Utilizing de Bruijn graph of metagenome assembly for metatranscriptome analysis
Haixu Tang was one of the co-authors of Pevzner’s 2001 paper and also developed the RAPsearch2 program for gene annotation. In this paper, they are mapping the meta-transcriptome on to the dBG of metagenome.
Metagenomics research has accelerated the studies of microbial organisms, providing insights into the composition and potential functionality of various microbial communities. Metatranscriptomics (studies of the transcripts from a mixture of microbial species) and other meta-omics approaches hold even greater promise for providing additional insights into functional and regulatory characteristics of the microbial communities. Current metatranscriptomics projects are often carried out without matched metagenomic datasets (of the same microbial communities). For the projects that produce both metatranscriptomic and metagenomic datasets, their analyses are often not integrated. Metagenome assemblies are far from perfect, partially explaining why metagenome assemblies are not used for the analysis of metatranscriptomic datasets. Here we report a reads mapping algorithm for mapping of short reads onto a de Bruijn graph of assemblies. A hash table of junction k-mers (k-mers spanning branching structures in the de Bruijn graph) is used to facilitate fast mapping of reads to the graph. We developed an application of this mapping algorithm: a reference based approach to metatranscriptome assembly using graphs of metagenome assembly as the reference. Our results show that this new approach (called TAG) helps to assemble substantially more transcripts that otherwise would have been missed or truncated because of the fragmented nature of the reference metagenome. TAG was implemented in C++ and has been tested extensively on the linux platform. It is available for download as open source at this http URL
