Methylation of histone H3 on lysine 79 associates with a group of replication origins and helps limit DNA replication once per cell cycle.

Mammalian DNA replication starts at distinct chromosomal sites in a tissue-specific pattern coordinated with transcription, but previous studies have not yet identified a chromatin modification that correlates with the initiation of DNA replication at particular genomic locations. Here we report that a distinct fraction of replication initiation sites in the human genome are associated with a high frequency of dimethylation of histone H3 lysine K79 (H3K79Me2). H3K79Me2-containing chromatin exhibited the highest genome-wide enrichment for replication initiation events observed for any chromatin modification examined thus far (23.39% of H3K79Me2 peaks were detected in regions adjacent to replication initiation events). The association of H3K79Me2 with replication initiation sites was independent and not synergistic with other chromatin modifications. H3K79 dimethylation exhibited wider distribution on chromatin during S-phase, but only regions with H3K79 methylation in G1 and G2 were enriched in replication initiation events. H3K79 was dimethylated in a region containing a functional replicator (a DNA sequence capable of initiating DNA replication), but the methylation was not evident in a mutant replicator that could not initiate replication. Depletion of DOT1L, the sole enzyme responsible for H3K79 methylation, triggered limited genomic over-replication although most cells could continue to proliferate and replicate DNA in the absence of methylated H3K79. Thus, prevention of H3K79 methylation might affect regulatory processes that modulate the order and timing of DNA replication. These data are consistent with the hypothesis that dimethylated H3K79 associates with some replication origins and marks replicated chromatin during S-phase to prevent re-replication and preserve genomic stability.

ColoWeb: a resource for analysis of colocalization of genomic features.

BACKGROUND: Next-generation sequencing techniques such as ChIP-seq allow researchers to investigate the genomic position of nuclear components and events. These experiments provide researchers with thousands of regions of interest to probe in order to identify biological relevance. As the cost of sequencing decreases and its robustness increases, more and more researchers turn to genome-wide studies to better understand the genomic elements they are studying. One way to interpret the output of sequencing studies is to investigate how the element of interest localizes in relationship to genome annotations and the binding of other nuclear components. Colocalization of genomic features could indicate cooperation and provide evidence for more detailed investigations. Although there are several existing tools for visualizing and analyzing colocalization, either they are difficult to use for experimental researchers, not well maintained, or without measurements for colocalization strength. Here we describe an online tool, ColoWeb, designed to allow experimentalists to compare their datasets to existing genomic features in order to generate hypotheses about biological interactions easily and quickly. RESULTS: ColoWeb is a web-based service for evaluating the colocation of genomic features. Users submit genomic regions of interest, for example, a set of locations from a ChIP-seq analysis. ColoWeb compares the submitted regions of interest to the location of other genomic features such as transcription factors and chromatin modifiers. To facilitate comparisons among various genomic features, the output consists of both graphical representations and quantitative measures of the degree of colocalization between user's genomic regions and selected features. Frequent colocation may indicate a biological relationship. CONCLUSION: ColoWeb is a biologist-friendly web service that can quickly provide an assessment of thousands of genomic regions to identify colocated genomic features. ColoWeb is freely available at: http://projects.insilico.us.com/ColoWeb .

Genome-wide depletion of replication initiation events in highly transcribed regions.

This report investigates the mechanisms by which mammalian cells coordinate DNA replication with transcription and chromatin assembly. In yeast, DNA replication initiates within nucleosome-free regions, but studies in mammalian cells have not revealed a similar relationship. Here, we have used genome-wide massively parallel sequencing to map replication initiation events, thereby creating a database of all replication initiation sites within nonrepetitive DNA in two human cell lines. Mining this database revealed that genomic regions transcribed at moderate levels were generally associated with high replication initiation frequency. In genomic regions with high rates of transcription, very few replication initiation events were detected. High-resolution mapping of replication initiation sites showed that replication initiation events were absent from transcription start sites but were highly enriched in adjacent, downstream sequences. Methylation of CpG sequences strongly affected the location of replication initiation events, whereas histone modifications had minimal effects. These observations suggest that high levels of transcription interfere with formation of pre-replication protein complexes. Data presented here identify replication initiation sites throughout the genome, providing a foundation for further analyses of DNA-replication dynamics and cell-cycle progression.

