Biomedical subjects

Hongyu Zhao

Publications and source records attributed to Hongyu Zhao.

At least 91 records · Page 5Linked to original sources

PubMed2004

Haplotype block structures show significant variation among populations.

Recent studies suggest that haplotypes tend to have block-like structures throughout the human genome. Several methods were proposed for haplotype block partitioning and for tagging single-nucleotide polymorphism (SNP) identification. In population genetics studies, several research groups compared block structures across human populations. However, the measures used to quantify population similarity are either less than satisfactory or nonexistent. In this article, we propose several similarity measures to facilitate the comparisons of haplotype structures, namely block boundaries and tagging SNPs, across populations. With these measures, we can more objectively compare haplotype block structures and tagging SNP sets between different populations. In addition, these measures allow us to compare the results of different methods for block partition and tagging SNP identification. When we applied these measures to a real data set on chromosome 10 in 16 worldwide populations, we found that in this genome region: 1) haplotype block boundaries vary among populations, with European and some African populations showing similar boundaries but other populations showing other patterns; 2) tagging SNP sets are generally similar for populations with similar haplotype block structures but differ if the block structures differ; and 3) all but one of the block finding methods we tested yield consistent results, although variations exist regarding consistency. Our tentative results show that at least in the genome region studied, it is unlikely that a common haplotype pattern exists for all human populations: many populations, even in the same geographical region, may have different haplotype patterns.

Chromosome Mapping↗

PubMed2004

Fine mapping of a seizure susceptibility locus on mouse Chromosome 1: nomination of Kcnj10 as a causative gene.

Previous quantitative trait loci (QTL) mapping studies document that the distal region of mouse Chromosome (Chr) 1 contains a gene(s) that is in large part responsible for the difference in seizure susceptibility between C57BL/6 (B6) (relatively seizure-resistant) and DBA/2 (D2) (relatively seizure-sensitive) mice. We now confirm this seizure-related QTL ( Szs1) using reciprocal, interval-specific congenic strains and map it to a 6.6-Mb segment between Pbx1 and D1Mit150. Haplotype conservation between strains within this segment suggests that Szs1 may be localized more precisely to a 4.1-Mb critical interval between Fcgr3 and D1Mit150. We compared the coding region sequences of candidate genes between B6 and D2 mice using RT-PCR, amplification from genomic DNA, and database searching and discovered 12 brain-expressed genes with SNPs that predict a protein amino acid variation. Of these, the most compelling seizure susceptibility candidate is Kcnj10. A survey of the Kcnj10 SNP among other inbred mouse strains revealed a significant effect on seizure sensitivity such that most strains possessing a haplotype containing the B6 variant of Kcnj10 have higher seizure thresholds than those strains possessing the D2 variant. The unique role of inward-rectifying potassium ion channels in membrane physiology coupled with previous strong association between ion channel gene mutations and seizure phenotypes puts even greater focus on Kcnj10 in the present model. In summary, we confirmed a seizure-related QTL of large effect on mouse Chr 1 and mapped it to a finely delimited region. The critical interval contains several candidate genes, one of which, Kcnj10, exhibits a potentially important polymorphism with regard to fundamental aspects of seizure susceptibility.

Amino Acid Sequence↗

PubMed2004

Study of Arabidopsis thaliana resistome in response to cucumber mosaic virus infection using whole genome microarray.

The plant innate immune response is mediated by resistance (R) genes and involves hypersensitive response (HR) cell death. During resistance responses, the host undergoes net changes in the transcriptome. To understand these changes, we generated a whole genome transcript profile for RCY1-mediated resistance to cucumber mosaic virus strain Y (CMV-Y) in Arabidopsis. Using a very stringent selection criterion, we identified 444 putative factors belonging to nine different functional classes that show significant transcript regulation during Arabidopsis-CMV-Y interaction. Genes with unknown function formed the largest class. Other functional classes represented in the resistome include kinases and phosphatases, protein degradation machinery/proteases, transcriptional regulators, and others. Interestingly, several of the unknown function genes possess well characterized domains and secondly many genes encode small peptides with less than 100 amino acids. Analysis of 1.1 kb promoter regions of the 444 genes revealed that 9 out of the 12 known cis-binding elements are significantly associated with pathogen responsive cluster. Location and distribution of five prominent binding elements for select group of disease resistance related and unknown function genes is presented. The analysis also revealed 80 defense-responsive genes that might participate in R gene-mediated defense against both viral and bacterial pathogens. In addition, chromosome distribution of genes that respond to bacterial and viral pathogens suggests that they are located in small gene clusters and may be transcriptionally co-regulated. Exploring the precise function of the new genes identified in this analysis will offer new insights into plant defense.

