Haplotype-resolved assembly of a tetraploid potato genome using long reads and low-depth offspring data.

Potato is one of the world's major staple crops, and like many important crop plants, it has a polyploid genome. Polyploid haplotype assembly poses a major computational challenge. We introduce a novel strategy for the assembly of polyploid genomes and present an assembly of the autotetraploid potato cultivar Altus. Our method uses low-depth sequencing data from an offspring population to achieve chromosomal clustering and haplotype phasing on the assembly graph. Our approach generates high-quality assemblies of individual chromosomes with haplotype-specific sequence resolution of whole chromosome arms and can be applied in common breeding scenarios where collections of offspring are available.

The use of a candidate gene approach to study Botrytis cinerea resistance in Gerbera hybrida.

Candidate genes (CG) for Botrytis cinerea resistance described in literature were mapped on gerbera linkage maps for which several QTL for Botrytis resistance had been found previously using a rapid, low-cost platform for SNP genotyping. In total, 29 CGs were mapped in either of two mapping populations. Four CGs were mapped within the previous identified QTL intervals and three co-localized with QTL. Two of these CGs for resistance against B. cinerea, PG1 (polygalacturonase gene) and sit (sitiens, ABA-aldehyde oxidase gene) that mapped in QTL regions for the ray floret disease resistance test were studied in detail. Virus-induced gene silencing (VIGS) was used for gene function analysis to determine the CGs' role in gerbera resistance to Botrytis. Ray florets, of which the CGs were silenced, showed a significantly delayed growth of lesions upon Botrytis infection compared to controls. Combining QTL analysis, candidate gene mapping and VIGS showed to be an useful combination to identify possible causal genes and for understanding the molecular mechanisms of Botrytis resistance in gerbera. The two genes seem to act as partial S-genes and are likely among the determining genes leading to the variation observed for B. cinerea resistance in gerbera.

Smooth Descent: A ploidy-aware algorithm to improve linkage mapping in the presence of genotyping errors.

Linkage mapping is an approach to order markers based on recombination events. Mapping algorithms cannot easily handle genotyping errors, which are common in high-throughput genotyping data. To solve this issue, strategies have been developed, aimed mostly at identifying and eliminating these errors. One such strategy is SMOOTH, an iterative algorithm to detect genotyping errors. Unlike other approaches, SMOOTH can also be used to impute the most probable alternative genotypes, but its application is limited to diploid species and to markers heterozygous in only one of the parents. In this study we adapted SMOOTH to expand its use to any marker type and to autopolyploids with the use of identity-by-descent probabilities, naming the updated algorithm Smooth Descent (SD). We applied SD to real and simulated data, showing that in the presence of genotyping errors this method produces better genetic maps in terms of marker order and map length. SD is particularly useful for error rates between 5% and 20% and when error rates are not homogeneous among markers or individuals. With a starting error rate of 10%, SD reduced it to ∼5% in diploids, ∼7% in tetraploids and ∼8.5% in hexaploids. Conversely, the correlation between true and estimated genetic maps increased by 0.03 in tetraploids and by 0.2 in hexaploids, while worsening slightly in diploids (∼0.0011). We also show that the combination of genotype curation and map re-estimation allowed us to obtain better genetic maps while correcting wrong genotypes. We have implemented this algorithm in the R package Smooth Descent.

Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit.

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.

Genetic polyploid phasing from low-depth progeny samples.

An important challenge in genome assembly is haplotype phasing, that is, to reconstruct the different haplotype sequences of an individual genome. Phasing becomes considerably more difficult with increasing ploidy, which makes polyploid phasing a notoriously hard computational problem. We present a novel genetic phasing method for plant breeding with the aim to phase two deep-sequenced parental samples with the help of a large number of progeny samples sequenced at low depth. The key ideas underlying our approach are to (i) integrate the individually weak Mendelian progeny signals with a Bayesian log-likelihood model, (ii) cluster alleles according to their likelihood of co-occurrence, and (iii) assign them to haplotypes via an interval scheduling approach. We show on two deep-sequenced parental and 193 low-depth progeny potato samples that our approach computes high-quality sparse phasings and that it scales to whole genomes.

Multiallelic models for QTL mapping in diverse polyploid populations.

