Browsing by Author "Tang, H."

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A de Bruijn graph approach to the quantification of closely-related genomes in a microbial community
(Mary Ann Liebert, Inc. publishers, 2012) Wang, M.; Ye, Y.; Tang, H.
The wide applications of next-generation sequencing (NGS) technologies in metagenomics have raised many computational challenges. One of the essential problems in metagenomics is to estimate the taxonomic composition of a microbial community, which can be approached by mapping shotgun reads acquired from the community to previously characterized microbial genomes followed by quantity profiling of these species based on the number of mapped reads. This procedure, however, is not as trivial as it appears at first glance. A shotgun metagenomic dataset often contains DNA sequences from many closely-related microbial species (e.g., within the same genus) or strains (e.g., within the same species), thus it is often difficult to determine which species/strain a specific read is sampled from when it can be mapped to a common region shared by multiple genomes at high similarity. Furthermore, high genomic variations are observed among individual genomes within the same species, which are difficult to be differentiated from the inter-species variations during reads mapping. To address these issues, a commonly used approach is to quantify taxonomic distribution only at the genus level, based on the reads mapped to all species belonging to the same genus; alternatively, reads are mapped to a set of representative genomes, each selected to represent a different genus. Here, we introduce a novel approach to the quantity estimation of closely-related species within the same genus by mapping the reads to their genomes represented by a de Bruijn graph, in which the common genomic regions among them are collapsed. Using simulated and real metagenomic datasets, we show the de Bruijn graph approach has several advantages over existing methods, including (1) it avoids redundant mapping of shotgun reads to multiple copies of the common regions in different genomes, and (2) it leads to more accurate quantification for the closely-related species (and even for strains within the same species).
Diverse CRISPRs evolving in human microbiomes
(Public Library of Science, 2012) Rho, M.; Wu, Y.-W.; Tang, H.; Doak, T.G.; Ye, Y.
CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) loci, together with cas (CRISPR-associated) genes, form the CRISPR/Cas adaptive immune system, a primary defense strategy that eubacteria and archaea mobilize against foreign nucleic acids, including phages and conjugative plasmids. Short spacer sequences separated by the repeats are derived from foreign DNA and direct interference to future infections. The availability of hundreds of shotgun metagenomic datasets from the Human Microbiome Project (HMP) enables us to explore the distribution and diversity of known CRISPRs in human-associated microbial communities and to discover new CRISPRs. We propose a targeted assembly strategy to reconstruct CRISPR arrays, which whole-metagenome assemblies fail to identify. For each known CRISPR type (identified from reference genomes), we use its direct repeat consensus sequence to recruit reads from each HMP dataset and then assemble the recruited reads into CRISPR loci; the unique spacer sequences can then be extracted for analysis. We also identified novel CRISPRs or new CRISPR variants in contigs from whole-metagenome assemblies and used targeted assembly to more comprehensively identify these CRISPRs across samples. We observed that the distributions of CRISPRs (including 64 known and 86 novel ones) are largely body-site specific. We provide detailed analysis of several CRISPR loci, including novel CRISPRs. For example, known streptococcal CRISPRs were identified in most oral microbiomes, totaling ~8,000 unique spacers: samples resampled from the same individual and oral site shared the most spacers; different oral sites from the same individual shared significantly fewer, while different individuals had almost no common spacers, indicating the impact of subtle niche differences on the evolution of CRISPR defenses. We further demonstrate potential applications of CRISPRs to the tracing of rare species and the virus exposure of individuals. This work indicates the importance of effective identification and characterization of CRISPR loci to the study of the dynamic ecology of microbiomes.