Using Bioinformatics Tools for Identifying Disease-Causal Genetic Variants from Human Genomes

Abstract

Identification of the disease-causal genomic variants that alter human phenotypes, particularly those that lead to diseases, is the central goal of human genetics studies. In the past decade, genome-wide studies have identified several hundreds of common variants associated with complex human diseases and traits. Despite these successes, most of the common variants only have a small individual contribution to the estimated heritability underlying common diseases and traits. Many explanations for these missing heritabilities have been suggested, including rare variants, structural variants, regulatory variants, and epigenetic variants. Recent advances in high-throughput technologies have provided an opportunity to construct comprehensive maps of genetic variation, including the several million single nucleotide variants, thousands of small insertion or deletion events, and thousands of structural variants, in both the proteincoding and noncoding regions of the human genome without time and cost limitations. The present review describes current bioinformatics tools for identifying deleterious variants in protein-coding regions based on the evolutionary and functional constraints of human proteins.