Identification and validation of reference genes for RT-qPCR normalization in wheat meiosis.
José GarridoMiguel AguilarPilar PrietoPublished in: Scientific reports (2020)
Meiosis is a specialized type of cell division occurring in sexually reproducing organisms to generate haploid cells known as gametes. In flowering plants, male gametes are produced in anthers, being encased in pollen grains. Understanding the genetic regulation of meiosis key events such as chromosome recognition and pairing, synapsis and recombination, is needed to manipulate chromosome associations for breeding purposes, particularly in important cereal crops like wheat. Reverse transcription-quantitative PCR (RT-qPCR) is widely used to analyse gene expression and to validate the results obtained by other transcriptomic analyses, like RNA-seq. Selection and validation of appropriate reference genes for RT-qPCR normalization is essential to obtain reproducible and accurate expression data. In this work, twelve candidate reference genes were evaluated using the mainstream algorithms geNorm, Normfinder, BestKeeper and ΔCt, then ranked from most to least suitable for normalization with RefFinder. Different sets of reference genes were recommended to normalize gene expression data in anther meiosis of bread and durum wheat, their corresponding genotypes in the absence of the Ph1 locus and for comparative studies among wheat genotypes. Comparisons between meiotic (anthers) and somatic (leaves and roots) wheat tissues were also carried out. To the best of our knowledge, our study provides the first comprehensive list of reference genes for robust RT-qPCR normalization to study differentially expressed genes during male meiosis in wheat in a breeding framework.
Keyphrases
- gene expression
- genome wide
- bioinformatics analysis
- rna seq
- single cell
- genome wide identification
- dna methylation
- copy number
- machine learning
- healthcare
- poor prognosis
- computed tomography
- palliative care
- stem cells
- high resolution
- electronic health record
- big data
- genome wide analysis
- dna repair
- binding protein
- cell therapy
- cell death
- endoplasmic reticulum stress
- artificial intelligence