Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.9K
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%...
18.9K
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

60
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...
60
Mutations01:35

Mutations

44.9K
Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
44.9K
Mutations01:39

Mutations

95.1K
Overview
95.1K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

8.3K
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...
8.3K
Mismatch Repair01:20

Mismatch Repair

6.8K
Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
6.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

spammR: an R package designed for analysis and integration of spatial multi-omic measurements.

Bioinformatics advances·2026
Same author

Whole metagenome sequencing: not deep enough for complete microbial function recovery.

Microbiome·2026
Same author

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same author

Advances in Protein Function Prediction from the Fifth CAFA Challenge.

bioRxiv : the preprint server for biology·2026
Same author

Quantifying uncertainty in protein representations across models and tasks.

Nature methods·2026
Same author

Session Introduction: Biological molecular function: methods and benchmarks for finding function in biological dark matter.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Integrated multi-assessment and structural performance index framework for stacking-sequence optimisation of natural fibre reinforced laminates.

Scientific reports·2026
Same journal

SuperiorGAT: graph attention networks for sparse LiDAR point cloud reconstruction in autonomous systems.

Scientific reports·2026
Same journal

The effect of stretching the pectoralis major, sternocleidomastoid, and iliopsoas muscles on 800 m swimming performance in master swimmers.

Scientific reports·2026
Same journal

ISNR-PQC: isometry noise resilience post quantum cryptography primitive.

Scientific reports·2026
Same journal

Identification of high-yielding and stable genotypes of barley in the cold climate of Iran using AMMI and GGE biplot models.

Scientific reports·2026
Same journal

Bayesian negative binomial modelling of spatial and temporal patterns of road traffic deaths in Ghana.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Mar 2, 2026

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.4K

Common sequence variants affect molecular function more than rare variants?

Yannick Mahlich1,2,3,4, Jonas Reeb5,6, Maximilian Hecht5

  • 1Computational Biology & Bioinformatics - i12, Informatics, Technical University of Munich (TUM), Boltzmannstrasse 3, 85748, Garching/Munich, Germany. ymahlich@bromberglab.org.

Scientific Reports
|May 11, 2017
PubMed
Summary
This summary is machine-generated.

Single amino acid variants (SAVs) impact protein function. Computational methods predict SAV effects, revealing more common variants affect function within species than between species, challenging existing predictions.

More Related Videos

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

11.5K
In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

21.4K

Related Experiment Videos

Last Updated: Mar 2, 2026

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.4K
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

11.5K
In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

21.4K

Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • Evolutionary Biology

Background:

  • Individuals differ by thousands of single amino acid variants (SAVs), potentially impacting molecular function.
  • Experimental validation of SAV functional impact is not comprehensive; computational prediction methods are essential.
  • Existing prediction tools show agreement for rare SAVs but diverge significantly for common SAVs.

Purpose of the Study:

  • To computationally predict the functional impacts of single amino acid variants (SAVs) within humans and between species.
  • To compare the performance and predictions of different state-of-the-art SAV prediction tools.
  • To investigate the evolutionary patterns of SAV functional impact within and across species.

Main Methods:

  • Utilized four prediction methods: CADD, PolyPhen-2, SIFT, and SNAP2.
  • Analyzed SAVs within the human population using large datasets (ExAC, 60,706 individuals).
  • Compared predicted functional impacts of SAVs within humans versus SAVs between human and other species.

Main Results:

  • Four prediction methods showed agreement on rare SAVs but substantial differences for common SAVs.
  • SNAP2 predicted a higher functional impact for common SAVs compared to rare SAVs, differing from other methods.
  • A significantly higher fraction of SAVs were predicted to have functional effects within humans than between species, with this difference increasing for more distant species.

Conclusions:

  • SNAP2's unique development focus may provide more accurate predictions for common SAVs.
  • SAVs conserved across species may be functionally constrained, while intra-species variants drive significant adaptive or deleterious changes.
  • The study highlights distinct evolutionary pressures on variants within and between species, impacting protein function.