StCoExpNet: a global co-expression network analysis facilitates identifying genes underlying agronomic traits in potatoes.

KEY MESSAGE: We constructed a gene expression atlas and co-expression network for potatoes and identified several novel genes associated with various agronomic traits. This resource will accelerate potato genetics and genomics research. Potato (Solanum tuberosum L.) is the world's most crucial non-cereal food crop and ranks third in food production after wheat and rice. Despite the availability of several potato transcriptome datasets at public databases like NCBI SRA, an effort has yet to be put into developing a global transcriptome atlas and a co-expression network for potatoes. The objectives of our study were to construct a global expression atlas for potatoes using publicly available transcriptome datasets, identify housekeeping and tissue-specific genes, construct a global co-expression network and identify co-expression clusters, investigate the transcriptional complexity of genes involved in various essential biological processes related to agronomic traits, and provide a web server (StCoExpNet) to easily access the newly constructed expression atlas and co-expression network to investigate the expression and co-expression of genes of interest. In this study, we used data from 2299 publicly available potato transcriptome samples obtained from 15 different tissues to construct a global transcriptome atlas. We found that roughly 87% of the annotated genes exhibited detectable expression in at least one sample. Among these, we identified 281 genes with consistent and stable expression levels, indicating their role as housekeeping genes. Conversely, 308 genes exhibited marked tissue-specific expression patterns. We exemplarily linked some co-expression clusters to important agronomic traits of potatoes, such as self-incompatibility, anthocyanin biosynthesis, tuberization, and defense responses against multiple pathogens. The dataset compiled here constitutes a new resource (StCoExpNet), which can be accessed at https://stcoexpnet.julius-kuehn.de . This transcriptome atlas and the co-expression network will accelerate potato genetics and genomics research.

Using drone-retrieved multispectral data for phenomic selection in potato breeding.

Predictive breeding approaches, like phenomic or genomic selection, have the potential to increase the selection gain for potato breeding programs which are characterized by very large numbers of entries in early stages and the availability of very few tubers per entry in these stages. The objectives of this study were to (i) explore the capabilities of phenomic prediction based on drone-derived multispectral reflectance data in potato breeding by testing different prediction scenarios on a diverse panel of tetraploid potato material from all market segments and considering a broad range of traits, (ii) compare the performance of phenomic and genomic predictions, and (iii) assess the predictive power of mixed relationship matrices utilizing weighted SNP array and multispectral reflectance data. Predictive abilities of phenomic prediction scenarios varied greatly within a range of - 0.15 and 0.88 and were strongly dependent on the environment, predicted trait, and considered prediction scenario. We observed high predictive abilities with phenomic prediction for yield (0.45), maturity (0.88), foliage development (0.73), and emergence (0.73), while all other traits achieved higher predictive ability with genomic compared to phenomic prediction. When a mixed relationship matrix was used for prediction, higher predictive abilities were observed for 20 out of 22 traits, showcasing that phenomic and genomic data contained complementary information. We see the main application of phenomic selection in potato breeding programs to allow for the use of the principle of predictive breeding in the pot seedling or single hill stage where genotyping is not recommended due to high costs.

Optimal implementation of genomic selection in clone breeding programs-Exemplified in potato: I. Effect of selection strategy, implementation stage, and selection intensity on short-term genetic gain.

