Amplicon Analysis
Amplicon Analysis - Related Videos
08:57
Amplicon Sequencing using the Long-Read Sequencing Technologies
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2025
This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.
10:24
Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
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Cited by 120 •
2014
Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer.
03:29
Capillary Electrophoresis: A Technique to Analyze Fluorescently Labeled Polymerase Chain Reaction Amplicons
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2025
This video describes the technique of capillary electrophoresis to analyze fluorescently labeled PCR amplicons obtained from various samples based on their size. It generates a migratory pattern that determines the fragments’ base-pair lengths with the help of the labeled fluorescent dye in each fragment.
03:41
Agarose Gel Electrophoresis of DNA Amplicons Post PCR: A Method to Analyze Products of Multiplex PCR and Evaluate PCR Reaction Success
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2025
In this video, we demonstrate the separation of bacterial PCR-amplified DNA using agarose gel electrophoresis. Agarose gel functions as a molecular sieve, enabling the negatively-charged DNA to migrate based upon their size under an applied electric field.
07:34
Profiling the Bacterial Community of Fermenting Traminette Grapes during Wine Production using Metagenomic Amplicon Sequencing
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Cited by 1 •
2023
Here, we present a protocol to describe amplicon metagenomic for determining the bacterial community of Traminette grapes, fermenting grapes, and final wine.
FAQs
The selected marker determines which biological features can be characterized. Bacterial 16S rRNA regions support profiling of bacterial communities, whereas fungal ITS regions support analysis of fungal communities. Choosing an appropriate target therefore aligns the sequencing result with the organismal group or biological question under investigation, such as community composition, biodiversity, or pathogen detection.
After sequencing, computational workflows filter the resulting reads, group related sequences, and assign taxonomic or functional identities. Filtering helps organize the sequence data before interpretation, while grouping and identity assignment convert raw amplicon results into information about the organisms or functions represented in each sample. These processed results enable systematic comparisons among samples.
Community composition shows which biological identities are represented in a sample, while relative abundance indicates how their representation compares within that community. Together, these outputs allow researchers to compare samples, identify changes in biological communities, and examine responses to environmental conditions. The same measurements can support ecological studies, clinical investigations, and monitoring efforts.
The target region provides the main distinction between these applications. A bacterial 16S rRNA marker is used when the investigation focuses on bacterial communities, while a fungal ITS marker is used for fungal communities. This target-specific design lets the same general sequencing strategy address different organismal groups without treating all community members as one undifferentiated population.
A typical workflow begins by selecting and PCR-amplifying a marker region from the DNA being studied. Researchers then sequence the resulting amplicons and process the reads computationally. The analysis includes read filtering, grouping related sequences, and assigning taxonomic or functional identities. The final profiles can then be compared across samples or conditions.
This approach is useful when the goal is to profile microbial communities, assess biodiversity, detect pathogens, or monitor biological changes in an environment. It can reveal differences in community composition and relative abundance between samples, making it suitable for tracking ecological or clinical changes and for examining how communities respond to environmental conditions.
Amplicon analysis can address whether biological communities differ between samples, which organisms are represented, and how community profiles change over time or under different environmental conditions. In biological research, these results support environmental monitoring, biodiversity assessment, microbial community studies, and pathogen-focused investigations by linking sequence-based identities with broader changes in biological systems.