A next-generation sequencing method for genotyping-by-sequencing of highly heterozygous autotetraploid potato

Polyploid QTL-seq identified QTLs controlling potato flesh color and tuber starch phosphorus content in a plexity-dependent manner

The progenies of polyploid crops inherit multiple sets of homoeologous chromosomes through various combinations, which impedes the identification of the quantitative trait loci (QTL) governing agronomic traits and the implementation of DNA marker-assisted breeding. Previously, we developed a whole-genome sequencing-based polyploid QTL-seq method that utilizes comprehensively extracted simplex polymorphisms for QTL mapping. Here, we verified the detection of duplex QTLs by modifying the analytical settings to explore the QTLs governing tuber flesh color and starch phosphorus content using tetraploid potato (Solanum tuberosum L.). The F1 progenies were obtained from a cross between 'Touya' (TY) and 'Benimaru' (BM). A single TY-derived QTL responsible for yellow flesh color was identified around a β-carotene hydroxylase gene on chromosome 3 using simplex polymorphisms, and a BM-derived QTL associated with decreased starch phosphorus content near a starch synthase II gene on chromosome 2 was detected using duplex polymorphisms. Furthermore, linked DNA markers were developed at the QTL sites. For the latter QTL, plexity-distinguishable markers were developed using quantitative PCR, fragment analysis, and amplicon sequencing. These revealed the allele dosage-dependent effect of the reduced starch phosphorus content. Thus, the polyploid QTL-seq pipeline can explore versatile QTLs beyond simplex, facilitating DNA marker-assisted breeding in various polyploid crops.

DeepHapNet: a haplotype assembly method based on RetNet and deep spectral clustering

Gene polymorphism originates from single-nucleotide polymorphisms (SNPs), and the analysis and study of SNPs are of great significance in the field of biogenetics. The haplotype, which consists of the sequence of SNP loci, carries more genetic information than a single SNP. Haplotype assembly plays a significant role in understanding gene function, diagnosing complex diseases, and pinpointing species genes. We propose a novel method, DeepHapNet, for haplotype assembly through the clustering of reads and learning correlations between read pairs. We employ a sequence model called Retentive Network (RetNet), which utilizes a multiscale retention mechanism to extract read features and learn the global relationships among them. Based on the feature representation of reads learned from the RetNet model, the clustering process of reads is implemented using the SpectralNet model, and, finally, haplotypes are constructed based on the read clusters. Experiments with simulated and real datasets show that the method performs well in the haplotype assembly problem of diploid and polyploid based on either long or short reads. The code implementation of DeepHapNet and the processing scripts for experimental data are publicly available at https://github.com/wjj6666/DeepHapNet.

Identification of heat stress-related genomic regions by genome-wide association study in Solanum tuberosum

The climate crisis impairs yield and quality of crucial crops like potatoes. We investigated the effects of heat stress on five morpho-physiological parameters in a diverse panel of 178 potato cultivars under glasshouse conditions. Overall, heat stress increased shoot elongation and green fresh weight, but reduced tuber yield, starch content and harvest index. Genomic information was obtained from 258 tetraploid and three diploid cultivars by a genotyping-by-sequencing approach using methylation-sensitive restriction enzymes. This resulted in an enrichment of sequences in gene-rich regions. Population structure analyses using genetic distances and hierarchical clustering revealed strong kinship but weak overall population structure cultivars. A genome-wide association study (GWAS) was conducted with a subset of 20 K stringently filtered SNPs to identify quantitative trait loci (QTL) linked to heat tolerance. We identified 67 QTL and established haploblock boundaries to narrow down the number of candidate genes. Additionally, GO-enrichment analyses provided insights into gene functions. Heritability and genomic prediction were conducted to assess the usability of the collected data for selecting breeding material. The detected QTL might be exploited in marker-assisted selection to develop heat-resilient potato cultivars.

A stepwise guide for pangenome development in crop plants: an alfalfa (Medicago sativa) case study

BACKGROUND

The concept of pangenomics and the importance of structural variants is gaining recognition within the plant genomics community. Due to advancements in sequencing and computational technology, it has become feasible to sequence the entire genome of numerous individuals of a single species at a reasonable cost. Pangenomes have been constructed for many major diploid crops, including rice, maize, soybean, sorghum, pearl millet, peas, sunflower, grapes, and mustards. However, pangenomes for polyploid species are relatively scarce and are available in only few crops including wheat, cotton, rapeseed, and potatoes.

MAIN BODY

In this review, we explore the various methods used in crop pangenome development, discussing the challenges and implications of these techniques based on insights from published pangenome studies. We offer a systematic guide and discuss the tools available for constructing a pangenome and conducting downstream analyses. Alfalfa, a highly heterozygous, cross pollinated and autotetraploid forage crop species, is used as an example to discuss the concerns and challenges offered by polyploid crop species. We conducted a comparative analysis using linear and graph-based methods by constructing an alfalfa graph pangenome using three publicly available genome assemblies. To illustrate the intricacies captured by pangenome graphs for a complex crop genome, we used five different gene sequences and aligned them against the three graph-based pangenomes. The comparison of the three graph pangenome methods reveals notable variations in the genomic variation captured by each pipeline.

