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Related Concept Videos

Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
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What is Population Genetics?01:25

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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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Genetic Variation01:25

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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.
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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).
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Genetic Drift03:33

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Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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SimBit: A high performance, flexible and easy-to-use population genetic simulator.

Remi Matthey-Doret1,2

  • 1Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada.

Molecular Ecology Resources
|March 13, 2021
PubMed
Summary

SimBit is a high-performance population genetics simulator capable of modeling complex selection, demographic, and mating scenarios. It offers broad applicability and efficient performance, often outperforming other simulators in benchmarks.

Keywords:
ecological geneticsevolutionary theoryforward genetic simulationmolecular evolutionpopulation genetics - theoreticalsoftware

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Area of Science:

  • Population Genetics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Population genetics simulators are crucial for understanding evolutionary processes.
  • Existing tools often have limitations in simulating complex scenarios or computational efficiency.

Purpose of the Study:

  • Introduce SimBit, a novel, high-performance forward-in-time population genetics simulator.
  • Highlight SimBit's capabilities in handling diverse genetic and ecological models.
  • Evaluate SimBit's performance against established simulators.

Main Methods:

  • SimBit simulates forward-in-time population genetics.
  • It models complex selection, demographic, and mating systems.
  • Performance benchmarks were conducted against SLiM, Nemo, and SFS_CODE.

Main Results:

  • SimBit supports a wide range of genetic and ecological scenarios, including QTL tracking and multi-species interactions.
  • It features an R wrapper for streamlined research project management.
  • SimBit demonstrated high performance, frequently outperforming other simulators in benchmarks.

Conclusions:

  • SimBit is a versatile and high-performance tool for population genetics research.
  • Its comprehensive features and efficiency make it valuable for diverse evolutionary studies.
  • SimBit provides a robust platform for complex simulations and data analysis.