The Brisbane Systems Genetics Study: genetical genomics meets complex trait genetics - PubMed (original) (raw)

The Brisbane Systems Genetics Study: genetical genomics meets complex trait genetics

Joseph E Powell et al. PLoS One. 2012.

Abstract

There is growing evidence that genetic risk factors for common disease are caused by hereditary changes of gene regulation acting in complex pathways. Clearly understanding the molecular genetic relationships between genetic control of gene expression and its effect on complex diseases is essential. Here we describe the Brisbane Systems Genetics Study (BSGS), a family-based study that will be used to elucidate the genetic factors affecting gene expression and the role of gene regulation in mediating endophenotypes and complex diseases.BSGS comprises of a total of 962 individuals from 314 families, for which we have high-density genotype, gene expression and phenotypic data. Families consist of combinations of both monozygotic and dizygotic twin pairs, their siblings, and, for 72 families, both parents. A significant advantage of the inclusion of parents is improved power to disentangle environmental, additive genetic and non-additive genetic effects of gene expression and measured phenotypes. Furthermore, it allows for the estimation of parent-of-origin effects, something that has not previously been systematically investigated in human genetical genomics studies. Measured phenotypes available within the BSGS include blood phenotypes and biochemical traits measured from components of the tissue sample in which transcription levels are determined, providing an ideal test case for systems genetics approaches.We report results from an expression quantitative trait loci (eQTL) analysis using 862 individuals from BSGS to test for associations between expression levels of 17,926 probes and 528,509 SNP genotypes. At a study wide significance level approximately 15,000 associations were observed between expression levels and SNP genotypes. These associations corresponded to a total of 2,081 expression quantitative trait loci (eQTL) involving 1,503 probes. The majority of identified eQTL (87%) were located within cis-regions.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Summary of BSGS study design.

The structure of the study design allows us to investigate fundamental questions about the genetic basis of gene expression and their correlation with phenotypes that are known risk factors for disease.

Figure 2

Figure 2. Samples collected in BSGS comprise of a number of different families.

Family structure h represents the 50 MZ pairs comprising the stage I study. The remaining family structures are from stage II. The numbers of each family structure are given below the pedigree diagram. By utilising expression information contained between and within twin pairs, siblings and between progeny and parents we are able to estimate genetic and non-genetic variance components using linear mixed models.

Figure 3

Figure 3. Distribution of the R2 observed for the best eSNP from the 1,885 eQTLs.

Figure 4

Figure 4. The distribution of _cis_-eSNPs distance from the Transcription Start Site (TSS).

The distances of eSNPs from the TSS were divided into 50KB bins across the _cis_-region.

Figure 5

Figure 5. Positions of cis (A) and trans (defined as greater than 2MB from the transcription start site) (B) eSNP across the genome.

The number of eSNP within 1MB bins is shown. A single eSNP represents a unique eQTL.

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