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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...
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Evolution of Microbial Genome

Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.
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.
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Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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...

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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Published on: May 28, 2021

ALF--a simulation framework for genome evolution.

Daniel A Dalquen1, Maria Anisimova, Gaston H Gonnet

  • 1Computational Biochemistry Research Group, Department of Computer Science, ETH Zurich, Universitätstrasse 6, Zürich, Switzerland. ddalquen@inf.ethz.ch

Molecular Biology and Evolution
|December 14, 2011
PubMed
Summary
This summary is machine-generated.

Artificial Life Framework (ALF) simulates diverse genomic evolutionary forces, from nucleotide substitutions to speciation. This tool aids in verifying computational evolutionary biology methods and reveals how lateral gene transfer impacts orthology inference.

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Area of Science:

  • Computational evolutionary biology
  • Bioinformatics
  • Genomics

Background:

  • Verification and benchmarking of computational evolutionary biology methods are challenging due to unknown evolutionary histories.
  • Existing simulation packages often focus on either gene-level (e.g., substitutions, indels) or genome-level (e.g., rearrangements, speciation) evolutionary aspects.
  • A comprehensive simulation framework is needed to model the full spectrum of evolutionary forces acting on genomes.

Purpose of the Study:

  • Introduce Artificial Life Framework (ALF), a novel tool for simulating a wide range of genomic evolutionary processes.
  • Provide a user-friendly web interface for ALF to enhance accessibility for researchers.
  • Demonstrate ALF's utility in reanalyzing existing data and evaluating the impact of evolutionary events on bioinformatics methods.

Main Methods:

  • ALF simulates nucleotide, codon, or amino acid substitutions (simple/mixture models), insertions/deletions (indels), GC-content amelioration, gene duplication/loss/fusion/fission, genome rearrangement, lateral gene transfer (LGT), and speciation.
  • The framework offers a web interface and stand-alone application.
  • ALF was used to reanalyze globin gene duplication data and assess the effect of LGT on orthology inference methods.

Main Results:

  • ALF successfully simulates a comprehensive suite of evolutionary forces acting on genomes.
  • Reanalysis of globin gene duplication data using ALF allowed for testing the statistical significance of original conclusions.
  • Simulations demonstrated that lateral gene transfer (LGT) can significantly reduce the accuracy of established orthology inference methods.

Conclusions:

  • ALF provides a versatile platform for simulating complex evolutionary scenarios in silico.
  • The framework is valuable for verifying and benchmarking computational evolutionary biology tools.
  • ALF highlights the critical impact of LGT on genomic analyses, particularly orthology detection.