SUMMARY Tomato ( Solanum lycopersicum L.) has become a popular model for genetic studies of fruit flavor in the last two decades. In this article we present a study of tomato fruit flavor, including an analysis of the genetic, metabolic and sensorial variation of a collection of contemporary commercial glasshouse tomato cultivars, followed by a validation of the associations found by quantitative trait locus (QTL) analysis of representative biparental segregating populations. This led to the identification of the major sensorial and chemical components determining fruit flavor variation and detection of the underlying QTLs. The high representation of QTL haplotypes in the breeders’ germplasm suggests that there is great potential for applying these QTLs in current breeding programs aimed at improving tomato flavor. A QTL on chromosome 4 was found to affect the levels of the phenylalanine‐derived volatiles (PHEVs) 2‐phenylethanol, phenylacetaldehyde and 1‐nitro‐2‐phenylethane. Fruits of near‐isogenic lines contrasting for this locus and in the composition of PHEVs significantly differed in the perception of fruity and rose‐hip‐like aroma. The PHEV locus was fine mapped, which allowed for the identification of FLORAL4 as a candidate gene for PHEV regulation. Using a gene‐editing‐based (CRISPR‐CAS9) reverse‐genetics approach, FLORAL4 was demonstrated to be the key factor in this QTL affecting PHEV accumulation in tomato fruit.

The damage caused by the parasitic root cyst nematode Globodera pallida is a major yield-limiting factor in potato cultivation . Breeding for resistance is facilitated by the PCR-based marker 'HC', which is diagnostic for an allele conferring high resistance against G. pallida pathotype Pa2/3 that has been introgressed from the wild potato species Solanum vernei into the Solanum tuberosum tetraploid breeding pool. The major quantitative trait locus (QTL) controlling this nematode resistance maps on potato chromosome V in a hot spot for resistance to various pathogens including nematodes and the oomycete Phytophthora infestans. An unstructured sample of 79 tetraploid, highly heterozygous varieties and breeding clones was selected based on presence (41 genotypes) or absence (38 genotypes) of the HC marker. Testing the clones for resistance to G. pallida conWrmed the diagnostic power of the HC marker. The 79 individuals were genotyped for 100 single nucleotide polymorphisms (SNPs) at 10 loci distributed over 38 cM on chromosome V. Forty-Wve SNPs at six loci spanning 2 cM in the interval between markers GP21-GP179 were associated with resistance to G. pallida. Based on linkage disequilibrium (LD) between SNP markers, six LD groups comprising between 2 and 18 SNPs were identiWed. The LD groups indicated the existence of multiple alleles at a single resistance locus or at several, physically linked resistance loci. LD group C comprising 18 SNPs corresponded to the 'HC' marker. LD group E included 16 SNPs and showed an association peak, which positioned one nematode resistance locus physically close to the R1 gene family.Communicated by J. E. Bradshaw. Electronic supplementary materialThe online version of this article

Modeling genotype-phenotype relationships is a central objective in plant genetics and breeding. Commonly, variations in phenotypic traits are modeled directly in relation to variations at the DNA level, regardless of intermediate levels of biological variation. Here we present an integrative method for the simultaneous modeling of a set of multilevel phenotypic responses to variations at the DNA level. More specifically, for ripe tomato fruits, we use Gaussian graphical models and causal inference techniques to learn the dependencies of 24 sensory traits on 29 metabolites and the dependencies of those sensory and metabolic traits on 21 QTLs. The inferred dependency network which, though not essentially representing biological pathways, suggests how the effects of allele substitutions propagate through multilevel phenotypes. Such simultaneous study of the underlying genetic architecture and multifactorial interactions is expected to enhance the prediction and manipulation of complex traits.

We summarize the concept of molecular diagnostic of complex traits related to pest and disease resistance and to tuber quality of potato, and describe recent achievements and perspectives. Many potato characteristics are controlled by multiple genetic and environmental factors. Knowing the genes and their allelic variants that underlay these characteristics allows developing molecular diagnostic tools to select for improved potato cultivars. Diagnostic DNA-based markers can be used to identify superior genotypes (precision breeding). Diagnostic markers can be identified by combining quantitative trait locus mapping, candidate gene mapping and association mapping using functional and positional candidate genes as markers. This approach was successfully used to identify loci, which contribute to the natural variation of important agronomic traits, including resistance against root cyst nematodes, late blight and wart disease and tuber quality (resistance to bruising and chip colour). In the future, whole genome association mapping based on single-nucleotide polymorphism genotyping methods in combination with the annotated potato genome sequence will allow identifying additional genes and gene variants controlling agronomic performance in potato. Prerequisites are accurate phenotyping under field conditions of advanced breeding materials, cost-effective and reliable genome-wide genotyping methods, and user-friendly software tools allowing to extract knowledge from massive quantities of data. This will further facilitate molecular diagnosis, selection and combination of superior alleles in potato-breeding programmes.