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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

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.Positive Frequency-Dependent SelectionIn positive...
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Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
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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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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,...

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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
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Published on: December 28, 2010

Estimating selection pressures on HIV-1 using phylogenetic likelihood models.

S L Kosakovsky Pond1, A F Y Poon, S Zárate

  • 1Department of Pathology, University of California, San Diego, CA 92093, USA.

Statistics in Medicine
|April 3, 2008
PubMed
Summary
This summary is machine-generated.

Statistical models reveal how human immunodeficiency virus (HIV-1) evolves under immune and drug pressures. Analyzing viral sequences helps understand HIV-1 evolution in different body compartments and genes.

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Pairwise Growth Competition Assay for Determining the Replication Fitness of Human Immunodeficiency Viruses

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Area of Science:

  • Evolutionary biology
  • Virology
  • Computational biology

Background:

  • Human immunodeficiency virus (HIV-1) exhibits rapid evolution.
  • Viral evolution is driven by immune responses, antiviral drugs, and host factors.
  • Understanding HIV-1 evolution is crucial for treatment and prevention.

Purpose of the Study:

  • To review and apply statistical models for analyzing HIV-1 evolution.
  • To elucidate selection pressures shaping HIV-1 in vivo.
  • To investigate compartment-specific and site-specific viral evolution.

Main Methods:

  • Comparative analysis of non-synonymous and synonymous substitution rates in HIV-1 sequences.
  • Development and application of statistical models accounting for sequence non-independence.
  • Analysis of HIV-1 env evolution in blood and cerebrospinal fluid.
  • Examination of gag gene variation in subtype C HIV-1.

Main Results:

  • Statistical models effectively characterize in vivo HIV-1 evolution.
  • Identified distinct evolutionary patterns in different body compartments (blood vs. CSF).
  • Revealed site-specific variation within the HIV-1 gag gene.

Conclusions:

  • Statistical modeling is a powerful tool for understanding HIV-1 evolutionary dynamics.
  • Compartment-specific pressures significantly influence HIV-1 evolution.
  • Site-specific analyses provide insights into viral adaptation and immune evasion.