The biological function of some human transcription factor binding motifs varies with position relative to the transcription start site

A number of previous studies have predicted transcription factor binding sites (TFBSs) by exploiting the position of genomic landmarks like the transcriptional start site (TSS). The studies’ methods are generally too computationally intensive for genome-scale investigation, so the full potential of ‘positional regulomics’ to discover TFBSs and determine their function remains unknown. Because databases often annotate the genomic landmarks in DNA sequences, the methodical exploitation of positional regulomics has become increasingly urgent. Accordingly, we examined a set of 7914 human putative promoter regions (PPRs) with a known TSS. Our methods identified 1226 eight-letter DNA words with significant positional preferences with respect to the TSS, of which only 608 of the 1226 words matched known TFBSs. Many groups of genes whose PPRs contained a common word displayed similar expression profiles and related biological functions, however. Most interestingly, our results included 78 words, each of which clustered significantly in two or three different positions relative to the TSS. Often, the gene groups corresponding to different positional clusters of the same word corresponded to diverse functions, e.g. activation or repression in different tissues. Thus, different clusters of the same word likely reflect the phenomenon of ‘positional regulation’, i.e. a word's regulatory function can vary with its position relative to a genomic landmark, a conclusion inaccessible to methods based purely on sequence. Further integrative analysis of words co-occurring in PPRs also yielded 24 different groups of genes, likely identifying cis-regulatory modules de novo. Whereas comparative genomics requires precise sequence alignments, positional regulomics exploits genomic landmarks to provide a ‘poor man's alignment’. By exploiting the phenomenon of positional regulation, it uses position to differentiate the biological functions of subsets of TFBSs sharing a common sequence motif

The Histone Database: an integrated resource for histones and histone fold-containing proteins

Eukaryotic chromatin is composed of DNA and protein components—core histones—that act to compactly pack the DNA into nucleosomes, the fundamental building blocks of chromatin. These nucleosomes are connected to adjacent nucleosomes by linker histones. Nucleosomes are highly dynamic and, through various core histone post-translational modifications and incorporation of diverse histone variants, can serve as epigenetic marks to control processes such as gene expression and recombination. The Histone Sequence Database is a curated collection of sequences and structures of histones and non-histone proteins containing histone folds, assembled from major public databases. Here, we report a substantial increase in the number of sequences and taxonomic coverage for histone and histone fold-containing proteins available in the database. Additionally, the database now contains an expanded dataset that includes archaeal histone sequences. The database also provides comprehensive multiple sequence alignments for each of the four core histones (H2A, H2B, H3 and H4), the linker histones (H1/H5) and the archaeal histones. The database also includes current information on solved histone fold-containing structures. The Histone Sequence Database is an inclusive resource for the analysis of chromatin structure and function focused on histones and histone fold-containing proteins

Functional Characterization of Two Mutations Located in the Ligand Binding Domain in the SF1

Purpose: Since SF1 gene mutations located in the ligand binding domain are associated with a wide phenotypic spectrum in 46,XY subjects, the functional and structural characterization of these variations is of great interest. The aim of this study is to evaluate the clinical phenotype, hormonal pattern and molecular studies (genetic, functional data and protein structural analysis) in two non-related 46,XY disorder of sex development (DSD) index patients. Methods: Clinical characteristics, genomic DNA sequencing analysis, protein prediction software study and protein structure analysis, and functional characterization of the mutations was carried out. Results: Both index DSD patients showed a similar phenotype, however several affected members of Family 1 showed variable phenotypes. While in Family 1 a previously reported heterozygous missense point mutation (p.Arg313His) was found, in Family 2 a novel heterozygous missense point mutation (p.Ser303Arg) was detected. Both mutations were predicted to be as “probably damaging”. The transcriptional activity of SF1 mutants p.Arg313His and p.Ser303Arg, studied using two different promoters in two cell lines, exhibited significant reductions of transactivation activity. Structural analysis showed differences between both mutants, such as changes in the flexibility of the receptor backbone and in the tertiary structure around the ligand and in the AF-2 domain. Conclusions: One of these ligand binding domain mutations in SF1 showed phenotypic heterogeneity among family members, while both variations showed similarities in prepubertal phenotype, as well as in damage prediction and experimental decreases in transcriptional activity, but marked differences in structural consequence predictions. Finally the present study reinforces the concept of the wide variability in the clinical phenotype in affected 46,XY DSD patients.Fil: Perez Garrido, Natalia Isabel. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Saraco, Nora Isabel. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Marino, R.. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Ramirez, P.. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Ciaccio, Marta Graciela Cristina. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Costanzo, M.. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Guercio, Gabriela Viviana. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Warman, M.. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Minini, L.. Universidad de la República. Facultad de Ciencias; UruguayFil: Portillo Ledesma, S.. Universidad de la República. Facultad de Ciencias; UruguayFil: Rivarola, Marco Aurelio. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Coitiño, E. L.. Universidad de la República. Facultad de Ciencias; UruguayFil: Belgorosky, Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentin

