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Single Nucleotide Polymorphisms-SNPs

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

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

Rebecca J Swett¹, Angela Elias, Jeffrey A Miller

¹Department of Chemistry, Wayne State University, 5101 Cass Avenue, Detroit, MI 48202, USA.

|July 9, 2013

Summary

This summary is machine-generated.

This study introduces HyDn-SNP-S, a novel method for analyzing large-scale genotyping data to identify single nucleotide polymorphisms (SNPs) linked to phenotypes. It successfully identified novel SNPs associated with breast and prostate cancer risk.

Keywords:

Biomarkers Cancer DNA polymerases Molecular dynamics SNP search

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Complete-genome genotyping provides vast data for bioinformaticians.
Current SNP searches are often hypothesis-free and study-specific.
Identifying phenotype-predictive SNPs requires efficient data analysis methods.

Purpose of the Study:

To develop a method for analyzing large SNP datasets to link genetic variations to phenotypes.
To enable hypothesis-driven searches within combined genotyping studies.
To facilitate targeted correlation of genetic locations with observed phenotypes.

Main Methods:

Designed HyDn-SNP-S to sort and trace large SNP lists (gigabytes) to protein structure.
Integrated multiple genotyping studies for comprehensive analysis.
Applied logistic regression and haplotype analysis to cancer phenotype data from dbGaP.

Main Results:

Identified approximately 80 previously overlooked, statistically significant SNPs.
Derived haplotypes link POLL to breast cancer (3.01-fold increase) and POLG to prostate cancer (9.6-fold increase).
Molecular dynamics simulations provided atomic-level insights into SNP functional impact.

Conclusions:

HyDn-SNP-S enables efficient, targeted analysis of large-scale genotyping data.
The method identified novel genetic markers for breast and prostate cancer.
The approach offers a powerful tool for discovering genotype-phenotype correlations across various biological systems.