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Genome Annotation and Assembly

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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: Dec 11, 2025

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

TransBorrow: genome-guided transcriptome assembly by borrowing assemblies from different assemblers.

Ting Yu¹, Zengchao Mu¹, Zhaoyuan Fang²

¹School of Mathematics and Statistics, Shandong University (Weihai), Weihai 264209, China.

Genome Research

|August 21, 2020

Summary

This summary is machine-generated.

TransBorrow, a novel transcriptome assembler, enhances RNA sequencing (RNA-seq) data analysis by borrowing assemblies to identify reliable subsequences. This method significantly outperforms existing assemblers in transcriptomic studies.

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Last Updated: Dec 11, 2025

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

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Published on: August 20, 2021

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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:

Bioinformatics
Genomics
Molecular Biology

Background:

RNA sequencing (RNA-seq) is a powerful technology for transcriptomic studies, enabling the exploration of complex transcriptome structures.
Effective analysis of RNA-seq data is crucial for understanding gene expression and regulation.
Existing transcriptome assemblers face challenges in accurately reconstructing transcript structures.

Purpose of the Study:

To introduce TransBorrow, a novel computational tool for improving transcriptome assembly from RNA-seq data.
To enhance the accuracy and reliability of transcript structure identification.
To provide a superior alternative to current leading transcriptome assemblers.

Main Methods:

TransBorrow utilizes a novel approach by borrowing assemblies from multiple assemblers.
It constructs a colored graph to identify reliable subsequences from these borrowed assemblies.
A new path extension strategy is employed to accurately determine transcript-representing paths within splicing graphs.

Main Results:

TransBorrow demonstrated superior performance compared to leading transcriptome assemblers.
The assembler showed high accuracy in reconstructing transcript structures on both simulated and real RNA-seq datasets.
The borrowing strategy and path extension method proved effective in identifying reliable transcript subsequences.

Conclusions:

TransBorrow offers a significant advancement in transcriptome assembly for RNA-seq data analysis.
The tool's innovative approach overcomes limitations of existing assemblers.
It provides a more accurate and reliable method for exploring complex transcriptomes.