Specificity of the E. coli LysR-Type Transcriptional Regulators

Families of paralogous oligomeric proteins are common in biology. How the specificity of assembly evolves is a fundamental question of biology. The LysR-Type Transcriptional Regulators (LTTR) form perhaps the largest family of transcriptional regulators in bacteria. Because genomes often encode many LTTR family members, it is assumed that many distinct homooligomers are formed simultaneously in the same cell without interfering with each other's activities, suggesting specificity in the interactions. However, this assumption has not been systematically tested.A negative-dominant assay with λcI repressor fusions was used to evaluate the assembly of the LTTRs in E. coli K-12. Thioredoxin (Trx)-LTTR fusions were used to challenge the homooligomeric interactions of λcI-LTTR fusions. Eight cI-LTTR fusions were challenged with twenty-eight Trx fusions. LTTRs could be divided into three classes based on their interactions with other LTTRs.Multimerization of LTTRs in E. coli K-12 is mostly specific. However, under the conditions of the assay, many LTTRs interact with more than one noncognate partner. The physiological significance and physical basis for these interactions are not known

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

<p>Abstract</p> <p>Background</p> <p>Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server.</p> <p>Results</p> <p>MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only.</p> <p>Conclusions</p> <p>An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at <url>http://www.metnetonline.org/api</url>.</p

Impact of Environmental Parameters on Marathon Running Performance

PURPOSE: The objectives of this study were to describe the distribution of all runners' performances in the largest marathons worldwide and to determine which environmental parameters have the maximal impact. METHODS: We analysed the results of six European (Paris, London, Berlin) and American (Boston, Chicago, New York) marathon races from 2001 to 2010 through 1,791,972 participants' performances (all finishers per year and race). Four environmental factors were gathered for each of the 60 races: temperature (°C), humidity (%), dew point (°C), and the atmospheric pressure at sea level (hPA); as well as the concentrations of four atmospheric pollutants: NO(2)-SO(2)-O(3) and PM(10) (μg x m(-3)). RESULTS: All performances per year and race are normally distributed with distribution parameters (mean and standard deviation) that differ according to environmental factors. Air temperature and performance are significantly correlated through a quadratic model. The optimal temperatures for maximal mean speed of all runners vary depending on the performance level. When temperature increases above these optima, running speed decreases and withdrawal rates increase. Ozone also impacts performance but its effect might be linked to temperature. The other environmental parameters do not have any significant impact. CONCLUSIONS: The large amount of data analyzed and the model developed in this study highlight the major influence of air temperature above all other climatic parameter on human running capacity and adaptation to race conditions

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Molecular Recognition of H3/H4 Histone Tails by the Tudor Domains of JMJD2A: A Comparative Molecular Dynamics Simulations Study

