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Related Concept Videos

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

Microbial communities, comprising bacteria, archaea, and eukaryotic microorganisms, inhabit diverse ecosystems and play crucial roles in environmental and biological processes. Their diversity is defined by three main parameters: species richness (the number of distinct species), species abundance (the relative quantity of each species), and species evenness (how uniformly individual species are distributed in various locations). These factors together shape the structure and ecological balance...
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...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Evolution of Microbial Genome01:08

Evolution of Microbial Genome

Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.

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Related Experiment Video

Updated: Jun 3, 2026

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
07:21

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

Rethinking microbial diversity analysis in the high throughput sequencing era.

Leandro N Lemos1, Roberta R Fulthorpe, Eric W Triplett

  • 1Universidade Federal do Pampa, Campus São Gabriel, Av. Antônio Trilha, 1847, São Gabriel, RS, Brazil.

Journal of Microbiological Methods
|April 5, 2011
PubMed
Summary

Sequencing depth in 16S rRNA gene studies significantly impacts microbial community analysis. Insufficient sequencing effort can bias results, favoring phylogenetic methods for low-coverage datasets.

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Last Updated: Jun 3, 2026

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
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Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing
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Published on: March 19, 2018

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
10:24

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Published on: August 29, 2014

Area of Science:

  • Microbiology
  • Bioinformatics
  • Ecology

Background:

  • 16S rRNA gene sequencing is a primary method for microbial diversity studies.
  • High-throughput sequencing enables large-scale, cost-effective microbial community analysis.
  • Determining adequate sequencing depth is critical to avoid biased results.

Purpose of the Study:

  • To investigate how sequencing effort influences the analysis of microbial communities.
  • To identify optimal sequencing depths for different analytical approaches.
  • To assess the impact of sequencing depth on diversity metrics and community comparisons.

Main Methods:

  • Simulations were conducted using four independent pyrosequencing-generated 16S rRNA gene libraries.
  • Analysis focused on comparing OTU-based and phylogenetic approaches under varying sequence coverage.
  • Data normalization strategies were evaluated for datasets with different sample sizes.

Main Results:

  • Sequencing effort demonstrably biases microbial community analysis results.
  • OTU-based approaches lack resolution with low sequence coverage; 90% coverage is recommended.
  • Phylogenetic approaches offer better resolution for low-coverage datasets.
  • Diversity indices correlate with sample size, necessitating normalization.

Conclusions:

  • Adequate sequencing depth is crucial for accurate microbial community profiling.
  • Phylogenetic methods are advantageous for low-coverage 16S rRNA gene data.
  • Careful consideration of sequencing effort and analytical methods is essential for reliable microbiome research.