Genomic architecture of potato resistance to Synchytrium endobioticum disentangled using SSR markers and the 8.3k SolCAP SNP genotyping array

Genetic Analysis of Potato Breeding Collection Using Single-Nucleotide Polymorphism (SNP) Markers

The autotetraploid potato (Solanum tuberosum L.) is an important crop in China, and it is widely cultivated from Northeast China to South China. Thousands of varieties are bred by breeding institutions or companies, and distinguishing the different varieties based on morphological characteristics is difficult. Using DNA fingerprints is an efficient method to identify varieties that plays an increasingly important role in germplasm identification and property rights protection. In this study, the genetic diversity and population structure of 135 autotetraploid potatoes were evaluated using specific-locus amplified fragment sequencing (SLAF-seq) methods. A total of 3,397,137 high-quality single-nucleotide polymorphisms (SNPs), which were distributed across 12 chromosomes, were obtained. Principal component analysis (PCA), neighbour-joining genetic trees, and model-based structure analysis showed that these autotetraploid potato subpopulations, classified by their SNPs, were not consistent with their geographical origins. On the basis of the obtained 3,397,137 SNPs, 160 perfect SNPs were selected, and 71 SNPs were successfully converted to penta-primer amplification refractory mutation (PARMS-SNP) markers. Additionally, 190 autotetraploid potato varieties were analysed using these 71 PARMS-SNP markers. The PCA results show that the accessions were not completely classified on the basis of their geographical origins. The SNP DNA fingerprints of the 190 autotetraploid potato varieties were also constructed. The SNP fingerprint results show that both synonyms and homonyms were present amongst the 190 autotetraploid potatoes. Above all, these novel SNP markers can lay a good foundation for the analysis of potato genetic diversity, DUS (distinctness, uniformity, and stability) testing, and plant variety protection.

Construction of drought stress regulation networks in potato based on SMRT and RNA sequencing data

BACKGROUND

Potato (Solanum tuberosum) is the fourth most important food crop in the world and plays an important role in food security. Drought stress has a significantly negative impact on potato growth and production. There are several publications involved drought stress in potato, this research contributes to enrich the knowledge.

RESULTS

In this study, next-generation sequencing (NGS) and single-molecule real-time (SMRT) sequencing technology were used to study the transcription profiles in potato in response to 20%PEG6000 simulates drought stress. The leaves of the variety "Désirée" from in vitro plantlets after drought stress at six time points from 0 to 48 hours were used to perform NGS and SMRT sequencing. According to the sequencing data, a total of 12,798 differentially expressed genes (DEGs) were identified in six time points. The real-time (RT)-PCR results are significantly correlated with the sequencing data, confirming the accuracy of the sequencing data. Gene ontology and KEGG analysis show that these DEGs participate in response to drought stress through galactose metabolism, fatty acid metabolism, plant-pathogen interaction, glutathione metabolism and other pathways. Through the analysis of alternative splicing of 66,888 transcripts, the functional pathways of these transcripts were enriched, and 51,098 transcripts were newly discovered from alternative splicing events and 47,994 transcripts were functionally annotated. Moreover, 3445 lncRNAs were predicted and enrichment analysis of corresponding target genes was also performed. Additionally, Alternative polyadenylation was analyzed by TADIS, and 26,153 poly (A) sites from 13,010 genes were detected in the Iso-Seq data.

CONCLUSION

Our research greatly enhanced potato drought-induced gene annotations and provides transcriptome-wide insights into the molecular basis of potato drought resistance.

Synchytrium endobioticum, the potato wart disease pathogen

Potato wart disease is considered one of the most important quarantine pests for cultivated potato and is caused by the obligate biotrophic chytrid fungus Synchytrium endobioticum. This review integrates observations from early potato wart research and recent molecular, genetic, and genomic studies of the pathogen and its host potato. Taxonomy, epidemiology, pathology, and formation of new pathotypes are discussed, and a model for molecular S. endobioticum-potato interaction is proposed.

TAXONOMY

Currently classified as kingdom: Fungi, phylum: Chytridiomycota, class: Chytridiomycetes, order: Chytridiales, family: Synchytriaceae, genus: Synchytrium, species: Synchytrium endobioticum, there is strong molecular support for Synchytriaceae to be transferred to the order Synchytriales.