Background: Histone demethylase, JMJD2A, specifically recognizes and binds to methylated lysine residues at histone H3 and H4 tails (especially trimethylated H3K4 (H3K4me3), trimethylated H3K9 (H3K9me3) and di, trimethylated H4K20 (H4K20me2, H4K20me3)) via its tandem tudor domains. Crystal structures of JMJD2A-tudor binding to H3K4me3 and H4K20me3 peptides are available whereas the others are not. Complete picture of the recognition of the four histone peptides by the tandem tudor domains yet remains to be clarified. Methodology/Principal Findings: We report a detailed molecular dynamics simulation and binding energy analysis of the recognition of JMJD2A-tudor with four different histone tails. 25 ns fully unrestrained molecular dynamics simulations are carried out for each of the bound and free structures. We investigate the important hydrogen bonds and electrostatic interactions between the tudor domains and the peptide molecules and identify the critical residues that stabilize the complexes. Our binding free energy calculations show that H4K20me2 and H3K9me3 peptides have the highest and lowest affinity to JMJD2A-tudor, respectively. We also show that H4K20me2 peptide adopts the same binding mode with H4K20me3 peptide, and H3K9me3 peptide adopts the same binding mode with H3K4me3 peptide. Decomposition of the enthalpic and the entropic contributions to the binding free energies indicate that the recognition of the histone peptides is mainly driven by favourable van der Waals interactions. Residue decomposition of the binding free energies with backbone and side chain contributions as well as their energetic constituents identify the hotspots in the binding interface of the structures. Conclusion: Energetic investigations of the four complexes suggest that many of the residues involved in the interactions are common. However, we found two receptor residues that were related to selective binding of the H3 and H4 ligands. Modifications or mutations on one of these residues can selectively alter the recognition of the H3 tails or the H4 tails

Dengue Virus Capsid Protein Binds Core Histones and Inhibits Nucleosome Formation in Human Liver Cells

Dengue virus (DENV) is a member of the Flaviviridae and a globally (re)emerging pathogen that causes serious human disease. There is no specific antiviral or vaccine for dengue virus infection. Flavivirus capsid (C) is a structural protein responsible for gathering the viral RNA into a nucleocapsid that forms the core of a mature virus particle. Flaviviral replication is known to occur in the cytoplasm yet a large portion of capsid protein localizes to the nucleus during infection. The reasons for the nuclear presences of capsid are not completely understood. Here, we expressed mature DENV C in a tandem affinity purification assay to identify potential binding partners in human liver cells. DENV C targeted the four core histones, H2A, H2B, H3 and H4. DENV C bound recombinant histones in solution and colocalized with histones in the nucleus and cytoplasm of liver cells during DENV infection. We show that DENV C acts as a histone mimic, forming heterodimers with core histones, binding DNA and disrupting nucleosome formation. We also demonstrate that DENV infection increases the amounts of core histones in livers cells, which may be a cellular response to C binding away the histone proteins. Infection with DENV additionally alters levels of H2A phosphorylation in a time-dependent manner. The interactions of C and histones add an interesting new role for the presence of C in the nucleus during DENV infection

Analysis of Transposon Interruptions Suggests Selection for L1 Elements on the X Chromosome

It has been hypothesised that the massive accumulation of L1 transposable elements on the X chromosome is due to their function in X inactivation, and that the accumulation of Alu elements near genes is adaptive. We tested the possible selective advantage of these two transposable element (TE) families with a novel method, interruption analysis. In mammalian genomes, a large number of TEs interrupt other TEs due to the high overall abundance and age of repeats, and these interruptions can be used to test whether TEs are selectively neutral. Interruptions of TEs, which are beneficial for the host, are expected to be deleterious and underrepresented compared with neutral ones. We found that L1 elements in the regions of the X chromosome that contain the majority of the inactivated genes are significantly less frequently interrupted than on the autosomes, while L1s near genes that escape inactivation are interrupted with higher frequency, supporting the hypothesis that L1s on the X chromosome play a role in its inactivation. In addition, we show that TEs are less frequently interrupted in introns than in intergenic regions, probably due to selection against the expansion of introns, but the insertion pattern of Alus is comparable to other repeats