Genomic selection (GS) is used in many animal and plant breeding programs to enhance genetic gain for complex traits. However, its optimal integration in clone breeding programs, for example potato, that up to now relied on phenotypic selection (PS) requires further research. In this study, we performed computer simulations based on an empirical genomic dataset of tetraploid potato to (i) investigate under a fixed budget how the weight of GS relative to PS, the stage of implementing GS, the correlation between an auxiliary trait and the target trait, the variance components, and the prediction accuracy affect the genetic gain of the target trait, (ii) determine the optimal allocation of resources maximizing the genetic gain of the target trait, and (iii) make recommendations to breeders how to implement GS in clone and especially potato breeding programs. In our simulation results, any selection strategy involving GS had a higher short-term genetic gain for the target trait than Standard-PS. In addition, we showed that implementing GS in consecutive selection stages can largely enhance short-term genetic gain and recommend the breeders to implement GS at single hills and A clone stages. Furthermore, we observed for selection strategies involving GS that the optimal allocation of resources maximizing the genetic gain of the target trait differed considerably from those typically used in potato breeding programs and, thus, require the adjustment of the selection and phenotyping intensities. The trends are described in our study. Therefore, our study provides new insight for breeders regarding how to optimally implement GS in a commercial potato breeding program to improve the short-term genetic gain for their target trait.

Benchmarking of structural variant detection in the tetraploid potato genome using linked-read sequencing.

It has recently been shown that structural variants (SV) can have a higher impact on gene expression variation compared to single nucleotide variants (SNV) in different plant species. Additionally, SV were associated with phenotypic variation in several crops. However, compared to the established SV detection based on short-read sequencing, less approaches were described for linked-read based SV calling. We therefore evaluated the performance of six linked-read SV callers compared to an established short-read SV caller based on simulated linked-reads in tetraploid potato. The objectives of our study were to i) compare the performance of SV callers based on linked-read sequencing to short-read sequencing, ii) examine the influence of SV type, SV length, haplotype incidence (HI), as well as sequencing coverage on the SV calling performance in the tetraploid potato genome, and iii) evaluate the accuracy of detecting insertions by linked-read compared to short-read sequencing. We observed high break point resolutions (BPR) detecting short SV and slightly lower BPR for large SV. Our observations highlighted the importance of short-read signals provided by Manta and LinkedSV to detect short SV. Manta and NAIBR performed well for detecting larger deletions, inversions, and duplications. Detected large SV were weakly influenced by the HI. Furthermore, we illustrated that large insertions can be assembled by Novel-X. Our results suggest the usage of the short-read and linked-read SV callers Manta, NAIBR, LinkedSV, and Novel-X based on at least 90x linked-read sequencing coverage to ensure the detection of a broad range of SV in the tetraploid potato genome.

Chromosome-scale reference genome assembly of a diploid potato clone derived from an elite variety.

Potato (Solanum tuberosum L.) is one of the most important crops with a worldwide production of 370 million metric tons. The objectives of this study were (1) to create a high-quality consensus sequence across the two haplotypes of a diploid clone derived from a tetraploid elite variety and assess the sequence divergence from the available potato genome assemblies, as well as among the two haplotypes; (2) to evaluate the new assembly's usefulness for various genomic methods; and (3) to assess the performance of phasing in diploid and tetraploid clones, using linked-read sequencing technology. We used PacBio long reads coupled with 10x Genomics reads and proximity ligation scaffolding to create the dAg1_v1.0 reference genome sequence. With a final assembly size of 812 Mb, where 750 Mb are anchored to 12 chromosomes, our assembly is larger than other available potato reference sequences and high proportions of properly paired reads were observed for clones unrelated by pedigree to dAg1. Comparisons of the new dAg1_v1.0 sequence to other potato genome sequences point out the high divergence between the different potato varieties and illustrate the potential of using dAg1_v1.0 sequence in breeding applications.

Tapping natural variation at functional level reveals allele specific molecular characteristics of potato invertase Pain-1.