CONCLUSION

Pangenome resources are proving invaluable by offering insights into core and dispensable genes, novel gene discovery, and genome-wide patterns of variation. Developing user-friendly online portals for linear pangenome visualization has made these resources accessible to the broader scientific and breeding community. However, challenges remain with graph-based pangenomes including compatibility with other tools, extraction of sequence for regions of interest, and visualization of genetic variation captured in pangenome graphs. These issues necessitate further refinement of tools and pipelines to effectively address the complexities of polyploid, highly heterozygous, and cross-pollinated species.

QTL discovery for agronomic and quality traits in diploid potato clones using PotatoMASH amplicon sequencing

We genotyped a population of 618 diploid potato clones derived from six independent potato-breeding programmes from NW-Europe. The diploids were phenotyped for 23 traits, using standardized protocols and common check varieties, enabling us to derive whole population estimators for most traits. We subsequently performed a genome-wide association study (GWAS) to identify quantitative trait loci (QTL) for all traits with SNPs and short-read haplotypes derived from read-backed phasing. In this study, we used a marker platform called PotatoMASH (Potato Multi-Allele Scanning Haplotags); a pooled multiplex amplicon sequencing based approach. Through this method, neighboring SNPs within an amplicon can be combined to generate multiallelic short-read haplotypes (haplotags) that capture recombination history between the constituent SNPs and reflect the allelic diversity of a given locus in a different way than single bi-allelic SNPs. We found a total of 37 unique QTL across both marker types. A core of 10 QTL was detected with SNPs as well as with haplotags. Haplotags allowed to detect an additional 14 QTL not found based on the SNP set. Conversely, the bi-allelic SNP set also found 13 QTL not detectable using the haplotag set. We conclude that both marker types should routinely be used in parallel to maximize the QTL detection power. We report 19 novel QTL for nine traits: Skin Smoothness, Sprout Dormancy, Total Tuber Number, Tuber Length, Yield, Chipping Color, After-cooking Blackening, Cooking Type, and Eye depth.

Targeted genotyping-by-sequencing of potato and data analysis with R/polyBreedR

Mid-density targeted genotyping-by-sequencing (GBS) combines trait-specific markers with thousands of genomic markers at an attractive price for linkage mapping and genomic selection. A 2.5K targeted GBS assay for potato (Solanum tuberosum L.) was developed using the DArTag technology and later expanded to 4K targets. Genomic markers were selected from the potato Infinium single nucleotide polymorphism (SNP) array to maximize genome coverage and polymorphism rates. The DArTag and SNP array platforms produced equivalent dendrograms in a test set of 298 tetraploid samples, and 83% of the common markers showed good quantitative agreement, with RMSE (root mean squared error) <0.5. DArTag is suited for genomic selection candidates in the clonal evaluation trial, coupled with imputation to a higher density platform for the training population. Using the software polyBreedR, an R package for the manipulation and analysis of polyploid marker data, the RMSE for imputation by linkage analysis was 0.15 in a small half-diallel population (N = 85), which was significantly lower than the RMSE of 0.42 with the random forest method. Regarding high-value traits, the DArTag markers for resistance to potato virus Y, golden cyst nematode, and potato wart appeared to track their targets successfully, as did multi-allelic markers for maturity and tuber shape. In summary, the potato DArTag assay is a transformative and publicly available technology for potato breeding and genetics.

To be or not to be tetraploid-the impact of marker ploidy on genomic prediction and GWAS of potato

Cultivated potato, Solanum tuberosum L., is considered an autotetraploid with 12 chromosomes with four homologous phases. However, recent evidence found that, due to frequent large phase deletions in the genome, gene ploidy is not constant across the genome. The elite cultivar "Otava" was found to have an average gene copy number of 3.2 across all loci. Breeding programs for elite potato cultivars rely increasingly on genomic prediction tools for selection breeding and elucidation of quantitative trait loci underpinning trait genetic variance. These are typically based on anonymous single nucleotide polymorphism (SNP) markers, which are usually called from, for example, SNP array or sequencing data using a tetraploid model. In this study, we analyzed the impact of using whole genome markers genotyped as either tetraploid or observed allele frequencies from genotype-by-sequencing data on single-trait additive genomic best linear unbiased prediction (GBLUP) genomic prediction (GP) models and single-marker regression genome-wide association studies of potato to evaluate the implications of capturing varying ploidy on the statistical models employed in genomic breeding. A panel of 762 offspring of a diallel cross of 18 parents of elite breeding material was used for modeling. These were genotyped by sequencing and phenotyped for five key performance traits: chipping quality, length/width ratio, senescence, dry matter content, and yield. We also estimated the read coverage required to confidently discriminate between a heterozygous triploid and tetraploid state from simulated data. It was found that using a tetraploid model neither impaired nor improved genomic predictions compared to using the observed allele frequencies that account for true marker ploidy. In genome-wide associations studies (GWAS), very minor variations of both signal amplitude and number of SNPs supporting both minor and major quantitative trait loci (QTLs) were observed between the two data sets. However, all major QTLs were reproducible using both data sets.