HOSTS AND DISEASE SYMPTOMS

Solanum tuberosum is the main host for S. endobioticum but other solanaceous species have been reported as alternative hosts. It is not known if these alternative hosts play a role in the survival of the pathogen in (borders of) infested fields. Disease symptoms on potato tubers are characterized by the warty cauliflower-like malformations that are the result of cell enlargement and cell multiplication induced by the pathogen. Meristematic tissue on tubers, stolons, eyes, sprouts, and inflorescences can be infected while the potato root system seems to be immune.

PATHOTYPES

For S. endobioticum over 40 pathotypes, which are defined as groups of isolates with a similar response to a set of differential potato varieties, are described. Pathotypes 1(D1), 2(G1), 6(O1), and 18(T1) are currently regarded to be most widespread. However, with the current differential set other pathogen diversity largely remains undetected.

PATHOGEN-HOST INTERACTION

A single effector has been described for S. endobioticum (AvrSen1), which is recognized by the potato Sen1 resistance gene product. This is also the first effector that has been described in Chytridiomycota, showing that in this fungal division resistance also fits the gene-for-gene concept. Although significant progress was made in the last decade in mapping wart disease resistance loci, not all resistances present in potato breeding germplasm could be identified. The use of resistant varieties plays an essential role in disease management.

Germplasm, Breeding, and Genomics in Potato Improvement of Biotic and Abiotic Stresses Tolerance

Potato is one of the most important food crops in the world. Late blight, viruses, soil and tuber-borne diseases, insect-pests mainly aphids, whiteflies, and potato tuber moths are the major biotic stresses affecting potato production. Potato is an irrigated and highly fertilizer-responsive crop, and therefore, heat, drought, and nutrient stresses are the key abiotic stresses. The genus Solanum is a reservoir of genetic diversity, however, a little fraction of total diversity has been utilized in potato breeding. The conventional breeding has contributed significantly to the development of potato varieties. In recent years, a tremendous progress has been achieved in the sequencing technologies from short-reads to long-reads sequence data, genomes of Solanum species (i.e., pan-genomics), bioinformatics and multi-omics platforms such as genomics, transcriptomics, proteomics, metabolomics, ionomics, and phenomics. As such, genome editing has been extensively explored as a next-generation breeding tool. With the available high-throughput genotyping facilities and tetraploid allele calling softwares, genomic selection would be a reality in potato in the near future. This mini-review covers an update on germplasm, breeding, and genomics in potato improvement for biotic and abiotic stress tolerance.

Genotyping of potato samples from the GenAgro ICG SB RAS collection using DNA markers of genes conferring resistance to phytopathogens

Wart (a disease caused by Synchytrium endobioticum) and golden cyst potato nematode (Globodera rostochiensis), which parasitize the roots of the host plant, cause signif icant damage to potato crop. Both of these disease factors are quarantined in the Russian Federation, and each registered variety is tested for resistance to their most common races and pathotypes. The main method of opposing such diseases is by the development of resistant varieties. An important step in this process is the selection of resistant genotypes from the population and the estimation of the resistance of hybrids obtained by crosses during the breeding process. Conducting a permanent phenotypic evaluation is associated with diff iculties, for example, it is not always possible to work with pathogens, and phenotypic evaluation is very costly and time consuming. However, the use of DNA markers linked to resistance genes can signif icantly speed up and reduce the cost of the breeding process. The aim of the study was to screen the GenAgro potato collection of ICG SB RAS using known diagnostic PCR markers linked to golden potato cyst nematode and wart resistance. Genotyping was carried out on 73 potato samples using three DNA markers 57R, CP113, Gro1-4 associated with nematode resistance and one marker, NL25, associated with wart resistance. The genotyping data were compared with the data on the resistance of the collection samples. Only the 57R marker had a high level of correlation (Spearman R = 0.722008, p = 0.000000, p < 0.05) between resistance and the presence of a diagnostic fragment. The diagnostic eff iciency of the 57R marker was 86.11 %. This marker can be successfully used for screening a collection, searching for resistant genotypes and marker-assisted selection. The other markers showed a low correlation between the presence of the DNA marker and resistance. The diagnostic eff iciency of the CP113 marker was only 44.44 %. Spearman's correlation coeff icient (Spearman R = -0.109218, p = 0.361104, p < 0.05) did not show signif icant correlation between resistance and the DNA marker. The diagnostic eff iciency of the NL25 marker was 61.11 %. No signif icant correlation was found between the NL25 marker and resistance (Spearman R = -0.017946, p = 0.881061, p < 0.05). The use of these markers for the search for resistant samples is not advisable.

