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Related Concept Videos

Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
Comparing Copy Number Variations and SNPs02:26

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%...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

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...
Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles, which...
Single Nucleotide Polymorphisms-SNPs01:05

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,...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...

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Related Experiment Video

Updated: May 8, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

Neutral and weakly nonneutral sequence variants may define individuality.

Yana Bromberg1, Peter C Kahn, Burkhard Rost

  • 1Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ 08901, USA. yanab@rci.rutgers.edu

Proceedings of the National Academy of Sciences of the United States of America
|August 14, 2013
PubMed
Summary
This summary is machine-generated.

Healthy genomes contain numerous variants impacting protein function. Computational tools reveal these genetic variations may explain non-disease traits, unlike severe mutations causing disease.

Keywords:
coding SNVevolutiongenomic variant burdennsSNPvariome analysis

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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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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)

Published on: August 21, 2016

Area of Science:

  • Genomics
  • Computational Biology
  • Human Genetics

Background:

  • Genome-variation data analysis reveals expected disease-causing variants and surprising functional variants in healthy individuals.
  • Complete experimental analysis of all human genome variants is infeasible, necessitating computational approaches.

Purpose of the Study:

  • To investigate the role of genetic variants in healthy individuals using computational prediction methods.
  • To explore the genomic basis of non-disease phenotypes.

Main Methods:

  • Large-scale computational analyses of genome-variation data.
  • Utilizing prediction methods like PolyPhen, SNAP, and SIFT to assess variant effects on protein function.

Main Results:

  • Computational methods predict many variants in healthy individuals have subtle effects on protein function.
  • These variants are often neutral or weakly disruptive, falling within the normal physiological range.
  • Diseases are linked to few, severely disruptive variants, while non-disease phenotypes may arise from cumulative effects of many weakly disruptive variants.

Conclusions:

  • Computational prediction tools offer valuable insights into the functional impact of genetic variants.
  • Non-disease phenotypes may result from the combined effects of numerous weakly disruptive genetic variants.
  • Understanding subtle genetic variations is crucial for comprehending the full spectrum of human phenotypic variation.