Vimentin binds to G-quadruplex repeats found at telomeres and gene promoters.

G-quadruplex (G4) structures that can form at guanine-rich genomic sites, including telomeres and gene promoters, are actively involved in genome maintenance, replication, and transcription, through finely tuned interactions with protein networks. In the present study, we identified the intermediate filament protein Vimentin as a binder with nanomolar affinity for those G-rich sequences that give rise to at least two adjacent G4 units, named G4 repeats. This interaction is supported by the N-terminal domains of soluble Vimentin tetramers. The selectivity of Vimentin for G4 repeats versus individual G4s provides an unprecedented result. Based on GO enrichment analysis performed on genes having putative G4 repeats within their core promoters, we suggest that Vimentin recruitment at these sites may contribute to the regulation of gene expression during cell development and migration, possibly by reshaping the local higher-order genome topology, as already reported for lamin B.

BamSnap: a lightweight viewer for sequencing reads in BAM files.

SUMMARY: Despite the improvement in variant detection algorithms, visual inspection of the read-level data remains an essential step for accurate identification of variants in genome analysis. We developed BamSnap, an efficient BAM file viewer utilizing a graphics library and BAM indexing. In contrast to existing viewers, BamSnap can generate high-quality snapshots rapidly, with customized tracks and layout. As an example, we produced read-level images at 1000 genomic loci for >2500 whole-genomes. AVAILABILITY AND IMPLEMENTATION: BamSnap is freely available at https://github.com/parklab/bamsnap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

QPARSE: searching for long-looped or multimeric G-quadruplexes potentially distinctive and druggable.

MOTIVATION: G-quadruplexes (G4s) are non-canonical nucleic acid conformations that are widespread in all kingdoms of life and are emerging as important regulators both in RNA and DNA. Recently, two new higher-order architectures have been reported: adjacent interacting G4s and G4s with stable long loops forming stem-loop structures. As there are no specialized tools to identify these conformations, we developed QPARSE. RESULTS: QPARSE can exhaustively search for degenerate potential quadruplex-forming sequences (PQSs) containing bulges and/or mismatches at genomic level, as well as either multimeric or long-looped PQS (MPQS and LLPQS, respectively). While its assessment versus known reference datasets is comparable with the state-of-the-art, what is more interesting is its performance in the identification of MPQS and LLPQS that present algorithms are not designed to search for. We report a comprehensive analysis of MPQS in human gene promoters and the analysis of LLPQS on three experimentally validated case studies from HIV-1, BCL2 and hTERT. AVAILABILITY AND IMPLEMENTATION: QPARSE is freely accessible on the web at http://www.medcomp.medicina.unipd.it/qparse/index or downloadable from github as a python 2.7 program https://github.com/B3rse/qparse. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

NeSSie: a tool for the identification of approximate DNA sequence symmetries.

Motivation: Non-B DNA conformations play an important role in genomic rearrangements, structural three-dimensional organization and gene regulation. Many non-B DNA structures show symmetrical properties as palindromes and mirrors that can form hairpins, cruciform structures or triplexes. A comprehensive tool, capable to perform a fast genome wide search for exact and degenerate symmetrical patterns, is needed for further investigating nucleotide tracts potentially forming non-B DNA structures. Results: We developed NeSSie, an easily customizable C/C++ 64-bit library and tool, based on dynamic programming, to quickly scan for perfect and degenerate DNA palindromes, mirrors and potential triplex forming patterns. In addition, the tool computes linguistic complexity and Shannon entropy measures to verify the repetitive nature of the DNA regions enriched in these motifs. As a case study, the analysis of the Mycobacterium bovis genome is presented. Availability and implementation: http://www.medcomp.medicina.unipd.it/main_site/doku.php? id=nessie and https://github.com/B3rse/nessie. Supplementary information: Supplementary data are available at Bioinformatics online.

G-quadruplex forming sequences in the genome of all known human viruses: A comprehensive guide.

G-quadruplexes are non-canonical nucleic-acid structures that control transcription, replication, and recombination in organisms. G-quadruplexes are present in eukaryotes, prokaryotes, and viruses. In the latter, mounting evidence indicates their key biological activity. Since data on viruses are scattered, we here present a comprehensive analysis of potential quadruplex-forming sequences (PQS) in the genome of all known viruses that can infect humans. We show that occurrence and location of PQSs are features characteristic of each virus class and family. Our statistical analysis proves that their presence within the viral genome is orderly arranged, as indicated by the possibility to correctly assign up to two-thirds of viruses to their exact class based on the PQS classification. For each virus we provide: i) the list of all PQS present in the genome (positive and negative strands), ii) their position in the viral genome, iii) the degree of conservation among strains of each PQS in its genome context, iv) the statistical significance of PQS abundance. This information is accessible from a database to allow the easy navigation of the results: http://www.medcomp.medicina.unipd.it/main_site/doku.php?id=g4virus. The availability of these data will greatly expedite research on G-quadruplex in viruses, with the possibility to accelerate finding therapeutic opportunities to numerous and some fearsome human diseases.

Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform "N-of-1" analyses on individual patients. The increasing sizes of ultra-rare, "N-of-1" disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development.1,2 The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale N-of-1 analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We apply existing and introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We make our gene-level findings and variant-level information across the cohort available in a public-facing browser (https://dbmi-bgm.github.io/udn-browser/). These results show that N-of-1 efforts should be supplemented by a joint genomic analysis across cohorts.

Eliciting the Functional Taxonomy from protein annotations and taxa.

The advances of omics technologies have triggered the production of an enormous volume of data coming from thousands of species. Meanwhile, joint international efforts like the Gene Ontology (GO) consortium have worked to provide functional information for a vast amount of proteins. With these data available, we have developed FunTaxIS, a tool that is the first attempt to infer functional taxonomy (i.e. how functions are distributed over taxa) combining functional and taxonomic information. FunTaxIS is able to define a taxon specific functional space by exploiting annotation frequencies in order to establish if a function can or cannot be used to annotate a certain species. The tool generates constraints between GO terms and taxa and then propagates these relations over the taxonomic tree and the GO graph. Since these constraints nearly cover the whole taxonomy, it is possible to obtain the mapping of a function over the taxonomy. FunTaxIS can be used to make functional comparative analyses among taxa, to detect improper associations between taxa and functions, and to discover how functional knowledge is either distributed or missing. A benchmark test set based on six different model species has been devised to get useful insights on the generated taxonomic rules.