Genotyping-by-sequencing and weighted gene co-expression network analysis of genes responsive against Potato virus Y in commercial potato cultivars

Potato is considered a key component of the global food system and plays a vital role in strengthening world food security. A major constraint to potato production worldwide is the Potato Virus Y (PVY), belonging to the genus Potyvirus in the family of Potyviridae. Selective breeding of potato with resistance to PVY pathogens remains the best method to limit the impact of viral infections. Understanding the genetic diversity and population structure of potato germplasm is important for breeders to improve new cultivars for the sustainable use of genetic materials in potato breeding to PVY pathogens. While, genetic diversity improvement in modern potato breeding is facing increasingly narrow genetic basis and the decline of the genetic diversity. In this research, we performed genotyping-by-sequencing (GBS)-based diversity analysis on 10 commercial potato cultivars and weighted gene co-expression network analysis (WGCNA) to identify candidate genes related to PVY-resistance. WGCNA is a system biology technique that uses the WGCNA R software package to describe the correlation patterns between genes in multiple samples. In terms of consumption, these cultivars are a high rate among Iranian people. Using population structure analysis, the 10 cultivars were clustered into three groups based on the 118343 single nucleotide polymorphisms (SNPs) generated by GBS. Read depth ranged between 5 and 18. The average data size and Q30 of the reads were 145.98 Mb and 93.63%, respectively. Based on the WGCNA and gene expression analysis, the StDUF538, StGTF3C5, and StTMEM161A genes were associated with PVY resistance in the potato genome. Further, these three hub genes were significantly involved in defense mechanism where the StTMEM161A was involved in the regulation of alkalization apoplast, the StDUF538 was activated in the chloroplast degradation program, and the StGTF3C5 regulated the proteins increase related to defense in the PVY infected cells. In addition, in the genetic improvement programs, these hub genes can be used as genetic markers for screening commercial cultivars for PVY resistance. Our survey demonstrated that the combination of GBS-based genetic diversity germplasm analysis and WGCNA can assist breeders to select cultivars resistant to PVY as well as help design proper crossing schemes in potato breeding.

Is there hybridization between 2 species of the same genus in sympatry?-The genetic relationships between Anoplophora glabripennis, Anoplophora chinensis, and putative hybrids

Anoplophora glabripennis (Asian longhorn beetle, ALB) and Anoplophora chinensis (Citrus longhorn beetle, CLB) are native forest pests in China; they have become important international quarantine pests. They are found using the same Salix aureo-pendula host tree of Cixi, Zhejiang province, China. On this host tree, we collected additional beetles that appeared to be morphologically intermediate between ALB and CLB. By using a stereoscope, we observed that there were several bumps on the base of the elytra, which was inconsistent with ALB, which typically has a smooth elytral base, but was more like CLB, which has numerous short tubercles on the elytral base. Given their sympatry and intermediate morphology, we hypothesized that these may represent ALB × CLB hybrids. We studied the genomic profiles for 46 samples (ALB, CLB, and putative hybrids) using genotyping-by-sequencing (GBS) providing a reduced representation of the entire genome. Employing principal component analyses on the 163 GBS-derived single nucleotide polymorphism data, we found putative hybrids tightly clustered with ALB, but genetically distinct from the CLB individuals. Therefore, our initial hybrid hypothesis was not supported by genomic data. Further, while mating experiments between adult ALB and CLB were successful in 4 separate years (2017, 2018, 2020, and 2021), and oviposition behavior was observed, no progeny was produced. Having employed population genomic analysis and biological hybridization experiments, we conclude that the putative hybrids represent newly discovered morphological variants within ALB. Our approach further confirmed the advantage of genome-wide information for Anoplophora species assignment in certain ambiguous classification cases.

QTL identified that influence tuber length-width ratio, degree of flatness, tuber size, and specific gravity in a russet-skinned, tetraploid mapping population

Potato tuber shape, size, and specific gravity are important agronomic traits in the russet market class of potatoes with an impact on quality, consistency, and product recovery of processed foods such as French fries. Therefore, identifying genetic regions associated with the three traits through quantitative trait locus/loci (QTL) analysis is a crucial process in the subsequent development of marker-assisted selection for use in potato breeding programs. QTL analysis was conducted on a tetraploid mapping population consisting of 190 individuals derived from the cross between two russet-skinned parents, Palisade Russet and the breeding clone ND028673B-2Russ. Field data collected over a 2-year period and used in the QTL analyses included tuber length-width and width-depth ratios that were obtained using a digital caliper. The width-depth ratio provided an assessment of the "flatness" of a tuber, which is of importance in potato processing. To cross-validate the accuracy and differences among tuber shape measurement methods, a trained evaluator also assessed the identical tubers based on 1-5 scale (compressed to long) visual assessment method. Furthermore, the weights of analyzed tubers and specific gravities were also collected during the phenotyping process for each mapping clone. A major tuber shape QTL was consistently observed on chromosome 10 with both the length-width ratio and visual assessments. On chromosome 4, a significant QTL for tuber shape from the visual assessment phenotypic data was also detected. Additionally, a tuber shape-related QTL on chromosome 6 was also detected from the length-width ratio data from 2020. Chromosome 2 was also identified as having a significant QTL for the width-depth ratio, which is of importance in influencing the flatness of a tuber. One significant QTL for tuber weight (i.e., tuber size) was observed on chromosome 5, and a significant QTL for specific gravity was found on chromosome 3. These significant and major QTL should be useful for developing marker-assisted selection for more efficient potato breeding.

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.

Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data

KEY MESSAGE

An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Impact of genotype-calling methodologies on genome-wide association and genomic prediction in polyploids

Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost-efficient genotyping using next-generation sequencing. However, accurate genotype calling from next-generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome-wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype-calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum, and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype-calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost-efficiently implement GWAS and genomic prediction in polyploid crops.

Genome-wide association mapping and genomic prediction for late blight and potato cyst nematode resistance in potato (Solanum tuberosum L.)

