title: Next-generation sequencing in aging research: emerging applications, problems, pitfalls and possible solutions.
abstract: Recent technological advances that allow faster and cheaper DNA sequencing are now driving biological and medical research. In this review, we provide an overview of state-of-the-art next-generation sequencing (NGS) platforms and their applications, including in genome sequencing and resequencing, transcriptional profiling (RNA-Seq) and high-throughput survey of DNA-protein interactions (ChIP-Seq) and of the epigenome. Particularly, we focus on how new methods made possible by NGS can help unravel the biological and genetic mechanisms of aging, longevity and age-related diseases. In the same way, however, NGS platforms open discovery not available before, they also give rise to new challenges, in particular in processing, analyzing and interpreting the data. Bioinformatics and software issues plus statistical difficulties in genome-wide studies are discussed, as well as the use of targeted sequencing to decrease costs and facilitate statistical analyses. Lastly, we discuss a number of methods to gather biological insights from massive amounts of data, such as functional enrichment, transcriptional regulation and network analyses. Although in the fast-moving field of NGS new platforms will soon take center stage, the approaches made possible by NGS will be at the basis of molecular biology, genetics and systems biology for years to come, making them instrumental for research on aging.
authors.affiliation: School of Biological Sciences, University of Liverpool, Biosciences Building, Crown Street, Liverpool L697ZB, UK. jp@senescence.info
authors.forename: João Pedro
authors.initials: JP
authors.lastname: de Magalhães
authors.forename: Caleb E
authors.initials: CE
authors.lastname: Finch
authors.forename: Georges
authors.initials: G
authors.lastname: Janssens
mesh_terms: D000375:Aging / Q000235:genetics*; D000818:Animals; D019295:Computational Biology / Q000379:methods; D023281:Genomics / Q000379:methods; D006801:Humans; D017422:Sequence Analysis, DNA / Q000379:methods / Q000639:trends*