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Updated: May 29, 2025

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Combining Short- and Long-Read Transcriptomes for Targeted Enzyme Discovery.

Mojca Juteršek1, Marko Petek2, Špela Baebler2

  • 1National Institute of Biology, Department of Biotechnology and Systems Biology, Ljubljana, Slovenia. Mojca.Jutersek@nib.si.

Methods in Molecular Biology (Clifton, N.J.)
|February 3, 2025
PubMed
Summary

This study presents a transcriptomics pipeline to identify genes with specific enzymatic activity in nonmodel organisms. The method combines diverse sequencing data for accurate gene discovery, aiding biotechnology and metabolic pathway research.

Keywords:
De novo transcriptome assemblyEnzyme identificationIso-SeqTranscriptomics

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Area of Science:

  • Life Science
  • Biotechnology
  • Genomics

Background:

  • Identifying genes for specific enzymatic activity is crucial for life sciences and biotechnology.
  • Many genes involved in secondary metabolite production and specialized metabolic pathways remain undiscovered.
  • High-throughput methods are needed to discover genes with minimal prior knowledge due to nature's diversity.

Purpose of the Study:

  • To describe a transcriptomics pipeline for discovering candidate genes encoding specific enzymatic activity in nonmodel species.
  • To provide a method for targeted gene discovery using combined sequencing data.
  • To offer detailed instructions for analysis and quality control applicable to various biological questions.

Main Methods:

  • Generated and integrated short- and long-read transcriptomic data.
  • Obtained full-length transcript sequences, allelic variation, and isoform expression data.
  • Utilized protein domain annotations and transcriptomic data to select candidate genes for activity assays.

Main Results:

  • Developed a robust transcriptomics pipeline for identifying genes with enzymatic activity.
  • Successfully selected candidate genes for further functional validation.
  • The pipeline provides reliable full-length transcript sequences and expression information.

Conclusions:

  • The described transcriptomics pipeline is effective for discovering genes encoding specific enzymatic activities in nonmodel organisms.
  • This approach facilitates the identification of novel genes for biotechnological applications.
  • The pipeline's detailed instructions and quality control steps enhance its applicability to diverse research areas.