Analysis of Variance↗

PubMed2004

An arabidopsis promoter microarray and its initial usage in the identification of HY5 binding targets in vitro.

To analyze transcription factor-promoter interactions in Arabidopsis, a general strategy for generating a promoter microarray has been established. This includes an integrated platform for promoter sequence extraction and the design of primers for the PCR amplification of the promoter regions of annotated genes in the Arabidopsis genome. A web-interfaced primer-retrieval program was used to obtain up to 10 primer pairs with a suitability ranking given to each gene. We selected primer pairs for the promoters of about 3800 genes, and greater than 95% of the promoter fragments from the total genomic DNA were successfully amplified by PCR. These PCR products were purified and used to print an Arabidopsis promoter microarray. This initial promoter microarray was used to study the in vitro binding of the transcription factor HY5 to its promoter targets. A set of promoter fragments exhibited consistent and strong interaction with the HY5 protein in vitro, and computational analysis revealed that they were enriched with the HY5 consensus binding G-box motif. Thus, a promoter microarray can be a useful tool for identifying transcription factor binding sites at the genomic scale in higher plants.

Arabidopsis↗

PubMed2004

Analyzing cellular biochemistry in terms of molecular networks.

One way to understand cells and circumscribe the function of proteins is through molecular networks. These networks take a variety of forms including webs of protein-protein interactions, regulatory circuits linking transcription factors and targets, and complex pathways of metabolic reactions. We first survey experimental techniques for mapping networks (e.g., the yeast two-hybrid screens). We then turn our attention to computational approaches for predicting networks from individual protein features, such as correlating gene expression levels or analyzing sequence coevolution. All the experimental techniques and individual predictions suffer from noise and systematic biases. These problems can be overcome to some degree through statistical integration of different experimental datasets and predictive features (e.g., within a Bayesian formalism). Next, we discuss approaches for characterizing the topology of networks, such as finding hubs and analyzing subnetworks in terms of common motifs. Finally, we close with perspectives on how network analysis represents a preliminary step toward a systems approach for modeling cells.

Biochemical Phenomena↗

PubMed2004

The impact of sample size and marker selection on the study of haplotype structures.

Several studies of haplotype structures in the human genome in various populations have found that the human chromosomes are structured such that each chromosome can be divided into many blocks, within which there is limited haplotype diversity. In addition, only a few genetic markers in a putative block are needed to capture most of the diversity within a block. There has been no systematic empirical study of the effects of sample size and marker set on the identified block structures and representative marker sets, however. The purpose of this study was to conduct a detailed empirical study to examine such impacts. Towards this goal, we have analysed three representative autosomal regions from a large genome-wide study of haplotypes with samples consisting of African-Americans and samples consisting of Japanese and Chinese individuals. For both populations, we have found that the sample size and marker set have significant impact on the number of blocks and the total number of representative markers identified. The marker set in particular has very strong impacts, and our results indicate that the marker density in the original datasets may not be adequate to allow a meaningful characterisation of haplotype structures. In general, we conclude that we need a relatively large sample size and a very dense marker panel in the study of haplotype structures in human populations.

Black or African American↗

PubMed2004

Genomic approaches in dissecting complex biological pathways.

Advances in genomic research have provided many types of large-scale data that contain rich information on various biological pathways. Intensive efforts have been made to qualitatively or quantitatively model biological pathways using these genomic data. Some general network properties, such as the scale-free property and network motifs, have been discussed and various network models have been applied to reconstruct pathways. However, there is a lack of systematic integration of prior knowledge and different genomic data in these analyses. In this review, we discuss pathway reconstruction under the consideration of the complexity embedded in the biological system, and the global and local properties of biological pathways. We review major methodologies, including clustering methods, scale-free networks models, Bayesian networks models, Boolean networks models, systems of differential equations, and data integration methods. We focus on the difficulty of each methodology in modeling biological pathways, and emphasize that different models capture different aspects of biological pathways or genomic data. The 'noisy' large-scale genomic data require the mathematical models and computational methods to be both robust and identifiable. In addition, we believe that ideal models should have the capability of incorporating various data types and these models need to be assessed through rigorous comparisons with empirical data.

