A comprehensive analysis of non-sequential alignments between all protein structures

<p>Abstract</p> <p>Background</p> <p>The majority of relations between proteins can be represented as a conventional sequential alignment. Nevertheless, unusual non-sequential alignments with different connectivity of the aligned fragments in compared proteins have been reported by many researchers. It is interesting to understand those non-sequential alignments; are they unique, sporadic cases or they occur frequently; do they belong to a few specific folds or spread among many different folds, as a common feature of protein structure. We present here a comprehensive large-scale study of non-sequential alignments between available protein structures in Protein Data Bank.</p> <p>Results</p> <p>The study has been conducted on a non-redundant set of 8,865 protein structures aligned with the aid of the TOPOFIT method. It has been estimated that between 17.4% and 35.2% of all alignments are non-sequential depending on variations in the parameters. Analysis of the data revealed that non-sequential relations between proteins do occur systematically and in large quantities. Various sizes and numbers of non-sequential fragments have been observed with all possible complexities of fragment rearrangements found for alignments consisting of up to 12 fragments. It has been found that non-sequential alignments are not limited to proteins of any particular fold and are present in more than two hundred of them. Moreover, many of them are found between proteins with different fold assignments. It has been shown that protein structure symmetry does not explain non-sequential alignments. Therefore, compelling evidences have been provided that non-sequential alignments between proteins are systematic and widespread across the protein universe.</p> <p>Conclusion</p> <p>The phenomenon of the widespread occurrence of non-sequential alignments between proteins might represent a missing rule of protein structure organization. More detailed study of this phenomenon will enhance our understanding of protein stability, folding, and evolution.</p

TOPOFIT-DB, a database of protein structural alignments based on the TOPOFIT method

TOPOFIT-DB (T-DB) is a public web-based database of protein structural alignments based on the TOPOFIT method, providing a comprehensive resource for comparative analysis of protein structure families. The TOPOFIT method is based on the discovery of a saturation point on the alignment curve (topomax point) which presents an ability to objectively identify a border between common and variable parts in a protein structural family, providing additional insight into protein comparison and functional annotation. TOPOFIT also effectively detects non-sequential relations between protein structures. T-DB provides users with the convenient ability to retrieve and analyze structural neighbors for a protein; do one-to-all calculation of a user provided structure against the entire current PDB release with T-Server, and pair-wise comparison using the TOPOFIT method through the T-Pair web page. All outputs are reported in various web-based tables and graphics, with automated viewing of the structure-sequence alignments in the Friend software package for complete, detailed analysis. T-DB presents researchers with the opportunity for comprehensive studies of the variability in proteins and is publicly available at

Structure SNP (StSNP): a web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways

SNPs located within the open reading frame of a gene that result in an alteration in the amino acid sequence of the encoded protein [nonsynonymous SNPs (nsSNPs)] might directly or indirectly affect functionality of the protein, alone or in the interactions in a multi-protein complex, by increasing/decreasing the activity of the metabolic pathway. Understanding the functional consequences of such changes and drawing conclusions about the molecular basis of diseases, involves integrating information from multiple heterogeneous sources including sequence, structure data and pathway relations between proteins. The data from NCBI's SNP database (dbSNP), gene and protein databases from Entrez, protein structures from the PDB and pathway information from KEGG have all been cross referenced into the StSNP web server, in an effort to provide combined integrated, reports about nsSNPs. StSNP provides ‘on the fly’ comparative modeling of nsSNPs with links to metabolic pathway information, along with real-time visual comparative analysis of the modeled structures using the Friend software application. The use of metabolic pathways in StSNP allows a researcher to examine possible disease-related pathways associated with a particular nsSNP(s), and link the diseases with the current available molecular structure data. The server is publicly available at http://glinka.bio.neu.edu/StSNP/

