Detection of strain-level variation in the microbiome

A paper I recently contributed to is now accepted at Genome Research:

An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography

Stephen Nayfach, Beltran Rodriguez-Mueller, Nandita Garud, Katherine S Pollard
In this paper, we introduce a new software, MIDAS, which can identify SNPs and CNVs in shotgun metagenomic data. We then apply the software to a mother-infant data set and show that while infant gut microbiomes resemble mother’s microbiomes over time at the species level, the majority of the strain transmissions from mother to infant occur closer to birth rather than later in life. We also apply MIDAS to ocean metagenomic data and show that there is substructure at the strain level in different geographic regions. MIDAS offers the ability to track strain level variation in the microbiome, making it possible to delve more deeply into the evolutionary forces shaping the the microbiome.