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Related Concept Videos

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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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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Single Nucleotide Polymorphisms-SNPs01:05

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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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Principles of Pharmacogenetics: Types of Genetic Variants01:27

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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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lncRNA - Long Non-coding RNAs02:39

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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Updated: May 5, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Functional interpretation of non-coding sequence variation: concepts and challenges.

Dirk S Paul1, Nicole Soranzo, Stephan Beck

  • 1UCL Cancer Institute, University College London, London, United Kingdom.

Bioessays : News and Reviews in Molecular, Cellular and Developmental Biology
|December 7, 2013
PubMed
Summary
This summary is machine-generated.

Interpreting non-coding genetic signals is key to understanding complex diseases. This study presents strategies using genome annotation and CRISPR/Cas9 to uncover the functional mechanisms of these genetic variants.

Keywords:
GWASchromatincomplex traitsgene regulationgenome editingregulatory variants

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Area of Science:

  • Genomics
  • Molecular Biology
  • Genetics

Background:

  • Genome-wide association studies (GWAS) identify genetic variants linked to complex traits and diseases like cancer, diabetes, and Alzheimer's.
  • A significant portion of these identified variants reside in non-protein coding regions, posing challenges for functional interpretation.
  • Understanding the molecular mechanisms of non-coding variants is crucial for translating genetic discoveries into clinical applications.

Purpose of the Study:

  • To outline systematic strategies for interpreting non-coding genetic signals.
  • To highlight methods for both global analysis of association intervals and in-depth molecular investigation of individual intervals.
  • To emphasize the role of advanced techniques, including genome editing, in validating regulatory variants.

Main Methods:

  • Utilizing comprehensive genome annotation datasets across diverse cellular systems.
  • Employing strategies for the global analysis of multiple genetic association intervals.
  • Conducting in-depth molecular investigations of individual intervals.
  • Applying experimental validation techniques, including CRISPR/Cas9 genome editing, for candidate regulatory variants.

Main Results:

  • The study provides a framework for the systematic interpretation of non-coding genetic signals.
  • It details approaches for analyzing multiple association regions and investigating specific intervals.
  • Experimental validation methods, particularly CRISPR/Cas9, are highlighted for identifying causal regulatory variants.
  • The presented approaches are applicable to common, low-frequency, and rare variants.

Conclusions:

  • Translating genetic signals from non-coding regions into biological mechanisms is essential for advancing prognostic, diagnostic, and therapeutic strategies.
  • Systematic interpretation of non-coding variants using genome annotation and advanced molecular techniques is feasible and necessary.
  • Genome editing technologies offer powerful tools for validating the functional impact of genetic variants in complex diseases.