Michael Q. Zhang

Combinatorial patterns of histone acetylations and methylations in the human genome

Histones are characterized by numerous posttranslational modifications that influence gene transcription. However, because of the lack of global distribution data in higher eukaryotic systems, the extent to which gene-specific combinatorial patterns of histone modifications exist remains to be determined. Here, we report the patterns derived from the analysis of 39 histone modifications in human CD4+ T cells. Our data indicate that a large number of patterns are associated with promoters and enhancers. In particular, we identify a common modification module consisting of 17 modifications detected at 3,286 promoters. These modifications tend to colocalize in the genome and correlate with each other at an individual nucleosome level. Genes associated with this module tend to have higher expression, and addition of more modifications to this module is associated with further increased expression. Our data suggest that these histone modifications may act cooperatively to prepare chromatin for transcriptional activation.

ESEfinder: a web resource to identify exonic splicing enhancers

Point mutations frequently cause genetic diseases by disrupting the correct pattern of pre-mRNA splicing. The effect of a point mutation within a coding sequence is traditionally attributed to the deduced change in the corresponding amino acid. However, some point mutations can have much more severe effects on the structure of the encoded protein, for example when they inactivate an exonic splicing enhancer (ESE), thereby resulting in exon skipping. ESEs also appear to be especially important in exons that normally undergo alternative splicing. Different classes of ESE consensus motifs have been described, but they are not always easily identified. ESEfinder (http://exon.cshl.edu/ESE/) is a web-based resource that facilitates rapid analysis of exon sequences to identify putative ESEs responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.

Analysis of the vertebrate insulator protein CTCF-binding sites in the human genome

Insulator elements affect gene expression by preventing the spread of heterochromatin and restricting transcriptional enhancers from activation of unrelated promoters. In vertebrates, insulators function requires association with the CCCTC-binding factor (CTCF), a protein that recognizes long and diverse nucleotide sequences. While insulators are critical in gene regulation, only a few have been reported. Here, we describe 13,804 CTCF-binding sites in potential insulators of the human genome, discovered experimentally in primary human fibroblasts. Most of these sequences are located far from the transcriptional start sites, with their distribution strongly correlated with genes. The majority of them fit to a consensus motif highly conserved and suitable for predicting possible insulators driven by CTCF in other vertebrate genomes. In addition, CTCF localization is largely invariant across different cell types. Our results provide a resource for investigating insulator function and possible other general and evolutionarily conserved activities of CTCF sites.

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications

Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.

Network-based global inference of human disease genes

Deciphering the genetic basis of human diseases is an important goal of biomedical research. On the basis of the assumption that phenotypically similar diseases are caused by functionally related genes, we propose a computational framework that integrates human protein–protein interactions, disease phenotype similarities, and known gene–phenotype associations to capture the complex relationships between phenotypes and genotypes. We develop a tool named CIPHER to predict and prioritize disease genes, and we show that the global concordance between the human protein network and the phenotype network reliably predicts disease genes. Our method is applicable to genetically uncharacterized phenotypes, effective in the genome‐wide scan of disease genes, and also extendable to explore gene cooperativity in complex diseases. The predicted genetic landscape of over 1000 human phenotypes, which reveals the global modular organization of phenotype–genotype relationships. The genome‐wide prioritization of candidate genes for over 5000 human phenotypes, including those with under‐characterized disease loci or even those lacking known association, is publicly released to facilitate future discovery of disease genes.

A global transcriptional regulatory role for c-Myc in Burkitt's lymphoma cells

Overexpression of c-Myc is one of the most common alterations in human cancers, yet it is not clear how this transcription factor acts to promote malignant transformation. To understand the molecular targets of c-Myc function, we have used an unbiased genome-wide location-analysis approach to examine the genomic binding sites of c-Myc in Burkitts lymphoma cells. We find that c-Myc together with its heterodimeric partner, Max, occupy >15% of gene promoters tested in these cancer cells. The DNA binding of c-Myc and Max correlates extensively with gene expression throughout the genome, a hallmark attribute of general transcription factors. The c-Myc/Max heterodimer complexes also colocalize with transcription factor IID in these cells, further supporting a general role for overexpressed c-Myc in global gene regulation. In addition, transcription of a majority of c-Myc target genes exhibits changes correlated with levels of c-myc mRNA in a diverse set of tissues and cell lines, supporting the conclusion that c-Myc regulates them. Taken together, these results suggest a general role for overexpressed c-Myc in global transcriptional regulation in some cancer cells and point toward molecular mechanisms for c-Myc function in malignant transformation.