Potatoes are an important source of food for millions of people worldwide. Biotic stresses, notably late blight and potato cyst nematodes (PCN) pose a major threat to potato production worldwide, and knowledge of genes controlling these traits is limited. A genome-wide association mapping study was conducted to identify the genomic regulators controlling these biotic stresses, and the genomic prediction accuracy was worked out using the GBLUP model of genomic selection (GS) in a panel of 222 diverse potato accessions. The phenotype data on resistance to late blight and two PCN species (Globodera pallida and G. rostochiensis) were recorded for three and two consecutive years, respectively. The potato panel was genotyped using genotyping by sequencing (GBS), and 1,20,622 SNP markers were identified. A total of 7 SNP associations for late blight resistance, 9 and 11 for G. pallida and G. rostochiensis, respectively, were detected by additive and simplex dominance models of GWAS. The associated SNPs were distributed across the chromosomes, but most of the associations were found on chromosomes 5, 10 and 11, which have been earlier reported as the hotspots of disease-resistance genes. The GS prediction accuracy estimates were low to moderate for resistance to G. pallida (0.04-0.14) and G. rostochiensis (0.14-0.21), while late blight resistance showed a high prediction accuracy of 0.42-0.51. This study provides information on the complex genetic nature of these biotic stress traits in potatoes and putative SNP markers for resistance breeding.

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.

Assessment of the Genetic Diversity and Population Structure of the Peruvian Andean Legume, Tarwi (Lupinus mutabilis), with High Quality SNPs

Lupinus mutabilis Sweet (Fabaceae), “tarwi” or “chocho”, is an important grain legume in the Andean region. In Peru, studies on tarwi have mainly focused on morphological features; however, they have not been molecularly characterized. Currently, it is possible to explore the genetic parameters of plants with reliable and modern methods such as genotyping by sequencing (GBS). Here, for the first time, we used single nucleotide polymorphism (SNP) markers to infer the genetic diversity and population structure of 89 accessions of tarwi from nine Andean regions of Peru. A total of 5922 SNPs distributed along all chromosomes of tarwi were identified. STRUCTURE analysis revealed that this crop is grouped into two clusters. A dendrogram was generated using the UPGMA clustering algorithm and, like the principal coordinate analysis (PCoA), it showed two groups that correspond to the geographic origin of the tarwi samples. AMOVA showed a reduced variation between clusters (7.59%) and indicated that variability within populations is 92.41%. Population divergence (Fst) between clusters 1 and 2 revealed low genetic difference (0.019). We also detected a negative Fis for both populations, demonstrating that, like other Lupinus species, tarwi also depends on cross-pollination. SNP markers were powerful and effective for the genotyping process in this germplasm. We hope that this information is the beginning of the path towards a modern genetic improvement and conservation strategies of this important Andean legume.

Application of SolCAP Genotyping in Potato (Solanum tuberosum L.) Association Mapping

Potato variety development entails a number of breeding steps, as well as testing and, finally, commercialization. Historically, phenotypic assesment were carried out to select and germplasm development. The US Department of Agriculture (USDA) funded the Solanaceae Coordinated Agricultural Project (SolCAP) to decode genomic resources into tools that breeders and geneticists can use. This project resulted in the creation of a genome-wide single-nucleotide polymorphism (SNP) array that can be used to evaluate elite potato-breeding germplasm. This array was used to genotype a diverse panel of Solanum species, as well as numerous biparental, diploid, and tetraploid populations. It has high marker density to generate genetic maps that can be used to identify numerous quantitative trait loci (QTLs) for agronomic, quality, biotic, and abiotic resistance traits. Up to now, numerous QTLs for important traits have been identified using new diploid and tetraploid genetic maps. SNP markers were used to assess germplasm relationships and fingerprint varieties and identify candidate genes. The Infinium 8303 SolCAP Potato array offers a common set of SNP markers that can be used for mapping, germplasm assessment, and fingerprinting with confidence. This array has also been helpful in furthering our understanding of the potato genome. Furthermore, some other Infinium potato arrays (i.e., 12 K, 20 K, and 25 K) have been genotyped, and breeders can map quantitative trait loci (QTLs) across multiple populations to improve our understanding of economically important traits and lead to marker-assisted selection (MAS) and breeding and, ultimately, improved varieties.

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.

GWAS in tetraploid potato: identification and validation of SNP markers associated with glycoalkaloid content

Genome-wide association studies (GWAS) are a useful tool to unravel the genetic architecture of complex traits, but the results can be difficult to interpret. Population structure, genetic heterogeneity, and rare alleles easily result in false positive or false negative associations. This paper describes the analysis of a GWAS panel combined with three bi-parental mapping populations to validate GWAS results, using phenotypic data for steroidal glycoalkaloid (SGA) accumulation and the ratio (SGR) between the two major glycoalkaloids α-solanine and α-chaconine in potato tubers. SGAs are secondary metabolites in the Solanaceae family, functional as a defence against various pests and pathogens and in high quantities toxic for humans. With GWAS, we identified five quantitative trait loci (QTL) of which Sga1.1, Sgr8.1, and Sga11.1 were validated, but not Sga3.1 and Sgr7.1. In the bi-parental populations, Sga5.1 and Sga7.1 were mapped, but these were not identified with GWAS. The QTLs Sga1.1, Sga7.1, Sgr7.1, and Sgr8.1 co-localize with genes GAME9, GAME 6/GAME 11, SGT1, and SGT2, respectively. For other genes involved in SGA synthesis, no QTLs were identified. The results of this study illustrate a number of pitfalls in GWAS of which population structure seems the most important. We also show that introgression breeding for disease resistance has introduced new haplotypes to the gene pool involved in higher SGA levels in certain pedigrees. Finally, we show that high SGA levels remain unpredictable in potato but that α-solanine/α-chaconine ratio has a predictable outcome with specific SGT1 and SGT2 haplotypes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01344-2.

