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Single Nucleotide Polymorphisms-SNPs

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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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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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Related Experiment Video

Updated: Mar 17, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Characterizing polymorphic inversions in human genomes by single-cell sequencing.

Ashley D Sanders¹, Mark Hills¹, David Porubský²

¹Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, British Columbia, V5Z 1L3, Canada.

Genome Research

|July 31, 2016

Summary

This summary is machine-generated.

This study introduces a new method combining Strand-seq and software to map genomic rearrangements in single cells. This advances the study of genetic variations influencing health and disease.

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Published on: October 25, 2018

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Genomic variations influence phenotypes and disease.
Single-cell studies are crucial for understanding cellular heterogeneity.
Accurate mapping of structural rearrangements has been a challenge.

Purpose of the Study:

To develop a high-resolution method for discovering and mapping genomic rearrangements in single cells.
To analyze the distribution and frequency of inversions in heterogeneous cell populations.
To create a comprehensive reference of structural variations in the human genome.

Main Methods:

Coupling single-cell sequencing of DNA template strands (Strand-seq) with custom analysis software.
High-resolution discovery, mapping, and genotyping of genomic rearrangements.
Characterizing inversion profiles in individuals and building a global reference.

Main Results:

Rapid discovery and mapping of genomic rearrangements at high resolution.
Exploration of inversion distribution and frequency in cell populations.
Identification of polymorphic domains and rare alleles.
Mapping of inversion complements in two individuals and creation of a human genome structural rearrangement reference.

Conclusions:

The developed framework enables robust study of structural variation and genomic heterogeneity in single-cell samples.
This approach supports population studies and biomarker discovery through analysis of individual and tissue-specific variations.
Provides a powerful new tool for understanding the role of rare cellular subpopulations in disease.