Deepayan Sarkar

Genome-wide MyoD Binding in Skeletal Muscle Cells: A Potential for Broad Cellular Reprogramming

Recent studies have demonstrated that MyoD initiates a feed-forward regulation of skeletal muscle gene expression, predicting that MyoD binds directly to many genes expressed during differentiation. We have used chromatin immunoprecipitation and high-throughput sequencing to identify genome-wide binding of MyoD in several skeletal muscle cell types. As anticipated, MyoD preferentially binds to a VCASCTG sequence that resembles the in vitro-selected site for a MyoD:E-protein heterodimer, and MyoD binding increases during differentiation at many of the regulatory regions of genes expressed in skeletal muscle. Unanticipated findings were that MyoD was constitutively bound to thousands of additional sites in both myoblasts and myotubes, and that the genome-wide binding of MyoD was associated with regional histone acetylation. Therefore, in addition to regulating muscle gene expression, MyoD binds genome wide and has the ability to broadly alter the epigenome in myoblasts and myotubes.

flowCore: a Bioconductor package for high throughput flow cytometry

BackgroundRecent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates.ResultsWe developed a set of flexible open source computational tools in the R package flowCore to facilitate the analysis of these complex data. A key component of which is having suitable data structures that support the application of similar operations to a collection of samples or a clinical cohort. In addition, our software constitutes a shared and extensible research platform that enables collaboration between bioinformaticians, computer scientists, statisticians, biologists and clinicians. This platform will foster the development of novel analytic methods for flow cytometry.ConclusionThe software has been applied in the analysis of various data sets and its data structures have proven to be highly efficient in capturing and organizing the analytic work flow. Finally, a number of additional Bioconductor packages successfully build on the infrastructure provided by flowCore, open new avenues for flow data analysis.

High-resolution human genome structure by single-molecule analysis

Variation in genome structure is an important source of human genetic polymorphism: It affects a large proportion of the genome and has a variety of phenotypic consequences relevant to health and disease. In spite of this, human genome structure variation is incompletely characterized due to a lack of approaches for discovering a broad range of structural variants in a global, comprehensive fashion. We addressed this gap with Optical Mapping, a high-throughput, high-resolution single-molecule system for studying genome structure. We used Optical Mapping to create genome-wide restriction maps of a complete hydatidiform mole and three lymphoblast-derived cell lines, and we validated the approach by demonstrating a strong concordance with existing methods. We also describe thousands of new variants with sizes ranging from kb to Mb.

Mutational landscape of gingivo-buccal oral squamous cell carcinoma reveals new recurrently-mutated genes and molecular subgroups

Gingivo-buccal oral squamous cell carcinoma (OSCC-GB), an anatomical and clinical subtype of head and neck squamous cell carcinoma (HNSCC), is prevalent in regions where tobacco-chewing is common. Exome sequencing (n=50) and recurrence testing (n=60) reveals that some significantly and frequently altered genes are specific to OSCC-GB (USP9X, MLL4, ARID2, UNC13C and TRPM3), while some others are shared with HNSCC (for example, TP53, FAT1, CASP8, HRAS and NOTCH1). We also find new genes with recurrent amplifications (for example, DROSHA, YAP1) or homozygous deletions (for example, DDX3X) in OSCC-GB. We find a high proportion of C>G transversions among tobacco users with high numbers of mutations. Many pathways that are enriched for genomic alterations are specific to OSCC-GB. Our work reveals molecular subtypes with distinctive mutational profiles such as patients predominantly harbouring mutations in CASP8 with or without mutations in FAT1. Mean duration of disease-free survival is significantly elevated in some molecular subgroups. These findings open new avenues for biological characterization and exploration of therapies.

An integrative genomic approach identifies p73 and p63 as activators of miR-200 microRNA family transcription

Although microRNAs (miRNAs) are important regulators of gene expression, the transcriptional regulation of miRNAs themselves is not well understood. We employed an integrative computational pipeline to dissect the transcription factors (TFs) responsible for altered miRNA expression in ovarian carcinoma. Using experimental data and computational predictions to define miRNA promoters across the human genome, we identified TFs with binding sites significantly overrepresented among miRNA genes overexpressed in ovarian carcinoma. This pipeline nominated TFs of the p53/p63/p73 family as candidate drivers of miRNA overexpression. Analysis of data from an independent set of 253 ovarian carcinomas in The Cancer Genome Atlas showed that p73 and p63 expression is significantly correlated with expression of miRNAs whose promoters contain p53/p63/p73 family binding sites. In experimental validation of specific miRNAs predicted by the analysis to be regulated by p73 and p63, we found that p53/p63/p73 family binding sites modulate promoter activity of miRNAs of the miR-200 family, which are known regulators of cancer stem cells and epithelial–mesenchymal transitions. Furthermore, in chromatin immunoprecipitation studies both p73 and p63 directly associated with the miR-200b/a/429 promoter. This study delineates an integrative approach that can be applied to discover transcriptional regulatory mechanisms in other biological settings where analogous genomic data are available.

