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Shuying Sue Li

Publications and source records attributed to Shuying Sue Li.

7 recordsLinked to original sources

A haplotype-linkage analysis method for estimating recombination rates using dense SNP trio data.

Meiotic recombination is an important evolution force in shaping human genomes and creating human diversity. Recent explorations suggest that meiotic recombination events tend to happen in certain regions of the genome, leading to the hypothesis of recombination hot spots. To identify such hot spots, we describe an empirical method for estimating the recombination rate, which reflects both historical and current meiotic events, using unphased genotypes from nuclear families, in particular, parents-child trios. The key idea is that use of the haplotypic polymorphisms with multiple adjacent SNPs will increase the number of informative meioses and hence would improve the power of linkage analysis. Since haplotypes of individuals are not directly observed, e.g., in HapMap data, we infer the haplotypes simultaneously while estimating recombination rate. We refer this described method as haplotype-linkage (HALIN) method. Our simulation results show that HALIN gives unbiased estimates of recombination rate. We apply HALIN to analyze the genotype data of chromosome 20 from HapMap data and compare the results to the results using two existing methods, Bayesian coalescent method described by McVean et al. [2004] science 304:581-584 and empirical method by Clarke and Cardon ([2005] Genetics). Results suggest that HALIN identified 75 hot spots on chromosome 20, and 85% of them are also identified by the method by McVean et al. ([2004] science 304:581-584), in addition to a few new hot spots. In comparison with Clarke and Cardon's result, estimated recombination rates (RRs) under these 75 hot spots are significantly greater than those outside of hot spots, which support the general consistency in discovering recombination hot spots between two methods.

Child↗

HLA-E, HLA-F, and HLA-G polymorphism: genomic sequence defines haplotype structure and variation spanning the nonclassical class I genes.

Despite several studies that defined the polymorphism of the nonclassical human leukocyte antigen-E (HLA-E), HLA-F, and HLA-G genes, most polymorphisms thus far examined in correlative studies were derived from the coding sequences of these genes. In addition, some discrepancies and ambiguities in the available data have persisted in current databases. To expand the data available and to resolve some of the discrepant data, we have defined protocols that allow for the amplification of 6 to 7 kb of contiguous genomic sequence for each gene, including all of the coding and intron sequences, approximately 2 kb of 5' flanking promoter sequence, and 1 kb of 3' flanking sequence. Using long-range polymerase chain reaction (PCR) protocols, generating either one or two PCR products depending on the locus, amplified genomic DNA was directly sequenced to completion using a set of about 30 primers over each locus to yield contiguous sequence data from both strands. Using this approach, we sequenced 33 genomic DNAs, from Asian, African American, and Caucasian samples. The results of this analysis confirmed several previously reported coding sequence variants, identified several new allelic variants, and also defined extensive variation in intron and flanking sequences. It was possible to construct haplotype maps and to identify tagging single nucleotide polymorphisms that can be used to detect the composite variation spanning all three genes.

Alleles↗

Toward understanding MHC disease associations: partial resequencing of 46 distinct HLA haplotypes.

We carried out a resequencing project that examined 552 kb of sequence from each of 46 individual HLA haplotypes representing a diversity of HLA allele types, generating nearly 27 Mb of fully phased genomic sequence. Haplotype blocks were defined extending from telomeric of HLA-F to centromeric of HLA-DP including in total 5186 MHC SNPs. To investigate basic questions about the evolutionary origin of common HLA haplotypes, and to obtain an estimate of rare variation in the MHC, we similarly examined two additional sets of samples. In 19 independent HLA-A1, B8, DR3 chromosomes, the most common HLA haplotype in Northern European Caucasians, variation was found at 11 SNP positions in the 3600-kb region from HLA-A to DR. Partial resequencing of 282 individuals in the gene-dense class III region identified significant variability beyond what could have been detected by linkage to common SNPs.

Cell Line, Transformed↗

Genetic association of the antiviral restriction factor TRIM5alpha with human immunodeficiency virus type 1 infection.

