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Updated: Aug 29, 2025

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Protocol for affordable and efficient profiling of nascent RNAs in bread wheat using GRO-seq
Yan Chen1, Jiafu Zhu1, Yilin Xie2
1Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510006, China.
This study presents a cost-effective Global Run-On sequencing (GRO-seq) protocol by adding a ribosomal RNA (rRNA) removal step. This innovation significantly enhances data quality for transcriptional activity analysis, particularly in complex genomes like wheat.
Area of Science:
- Molecular Biology
- Genomics
- Transcriptomics
Background:
- Global Run-On sequencing (GRO-seq) is crucial for detecting transcriptional activity.
- High sequencing costs hinder the widespread adoption of GRO-seq.
- Existing GRO-seq protocols face challenges in data yield and affordability.
Purpose of the Study:
- To develop a more efficient and affordable GRO-seq protocol.
- To improve the yield of valid sequencing data.
- To enable detailed profiling of transcriptional activity, including enhancer transcription.
Main Methods:
- Incorporated a ribosomal RNA (rRNA) removal step into the GRO-seq protocol.
- Performed rRNA removal after nuclear RNA isolation and before nascent RNA immunoprecipitation.
- Applied the modified protocol to profile enhancer transcription in allohexaploid bread wheat.
Main Results:
- The modified GRO-seq protocol significantly reduces costs and increases efficiency.
- Achieved a 20-fold increase in the proportion of valid sequencing data.
- Successfully profiled enhancer transcription in allohexaploid bread wheat.
Conclusions:
- The optimized GRO-seq protocol overcomes cost barriers for widespread application.
- This method provides a powerful tool for studying transcriptional regulation in complex organisms.
- Enhanced data quality facilitates deeper insights into gene expression and regulatory elements.
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