Bayes Theorem↗

PubMed2004

An obesity-related locus in chromosome region 12q23-24.

Obesity is a growing health problem in the U.S. As a complex trait, obesity involves multiple genes and gene-gene and gene-environment interactions that contribute to its pathogenesis. Here we report significant linkage from a scan of a large sample segregating extreme obesity and normal weight. We have used 382 microsatellite markers in 1,297 individuals from 260 European-American families. We conducted nonparametric linkage (NPL) analyses for dichotomous BMI (using BMI >/=27, >/=30, >/=35, and >/=40 kg/m(2)) using Genehunter. We also analyzed quantitative traits (BMI, percentage of fat, and waist circumference) by the family regression method using Merlin_regress. We found evidence for linkage on chromosome 12 (125 cM, D12S2070, logarithm of odds [LOD] 3.79, P = 0.00001 for percentage of fat; LOD 2.98, P = 0.0001 for BMI; and LOD 2.86, P = 0.00014 for waist circumference) by family regression analyses. Adding three additional markers to the intervals flanking the chromosome 12 peak yielded an LOD score of 4.08 (P = 0.00001) for percentage of fat at 116 cM and LOD scores of 3.57 (P = 0.00003) and 3.05 (P = 0.00009) for BMI and waist circumference, respectively, at 125 cM. We also obtained other suggestive linkages on chromosomes 2, 3, 7, 8, 9, 12, 13, and 21. Our results suggest multiple loci that could influence obesity, particularly a locus in chromosome region 12q23-24.

Adolescent↗

PubMed2003

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

Arabidopsis↗

PubMed2003

A genome-wide analysis of blue-light regulation of Arabidopsis transcription factor gene expression during seedling development.

A microarray based on PCR amplicons of 1864 confirmed and predicted Arabidopsis transcription factor genes was produced and used to profile the global expression pattern in seedlings, specifically their light regulation. We detected expression of 1371 and 1241 genes in white-light- and dark-grown 6-d-old seedlings, respectively. Together they account for 84% of the transcription factor genes examined. This array was further used to study the kinetics of transcription factor gene expression change of dark-grown seedlings in response to blue light and the role of specific photoreceptors in this blue-light regulation. The expression of about 20% of those transcription factor genes are responsive to blue-light exposure, with 249 and 115 genes up or down-regulated, respectively. A large portion of blue-light-responsive transcription factor genes exhibited very rapid expression changes in response to blue light, earlier than the bulk of blue-light-regulated genes. This result suggests the involvement of transcription cascades in blue-light control of genome expression. Comparative analysis of the expression profiles of wild type and various photoreceptor mutants demonstrated that during early seedling development cryptochromes are the major photoreceptors for blue-light control of transcription factor gene expression, whereas phytochrome A and phototropins play rather limited roles.

Arabidopsis↗

PubMed2003

Sample size needed to detect gene-gene interactions using association designs.

It is likely that many complex diseases result from interactions among several genes, as well as environmental factors. The presence of such interactions poses challenges to investigators in identifying susceptibility genes, understanding biologic pathways, and predicting and controlling disease risks. Recently, Gauderman (Am J Epidemiol 2002;155:478-84) reported results from the first systematic analysis of the statistical power needed to detect gene-gene interactions in association studies. However, Gauderman used different statistical models to model disease risks for different study designs, and he assumed a very low disease prevalence to make different models more comparable. In this article, assuming a logistic model for disease risk for different study designs, the authors investigate the power of population-based and family-based association designs to detect gene-gene interactions for common diseases. The results indicate that population-based designs are more powerful than family-based designs for detecting gene-gene interactions when disease prevalence in the study population is moderate.

Genetic Predisposition to Disease↗

PubMed2003

Quantitative trait loci in Anopheles gambiae controlling the encapsulation response against Plasmodium cynomolgi Ceylon.