MuPIT interactive: webserver for mapping variant positions to annotated, interactive 3D structures.

Mutation position imaging toolbox (MuPIT) interactive is a browser-based application for single-nucleotide variants (SNVs), which automatically maps the genomic coordinates of SNVs onto the coordinates of available three-dimensional (3D) protein structures. The application is designed for interactive browser-based visualization of the putative functional relevance of SNVs by biologists who are not necessarily experts either in bioinformatics or protein structure. Users may submit batches of several thousand SNVs and review all protein structures that cover the SNVs, including available functional annotations such as binding sites, mutagenesis experiments, and common polymorphisms. Multiple SNVs may be mapped onto each structure, enabling 3D visualization of SNV clusters and their relationship to functionally annotated positions. We illustrate the utility of MuPIT interactive in rationalizing the impact of selected polymorphisms in the PharmGKB database, somatic mutations identified in the Cancer Genome Atlas study of invasive breast carcinomas, and rare variants identified in the exome sequencing project. MuPIT interactive is freely available for non-profit use at http://mupit.icm.jhu.edu .

SpliceSeq: a resource for analysis and visualization of RNA-Seq data on alternative splicing and its functional impacts.

SUMMARY: SpliceSeq is a resource for RNA-Seq data that provides a clear view of alternative splicing and identifies potential functional changes that result from splice variation. It displays intuitive visualizations and prioritized lists of results that highlight splicing events and their biological consequences. SpliceSeq unambiguously aligns reads to gene splice graphs, facilitating accurate analysis of large, complex transcript variants that cannot be adequately represented in other formats. AVAILABILITY AND IMPLEMENTATION: SpliceSeq is freely available at http://bioinformatics.mdanderson.org/main/SpliceSeq:Overview. The application is a Java program that can be launched via a browser or installed locally. Local installation requires MySQL and Bowtie. CONTACT: mryan@insilico.us.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TFinDit: transcription factor-DNA interaction data depository.

BACKGROUND: One of the crucial steps in regulation of gene expression is the binding of transcription factor(s) to specific DNA sequences. Knowledge of the binding affinity and specificity at a structural level between transcription factors and their target sites has important implications in our understanding of the mechanism of gene regulation. Due to their unique functions and binding specificity, there is a need for a transcription factor-specific, structure-based database and corresponding web service to facilitate structural bioinformatics studies of transcription factor-DNA interactions, such as development of knowledge-based interaction potential, transcription factor-DNA docking, binding induced conformational changes, and the thermodynamics of protein-DNA interactions. DESCRIPTION: TFinDit is a relational database and a web search tool for studying transcription factor-DNA interactions. The database contains annotated transcription factor-DNA complex structures and related data, such as unbound protein structures, thermodynamic data, and binding sequences for the corresponding transcription factors in the complex structures. TFinDit also provides a user-friendly interface and allows users to either query individual entries or generate datasets through culling the database based on one or more search criteria. CONCLUSIONS: TFinDit is a specialized structural database with annotated transcription factor-DNA complex structures and other preprocessed data. We believe that this database/web service can facilitate the development and testing of TF-DNA interaction potentials and TF-DNA docking algorithms, and the study of protein-DNA recognition mechanisms.

Benchmarks for flexible and rigid transcription factor-DNA docking.

BACKGROUND: Structural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms. RESULTS: We constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered. CONCLUSIONS: We believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.

Systematic analysis of short internal indels and their impact on protein folding.

