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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.9K
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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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.
GWAS does not require the identification of the target gene involved in...
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Single Nucleotide Polymorphisms-SNPs01:05

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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Related Experiment Video

Updated: Sep 15, 2025

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
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Chromosomal quality control in hPSCs: A practical guide to SNP array analysis with GenomeStudio.

Josephine Haake1, Laura Steenpass1,2

  • 1Department of Human and Animal Cell Lines, Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany.

Frontiers in Cell and Developmental Biology
|July 16, 2025
PubMed
Summary

Ensuring chromosomal stability in human pluripotent stem cells (hPSCs) is crucial for reliable research. This guide simplifies SNP array analysis for detecting aberrations, improving quality control workflows for genomic stability.

Keywords:
B-allele frequencyGenomeStudioSNP array analysischromosomal stability in hPSCslog R ratioquality control of hPSCs

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Last Updated: Sep 15, 2025

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DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
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DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

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Area of Science:

  • Stem cell biology
  • Genomics
  • Quality control

Background:

  • Human pluripotent stem cells (hPSCs) are vital for research and disease modeling.
  • Chromosomal instability in hPSCs can arise during culture and compromise experimental validity.
  • Traditional G-banding has limitations in resolution, necessitating advanced genomic analysis methods.

Purpose of the Study:

  • To provide a user-friendly guide for detecting chromosomal aberrations in hPSCs using SNP array analysis.
  • To streamline quality control (QC) workflows for researchers with limited bioinformatics experience.
  • To highlight critical QC metrics and values for assessing hPSC genomic stability.

Main Methods:

  • Utilized Illumina's GenomeStudio software for SNP array analysis.
  • Developed a step-by-step protocol for identifying chromosomal aberrations.
  • Applied the protocol to analyze 32 hPSC samples for quality control.

Main Results:

  • Identified chromosomal aberrations in 9 out of 32 hPSC samples.
  • Confirmed the frequent occurrence of gain of 20q11.21, a known hPSC anomaly.
  • Demonstrated the practical utility of SNP array analysis in routine hPSC QC.

Conclusions:

  • SNP array analysis, guided by this protocol, enhances hPSC quality control.
  • Standardized QC processes ensure the genomic integrity of hPSCs for research and clinical use.
  • This guide promotes broader adoption of robust methods for monitoring chromosomal stability in hPSCs.