SUMMARYOver 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.

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.

These authors contributed equally to this work. SUMMARYThe 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.

27The temporal control or timing of the life cycle of annual plants is presumed to provide 28 adaptive strategies to escape harsh environments for survival and reproduction. This is 29 mainly determined by the timing of germination, which is controlled by the level of seed

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.