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Related Concept Videos

Next-generation Sequencing03:00

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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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Single Nucleotide Polymorphisms-SNPs01:05

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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,...
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Comparing Copy Number Variations and SNPs02:26

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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.
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Genome-wide Association Studies-GWAS01:11

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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.
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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...
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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Infinium Assay for Large-scale SNP Genotyping Applications
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Genome Wide Sampling Sequencing for SNP Genotyping: Methods, Challenges and Future Development.

Zhihua Jiang1, Hongyang Wang2, Jennifer J Michal1

  • 11. Department of Animal Sciences, Washington State University, Pullman, WA 99164-7620, USA;

International Journal of Biological Sciences
|January 2, 2016
PubMed
Summary
This summary is machine-generated.

Genome-wide sampling sequencing (GWSS) methods enable cost-effective genetic variant discovery. Optimizing library preparation can improve data consistency and accuracy for genomics research.

Keywords:
dominant and co-dominant markers, genome wide association study, human, animals and plantsrestriction site associated DNA sequencing, genotyping by sequencing, reduced representation library sequencing, complexity reduction of polymorphism sequencing

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Single nucleotide polymorphisms (SNPs) are crucial for various genomics fields.
  • Next-generation sequencing (NGS) aims for comprehensive variant discovery.
  • Genome-wide sampling sequencing (GWSS) offers a cost-effective alternative to whole-genome sequencing.

Purpose of the Study:

  • To review library preparation methods for GWSS.
  • To identify limitations in current GWSS approaches.
  • To propose strategies for enhancing GWSS efficiency and data quality.

Main Methods:

  • Review of library preparation steps, including adapter ligation and primer design.
  • Analysis of existing GWSS methods and their associated challenges.
  • Development of recommendations for improved library construction.

Main Results:

  • Current GWSS methods suffer from inconsistencies in read counts and missing data.
  • Inconsistent data impacts the number of identified sites and read depth per site.
  • Proposed optimizations focus on unique target site generation and even coverage.

Conclusions:

  • Optimized GWSS library preparation is essential for accurate and comprehensive genetic variant analysis.
  • Improvements in library construction can enhance genotype calling accuracy and marker density.
  • Even coverage across target sites improves the reliability of genomic data from reduced representation sequencing.