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Genome Annotation and Assembly

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.

Gene Families

Gene Families

Protein Networks

Protein Networks

Cell Specific Gene Expression

Cell Specific Gene Expression

Protein Families

Protein Families

RNA-seq

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...

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Related Experiment Video

Updated: Sep 3, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Functional Annotation of Custom Transcriptomes.

Fursham Hamid¹, Kaur Alasoo², Jaak Vilo²

¹Centre for Developmental Neurobiology, King's College London, London, UK. fursham.hamid@kcl.ac.uk.

Methods in Molecular Biology (Clifton, N.J.)

|July 27, 2022

Summary

This summary is machine-generated.

Understanding gene regulation requires analyzing alternative RNA transcripts. Our bioinformatics workflows and the factR R package simplify the annotation and functional prediction of these novel transcripts.

Keywords:

Alternative pre-mRNA processing Custom transcriptome Long-read RNA-seq Nonsense-mediated decay Protein domains RNA sequencing Single-cell RNA-seq

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Last Updated: Sep 3, 2025

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

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

Published on: May 9, 2017

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Eukaryotic genes exhibit alternative splicing, producing diverse RNA transcripts.
Transcriptome-wide sequencing technologies enable detailed profiling of RNA isoforms.
Functional characterization of sample-specific transcripts presents a significant challenge.

Purpose of the Study:

To develop streamlined bioinformatics workflows for reference-guided annotation of novel transcripts.
To facilitate the understanding of biological functions for alternative RNA isoforms.
To introduce the factR R package for transcript analysis.

Main Methods:

Development of bioinformatics pipelines for transcript annotation.
Utilizing the R package factR for transcript-to-gene matching.
Deducing protein sequence and domain structures of novel products.
Predicting RNA isoform sensitivity to nonsense-mediated decay.

Main Results:

A simplified workflow for annotating novel transcripts was established.
The factR package efficiently matches custom transcripts to host genes.
Prediction of protein product features and decay sensitivity is enabled.

Conclusions:

Bioinformatics workflows, particularly using factR, simplify the annotation and functional analysis of alternative RNA transcripts.
These tools aid in understanding the functional implications of transcript diversity.
The methods support advancing research in genomics and RNA processing.