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RNA-seq

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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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Updated: May 19, 2026

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

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

Published on: May 9, 2017

Optimizing de novo common wheat transcriptome assembly using short-read RNA-Seq data.

Jialei Duan¹, Chuan Xia, Guangyao Zhao

¹Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Zhongguancun, Beijing, People's Republic of China.

|August 16, 2012

Summary

This summary is machine-generated.

De novo assembly of the hexaploid wheat transcriptome from short reads is feasible. Optimizing steps like redundancy removal is crucial for accurate RNA profiling and valuable transcript data.

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Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

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Last Updated: May 19, 2026

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

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

Published on: May 9, 2017

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Area of Science:

Genomics
Bioinformatics
Plant Science

Background:

Next-generation sequencing (NGS) has advanced transcriptome sequencing (RNA-Seq).
RNA-Seq offers cost-efficient, in-depth transcriptome study for model and non-model organisms.
De novo assembly is essential for RNA-Seq in organisms lacking reference genomes.

Purpose of the Study:

To optimize de novo transcriptome assembly from short reads for hexaploid wheat.
To evaluate the performance of different assembly strategies and bioinformatic tools.
To provide new wheat transcript data for the scientific community.

Main Methods:

Utilized 212.6 million pair-end reads (16.2 Gb) for hexaploid wheat transcriptome assembly.
Employed two state-of-the-art assemblers: Trinity (single k-mer) and Trans-ABySS (multiple k-mer).
Implemented a four-step assembly process: pre-assembly, sample merging, redundancy removal, and scaffolding.

Main Results:

Optimized assembly achieved transcript continuity and accuracy comparable to Sanger-derived ESTs.
Demonstrated the feasibility of de novo assembly for hexaploid wheat using short reads.
Generated substantial new wheat transcript data.

Conclusions:

De novo assembly of the hexaploid wheat transcriptome from short reads is achievable.
Balancing expression levels and redundancy is critical when handling multiple samples.
Redundancy removal is essential for accurate RNA profiling in de novo assembly.