BACKGROUND: Anopheles gambiae females are the world's most successful vectors of human malaria. However, a fraction of these mosquitoes is refractory to Plasmodium development. L3-5, a laboratory selected refractory strain, encapsulates transforming ookinetes/early oocysts of a wide variety of Plasmodium species. Previous studies on these mosquitoes showed that one major (Pen1) and two minor (Pen2, Pen3) autosomal dominant quantitative trait loci (QTLs) control the melanotic encapsulation response against P. cynomolgi B, a simian malaria originating in Malaysia. RESULTS: We have investigated the response of L3-5 to infection with P. cynomolgi Ceylon, a different but related parasite species, in crosses with the susceptible strain 4Arr. Refractoriness to this parasite is incompletely recessive. Infection and genotyping of F2 intercross females at genome-spanning microsatellite loci revealed that 3 autosomal QTLs control encapsulation of this species. Two loci map to the regions containing Pen2 and Pen3. The novel QTL maps to chromosome 3R, probably to polytene division 32 or 33. Thus the relative contribution of any QTL to oocyst encapsulation varies with the species of parasite. Further, different QTLs were most readily identified in different F2 families. This, like the F1 data, suggests that L3-5 is not genetically homogeneous and that somewhat different pathways may be used to achieve an encapsulation response. CONCLUSION: We have shown here that different QTLs are involved in responses against different Plasmodium parasites.

Animals↗

PubMed2003

Fragment screening and assembly: a highly efficient approach to a selective and cell active protein tyrosine phosphatase 1B inhibitor.

Using an NMR-based fragment screening and X-ray crystal structure-based assembly, starting with millimolar ligands for both the catalytic site and the second phosphotyrosine binding site, we have identified a small-molecule inhibitor of protein tyrosine phosphatase 1B with low micromolar inhibition constant, high selectivity (30-fold) over the highly homologous T-cell protein tyrosine phosphatase, and good cellular activity in COS-7 cells.

Animals↗

PubMed2003

Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data.

MOTIVATION: Novel methods, both molecular and statistical, are urgently needed to take advantage of recent advances in biotechnology and the human genome project for disease diagnosis and prognosis. Mass spectrometry (MS) holds great promise for biomarker identification and genome-wide protein profiling. It has been demonstrated in the literature that biomarkers can be identified to distinguish normal individuals from cancer patients using MS data. Such progress is especially exciting for the detection of early-stage ovarian cancer patients. Although various statistical methods have been utilized to identify biomarkers from MS data, there has been no systematic comparison among these approaches in their relative ability to analyze MS data. RESULTS: We compare the performance of several classes of statistical methods for the classification of cancer based on MS spectra. These methods include: linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbor classifier, bagging and boosting classification trees, support vector machine, and random forest (RF). The methods are applied to ovarian cancer and control serum samples from the National Ovarian Cancer Early Detection Program clinic at Northwestern University Hospital. We found that RF outperforms other methods in the analysis of MS data.

Algorithms↗

PubMed2003

ras mutations are associated with aggressive tumor phenotypes and poor prognosis in thyroid cancer.

PURPOSE: ras oncogenic activation has long been demonstrated in thyroid carcinomas of follicular cell derivation, but no consistent relationship has been shown between mutations and clinicopathologic features. MATERIALS AND METHODS: We analyzed H-, K-, and N-ras mutations by polymerase chain reaction-single-strand conformational polymorphism followed by DNA sequencing in 125 thyroid carcinoma specimens from 107 patients, to include tumors covering the entire spectrum of thyroid tumor differentiation. RESULTS: Mutations were identified in four (8.2%) of 49 well-differentiated carcinomas (WDCs; two [6.7%] of 30 of the tumors were papillary carcinomas, two [10.5%] of 19 of them were follicular carcinomas), in 16 (55.2%) of 29 poorly differentiated carcinomas (PDCs), and in 15 (51.7%) of 29 undifferentiated carcinomas, with a significant association between ras mutation and poorly or undifferentiated tumors (P <.001). Twenty-six (74.3%) of 35 patients with ras-mutated tumors died as a result of disease as opposed to 23 (31.9%) of 72 patients with tumors lacking the mutations. Among patients with differentiated thyroid carcinomas (WDC and PDC), 11 (55.0%) of 20 patients with mutated tumors died as a result of disease as opposed to nine (15.5%) of 58 patients with wild-type ras tumors, and the correlation was independent of tumor differentiation and stage (P =.016). K-ras codon 13 mutations (all with G-A nucleotide transitions resulting in Gly>Asp substitution) and single activating mutations in any of the ras genes were also independent predictors of poor survival in differentiated thyroid carcinomas (P =.027 and P =.007, respectively). CONCLUSION: These findings demonstrate that ras mutations are a marker for aggressive cancer behavior and indicate a possible role of ras genotyping to identify thyroid carcinoma subsets associated with poor prognosis.

