FitTetra 2.0-improved genotype calling for tetraploids with multiple population and parental data support

BackgroundGenetic studies in tetraploids are lagging behind in comparison with studies of diploids as the complex genetics of tetraploids require much more elaborated computational methodologies. Recent advancements in development of molecular techniques and computational tools facilitate new methods for automated, high-throughput genotype calling in tetraploid species. We report on the upgrade of the widely-used fitTetra software aiming to improve its accuracy, which to date is hampered by technical artefacts in the data.ResultsOur upgrade of the fitTetra package is designed for a more accurate modelling of complex collections of samples. The package fits a mixture model where some parameters of the model are estimated separately for each sub-collection. When a full-sib family is analyzed, we use parental genotypes to predict the expected segregation in terms of allele dosages in the offspring. More accurate modelling and use of parental data increases the accuracy of dosage calling. We tested the package on data obtained with an Affymetrix Axiom 60k array and compared its performance with the original version and the recently published ClusterCall tool, showing that at least 20% more SNPs could be called with our updated.ConclusionOur updated software package shows clearly improved performance in genotype calling accuracy. Estimation of mixing proportions of the underlying dosage distributions is separated for full-sib families (where mixture proportions can be estimated from the parental dosages and inheritance model) and unstructured populations (where they are based on the assumption of Hardy-Weinberg equilibrium). Additionally, as the distributions of signal ratios of the dosage classes can be assumed to be the same for all populations, including parental data for some subpopulations helps to improve fitting other populations as well. The R package fitTetra 2.0 is freely available under the GNU Public License as Additional file with this article.</p

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

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

Towards marker assisted breeding in garden roses: from marker development to QTL detection

