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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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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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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Behavioral Genetics and Its Designs

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Updated: May 22, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Genetic analysis.

Gavin J D Smith1, Justin Bahl, Dhanasekaran Vijaykrishna

  • 1Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, Singapore, Singapore. gavin.smith@duke-nus.edu.sg

Methods in Molecular Biology (Clifton, N.J.)
|April 25, 2012
PubMed
Summary
This summary is machine-generated.

Phylogenetic analysis of influenza A virus sequence data reveals evolutionary history and molecular epidemiology. This study outlines routine methods including sequence alignment, evolutionary model selection, and tree reconstruction.

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Related Experiment Videos

Last Updated: May 22, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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Published on: November 3, 2010

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Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
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Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

Area of Science:

  • Virology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Influenza A virus (IAV) presents a complex ecosystem with multiple hosts, necessitating robust genetic analysis.
  • Understanding IAV evolution and epidemiology is crucial for public health and pandemic preparedness.

Purpose of the Study:

  • To outline routine phylogenetic analyses for influenza A virus sequence data.
  • To provide a framework for investigating viral evolution and molecular epidemiology.

Main Methods:

  • Multiple sequence alignment of viral genomes.
  • Selection of the best-fit evolutionary model for phylogenetic inference.
  • Phylogenetic tree reconstruction using Neighbor-Joining, Maximum Likelihood, and Bayesian inference methods.

Main Results:

  • Demonstration of established phylogenetic workflows applicable to influenza A virus.
  • Identification of key steps for accurate evolutionary history reconstruction.
  • Comparative overview of different phylogenetic reconstruction algorithms.

Conclusions:

  • Phylogenetic analysis is essential for understanding influenza A virus evolution and epidemiology.
  • Standardized methods ensure reliable reconstruction of viral evolutionary history.
  • These analyses support global surveillance and control strategies for influenza.