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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...

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Updated: Sep 5, 2025

Isolation and Transcriptome Analysis of Plant Cell Types

Isolation and Transcriptome Analysis of Plant Cell Types

Published on: April 7, 2023

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis.

Runxuan Zhang¹, Richard Kuo², Max Coulter³

¹Information and Computational Sciences, James Hutton Institute, Dundee, DD2 5DA, Scotland, UK. runxuan.zhang@hutton.ac.uk.

|July 7, 2022

Summary

A new Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3) offers a comprehensive transcriptome, improving gene expression analysis and identifying novel transcripts. Novel methods enhance splice junction and transcription site accuracy for any species.

Keywords:

Alternative polyadenylation Alternative splicing Arabidopsis Iso-seq Reference transcript dataset Splice junction Transcription start and end sites

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Area of Science:

Plant molecular biology
Genomics
Bioinformatics

Background:

Accurate transcript annotation is crucial for gene expression analysis.
Single-molecule long-read sequencing offers transcript integrity but faces accuracy challenges.
Sequencing errors, RNA degradation, and incomplete cDNA synthesis impact accuracy.

Purpose of the Study:

To present the Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3).
To introduce novel methods for accurate splice junction and transcription start/end site determination.
To improve transcript quantification and differential expression analysis.

Main Methods:

Development of novel computational methods for splice junction and transcription start/end site identification.
Utilizing Iso-seq data for high-accuracy transcript structure determination.
Stratified approaches to identify high-confidence sites and remove fragmentary transcripts.

Main Results:

AtRTD3 contains over 169,000 transcripts, doubling existing datasets and including over 1500 novel genes.
Seventy-eight percent of transcripts feature accurately defined splice junctions and transcription start/end sites.
Analysis of an Arabidopsis cold response dataset demonstrated improved transcript expression profiling and identification of differential transcription start/polyadenylation site usage.

Conclusions:

AtRTD3 is the most comprehensive Arabidopsis transcriptome available.
It enhances precision in analyzing gene expression, alternative splicing, and transcription start/end site usage from RNA-seq data.
The developed methods are broadly applicable to single-molecule sequencing analysis across species.