Genomic selection in tropical perennial crops and plantation trees: a review

To overcome the multiple challenges currently faced by agriculture, such as climate change and soil deterioration, more efficient plant breeding strategies are required. Genomic selection (GS) is crucial for the genetic improvement of quantitative traits, as it can increase selection intensity, shorten the generation interval, and improve selection accuracy for traits that are difficult to phenotype. Tropical perennial crops and plantation trees are of major economic importance and have consequently been the subject of many GS articles. In this review, we discuss the factors that affect GS accuracy (statistical models, linkage disequilibrium, information concerning markers, relatedness between training and target populations, the size of the training population, and trait heritability) and the genetic gain expected in these species. The impact of GS will be particularly strong in tropical perennial crops and plantation trees as they have long breeding cycles and constrained selection intensity. Future GS prospects are also discussed. High-throughput phenotyping will allow constructing of large training populations and implementing of phenomic selection. Optimized modeling is needed for longitudinal traits and multi-environment trials. The use of multi-omics, haploblocks, and structural variants will enable going beyond single-locus genotype data. Innovative statistical approaches, like artificial neural networks, are expected to efficiently handle the increasing amounts of heterogeneous multi-scale data. Targeted recombinations on sites identified from profiles of marker effects have the potential to further increase genetic gain. GS can also aid re-domestication and introgression breeding. Finally, GS consortia will play an important role in making the best of these opportunities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01326-4.

The genetic architectures of vine and skin maturity in tetraploid potato

The genetic architectures of potato vine and skin maturity, as well as the correlation between the traits, were investigated using multiple techniques from quantitative genetics and genomics. Potato vine and skin maturity, which refer to foliar senescence and adherence of the tuber periderm, respectively, are both important to production and therefore breeding. Our objective was to investigate the genetic architectures of these traits in a genome-wide association panel of 586 genotypes, and through joint linkage mapping in a half-diallel subset (N = 397). Skin maturity was measured by image analysis after mechanized harvest 120 days after planting. To correct for the influence of vine maturity on skin maturity under these conditions, the former was used as a covariate in the analysis. The genomic heritability based on a 10 K SNP array was 0.33 for skin maturity vs. 0.46 for vine maturity. Only minor QTLs were detected for skin maturity, the largest being on chromosome 9 and explaining 8% of the variation. As in many previous studies, S. tuberosum Cycling DOF Factor 1 (CDF1) had a large influence on vine maturity, explaining 33% of the variation in the panel as a bi-allelic SNP and 44% in the half-diallel as a multi-allelic QTL. From the estimated effects of the parental haplotypes in the half-diallel and prior knowledge of the allelic series for CDF1, the CDF1 allele for each haplotype was predicted and ultimately confirmed through whole-genome sequencing. The ability to connect statistical alleles from QTL models with biological alleles based on DNA sequencing represents a new milestone in genomics-assisted breeding for tetraploid species.

Descriptive Genomic Analysis and Sequence Genotyping of the Two Papaya Species (Vasconcellea pubescens and Vasconcellea chilensis) Using GBS Tools

A genotyping by sequencing (GBS) approach was used to analyze the organization of genetic diversity in V. pubescens and V. chilensis. GBS identified 4675 and 4451 SNPs/INDELs in two papaya species. The cultivated orchards of V. pubescens exhibited scarce genetic diversity and low but significant genetic differentiation. The neutrality test yielded a negative and significant result, suggesting that V. pubescens suffered a selective sweep or a rapid expansion after a bottleneck during domestication. In contrast, V. chilensis exhibited a high level of genetic diversity. The genetic differentiation among the populations was slight, but it was possible to distinguish the two genetic groups. The neutrality test indicated no evidence that natural selection and genetic drift affect the natural population of V. chilensis. Using the Carica papaya genome as a reference, we identified critical SNPs/INDELs associated with putative genes. Most of the identified genes are related to stress responses (salt and nematode) and vegetative and reproductive development. These results will be helpful for future breeding and conservation programs of the Caricaceae family.

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.

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Allows phasing of autopolyploid species through genetic information of progenies

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High number of low-depth progeny samples yields significant markers for phasing

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Informative variant types (simplex-nulliplex) phasable with high confidence

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Continuity not limited by read connectivity, but rather by the recombination rate

Potato Cultivar Identification in South Africa Using a Custom SNP Panel

DNA fingerprinting is a molecular technique applied to identify genetic differences between plant cultivars or lines and is used for genetic purity testing. The suitability of single nucleotide polymorphism (SNP) panels for the fingerprinting of tetraploid potato were investigated as a new high throughput, objective, and cost-effective method instead of simple sequence repeats (SSRs) and polyacrylamide gel electrophoresis (PAGE). One-hundred and ninety (190) potato cultivars, including various cultivars currently important in South Africa, were genotyped at 500 SNP positions utilising SeqSNP by LGC Biosearch Technologies. An optimal panel of 25 SNP markers was identified that could discriminate between South African potato cultivars on genetic allele dosage. The genotypes of these SNPs were validated on selected potato genotypes using KASP (Kompetitive Allele Specific PCR) SNP assays. A database of SNP genotype profiles was compiled for all the entries of the germplasm database. The panel of 21 successful SNPs accurately identified the unique potato cultivars in the database. The KASP SNP assays of the successful SNP panel are therefore available for potato DNA fingerprinting as new germplasm, or purity test requests are submitted to ARC-VIMP. This panel provides an objective method for assigning putative cultivar identity to unknown samples submitted for fingerprinting.