Biochemical, molecular and genetic studies emphasize the role of the potato vacuolar invertase Pain-1 in the accumulation of reducing sugars in potato tubers upon cold storage, and thereby its influence on the quality of potato chips and French fries. Previous studies showed that natural Pain-1 cDNA alleles were associated with better chip quality and higher tuber starch content. In this study, we focused on the functional characterization of these alleles. A genotype-dependent transient increase of total Pain-1 transcript levels in cold-stored tubers of six different genotypes as well as allele-specific expression patterns were detected. 3D modelling revealed putative structural differences between allelic Pain-1 proteins at the molecule's surface and at the substrate binding site. Furthermore, the yeast SUC2 mutant was complemented with Pain-1 cDNA alleles and enzymatic parameters of the heterologous expressed proteins were measured at 30 and 4 °C. Significant differences between the alleles were detected. The observed functional differences between Pain-1 alleles did not permit final conclusions on the mechanism of their association with tuber quality traits. Our results show that natural allelic variation at the functional level is present in potato, and that the heterozygous genetic background influences the manifestation of this variation.

Analysis of natural variation of the potato tuber proteome reveals novel candidate genes for tuber bruising.

Potato (Solanum tuberosum) presents a challenging organism for the genetic and molecular dissection of complex traits due to its tetraploidy and high heterozygosity. One such complex trait of high agronomic interest is the tuber susceptibility to bruising upon mechanical impact, which involves an enzymatic browning reaction. We have compared the tuber proteome of two groups of 10 potato cultivars differing in bruising susceptibility to (i) identify de novo proteins that contribute to bruising, based on differential protein expression, and (ii) validate these proteins by combining proteomics with association genetics. The comparison of 20 potato varieties yields insight into the high natural variation of tuber protein patterns due to genetic background. Seven genes or gene families were found that were both differentially expressed on the protein level between groups and for which DNA polymorphisms were associated with the investigated traits. A putative class III lipase was identified as a novel factor contributing to the natural variation of bruising. Additionally, tuber proteome changes triggered by mechanical impact, within and between groups, were monitored over time. Differentially expressed proteins were found, notably lipases, patatins, and annexins, showing remarkable time-dependent protein variation.

Genome-wide distribution of genetic diversity and linkage disequilibrium in elite sugar beet germplasm.

BACKGROUND: Characterization of population structure and genetic diversity of germplasm is essential for the efficient organization and utilization of breeding material. The objectives of this study were to (i) explore the patterns of population structure in the pollen parent heterotic pool using different methods, (ii) investigate the genome-wide distribution of genetic diversity, and (iii) assess the extent and genome-wide distribution of linkage disequilibrium (LD) in elite sugar beet germplasm. RESULTS: A total of 264 and 238 inbred lines from the yield type and sugar type inbreds of the pollen parent heterotic gene pools, respectively, which had been genotyped with 328 SNP markers, were used in this study. Two distinct subgroups were detected based on different statistical methods within the elite sugar beet germplasm set, which was in accordance with its breeding history. MCLUST based on principal components, principal coordinates, or lapvectors had high correspondence with the germplasm type information as well as the assignment by STRUCTURE, which indicated that these methods might be alternatives to STRUCTURE for population structure analysis. Gene diversity and modified Roger's distance between the examined germplasm types varied considerably across the genome, which might be due to artificial selection. This observation indicates that population genetic approaches could be used to identify candidate genes for the traits under selection. Due to the fact that r2 >0.8 is required to detect marker-phenotype association explaining less than 1% of the phenotypic variance, our observation of a low proportion of SNP loci pairs showing such levels of LD suggests that the number of markers has to be dramatically increased for powerful genome-wide association mapping. CONCLUSIONS: We provided a genome-wide distribution map of genetic diversity and linkage disequilibrium for the elite sugar beet germplasm, which is useful for the application of genome-wide association mapping in sugar beet as well as the efficient organization of germplasm.

Association genetics in Solanum tuberosum provides new insights into potato tuber bruising and enzymatic tissue discoloration.

