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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
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...
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...
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...
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Published on: December 7, 2021

Computing evolutionary distinctiveness indices in large scale analysis.

Iain Martyn1, Tyler S Kuhn, Arne O Mooers

  • 1IRMACS and BioSciences, Simon Fraser University, 8888 University Drive, Burnaby, V5A 1S6 Canada. amooers@sfu.ca.

Algorithms for Molecular Biology : AMB
|April 17, 2012
PubMed
Summary
This summary is machine-generated.

New algorithms efficiently calculate Shapley values and heightened evolutionary distinctiveness (HED) scores for phylogenetic trees. These methods provide novel insights into species conservation, highlighting those crucial for imperiled relatives.

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Area of Science:

  • Phylogenetics
  • Computational Biology
  • Conservation Science

Background:

  • Phylogenetic trees are crucial for understanding evolutionary relationships.
  • Existing methods for assessing species' evolutionary importance, like fair proportion (FP), have limitations.
  • There is a need for efficient and robust methods to quantify species' evolutionary distinctiveness.

Purpose of the Study:

  • To develop and present optimal linear time algorithms for computing Shapley values and heightened evolutionary distinctiveness (HED) scores.
  • To apply these algorithms to a large dataset of mammal phylogenetic trees.
  • To compare the results with existing indices like fair proportion (FP).

Main Methods:

  • Development of linear time algorithms for Shapley value and HED score computation.
  • Application of algorithms to 10,000 mammal phylogenetic trees (5,139 species each).
  • Comparative analysis of Shapley values, HED scores, and FP scores.

Main Results:

  • Shapley values strongly correlate with FP scores but give higher weight to monotremes.
  • HED scores are sensitive to extinction probabilities; low probabilities yield scores similar to species age.
  • High extinction probabilities for endangered species increase their HED scores, potentially altering conservation rankings.

Conclusions:

  • The new algorithms efficiently compute important evolutionary indices on large datasets.
  • Shapley values and HED scores offer nuanced perspectives on species' evolutionary significance.
  • HED scores highlight species critical for conserving genetic diversity of imperiled relatives, informing conservation priorities.