Quantitative trait locus (QTL) analysis allows to identify regions responsible for a trait and to associate alleles with their effect on phenotypes. When using biallelic markers to find these QTL regions, two alleles per QTL are modelled. This assumption might be close to reality in specific biparental crosses but is unrealistic in situations where broader genetic diversity is studied. Diversity panels used in genome-wide association studies or multi-parental populations can easily harbour multiple QTL alleles at each locus, more so in the case of polyploids that carry more than two alleles per individual. In such situations a multiallelic model would be closer to reality, allowing for different genetic effects for each potential allele in the population. To obtain such multiallelic markers we propose the usage of haplotypes, concatenations of nearby SNPs. We developed "mpQTL" an R package that can perform a QTL analysis at any ploidy level under biallelic and multiallelic models, depending on the marker type given. We tested the effect of genetic diversity on the power and accuracy difference between bi-allelic and multiallelic models using a set of simulated multiparental autotetraploid, outbreeding populations. Multiallelic models had higher detection power and were more precise than biallelic, SNP-based models, particularly when genetic diversity was higher. This confirms that moving to multi-allelic QTL models can lead to improved detection and characterization of QTLs. KEY MESSAGE: QTL detection in populations with more than two functional QTL alleles (which is likely in multiparental and/or polyploid populations) is more powerful when using multiallelic models, rather than biallelic models.

De novo whole-genome assembly of Chrysanthemum makinoi, a key wild chrysanthemum.

Chrysanthemum is among the top 10 cut, potted, and perennial garden flowers in the world. Despite this, to date, only the genomes of two wild diploid chrysanthemums have been sequenced and assembled. Here, we present the most complete and contiguous chrysanthemum de novo assembly published so far, as well as a corresponding ab initio annotation. The cultivated hexaploid varieties are thought to originate from a hybrid of wild chrysanthemums, among which the diploid Chrysanthemum makinoi has been mentioned. Using a combination of Oxford Nanopore long reads, Pacific Biosciences long reads, Illumina short reads, Dovetail sequences, and a genetic map, we assembled 3.1 Gb of its sequence into nine pseudochromosomes, with an N50 of 330 Mb and a BUSCO complete score of 92.1%. Our ab initio annotation pipeline predicted 95,074 genes and marked 80.0% of the genome as repetitive. This genome assembly of C. makinoi provides an important step forward in understanding the chrysanthemum genome, evolution, and history.

Detecting quantitative trait loci and exploring chromosomal pairing in autopolyploids using polyqtlR.

MOTIVATION: The investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms vary phenotypically. However, many important crop species are polyploid (carrying more than two copies of each chromosome), requiring specialized tools for such analyses. Moreover, deciphering meiotic processes at higher ploidy levels is not straightforward, but is necessary to understand the reproductive dynamics of these species, or uncover potential barriers to their genetic improvement. RESULTS: Here, we present polyqtlR, a novel software tool to facilitate such analyses in (auto)polyploid crops. It performs QTL interval mapping in F1 populations of outcrossing polyploids of any ploidy level using identity-by-descent probabilities. The allelic composition of discovered QTL can be explored, enabling favourable alleles to be identified and tracked in the population. Visualization tools within the package facilitate this process, and options to include genetic co-factors and experimental factors are included. Detailed information on polyploid meiosis including prediction of multivalent pairing structures, detection of preferential chromosomal pairing and location of double reduction events can be performed. AVAILABILITYAND IMPLEMENTATION: polyqtlR is freely available from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polyqtlR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fire Blight Susceptibility in Lilium spp. Correlates to Sensitivity to Botrytis elliptica Secreted Cell Death Inducing Compounds.

Fire blight represents a widespread disease in Lilium spp. and is caused by the necrotrophic Ascomycete Botrytis elliptica. There are >100 Lilium species that fall into distinct phylogenetic groups and these have been used to generate the contemporary commercial genotypes. It is known among lily breeders and growers that different groups of lilies differ in susceptibility to fire blight, but the genetic basis and mechanisms of susceptibility to fire blight are unresolved. The aim of this study was to quantify differences in fire blight susceptibility between plant genotypes and differences in virulence between fungal isolates. To this end we inoculated, in four biological replicates over 2 years, a set of 12 B. elliptica isolates on a panel of 18 lily genotypes representing seven Lilium hybrid groups. A wide spectrum of variation in symptom severity was observed in different isolate-genotype combinations. There was a good correlation between the lesion diameters on leaves and flowers of the Lilium genotypes, although the flowers generally showed faster expanding lesions. It was earlier postulated that B. elliptica pathogenicity on lily is conferred by secreted proteins that induce programmed cell death in lily cells. We selected two aggressive isolates and one mild isolate and collected culture filtrate (CF) samples to compare the cell death inducing activity of their secreted compounds in lily. After leaf infiltration of the CFs, variation was observed in cell death responses between the diverse lilies. The severity of cell death responses upon infiltration of the fungal CF observed among the diverse Lilium hybrid groups correlated well to their fire blight susceptibility. These results support the hypothesis that susceptibility to fire blight in lily is mediated by their sensitivity to B. elliptica effector proteins in a quantitative manner. Cell death-inducing proteins may provide an attractive tool to predict fire blight susceptibility in lily breeding programs.

