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Research on single nucleotide polymorphisms interaction detection from network perspective.

ABSTRACT: Single Nucleotide Polymorphisms (SNPs) found in Genome-Wide Association Study (GWAS) mainly influence the susceptibility of complex diseases, but they still could not comprehensively explain the relationships between mutations and diseases. Interactions between SNPs are considered so important for deeply understanding of those relationships that several strategies have been proposed to explore such interactions. However, part of those methods perform poorly when marginal effects of disease loci are weak or absent, others may lack of considering high-order SNPs interactions, few methods have achieved the requirements in both performance and accuracy. Considering the above reasons, not only low-order, but also high-order SNP interactions as well as main-effect SNPs, should be taken into account in detection methods under an acceptable computational complexity. In this paper, a new pairwise (or low-order) interaction detection method IG (Interaction Gain) is introduced, in which disease models are not required and parallel computing is utilized. Furthermore, high-order SNP interactions were proposed to be detected by finding closely connected function modules of the network constructed from IG detection results. Tested by a wide range of simulated datasets and four WTCCC real datasets, the proposed methods accurately detected both low-order and high-order SNP interactions as well as disease-associated main-effect SNPS and it surpasses all competitors in performances. The research will advance complex diseases research by providing more reliable SNP interactions.

SUBMITTER: Su L

PROVIDER: S-EPMC4357495 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Research on single nucleotide polymorphisms interaction detection from network perspective.

Su Lingtao L Liu Guixia G Wang Han H Tian Yuan Y Zhou Zhihui Z Han Liang L Yan Lun L

PloS one 20150312 3

Single Nucleotide Polymorphisms (SNPs) found in Genome-Wide Association Study (GWAS) mainly influence the susceptibility of complex diseases, but they still could not comprehensively explain the relationships between mutations and diseases. Interactions between SNPs are considered so important for deeply understanding of those relationships that several strategies have been proposed to explore such interactions. However, part of those methods perform poorly when marginal effects of disease loci ...[more]

PMID: 25763929

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Project description:Single-nucleotide polymorphisms (SNPs) provide an abundant source of DNA polymorphisms in a number of eukaryotic species. Information on the frequency, nature, and distribution of SNPs in plant genomes is limited. Thus, our objectives were (1) to determine SNP frequency in coding and noncoding soybean (Glycine max L. Merr.) DNA sequence amplified from genomic DNA using PCR primers designed to complete genes, cDNAs, and random genomic sequence; (2) to characterize haplotype variation in these sequences; and (3) to provide initial estimates of linkage disequilibrium (LD) in soybean. Approximately 28.7 kbp of coding sequence, 37.9 kbp of noncoding perigenic DNA, and 9.7 kbp of random noncoding genomic DNA were sequenced in each of 25 diverse soybean genotypes. Over the >76 kbp, mean nucleotide diversity expressed as Watterson's theta was 0.00097. Nucleotide diversity was 0.00053 and 0.00111 in coding and in noncoding perigenic DNA, respectively, lower than estimates in the autogamous model species Arabidopsis thaliana. Haplotype analysis of SNP-containing fragments revealed a deficiency of haplotypes vs. the number that would be anticipated at linkage equilibrium. In 49 fragments with three or more SNPs, five haplotypes were present in one fragment while four or less were present in the remaining 48, thereby supporting the suggestion of relatively limited genetic variation in cultivated soybean. Squared allele-frequency correlations (r(2)) among haplotypes at 54 loci with two or more SNPs indicated low genome-wide LD. The low level of LD and the limited haplotype diversity suggested that the genome of any given soybean accession is a mosaic of three or four haplotypes. To facilitate SNP discovery and the development of a transcript map, subsets of four to six diverse genotypes, whose sequence analysis would permit the discovery of at least 75% of all SNPs present in the 25 genotypes as well as 90% of the common (frequency >0.10) SNPs, were identified.

Project description:BACKGROUND: Screening tests for Trisomy 21 (T21), also known as Down syndrome, are routinely performed for the majority of pregnant women. However, current tests rely on either evaluating non-specific markers, which lead to false negative and false positive results, or on invasive tests, which while highly accurate, are expensive and carry a risk of fetal loss. We outline a novel, rapid, highly sensitive, and targeted approach to non-invasively detect fetal T21 using maternal plasma DNA. METHODS AND FINDINGS: Highly heterozygous tandem Single Nucleotide Polymorphism (SNP) sequences on chromosome 21 were analyzed using High-Fidelity PCR and Cycling Temperature Capillary Electrophoresis (CTCE). This approach was used to blindly analyze plasma DNA obtained from peripheral blood from 40 high risk pregnant women, in adherence to a Medical College of Wisconsin Institutional Review Board approved protocol. Tandem SNP sequences were informative when the mother was heterozygous and a third paternal haplotype was present, permitting a quantitative comparison between the maternally inherited haplotype and the paternally inherited haplotype to infer fetal chromosomal dosage by calculating a Haplotype Ratio (HR). 27 subjects were assessable; 13 subjects were not informative due to either low DNA yield or were not informative at the tandem SNP sequences examined. All results were confirmed by a procedure (amniocentesis/CVS) or at postnatal follow-up. Twenty subjects were identified as carrying a disomy 21 fetus (with two copies of chromosome 21) and seven subjects were identified as carrying a T21 fetus. The sensitivity and the specificity of the assay was 100% when HR values lying between 3/5 and 5/3 were used as a threshold for normal subjects. CONCLUSIONS: In summary, a targeted approach, based on calculation of Haplotype Ratios from tandem SNP sequences combined with a sensitive and quantitative DNA measurement technology can be used to accurately detect fetal T21 in maternal plasma when sufficient fetal DNA is present in maternal plasma.

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Research on single nucleotide polymorphisms interaction detection from network perspective.

Publications

Research on single nucleotide polymorphisms interaction detection from network perspective.

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