Gene Expression Analysis by Quantitative Real-Time PCR for Floral Tissues.

Real-time, or quantitative, reverse transcription polymerase chain reaction (qRT-PCR) is a powerful method for rapid and reliable quantification of mRNA abundance. Although it has not featured prominently in flower development research in the past, the availability of novel techniques for the synchronized induction of flower development, or for the isolation of cell-specific mRNA populations, suggests that detailed quantitative analyses of gene expression over time and in specific tissues and cell types by qRT-PCR will become more widely used. In this chapter, we discuss specific considerations for studying gene expression by using qRT-PCR, such as the identification of suitable reference genes for the experimental set-up used. In addition, we provide protocols for performing qRT-PCR experiments in a multiwell plate format (with the LightCycler® 480 system, Roche) and with nanofluidic arrays (BioMark™ system, Fluidigm), which allow the automatic combination of sets of samples with sets of assays, and significantly reduce reaction volume and the number of liquid-handling steps performed during the experiment.

Multi-Omics Methods Applied to Flower Development.

Developmental processes in multicellular organisms depend on the proficiency of cells to orchestrate different gene expression programs. Over the past years, several studies of reproductive organ development have considered genomic analyses of transcription factors and global gene expression changes, modeling complex gene regulatory networks. Nevertheless, the dynamic view of developmental processes requires, as well, the study of the proteome in its expression, complexity, and relationship with the transcriptome. In this chapter, we describe a dual extraction method-for protein and RNA-for the characterization of genome expression at proteome level and its correlation to transcript expression data. We also present a shotgun proteomic procedure (LC-MS/MS) followed by a pipeline for the imputation of missing values in mass spectrometry results.

Peptidomics Methods Applied to the Study of Flower Development.

Understanding the global and dynamic nature of plant developmental processes requires not only the study of the transcriptome, but also of the proteome, including its largely uncharacterized peptidome fraction. Recent advances in proteomics and high-throughput analyses of translating RNAs (ribosome profiling) have begun to address this issue, evidencing the existence of novel, uncharacterized, and possibly functional peptides. To validate the accumulation in tissues of sORF-encoded polypeptides (SEPs), the basic setup of proteomic analyses (i.e., LC-MS/MS) can be followed. However, the detection of peptides that are small (up to ~100 aa, 6-7 kDa) and novel (i.e., not annotated in reference databases) presents specific challenges that need to be addressed both experimentally and with computational biology resources. Several methods have been developed in recent years to isolate and identify peptides from plant tissues. In this chapter, we outline two different peptide extraction protocols and the subsequent peptide identification by mass spectrometry using the database search or the de novo identification methods.