BACKGROUND: Most agronomic plant traits result from complex molecular networks involving multiple genes and from environmental factors. One such trait is the enzymatic discoloration of fruit and tuber tissues initiated by mechanical impact (bruising). Tuber susceptibility to bruising is a complex trait of the cultivated potato (Solanum tuberosum) that is crucial for crop quality. As phenotypic evaluation of bruising is cumbersome, the application of diagnostic molecular markers would empower the selection of low bruising potato varieties. The genetic factors and molecular networks underlying enzymatic tissue discoloration are sparsely known. Hitherto there is no association study dealing with tuber bruising and diagnostic markers for enzymatic discoloration are rare. RESULTS: The natural genetic diversity for bruising susceptibility was evaluated in elite middle European potato germplasm in order to elucidate its molecular basis. Association genetics using a candidate gene approach identified allelic variants in genes that function in tuber bruising and enzymatic browning. Two hundred and five tetraploid potato varieties and breeding clones related by descent were evaluated for two years in six environments for tuber bruising susceptibility, specific gravity, yield, shape and plant maturity. Correlations were found between different traits. In total 362 polymorphic DNA fragments, derived from 33 candidate genes and 29 SSR loci, were scored in the population and tested for association with the traits using a mixed model approach, which takes into account population structure and kinship. Twenty one highly significant (p < 0.001) and robust marker-trait associations were identified. CONCLUSIONS: The observed trait correlations and associated marker fragments provide new insight in the molecular basis of bruising susceptibility and its natural variation. The markers diagnostic for increased or decreased bruising susceptibility will facilitate the combination of superior alleles in breeding programs. In addition, this study presents novel candidates that might control enzymatic tissue discoloration and tuber bruising. Their validation and characterization will increase the knowledge about the underlying biological processes.

Physical organization of mixed protease inhibitor gene clusters, coordinated expression and association with resistance to late blight at the StKI locus on potato chromosome III.

Protease inhibitors (PIs) play a role in plant defence against pests and pathogens as well as in plant development. Potato (Solanum tuberosum) contains abundant levels of diverse PIs. Most potato Kunitz-type inhibitor (KTI) genes map to the StKI locus on potato chromosome III, which is linked to a quantitative trait locus (QTL) for resistance to Phytophthora infestans. To elucidate the physical organization of PIs at the StKI locus, we screened bacterial artificial chromosome (BAC) libraries with KTI probes. Ten different clones were selected, sequenced and annotated. Of 100 putative genes, 22 corresponded to five PI classes. Expression analysis by quantitative real-time PCR (qRT-PCR) using PI class-specific primers in different tissues of the tetraploid potato cultivars 'Nikita' and 'Baltica' revealed different transcript levels, depending on PI type and genotype. During the compatible interaction with a complex race of P. infestans, four PI classes showed coordinated expression over 3 d after infection, a strong decrease in infected leaves and a transient induction in systemic leaves. Basal transcript levels in non-infected leaves differed strongly between the two genotypes examined. Two microsatellite markers located within the PI gene cluster were associated with resistance to P. infestans in a population of potato varieties and breeding clones.

Comparison of mixed-model approaches for association mapping in rapeseed, potato, sugar beet, maize, and Arabidopsis.

BACKGROUND: In recent years, several attempts have been made in plant genetics to detect QTL by using association mapping methods. The objectives of this study were to (i) evaluate various methods for association mapping in five plant species and (ii) for three traits in each of the plant species compare the Topt, the restricted maximum likelihood (REML) estimate of the conditional probability that two genotypes carry at the same locus alleles that are identical in state but not identical by descent. In order to compare the association mapping methods based on scenarios with realistic estimates of population structure and familial relatedness, we analyzed phenotypic and genotypic data of rapeseed, potato, sugar beet, maize, and Arabidopsis. For the same reason, QTL effects were simulated on top of the observed phenotypic values when examining the adjusted power for QTL detection. RESULTS: The correlation between the Topt values identified using REML deviance profiles and profiles of the mean of squared difference between observed and expected P values was 0.83. CONCLUSION: The mixed-model association mapping approaches using a kinship matrix, which was based on Topt, were more appropriate for association mapping than the recently proposed QK method with respect to the adherence to the nominal alpha level and the adjusted power for QTL detection. Furthermore, we showed that Topt differs considerably among the five plant species but only marginally among different traits.