SCPD: a promoter database of the yeast Saccharomyces cerevisiae

MOTIVATION In order to facilitate a systematic study of the promoters and transcriptionally regulatory cis-elements of the yeast Saccharomyces cerevisiae on a genomic scale, we have developed a comprehensive yeast-specific promoter database, SCPD. RESULTS Currently SCPD contains 580 experimentally mapped transcription factor (TF) binding sites and 425 transcriptional start sites (TSS) as its primary data entries. It also contains relevant binding affinity and expression data where available. In addition to mechanisms for promoter information (including sequence) retrieval and a data submission form, SCPD also provides some simple but useful tools for promoter sequence analysis. AVAILABILITY SCPD can be accessed from the URL http://cgsigma.cshl.org/jian. The database is continually updated.

Autophagy and chemotherapy resistance: a promising therapeutic target for cancer treatment

Induction of cell death and inhibition of cell survival are the main principles of cancer therapy. Resistance to chemotherapeutic agents is a major problem in oncology, which limits the effectiveness of anticancer drugs. A variety of factors contribute to drug resistance, including host factors, specific genetic or epigenetic alterations in the cancer cells and so on. Although various mechanisms by which cancer cells become resistant to anticancer drugs in the microenvironment have been well elucidated, how to circumvent this resistance to improve anticancer efficacy remains to be defined. Autophagy, an important homeostatic cellular recycling mechanism, is now emerging as a crucial player in response to metabolic and therapeutic stresses, which attempts to maintain/restore metabolic homeostasis through the catabolic lysis of excessive or unnecessary proteins and injured or aged organelles. Recently, several studies have shown that autophagy constitutes a potential target for cancer therapy and the induction of autophagy in response to therapeutics can be viewed as having a prodeath or a prosurvival role, which contributes to the anticancer efficacy of these drugs as well as drug resistance. Thus, understanding the novel function of autophagy may allow us to develop a promising therapeutic strategy to enhance the effects of chemotherapy and improve clinical outcomes in the treatment of cancer patients.

Computational identification of promoters and first exons in the human genome

The identification of promoters and first exons has been one of the most difficult problems in gene-finding. We present a set of discriminant functions that can recognize structural and compositional features such as CpG islands, promoter regions and first splice-donor sites. We explain the implementation of the discriminant functions into a decision tree that constitutes a new program called FirstEF. By using different models to predict CpG-related and non-CpG-related first exons, we showed by cross-validation that the program could predict 86% of the first exons with 17% false positives. We also demonstrated the prediction accuracy of FirstEF at the genome level by applying it to the finished sequences of human chromosomes 21 and 22 as well as by comparing the predictions with the locations of the experimentally verified first exons. Finally, we present the analysis of the predicted first exons for all of the 24 chromosomes of the human genome.

Epigenomic Analysis of Multilineage Differentiation of Human Embryonic Stem Cells

Epigenetic mechanisms have been proposed to play crucial roles in mammalian development, but their precise functions are only partially understood. To investigate epigenetic regulation of embryonic development, we differentiated human embryonic stem cells into mesendoderm, neural progenitor cells, trophoblast-like cells, and mesenchymal stem cells and systematically characterized DNA methylation, chromatin modifications, and the transcriptome in each lineage. We found that promoters that are active in early developmental stages tend to be CG rich and mainly engage H3K27me3 upon silencing in nonexpressing lineages. By contrast, promoters for genes expressed preferentially at later stages are often CG poor and primarily employ DNA methylation upon repression. Interestingly, the early developmental regulatory genes are often located in large genomic domains that are generally devoid of DNA methylation in most lineages, which we termed DNA methylation valleys (DMVs). Our results suggest that distinct epigenetic mechanisms regulate early and late stages of ES cell differentiation.