Carcinoma, Papillary, Follicular↗

PubMed2003

Protein-DNA interaction mapping using genomic tiling path microarrays in Drosophila.

We demonstrate the use of a chromosomal walk (or "tiling path") printed as DNA microarrays for mapping protein-DNA interactions across large regions of contiguous genomic DNA in Drosophila melanogaster. Microarrays were constructed with genomic DNA fragments 430-920 bp in length, covering 2.9 million base pairs of the Adh-cactus region of chromosome 2 and 85,000 base pairs of the 82F region of chromosome 3. We performed DNA localization mapping for the heterochromatin protein HP1 and for the sequence-specific GAGA transcription factor, producing a comprehensive, high-resolution map of in vivo protein-DNA interactions throughout these regions of the Drosophila genome.

Amino Acid Motifs↗

PubMed2003

Haplotypes at the OPRM1 locus are associated with susceptibility to substance dependence in European-Americans.

Our objective was to investigate the relationship between the gene encoding the mu-opioid receptor (OPRM1) and susceptibility to substance dependence in European-American (EA) and African-American (AA) subjects. Eight single nucleotide polymorphisms (SNPs) at the OPRM1 locus, i.e., -2044C/A, -1793T/A, -1699insT, -1469T/C, -1320A/G, -111C/T, +17C/T (Ala6Val), and +118A/G (Asn40Asp) were genotyped in 676 subjects: 318 EA subjects and 124 AA subjects with substance dependence, and 179 EA normal controls, and 55 AA normal controls. Affection status was defined by each unique combination of alcohol, cocaine, and opioid dependence and analysis of association examined in relation to the possible combinations. We used a newly implemented permutation method to evaluate statistical significance. In EAs, a significant difference in haplotype frequency distributions was found between controls and "alcohol + opioid" dependent patients (P = 0.0036). This finding is also supported by logistic regression analysis and a simulation method. The frequencies of allele -2044A and haplotypes including -2044A are higher in these patients than in controls. In AAs, no allele, haplotype, or genotype frequencies were significantly different between cases and controls. There were highly significant differences in the allele, haplotype, and genotype frequencies between EA and AA controls. Four of the variants [-1793T/A, -1699insT, -1320A/G, and -111C/T] are in virtually complete linkage disequilibrium (LD) to compose a sequence pattern, which does not associate with any of the seven categories of substance dependence. In EAs, allele -2044A and haplotypes that include -2044A are the susceptibility allele and haplotypes for substance dependence. These findings suggest that OPRM1 may play a role in the pathophysiology of substance dependence and this role is population- and diagnosis-specific.

Alcoholism↗

PubMed2003

Hypertonic induction of COX-2 expression in renal medullary epithelial cells requires transactivation of the EGFR.

Hypertonic stress increases expression of cyclooxygenase-2 (COX-2) in renal medullary epithelial and interstitial cells. Because hypertonic COX-2 expression is, in part, sensitive to inhibition of the ERK MAPK, an effector of activated receptor tyrosine kinases such as the EGF receptor, we investigated a role for this receptor in signaling to COX-2 expression. Hypertonic stress increased COX-2 expression at the mRNA and protein levels at 6 and 24 h of hypertonic treatment. Two potent, specific inhibitors of the EGF receptor kinase, AG-1478 and PD-153035, abrogated this effect. These inhibitors also blocked the ability of hypertonic stress to increase PGE2 release; in addition, they partially blocked tonicity-dependent phosphorylation of ERK but not of the related MAPKs, JNK or p38. Pharmacological inhibition of ERK activation partially blocked tonicity-dependent COX-2 expression. Hypertonic induction of COX-2 was likely transcriptionally mediated, as NaCl stress increased luciferase reporter gene activity under control of the human COX-2 promoter, and this effect was also sensitive to inhibition of the EGF receptor kinase. Metalloproteinase action is required for transactivation of the EGF receptor. Pharmacological inhibition of metalloproteinase function blocked tonicity-inducible COX-2 expression. Furthermore, the effect of hypertonicity on COX-2 expression was also evident in the EGF-responsive Madin-Darby canine kidney and 3T3 cell lines but was virtually absent from the EGF-unresponsive (and EGF receptor null) Chinese hamster-derived CHO cell line. Taken together, these data indicate that hypertonicity-dependent COX-2 expression in medullary epithelial cells requires transactivation of the EGF receptor and, potentially, ectodomain cleavage of an EGF receptor ligand.

Animals↗