The BES Microbial Ecology Special Interest Group is running a workshop today (Thursday 2 November) on Novel Tools for Microbial Ecology. To compliment this workshop, Xavier Harrison has edited a Virtual Issue of the best Methods in Ecology and Evolution articles on advances in methods of studying microbial evolution and ecology from the past few years.
Advances in Next-Generation Sequencing (NGS) technology now allow us to study associations between hosts and their microbial communities in unprecedented detail. However, studies investigating host-microbe interactions in the field of ecology and evolution are dominated by 16S and ITS amplicon sequencing. While amplicon sequencing is a useful tool for describing microbial community composition, it is limited in its ability to quantify the function(s) performed by members of those communities. Characterising function is vital to understanding how microbes and their hosts interact, and consequently whether those interactions are adaptive for, or detrimental to, the host. The articles in this Virtual Issue cover a broad suite of approaches that allow us to study host-microbe and microbe-microbe interactions in novel ways.
This month’s issue contains two Applications article and one Open Access article, all of which are freely available.
– LEA: This R package enables users to run ecological association studies from the R command line. It can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. The package derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results.
–PIPITS: An open-source stand-alone suite of software for automated processing of Illumina MiSeq sequences for fungal community analysis. PIPITS exploits a number of state of the art applications to process paired-end reads from quality filtering to producing OTU abundance tables.
Giovanni Strona and Joseph Veech provide this month’s Open Access article. Many studies have focused on nestedness, a pattern reflecting the tendency of network nodes to share interaction partners, as a method of measuring the structure of ecological networks. In ‘A new measure of ecological network structure based on node overlap and segregation‘ the authors introduce a new statistical procedure to measure both this kind of structure and the opposite one (i.e. species’ tendency against sharing interacting partners).