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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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
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BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome

Paulo Rapazote-Flores1, Micha Bayer1, Linda Milne1

  • 1Information and Computational Sciences, James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK.

BMC Genomics
|December 13, 2019
PubMed
Summary
This summary is machine-generated.

A new barley reference transcript dataset (BaRTv1.0) provides a high-quality resource for accurate RNA-seq analysis. This dataset improves gene expression and alternative splicing quantification in plants.

Keywords:
BarleyDifferential alternative splicingDifferential gene expressionReference transcript datasetTranscriptome

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Area of Science:

  • Plant Genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • RNA sequencing (RNA-seq) data analysis is time-consuming, involving gene expression and splicing quantification.
  • Fast alignment-free tools like Kallisto and Salmon require high-quality reference transcript datasets (RTDs), which are scarce for plants.

Purpose of the Study:

  • To generate a high-quality, non-redundant barley reference transcript dataset (RTD).
  • To develop a robust pipeline for accurate RNA-seq data analysis, including gene expression and alternative splicing.
  • To overcome limitations in current plant RTDs for advanced transcriptomic analyses.

Main Methods:

  • Construction of the Barley Reference Transcripts version 1.0 (BaRTv1.0) from diverse barley tissues, cultivars, and treatments.
  • Assembly and alignment of transcripts to the barley cv. Morex reference genome.
  • Validation of alternatively spliced (AS) transcripts using high-resolution RT-PCR and full-length cDNAs.
  • Development of BaRTv1.0-Quantification of Alternatively Spliced Isoforms (BaRTv1.0-QUASI) for accurate transcript quantification.

Main Results:

  • Generated BaRTv1.0, a comprehensive barley gene RTD with 60,444 genes and 177,240 transcripts.
  • BaRTv1.0 transcripts are longer, less fragmented, and feature improved gene models compared to existing datasets.
  • Analysis using BaRTv1.0-QUASI identified 20,972 differentially expressed genes, 2791 differentially alternatively spliced genes, and 2768 transcripts with differential transcript usage in five barley tissues.

Conclusions:

  • The BaRTv1.0 dataset offers a high-confidence resource for barley transcriptomics.
  • BaRTv1.0 enables precise quantification of gene expression and alternative splicing, facilitating routine analysis.
  • This resource addresses the need for comprehensive RTDs in plant research, improving the efficiency and accuracy of RNA-seq data interpretation.