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Tianhua Niu

Publications and source records attributed to Tianhua Niu.

9 recordsLinked to original sources
PubMed2003

SeqVISTA: a graphical tool for sequence feature visualization and comparison.

BACKGROUND: Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982-14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. RESULTS: SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. CONCLUSION: SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at http://zlab.bu.edu/SeqVISTA.

Amino Acid Sequence↗
PubMed2003

Haplotype information and linkage disequilibrium mapping for single nucleotide polymorphisms.

Single nucleotide polymorphisms in the human genome have become an increasingly popular topic in that their analyses promise to be a key step toward personalized medicine. We investigate two related questions, how much the haplotype information contributes to linkage disequilibrium (LD) mapping and whether an in silico haplotype construction preceding the LD analysis can help. For disease gene mapping, using both simulated and real data sets on cystic fibrosis and the Alzheimer disease, we reached the following conclusions: (1) for simple Mendelian diseases, in which case a tractable full statistical model can be developed, the loss of haplotype information for either control or disease data do not have a great impact on LD fine mapping, and haplotype inference should be carried out jointly with LD mapping; (2) for complex diseases, inferring haplotype phases for individuals prior to LD mapping helps achieve a better accuracy. An improved version of the linkage disequilibrium mapping program, BLADE v2, is available at http://www.fas.harvard.edu/junliu/TechRept/03folder/bladev2.tgz.

Algorithms↗
PubMed2002

Maternal cigarette smoking, metabolic gene polymorphism, and infant birth weight.

CONTEXT: Little is known about genetic susceptibility to cigarette smoke in relation to adverse pregnancy outcomes. OBJECTIVE: To investigate whether the association between maternal cigarette smoking and infant birth weight differs by polymorphisms of 2 maternal metabolic genes: CYP1A1 and GSTT1. DESIGN, SETTING, AND PARTICIPANTS: Case-control study conducted in 1998-2000 among 741 mothers (174 ever smokers and 567 never smokers) who delivered singleton live births at Boston Medical Center. A total of 207 cases were preterm or low-birth-weight infants and 534 were non-low-birth-weight, full-term infants (control). MAIN OUTCOME MEASURE: Birth weight, gestation, fetal growth by smoking status and CYP1A1 MspI (AA vs Aa and aa, where Aa and aa were combined because of small numbers of aa and similar results), and GSTT1 (present vs absent) genotypes. RESULTS: Without consideration of genotype, continuous maternal smoking during pregnancy was associated with a mean reduction of 377 g (SE, 89 g) in birth weight (odds ratio [OR], 2.1; 95% confidence interval [CI], 1.2-3.7). When CYP1A1 genotype was considered, the estimated reduction in birth weight was 252 g (SE, 111 g) for the AA genotype group (n = 75; OR, 1.3; 95% CI, 0.6-2.6), but was 520 g (SE, 124 g) for the Aa/aa genotype group (n = 43 for Aa, n = 6 for aa; OR, 3.2; 95% CI, 1.6-6.4). When GSTT1 genotype was considered, the estimated reduction in birth weight was 285 g (SE, 99 g) (OR, 1.7; 95% CI, 0.9-3.2) and 642 g (SE, 154 g) (OR, 3.5; 95% CI, 1.5-8.3) for the present and absent genotype groups, respectively. When both CYP1A1 and GSTT1 genotypes were considered, the greatest reduction in birth weight was found among smoking mothers with the CYP1A1 Aa/aa and GSTT1 absent genotypes (-1285 g; SE, 234 g; P<.001). Among never smokers, genotype did not independently confer an adverse effect. A similar pattern emerged in analyses stratified by maternal ethnicity and in analyses for gestation. CONCLUSIONS: In our study, maternal CYP1A1 and GSTT1 genotypes modified the association between maternal cigarette smoking and infant birth weight, suggesting an interaction between metabolic genes and cigarette smoking.

Adult↗
PubMed2002

The linkage information content value of polymorphism genetic markers in model-free linkage analysis.

Guo and Elston [Hum Hered 1999;49:112-118] developed a linkage information content (LIC) value to measure the informativeness of a marker for identity-by-descent (IBD) sharing status of relative pairs. LIC values were derived for five types of relative pairs: full sib, half sib, grandparent-grandchild, first cousin and avuncular. In this paper, we give corrected LIC values for full sib, grandparent-grandchild, first cousin and avuncular pairs, and indicate the availability of a computer program to calculate them.

Chromosome Mapping↗
PubMed2002

Angiotensin converting enzyme gene insertion/deletion polymorphism and cardiovascular disease: therapeutic implications.