Genetic Diversity Trends in the Cultivated Potato: A Spatiotemporal Overview

Simple Summary

Monitoring the change in genetic diversity over time and space in crop species is essential to facilitating further improvement. As the world’s most important tuber crop for human consumption, and an ideal candidate to help address global food security, the cultivated potato deserves in-depth study in this regard. In this overview, some aspects of spatiotemporal diversity assessment in the cultivated potato are examined with the aim of promoting appropriate strategies for breeding programs in line with challenges relating to sustainable crop production.

Abstract

We investigated the changes in genetic diversity over time and space of the cultivated potato (Solanum tuberosum L.) for the period pre-1800 to 2021. A substantial panel of 1219 potato varieties, belonging to different spatiotemporal groups, was examined using a set of 35 microsatellite markers (SSR). Genotypic data covering a total of 407 alleles was analyzed using both self-organizing map (SOM) and discriminant analysis of principal components (DAPC) de novo and a priori clustering methods, respectively. Data analysis based on different models of genetic structuring provided evidence of (1) at least two early lineages that have been maintained since their initial introduction from the Andes into Europe in the 16th century, followed by later ones coming from reintroduction events from the US in the mid-1800s; (2) a level of diversity that has gradually evolved throughout the studied time periods and areas, with the most modern variety groups encompassing most of the diversity found in earlier decades; (3) the emergence of new genetic groups within the current population due to increases in the use of germplasm enhancement practices using exotic germplasms. In addition, analysis revealed significant genetic differentiation both among and within the spatiotemporal groups of germplasm studied. Our results therefore highlight that no major genetic narrowing events have occurred within the cultivated potato over the past three centuries. On the contrary, the genetic base shows promising signs of improvement, thanks to extensive breeding work that is gaining momentum. This overview could be drawn on not only to understand better how past decisions have impacted the current genetic cultivated potato resources, but also to develop appropriate new strategies for breeding programs consistent with the socio-economic and sustainability challenges faced by agrifood systems.

Two fingerprinting sets for Humulus lupulus based on KASP and microsatellite markers

Verification of clonal identity of hop (Humulus lupulus L.) cultivars within breeding programs and germplasm collections is vital to conserving genetic resources. Accurate and economic DNA-based tools are needed in dioecious hop to confirm identity and parentage, neither of which can be reliably determined from morphological observations. In this study, we developed two fingerprinting sets for hop: a 9-SSR fingerprinting set containing high-core repeats that can be run in a single PCR reaction and a kompetitive allele specific PCR (KASP) assay of 25 single nucleotide polymorphisms (SNPs). The SSR set contains a sex-linked primer pair, HI-AGA7, that was used to genotype 629 hop accessions from the US Department of Agriculture (USDA) National Clonal Germplasm Repository (NCGR), the USDA Forage Seed and Cereal Research (FSCR), and the University of Nebraska-Lincoln (UNL) collections. The SSR set identified unique genotypes except for 89 sets of synonymous samples. These synonyms included: cultivars with different designations, the same cultivars from different sources, heat-treated clones, and clonal variants. Population structure analysis clustered accessions into wild North American (WNA) and cultivated groups. Diversity was slightly higher in the cultivated samples due to larger sample size. Parentage and sib-ship analyses were used to identify true-to-type cultivars. The HI-AGA7 marker generated two male- and nine female-specific alleles among the cultivated and WNA samples. The SSR and KASP fingerprinting sets were compared in 190 samples consisting of cultivated and WNA accession for their ability to confirm identity and assess diversity and population structure. The SSR fingerprinting set distinguished cultivars, selections and WNA accessions while the KASP assays were unable to distinguish the WNA samples and had lower diversity estimates than the SSR set. Both fingerprinting sets are valuable tools for identity confirmation and parentage analysis in hop for different purposes. The 9-SSR assay is cost efficient when genotyping a small number of wild and cultivated hop samples (<96) while the KASP assay is easy to interpret and cost efficient for genotyping a large number of cultivated samples (multiples of 96).

Mapping of Nematode Resistance in Hexaploid Sweetpotato Using an Next-Generation Sequencing-Based Association Study

