Jonathan Schug

Promoter features related to tissue specificity as measured by Shannon entropy

BackgroundThe regulatory mechanisms underlying tissue specificity are a crucial part of the development and maintenance of multicellular organisms. A genome-wide analysis of promoters in the context of gene-expression patterns in tissue surveys provides a means of identifying the general principles for these mechanisms.ResultsWe introduce a definition of tissue specificity based on Shannon entropy to rank human genes according to their overall tissue specificity and by their specificity to particular tissues. We apply our definition to microarray-based and expressed sequence tag (EST)-based expression data for human genes and use similar data for mouse genes to validate our results. We show that most genes show statistically significant tissue-dependent variations in expression level. We find that the most tissue-specific genes typically have a TATA box, no CpG island, and often code for extracellular proteins. As expected, CpG islands are found in most of the least tissue-specific genes, which often code for proteins located in the nucleus or mitochondrion. The class of genes with no CpG island or TATA box are the most common mid-specificity genes and commonly code for proteins located in a membrane. Sp1 was found to be a weak indicator of less-specific expression. YY1 binding sites, either as initiators or as downstream sites, were strongly associated with the least-specific genes.ConclusionsWe have begun to understand the components of promoters that distinguish tissue-specific from ubiquitous genes, to identify associations that can predict the broad class of gene expression from sequence data alone.

PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates the recently completed P. falciparum genome sequence and annotation, as well as draft sequence and annotation emerging from other Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for intra- and inter-species comparisons. Sequence information is integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects and proteomics studies. The relational schema used to build PlasmoDB, GUS (Genomics Unified Schema) employs a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically-based, queries of the database. A stand-alone version of the database is also available on CD-ROM (P. falciparum GenePlot), facilitating access to the data in situations where internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to facilitate utilization of the vast quantities of genomic-scale data produced by the global malaria research community. The software used to develop PlasmoDB has been used to create a second Apicomplexan parasite genome database, ToxoDB (http://ToxoDB.org).

Using TESS to Predict Transcription Factor Binding Sites in DNA Sequence

This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence‐specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites. Curr. Protoc. Bioinform. 21:2.6.1‐2.6.15.

Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM)

MOTIVATION A critical task in high-throughput sequencing is aligning millions of short reads to a reference genome. Alignment is especially complicated for RNA sequencing (RNA-Seq) because of RNA splicing. A number of RNA-Seq algorithms are available, and claim to align reads with high accuracy and efficiency while detecting splice junctions. RNA-Seq data are discrete in nature; therefore, with reasonable gene models and comparative metrics RNA-Seq data can be simulated to sufficient accuracy to enable meaningful benchmarking of alignment algorithms. The exercise to rigorously compare all viable published RNA-Seq algorithms has not been performed previously. RESULTS We developed an RNA-Seq simulator that models the main impediments to RNA alignment, including alternative splicing, insertions, deletions, substitutions, sequencing errors and intron signal. We used this simulator to measure the accuracy and robustness of available algorithms at the base and junction levels. Additionally, we used reverse transcription-polymerase chain reaction (RT-PCR) and Sanger sequencing to validate the ability of the algorithms to detect novel transcript features such as novel exons and alternative splicing in RNA-Seq data from mouse retina. A pipeline based on BLAT was developed to explore the performance of established tools for this problem, and to compare it to the recently developed methods. This pipeline, the RNA-Seq Unified Mapper (RUM), performs comparably to the best current aligners and provides an advantageous combination of accuracy, speed and usability. AVAILABILITY The RUM pipeline is distributed via the Amazon Cloud and for computing clusters using the Sun Grid Engine (http://cbil.upenn.edu/RUM). CONTACT ggrant@pcbi.upenn.edu; epierce@mail.med.upenn.edu SUPPLEMENTARY INFORMATION The RNA-Seq sequence reads described in the article are deposited at GEO, accession GSE26248.

