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Related Concept Videos

RNA-seq03:21

RNA-seq

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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. 
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Related Experiment Video

Updated: Jan 14, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Computational methods for the analysis of long-read RNA-seq data.

Kristina Santucci1, Yuning Cheng1, Si-Mei Xu1

  • 1School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia.

Genomics
|October 19, 2025
PubMed
Summary
This summary is machine-generated.

Long-read RNA sequencing (lrRNA-seq) enhances gene discovery and characterization. This review details lrRNA-seq applications in genomics, transcriptomics, and proteomics, exploring isoform analysis and RNA processing events.

Keywords:
Long-read sequencinggenomicsnovel genesnovel isoformsproteomicstranscriptomics

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Area of Science:

  • Genomics and Molecular Biology
  • Transcriptomics
  • Proteomics

Background:

  • Advancements in long-read sequencing and bioinformatics have expanded RNA sequencing (RNA-seq) capabilities.
  • RNA-seq is increasingly used for discovering and characterizing novel genes, isoforms, and proteins.

Purpose of the Study:

  • To review developments in long-read RNA sequencing (lrRNA-seq) across genomics, transcriptomics, and proteomics.
  • To explore methods for characterizing transcript isoforms from novel and annotated genes.
  • To elaborate on lrRNA-seq approaches for analyzing RNA processing events and discuss limitations.

Main Methods:

  • Review of recent literature on long-read sequencing technologies and bioinformatic tools.
  • Analysis of strategies for transcript isoform characterization, including protein-coding potential and functional domains.
  • Examination of lrRNA-seq applications for studying alternative splicing, polyadenylation, and RNA modifications.

Main Results:

  • lrRNA-seq facilitates the discovery and detailed characterization of novel genes and transcriptional isoforms.
  • Methods are presented for assessing protein-coding potential, functional domains, and conserved regions of isoforms.
  • lrRNA-seq enables comprehensive analysis of co-transcriptional and post-transcriptional RNA modifications and processing.

Conclusions:

  • Integrated analyses using lrRNA-seq offer powerful insights across diverse molecular biology domains.
  • Addressing limitations and conflicting recommendations is crucial for advancing lrRNA-seq methodologies.
  • Future research should prioritize refining lrRNA-seq approaches for comprehensive molecular profiling.