Quality Assessment and Data Analysis for microRNA Expression Arrays

MicroRNAs are small (∼22 nt) RNAs that regulate gene expression and play important roles in both normal and disease physiology. The use of microarrays for global characterization of microRNA expression is becoming increasingly popular and has the potential to be a widely used and valuable research tool. However, microarray profiling of microRNA expression raises a number of data analytic challenges that must be addressed in order to obtain reliable results. We introduce here a universal reference microRNA reagent set as well as a series of nonhuman spiked-in synthetic microRNA controls, and demonstrate their use for quality control and between-array normalization of microRNA expression data. We also introduce diagnostic plots designed to assess and compare various normalization methods. We anticipate that the reagents and analytic approach presented here will be useful for improving the reliability of microRNA microarray experiments.

Using flowViz to visualize flow cytometry data

UNLABELLED Automated analysis of flow cytometry (FCM) data is essential for it to become successful as a high throughput technology. We believe that the principles of Trellis graphics can be adapted to provide useful visualizations that can aid such automation. In this article, we describe the R/Bioconductor package flowViz that implements such visualizations. AVAILABILITY flowViz is available as an R package from the Bioconductor project: http://bioconductor.org

Coverage and error models of protein-protein interaction data by directed graph analysis

Using a directed graph model for bait to prey systems and a multinomial error model, we assessed the error statistics in all published large-scale datasets for Saccharomyces cerevisiae and characterized them by three traits: the set of tested interactions, artifacts that lead to false-positive or false-negative observations, and estimates of the stochastic error rates that affect the data. These traits provide a prerequisite for the estimation of the protein interactome and its modules.

Impairment of the transcriptional responses to oxidative stress in the heart of aged C57BL/6 mice

Abstract: To investigate the transcriptional response to oxidative stress in the heart and how it changes with age, we examined the cardiac gene expression profiles of young (5 months old), middle‐aged (15 months old), and old (25 months old) C57BL/6 mice treated with a single intraperitoneal injection of paraquat (50 mg/kg). Mice were killed at 0, 1, 3, 5, and 7 hours after paraquat treatment, and the gene expression profile was obtained with high‐density oligonucleotide microarrays. Of 9,977 genes represented on the microarray, 249 transcripts in the young mice, 298 transcripts in the middle‐aged mice, and 256 transcripts in the old mice displayed a significant change in mRNA levels (ANOVA, P < .01). Among these, a total of 55 transcripts were determined to be paraquat responsive for all age groups. Genes commonly induced in all age groups include those associated with stress, inflammatory, immune, and growth factor responses. Interestingly, only young mice displayed a significant increase in expression of all three isoforms of GADD45, a DNA damage‐responsive gene. Additionally, the number of immediate early genes found to be induced by paraquat was considerably higher in the younger animals. These results demonstrate that, at the transcriptional level, there is an age‐related impairment of specific inducible pathways in the response to oxidative stress in the mouse heart.

Discovery of structural alterations in solid tumor oligodendroglioma by single molecule analysis

BackgroundSolid tumors present a panoply of genomic alterations, from single base changes to the gain or loss of entire chromosomes. Although aberrations at the two extremes of this spectrum are readily defined, comprehensive discernment of the complex and disperse mutational spectrum of cancer genomes remains a significant challenge for current genome analysis platforms. In this context, high throughput, single molecule platforms like Optical Mapping offer a unique perspective.ResultsUsing measurements from large ensembles of individual DNA molecules, we have discovered genomic structural alterations in the solid tumor oligodendroglioma. Over a thousand structural variants were identified in each tumor sample, without any prior hypotheses, and often in genomic regions deemed intractable by other technologies. These findings were then validated by comprehensive comparisons to variants reported in external and internal databases, and by selected experimental corroborations. Alterations range in size from under 5 kb to hundreds of kilobases, and comprise insertions, deletions, inversions and compound events. Candidate mutations were scored at sub-genic resolution and unambiguously reveal structural details at aberrant loci.ConclusionsThe Optical Mapping system provides a rich description of the complex genomes of solid tumors, including sequence level aberrations, structural alterations and copy number variants that power generation of functional hypotheses for oligodendroglioma genetics.