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Michael Q Zhang

Publications and source records attributed to Michael Q Zhang.

10 recordsLinked to original sources
PubMed2003

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.

Base Sequence↗
PubMed2003

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 Burkitt's 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.

Basic Helix-Loop-Helix Leucine Zipper Transcriptio↗
PubMed2002

Computational comparison of two mouse draft genomes and the human golden path.

BACKGROUND: The availability of both mouse and human draft genomes has marked the beginning of a new era of comparative mammalian genomics. The two available mouse genome assemblies, from the public mouse genome sequencing consortium and Celera Genomics, were obtained using different clone libraries and different assembly methods. RESULTS: We present here a critical comparison of the two latest mouse genome assemblies. The utility of the combined genomes is further demonstrated by comparing them with the human 'golden path' and through a subsequent analysis of a resulting conserved sequence element (CSE) database, which allows us to identify over 6,000 potential novel genes and to derive independent estimates of the number of human protein-coding genes. CONCLUSION: The Celera and public mouse assemblies differ in about 10% of the mouse genome. Each assembly has advantages over the other: Celera has higher accuracy in base-pairs and overall higher coverage of the genome; the public assembly, however, has higher sequence quality in some newly finished bacterial artificial chromosome clone (BAC) regions and the data are freely accessible. Perhaps most important, by combining both assemblies, we can get a better annotation of the human genome; in particular, we can obtain the most complete set of CSEs, one third of which are related to known genes and some others are related to other functional genomic regions. More than half the CSEs are of unknown function. From the CSEs, we estimate the total number of human protein-coding genes to be about 40,000. This searchable publicly available online CSEdb will expedite new discoveries through comparative genomics.

Animals↗
PubMed2002

Gene expression profiling in developing human hippocampus.

The gene expression profile of developing human hippocampus is of particular interest and importance to neurobiologists devoted to development of the human brain and related diseases. To gain further molecular insight into the developmental and functional characteristics, we analyzed the expression profile of active genes in developing human hippocampus. Expressed sequence tags (ESTs) were selected by sequencing randomly selected clones from an original 3'-directed cDNA library of 150-day human fetal hippocampus, and a digital expression profile of 946 known genes that could be divided into 16 categories was generated. We also used for comparison 14 other expression profiles of related human neural cells/tissues, including human adult hippocampus. To yield more confidence regarding differential expression, a method was applied to attach normalized expression data to genes with a low false-positive rate (<0.05). Finally, hierarchical cluster analysis was used to exhibit related gene expression patterns. Our results are in accordance with anatomical and physiological observations made during the developmental process of the human hippocampus. Furthermore, some novel findings appeared to be unique to our results. The abundant expression of genes for cell surface components and disease-related genes drew our attention. Twenty-four genes are significantly different from adult, and 13 genes might be developing hippocampus-specific candidate genes, including wnt2b and some Alzheimer's disease-related genes. Our results could provide useful information on the ontogeny, development, and function of cells in the human hippocampus at the molecular level and underscore the utility of large-scale, parallel gene expression analyses in the study of complex biological phenomena.

Adult↗
PubMed2002

Functional genomics as applied to mapping transcription regulatory networks.

The sequencing of the human genome and the entire genomes of many model organisms has resulted in the identification of many genes. Many large-scale experiments for generating gene disruptions and analyzing the phenotypes are underway to ascertain gene function. A future challenge will be to determine interaction and regulation of all the genes of an organism. Recent advances in functional genomic technology have begun to shine light on such gene network problems at both transcriptomic and proteomic levels. Functional genomics will not only elucidate what the genes do, but will also help determine when, where and how they are expressed as an orchestrated system. In this review, we discuss the functional genomics approaches to extract knowledge about transcription regulatory mechanisms from combinations of sequence data, microarray data and ChIP data. We focus in particular on the budding yeast Saccharomyces cerevisiae.

Gene Expression Regulation, Fungal↗
PubMed2002

Direct coupling of the cell cycle and cell death machinery by E2F.

Unrestrained E2F activity forces S phase entry and promotes apoptosis through p53-dependent and -independent mechanisms. Here, we show that deregulation of E2F by adenovirus E1A, loss of Rb or enforced E2F-1 expression results in the accumulation of caspase proenzymes through a direct transcriptional mechanism. Increased caspase levels seem to potentiate cell death in the presence of p53-generated signals that trigger caspase activation. Our results demonstrate that mitogenic oncogenes engage a tumour suppressor network that functions at multiple levels to efficiently induce cell death. The data also underscore how cell cycle progression can be coupled to the apoptotic machinery.

Adenovirus E1A Proteins↗
PubMed2002

Computational prediction of eukaryotic protein-coding genes.

The human genome sequence is the book of our life. Buried in this large volume are our genes, which are scattered as small DNA fragments throughout the genome and comprise a small percentage of the total text. Finding these indistinct 'needles' in a vast genomic 'haystack' can be extremely challenging. In response to this challenge, computational prediction approaches have proliferated in recent years that predict the location and structure of genes. Here, I discuss these approaches and explain why they have become essential for the analyses of newly sequenced genomes.

Amino Acid Sequence↗
PubMed2002

GFScan: a gene family search tool at genomic DNA level.

We have developed GFScan(Gene Family Scan), a tool that identifies members of a gene family by searching genomic DNA sequences with genomic DNA motifs (or matrices) that are representative of the family. We have tested GFScan on four human gene families including the neurotransmitter-gated ion-channels (NGIC) family, the carbonic anhydrases (CA) family, the Dbl homology (DH) domain family, and the ETS-domain family. All known members of these families with motifs mapped to sequenced genomic DNA regions were found, whereas some novel genomic locations were also found to match the motifs, which may indicate new members in these families. Compared with other methods, GFScan recognized all true positives with much fewer false positives. We also showed that motifs constructed based on human genes could be used to search the mouse genome to identify orthologous family members in mouse. This program is available at http://www.cshl.org/mzhanglab/.

Amino Acid Sequence↗