A Hitchhiker's guide to the potato wart disease resistance galaxy

KEY MESSAGE

Two novel major effect loci (Sen4 and Sen5) and several minor effect QTLs for potato wart disease resistance have been mapped. The importance of minor effect loci to bring full resistance to wart disease was investigated. Using the newly identified and known wart disease resistances, a panel of potato breeding germplasm and Solanum wild species was screened. This provided a state-of-the-art "hitch-hikers-guide" of complementary wart disease resistance sources. Potato wart disease, caused by the obligate biotrophic soil-born fungus Synchytrium endobioticum, is the most important quarantine disease of potato. Because of its huge impact on yield, the lack of chemical control and the formation of resting spores with long viability, breeding for resistant varieties combined with strict quarantine measures are the only way to efficiently and durably manage the disease. In this study, we set out to make an inventory of the different resistance sources. Using a Genome-Wide Association Study (GWAS) in the potato breeding genepool, we identified Sen4, associated with pathotypes 2, 6 and 18 resistance. Associated SNPs mapped to the south arm of chromosome 12 and were validated to be linked to resistance in one full-sib population. Also, a bulked segregant analysis combined with a Comparative Subsequence Sets Analysis (CoSSA) resulted in the identification of Sen5, associated with pathotypes 2, 6 and 18 resistance, on the south arm of chromosome 5. In addition to these two major effect loci, the GWAS and CoSSA allowed the identification of several quantitative trait loci necessary to bring full resistance to certain pathotypes. Panels of varieties and Solanum accessions were screened for the presence of Sen1, Sen2, Sen3, Sen4 and Sen5. Combined with pedigree analysis, we could trace back some of these genes to the ancestral resistance donors. This analysis revealed complementary resistance sources and allows elimination of redundancy in wart resistance breeding programs.

Distribution of P1(D1) wart disease resistance in potato germplasm and GWAS identification of haplotype-specific SNP markers

KEY MESSAGE

A Genome-Wide Association Study using 330 commercial potato varieties identified haplotype specific SNP markers associated with pathotype 1(D1) wart disease resistance. Synchytrium endobioticum is a soilborne obligate biotrophic fungus responsible for wart disease. Growing resistant varieties is the most effective way to manage the disease. This paper addresses the challenge to apply molecular markers in potato breeding. Although markers linked to Sen1 were published before, the identification of haplotype-specific single-nucleotide polymorphisms may result in marker assays with high diagnostic value. To identify hs-SNP markers, we performed a genome-wide association study (GWAS) in a panel of 330 potato varieties representative of the commercial potato gene pool. SNP markers significantly associated with pathotype 1 resistance were identified on chromosome 11, at the position of the previously identified Sen1 locus. Haplotype specificity of the SNP markers was examined through the analysis of false positives and false negatives and validated in two independent full-sib populations. This paper illustrates why it is not always feasible to design markers without false positives and false negatives for marker-assisted selection. In the case of Sen1, founders could not be traced because of a lack of identity by descent and because of the decay of linkage disequilibrium between Sen1 and flanking SNP markers. Sen1 appeared to be the main source of pathotype 1 resistance in potato varieties, but it does not explain all the resistance observed. Recombination and introgression breeding may have introduced new, albeit rare haplotypes involved in pathotype 1 resistance. The GWAS approach, in such case, is instrumental to identify SNPs with the best possible diagnostic value for marker-assisted breeding.

QTL analysis of resistance to bacterial wilt caused by Ralstonia solanacearum in potato

Ralstonia solanacearum causes bacterial wilt, a soil-borne disease and one of the most important maladies of potato and other Solanaceae crops. We analyzed the resistance of a potato clone to bacterial wilt by quantitative trait locus (QTL) analysis. A resistant diploid potato clone 10-03-30 was crossed with a susceptible diploid clone F₁-1 to generate a diploid, two-way pseudo-testcross F₁ population comprised of 94 genotypes. Dense linkage maps, containing 4,139 single nucleotide polymorphism markers with an average distance of 0.6 and 0.3 cM between markers, were constructed for both parents. The resistance level was evaluated by in vitro inoculation test with R. solanacearum (phylotype I/biovar 4/race 1). Five QTLs (qBWR-1 to -5) were identified on potato chromosomes 1, 3, 7, 10, and 11, and they explained 9.3-18.4% of the phenotypic variance. The resistant parent had resistant alleles in qBWR-2, qBWR-3, and qBWR-4 and susceptible alleles in qBWR-1 and qBWR-5. Accumulation of the resistant alleles in all five QTLs increased the level of resistance compared with that of the resistant parent. This is the first study to identify novel QTLs for bacterial wilt resistance in potato by using genome-wide markers.

