Genomic variation landscape of the human gut microbiome - Schloissnig, Siegfried; Arumugam, Manimozhiyan; Sunagawa, Shinichi; Mitreva, Makedonka; Tap, Julien; Zhu, Ana; Waller, Alison; Mende, Daniel R.; Kultima, Jens Roat; Martin, John; Kota, Karthik; Sunyaev, Shamil R.; et al. (Nature (London), 2013)
Whereas large-scale efforts have rapidly advanced the understanding and practical impact of human genomic variation, the practical impact of variation is largely unexplored in the human microbiome. We therefore developed a framework for metagenomic variation analysis and applied it to 252 faecal metagenomes of 207 individuals from Europe and North America. Using 7.4 billion reads aligned to 101 reference species, we detected 10.3 million single nucleotide polymorphisms (SNPs), 107,991 short insertions/deletions, and 1,051 structural variants. The average ratio of non-synonymous to synonymous polymorphism rates of 0.11 was more variable between gut microbial species than across human hosts. Subjects sampled at varying time intervals exhibited individuality and temporal stability of SNP variation patterns, despite considerable composition changes of their gut microbiota. This indicates that individual-specific strains are not easily replaced and that an individual might have a unique metagenomic genotype, which may be exploitable for personalized diet or drug intake. A framework for metagenomic variation analysis to explore variation in the human microbiome is developed; the study describes SNPs, short indels and structural variants in 252 faecal metagenomes of 207 individuals from Europe and North America. Gene variation in human gut microbes A collaboration between members of the European MetaHIT and American NIH Human Microbiome projects has led to the development of a framework for metagenomic variation analysis, which is used to analyse single nucleotide polymorphisms, short indels and structural variants in 252 faecal metagenomes of 207 individuals from Europe and North America. Variation patterns suggest that individuals might have unique metagenomic genotypes that could provide data relevant to personalized dietary or drug choices.