Single strain high-depth ngs reveals high rdna (Its-lsu) variability in the four prevalent pathogenic species of the genus candida

Ribosomal RNA in fungi is encoded by a series of genes and spacers included in a large operon present in 100 tandem repeats, normally in a single locus. The multigene nature of this locus was somehow masked by Sanger sequencing, which produces a single sequence reporting the prevalent nucleotide of each site. The introduction of next generation sequencing led to deeper knowledge of the individual sequences (reads) and therefore of the variants between the same DNA sequences located in different tandem repeats. In this framework, NGS sequencing of the rDNA region was used to elucidate the extent of intra-and inter-genomic variation at both the strain and species level. Specifically, the use of an innovative NGS technique allowed the high-throughput highdepth sequencing of the ITS1-LSU D1/D2 amplicons of 252 strains belonging to four opportunistic yeast species of the genus Candida. Results showed the presence of a large extent of variability among strains and species. These variants were differently distributed throughout the analyzed regions with a higher concentration within the Internally Transcribed Spacer (ITS) region, suggesting that concerted evolution was not able to totally homogenize these sequences. Both the internal variability and the SNPs between strain can be used for a deep typing of the strains and to study their ecology

A reference map of the human binary protein interactome.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships(1,2). Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome(3), transcriptome(4) and proteome(5) data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes