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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,...
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.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
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%...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

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Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
12:33

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Published on: July 28, 2017

Single nucleotide polymorphism discovery from wheat next-generation sequence data.

Kaitao Lai1, Chris Duran, Paul J Berkman

  • 1School of Agriculture and Food Science, University of Queensland, Brisbane, QLD, Australia.

Plant Biotechnology Journal
|July 4, 2012
PubMed
Summary
This summary is machine-generated.

Researchers identified 38,928 single nucleotide polymorphisms (SNPs) in wheat using next-generation sequencing and a modified autoSNPdb tool. This advance facilitates genetic mapping and marker-assisted breeding in complex polyploid genomes.

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Area of Science:

  • Genomics
  • Plant Science
  • Molecular Biology

Background:

  • Single nucleotide polymorphisms (SNPs) are crucial genetic markers for high-resolution genetic mapping, association studies, and marker-assisted breeding.
  • Large, polyploid genomes like wheat pose challenges for SNP discovery due to multiple homoeologs per gene.
  • Previous SNP discovery tools, like autoSNPdb, were limited by data volume for complex genomes such as wheat.

Purpose of the Study:

  • To develop and apply a modified autoSNPdb method for efficient SNP discovery in the complex wheat genome.
  • To leverage next-generation sequencing (NGS) technology for large-scale SNP identification in wheat.

Main Methods:

  • Generated wheat transcriptome sequence data using 454 sequencing technology.
  • Applied a modified autoSNPdb method integrating SNP and gene annotation information with a graphical viewer.
  • Assembled 4,694,141 sequence reads from three bread wheat varieties.

Main Results:

  • Identified a total of 38,928 candidate SNPs across three bread wheat varieties.
  • Each identified SNP is located within a gene assembly with complete annotation.
  • The method enables the selection of polymorphisms within genes of interest.

Conclusions:

  • The modified autoSNPdb method, combined with NGS data, is effective for SNP discovery in the challenging wheat genome.
  • This approach provides a valuable resource for high-resolution genetic mapping and marker-assisted breeding in wheat.
  • The annotated SNPs facilitate targeted selection of polymorphisms for crop improvement.