Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
| Autor: | Nese Sreeenivasulu, Markus Kuhlmann, Vito M. Butardo, Christianne Seiler |
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| Rok vydání: | 2020 |
| Předmět: |
Quality Control
General Immunology and Microbiology Abiotic stress General Chemical Engineering General Neuroscience Gene Expression Profiling Gene regulatory network food and beverages RNA Chromosome Mapping Computational Biology Germination Computational biology Biology Genome General Biochemistry Genetics and Molecular Biology Gene expression profiling Transcriptome Complementary DNA Gene expression Seeds Gene Regulatory Networks Edible Grain Oligonucleotide Array Sequence Analysis |
| Zdroj: | Journal of visualized experiments : JoVE. (159) |
| ISSN: | 1940-087X |
| Popis: | The characterization of gene expression is dependent on RNA quality. In germinating, developing and mature cereal seeds, the extraction of high-quality RNA is often hindered by high starch and sugar content. These compounds can reduce both the yield and the quality of the extracted total RNA. The deterioration in quantity and quality of total RNA can subsequently have a significant impact on the downstream transcriptomic analyses, which may not accurately reflect the spatial and/or temporal variation in the gene expression profile of the samples being tested. In this protocol, we describe an optimized method for extraction of total RNA with sufficient quantity and quality to be used for whole transcriptome analysis of cereal grains. The described method is suitable for several downstream applications used for transcriptomic profiling of developing, germinating, and mature cereal seeds. The method of transcriptome profiling using a microarray platform is shown. This method is specifically designed for gene expression profiling of cereals with described genome sequences. The detailed procedure from microarray handling to final quality control is described. This includes cDNA synthesis, cRNA labelling, microarray hybridization, slide scanning, feature extraction, and data quality validation. The data generated by this method can be used to characterize the transcriptome of cereals during germination, in various stages of grain development, or at different biotic or abiotic stress conditions. The results presented here exemplify high-quality transcriptome data amenable for downstream bioinformatics analyses, such as the determination of differentially expressed genes (DEGs), characterisation of gene regulatory networks, and conducting transcriptome-wide association study (TWAS). |
| Databáze: | OpenAIRE |
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