Disentangling hexaploid genetics : towards DNA-informed breeding for postharvest performance in chrysanthemum

Abstract

DNA-informed selection can strongly improve the process of plant breeding. It requires the detection of DNA polymorphisms, calculation of genetic linkage, access to reliable phenotypes and methods to detect genetic loci associated with phenotypic traits of interest. Cultivated chrysanthemum is an outcrossing hexaploid with an unknown mode of inheritance. This complicates the development of resources and methods that enable the detection of trait loci. Postharvest performance is an essential trait in chrysanthemum, but is difficult to measure. This makes it an interesting but challenging trait to phenotype and detect associated genetic loci. In this thesis I describe the development of resources and methods to enable phenotyping for postharvest performance, genetic linkage map construction and detection of quantitative trait loci in hexaploid chrysanthemum. Postharvest performance is a complicated trait because it is related to many different disorders that reduce quality. One of these disorders in chrysanthemum is disk floret degreening, which occurs after long storage. In chapter 2, we show that degreening can be prevented by feeding the flower heads with sucrose, suggesting carbohydrate starvation plays a role in the degreening process. To investigate the response to carbohydrate starvation of genotypes with different sensitivity to disk floret degreening, we investigated the metabolome of sugar-fed and carbohydrate-starved disk florets by 1H-NMR and HPAEC. We show that the metabolome is severely altered at carbohydrate starvation. In general, starvation results in an upregulation of amino acid and secondary metabolism. Underlying causes of genotypic differences explaining variation in disk floret degreening in the three investigated genotypes remained to be elucidated, but roles of regulation of respiration rate and camphor metabolism were posed as possible candidates. In chapter 3, disk floret degreening was found to be the most important postharvest disorder after 3 weeks of storage among 44 white chrysanthemum cultivars. To investigate the inheritance of disk floret degreening, we crossed two genotypes with opposite phenotypic values of both disk floret degreening and carbohydrate content to obtain a population segregating for disk floret degreening. To phenotype the cultivar panel and the bi-parental population precisely and in a high throughput manner, we developed a method that quantified colour of detached capitula over time. This method was validated with visual observations of disk floret degreening during vase life tests. In a subset of the bi-parental population we measured carbohydrate content of the disk florets at harvest. The amount of total carbohydrates co-segregated with sensitivity to degreening, which shows that the difference in disk floret degreening sensitivity between the parents could be explained by their difference in carbohydrate content. However, the correlation was rather weak, indicating carbohydrate content is not the only factor playing a role. In order to develop resources for DNA-informed breeding, one needs to be able to characterize DNA polymorphisms. In chapter 4, we describe the development of a genotyping array containing 183,000 single nucleotide polymorphisms (SNPs). These SNPs were acquired by sequencing the transcriptome of 13 chrysanthemum cultivars. By comparing the genomic dosage based on the SNP assay and the dosage as estimated by the read depth from the transcriptome sequencing data, we show that alleles are expressed conform the genomic dosage, which contradicts to what is often found in disomic polyploids. In line with this finding, we conclusively show that cultivated chrysanthemum exhibits genome-wide hexasomic inheritance, based on the segregation ratios of large numbers of different types of markers in two different populations. Tools for genetic analysis in diploids are widely available, but these have limited use for polyploids. In chapter 5, we present a modular software package that enables genetic linkage map construction in tetraploids and hexaploids. Because of the modularity, functionality for other ploidy levels can be easily added. The software is written in the programming language R and we named it polymapR. It can generate genetic linkage maps from marker dosage scores in an F1 population, while taking the following steps: data inspection and filtering, linkage analysis, linkage group assignment and marker ordering. It is the first software package that can handle polysomic hexaploid and partial polysomic tetraploid data, and has advantages over other polyploid mapping software because of its scalability and cross-platform applicability. With the marker dosage scores of the bi-parental F1 population from the genotyping array and the developed methods to perform linkage analysis we constructed an integrated genetic linkage map for the hexaploid bi-parental population described in chapter 3 and 4. We describe this process in chapter 6. With this integrated linkage map, we reconstructed the inheritance of parental haplotypes for each individual, and expressed this as identity-by-descent (IBD) probabilities. The phenotypic data on disk floret degreening sensitivity that was acquired as described in chapter 3, was used in addition to three other traits to detect quantitative trait loci (QTL). These QTL were detected based on the IBD probabilities of 1 centiMorgan intervals of each parental homologue. This enabled us to study genetic architecture by estimating the effects of each separate allele within a QTL on the trait. We showed that for many QTL the trait was affected by more than two alleles. In chapter 7, the findings in this thesis are discussed in the context of breeding for heterogeneous traits, the implications of the mode of inheritance for breeding and the advantages and disadvantages of polyploidy in crop breeding. In conclusion, this thesis provides in general a significant step for DNA-informed breeding in polysomic hexaploids, and for postharvest performance in chrysanthemum in particular.</p