Epigenomic plasticity enables human pancreatic α to β cell reprogramming

Insulin-secreting β cells and glucagon-secreting α cells maintain physiological blood glucose levels, and their malfunction drives diabetes development. Using ChIP sequencing and RNA sequencing analysis, we determined the epigenetic and transcriptional landscape of human pancreatic α, β, and exocrine cells. We found that, compared with exocrine and β cells, differentiated α cells exhibited many more genes bivalently marked by the activating H3K4me3 and repressing H3K27me3 histone modifications. This was particularly true for β cell signature genes involved in transcriptional regulation. Remarkably, thousands of these genes were in a monovalent state in β cells, carrying only the activating or repressing mark. Our epigenomic findings suggested that α to β cell reprogramming could be promoted by manipulating the histone methylation signature of human pancreatic islets. Indeed, we show that treatment of cultured pancreatic islets with a histone methyltransferase inhibitor leads to colocalization of both glucagon and insulin and glucagon and insulin promoter factor 1 (PDX1) in human islets and colocalization of both glucagon and insulin in mouse islets. Thus, mammalian pancreatic islet cells display cell-type-specific epigenomic plasticity, suggesting that epigenomic manipulation could provide a path to cell reprogramming and novel cell replacement-based therapies for diabetes.

Prospective isolation of a bipotential clonogenic liver progenitor cell in adult mice

The molecular identification of adult hepatic stem/progenitor cells has been hampered by the lack of truly specific markers. To isolate putative adult liver progenitor cells, we used cell surface-marking antibodies, including MIC1-1C3, to isolate subpopulations of liver cells from normal adult mice or those undergoing an oval cell response and tested their capacity to form bilineage colonies in vitro. Robust clonogenic activity was found to be restricted to a subset of biliary duct cells antigenically defined as CD45(-)/CD11b(-)/CD31(-)/MIC1-1C3(+)/CD133(+)/CD26(-), at a frequency of one of 34 or one of 25 in normal or oval cell injury livers, respectively. Gene expression analyses revealed that Sox9 was expressed exclusively in this subpopulation of normal liver cells and was highly enriched relative to other cell fractions in injured livers. In vivo lineage tracing using Sox9creER(T2)-R26R(YFP) mice revealed that the cells that proliferate during progenitor-driven liver regeneration are progeny of Sox9-expressing precursors. A comprehensive array-based comparison of gene expression in progenitor-enriched and progenitor-depleted cells from both normal and DDC (3,5-diethoxycarbonyl-1,4-dihydrocollidine or diethyl1,4-dihydro-2,4,6-trimethyl-3,5-pyridinedicarboxylate)-treated livers revealed new potential regulators of liver progenitors.

Propagation of adipogenic signals through an epigenomic transition state.

The transcriptional mechanisms by which temporary exposure to developmental signals instigates adipocyte differentiation are unknown. During early adipogenesis, we find transient enrichment of the glucocorticoid receptor (GR), CCAAT/enhancer-binding protein beta (CEBPbeta), p300, mediator subunit 1, and histone H3 acetylation near genes involved in cell proliferation, development, and differentiation, including the gene encoding the master regulator of adipocyte differentiation, peroxisome proliferator-activated receptor gamma2 (PPARgamma2). Occupancy and enhancer function are triggered by adipogenic signals, and diminish upon their removal. GR, which is important for adipogenesis but need not be active in the mature adipocyte, functions transiently with other enhancer proteins to propagate a new program of gene expression that includes induction of PPARgamma2, thereby providing a memory of the earlier adipogenic signal. Thus, the conversion of preadipocyte to adipocyte involves the formation of an epigenomic transition state that is not observed in cells at the beginning or end of the differentiation process.

Glucocorticoid Receptor-Dependent Gene Regulatory Networks

While the molecular mechanisms of glucocorticoid regulation of transcription have been studied in detail, the global networks regulated by the glucocorticoid receptor (GR) remain unknown. To address this question, we performed an orthogonal analysis to identify direct targets of the GR. First, we analyzed the expression profile of mouse livers in the presence or absence of exogenous glucocorticoid, resulting in over 1,300 differentially expressed genes. We then executed genome-wide location analysis on chromatin from the same livers, identifying more than 300 promoters that are bound by the GR. Intersecting the two lists yielded 53 genes whose expression is functionally dependent upon the ligand-bound GR. Further network and sequence analysis of the functional targets enabled us to suggest interactions between the GR and other transcription factors at specific target genes. Together, our results further our understanding of the GR and its targets, and provide the basis for more targeted glucocorticoid therapies.