The southern root-knot nematode (SRKN; Meloidogyne incognita) is a typical parasitic nematode that affects sweetpotato [Ipomoea batatas (L.) Lam.], causing a significant decrease in crop yield and commercial value. In Japan, the SRKN is classified into 10 races: SP1-SP5, SP6-1, SP6-2, and SP7-SP9, with the dominant race differing according to the cultivation area. Soil insecticides have previously been used to reduce the soil density of SRKNs; however, this practice is both costly and labor intensive. Therefore, the development of SRKN-resistant sweetpotato lines and cultivars is necessary. However, due to the complexity of polyploid inheritance and the highly heterogeneous genomic composition of sweetpotato, genetic information and research for this species are significantly lacking compared to those for other major diploid crop species. In this study, we utilized the recently developed genome-wide association approach, which uses multiple-dose markers to assess autopolyploid species. We performed an association analysis to investigate resistance toward SRKN-SP2, which is the major race in areas with high sweetpotato production in Japan. The segregation ratio of resistant and susceptible lines in the F₁ mapping population derived from the resistant "J-Red" and susceptible "Choshu" cultivars was fitted to 1: 3, suggesting that resistance to SP2 may be regulated by two loci present in the simplex. By aligning the double digest restriction-site associated DNA sequencing reads to the published Ipomoea trifida reference sequence, 46,982 single nucleotide polymorphisms (SNPs) were identified (sequencing depth > 200). The association study yielded its highest peak on chromosome 7 (Chr07) and second highest peak on chromosome 3 (Chr03), presenting as a single-dose in both loci. Selective DNA markers were developed to screen for resistant plants using the SNPs identified on Chr03 and Chr07. Our results showed that SRKN-SP2-resistant plants were selected with a probability of approximately 70% when combining the two selective DNA markers. This study serves as a model for the identification of genomic regions that control agricultural traits and the elucidation of their effects, and is expected to greatly advance marker-assisted breeding and association studies in polyploid crop species.

Allelic variation for alpha-Glucan Water Dikinase is associated with starch phosphate content in tetraploid potato

Association analysis resulted in the identification of specific StGWD alleles causing either an increase or decrease in starch phosphate content which was verified in diploid and tetraploid potato mapping populations. Potatoes are grown for various purposes like French fries, table potatoes, crisps and for their starch. One of the most important aspects of potato starch is that it contains a high amount of phosphate ester groups which are considered to be important for providing improved functionalization after derivatization processes. Little is known about the variation in phosphate content as such in different potato varieties and thus we studied the genetic diversity for this trait. From other studies it was clear that the phosphate content is controlled by a quantitative trait locus (QTL) underlying the candidate gene α-Glucan Water Dikinase (StGWD) on chromosome 5. We performed direct amplicon sequencing of this gene by Sanger sequencing. Sequences of two StGWD amplicons from a global collection of 398 commercial cultivars and progenitor lines were used to identify 16 different haplotypes. By assigning tag SNPs to these haplotypes, each of the four alleles present in a cultivar could be deduced and linked to a phosphate content. A high value for intra-individual heterozygosity was observed (Ho = 0.765). The average number of different haplotypes per individual (Ai) was 3.1. Pedigree analysis confirmed that the haplotypes are identical-by-descent (IBD) and offered insight in the breeding history of elite potato germplasm. Haplotypes originating from introgression of wild potato accessions carrying resistance genes could be traced. Furthermore, association analysis resulted in the identification of specific StGWD alleles causing either an increase or decrease in starch phosphate content varying from 12 nmol PO₄/mg starch to 38 nmol PO₄/mg starch. These allele effects were verified in diploid and tetraploid mapping populations and offer possibilities to breed and select for this trait.

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.

Benchmarking small-variant genotyping in polyploids

Genotyping from sequencing is the basis of emerging strategies in the molecular breeding of polyploid plants. However, compared with the situation for diploids, in which genotyping accuracies are confidently determined with comprehensive benchmarks, polyploids have been neglected; there are no benchmarks measuring genotyping error rates for small variants using real sequencing reads. We previously introduced a variant calling method, Octopus, that accurately calls germline variants in diploids and somatic mutations in tumors. Here, we evaluate Octopus and other popular tools on whole-genome tetraploid and hexaploid data sets created using in silico mixtures of diploid Genome in a Bottle (GIAB) samples. We find that genotyping errors are abundant for typical sequencing depths but that Octopus makes 25% fewer errors than other methods on average. We supplement our benchmarks with concordance analysis in real autotriploid banana data sets.

flopp: Extremely Fast Long-Read Polyploid Haplotype Phasing by Uniform Tree Partitioning

Resolving haplotypes in polyploid genomes using phase information from sequencing reads is an important and challenging problem. We introduce two new mathematical formulations of polyploid haplotype phasing: (1) the min-sum max tree partition problem, which is a more flexible graphical metric compared with the standard minimum error correction (MEC) model in the polyploid setting, and (2) the uniform probabilistic error minimization model, which is a probabilistic analogue of the MEC model. We incorporate both formulations into a long-read based polyploid haplotype phasing method called flopp. We show that flopp compares favorably with state-of-the-art algorithms-up to 30 times faster with 2 times fewer switch errors on 6 × ploidy simulated data. Further, we show using real nanopore data that flopp can quickly reveal reasonable haplotype structures from the autotetraploid Solanum tuberosum (potato).

When do autopolyploids need poly-sequencing data?

The sequencing depth required to genotype autopolyploid populations is a very controversial topic. Different studies have adopted variable depth values without a clear guide on the optimal sequencing depth value. Many studies suggest high depth thresholds for different ploidies that may not be practical and substantially increase the overall genotyping cost for different projects. However, such conservative thresholds may not be required to achieve the most common research goals. In fact, some recent reports in the field of quantitative genetics found that much lower sequencing depth thresholds could achieve the same accuracy as high depth thresholds. In this manuscript, I discuss when researchers need to use stringent sequencing depth thresholds and when they can use more relaxed ones. I support my argument by calculating the probabilities of sampling different homologues at a given sequencing depth. I also discuss the uses and the uncertainty in calculating a continuous allelic dosage as the proportion of sequencing reads that hold the alternative allele, which is becoming a common method now in quantitative genetics to replace discrete dosage estimation.

Strategies to Increase Prediction Accuracy in Genomic Selection of Complex Traits in Alfalfa (Medicago sativa L.)

