CiteULike: lp2's Johnson

Mapping the Genetic Architecture of Gene Expression in Human Liver

Eric Schadt — 2008-05-06T08:52:37-00:00

PLoS Biology, Vol. 6, No. 5. (1 May 2008), e107.

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process.

Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets

David Johnson — 2008-02-11T14:28:53-00:00

Genome Res. (7 February 2008), gr.7080508.

The most widely used method for detecting genome-wide proteinDNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols, and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. 10.1101/gr.7080508

Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs

Lee Lim — 2005-01-31T21:29:42-00:00

Nature, Vol. aop, No. current. (30 January 2005)

Population genetics of the wild yeast Saccharomyces paradoxus.

Louise Johnson — 2008-02-01T09:55:06-00:00

Genetics, Vol. 166, No. 1. (Jan 2004), pp. 43-52.

Saccharomyces paradoxus is the closest known relative of the well-known S. cerevisiae and an attractive model organism for population genetic and genomic studies. Here we characterize a set of 28 wild isolates from a 10-km(2) sampling area in southern England. All 28 isolates are homothallic (capable of mating-type switching) and wild type with respect to nutrient requirements. Nine wild isolates and two lab strains of S. paradoxus were surveyed for sequence variation at six loci totaling 7 kb, and all 28 wild isolates were then genotyped at seven polymorphic loci. These data were used to calculate nucleotide diversity and number of segregating sites in S. paradoxus and to investigate geographic differentiation, population structure, and linkage disequilibrium. Synonymous site diversity is approximately 0.3\\%. Extensive incompatibilities between gene genealogies indicate frequent recombination between unlinked loci, but there is no evidence of recombination within genes. Some localized clonal growth is apparent. The frequency of outcrossing relative to inbreeding is estimated at 1.1\\% on the basis of heterozygosity. Thus, all three modes of reproduction known in the lab (clonal replication, inbreeding, and outcrossing) have been important in molding genetic variation in this species.