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Related Concept Videos

RNA-seq03:21

RNA-seq

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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: Jun 9, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

HyDRA: A pipeline for integrating long- and short-read RNAseq data for custom transcriptome assembly.

Isabela Almeida1,2, Xue Lu1, Stacey L Edwards1,2,3

  • 1Cancer Program, QIMR Berghofer, Brisbane, QLD 4029, Australia.

Iscience
|June 8, 2026
PubMed
Summary

This study introduces HyDRA, a novel pipeline for transcriptome assembly. HyDRA combines short and long sequencing reads to accurately reconstruct full-length transcripts and discover novel noncoding RNAs.

Keywords:
BioinformaticsMolecular biologySystems biology

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Area of Science:

  • Genomics
  • Bioinformatics
  • Transcriptomics

Background:

  • Short-read RNA sequencing (RNAseq) is limited in reconstructing full-length transcripts and capturing transcript diversity.
  • Long-read RNAseq offers structural resolution but suffers from high error rates.
  • Noncoding RNA transcripts are often underrepresented in current genomic references.

Purpose of the Study:

  • To develop a hybrid bioinformatics pipeline for *de novo* transcriptome assembly.
  • To integrate short-read accuracy with long-read structural resolution.
  • To improve the completeness and accuracy of transcriptome reconstruction, particularly for noncoding RNAs.

Main Methods:

  • Presentation of the hybrid *de novo* RNA assembly (HyDRA) pipeline.
  • Integration of short-read and long-read sequencing data.
  • Benchmarking of HyDRA against existing transcriptome assembly methods.

Main Results:

  • HyDRA outperforms existing methods by up to 40% in transcriptome assembly.
  • Identification of over 50,000 high-confidence long noncoding RNAs in the human ovarian metatranscriptome.
  • Discovery of numerous previously undetected noncoding RNAs.

Conclusions:

  • HyDRA provides a more complete *de novo* transcriptome assembly by leveraging both short and long reads.
  • The pipeline significantly enhances the detection of long noncoding RNAs.
  • HyDRA is crucial for advancing the understanding of transcriptomic complexity and the noncoding genome, especially given the abundance of short-read data.