A Guideline to Family-Wide Comparative State-of-the-Art Quantitative RT-PCR Analysis Exemplified with a Brassicaceae Cross-Species Seed Germination Case Study  

Abstract

Comparative biology includes the comparison of transcriptome and quantitative real-time RT-PCR (qRT-PCR) data sets in a range of species to detect evolutionarily conserved and divergent processes. Transcript abundance analysis of target genes by qRT-PCR requires a highly accurate and robust workflow. This includes reference genes with high expression stability (i.e., low intersample transcript abundance variation) for correct target gene normalization. Cross-species qRT-PCR for proper comparative transcript quantification requires reference genes suitable for different species. We addressed this issue using tissue-specific transcriptome data sets of germinating Lepidium sativum seeds to identify new candidate reference genes. We investigated their expression stability in germinating seeds of L. sativum and Arabidopsis thaliana by qRT-PCR, combined with in silico analysis of Arabidopsis and Brassica napus microarray data sets. This revealed that reference gene expression stability is higher for a given developmental process between distinct species than for distinct developmental processes within a given single species. The identified superior cross-species reference genes may be used for family-wide comparative qRT-PCR analysis of Brassicaceae seed germination. Furthermore, using germinating seeds, we exemplify optimization of the qRT-PCR workflow for challenging tissues regarding RNA quality, transcript stability, and tissue abundance. Our work therefore can serve as a guideline for moving beyond Arabidopsis by establishing high-quality cross-species qRT-PCR.

Spatiotemporal Seed Development Analysis Provides Insight into Primary Dormancy Induction and Evolution of theLepidium DELAY OF GERMINATION1Genes

“…Comparative work with Lepidium spp. and Arabidopsis seeds (Linkies et al, 2009;Graeber et al, 2010Graeber et al, , 2011Voegele et al, 2011), fruits Mühlhausen et al, 2010), and flowers (Lee et al, 2002) emphasizes that the genus Lepidium provides a phylogenetically and environmentally defined framework highly suited for evolutionary and developmental research on seed/ fruit-related traits. DOG1 gene homologs are present in Lepidium spp.…”

“…DOG1 fragments were PCR amplified from genomic DNA or RNA extracted from seeds. RNA was extracted as described by Graeber et al (2011) and subsequently cDNA synthesized as described by Graeber et al (2010), but using random hexamers (Fermentas). DNA extraction from seeds using commercial extraction kits can be difficult due to clogging of membranes by seed storage compounds and mucilage.…”

“…Intercontinental dispersal of mucilaginous seeds adhering to birds led to a relatively rapid worldwide distribution, forming the basis for adaptations to very different habitats (Mummenhoff et al, 2004;Dierschke et al, 2009). Comparative work with L. sativum and Arabidopsis seeds (Linkies et al, 2009;Graeber et al, 2010Graeber et al, , 2011Voegele et al, 2011) and fruits Mühlhausen et al, 2010) highlights the suitability of the genus Lepidium for cross-species research on diverse developmental aspects. Here, we exploit the experimental advantage of the highly structured Lepidium papillosum infructescence (i.e.…”

ArabidopsisPaired Amphipathic Helix Proteins SNL1 and SNL2 Redundantly Regulate Primary Seed Dormancy via Abscisic Acid–Ethylene Antagonism Mediated by Histone Deacetylation

“…qRT-PCR was performed using the SYBR Premix Ex Taq (TaKaRa). The expression value for each gene was quantified using a standard curve with a serial dilution of plasmid of known concentration, and they were normalized to the value of ACTIN8 and At2g28390 (Chua et al, 2005;Czechowski et al, 2005;Graeber et al, 2011). At least three biological replicates were analyzed.…”

Demethylesterification of Cell Wall Pectins in Arabidopsis Plays a Role in Seed Germination

“…The efficiency (E) of the primer pairs was calculated as the average of the efficiencies of the individual reactions by using raw fluorescence data with the publicly available PCR Miner tool (http://www.miner.ewindup.info/ version2; Zhao and Fernald, 2005). The efficiency was then used to calculate transcript abundance for the individual samples as (1 + E)^(2CT) as described by Graeber et al (2011). No-template controls were included for each primer pair to check for contamination of the reaction solutions, and noreverse transcription controls were used to check for genomic DNA contamination in the RNA.…”