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Related Concept Videos

Gene Duplication and Divergence02:37

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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...
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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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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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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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A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
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Detection of Copy Number Alterations Using Single Cell Sequencing
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Detecting Selection on Segregating Gene Duplicates in a Population.

Tristan L Stark1,2, Rebecca S Kaufman3, Maria A Maltepes3

  • 1Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA. tristan.stark@utas.edu.au.

Journal of Molecular Evolution
|August 3, 2021
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Summary
This summary is machine-generated.

This study introduces a new method to detect selection on gene copy number variants (CNVs) within populations. The approach uses allele age and frequency to identify adaptive diversification driven by gene duplication.

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Area of Science:

  • Evolutionary genetics
  • Population genetics
  • Genomics

Background:

  • Gene duplication is a key driver of phenotypic evolution and adaptive diversification.
  • Existing methods for detecting selection on gene duplicates primarily focus on inter-specific comparisons and coding sequence changes.
  • There is a need for methods to detect selection directly on copy number variants (CNVs) segregating within populations.

Purpose of the Study:

  • To develop and validate a novel method for detecting selection acting directly on gene copy number variants (CNVs) within a population.
  • To establish a neutral baseline for CNVs using population genetics models.
  • To assess the power of the method in detecting selection under varying population sizes and ploidy levels.

Main Methods:

  • Utilized a Moran Model to simulate neutral baselines for CNVs in both haploid and diploid populations of varying effective population sizes.
  • Employed mathematical analysis and simulations to establish the method's ability to reject neutrality based on allele age (measured by pairwise dS) and frequency.
  • Developed an R package (CNVSelectR) to implement the proposed methodology.

Main Results:

  • The method successfully establishes a neutral baseline for CNVs based on expected relationships between allele age and frequency, influenced by effective population size.
  • Simulations and mathematical analyses demonstrate the method's power to detect selection on CNVs, particularly in diploid populations and those with larger effective population sizes.
  • The study provides a robust tool for analyzing selection on CNVs in diverse evolutionary contexts.

Conclusions:

  • The developed method offers a powerful new approach to detect selection on gene copy number variants within populations.
  • This tool can be extended to analyze selection on CNVs in natural and experimentally evolving populations.
  • The availability of the CNVSelectR R package facilitates the application of this method in broader research.