Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses

Abstract

Metagenomics and marker gene approaches, coupled with high-throughput sequencing technologies, have revolutionized the field of microbial ecology. Metagenomics is a culture-independent method that allows the identification and characterization of organisms from all kinds of samples. Whole-genome shotgun sequencing analyses the total DNA of a chosen sample to determine the presence of micro-organisms from all domains of life and their genomic content. Importantly, the whole-genome shotgun sequencing approach reveals the genomic diversity present, but can also give insights into the functional potential of the micro-organisms identified. The marker gene approach is based on the sequencing of a specific gene region. It allows one to describe the microbial composition based on the taxonomic groups present in the sample. It is frequently used to analyse the biodiversity of microbial ecosystems. Despite its importance, the analysis of metagenomic sequencing and marker gene data is quite a challenge. Here we review the primary workflows and software used for both approaches and discuss the current challenges in the field.

ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

“…In addition, ResistoXplorer supports other normalization methods like centered log-ratio (clr) and additive log-ratio (alr) transformation to facilitate compositional data analysis. The choice of method is dependent upon the type of analyses to be performed ( 20 , 31 ). The normalized data is used for exploratory data analysis including ordination, clustering and integrative analysis.…”

“…The best results are achieved from a trade-off between data characteristics (sample or group size, sequencing depth, effect sizes, genes abundances, etc.) and the normalization method, incorporated with the coupled exploratory and comparative analysis ( 31 ). Therefore, various statistical and normalization methods are required for different metagenomic datasets, analyses and research questions addressed ( 6 , 19 , 25 , 26 , 31 ).…”

ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

“…In addition, ResistoXplorer supports other normalization methods like centered log-ratio (clr) and additive log-ratio (alr) transformation to facilitate compositional data analysis. The choice of method is dependent upon the type of analyses to be performed [20,31].…”

“…[20,25,26,46]. Indeed, it has been recently suggested that metagenomic analysis should be explored comparatively using different available approaches [31]. However, this is a time consuming task and requires knowledge and bioinformatics training on the implementation of each statistical method employed.…”

“…The best results are achieved from a trade-off between data characteristics (sample or group size, sequencing depth, effect sizes, genes abundances, etc.) and the normalization method, incorporated with the coupled exploratory and comparative analysis [31]. Therefore, various statistical and normalization methods are required for different metagenomic datasets, analyses and research questions addressed [6,19,25,26,31].…”