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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.

Protein Complex Assembly

Protein Complex Assembly

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: Nov 3, 2025

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

TrancriptomeReconstructoR: data-driven annotation of complex transcriptomes.

Maxim Ivanov¹, Albin Sandelin^2,3, Sebastian Marquardt⁴

¹Department of Plant and Environmental Sciences, Copenhagen Plant Science Centre, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiskberg C, Denmark. maxim.ivanov@plen.ku.dk.

BMC Bioinformatics

|June 1, 2021

Summary

This summary is machine-generated.

This study introduces TranscriptomeReconstructoR, an R package for automated transcriptome annotation. It improves gene model accuracy and comprehensiveness by integrating diverse RNA-seq data, enhancing genome research quality.

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Last Updated: Nov 3, 2025

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Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Area of Science:

Genomics
Transcriptomics
Bioinformatics

Background:

Accurate gene annotation is crucial for interpreting transcriptomic study results.
The increasing volume of genomic data necessitates efficient de novo transcriptome annotation pipelines.
Gene and transcript models ideally should be derived from minimal key experimental data.

Purpose of the Study:

To develop an automated pipeline for de novo transcriptome annotation.
To enhance the accuracy and comprehensiveness of gene and transcript models.
To provide a cost-efficient strategy for annotating complex eukaryotic transcriptomes.

Main Methods:

Developed TranscriptomeReconstructoR, an R package implementing an automated annotation pipeline.
Integrated full-length RNA-seq data for splicing pattern detection.
Utilized high-throughput 5' and 3' tag sequencing data for gene border definition.
Incorporated nascent RNA-seq data to identify transient transcripts.

Main Results:

Successfully reconstructed the transcriptional landscape of Arabidopsis thaliana and Saccharomyces cerevisiae.
Demonstrated that the new gene models are more accurate and comprehensive than existing community models (TAIR10, Araport11, SacCer3).
Identified numerous transient transcripts previously missing from current annotations.

Conclusions:

The TranscriptomeReconstructoR package offers a cost-efficient strategy for rapid and accurate transcriptome annotation.
The pipeline requires only reference genomic DNA sequence, not transcriptome data.
Seamless integration with Bioconductor facilitates downstream analysis.