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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

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,...
Sanger Sequencing01:57

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Although all next-generation methods use different technologies, they all share a set of standard features.
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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Sequencing genes in silico using single nucleotide polymorphisms.

Xinyi Cindy Zhang1, Bo Zhang, Shuying Sue Li

  • 1Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.

BMC Genetics
|February 1, 2012
PubMed
Summary
This summary is machine-generated.

An in silico gene sequencing method predicts phased sequences using SNPs, enabling cost-effective disease gene characterization. This approach accelerates functional studies by inferring diploid sequences from large datasets.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Genetic Association Studies

Background:

  • High-throughput sequencing enables large-scale genetic data generation, exemplified by the 1000 Genomes Project.
  • Interpreting disease associations with single nucleotide polymorphisms (SNPs) is crucial but hindered by costly direct sequencing.
  • Existing methods for large-scale genetic analysis are time- and cost-prohibitive.

Purpose of the Study:

  • To develop a cost- and time-effective method for predicting phased sequences of intragenic regions.
  • To accelerate the translation of genetic discoveries into functional studies.
  • To facilitate the interpretation of disease-associated SNPs and regions.

Main Methods:

  • Developed an in silico gene sequencing (ISS) method to predict phased sequences using SNPs.
  • Inferred diploid sequences at functional loci using 1000 Genomes Project data and HapMap SNP data.
  • Built prediction models utilizing flanking SNPs and created a database for 611 genes.

Main Results:

  • Achieved an average sequence prediction accuracy of 96.26% across 611 genes.
  • Demonstrated application of the predictive model for KCNJ11 in a Type 2 diabetes cohort.
  • Showcased how predicted phased sequences aid in interpreting GWAS SNP genotype data and identifying functional mechanisms.

Conclusions:

  • The ISS method offers a time- and cost-effective alternative to routine sequencing for characterizing disease-associated SNPs.
  • Facilitates prioritization of candidate genes for in-depth functional and mechanistic investigations.
  • Enhances the utility of large-scale genetic datasets for disease research.