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

BACKGROUND

Genetic 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.

RESULTS

Our 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 60 k 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.

CONCLUSION

Our 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.

Comparative Subsequence Sets Analysis (CoSSA) is a robust approach to identify haplotype specific SNPs; mapping and pedigree analysis of a potato wart disease resistance gene Sen3

BACKGROUND

Standard strategies to identify genomic regions involved in a specific trait variation are often limited by time and resource consuming genotyping methods. Other limiting pre-requisites are the phenotyping of large segregating populations or of diversity panels and the availability and quality of a closely related reference genome. To overcome these limitations, we designed efficient Comparative Subsequence Sets Analysis (CoSSA) workflows to identify haplotype specific SNPs linked to a trait of interest from Whole Genome Sequencing data.

RESULTS

As a model, we used the resistance to Synchytrium endobioticum pathotypes 2, 6 and 18 that co-segregated in a tetraploid full sib population. Genomic DNA from both parents, pedigree genotypes, unrelated potato varieties lacking the wart resistance traits and pools of resistant and susceptible siblings were sequenced. Set algebra and depth filtering of subsequences (k-mers) were used to delete unlinked and common SNPs and to enrich for SNPs from the haplotype(s) harboring the resistance gene(s). Using CoSSA, we identified a major and a minor effect locus. Upon comparison to the reference genome, it was inferred that the major resistance locus, referred to as Sen3, was located on the north arm of chromosome 11 between 1,259,552 and 1,519,485 bp. Furthermore, we could anchor the unanchored superscaffold DMB734 from the potato reference genome to a synthenous interval. CoSSA was also successful in identifying Sen3 in a reference genome independent way thanks to the de novo assembly of paired end reads matching haplotype specific k-mers. The de novo assembly provided more R haplotype specific polymorphisms than the reference genome corresponding region. CoSSA also offers possibilities for pedigree analysis. The origin of Sen3 was traced back until Ora. Finally, the diagnostic power of the haplotype specific markers was shown using a panel of 56 tetraploid varieties.

CONCLUSIONS

CoSSA is an efficient, robust and versatile set of workflows for the genetic analysis of a trait of interest using WGS data. Because the WGS data are used without intermediate reads mapping, CoSSA does not require the use of a reference genome. This approach allowed the identification of Sen3 and the design of haplotype specific, diagnostic markers.

Improved genetic resolution for linkage mapping of resistance to potato wart in monoparental dihaploids with potential diagnostic value in tetraploid potato varieties

KEY MESSAGE

We achieved improved mapping resolution of the major wart resistance locus Xla-TNL containing also Sen1 in a dihaploid population using SNP data and developed additional markers with diagnostic value in tetraploid varieties. We analyzed a segregating monoparental dihaploid potato population comprising 215 genotypes derived from a tetraploid variety that is highly resistant to Synchytrium endobioticum pathotypes 18 and 6. The clear bimodal segregation for both pathotypes indicated that a major dominant resistance factor in a simplex allele configuration was present in the tetraploid donor genotype. Compared to that in previous analyses of the same tetraploid donor in conventional crosses with susceptible tetraploid genotypes, a segregation pattern with a reduced genetic complexity of resistance in dihaploids was observed here. Using the 12.8 k SolCAP SNP array, we mapped a resistance locus to the Xla-TNL region containing also Sen1 on potato chromosome 11. The improved mapping resolution provided by the monoparental dihaploids allowed for the localization of the genes responsible for the resistance to both pathotypes in an interval spanning less than 800 kbp on the reference genome. Furthermore, we identified eight molecular markers segregating without recombination to pathotype 18 and pathotype 6 resistance. Also, two developed markers display improved diagnostic properties in an independent panel of tetraploid varieties. Overall, our data provide the highest resolution mapping of wart resistance genes at the Xla-TNL locus thus far.