Genome-wide analysis reveals conserved and divergent features of Notch1/RBPJ binding in human and murine T-lymphoblastic leukemia cells

Notch1 regulates gene expression by associating with the DNA-binding factor RBPJ and is oncogenic in murine and human T-cell progenitors. Using ChIP-Seq, we find that in human and murine T-lymphoblastic leukemia (TLL) genomes Notch1 binds preferentially to promoters, to RBPJ binding sites, and near imputed ZNF143, ETS, and RUNX sites. ChIP-Seq confirmed that ZNF143 binds to ∼40% of Notch1 sites. Notch1/ZNF143 sites are characterized by high Notch1 and ZNF143 signals, frequent cobinding of RBPJ (generally through sites embedded within ZNF143 motifs), strong promoter bias, and relatively low mean levels of activating chromatin marks. RBPJ and ZNF143 binding to DNA is mutually exclusive in vitro, suggesting RBPJ/Notch1 and ZNF143 complexes exchange on these sites in cells. K-means clustering of Notch1 binding sites and associated motifs identified conserved Notch1-RUNX, Notch1-ETS, Notch1-RBPJ, Notch1-ZNF143, and Notch1-ZNF143-ETS clusters with different genomic distributions and levels of chromatin marks. Although Notch1 binds mainly to gene promoters, ∼75% of direct target genes lack promoter binding and are presumably regulated by enhancers, which were identified near MYC, DTX1, IGF1R, IL7R, and the GIMAP cluster. Human and murine TLL genomes also have many sites that bind only RBPJ. Murine RBPJ-only sites are highly enriched for imputed REST (a DNA-binding transcriptional repressor) sites, whereas human RPBJ-only sites lack REST motifs and are more highly enriched for imputed CREB sites. Thus, there is a conserved network of cis-regulatory factors that interacts with Notch1 to regulate gene expression in TLL cells, as well as unique classes of divergent RBPJ-only sites that also likely regulate transcription.

MicroRNAs Control Intestinal Epithelial Differentiation, Architecture, and Barrier Function

BACKGROUND & AIMS Whereas the importance of microRNA (miRNA) for the development of several tissues is well established, its role in the intestine is unknown. We aimed to quantify the complete miRNA expression profile of the mammalian intestinal mucosa and to determine the contribution of miRNAs to intestinal homeostasis using genetic means. METHODS We determined the miRNA transcriptome of the mouse intestinal mucosa using ultrahigh throughput sequencing. Using high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation (HITS-CLIP), we identified miRNA-messenger RNA target relationships in the jejunum. We employed gene ablation of the obligatory miRNA-processing enzyme Dicer1 to derive mice deficient for all miRNAs in intestinal epithelia. RESULTS miRNA abundance varies dramatically in the intestinal mucosa, from 1 read per million to 250,000. Of the 453 miRNA families identified, mmu-miR-192 is the most highly expressed in both the small and large intestinal mucosa, and there is a 53% overlap in the top 15 expressed miRNAs between the 2 tissues. The intestinal epithelium of Dicer1(loxP/loxP);Villin-Cre mutant mice is disorganized, with a decrease in goblet cells, a dramatic increase in apoptosis in crypts of both jejunum and colon, and accelerated jejunal cell migration. Furthermore, intestinal barrier function is impaired in Dicer1-deficient mice, resulting in intestinal inflammation with lymphocyte and neutrophil infiltration. Our list of miRNA-messenger RNA targeting relationships in the small intestinal mucosa provides insight into the molecular mechanisms behind the phenotype of Dicer1 mutant mice. CONCLUSIONS We have identified all intestinal miRNAs and shown using gene ablation of Dicer1 that miRNAs play a vital role in the differentiation and function of the intestinal epithelium.