Expression of tomato reference genes using established primer sets: Stability across experimental set‐ups

Reliable reference genes are critical for relative quantification using quantitative real‐time PCR (qPCR). Ten tomato genes (Solanum lycopersicum) and their respective primer sets, which have been used over the last 6 years as references in expression studies, were evaluated for their performance using leaf tissue samples grown under semi‐controlled conditions and infected with grey mould (Botrytis cinerea) or late blight (Phytophthora infestans). The target genes coding for U6 snRNA‐associated Sm‐like protein LSm7, calcineurin B‐like protein and V‐type proton ATPase were the most stable expressed of all the genes tested in three experimental repetitions. Evaluation of candidate reference genes with geNorm and NormFinder softwares yielded the lowest mean values for their respective primer sets LSM7, SlCBL1 and SlATPase, suggesting stable expression. However, SlATPase primer set revealed a comparably high intra‐group variation and was thus not considered further. In follow‐up experiments with P. infestans, the geNorm and NormFinder values of primer sets LSM7 and SlCBL1 were even lower, indicating the stability of their expression also under these conditions. Primer efficiency differed by ‐18 to +5 percentage points from values presented in the literature. Our findings show that a reference primer set which delivers the best results in one system may be outperformed by another under different experimental conditions, thus recommending a reassessment of both expression stability and qPCR efficiency whenever the biological or technical experimental set‐up is changed. On the basis of our results, we recommend the use of LSM7 and SlCBL1 as reference primer sets for gene expression studies on plant tissue derived from open or semi‐controlled conditions.     

Accurate measurements of dynamics and reproducibility in small genetic networks

Quantification of gene expression has become a central tool for understanding genetic networks. In many systems, the only viable way to measure protein levels is by immunofluorescence, which is notorious for its limited accuracy. Using the early Drosophila embryo as an example, we show that careful identification and control of experimental error allows for highly accurate gene expression measurements. We generated antibodies in different host species, allowing for simultaneous staining of four Drosophila gap genes in individual embryos. Careful error analysis of hundreds of expression profiles reveals that less than ～20% of the observed embryo‐to‐embryo fluctuations stem from experimental error. These measurements make it possible to extract not only very accurate mean gene expression profiles but also their naturally occurring fluctuations of biological origin and corresponding cross‐correlations. We use this analysis to extract gap gene profile dynamics with ～1 min accuracy. The combination of these new measurements and analysis techniques reveals a twofold increase in profile reproducibility owing to a collective network dynamics that relays positional accuracy from the maternal gradients to the pair‐rule genes.     

Phylogenomic analysis of gene co‐expression networks reveals the evolution of functional modules

Molecular evolutionary studies correlate genomic and phylogenetic information with the emergence of new traits of organisms. These traits are, however, the consequence of dynamic gene networks composed of functional modules, which might not be captured by genomic analyses. Here, we established a method that combines large‐scale genomic and phylogenetic data with gene co‐expression networks to extensively study the evolutionary make‐up of modules in the moss Physcomitrella patens, and in the angiosperms Arabidopsis thaliana and Oryza sativa (rice). We first show that younger genes are less annotated than older genes. By mapping genomic data onto the co‐expression networks, we found that genes from the same evolutionary period tend to be connected, whereas old and young genes tend to be disconnected. Consequently, the analysis revealed modules that emerged at a specific time in plant evolution. To uncover the evolutionary relationships of the modules that are conserved across the plant kingdom, we added phylogenetic information that revealed duplication and speciation events on the module level. This combined analysis revealed an independent duplication of cell wall modules in bryophytes and angiosperms, suggesting a parallel evolution of cell wall pathways in land plants. We provide an online tool allowing plant researchers to perform these analyses at http://www.gene2function.de .     