Over the last few decades the rose market in Eastern Europe showed a steady growth, which indicates that there is increasing demand for new cultivars that are adapted to the climate as well as to the customs and beauty criterion of that region. One of the possibilities to speed up breeding is to implement marker assisted selection (MAS). Implementation of MAS requires a specific infrastructure (molecular markers, knowledge on genetics of important traits, genetic maps) which is not yet available for tetraploid roses. In this thesis I developed some of the prerequisites for MAS in roses and discuss when and how MAS could have a positive effect on accelerating breeding and/or reducing the costs of the breeding process. The first step in understanding the structure of the genepool of garden roses was to evaluate the relatedness among available cultivars. For the first time genetic diversity among modern garden rose cultivars was evaluated (Chapter 2) using a set of 24 microsatellite markers covering most chromosomes. A total of 518 different alleles were obtained in a set of 138 rose cultivars. Genetic differentiation among types of garden roses (Fst=0.022) was four times that found among cut roses, and similar in magnitude to the differentiation among breeders, due to the fact that horticultural groups and breeders overlap largely in classification. In terms of genetic diversity cut roses can be considered as a subgroup of the garden roses. Winter hardy Canadian garden rose cultivars (Explorer roses) showed the least similarities to European roses, and introgression from wild species for winter hardiness was clearly visible. Roses of two breeding programmes (Harkness and Olesen) shared a similar genepool. Comparison of the differentiation among linkage groups indicated that linkage group 5 is potentially a region containing important QTLs for winter hardiness. Linkage group 6 contains the largest amount of genetic diversity, while linkage group 2 is the most differentiated among types of garden roses. Garden roses, as well as many other important crops (wheat, potato, strawberry, etc.) are polyploid. Genetic analyses of polyploids is complex as the same locus is present on multiple homologous chromosomes. SSR markers are suitable for mapping in segregating populations of polyploids as they are multi-allelic, making it possible to detect different alleles of the same locus on all homologous chromosomes. If a SSR marker gives fewer alleles than the ploidy level, quantification of allele dosages increases the information content. In Chapter 3 I showed the power of this approach. Alleles were scored quantitatively using the area under the peaks in ABI electropherograms, and allele dosages were inferred based on the ratios between the peak areas for two alleles in reference cases in which these two alleles occurred together. We resolved the full progeny genotypes, generated more data and mapped markers more accurately, including markers with “null” alleles. Even though SSR markers are one of the most appropriate marker systems for genetic studies in polyploids still few hurdles complicate (reduce) their implementation. The first major hurdle in developing microsatellite markers, the cloning step, has been overcome by next generation sequencing techniques. The second hurdle is the testing step to differentiate polymorphic from non-polymorphic loci. The third hurdle, somewhat hidden, is that only those polymorphic markers that detect a large effective number of alleles in the germplasm to be studied, are sufficiently informative to be deployed in multiple studies. Both selection steps are laborious and still done manually. In Chapter 4 I present a strategy in which we first screen sequence reads from multiple genotypes for repeats that show the most variation in length, and only these are subsequently developed into markers. We validated our strategy in tetraploid garden rose using Illumina paired-end transcriptome sequences of 11 roses. Out of 48 tested two markers did not amplify but all others were polymorphic. Ten loci amplified more than one locus, indicating duplicated genes or gene families. Completely avoiding this will be difficult, as the range of numbers of predicted alleles of highly polymorphic single- and multi-locus markers largely overlapped. Of the remainder, half were duplicates, indicating the difficulty of correctly filtering short sequence reads containing repeat sequences. The remaining 18 markers were all highly polymorphic, amplifying between 6 and 20 alleles in the 11 tetraploid garden roses. This strategy therefore represents a major step forward in the development of highly polymorphic microsatellite markers. Despite that garden roses are economically very important ornamentals, breeding is still mostly conventional, mainly due to tetraploidy and the lack of genetic maps and knowledge about the genetic base of important traits. Furthermore, crosses with unintended parents occur regularly and detection of these is not always straightforward, especially when genetically related varieties are used. Moreover, in polyploids detection of off-type offspring often relies on detecting differences in allele dosage rather than the presence of new alleles. In Chapter 5 I applied the WagRhSNP Axiom rose SNP array to generate 10,000s of SNPs for parentage analysis and to generate a dense genetic map in tetraploid rose. I described a method to separate progeny into putative populations which share parents, even if one of the parents is unknown, using PCO analysis and sets of markers for which allele dosages are incompatible. Subsequently, dense SNP maps were generated for a biparental and a self-pollinated mapping population with one parent in common. I confirmed a tetrasomic mode of inheritance for these crosses and created a starting point for implementation of marker-assisted breeding in garden roses by QTL analysis for important morphological traits (recurrent blooming and prickle shape). Winter hardiness is a complex trait and one of the most important limiting factors for garden rose growth and distribution in areas characterized by a continental climate. In Chapter 6 research was undertaken to determine the genetic regions underlying winter hardiness of garden roses, and to generate markers linked to them. For this purpose we exposed two segregating populations, RNDxRND and RNDxHP, to temperatures below -15C in a cold chamber and in the field in Serbia. The frost damage in the hardened plants was estimated directly at the phenotypic level (proportion of dieback) and at the non-visible physiological level indirectly (through the potential for meristem production in spring; regrowth). For winter hardiness we detected two tentative QTLs in the RNDxRND population and two tentative QTLs in the RNDxHP population, of which one was the same in both populations. The ability of plants to regrow in spring was associated to genomic regions on three linkage groups of the RNDxRND population, and on two different linkage groups in the RNDxHP population. A comparison of the ability for regrowth and level of damage caused by low temperature revealed that these two traits are inherited independently and that the final cold tolerance depends on the plant’s ability to withstand low temperature and to regrow fast in spring. In résumé, this thesis resulted in the development of basic tools (a fast strategy for polymorphic SSR marker development), basic methods/concepts for genetic analyses in polyploids (quantification of SSR allele dosage, distinguishing outliers from population in polyploid crops, dense SNP map generation and QTL study in tetraploids), and knowledge on genetics of important traits in rose (relatedness among modern garden roses (genetic diversity approach), mode of inheritance, occurrence of selfing, QTLs for morphological traits (recurrent blooming and prickle shape) and dissection of winter hardiness (level of damage caused by low temperature and regrowth)). Additionally, potential use of markers in every phase of rose breeding was discussed (Chapter 7). All these aspects contribute to a solid basis for marker assisted breeding in (garden) rose. </p

Additional file 4: of FitTetra 2.0 - improved genotype calling for tetraploids with multiple population and parental data support

An R script containing all the code needed to run comparison between ClusterCall and fitTetra 2.0 on the dataset attached to the ClusterCall manuscript. (R 6 kb

Additional file 2: of FitTetra 2.0 - improved genotype calling for tetraploids with multiple population and parental data support

A zip archive containing all the data and code needed to run the comparisons. (ZIP 33420 kb

Additional file 1: of FitTetra 2.0 â improved genotype calling for tetraploids with multiple population and parental data support

A tar archive containing fitTetra 2.0 package. (GZ 46494 kb