Metagenomics and Microbiomes
Johannes B. Goll, Sebastian Szpakowski, Konstantinos Krampis and Karen E. Nelson
from: Bioinformatics and Data Analysis in Microbiology (Edited by: Özlem Taştan Bishop). Caister Academic Press, U.K. (2014)
Abstract
Metagenomics aims to estimate the organismal composition and metabolic potential encoded in genetic material obtained from microbial communities. The ultimate goal is to correlate genetic information with environment/host specific meta-data to discover genetic biomarkers of disease, health, and environmental change/adaptation. The power of investigating whole microbial communities, the direct application of sequencing without a need for prior cultivation in combination with increasingly efficient sequencing technologies have made such studies commonplace. This chapter provides an overview of metagenomic research emphasizing two commonly used experimental approaches: (1) marker gene (including 16S rRNA gene) and (2) whole genome shotgun sequencing (WGS). We exemplify these approaches by focusing on two studies we have worked on extensively: the National Institutes of Health (NIH) funded Human Microbiome Project (HMP) and a Baltic Sea study. In particular, we discuss experimental design aspects, preprocessing of sequence data, sequence assembly, constructing gene catalogs, estimating microbial community composition, and metabolic potential. Wherever appropriate, we describe normalization methods to avoid systematic biases, and describe a selection of suitable statistical methodology for exploratory multivariate and differential abundance analysis. We conclude with a section on cloud computing to facilitate on-demand metagenomic analysis including a review of effective bioinformatics software, and future trends read more ...
