Evolutionary meta-analysis of association studies reveals ancient constraints affecting disease marker discovery.

Genome-wide disease association studies contrast genetic variation between disease cohorts and healthy populations to discover single nucleotide polymorphisms (SNPs) and other genetic markers revealing underlying genetic architectures of human diseases. Despite scores of efforts over the past decade, many reproducible genetic variants that explain substantial proportions of the heritable risk of common human diseases remain undiscovered. We...

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Sequencing and analysis of a South Asian-Indian personal genome.

BACKGROUND: With over 1.3 billion people, India is estimated to contain three times more genetic diversity than does Europe. Next-generation sequencing technologies have facilitated the understanding of diversity by enabling whole genome sequencing at greater speed and lower cost. While genomes from people of European and Asian descent have been sequenced, only recently has a single male genome from the Indian subcontinent been published at...

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Integration of disease-specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression networks reveal novel candidate genes for type 2 diabetes.

AIMS/HYPOTHESIS: While genome-wide association studies (GWASs) have been successful in identifying novel variants associated with various diseases, it has been much more difficult to determine the biological mechanisms underlying these associations. Expression quantitative trait loci (eQTL) provide another dimension to these data by associating single nucleotide polymorphisms (SNPs) with gene expression. We hypothesised that integrating SNPs...

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Human genomic disease variants: A neutral evolutionary explanation.

Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and...

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Clinical utility of sequence-based genotype compared with that derivable from genotyping arrays.

Objective We investigated the common-disease relevant information obtained from sequencing compared with that reported from genotyping arrays. Materials and methods Using 187 publicly available individual human genomes, we constructed genomic disease risk summaries based on 55 common diseases with reported gene–disease associations in the research literature using two different risk models, one based on the product of likelihood ratios and the...

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