Dataset Information

Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S).

ABSTRACT: The advent of complete-genome genotyping across phenotype cohorts has provided a rich source of information for bioinformaticians. However the search for SNPs from this data is generally performed on a study-by-study case without any specific hypothesis of the location for SNPs that are predictive for the phenotype. We have designed a method whereby very large SNP lists (several gigabytes in size), combining several genotyping studies at once, can be sorted and traced back to their ultimate consequence in protein structure. Given a working hypothesis, researchers are able to easily search whole genome genotyping data for SNPs that link genetic locations to phenotypes. This allows a targeted search for correlations between phenotypes and potentially relevant systems, rather than utilizing statistical methods only. HyDn-SNP-S returns results that are less data dense, allowing more thorough analysis, including haplotype analysis. We have applied our method to correlate DNA polymerases to cancer phenotypes using four of the available cancer databases in dbGaP. Logistic regression and derived haplotype analysis indicates that ~80SNPs, previously overlooked, are statistically significant. Derived haplotypes from this work link POLL to breast cancer and POLG to prostate cancer with an increase in incidence of 3.01- and 9.6-fold, respectively. Molecular dynamics simulations on wild-type and one of the SNP mutants from the haplotype of POLL provide insights at the atomic level on the functional impact of this cancer related SNP. Furthermore, HyDn-SNP-S has been designed to allow application to any system. The program is available upon request from the authors.

SUBMITTER: Swett RJ

PROVIDER: S-EPMC3916134 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S).

Swett Rebecca J RJ Elias Angela A Miller Jeffrey A JA Dyson Gregory E GE Andrés Cisneros G G

DNA repair 20130705 9

The advent of complete-genome genotyping across phenotype cohorts has provided a rich source of information for bioinformaticians. However the search for SNPs from this data is generally performed on a study-by-study case without any specific hypothesis of the location for SNPs that are predictive for the phenotype. We have designed a method whereby very large SNP lists (several gigabytes in size), combining several genotyping studies at once, can be sorted and traced back to their ultimate cons ...[more]

PMID: 23830898

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Project description:Dear Editor, The recent article by Mohammadzadeh et al.[1] on the latest issue of this Journal showed that the T allele +276G/T SNP of ADIPOQ gene is more associated with the increasing risk of coronary artery disease (CAD) in subjects with type 2 diabetes. Adipocytes were described in myocardial tissue of CAD patients and their role recently discussed[2,3]. Susceptibility to CAD by polymorphism in the Q gene of adiponectin has been reported for 3'-UTR, which harbours some genetic loci associated with metabolic risks and atherosclerosis[4]. Actually, previous studies have shown that the haplotype SNP +276G>T was associated with a decreased risk of CAD, after adjustment for potential confounding factors, therefore some controversial opinion still exists[5]. This evidence should be associated with the role exerted by adipocytes and adiponectin in heart physiology. In particular, in hypertensive disorder complicating pregnancy (HDCP), by investigating the population frequency of alleles, genotypes, and haplotypes of two single nucleotide polymorphisms (SNPs), namely +45T>G (rs2241766) and +276G>T (rs1501299), some authors found that the SNP +276 TT genotype was significantly associated with protection against HDCP, when compared to the pooled G genotypes[6]. Moreover, the same +276G/T SNP haplotype was strongly associated with biliary atresia, an intractable neonatal inflammatory and obliterative cholangiopathy, leading to progressive fibrosis and cirrhosis[7]. CAD is closely related to adiponectin biology. The same isoforms of adiponectin seem to be not associated to CAD severity but to glucose metabolism and its impairment[8]. In the paper by Mohammadzadeh et al.[1], T allele in +276G/T SNP haplotype is highly associated with CAD in subjects with type 2 diabetes, but this linkage should be reappraised if related much more to diabetes rather than CAD. Association of T allele in the indicated SNP with CAD may be an indirect consequence of type 2 diabetes, as reported by others[9] or a direct marker for CAD affected patients[10]. The paper by Mohammadzadeh et al.[1] assesses data coming elsewhere from literature but raises important concerns about the suitability of ADIPOQ SNPs in diagnosing susceptibility to CAD and the relationship with plasma adiponectin level. In normal, non diabetic, normoglycemic subject, this relationship does not seem to work. Therefore the question is how much predictive this SNP haplotype may be to foresee metabolic syndrome and CAD onset risk in young health subjects? Maybe, the role of adiponectin in cardiovascular physiology depends on its ability to target adiponectin receptors and to negatively regulate obesity. Some authors reported in healthy volunteers an absence of correlation between circulating adiponectin levels and biochemical markers, particularly lipoproteins and suggested that SNP +276G>T was related to an independent effect on adiponectin levels and on lipoprotein metabolism[11]. On the contrary, adiponectin genetic variants and SNP +276G>T was associated with increasing susceptibility of type 2 diabetes and plasma glucose impairment[12]. The interesting study by Mohammadzadeh et al.[1] suggests that SNP of ADIPOQ +276G>T should be related to susceptibility to glucose metabolism, while indirectly to lipid metabolism and fat-related cardiovascular damage.