Using probabilistic genotypes in linkage analysis of polyploids.

KEY MESSAGE: In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.

Analysis of allelic variants of RhMLO genes in rose and functional studies on susceptibility to powdery mildew related to clade V homologs.

KEY MESSAGE: Rose has 19 MLO genes. Of these, RhMLO1 and RhMLO2 were shown to be required for powdery mildew infection, which suggests their potential as susceptibility targets towards disease resistance. Powdery mildew, caused by Podosphaera pannosa, is one of the most serious and widespread fungal diseases for roses, especially in greenhouse-grown cut roses. It has been shown that certain MLO genes are involved in powdery mildew susceptibility and that loss of function in these genes in various crops leads to broad-spectrum, long-lasting resistance against this fungal disease. For this reason, these MLO genes are called susceptibility genes. We carried out a genome-wide identification of the MLO gene family in the Rosa chinensis genome, and screened for allelic variants among 22 accessions from seven different Rosa species using re-sequencing and transcriptome data. We identified 19 MLO genes in rose, of which four are candidate genes for functional homologs in clade V, which is the clade containing all dicot MLO susceptibility genes. We detected a total of 198 different allelic variants in the set of Rosa species and accessions, corresponding to 5-15 different alleles for each of the genes. Some diploid Rosa species shared alleles with tetraploid rose cultivars, consistent with the notion that diploid species have contributed to the formation of tetraploid roses. Among the four RhMLO genes in clade V, we demonstrated using expression study, virus-induced gene silencing as well as transient RNAi silencing that two of them, RhMLO1 and RhMLO2, are required for infection by P. pannosa and suggest their potential as susceptibility targets for powdery mildew resistance breeding in rose.

De novo transcriptome analysis of Viola ×wittrockiana exposed to high temperature stress.

Around the world, pansies are one of the most popular garden flowers, but they are generally sensitive to high temperatures, and this limits the practicality of planting them during the warmest days of the year. However, a few pansy germplasms with improved heat tolerance have been discovered or bred, but the mechanisms of their heat resistance are not understood. In this study, we investigated the transcript profiles of a heat-tolerant pansy inbred line, DFM16, in response to high temperatures using RNAseq. Approximately 55.48 Gb of nucleotide data were obtained and assembled into 167,576 unigenes with an average length of 959 bp, of which, 5,708 genes were found to be differentially expressed after heat treatments. Real-time qPCR was performed to validate the expression profiles of the selected genes. Nine metabolic pathways were found to be significantly enriched, in the analysis of the differentially expressed genes. Several potentially interesting genes that encoded putative transcription regulators or key components involving heat shock protein (HSP), heat shock transcription factors (HSF), and antioxidants biosynthesis, were identified. These genes were highlighted to indicate their significance in response to heat stress and will be used as candidate genes to improve pansy heat-tolerance in the future.

In the name of the rose: a roadmap for rose research in the genome era.

The recent completion of the rose genome sequence is not the end of a process, but rather a starting point that opens up a whole set of new and exciting activities. Next to a high-quality genome sequence other genomic tools have also become available for rose, including transcriptomics data, a high-density single-nucleotide polymorphism array and software to perform linkage and quantitative trait locus mapping in polyploids. Rose cultivars are highly heterogeneous and diverse. This vast diversity in cultivated roses can be explained through the genetic potential of the genus, introgressions from wild species into commercial tetraploid germplasm and the inimitable efforts of historical breeders. We can now investigate how this diversity can best be exploited and refined in future breeding work, given the rich molecular toolbox now available to the rose breeding community. This paper presents possible lines of research now that rose has entered the genomics era, and attempts to partially answer the question that arises after the completion of any draft genome sequence: 'Now that we have "the" genome, what's next?'. Having access to a genome sequence will allow both (fundamental) scientific and (applied) breeding-orientated questions to be addressed. We outline possible approaches for a number of these questions.

polymapR-linkage analysis and genetic map construction from F1 populations of outcrossing polyploids.

