Leo A. J. Willems

Identification of Reference Genes for RT–qPCR Expression Analysis in Arabidopsis and Tomato Seeds

Quantifying gene expression levels is an important research tool to understand biological systems. Reverse transcription-quantitative real-time PCR (RT-qPCR) is the preferred method for targeted gene expression measurements because of its sensitivity and reproducibility. However, normalization, necessary to correct for sample input and reverse transcriptase efficiency, is a crucial step to obtain reliable RT-qPCR results. Stably expressed genes (i.e. genes whose expression is not affected by the treatment or developmental stage under study) are indispensable for accurate normalization of RT-qPCR experiments. Lack of accurate normalization could affect the results and may lead to false conclusions. Since transcriptomes of seeds are different from other plant tissues, we aimed to identify reference genes specifically for RT-qPCR analyses in seeds of two important seed model species, i.e. Arabidopsis and tomato. We mined Arabidopsis seed microarray data to identify stably expressed genes and analyzed these together with putative reference genes from other sources. In total, the expression stability of 24 putative reference genes was validated by RT-qPCR in Arabidopsis seed samples. For tomato, we lacked transcriptome data sets of seeds and therefore we tested the tomato homologs of the reference genes found for Arabidopsis seeds. In conclusion, we identified 14 Arabidopsis and nine tomato reference genes. This provides a valuable resource for accurate normalization of gene expression experiments in seed research for two important seed model species.

GERMINATOR: a software package for high-throughput scoring and curve fitting of Arabidopsis seed germination

Over the past few decades seed physiology research has contributed to many important scientific discoveries and has provided valuable tools for the production of high quality seeds. An important instrument for this type of research is the accurate quantification of germination; however gathering cumulative germination data is a very laborious task that is often prohibitive to the execution of large experiments. In this paper we present the germinator package: a simple, highly cost-efficient and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The germinator package contains three modules: (i) design of experimental setup with various options to replicate and randomize samples; (ii) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (iii) curve fitting of cumulative germination data and the extraction, recap and visualization of the various germination parameters. The curve-fitting module enables analysis of general cumulative germination data and can be used for all plant species. We show that the automatic scoring system works for Arabidopsis thaliana and Brassica spp. seeds, but is likely to be applicable to other species, as well. In this paper we show the accuracy, reproducibility and flexibility of the germinator package. We have successfully applied it to evaluate natural variation for salt tolerance in a large population of recombinant inbred lines and were able to identify several quantitative trait loci for salt tolerance. Germinator is a low-cost package that allows the monitoring of several thousands of germination tests, several times a day by a single person.

Visualizing the Genetic Landscape of Arabidopsis Seed Performance

Perfect timing of germination is required to encounter optimal conditions for plant survival and is the result of a complex interaction between molecular processes, seed characteristics, and environmental cues. To detangle these processes, we made use of natural genetic variation present in an Arabidopsis (Arabidopsis thaliana) Bayreuth × Shahdara recombinant inbred line population. For a detailed analysis of the germination response, we characterized rate, uniformity, and maximum germination and discuss the added value of such precise measurements. The effects of after-ripening, stratification, and controlled deterioration as well as the effects of salt, mannitol, heat, cold, and abscisic acid (ABA) with and without cold stratification were analyzed for these germination characteristics. Seed morphology (size and length) of both dry and imbibed seeds was quantified by using image analysis. For the overwhelming amount of data produced in this study, we developed new approaches to perform and visualize high-throughput quantitative trait locus (QTL) analysis. We show correlation of trait data, (shared) QTL positions, and epistatic interactions. The detection of similar loci for different stresses indicates that, often, the molecular processes regulating environmental responses converge into similar pathways. Seven major QTL hotspots were confirmed using a heterogeneous inbred family approach. QTLs colocating with previously reported QTLs and well-characterized mutants are discussed. A new connection between dormancy, ABA, and a cripple mucilage formation due to a naturally occurring mutation in the MUCILAGE-MODIFIED2 gene is proposed, and this is an interesting lead for further research on the regulatory role of ABA in mucilage production and its multiple effects on germination parameters.

