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Updated: Apr 21, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Next generation sequencing and de novo transcriptomics to study gene evolution.

Achala S Jayasena¹, David Secco¹, Kalia Bernath-Levin¹

¹The University of Western Australia, School of Chemistry and Biochemistry & ARC Centre of Excellence in Plant Energy Biology, 35 Stirling Highway, Crawley Perth, 6009 Australia.

|November 4, 2014

Summary

This summary is machine-generated.

De novo transcriptomics enables studying gene evolution in non-model species by analyzing gene transcripts. This approach overcomes limitations of PCR-based methods for conserved genes, making it effective for diverse species.

Keywords:

Cyclic peptides De novo transcriptomics Gene evolution PawS1

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Area of Science:

Genomics
Evolutionary Biology
Bioinformatics

Background:

Studying gene evolution in non-model organisms is challenging with traditional PCR methods, which are restricted to highly conserved genes.
Advances in next-generation sequencing (NGS) have made de novo transcriptomics a cost-effective and accessible tool for any species.

Purpose of the Study:

To describe a methodology for applying de novo transcriptomics to investigate the evolution of a single gene of interest.
To demonstrate the utility of this approach for rapidly evolving genes, using a seed protein as a model.

Main Methods:

Assembly of four de novo seed transcriptomes using user-friendly software.
Confirmation of predicted genes at the peptide level in a species with multiple gene copies.
Development of strategies for assembling low-abundance genes and optimizing assembly parameters for transcript capture.
Comparison of various sequencing depths to balance cost and data volume.

Main Results:

Successful assembly of de novo transcriptomes for four species.
Validation of gene predictions at the peptide level, demonstrating assembly accuracy.
Identification of optimal strategies and parameters for capturing low-abundance transcripts and maximizing assembly quality.
Evaluation of sequencing depth trade-offs for cost-efficiency.

Conclusions:

De novo transcriptomics provides an effective strategy for gene evolution studies in species lacking genomic resources.
This approach significantly expands the scope of evolutionary genetic research to a wider range of organisms.