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Related Concept Videos

Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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.
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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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: Mar 8, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

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A practical guide to filtering and prioritizing genetic variants.

Mahjoubeh Jalali Sefid Dashti1, Junaid Gamieldien1

  • 1South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa.

Biotechniques
|January 26, 2017
PubMed
Summary

This study provides guidelines and tools for biologists and clinicians to identify and prioritize disease-associated genetic variants from next-generation sequencing data. It simplifies complex variant analysis for researchers without extensive bioinformatics expertise.

Keywords:
functional variantsvariant prioritizationwhole-exome sequencingwhole-genome sequencing

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

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates vast amounts of data, posing challenges for identifying disease-causing genetic variants.
  • Existing computational workflows improve variant calling but require expert bioinformaticians for filtering and prioritization.
  • Biologists and clinicians increasingly need to perform variant prioritization themselves, requiring accessible tools and methods.

Purpose of the Study:

  • To provide biologists and clinicians with guidelines, tools, and online resources for identifying functional variants from whole-genome and whole-exome sequencing data.
  • To enable researchers to prioritize genetic variants associated with specific phenotypes of interest.
  • To leverage large-scale human genetic variation data, such as from the Exome Aggregation Consortium (ExAC), for variant interpretation.

Main Methods:

  • Development of a set of guidelines for variant identification and prioritization.
  • Compilation of relevant computational tools and online resources.
  • Integration of insights from large-scale human genetic variation datasets (e.g., ExAC).

Main Results:

  • A practical framework for identifying and prioritizing functional variants from NGS data.
  • Accessible resources empowering biologists and clinicians to conduct their own variant analysis.
  • Improved ability to link genetic variants to specific disease phenotypes.

Conclusions:

  • Biologists and clinicians can effectively identify and prioritize disease-associated variants using the provided guidelines and resources.
  • The approach facilitates a deeper understanding of genetic contributions to disease by enabling direct researcher involvement in variant analysis.
  • Leveraging large datasets enhances the accuracy and relevance of variant prioritization for biomedical research and diagnostics.