Identifying genotype-by-environment interactions in the metabolism of germinating Arabidopsis seeds using Generalized Genetical Genomics

A novel genetical genomics analysis of metabolites in four developmental stages of Arabidopsis germination unravels both genetic and genetic × environment loci controlling these metabolites. A complex phenotype such as seed germination is the result of several genetic and environmental cues and requires the concerted action of many genes. The use of well-structured recombinant inbred lines in combination with “omics” analysis can help to disentangle the genetic basis of such quantitative traits. This so-called genetical genomics approach can effectively capture both genetic and epistatic interactions. However, to understand how the environment interacts with genomic-encoded information, a better understanding of the perception and processing of environmental signals is needed. In a classical genetical genomics setup, this requires replication of the whole experiment in different environmental conditions. A novel generalized setup overcomes this limitation and includes environmental perturbation within a single experimental design. We developed a dedicated quantitative trait loci mapping procedure to implement this approach and used existing phenotypical data to demonstrate its power. In addition, we studied the genetic regulation of primary metabolism in dry and imbibed Arabidopsis (Arabidopsis thaliana) seeds. In the metabolome, many changes were observed that were under both environmental and genetic controls and their interaction. This concept offers unique reduction of experimental load with minimal compromise of statistical power and is of great potential in the field of systems genetics, which requires a broad understanding of both plasticity and dynamic regulation.

The Arabidopsis DELAY OF GERMINATION 1 gene affects ABSCISIC ACID INSENSITIVE 5 (ABI5) expression and genetically interacts with ABI3 during Arabidopsis seed development

The seed expressed gene DELAY OF GERMINATION (DOG) 1 is absolutely required for the induction of dormancy. Next to a non-dormant phenotype, the dog1-1 mutant is also characterized by a reduced seed longevity suggesting that DOG1 may affect additional seed processes as well. This aspect however, has been hardly studied and is poorly understood. To uncover additional roles of DOG1 in seeds we performed a detailed analysis of the dog1 mutant using both transcriptomics and metabolomics to investigate the molecular consequences of a dysfunctional DOG1 gene. Further, we used a genetic approach taking advantage of the weak aba insensitive (abi) 3-1 allele as a sensitized genetic background in a cross with dog1-1. DOG1 affects the expression of hundreds of genes including LATE EMBRYOGENESIS ABUNDANT and HEAT SHOCK PROTEIN genes which are affected by DOG1 partly via control of ABI5 expression. Furthermore, the content of a subset of primary metabolites, which normally accumulate during seed maturation, was found to be affected in the dog1-1 mutant. Surprisingly, the abi3-1 dog1-1 double mutant produced green seeds which are highly ABA insensitive, phenocopying severe abi3 mutants, indicating that dog1-1 acts as an enhancer of the weak abi3-1 allele and thus revealing a genetic interaction between both genes. Analysis of the dog1 and dog1 abi3 mutants revealed additional seed phenotypes and therefore we hypothesize that DOG1 function is not limited to dormancy but that it is required for multiple aspects of seed maturation, in part by interfering with ABA signalling components.

Exploring the Natural Variation for Seedling Traits and Their Link with Seed Dimensions in Tomato

The success of germination, growth and final yield of every crop depends to a large extent on the quality of the seeds used to grow the crop. Seed quality is defined as the viability and vigor attribute of a seed that enables the emergence and establishment of normal seedlings under a wide range of environments. We attempt to dissect the mechanisms involved in the acquisition of seed quality, through a combined approach of physiology and genetics. To achieve this goal we explored the genetic variation found in a RIL population of Solanum lycopersicum (cv. Moneymaker) x Solanum pimpinellifolium through extensive phenotyping of seed and seedling traits under both normal and nutrient stress conditions and root system architecture (RSA) traits under optimal conditions. We have identified 62 major QTLs on 21 different positions for seed, seedling and RSA traits in this population. We identified QTLs that were common across both conditions, as well as specific to stress conditions. Most of the QTLs identified for seedling traits co-located with seed size and seed weight QTLs and the positive alleles were mostly contributed by the S. lycopersicum parent. Co-location of QTLs for different traits might suggest that the same locus has pleiotropic effects on multiple traits due to a common mechanistic basis. We show that seed weight has a strong effect on seedling vigor and these results are of great importance for the isolation of the corresponding genes and elucidation of the underlying mechanisms.

Altitudinal and climatic associations of seed dormancy and flowering traits evidence adaptation of annual life cycle timing in Arabidopsis thaliana.

The temporal control or timing of the life cycle of annual plants is presumed to provide adaptive strategies to escape harsh environments for survival and reproduction. This is mainly determined by the timing of germination, which is controlled by the level of seed dormancy, and of flowering initiation. However, the environmental factors driving the evolution of plant life cycles remain largely unknown. To address this question we have analysed nine quantitative life history traits, in a native regional collection of 300 wild accessions of Arabidopsis thaliana. Seed dormancy and flowering time were negatively correlated, indicating that these traits have coevolved. In addition, environmental-phenotypic analyses detected strong altitudinal and climatic clines for most life history traits. Overall, accessions showing life cycles with early flowering, small seeds, high seed dormancy and slow germination rate were associated with locations exposed to high temperature, low summer precipitation and high radiation. Furthermore, we analysed the expression level of the positive regulator of seed dormancy DELAY OF GERMINATION 1 (DOG1), finding similar but weaker altitudinal and climatic patterns than seed dormancy. Therefore, DOG1 regulatory mutations are likely to provide a quantitative molecular mechanism for the adaptation of A. thaliana life cycle to altitude and climate.