BACKGROUND: Protein sequence insertions/deletions (indels) can be introduced during evolution or through alternative splicing (AS). Alternative splicing is an important biological phenomenon and is considered as the major means of expanding structural and functional diversity in eukaryotes. Knowledge of the structural changes due to indels is critical to our understanding of the evolution of protein structure and function. In addition, it can help us probe the evolution of alternative splicing and the diversity of functional isoforms. However, little is known about the effects of indels, in particular the ones involving core secondary structures, on the folding of protein structures. The long term goal of our study is to accurately predict the protein AS isoform structures. As a first step towards this goal, we performed a systematic analysis on the structural changes caused by short internal indels through mining highly homologous proteins in Protein Data Bank (PDB). RESULTS: We compiled a non-redundant dataset of short internal indels (2-40 amino acids) from highly homologous protein pairs and analyzed the sequence and structural features of the indels. We found that about one third of indel residues are in disordered state and majority of the residues are exposed to solvent, suggesting that these indels are generally located on the surface of proteins. Though naturally occurring indels are fewer than engineered ones in the dataset, there are no statistically significant differences in terms of amino acid frequencies and secondary structure types between the "Natural" indels and "All" indels in the dataset. Structural comparisons show that all the protein pairs with short internal indels in the dataset preserve the structural folds and about 85% of protein pairs have global RMSDs (root mean square deviations) of 2A or less, suggesting that protein structures tend to be conserved and can tolerate short insertions and deletions. A few pairs with high RMSDs are results of relative domain positions of the proteins, probably due to the intrinsically dynamic nature of the proteins. CONCLUSIONS: The analysis demonstrated that protein structures have the "plasticity" to tolerate short indels. This study can provide valuable guides in modeling protein AS isoform structures and homologous proteins with indels through placing the indels at the right locations since the accuracy of sequence alignments dictate model qualities in homology modeling.

PDA: an automatic and comprehensive analysis program for protein-DNA complex structures.

BACKGROUND: Knowledge of protein-DNA interactions at the structural-level can provide insights into the mechanisms of protein-DNA recognition and gene regulation. Although over 1400 protein-DNA complex structures have been deposited into Protein Data Bank (PDB), the structural details of protein-DNA interactions are generally not available. In addition, current approaches to comparison of protein-DNA complexes are mainly based on protein sequence similarity while the DNA sequences are not taken into account. With the number of experimentally-determined protein-DNA complex structures increasing, there is a need for an automatic program to analyze the protein-DNA complex structures and to provide comprehensive structural information for the benefit of the whole research community. RESULTS: We developed an automatic and comprehensive protein-DNA complex structure analysis program, PDA (for protein-DNA complex structure analyzer). PDA takes PDB files as inputs and performs structural analysis that includes 1) whole protein-DNA complex structure restoration, especially the reconstruction of double-stranded DNA structures; 2) an efficient new approach for DNA base-pair detection; 3) systematic annotation of protein-DNA interactions; and 4) extraction of DNA subsequences involved in protein-DNA interactions and identification of protein-DNA binding units. Protein-DNA complex structures in current PDB were processed and analyzed with our PDA program and the analysis results were stored in a database. A dataset useful for studying protein-DNA interactions involved in gene regulation was generated using both protein and DNA sequences as well as the contact information of the complexes. WebPDA was developed to provide a web interface for using PDA and for data retrieval. CONCLUSION: PDA is a computational tool for structural annotations of protein-DNA complexes. It provides a useful resource for investigating protein-DNA interactions. Data from the PDA analysis can also facilitate the classification of protein-DNA complexes and provide insights into rational design of benchmarks. The PDA program is freely available at http://bioinfozen.uncc.edu/webpda.

Assessment of programs for ligand binding affinity prediction.