Motivation: Polyploid species carry more than two copies of each chromosome, a condition found in many of the world's most important crops. Genetic mapping in polyploids is more complex than in diploid species, resulting in a lack of available software tools. These are needed if we are to realize all the opportunities offered by modern genotyping platforms for genetic research and breeding in polyploid crops. Results: polymapR is an R package for genetic linkage analysis and integrated genetic map construction from bi-parental populations of outcrossing autopolyploids. It can currently analyse triploid, tetraploid and hexaploid marker datasets and is applicable to various crops including potato, leek, alfalfa, blueberry, chrysanthemum, sweet potato or kiwifruit. It can detect, estimate and correct for preferential chromosome pairing, and has been tested on high-density marker datasets from potato, rose and chrysanthemum, generating high-density integrated linkage maps in all of these crops. Availability and implementation: polymapR is freely available under the general public license from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polymapR. Supplementary information: Supplementary data are available at Bioinformatics online.

Conclusive evidence for hexasomic inheritance in chrysanthemum based on analysis of a 183 k SNP array.

BACKGROUND: Cultivated chrysanthemum is an outcrossing hexaploid (2n = 6× = 54) with a disputed mode of inheritance. In this paper, we present a single nucleotide polymorphism (SNP) selection pipeline that was used to design an Affymetrix Axiom array with 183 k SNPs from RNA sequencing data (1). With this array, we genotyped four bi-parental populations (with sizes of 405, 53, 76 and 37 offspring plants respectively), and a cultivar panel of 63 genotypes. Further, we present a method for dosage scoring in hexaploids from signal intensities of the array based on mixture models (2) and validation of selection steps in the SNP selection pipeline (3). The resulting genotypic data is used to draw conclusions on the mode of inheritance in chrysanthemum (4), and to make an inference on allelic expression bias (5). RESULTS: With use of the mixture model approach, we successfully called the dosage of 73,936 out of 183,130 SNPs (40.4%) that segregated in any of the bi-parental populations. To investigate the mode of inheritance, we analysed markers that segregated in the large bi-parental population (n = 405). Analysis of segregation of duplex x nulliplex SNPs resulted in evidence for genome-wide hexasomic inheritance. This evidence was substantiated by the absence of strong linkage between markers in repulsion, which indicated absence of full disomic inheritance. We present the success rate of SNP discovery out of RNA sequencing data as affected by different selection steps, among which SNP coverage over genotypes and use of different types of sequence read mapping software. Genomic dosage highly correlated with relative allele coverage from the RNA sequencing data, indicating that most alleles are expressed according to their genomic dosage. CONCLUSIONS: The large population, genotyped with a very large number of markers, is a unique framework for extensive genetic analyses in hexaploid chrysanthemum. As starting point, we show conclusive evidence for genome-wide hexasomic inheritance.

An ultra-dense integrated linkage map for hexaploid chrysanthemum enables multi-allelic QTL analysis.

KEY MESSAGE: We constructed the first integrated genetic linkage map in a polysomic hexaploid. This enabled us to estimate inheritance of parental haplotypes in the offspring and detect multi-allelic QTL. Construction and use of linkage maps are challenging in hexaploids with polysomic inheritance. Full map integration requires calculations of recombination frequency between markers with complex segregation types. In addition, detection of QTL in hexaploids requires information on all six alleles at one locus for each individual. We describe a method that we used to construct a fully integrated linkage map for chrysanthemum (Chrysanthemum × morifolium, 2n = 6x = 54). A bi-parental F1 population of 406 individuals was genotyped with an 183,000 SNP genotyping array. The resulting linkage map consisted of 30,312 segregating SNP markers of all possible marker dosage types, representing nine chromosomal linkage groups and 107 out of 108 expected homologues. Synteny with lettuce (Lactuca sativa) showed local colinearity. Overall, it was high enough to number the chrysanthemum chromosomal linkage groups according to those in lettuce. We used the integrated and phased linkage map to reconstruct inheritance of parental haplotypes in the F1 population. Estimated probabilities for the parental haplotypes were used for multi-allelic QTL analyses on four traits with different underlying genetic architectures. This resulted in the identification of major QTL that were affected by multiple alleles having a differential effect on the phenotype. The presented linkage map sets a standard for future genetic mapping analyses in chrysanthemum and closely related species. Moreover, the described methods are a major step forward for linkage mapping and QTL analysis in hexaploids.