Complex genetics controls natural variation among seed quality phenotypes in a recombinant inbred population of an interspecific cross between Solanum lycopersicum × Solanum pimpinellifolium

Seed quality in tomato is associated with many complex physiological and genetic traits. While plant processes are frequently controlled by the action of small- to large-effect genes that follow classic Mendelian inheritance, our study suggests that seed quality is primarily quantitative and genetically complex. Using a recombinant inbred line population of Solanum lycopersicum × Solanum pimpinellifolium, we identified quantitative trait loci (QTLs) influencing seed quality phenotypes under non-stress, as well as salt, osmotic, cold, high-temperature and oxidative stress conditions. In total, 42 seed quality traits were analysed and 120 QTLs were identified for germination traits under different conditions. Significant phenotypic correlations were observed between germination traits under optimal conditions, as well as under different stress conditions. In conclusion, one or more QTLs were identified for each trait with some of these QTLs co-locating. Co-location of QTLs for different traits can be an indication that a locus has pleiotropic effects on multiple traits due to a common mechanistic basis. However, several QTLs also dissected seed quality in its separate components, suggesting different physiological mechanisms and signalling pathways for different seed quality attributes.

Galactinol as marker for seed longevity

Reduced seed longevity or storability is a major problem in seed storage and contributes to increased costs in crop production. Here we investigated whether seed galactinol contents could be predictive for seed storability behavior in Arabidopsis, cabbage and tomato. The analyses revealed a positive correlation between galactinol content and seed longevity in the three species tested, which indicates that this correlation is conserved in the Brassicaceae and beyond. Quantitative trait loci (QTL) mapping in tomato revealed a co-locating QTL for galactinol content and seed longevity on chromosome 2. A candidate for this QTL is the GALACTINOL SYNTHASE gene (Solyc02g084980.2.1) that is located in the QTL interval. GALACTINOL SYNTHASE is a key enzyme of the raffinose family oligosaccharide (RFO) pathway. To investigate the role of enzymes in the RFO pathway in more detail, we applied a reverse genetics approach using T-DNA knock-out lines in genes encoding enzymes of this pathway (GALACTINOL SYNTHASE 1, GALACTINOL SYNTHASE 2, RAFFINOSE SYNTHASE, STACHYOSE SYNTHASE and ALPHA-GALACTOSIDASE) and overexpressors of the cucumber GALACTINOL SYNTHASE 2 gene in Arabidopsis. The galactinol synthase 2 mutant and the galactinol synthase 1 galactinol synthase 2 double mutant contained the lowest seed galactinol content which coincided with lower seed longevity. These results show that galactinol content of mature dry seed can be used as a biomarker for seed longevity in Brassicaceae and tomato.

Effects of Parental Temperature and Nitrate on Seed Performance are Reflected by Partly Overlapping Genetic and Metabolic Pathways

Seed performance is affected by the seed maturation environment, and previously we have shown that temperature, nitrate and light intensity were the most influential environmental factors affecting seed performance. Seeds developed in these environments were selected to assess the underlying metabolic pathways, using a combination of transcriptomics and metabolomics. These analyses revealed that the effects of the parental temperature and nitrate environments were reflected by partly overlapping genetic and metabolic networks, as indicated by similar changes in the expression levels of metabolites and transcripts. Nitrogen metabolism-related metabolites (asparagine, γ-aminobutyric acid and allantoin) were significantly decreased in both low temperature (15 °C) and low nitrate (N0) maturation environments. Correspondingly, nitrogen metabolism genes (ALLANTOINASE, NITRATE REDUCTASE 1, NITRITE REDUCTASE 1 and NITRILASE 4) were differentially regulated in the low temperature and nitrate maturation environments, as compared with control conditions. High light intensity during seed maturation increased galactinol content, and displayed a high correlation with seed longevity. Low light had a genotype-specific effect on cell surface-encoding genes in the DELAY OF GERMINATION 6-near isogenic line (NILDOG6). Overall, the integration of phenotypes, metabolites and transcripts led to new insights into the regulation of seed performance.