The prediction of the binding free energy between a ligand and a protein is an important component in the virtual screening and lead optimization of ligands for drug discovery. To determine the quality of current binding free energy estimation programs, we examined FlexX, X-Score, AutoDock, and BLEEP for their performance in binding free energy prediction in various situations including cocrystallized complex structures, cross docking of ligands to their non-cocrystallized receptors, docking of thermally unfolded receptor decoys to their ligands, and complex structures with "randomized" ligand decoys. In no case was there a satisfactory correlation between the experimental and estimated binding free energies over all the datasets tested. Meanwhile, a strong correlation between ligand molecular weight-binding affinity correlation and experimental predicted binding affinity correlation was found. Sometimes the programs also correctly ranked ligands' binding affinities even though native interactions between the ligands and their receptors were essentially lost because of receptor deformation or ligand randomization, and the programs could not decisively discriminate randomized ligand decoys from their native ligands; this suggested that the tested programs miss important components for the accurate capture of specific ligand binding interactions.

CRAVAT 4: Cancer-Related Analysis of Variants Toolkit.

Cancer sequencing studies are increasingly comprehensive and well powered, returning long lists of somatic mutations that can be difficult to sort and interpret. Diligent analysis and quality control can require multiple computational tools of distinct utility and producing disparate output, creating additional challenges for the investigator. The Cancer-Related Analysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation mapping and quality control, impact prediction and extensive annotation, gene- and mutation-level interpretation, including joint prioritization of all nonsilent mutation consequence types, and structural and mechanistic visualization. Results from CRAVAT submissions are explored in an interactive, user-friendly web environment with dynamic filtering and sorting designed to highlight the most informative mutations, even in the context of very large studies. CRAVAT can be run on a public web portal, in the cloud, or downloaded for local use, and is easily integrated with other methods for cancer omics analysis. Cancer Res; 77(21); e35-38. ©2017 AACR.

Fragment library-based representation system for protein conformation.

The representation system for protein conformation has a crucial effect on the speed of various protein-related simulations, including ab initio protein structure prediction and protein-protein docking simulation. Usually, the finer a representation system, the longer is the computational time required to employ the representation system in simulations. On the other hand, very coarse lattice systems cannot be directly applied to the simulation problems with real proteins. We report a new, fragment library-based protein conformation representation system, prepared by clustering amino acid conformations from 154 proteins. This system was composed of 64 most representative fragments per each amino acid, and based on the unified residue approach in which two spheres per amino acid were used. It could represent the conformation of the 82 proteins in an independent test set with the mean and standard deviation RMSD of 1.01 and 0.09 A, respectively, based on the position of alpha carbons and the centers of mass of sidechains.

A replicator-specific binding protein essential for site-specific initiation of DNA replication in mammalian cells.

Mammalian chromosome replication starts from distinct sites; however, the principles governing initiation site selection are unclear because proteins essential for DNA replication do not exhibit sequence-specific DNA binding. Here we identify a replication-initiation determinant (RepID) protein that binds a subset of replication-initiation sites. A large fraction of RepID-binding sites share a common G-rich motif and exhibit elevated replication initiation. RepID is required for initiation of DNA replication from RepID-bound replication origins, including the origin at the human beta-globin (HBB) locus. At HBB, RepID is involved in an interaction between the replication origin (Rep-P) and the locus control region. RepID-depleted murine embryonic fibroblasts exhibit abnormal replication fork progression and fewer replication-initiation events. These observations are consistent with a model, suggesting that RepID facilitates replication initiation at a distinct group of human replication origins.

The DNA repair endonuclease Mus81 facilitates fast DNA replication in the absence of exogenous damage.

The Mus81 endonuclease resolves recombination intermediates and mediates cellular responses to exogenous replicative stress. Here, we show that Mus81 also regulates the rate of DNA replication during normal growth by promoting replication fork progression while reducing the frequency of replication initiation events. In the absence of Mus81 endonuclease activity, DNA synthesis is slowed and replication initiation events are more frequent. In addition, Mus81-deficient cells fail to recover from exposure to low doses of replication inhibitors and cell viability is dependent on the XPF endonuclease. Despite an increase in replication initiation frequency, cells lacking Mus81 use the same pool of replication origins as Mus81-expressing cells. Therefore, decelerated DNA replication in Mus81-deficient cells does not initiate from cryptic or latent origins not used during normal growth. These results indicate that Mus81 plays a key role in determining the rate of DNA replication without activating a novel group of replication origins.