A comparison of association statistics between pooled and individual genotypes

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Identification of a common variant affecting human episodic memory performance using a pooled genome-wide association approach: a case study of disease gene identification

Genome-wide association studies (GWAS) are an important tool for discovering novel genes associated with disease or traits. Careful design of case-control groups greatly facilitates the efficacy of these studies. Here we describe a pooled GWAS study undertaken to find novel genes associated with human episodic memory performance. A genomic locus for the WW and C2 domain-containing 1 protein, KIBRA (also known as WWC1), was found to be associated with memory performance in three cognitively normal cohorts from Switzerland and the USA. This result was further supported by correlation of KIBRA genotype and differences in hippocampal activation as measured by functional magnetic resonance imaging (fMRI). These findings provide an excellent example of the application of GWAS using a pooled genomic DNA approach to successfully identify a locus with strong effects on human memory.

Use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry for multiplex genotyping

After completion of the human genome project, the focus of geneticists has shifted to elucidation of gene function and genetic diversity to understand the mechanisms of complex diseases or variation of patient response in drug treatment. In the past decade, many different genotyping techniques have been described for the detection of single-nucleotide polymorphisms (SNPs) and other common polymorphic variants. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is among the most powerful and widely used genotyping technologies. The method offers great flexibility in assay design and enables highly accurate genotyping at high sample throughput. Different strategies for allele discrimination and quantification have been combined with MALDI (hybridization, ligation, cleavage, and primer extension). Approaches based on primer extension have become the most popular applications. This combination enables rapid and reliable multiplexing of SNPs and other common variants, and makes MALDI-TOF-MS well suited for large-scale studies in fine-mapping and verification of genome-wide scans. In contrast to standard genotyping, more demanding approaches have enabled genotyping of DNA pools, molecular haplotyping or the detection of free circulating DNA for prenatal or cancer diagnostics. In addition, MALDI can also be used in novel applications as DNA methylation analysis, expression profiling, and resequencing. This review gives an introduction to multiplex genotyping by MALDI-MS and will focus on the latest developments of this technology.

Genome wide association for addiction: replicated results and comparisons of two analytic approaches

BACKGROUND

Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. "Nontemplate" genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance.

METHODOLOGY/PRINCIPAL FINDINGS

We report pooled "nontemplate" genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both "converge then cluster" and "cluster then converge" analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals.

CONCLUSIONS/SIGNIFICANCE

These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to "cell adhesion" processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. "Nontemplate" GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, "template" GWA approaches in which "genome wide" levels of significance are sought for SNP data from single case vs control comparisons.