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

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

8.4K
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...
8.4K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

3.8K
3.8K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

7.2K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
7.2K
Speciation Rates01:07

Speciation Rates

23.4K
Overview
23.4K
Microbial Phylogeny01:28

Microbial Phylogeny

22
Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
22
Phylogeny01:23

Phylogeny

64.4K
Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.
64.4K

You might also read

Related Articles

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

Sort by
Same author

Benchmarking the Mantel test and derived methods for testing association between distance matrices.

Molecular ecology resources·2023
Same author

CastNet: a systems-level sequence evolution simulator.

BMC bioinformatics·2023
Same author

Whole genome assembly of the armored loricariid catfish Ancistrus triradiatus highlights herbivory signatures.

Molecular genetics and genomics : MGG·2022
Same author

Distribution extension of Hypostomus uruguayensis (Siluriformes: Loricariidae) in Argentina and first record for Bolivia. Molecular, morphology and biogeography data.

Zootaxa·2021
Same author

Processes that drive the population structuring of <i>Jenynsia lineata</i> (Cyprinidontiformes, Anablepidae) in the La Plata Basin.

Ecology and evolution·2021
Same author

Air temperature influences early Covid-19 outbreak as indicated by worldwide mortality.

The Science of the total environment·2021
Same journal

The life history of recessive deleterious alleles as seen through the eyes of a honey bee (Apis mellifera).

Molecular biology and evolution·2026
Same journal

Severe bottleneck of ancient Homo populations: Insights from computational modeling and relevant fossil evidence.

Molecular biology and evolution·2026
Same journal

Population Epigenetics: Deciphering DNA Methylation Diversity and its Implications for Health, Disease, and Evolution.

Molecular biology and evolution·2026
Same journal

Genomic signature of repeated transitions to diurnality in spiders.

Molecular biology and evolution·2026
Same journal

Phylogenomic blind spots: The limits of UCE and BUSCO loci in the presence of gene flow.

Molecular biology and evolution·2026
Same journal

seqLens: Optimizing Language Models for Genomic Predictions.

Molecular biology and evolution·2026
See all related articles

Related Experiment Video

Updated: Mar 25, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.3K

LS³: A Method for Improving Phylogenomic Inferences When Evolutionary Rates Are Heterogeneous among Taxa.

Carlos J Rivera-Rivera1, Juan I Montoya-Burgos2

  • 1Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland Institute of Genetics and Genomics in Geneva (iGE3), Geneva, Switzerland.

Molecular Biology and Evolution
|February 26, 2016
PubMed
Summary
This summary is machine-generated.

Long-branch attraction (LBA) artifacts in phylogenetic inference are reduced using Locus Specific Sequence Subsampling (LS³). This method identifies and removes problematic taxa, improving phylogenetic accuracy for complex evolutionary datasets.

Keywords:
GliresNematoda.artifactslong branch attractionphylogenomicsrate heterogeneity

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.6K
A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

740

Related Experiment Videos

Last Updated: Mar 25, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.3K
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.6K
A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

740

Area of Science:

  • Evolutionary Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Phylogenetic inference can be misled by artifacts when evolutionary models do not fit sequence evolution.
  • Long-branch attraction (LBA) is a common artifact caused by violations of model assumptions and heterogeneous evolutionary rates.
  • Accurate phylogenetic trees are crucial for understanding evolutionary relationships.

Purpose of the Study:

  • To develop an objective criterion and computational method to detect and mitigate LBA artifacts.
  • To improve the accuracy of phylogenetic inference, especially in multi-gene datasets with rate heterogeneity.

Main Methods:

  • Defined an objective criterion using a likelihood ratio test to assess lineage evolutionary rate heterogeneity.
  • Implemented the criterion in the Locus Specific Sequence Subsampling (LS³) algorithm.
  • LS³ sequentially removes fastest-evolving taxa and tests for rate homogeneity, flagging problematic sequences.

Main Results:

  • LS³ successfully identified problematic taxa in both simulated and real biological datasets.
  • Removing flagged sequences corrected previously incorrect phylogenies in all tested cases.
  • The method demonstrated effectiveness in reducing LBA artifacts in nucleotide and amino-acid datasets.

Conclusions:

  • LS³ provides a robust method for identifying and removing data that cause LBA artifacts.
  • This approach enhances the reliability of phylogenetic reconstructions from complex, multi-gene datasets.
  • The software facilitates the generation of more accurate phylogenetic trees by addressing evolutionary rate heterogeneity.