Novel gene Sen2 conferring broad-spectrum resistance to Synchytrium endobioticum mapped to potato chromosome XI

Key message Sen2 gene for potato wart resistance, located on chromosome XI in a locus distinct from Sen1 , provides resistance against eight wart pathotypes, including the virulent ones important in Europe. Synchytrium endobioticum causes potato wart disease imposing severe losses in potato production, and as a quarantine pathogen in many countries, it results in lost trade markets and land for potato cultivation. The resistance to S. endobioticum pathotype 1(D1) is widespread in potato cultivars but new virulent pathotypes appear and the problem re-emerges. To characterize and map a new gene for resistance to potato wart, we used diploid F1 potato population from a cross of potato clone resistant to S. endobioticum pathotype 1(D1) and virulent pathotypes: 2(G1), 6(O1), 8(F1), 18(T1), 2(Ch1), 3(M1) and 39(P1) with a potato clone resistant to pathotype 1(D1) only. The 176 progeny clones were tested for resistance to eight wart pathotypes with a modified Glynne-Lemmerzahl method. Bimodal distributions and co-segregation of resistance in the population show that a single resistance gene, Sen2, underlies the resistance to eight pathotypes. Resistance to pathotype 1(D1) was additionally conferred by the locus Sen1 inherited from both parents. Sen2 was mapped to chromosome XI using DArTseq markers. The genetic and physical distances between Sen1 and Sen2 loci were indirectly estimated at 63 cM and 32 Mbp, respectively. We developed PCR markers co-segregating with the Sen2 locus that can be applied in marker-assisted selection of potatoes resistant to eight important pathotypes of S. endobioticum. Wide spectrum of the Sen2 resistance may be an indication of durability which can be enhanced by the pyramiding of the Sen2 and Sen1 loci as in 61 clones selected within this study.

Exploring the potential and limitations of genotyping-by-sequencing for SNP discovery and genotyping in tetraploid potato

Genotyping-by-sequencing (GBS) potentially offers a cost-effective alternative for SNP discovery and genotyping. Here, we report the exploration of GBS in tetraploid potato. Both ApeKI and PstI/MspI enzymes were used for library preparation on eight diverse potato genotypes. ApeKI yielded more markers than PstI/MspI but provided a lower read coverage per marker, resulting in more missing data and limiting effective genotyping to the tetraploid mode. We then assessed the accuracy of these SNPs by comparison with SolCAP data (5824 data points in diploid mode and 3243 data points in tetraploid mode) and found the match rates between genotype calls was 90.4% and 81.3%, respectively. Imputation of missing data did not prove very accurate because of incomplete haplotype discovery, suggesting caution in setting the allowance for missing data. To further assess the quality of GBS-derived data, a genome-wide association analysis was performed for flower color on 318 clones (with ApeKI). A strong association signal on chromosome 2 was obtained with the most significant SNP located in the middle of the dihydroflavonol 4-reductase (DFR) gene. We conclude that an appropriate choice of enzyme for GBS library preparation makes it possible to obtain high-quality SNPs in potato and will be helpful for marker-assisted genomics.

Genetic diversity and association mapping in the Colombian Central Collection of Solanum tuberosum L. Andigenum group using SNPs markers

The potato (Solanum tuberosum L.) is the fourth most important crop food in the world and Colombia has one of the most important collections of potato germplasm in the world (the Colombian Central Collection-CCC). Little is known about its potential as a source of genetic diversity for molecular breeding programs. In this study, we analyzed 809 Andigenum group accessions from the CCC using 5968 SNPs to determine: 1) the genetic diversity and population structure of the Andigenum germplasm and 2) the usefulness of this collection to map qualitative traits across the potato genome. The genetic structure analysis based on principal components, cluster analyses, and Bayesian inference revealed that the CCC can be subdivided into two main groups associated with their ploidy level: Phureja (diploid) and Andigena (tetraploid). The Andigena population was more genetically diverse but less genetically substructured than the Phureja population (three vs. five subpopulations, respectively). The association mapping analysis of qualitative morphological data using 4666 SNPs showed 23 markers significantly associated with nine morphological traits. The present study showed that the CCC is a highly diverse germplasm collection genetically and phenotypically, useful to implement association mapping in order to identify genes related to traits of interest and to assist future potato genetic breeding programs.