How to design an efficient and robust pipeline for 16S rRNA-gene sequence analysis to improve our understanding on microbial communities?
Résumé
Microorganisms are considered one of the most important players involved in different environmental processes and services including nutrient cycling, pollutants attenuation as well as plant, animal and human health. In order to understand the functioning of microbial ecosystems and their impact on ecosystem processes we need to accurately assess their composition and response to environmental constraints. The application of high-throughput sequencing technologies to the study of 16S/18S rRNA-genes has revolutionized the characterization of complex microbial ecosystems. However, although it is now possible to generate hundreds of thousands of sequence reads at low costs, the analysis of the obtained data is still challenging: potential source errors including amplification biases, technical contamination, sequencing artifacts and taxonomical affiliation mistakes can lead to misinterpretations of microbial community diversity. Furthermore, progresses in sequencing technologies produce larger number of sequences at lower cost, but many tools are not scalable and pipelines have to be adapted for huge dataset. With the objective of defining best practices to analyze 16S/18S rRNA-gene sequence data, the Metagenomics, species identification, phylogeny pole of INRA was created to put together experience of biologist, bioinformaticians and statisticians of different laboratories.