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Related Concept Videos

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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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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Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
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Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...
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Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
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Gene therapy is a technique where a gene is inserted into a person’s cells to prevent or treat a serious disease. The added gene may be a healthy version of the gene that is mutated in the patient, or it could be a different gene that inactivates or compensates for the patient’s disease-causing gene. For example, in patients with severe combined immunodeficiency (SCID) due to a mutation in the gene for the enzyme adenosine deaminase, a functioning version of the gene can be...
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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
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Related Experiment Video

Updated: Feb 4, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

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16S rRNA Gene Analysis with QIIME2.

Michael Hall1, Robert G Beiko2

  • 1Dalhousie University, Halifax, Nova Scotia, Canada. ailmike.hall@dal.ca.

Methods in Molecular Biology (Clifton, N.J.)
|October 10, 2018
PubMed
Summary

This study demonstrates how the Quantitative Insights Into Microbial Ecology version 2 (QIIME2) software simplifies microbial community analysis. QIIME2 transforms raw gene sequences into understandable taxonomic profiles and visualizations, aiding microbial ecology research.

Keywords:
16S rRNA geneBioinformaticsMarker geneMicrobial ecologyQIIME

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Area of Science:

  • Microbial Ecology
  • Bioinformatics
  • Computational Biology

Background:

  • Microbial marker-gene sequence data provides insights into microbial community composition and diversity.
  • Analyzing this data involves complex computational steps, including quality checking, denoising, and taxonomic classification.
  • Numerous bioinformatics tools are required for these transformations, often leading to complex workflows.

Purpose of the Study:

  • To demonstrate the utility of the Quantitative Insights Into Microbial Ecology version 2 (QIIME2) software suite.
  • To simplify the analysis of 16S rRNA marker-gene data for microbial community studies.
  • To showcase the transformation of raw sequence data into meaningful ecological insights.

Main Methods:

  • Utilized the QIIME2 software suite for microbial marker-gene sequence analysis.
  • Applied QIIME2 to an example dataset of bumblebee gut microbial communities.
  • Demonstrated QIIME2's capabilities in sequence quality checking, denoising, and taxonomic classification.

Main Results:

  • QIIME2 effectively transforms raw 16S rRNA sequences into comprehensive taxonomic profiles.
  • The software facilitates the generation of phylogenetic trees and principal co-ordinate analyses.
  • Visualizations such as taxonomic bar plots were produced, illustrating microbial diversity.

Conclusions:

  • QIIME2 offers a streamlined and integrated approach to microbial marker-gene data analysis.
  • The software simplifies complex bioinformatics pipelines, making microbial ecology research more accessible.
  • QIIME2 enhances the visualization and interpretation of microbial community structures and diversity.