The innate antiviral factor TRIM5alpha restricts the replication of some retroviruses through its interaction with the viral capsid protein, leading to abortive infection. While overexpression of human TRIM5alpha results in modest restriction of human immunodeficiency virus type 1 (HIV-1), this inhibition is insufficient to block productive infection of human cells. We hypothesized that polymorphisms within TRIM5 may result in increased restriction of HIV-1 infection. We sequenced the TRIM5 gene (excluding exon 5) and the 4.8-kb 5' putative regulatory region in genomic DNA from 110 HIV-1-infected subjects and 96 exposed seronegative persons, along with targeted gene sequencing in a further 30 HIV-1-infected individuals. Forty-eight single nucleotide polymorphisms (SNPs), including 20 with allele frequencies of >1.0%, were identified. Among these were two synonymous and eight nonsynonymous coding polymorphisms. We observed no association between TRIM5 polymorphism in HIV-1-infected subjects and their set-point viral load after acute infection, although one TRIM5 haplotype was weakly associated with more rapid CD4(+) T-cell loss. Importantly, a TRIM5 haplotype containing the nonsynonymous SNP R136Q showed increased frequency among HIV-1-infected subjects relative to exposed seronegative persons, with an odds ratio of 5.49 (95% confidence interval = 1.83 to 16.45; P = 0.002). Nonetheless, we observed no effect of individual TRIM5alpha nonsynonymous mutations on the in vitro HIV-1 susceptibility of CD4(+) T cells. Therefore, any effect of TRIM5alpha polymorphism on HIV-1 infection in primary lymphocytes may depend on combinations of SNPs or on DNA sequences in linkage disequilibrium with the TRIM5alpha coding sequence.

Adult↗

A common dominant TLR5 stop codon polymorphism abolishes flagellin signaling and is associated with susceptibility to legionnaires' disease.

Although Toll-like receptors (TLRs) are critical mediators of the immune response to pathogens, the influence of polymorphisms in this gene family on human susceptibility to infection is poorly understood. We demonstrated recently that TLR5 recognizes flagellin, a potent inflammatory stimulus present in the flagellar structure of many bacteria. Here, we show that a common stop codon polymorphism in the ligand-binding domain of TLR5 (TLR5392STOP) is unable to mediate flagellin signaling, acts in a dominant fashion, and is associated with susceptibility to pneumonia caused by Legionella pneumophila, a flagellated bacterium. We also show that flagellin is a principal stimulant of proinflammatory cytokine production in lung epithelial cells. Together, these observations suggest that TLR5392STOP increases human susceptibility to infection through an unusual dominant mechanism that compromises TLR5's essential role as a regulator of the lung epithelial innate immune response.

Codon, Terminator↗

A method for the assessment of disease associations with single-nucleotide polymorphism haplotypes and environmental variables in case-control studies.

The rough draft of the human genome map has been used to identify most of the functional genes in the human genome, as well as to identify nucleotide variations, known as "single-nucleotide polymorphisms" (SNPs), in these genes. By use of advanced biotechnologies, researchers are beginning to genotype thousands of SNPs from biological samples. Among the many possible applications, one of them is the study of SNP associations with complex human diseases, such as cancers or coronary heart diseases, by using a case-control study design. Through the gathering of environmental risk factors and other lifestyle factors, such a study can be effectively used to investigate interactions between genes and environmental factors in their associations with disease phenotype. Earlier, we developed a method to statistically construct individuals' haplotypes and to estimate the distribution of haplotypes of multiple SNPs in a defined population, by use of estimating-equation techniques. Extending this idea, we describe here an analytic method for assessing the association between the constructed haplotypes along with environmental factors and the disease phenotype. This method is also robust to the model assumptions and is scalable to a large number of SNPs. Asymptotic properties of estimations in the method are proved theoretically and are tested for finite sample sizes by use of simulations. To demonstrate the use of the method, we applied it to assess the possible association between apolipoprotein CIII (six coding SNPs) and restenosis by using a case-control data set. Our analysis revealed two haplotypes that may reduce the risk of restenosis.

Apolipoprotein C-III↗

Estimating haplotype frequencies and standard errors for multiple single nucleotide polymorphisms.

Estimating haplotype frequencies becomes increasingly important in the mapping of complex disease genes, as millions of single nucleotide polymorphisms (SNPs) are being identified and genotyped. When genotypes at multiple SNP loci are gathered from unrelated individuals, haplotype frequencies can be accurately estimated using expectation-maximization (EM) algorithms (Excoffier and Slatkin, 1995; Hawley and Kidd, 1995; Long et al., 1995), with standard errors estimated using bootstraps. However, because the number of possible haplotypes increases exponentially with the number of SNPs, handling data with a large number of SNPs poses a computational challenge for the EM methods and for other haplotype inference methods. To solve this problem, Niu and colleagues, in their Bayesian haplotype inference paper (Niu et al., 2002), introduced a computational algorithm called progressive ligation (PL). But their Bayesian method has a limitation on the number of subjects (no more than 100 subjects in the current implementation of the method). In this paper, we propose a new method in which we use the same likelihood formulation as in Excoffier and Slatkin's EM algorithm and apply the estimating equation idea and the PL computational algorithm with some modifications. Our proposed method can handle data sets with large number of SNPs as well as large numbers of subjects. Simultaneously, our method estimates standard errors efficiently, using the sandwich-estimate from the estimating equation, rather than the bootstrap method. Additionally, our method admits missing data and produces valid estimates of parameters and their standard errors under the assumption that the missing genotypes are missing at random in the sense defined by Rubin (1976).

Algorithms↗