Project description:BackgroundGenome-wide association studies (GWAS) identify disease-associations for single-nucleotide-polymorphisms (SNPs) from scattered genomic-locations. However, SNPs frequently reside on several different SNP-haplotypes, only some of which may be disease-associated. This circumstance lowers the observed odds-ratio for disease-association.Methodology/principal findingsHere we develop a method to identify the two SNP-haplotypes, which combine to produce each person's SNP-genotype over specified chromosomal segments. Two multiple sclerosis (MS)-associated genetic regions were modeled; DRB1 (a Class II molecule of the major histocompatibility complex) and MMEL1 (an endopeptidase that degrades both neuropeptides and β-amyloid). For each locus, we considered sets of eleven adjacent SNPs, surrounding the putative disease-associated gene and spanning ∼200 kb of DNA. The SNP-information was converted into an ordered-set of eleven-numbers (subject-vectors) based on whether a person had zero, one, or two copies of particular SNP-variant at each sequential SNP-location. SNP-strings were defined as those ordered-combinations of eleven-numbers (0 or 1), representing a haplotype, two of which combined to form the observed subject-vector. Subject-vectors were resolved using probabilistic methods. In both regions, only a small number of SNP-strings were present. We compared our method to the SHAPEIT-2 phasing-algorithm. When the SNP-information spanning 200 kb was used, SHAPEIT-2 was inaccurate. When the SHAPEIT-2 window was increased to 2,000 kb, the concordance between the two methods, in both of these eleven-SNP regions, was over 99%, suggesting that, in these regions, both methods were quite accurate. Nevertheless, correspondence was not uniformly high over the entire DNA-span but, rather, was characterized by alternating peaks and valleys of concordance. Moreover, in the valleys of poor-correspondence, SHAPEIT-2 was also inconsistent with itself, suggesting that the SNP-string method is more accurate across the entire region.Conclusions/significanceAccurate haplotype identification will enhance the detection of genetic-associations. The SNP-string method provides a simple means to accomplish this and can be extended to cover larger genomic regions, thereby improving a GWAS's power, even for those published previously.

Project description:Summary In this work, we developed a simple and robust assay to rapidly detect SNPs in nucleic acid samples. Our approach combines loop-mediated isothermal amplification (LAMP)-based target amplification with fluorescent probes to detect SNPs with high specificity. A competitive “sink” strand preferentially binds to non-SNP amplicons and shifts the free energy landscape to favor specific activation by SNP products. We demonstrated the broad utility and reliability of our SNP-LAMP method by detecting three distinct SNPs across the human genome. We also designed an assay to rapidly detect highly transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants from crude biological samples. This work demonstrates that competitive SNP-LAMP is a powerful and universal method that could be applied in point-of-care settings to detect any target SNP with high specificity and sensitivity. We additionally developed a publicly available web application for researchers to design SNP-LAMP probes for any target sequence of interest. Graphical abstract Highlights • A simple and rapid assay to detect specific SNPs in complex nucleic acid samples• Approach leverages competitive probes to specifically detect SNP over non-SNP sequences• Demonstrated utility across diverse targets and sample types• Web application for researchers to design SNP-LAMP probes for any target of interest Motivation Single-nucleotide polymorphisms (SNPs) are the most common source of genetic variation between individuals and have implications in human disease, pathogen drug resistance, and agriculture. SNPs are often detected using DNA sequencing or PCR, both of which can be difficult to deploy for on-site testing or in low-resource settings. There is a need for new SNP detection methods that can be performed rapidly without advanced laboratory equipment or a cold supply chain. Detecting single-nucleotide polymorphisms (SNPs) is important for understanding human disease, the emergence of pathogen variants, and the application of genetic agricultural breeding programs. Hyman et al. develop a simple and rapid assay to detect SNPs in complex nucleic acid samples. A web-based tool allows researchers to design custom SNP probes.

Dataset Information

Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S).

Publications

Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S).

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