Abstract:

Genome-wide association studies (GWASs) have been playing an important role on human complex diseases. Generally speaking, GWAS tries to detect the relationship between genome-wide genetic variants and measurable traits in the population level. Although fruitful, array-based GWASs still exist some problems, for example, the so-called “missing heritability”--significantly associated SNPs can only explain a small part of phenotypic variation. Other problems include that, in some traits, significantly associated SNPs in one study are hard to be repeated by other studies; and that the functions of significantly associated SNPs are often difficult to interpret. High-throughput sequencing, also known as next-generation sequencing (NGS), could be one of the most promising technologies to solve those problems by quickly producing accurate variations in a high-throughput way. NGS-based GWASs (NGS-GWAS), to some extent, provide a better solution compared with traditional array-based GWASs. We systematically review the strategies and methods for NGS-GWASs, pick out the most feasible and efficient strategies and methods for NGS-GWASs, and discuss their applications in personalized medicine.

Key words: genome-wide association study (GWAS), next-generation sequencing (NGS), personalized medicine (PM)