Partial preferential chromosome pairing is genotype dependent in tetraploid rose.

It has long been recognised that polyploid species do not always neatly fall into the categories of auto- or allopolyploid, leading to the term 'segmental allopolyploid' to describe everything in between. The meiotic behaviour of such intermediate species is not fully understood, nor is there consensus as to how to model their inheritance patterns. In this study we used a tetraploid cut rose (Rosa hybrida) population, genotyped using the 68K WagRhSNP array, to construct an ultra-high-density linkage map of all homologous chromosomes using methods previously developed for autotetraploids. Using the predicted bivalent configurations in this population we quantified differences in pairing behaviour among and along homologous chromosomes, leading us to correct our estimates of recombination frequency to account for this behaviour. This resulted in the re-mapping of 25 695 SNP markers across all homologues of the seven rose chromosomes, tailored to the pairing behaviour of each chromosome in each parent. We confirmed the inferred differences in pairing behaviour among chromosomes by examining repulsion-phase linkage estimates, which also carry information about preferential pairing and recombination. Currently, the closest sequenced relative to rose is Fragaria vesca. Aligning the integrated ultra-dense rose map with the strawberry genome sequence provided a detailed picture of the synteny, confirming overall co-linearity but also revealing new genomic rearrangements. Our results suggest that pairing affinities may vary along chromosome arms, which broadens our current understanding of segmental allopolyploidy.

Genetic mapping and QTL analysis of Botrytis resistance in Gerbera hybrida.

Gerbera hybrida is an economically important cut flower. In the production and transportation of gerbera with unavoidable periods of high relative humidity, grey mould occurs and results in losses in quality and quantity of flowers. Considering the limitations of chemical use in greenhouses and the impossibility to use these chemicals in auction or after sale, breeding for resistant gerbera cultivars is considered as the best practical approach. In this study, we developed two segregating F1 populations (called S and F). Four parental linkage maps were constructed using common and parental specific SNP markers developed from expressed sequence tag sequencing. Parental genetic maps, containing 30, 29, 27 and 28 linkage groups and a consensus map covering 24 of the 25 expected chromosomes, could be constructed. After evaluation of Botrytis disease severity using three different tests, whole inflorescence, bottom (of disc florets) and ray floret, quantitative trait locus (QTL) mapping was performed using the four individual parental maps. A total of 20 QTLs (including one identical QTL for whole inflorescence and bottom tests) were identified in the parental maps of the two populations. The number of QTLs found and the explained variance of most QTLs detected reflect the complex mechanism of Botrytis disease response.

High-density SNP-based genetic maps for the parents of an outcrossed and a selfed tetraploid garden rose cross, inferred from admixed progeny using the 68k rose SNP array.

Dense genetic maps create a base for QTL analysis of important traits and future implementation of marker-assisted breeding. In tetraploid rose, the existing linkage maps include <300 markers to cover 28 linkage groups (4 homologous sets of 7 chromosomes). Here we used the 68k WagRhSNP Axiom single-nucleotide polymorphism (SNP) array for rose, in combination with SNP dosage calling at the tetraploid level, to genotype offspring from the garden rose cultivar 'Red New Dawn'. The offspring proved to be not from a single bi-parental cross. In rose breeding, crosses with unintended parents occur regularly. We developed a strategy to separate progeny into putative populations, even while one of the parents was unknown, using principle component analysis on pairwise genetic distances based on sets of selected SNP markers that were homozygous, and therefore uninformative for one parent. One of the inferred populations was consistent with self-fertilization of 'Red New Dawn'. Subsequently, linkage maps were generated for a bi-parental and a self-pollinated population with 'Red New Dawn' as the common maternal parent. The densest map, for the selfed parent, had 1929 SNP markers on 25 linkage groups, covering 1765.5 cM at an average marker distance of 0.9 cM. Synteny with the strawberry (Fragaria vesca) genome was extensive. Rose ICM1 corresponded to F. vesca pseudochromosome 7 (Fv7), ICM4 to Fv4, ICM5 to Fv3, ICM6 to Fv2 and ICM7 to Fv5. Rose ICM2 corresponded to parts of F. vesca pseudochromosomes 1 and 6, whereas ICM3 is syntenic to the remainder of Fv6.