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Next-generation Sequencing

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 SNPs

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%...

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

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...

RNA-seq

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...

Sanger Sequencing

Sanger Sequencing

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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Updated: May 16, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

SNP Discovery through Next-Generation Sequencing and Its Applications.

Santosh Kumar¹, Travis W Banks, Sylvie Cloutier

¹Department of Plant Science, University of Manitoba, Winnipeg, MB, Canada R3T 2N2.

International Journal of Plant Genomics

|December 11, 2012

Summary

Next-generation sequencing and bioinformatics enable large-scale single nucleotide polymorphism (SNP) discovery in plants. This review connects sequencing, bioinformatics, and SNP applications for genetic studies.

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Published on: April 4, 2018

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

Plant genomics
Bioinformatics
Molecular genetics

Background:

Decreasing costs and advancements in next-generation sequencing (NGS) and bioinformatics have enabled large-scale discovery of single nucleotide polymorphisms (SNPs).
SNPs are valuable genetic markers, especially in sequenced plant genomes, due to their abundance and genome-wide distribution.
Existing reviews cover NGS, bioinformatics challenges, and SNP applications separately, but a comprehensive overview linking these areas is lacking.

Purpose of the Study:

To provide a comprehensive review connecting next-generation sequencing, bioinformatics, and SNP discovery and applications in plant genetics.
To highlight key considerations for SNP discovery, including platform selection, bioinformatics pipelines, and filtering criteria.
To discuss the application of SNPs in genetic studies, particularly in non-model crops.

Main Methods:

Review of current literature on next-generation sequencing technologies and bioinformatics tools for SNP discovery.
Analysis of strategies for SNP filtering and selection.
Discussion of the implementation and application of SNPs in plant genetic research, including non-model species.

Main Results:

Next-generation sequencing and open-source bioinformatics software have accelerated cost-effective SNP discovery.
Effective SNP filtering and pipeline selection are crucial for reliable genetic analyses.
SNPs are increasingly utilized in diverse genetic studies across various plant species, including non-model crops.

Conclusions:

The integration of NGS and bioinformatics has revolutionized SNP discovery and its application in plant genetics.
Careful consideration of sequencing platforms, bioinformatics pipelines, and filtering criteria is essential for successful SNP implementation.
Continued development of accessible bioinformatics tools will further enhance SNP-based genetic research in plants.