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Related Experiment Video

Updated: May 13, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

BRANCH: boosting RNA-Seq assemblies with partial or related genomic sequences.

Ergude Bao¹, Tao Jiang, Thomas Girke

¹Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.

Bioinformatics (Oxford, England)

|March 16, 2013

Summary

BRANCH improves de novo transcriptome assemblies using genomic data. This algorithm enhances transcript accuracy and completeness for genomics applications, even with related species' genomes.

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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

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

De novo transcriptome assembly is crucial for unsequenced organisms.
Challenges include transcript complexity and incomplete sequencing.
Genomic sequences can aid RNA-Seq assembly.

Purpose of the Study:

Introduce BRANCH, an algorithm to improve de novo transcriptome assemblies.
Utilize genomic information to enhance RNA-Seq assembly quality.
Increase sensitivity and precision of transcript identification.

Main Methods:

BRANCH algorithm uses assembled RNA reads (transfrags) and genomic sequences.
Customized BLAT aligns transfrags and reads to genomes.
Identifies exons, defines a directed acyclic graph, and maps transfrags.
Applies combinatorial optimization to join and extend transfrags.

Main Results:

BRANCH improved transfrag sensitivity by 5.1-56.7% and precision by 0.3-10.5% in tests.
Increased complete transcripts by 3.8-74.1% and proteins by 8.3-3.8%.
Effective even when using related species' genomic sequences (e.g., rat for mouse).

Conclusions:

BRANCH effectively enhances de novo transcriptome assemblies.
The algorithm improves accuracy and completeness of transcript and protein identification.
Applicable across different species, including cross-species genome guidance.