Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. Standard methods of analyzing microbial communities often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In 2013, Murat Eren and others in the Bay Paul Center developed a technique called oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms using next-generation sequencing data. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.
Eren, A. M., Maignien, L., Sul, W. J., Murphy, L. G., Grim, S. L., Morrison, H. G., and Sogin, M. L. (2013). “Oligotyping: Differentiating between closely related microbial taxa using 16S rRNA gene data.” Methods Ecol Evol, 4(12).
Learn more about Meren and his research here.