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Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

Transcriptome database resource and gene expression atlas for the rose.

Annick Dubois¹, Sebastien Carrere, Olivier Raymond

¹Reproduction et Développement des Plantes UMR INRA-CNRS- Université Lyon 1-ENSL, Ecole Normale Supérieure, 46 allée d'Italie, Lyon Cedex 07 69364, France.

|November 21, 2012

Summary

This summary is machine-generated.

This study reveals rose gene expression patterns using advanced sequencing, providing valuable genetic insights for this important ornamental plant. The ROSAseq database offers a new resource for rose research and breeding.

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Published on: December 22, 2017

Area of Science:

Plant genomics
Molecular biology
Ornamental horticulture

Background:

Roses have been cultivated for centuries, but their genetic and molecular basis remains poorly understood.
Limited data exists on expressed genes in roses, hindering research into economically important traits.

Purpose of the Study:

To generate comprehensive information on rose (Rosa sp.) transcripts.
To analyze gene expression patterns across different tissues and under various stress conditions.
To create accessible bioinformatics resources for rose research.

Main Methods:

Utilized Illumina and 454 sequencing technologies for transcript discovery.
Performed digital gene expression analysis and validated with quantitative PCR (qPCR).
Developed the ROSAseq web interface and ROSAcyc pathway database.

Main Results:

Identified 80,714 transcript clusters and predicted 76,611 peptides.
Found orthologs in related species (strawberry, peach) for approximately half of the predicted rose peptides.
Successfully identified tissue-specific and condition-specific gene expression patterns.

Conclusions:

The study provides accurate and well-annotated data on rose expressed genes.
Expression pattern analysis offers valuable insights for understanding rose biology.
The developed resources (ROSAseq, ROSAcyc) facilitate future research in rose genetics and breeding.