Rotation gene set testing for longitudinal expression data

Gene set analysis methods are popular tools for identifying differentially expressed gene sets in microarray data. Most existing methods use a permutation test to assess significance for each gene set. The permutation test's assumption of exchangeable samples is often not satisfied for time‐series data and complex experimental designs, and in addition it requires a certain number of samples to compute p‐values accurately. The method presented here uses a rotation test rather than a permutation test to assess significance. The rotation test can compute accurate p‐values also for very small sample sizes. The method can handle complex designs and is particularly suited for longitudinal microarray data where the samples may have complex correlation structures. Dependencies between genes, modeled with the use of gene networks, are incorporated in the estimation of correlations between samples. In addition, the method can test for both gene sets that are differentially expressed and gene sets that show strong time trends. We show on simulated longitudinal data that the ability to identify important gene sets may be improved by taking the correlation structure between samples into account. Applied to real data, the method identifies both gene sets with constant expression and gene sets with strong time trends.     

Transient expression assays in grapevine: a step towards genetic improvement

In the past few years, the usefulness of transient expression assays has continuously increased for the characterization of unknown gene function and metabolic pathways. In grapevine (Vitis vinifera L.), one of the most economically important fruit crops in the world, recent systematic sequencing projects produced many gene data sets that require detailed analysis. Due to their rapid nature, transient expression assays are well suited for large‐scale genetic studies. Although genes and metabolic pathways of any species can be analysed by transient expression in model plants, a need for homologous systems has emerged to avoid the misinterpretation of results due to a foreign genetic background. Over the last 10 years, various protocols have thus been developed to apply this powerful technology to grapevine. Using cell suspension cultures, somatic embryos, leaves or whole plantlets, transient expression assays enabled the study of the function, regulation and subcellular localization of genes involved in specific metabolic pathways such as the biosynthesis of phenylpropanoids. Disease resistance genes that could be used for marker‐assisted selection in conventional breeding or for stable transformation of elite cultivars have also been characterized. Additionally, transient expression assays have proved useful for shaping new tools for grapevine genetic improvement: synthetic promoters, silencing constructs, minimal linear cassettes or viral vectors. This review provides an update on the different tools (DNA constructs, reporter genes, vectors) and methods (Agrobacterium‐mediated and direct gene transfer methods) available for transient gene expression in grapevine. The most representative results published thus far are then described.     

Development of iFOX‐hunting as a functional genomic tool and demonstration of its use to identify early senescence‐related genes in the polyploid Brassica napus

Functional genomic studies of many polyploid crops, including rapeseed (Brassica napus), are constrained by limited tool sets. Here we report development of a gain‐of‐function platform, termed ‘iFOX (inducible Full‐length cDNA OvereXpressor gene)‐Hunting’, for inducible expression of B. napus seed cDNAs in Arabidopsis. A Gateway‐compatible plant gene expression vector containing a methoxyfenozide‐inducible constitutive promoter for transgene expression was developed. This vector was used for cloning of random cDNAs from developing B. napus seeds and subsequent Agrobacterium‐mediated transformation of Arabidopsis. The inducible promoter of this vector enabled identification of genes upon induction that are otherwise lethal when constitutively overexpressed and to control developmental timing of transgene expression. Evaluation of a subset of the resulting ~6000 Arabidopsis transformants revealed a high percentage of lines with full‐length B. napus transgene insertions. Upon induction, numerous iFOX lines with visible phenotypes were identified, including one that displayed early leaf senescence. Phenotypic analysis of this line (rsl‐1327) after methoxyfenozide induction indicated high degree of leaf chlorosis. The integrated B. napuscDNA was identified as a homolog of an Arabidopsis acyl‐CoA binding protein (ACBP) gene designated BnACBP1‐like. The early senescence phenotype conferred by BnACBP1‐like was confirmed by constitutive expression of this gene in Arabidopsis and B. napus. Use of the inducible promoter in the iFOX line coupled with RNA‐Seq analyses allowed mechanistic clues and a working model for the phenotype associated with BnACBP1‐like expression. Our results demonstrate the utility of iFOX‐Hunting as a tool for gene discovery and functional characterization of Brassica napus genome.