Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project. Here we present an update to Factorbook which significantly expands the breadth of cell type and TF coverage. The update includes an expanded motif catalog derived from thousands of ENCODE Phase II and III ChIP-seq experiments and HT-SELEX experiments; this motif catalog is integrated with the ENCODE registry of candidate cis-regulatory elements to annotate a comprehensive collection of genome-wide candidate TF binding sites. The database also offers novel tools for applying the motif models within machine learning frameworks and using these models for integrative analysis, including annotation of variants and disease and trait heritability. Factorbook is publicly available at www.factorbook.org; we will continue to expand the resource as ENCODE Phase IV data are released.

Functional compensation among HMGN variants modulates the DNase I hypersensitive sites at enhancers.

DNase I hypersensitive sites (DHSs) are a hallmark of chromatin regions containing regulatory DNA such as enhancers and promoters; however, the factors affecting the establishment and maintenance of these sites are not fully understood. We now show that HMGN1 and HMGN2, nucleosome-binding proteins that are ubiquitously expressed in vertebrate cells, maintain the DHS landscape of mouse embryonic fibroblasts (MEFs) synergistically. Loss of one of these HMGN variants led to a compensatory increase of binding of the remaining variant. Genome-wide mapping of the DHSs in Hmgn1(-/-), Hmgn2(-/-), and Hmgn1(-/-)n2(-/-) MEFs reveals that loss of both, but not a single HMGN variant, leads to significant remodeling of the DHS landscape, especially at enhancer regions marked by H3K4me1 and H3K27ac. Loss of HMGN variants affects the induced expression of stress-responsive genes in MEFs, the transcription profiles of several mouse tissues, and leads to altered phenotypes that are not seen in mice lacking only one variant. We conclude that the compensatory binding of HMGN variants to chromatin maintains the DHS landscape, and the transcription fidelity and is necessary to retain wild-type phenotypes. Our study provides insight into mechanisms that maintain regulatory sites in chromatin and into functional compensation among nucleosome binding architectural proteins.

IRaPPA: information retrieval based integration of biophysical models for protein assembly selection.

MOTIVATION: In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. RESULTS: Atomic modeling of protein-protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. AVAILABILITY AND IMPLEMENTATION: IRaPPA has been implemented in the SwarmDock server ( http://bmm.crick.ac.uk/∼SwarmDock/ ), pyDock server ( http://life.bsc.es/pid/pydockrescoring/ ) and ZDOCK server ( http://zdock.umassmed.edu/ ), with code available on request. CONTACT: moal@ebi.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Annotation of chromatin states in 66 complete mouse epigenomes during development.

The morphologically and functionally distinct cell types of a multicellular organism are maintained by their unique epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 11.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by polycomb repressive complex proteins, and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.

Quantifying the displacement of mismatches in multiple sequence alignment benchmarks.

Multiple Sequence Alignment (MSA) methods are typically benchmarked on sets of reference alignments. The quality of the alignment can then be represented by the sum-of-pairs (SP) or column (CS) scores, which measure the agreement between a reference and corresponding query alignment. Both the SP and CS scores treat mismatches between a query and reference alignment as equally bad, and do not take the separation into account between two amino acids in the query alignment, that should have been matched according to the reference alignment. This is significant since the magnitude of alignment shifts is often of relevance in biological analyses, including homology modeling and MSA refinement/manual alignment editing. In this study we develop a new alignment benchmark scoring scheme, SPdist, that takes the degree of discordance of mismatches into account by measuring the sequence distance between mismatched residue pairs in the query alignment. Using this new score along with the standard SP score, we investigate the discriminatory behavior of the new score by assessing how well six different MSA methods perform with respect to BAliBASE reference alignments. The SP score and the SPdist score yield very similar outcomes when the reference and query alignments are close. However, for more divergent reference alignments the SPdist score is able to distinguish between methods that keep alignments approximately close to the reference and those exhibiting larger shifts. We observed that by using SPdist together with SP scoring we were able to better delineate the alignment quality difference between alternative MSA methods. With a case study we exemplify why it is important, from a biological perspective, to consider the separation of mismatches. The SPdist scoring scheme has been implemented in the VerAlign web server (http://www.ibi.vu.nl/programs/veralignwww/). The code for calculating SPdist score is also available upon request.

Role of CYB5A in pancreatic cancer prognosis and autophagy modulation.