Single nucleotide polymorphisms in the allene oxide synthase 2 gene are associated with field resistance to late blight in populations of tetraploid potato cultivars.

The oomycete Phytophthora infestans causes late blight, the most relevant disease of potato (Solanum tuberosum) worldwide. Field resistance to late blight is a complex trait. When potatoes are cultivated under long day conditions in temperate climates, this resistance is correlated with late plant maturity, an undesirable characteristic. Identification of natural gene variation underlying late blight resistance not compromised by late maturity will facilitate the selection of resistant cultivars and give new insight in the mechanisms controlling quantitative pathogen resistance. We tested 24 candidate loci for association with field resistance to late blight and plant maturity in a population of 184 tetraploid potato individuals. The individuals were genotyped for 230 single nucleotide polymorphisms (SNPs) and 166 microsatellite alleles. For association analysis we used a mixed model, taking into account population structure, kinship, allele substitution and interaction effects of the marker alleles at a locus with four allele doses. Nine SNPs were associated with maturity corrected resistance (P < 0.001), which collectively explained 50% of the genetic variance of this trait. A major association was found at the StAOS2 locus encoding allene oxide synthase 2, a key enzyme in the biosynthesis of jasmonates, plant hormones that function in defense signaling. This finding supports StAOS2 as being one of the factors controlling natural variation of pathogen resistance.

Association mapping in multiple segregating populations of sugar beet (Beta vulgaris L.).

Association mapping in multiple segregating populations (AMMSP) combines high power to detect QTL in genome-wide approaches of linkage mapping with high mapping resolution of association mapping. The main objectives of this study were to (1) examine the applicability of AMMSP in a plant breeding context based on segregating populations of various size of sugar beet (Beta vulgaris L.), (2) compare different biometric approaches for AMMSP, and (3) detect markers with significant main effect across locations for nine traits in sugar beet. We used 768 F(n) (n = 2, 3, 4) sugar beet genotypes which were randomly derived from 19 crosses among diploid elite sugar beet clones. For all nine traits, the genotypic and genotype x location interaction variances were highly significant (P < 0.01). Using a one-step AMMSP approach, the total number of significant (P < 0.05) marker-phenotype associations was 44. The identification of genome regions associated with the traits under consideration indicated that not only segregating populations derived from crosses of parental genotypes in a systematic manner could be used for AMMSP but also populations routinely derived in plant breeding programs from multiple, related crosses. Furthermore, our results suggest that data sets, whose size does not permit analysis by the one-step AMMSP approach, might be analyzed using the two-step approach based on adjusted entry means for each location without losing too much power for detection of marker-phenotype associations.

Multi-trait association mapping in sugar beet (Beta vulgaris L.).

Association mapping promises to overcome the limitations of linkage mapping methods. The main objective of this study was to examine the applicability of multivariate association mapping with an empirical data set of sugar beet. A total of 111 diploid sugar beet inbreds was selected from the seed parent heterotic pool to represent a broad diversity with respect to sugar content (SC). The inbreds were genotyped with 26 simple sequence repeat markers chosen according to their map positions in proximity to previously identified quantitative trait loci for SC. For SC and beet yield (BY), the genotypic variances were highly significant (P < 0.01). Based on the global test of the bivariate mixed-model approach, four markers were significantly associated with SC, BY, or both at a false discovery rate of 0.025. All four markers were significantly (P < 0.05) associated with BY but only two with SC. The identification of markers associated with SC, BY, or both indicated that association mapping can be successfully applied in a sugar beet breeding context for detection of marker-phenotype associations. Furthermore, based on our results multivariate association mapping can be recommended as a promising tool to discriminate with a high mapping resolution between pleiotropy and linkage as reasons for co-localization of marker-phenotype associations for different traits.