Credit: JING Gongchao
A new algorithm may reduce the need for expensive, time-consuming whole-genome sequencing computations to understand how a microbiome functions. A team led by JING Gongchao of the Qingdao Institute of BioEnergy and Bioprocess Technology (QIBEBT) of the Chinese Academy of Sciences (CAS) and SU Xiaoquan of Qingdao University, published their approach, called Meta-Apo, on Jan. 6 in
BMC Genomics.
Researchers routinely sequence samples of microbial communities found on human skin, in human guts, and in the environment to understand what genes they contain with the ultimate goal of understanding how they function.
According to JING, the first author of the study, two main approaches exist: shotgun whole-genome sequencing and 16S rRNA gene amplicons. Whole-genome sequencing requires significant sequencing cost as well as computing power to determine all of the genes and their functions in a single sample, while 16S rRNA gene amplicons can quickly tease out a sample's specific gene for taxonomy information and thus predict how they function.