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Related Concept Videos

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Related Experiment Video

Updated: Jun 30, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Enhanced RNA-Seq Expression Profiling and Functional Enrichment in Non-model Organisms Using Custom Annotations.

Infanta Saleth Teresa Eden M1, Umashankar Vetrivel1,2

  • 1Department of Virology and Biotechnology, Bioinformatics Division, Indian Council for Medical Research -National Institute for Research in Tuberculosis (ICMR-NIRT), Chennai, India.

Bio-Protocol
|June 29, 2026
PubMed
Summary

Researchers developed a new R package method for functional enrichment analysis in organisms lacking detailed gene annotations. This approach improves accuracy for microbial genomics by creating custom annotation packages from NCBI data.

Keywords:
Customized annotationGene enrichment analysisNon-model organismsR packagesclusterProfiler

More Related Videos

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Related Experiment Videos

Last Updated: Jun 30, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

  • Genomics
  • Bioinformatics
  • Microbial Research

Background:

  • Functional enrichment analysis is crucial for interpreting differentially expressed genes but is challenging for non-model organisms due to scarce annotations.
  • Existing tools often rely on homology-based annotation transfer, which can lead to errors and miss species-specific functions.
  • There is a need for reliable methods to perform accurate functional enrichment analysis in organisms with limited genomic annotation resources.

Purpose of the Study:

  • To present a user-friendly and adaptable method for creating custom R annotation packages using NCBI genomic data.
  • To enable effective gene ontology and pathway enrichment analysis for organisms with limited functional annotations.
  • To demonstrate the utility of this approach for microbial genomics research, specifically for *Mycobacterium tuberculosis*.

Main Methods:

  • Developed a workflow to build custom R annotation packages from a comprehensive SQLite database of NCBI genomic data.
  • Extracted species-specific records using taxonomic identifiers to create tailored annotation packages.
  • Utilized the custom R package with the clusterProfiler package for gene ontology and KEGG enrichment analysis on RNA-seq data (GSE292409) from *Mycobacterium tuberculosis* H37Rv.

Main Results:

  • Successfully constructed an R annotation package for *Mycobacterium tuberculosis* H37Rv.
  • Performed functional enrichment analysis on differentially expressed genes in response to rifampicin treatment.
  • Demonstrated the method's capability to provide accurate and biologically relevant gene expression interpretation.

Conclusions:

  • The developed workflow offers a reliable and scalable solution for functional enrichment analysis in organisms with limited annotation data.
  • Custom R annotation packages enhance the accuracy and biological relevance of gene expression interpretation in microbial genomics.
  • This approach facilitates deeper understanding of microbial responses and functions, even in under-annotated species.