Bioinformatics for personal genome interpretation

Abstract

An international consortium released the first draft sequence of the human genome 10 years ago. Although the analysis of this data has suggested the genetic underpinnings of many diseases, we have not yet been able to fully quantify the relationship between genotype and phenotype. Thus, a major current effort of the scientific community focuses on evaluating individual predispositions to specific phenotypic traits given their genetic backgrounds. Many resources aim to identify and annotate the specific genes responsible for the observed phenotypes. Some of these use intra-species genetic variability as a means for better understanding this relationship. In addition, several online resources are now dedicated to collecting single nucleotide variants and other types of variants, and annotating their functional effects and associations with phenotypic traits. This information has enabled researchers to develop bioinformatics tools to analyze the rapidly increasing amount of newly extracted variation data and to predict the effect of uncharacterized variants. In this work, we review the most important developments in the field--the databases and bioinformatics tools that will be of utmost importance in our concerted effort to interpret the human variome.

Tools for Predicting the Functional Impact of Nonsynonymous Genetic Variation

“…Despite a growing interest in other types of genetic variation, predicting the impact of NSVs remains an area of active research and continual improvement (Capriotti et al 2012). We have focused here on evolutionary conservation methods, combined methods using both conservation and structural features, and meta-prediction methods that make a unified prediction from multiple conservation, structural, or combined methods.…”

GABBR1 has a HERV-W LTR in its regulatory region – a possible implication for schizophrenia

“…This also leads us to the question of genetic changes that are outside of the coding region of protein-coding genes. This is becoming ever more evident as less single nucleotide variants are found to be associated with genetic diseases that affect the protein sequence than found in regulatory regions [15]. …”

Thoughts from SNP-SIG 2012: future challenges in the annotation of genetic variations

“…Single Nucleotide Polymorphisms (SNPs) are the most common type of genetic variation [1]. In the recent years the number of known SNPs has been increasing exponentially [2]; the last release of the NCBI's dbSNP database [3] contained more than 55 million human SNPs. SNPs are interesting as both markers of evolutionary history and in the context of their phenotypic manifestations (e.g.…”