Chesler EJ, Lu L, Shou SM, Qu YH, Gu J, Wang JT et al. Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function. Nat Genet 37: 233-242

University of Alabama at Birmingham, Birmingham, Alabama, United States
Nature Genetics (Impact Factor: 29.35). 04/2005; 37(3):233-42. DOI: 10.1038/ng1518
Source: PubMed


Patterns of gene expression in the central nervous system are highly variable and heritable. This genetic variation among normal individuals leads to considerable structural, functional and behavioral differences. We devised a general approach to dissect genetic networks systematically across biological scale, from base pairs to behavior, using a reference population of recombinant inbred strains. We profiled gene expression using Affymetrix oligonucleotide arrays in the BXD recombinant inbred strains, for which we have extensive SNP and haplotype data. We integrated a complementary database comprising 25 years of legacy phenotypic data on these strains. Covariance among gene expression and pharmacological and behavioral traits is often highly significant, corroborates known functional relations and is often generated by common quantitative trait loci. We found that a small number of major-effect quantitative trait loci jointly modulated large sets of transcripts and classical neural phenotypes in patterns specific to each tissue. We developed new analytic and graph theoretical approaches to study shared genetic modulation of networks of traits using gene sets involved in neural synapse function as an example. We built these tools into an open web resource called WebQTL that can be used to test a broad array of hypotheses.

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Available from: Nicole Elizabeth Baldwin, Oct 09, 2015
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    • "We converted permutationderived P-values to q-values with the QVALUE software, using the bootstrap method to estimate p 0 and the default l tuning parameters (Storey et al. 2004). We set the significance threshold for declaring an eQTL at a false discovery rate of 1% (Chesler et al. 2005). "
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    ABSTRACT: Massively parallel RNA sequencing (RNA-seq) has yielded a wealth of new insights into transcriptional regulation. A first step in the analysis of RNA-seq data is the alignment of short sequence reads to a common reference genome or transcriptome. Genetic variants that distinguish individual genomes from the reference sequence can cause reads to be misaligned, resulting in biased estimates of transcript abundance. Fine-tuning of read alignment algorithms does not correct this problem. We have developed Seqnature software to construct individualized diploid genomes and transcriptomes for multiparent populations and have implemented a complete analysis pipeline that incorporates other existing software tools. We demonstrate in simulated and real data sets that alignment to individualized transcriptomes increases read mapping accuracy, improves estimation of transcript abundance, and enables the direct estimation of allele-specific expression. Moreover, when applied to expression QTL mapping we find that our individualized alignment strategy corrects false-positive linkage signals and unmasks hidden associations. We recommend the use of individualized diploid genomes over reference sequence alignment for all applications of high-throughput sequencing technology in genetically diverse populations.
    Genetics 09/2014; 198(1):59-73. DOI:10.1534/genetics.114.165886 · 5.96 Impact Factor
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    • "In eQTL mapping, two types of eQTLs are analyzed: cis-eQTLs that are in close proximity to the gene locus and trans-eQTLs that occur at greater distances from the gene locus [10]. Previous eQTL studies for multiple organisms [2-4,6] have shown that many genes are trans-regulated by a small number of genomic regions, known as ‘regulatory hotspots’. Although several eQTL studies have successfully identified regulatory hotspots [11-13], it has been reported in studies of recombinant inbred mice that regulatory hotspots replicate poorly [14]. "
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    ABSTRACT: Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods.
    Genome biology 04/2014; 15(4):R61. DOI:10.1186/gb-2014-15-4-r61 · 10.81 Impact Factor
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    • "In this study, we focus on sex-specific genetic effects on immune response phenotypes to T. muris in a population of BXD recombinant inbred (RI) mice. This reference panel consists of experimentally tractable mouse lines capturing a large amount of naturally occurring genetic variation and is ideally suited to integrate and analyse massive phenotypic data sets [21,22] thus providing a valuable tool to identify loci that contribute to immune phenotypes in T. muris infection. To determine the heritable differences in immune phenotypes to T. muris, we profiled parasite burden and infection-induced cytokine responses in peripheral blood in 20 BXD lines and both parental strains, C57Bl/6J and DBA/2J. "
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    ABSTRACT: Many disease aetiologies have sex specific effects, which have important implications for disease management. It is now becoming increasingly evident that such effects are the result of the differential expression of autosomal genes rather than sex-specific genes. Such sex-specific variation in the response to Trichuris muris, a murine parasitic nematode infection and model for the human parasitic nematode T. trichiura, has been well documented, however, the underlying genetic causes of these differences have been largely neglected. We used the BXD mouse set of recombinant inbred strains to identify sex-specific loci that contribute to immune phenotypes in T. muris infection. Response phenotypes to T. muris infection were found to be highly variable between different lines of BXD mice. A significant QTL on chromosome 5 (TM5) associated with IFN-gamma production was found in male mice but not in female mice. This QTL was in the same location as a suggestive QTL for TNF-alpha and IL-6 production in male mice suggesting a common control of these pro-inflammatory cytokines. A second QTL was identified on chromosome 4 (TM4) affecting worm burden in both male and female cohorts. We have identified several genes as potential candidates for modifying responses to T. muris infection. We have used the largest mammalian genetic model system, the BXD mouse population, to identify candidate genes with sex-specific effects in immune responses to T. muris infection. Some of these genes may be differentially expressed in male and female mice leading to the difference in immune response between the sexes reported in previous studies. Our study further highlights the importance of considering sex as an important factor in investigations of immune response at the genome-wide level, in particular the bias that can be introduced when generalizing results obtained from only one sex or a mixed sex population. Rather, analyses of interaction effects between sex and genotype should be part of future studies.
    BMC Genomics 03/2014; 15(1):193. DOI:10.1186/1471-2164-15-193 · 3.99 Impact Factor
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