BACKGROUND: Loss of 18q22.3 is a prognostic marker in pancreatic ductal adenocarcinoma (PDAC). This study investigated genes encoded by this cytoband. METHODS: We studied mRNA/protein expression in radically resected (n = 130) and metastatic patients (n = 50). The role of CYB5A was tested in 11 PDAC cell lines and five primary cultures through retrovirus-mediated upregulation and small interfering RNA using wound-healing, invasion, annexin-V, electron microscopy, and autophagic assays, as well as autophagy genes and kinases arrays. CYB5A+ orthotopic models (n = 6 mice/group) were monitored by Firefly and Gaussia-luciferase bioluminescence, magnetic resonance imaging, and high-frequency ultrasound. Data were analyzed by t test, Fisher exact-test, log-rank test and Cox proportional hazards models. All statistical tests were two-sided. RESULTS: Both resected and metastatic patients with low mRNA or protein expression of CYB5A had statistically significantly shorter survival (eg, median = 16.7 months, 95% confidence interval [CI] = 13.5 to 19.9; vs median = 24.8 months, 95% CI = 12.8 to 36.9; P = .02, two-sided log-rank test; n = 82 radically resected PDACs), and multivariable analyses confirmed prognostic relevance. Moreover, we characterized a novel function to CYB5A, autophagy induction, concomitant with reduced proliferation and migration/invasion of PDAC cells. Network analysis of proautophagic pathways suggested CYB5A interaction with TRAF6, which was confirmed by TRAF6 downregulation after CYB5A reconstitution (-69% in SU.86.86-CYB5A+; P = .005, two-sided t test). CYB5A silencing had opposite effects, restoring TRAF6 expression and wound healing. In vivo studies showed that CYB5A induced autophagy while inhibiting tumor growth/metastasis and increasing survival (median = 57 days, 95% CI = 52 to 61; vs median = 44 days, 95% CI = 21 to 57; P = .03, two-sided log-rank test). CONCLUSIONS: These results define CYB5A as a novel prognostic factor for PDAC that exerts its tumor-suppressor function through autophagy induction and TRAF6 modulation.

High-throughput microRNA (miRNAs) arrays unravel the prognostic role of MiR-211 in pancreatic cancer.

BACKGROUND: Only a subset of radically resected pancreatic ductal adenocarcinoma (PDAC) patients benefit from chemotherapy, and identification of prognostic factors is warranted. Recently miRNAs emerged as diagnostic biomarkers and innovative therapeutic targets, while high-throughput arrays are opening new opportunities to evaluate whether they can predict clinical outcome. The present study evaluated whether comprehensive miRNA expression profiling correlated with overall survival (OS) in resected PDAC patients. METHODOLOGY/PRINCIPAL FINDINGS: High-resolution miRNA profiles were obtained with the Toray's 3D-Gene™-miRNA-chip, detecting more than 1200 human miRNAs. RNA was successfully isolated from paraffin-embedded primary tumors of 19 out of 26 stage-pT3N1 homogeneously treated patients (adjuvant gemcitabine 1000 mg/m(2)/day, days-1/8/15, every 28 days), carefully selected according to their outcome (OS<12 (N = 13) vs. OS>30 months (N = 6), i.e. short/long-OS). Highly stringent statistics included t-test, distance matrix with Spearman-ranked correlation, and iterative approaches. Unsupervised hierarchical analysis revealed that PDACs clustered according to their short/long-OS classification, while the feature selection algorithm RELIEF identified the top 4 discriminating miRNAs between the two groups. These miRNAs target more than 1500 transcripts, including 169 targeted by two or more. MiR-211 emerged as the best discriminating miRNA, with significantly higher expression in long- vs. short-OS patients. The expression of this miRNA was subsequently assessed by quantitative-PCR in an independent cohort of laser-microdissected PDACs from 60 resected patients treated with the same gemcitabine regimen. Patients with low miR-211 expression according to median value had a significantly shorter median OS (14.8, 95%CI = 13.1-16.5, vs. 25.7 months, 95%CI = 16.2-35.1, log-rank-P = 0.004). Multivariate analysis demonstrated that low miR-211 expression was an independent factor of poor prognosis (hazard ratio 2.3, P = 0.03) after adjusting for all the factors influencing outcome. CONCLUSIONS/SIGNIFICANCE: Through comprehensive microarray analysis and PCR validation we identified miR-211 as a prognostic factor in resected PDAC. These results prompt further prospective studies and research on the biological role of miR-211 in PDAC.