Wendy Czika

Geographical genomics of human leukocyte gene expression variation in southern Morocco

Studies of the genetics of gene expression can identify expression SNPs (eSNPs) that explain variation in transcript abundance. Here we address the robustness of eSNP associations to environmental geography and population structure in a comparison of 194 Arab and Amazigh individuals from a city and two villages in southern Morocco. Gene expression differed between pairs of locations for up to a third of all transcripts, with notable enrichment of transcripts involved in ribosomal biosynthesis and oxidative phosphorylation. Robust associations were observed in the leukocyte samples: cis eSNPs (P < 10−08) were identified for 346 genes, and trans eSNPs (P < 10−11) for 10 genes. All of these associations were consistent both across the three sample locations and after controlling for ancestry and relatedness. No evidence of large-effect trans-acting mediators of the pervasive environmental influence was found; instead, genetic and environmental factors acted in a largely additive manner.

Genomic Convergence Analysis of Schizophrenia: mRNA Sequencing Reveals Altered Synaptic Vesicular Transport in Post-Mortem Cerebellum

Schizophrenia (SCZ) is a common, disabling mental illness with high heritability but complex, poorly understood genetic etiology. As the first phase of a genomic convergence analysis of SCZ, we generated 16.7 billion nucleotides of short read, shotgun sequences of cDNA from post-mortem cerebellar cortices of 14 patients and six, matched controls. A rigorous analysis pipeline was developed for analysis of digital gene expression studies. Sequences aligned to approximately 33,200 transcripts in each sample, with average coverage of 450 reads per gene. Following adjustments for confounding clinical, sample and experimental sources of variation, 215 genes differed significantly in expression between cases and controls. Golgi apparatus, vesicular transport, membrane association, Zinc binding and regulation of transcription were over-represented among differentially expressed genes. Twenty three genes with altered expression and involvement in presynaptic vesicular transport, Golgi function and GABAergic neurotransmission define a unifying molecular hypothesis for dysfunction in cerebellar cortex in SCZ.

Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies

During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders’ quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low.

SNP selection and multidimensional scaling to quantify population structure.

In the new era of large‐scale collaborative Genome Wide Association Studies (GWAS), population stratification has become a critical issue that must be addressed. In order to build upon the methods developed to control the confounding effect of a structured population, it is extremely important to visualize and quantify that effect. In this work, we develop methodology for single nucleotide polymorphism (SNP) selection and subsequent population stratification visualization based on deviation from Hardy‐Weinberg equilibrium in conjunction with non‐metric multidimensional scaling (MDS); a distance‐based multivariate technique. Through simulation, it is shown that SNP selection based on Hardy‐Weinberg disequilibrium (HWD) is robust against confounding linkage disequilibrium patterns that have been problematic in past studies and methods as well as producing a differentiated SNP set. Non‐metric MDS is shown to be a multivariate visualization tool preferable to principal components in conjunction with HWD SNP selection through theoretical and empirical study from HapMap samples. The proposed selection tool offers a simple and effective way to select appropriate substructure‐informative markers for use in exploring the effect that population stratification may have in association studies. Genet. Epidemiol. 33:488–496, 2009.

Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.

Applying data mining techniques to the mapping of complex disease genes.

The simulated sequence data for the Genetic Analysis Workshop 12 were analyzed using data mining techniques provided by SAS ENTERPRISE MINERTM Release 4.0 in addition to traditional statistical tests for linkage and association of genetic markers with disease status. We examined two ways of combining these approaches to make use of the covariate data along with the genotypic data. The result of incorporating data mining techniques with more classical methods is an improvement in the analysis, both by correctly classifying the affection status of more individuals and by locating more single nucleotide polymorphisms related to the disease, relative to analyses that use classical methods alone.