in a sample of 195 reading-disabled sibling pairs from the United Kingdom. This was the first genomewide screen for any measure related to handedness. The mean PegQ in the sample was equivalent to that of normative data, and PegQ was not correlated with tests of reading ability (correlations between minus sign0.13 and 0.05). Relative hand skill could therefore be cons ...[more]

PMID: 11774074

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Project description:With the ability to measure thousands of related phenotypes from a single biological sample, it is now feasible to genetically dissect systems-level biological phenomena. The genetics of transcriptional regulation and protein abundance are likely to be complex, meaning that genetic variation at multiple loci will influence these phenotypes. Several recent studies have investigated the role of genetic variation in transcription by applying traditional linkage analysis methods to genomewide expression data, where each gene expression level was treated as a quantitative trait and analyzed separately from one another. Here, we develop a new, computationally efficient method for simultaneously mapping multiple gene expression quantitative trait loci that directly uses all of the available data. Information shared across gene expression traits is captured in a way that makes minimal assumptions about the statistical properties of the data. The method produces easy-to-interpret measures of statistical significance for both individual loci and the overall joint significance of multiple loci selected for a given expression trait. We apply the new method to a cross between two strains of the budding yeast Saccharomyces cerevisiae, and estimate that at least 37% of all gene expression traits show two simultaneous linkages, where we have allowed for epistatic interactions. Pairs of jointly linking quantitative trait loci are identified with high confidence for 170 gene expression traits, where it is expected that both loci are true positives for at least 153 traits. In addition, we are able to show that epistatic interactions contribute to gene expression variation for at least 14% of all traits. We compare the proposed approach to an exhaustive two-dimensional scan over all pairs of loci. Surprisingly, we demonstrate that an exhaustive two-dimensional scan is less powerful than the sequential search used here. In addition, we show that a two-dimensional scan does not truly allow one to test for simultaneous linkage, and the statistical significance measured from this existing method cannot be interpreted among many traits.

Dataset Information

A genomewide linkage screen for relative hand skill in sibling pairs.

Publications

A genomewide linkage screen for relative hand skill in sibling pairs.

Similar Datasets

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