Cardiovascular disease is the major cause of morbidity and mortality in Westernised societies. It is well known that the aetiology of this devastating disorder involves both genetic and environmental factors. Sequence variants of the components of the renin-angiotensin-aldosterone system and the kallikrein-kinin system are suggested to have significant influences on cardiovascular homeostasis. Both gene targeting and transgenic studies in mice have clearly suggested a critical role of the angiotensin converting enzyme (ACE) gene in blood pressure regulation. Furthermore, an up-regulation of myocardial ACE gene expression has been observed in patients with heart failure. Thus, the ACE gene has been recognised as a top candidate gene for cardiovascular research. Over the past decade, the insertion/deletion (I/D) polymorphism of a 287-bp Alu element in intron 16 of the ACE gene has attracted significant attention and has been extensively investigated in a spectrum of cardiovascular phenotypes, because of its correlation with serum ACE activity. A large majority of previous studies have shown a positive association between the DD genotype and an increased risk of myocardial infarction, but results in hypertension, left ventricular hypertrophy, cardiomyopathy and restenosis after percutaneous transluminal coronary angioplasty remain quite controversial. Since ACE inhibitors are widely used in hypertension and congestive heart failure, we also review the literature on the relationship of ACE I/D polymorphism with ACE inhibitor response. It appears that this polymorphism has some moderate impact on the cardiovascular response to ACE inhibitors but there is no consensus as to which allele confers a more pronounced effect. In addition, previous data are suggestive of an association between the ACE I allele and a greater risk of increased occurrence of ACE inhibitor-induced cough, but such a relationship needs further confirmation. Overall, since ACE I/D is only an intronic marker, the true locus that controls the ACE enzyme activity remains to be identified, and could be located within either the ACE gene or another nearby gene such as the human growth hormone gene. We note that since associations tend to vary across different gender or ethnic groups, or across different socio-ecological settings, consideration of potential gene-gene and gene-environment interactions should be made. Furthermore, the dissection of the genetic underpinning of cardiovascular disease needs delineation of all molecular variants of the key physiological pathways that influence cardiovascular function.

Angiotensin-Converting Enzyme Inhibitors↗
PubMed2002

Insertion/deletion polymorphism of the ACE gene is associated with type 2 diabetes.

In an attempt to examine the role of an ACE gene insertion/deletion (I/D) polymorphism in type 2 diabetes, we conducted a case-control association study among 132 couple-pairs from northern China. The genotype frequencies for II, ID, and DD were 39.8, 39.8, and 20.3%, respectively, in the case group and 44.8, 44.8, and 10.4% in the control group. The DD frequency was significantly higher in the case group than in the control group (chi(2)(1) = 4.77, P = 0.03), suggesting that the DD genotype is associated with an increased susceptibility to type 2 diabetes in our study population.

Adult↗
PubMed2002

Association of GYS1 and beta(3)-AR gene with postprandial hyperglycemia and serum uric acid in type 2 diabetes mellitus.

OBJECTIVE: To determine the relationships of Met416Val and XbaI polymorphism of muscle glycogen synthase (GYS1) gene and Trg64Arg variant of the beta(3)-adrenergic-receptor (beta(3)-AR) gene with type 2 diabetes mellitus (DM) and its intermediate phenotypes in the Chinese population. METHODS: Polymerase chain reaction-oligonucleotide ligation assay and restriction fragment length polymorphism assay were used to evaluate the GYS1 and beta(3)-AR gene polymorphisms in 102 pairs of case-control Chinese spouses. RESULTS: Subjects with Met416Val variant had a significantly higher 2-hour post-glucose level than subjects without this variant had in diabetic group (P = 0.032). The Met416Val polymorphism of GYS1 gene was not significantly associated with the risk of type 2 DM (adjusted OR = 1.67; 95% CI: 0.73 - 3.81, P = 0.223). Subjects with Trp64Arg variant had a significantly higher serum uric acid level than subjects without this variant had in diabetic group (P = 0.034). The combination of BMI and Arg64 allele carrier of the beta(3)-AR gene increased the diabetic risk over four-fold (adjusted OR = 4.00; 95% CI: 1.53 - 10.45, P = 0.005). CONCLUSIONS: In the Chinese population, Met416Val polymorphism is identified in a subgroup of diabetic subjects with high 2-hour post-glucose. It will explain why some diabetic patients appear to be genetically predisposed to developing high postpradial glucose level. The presence of the Arg64 allele in the beta(3)-AR gene may predispose patients to higher serum uric acid level.

Adult↗
PubMed2001

Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms.

Haplotypes have gained increasing attention in the mapping of complex-disease genes, because of the abundance of single-nucleotide polymorphisms (SNPs) and the limited power of conventional single-locus analyses. It has been shown that haplotype-inference methods such as Clark's algorithm, the expectation-maximization algorithm, and a coalescence-based iterative-sampling algorithm are fairly effective and economical alternatives to molecular-haplotyping methods. To contend with some weaknesses of the existing algorithms, we propose a new Monte Carlo approach. In particular, we first partition the whole haplotype into smaller segments. Then, we use the Gibbs sampler both to construct the partial haplotypes of each segment and to assemble all the segments together. Our algorithm can accurately and rapidly infer haplotypes for a large number of linked SNPs. By using a wide variety of real and simulated data sets, we demonstrate the advantages of our Bayesian algorithm, and we show that it is robust to the violation of Hardy-Weinberg equilibrium, to the presence of missing data, and to occurrences of recombination hotspots.

Algorithms↗