Estudi de l'evolució de la formació professional agrària a Catalunya

El projecte és una anàlisi profunda sobre l'evolució de la formació professional agrària a Catalunya, sobretot en els darrers vint-i-cinc anys. Parteix de la recollida i recopilació de totes les dades disponibles respecte a la formació, tan reglada o inicial, com la contínua; amb la corresponent anàlisi de les dades. A partir d'aquesta anàlisi, i de l'experiència viscuda i la visió des del lloc de treball que ocupa l'autor en l'actualitat -cap de servei de formació agrària-, s'arriba a plantejaments sobre els desajustaments que s'hi veuen en la formació agrària, i les possibles perspectives de futur de la mateixa

PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data

Paired-End Mapper (PEMer) enables mapping of genomic structural variants at considerably enhanced sensitivity, specificity and resolution over previous approaches

Colorectal Cancer with Residual Polyp of Origin: A Model of Malignant Transformation

AbstractThe majority of colorectal cancers (CRCs) arise from adenomatous polyps. In this study, we sought to present the underrecognized CRC with the residual polyp of origin (CRC RPO+) as an entity to be utilized as a model to study colorectal carcinogenesis. We identified all subjects with biopsy-proven CRC RPO+ that were evaluated over 10 years at Mayo Clinic, Rochester, MN, and compared their clinical and pathologic characteristics to CRC without remnant polyps (CRC RPO−). Overall survival and disease-free survival overlap with an equivalent hazard ratio between CRC RPO+ and RPO− cases when age, stage, and grade are adjusted. The somatic genomic profile obtained by whole genome sequencing and the gene expression profiles by RNA-seq for CRC RPO+ tumors were compared with that of age -and gender-matched CRC RPO− evaluated by The Cancer Genome Atlas. CRC RPO+ cases were more commonly found with lower-grade, earlier-stage disease than CRC RPO−. However, within the same disease stage and grade, their clinical course is very similar to that of CRC RPO−. The mutation frequencies of commonly mutated genes in CRC are similar between CRC RPO+ and RPO− cases. Likewise, gene expression patterns are indistinguishable between the RPO+ and RPO− cases. We have confirmed that CRC RPO+ is clinically and biologically similar to CRC RPO− and may be utilized as a model of the adenoma to carcinoma transition

Comparative transcriptome and gene regulation in human iPSC-derived organoids and donor-identical brain tissue

Modeling human brain development in vitro is critically important to understand the pathophysiology of neuropsychiatric disorders. As part of the PsychENCODE project, we generated human induced pluripotent stem cells (hiPSCs) from skin fibroblasts of three human specimens at 15, 16 and 17 postconceptional weeks. These hiPSC were differentiated into telencephalic organoids to study early genetic programs in forebrain development. By using RNA-seq and histone chromatin immunoprecipitation (ChIP-seq), we compared transcriptomes and epigenomes of hiPSCs-derived organoids to donor-identical cortical brain tissue. Immunocytochemical characterization of the organoids over a time course (TD0, TD11 and TD30) showed expression of radial glial markers and mature cortical neurons confirming telencephalic fate. Hierarchical clustering of the organoids’ transcriptomes demonstrated stage-specific patterns of gene expression during in vitro development. Mapping organoids’ transcriptomes against the BrainSpan dataset suggested highest correlations with neocortex and showed their correspondence to post-conceptional weeks 8-16 of human fetal development. We then inferred transcriptional alterations, by differential gene expression, between organoids and the two brain regions analyzed. We found ~5000 of differentially expressed genes (DEG) between TD0 and fetal cortex and a decreasing number of DEG at TD11 and TD30 suggesting a stronger, albeit incomplete similarity of the organoids to the cortex at later time points. ChIP-seq experiments identified H3K27ac and H3K4me3 peaks (putative promoters and enhancers) differentially active at different organoids developmental stages and between organoids and fetal brain. Overall, however, hierarchical clustering of H3K27ac and H3K4me3 peaks demonstrated clustering of organoids with human fetal brain samples from various databases, whereas neonatal and adult brain samples formed separate clusters. These data suggest that organoids recapitulate in part transcriptome and epigenome features of fetal human brain

AlleleSeq: analysis of allele-specific expression and binding in a network framework

A computational pipeline for constructing a personal diploid genome and determining sites of allele-specific activity is developed. Using a regulatory network framework, allele-specific binding and expression are found to be significantly coordinated across the genome