Biomedical subjects

Hongyu Zhao

Publications and source records attributed to Hongyu Zhao.

114 records · Page 7Linked to original sources

PubMed2002

Genomic evidence for COP1 as a repressor of light-regulated gene expression and development in Arabidopsis.

Microarray gene expression profiling was used to examine the role of COP1 in the light control of Arabidopsis genome expression. Qualitatively similar gene expression profiles were observed between wild-type seedlings grown in white light and multiple cop1 mutant alleles grown in the dark. Furthermore, overexpression of the dominant-negative-acting N terminus of COP1 (N282) in darkness produced a genome expression profile similar to those produced by white light and the cop1 mutations. Different cop1 mutant alleles, N282, and light treatment also resulted in distinct expression profiles in a small fraction of the genes examined. In the light, the genome expression of cop1 mutations displayed an exaggerated light response. COP1-regulated genes in the dark were estimated to account for >20% of the genome. Analysis of these COP1-regulated genes revealed that >28 cellular pathways are coordinately but antagonistically regulated by light and COP1. Interestingly, the gene expression regulation attributable to HY5 in the light is included largely within those genes regulated by COP1 in the dark. Thus, this genomic study supports the hypothesis that COP1 acts as a repressor of photomorphogenesis, possibly by controlling the degradation of transcription factors and their target gene expression. The majority of light-controlled genome expression could be accounted for by the negative regulation of COP1 activity.

Alleles↗

PubMed2002

Rottlerin inhibits tonicity-dependent expression and action of TonEBP in a PKCdelta-independent fashion.

Novel protein kinase C (PKC) isoforms PKCdelta and PKCepsilon have recently been implicated in signaling by hypertonic stress. We investigated the role of the putative PKCdelta inhibitor rottlerin on tonicity-dependent gene regulation. In the renal medullary mIMCD3 cell line, rottlerin blocked tonicity-dependent transcription of a tonicity enhancer (TonE)-driven luciferase reporter gene, as well as tonicity-dependent transcription of the physiological tonicity effector gene aldose reductase, but not urea-dependent transcription. Consistent with these data, rottlerin inhibited tonicity-dependent expression of TonE binding protein (TonEBP) at the mRNA and protein levels. Another inhibitor of both novel and conventional PKC isoforms, GF-109203X, suppressed TonEBP-dependent transcription but failed to influence tonicity-inducible TonEBP expression. Global PKC downregulation with protracted phorbol ester treatment, however, failed to influence tonicity-dependent signaling, arguing against a PKCdelta-dependent mechanism of rottlerin action in this model. In addition, hypertonic stress failed to induce phosphorylation of PKCdelta. Furthermore, in a PC-12 cell model with a comparable degree of tonicity-dependent transcription, constitutive overexpression of dominant negative-acting PKCdelta or PKCepsilon effectively decreased tonicity signaling to extracellular signal-regulated kinase activation, as expected, but failed to influence TonE-dependent transcription. TonE-dependent transcription, however, remained rottlerin sensitive in this PC-12 cell model. In the aggregate, these data indicate that rottlerin dramatically inhibits tonicity-dependent TonEBP expression and TonE-dependent transcription but, despite its reputed mode of action, does so through a PKCdelta-independent pathway.

Acetophenones↗

PubMed2002

On a family-based haplotype pattern mining method for linkage disequilibrium mapping.

Linkage disequilibrium mapping is an important tool in disease gene mapping. Recently, Toivonen et al. [1] introduced a haplotype mining (HPM) method that is applicable to data consisting of unrelated high-risk and normal haplotypes. The HPM method orders haplotypes by their strength of association with trait values, and uses all haplotypes exceeding a given threshold of strength of association to predict the gene location. In this study, we extend the HPM method to pedigree data by measuring the strength of association between a haplotype and quantitative traits of interest using the Quantitative Pedigree Disequilibrium Test proposed by Zhang et al. [2]. This family-based HPM (F-HPM) method can incorporate haplotype information across a set of markers and allow both missing marker data and ambiguous haplotype information. We use a simulation procedure to evaluate the statistical significance of the patterns identified from the F-HPM method. When the F-HPM method is applied to analyze the sequence data from the seven candidate genes in the simulated data sets in the 12th Genetic Analysis Workshop, the association between genes and traits can be detected with high power, and the estimated locations of the trait loci are close to the true sites.

Chromosome Mapping↗

PubMed2002

YMD: a microarray database for large-scale gene expression analysis.

The use of microarray technology to perform parallel analysis of the expression pattern of a large number of genes in a single experiment has created a new frontier of medical research. The vast amount of gene expression data generated from multiple microarray experiments requires a robust database system that allows efficient data storage, retrieval, secure access, data dissemination, and integrated data analyses. To address the growing needs of microarray researchers at Yale and their collaborators, we have built the Yale Microarray Database (YMD). YMD is Web-accessible with the following features: (i) a Web program that tracks DNA samples between source plates and arrays, (ii) the capability of finding common genes/clones across different array platforms, (iii) an image file server, (iv) laboratory-based user management and access privileges, (v) project management, (vi) template data entry, (vii) linking gene expression data to annotation databases for functional analysis. YMD is currently being used on a pilot basis by several laboratories for different organisms and array platforms.

Databases, Nucleic Acid↗

PubMedDate not supplied

No association between common variations in the human alpha 2 subunit gene (ATP1A2) of the sodium-potassium-transporting ATPase and idiopathic generalized epilepsy.

Quantitative trait loci studies in inbred mice have identified a locus on chromosome 1 (Szs1) of fundamental importance to seizure susceptibility. High-ranking candidate genes in this susceptibility region include KCNJ9, KCNJ10 and ATP1A2. We performed a systematic mutation scan of the coding region of the human ATP1A2 gene and performed a case-control association study with seven common markers. Genotypes were assessed in 152 idiopathic generalized epilepsy (IGE) patients of German ancestry and 111 healthy German controls for all seven polymorphisms. No significant differences were found in genotype or allele frequencies for any of the variations between the IGE patients and controls. No haplotypes were associated with IGE when compared to controls. Linkage disequilibrium was demonstrated throughout the gene. Results suggest that the polymorphisms we studied in the ATP1A2 gene do not represent major susceptibility factors for common forms of IGE.

DNA↗

PubMedDate not supplied

Multiple peak alignment in sequential data analysis: a scale-space-based approach.

In this paper, we address the multiple peak alignment problem in sequential data analysis with an approach based on the Gaussian scale-space theory. We assume that multiple sets of detected peaks are the observed samples of a set of common peaks. We also assume that the locations of the observed peaks follow unimodal distributions (e.g., normal distribution) with their means equal to the corresponding locations of the common peaks and variances reflecting the extension of their variations. Under these assumptions, we convert the problem of estimating locations of the unknown number of common peaks from multiple sets of detected peaks into a much simpler problem of searching for local maxima in the scale-space representation. The optimization of the scale parameter is achieved using an energy minimization approach. We compare our approach with a hierarchical clustering method using both simulated data and real mass spectrometry data. We also demonstrate the merit of extending the binary peak detection method (i.e., a candidate is considered either as a peak or as a nonpeak) with a quantitative scoring measure-based approach (i.e., we assign to each candidate a possibility of being a peak).

Algorithms↗