Agronomic traits such as biomass yield and abiotic stress tolerance are genetically complex and challenging to improve through conventional breeding approaches. Genomic selection (GS) is an alternative approach in which genome-wide markers are used to determine the genomic estimated breeding value (GEBV) of individuals in a population. In alfalfa (Medicago sativa L.), previous results indicated that low to moderate prediction accuracy values (<70%) were obtained in complex traits, such as yield and abiotic stress resistance. There is a need to increase the prediction value in order to employ GS in breeding programs. In this paper we reviewed different statistic models and their applications in polyploid crops, such as alfalfa and potato. Specifically, we used empirical data affiliated with alfalfa yield under salt stress to investigate approaches that use DNA marker importance values derived from machine learning models, and genome-wide association studies (GWAS) of marker-trait association scores based on different GWASpoly models, in weighted GBLUP analyses. This approach increased prediction accuracies from 50% to more than 80% for alfalfa yield under salt stress. Finally, we expended the weighted GBLUP approach to potato and analyzed 13 phenotypic traits and obtained similar results. This is the first report on alfalfa to use variable importance and GWAS-assisted approaches to increase the prediction accuracy of GS, thus helping to select superior alfalfa lines based on their GEBVs.

Continuous Mapping Identifies Loci Associated With Weevil Resistance [Cosmopolites sordidus (Germar)] in a Triploid Banana Population

The first step toward marker-assisted selection is linking the phenotypes to molecular markers through quantitative trait loci (QTL) analysis. While the process is straightforward in self-pollinating diploid (2x) species, QTL analysis in polyploids requires unconventional methods. In this study, we have identified markers associated with weevil Cosmopolites sordidus (Germar) resistance in bananas using 138 triploid (2n = 3x) hybrids derived from a cross between a tetraploid "Monyet" (2n = 4x) and a 2x "Kokopo" (2n = 2x) banana genotypes. The population was genotyped by Diversity Arrays Technology Sequencing (DArTSeq), resulting in 18,009 polymorphic single nucleotide polymorphisms (SNPs) between the two parents. Marker-trait association was carried out by continuous mapping where the adjusted trait means for the corm peripheral damage (PD) and total cross-section damage (TXD), both on the logit scale, were regressed on the marker allele frequencies. Forty-four SNPs that were associated with corm PD were identified on the chromosomes 5, 6, and 8, with 41 of them located on chromosome 6 and segregated in "Kokopo." Eleven SNPs associated with corm total TXD were identified on chromosome 6 and segregated in "Monyet." The additive effect of replacing one reference allele with the alternative allele was determined at each marker position. The PD QTL was confirmed using conventional QTL linkage analysis in the simplex markers segregating in "Kokopo" (AAAA × RA). We also identified 43 putative genes in the vicinity of the markers significantly associated with the two traits. The identified loci associated with resistance to weevil damage will be used in the efforts of developing molecular tools for marker-assisted breeding in bananas.

Genetic loci associated with winter survivorship in diverse lowland switchgrass populations

High winter mortality limits biomass yield of lowland switchgrass (Panicum virgatum L.) planted in the northern latitudes of North America. Breeding of cold tolerant switchgrass cultivars requires many years due to its perennial growth habit and the unpredictable winter selection pressure that is required to identify winter-hardy individuals. Identification of causal genetic variants for winter survivorship would accelerate the improvement of switchgrass biomass production. The objective of this study was to identify allelic variation associated with winter survivorship in lowland switchgrass populations using bulk segregant analysis (BSA). Twenty-nine lowland switchgrass populations were evaluated for winter survival at two locations in southern Wisconsin and 21 populations with differential winter survivorship were used for BSA. A maximum of 10% of the individuals (8-20) were bulked to create survivor and nonsurvivor DNA pools from each population and location. The DNA pools were evaluated using exome capture sequencing, and allele frequencies were used to conduct statistical tests. The BSA tests revealed nine quatitative trait loci (QTL) from tetraploid populations and seven QTL from octoploid populations. Many QTL were population-specific, but some were identified in multiple populations that originated across a broad geographic landscape. Four QTL (at positions 88 Mb on chromosome 2N, 115 Mb on chromosome 5K, and 1 and 100 Mb on chromosome 9N) were potentially the most useful QTL. Markers associated with winter survivorship in this study can be used to accelerate breeding cycles of lowland switchgrass populations and should lead to improvements in adaptation within USDA hardiness zones 4 and 5.

Haplotype reconstruction in connected tetraploid F1 populations

In diploid species, many multiparental populations have been developed to increase genetic diversity and quantitative trait loci (QTL) mapping resolution. In these populations, haplotype reconstruction has been used as a standard practice to increase the power of QTL detection in comparison with the marker-based association analysis. However, such software tools for polyploid species are few and limited to a single biparental F1 population. In this study, a statistical framework for haplotype reconstruction has been developed and implemented in the software PolyOrigin for connected tetraploid F1 populations with shared parents, regardless of the number of parents or mating design. Given a genetic or physical map of markers, PolyOrigin first phases parental genotypes, then refines the input marker map, and finally reconstructs offspring haplotypes. PolyOrigin can utilize single nucleotide polymorphism (SNP) data coming from arrays or from sequence-based genotyping; in the latter case, bi-allelic read counts can be used (and are preferred) as input data to minimize the influence of genotype calling errors at low depth. With extensive simulation we show that PolyOrigin is robust to the errors in the input genotypic data and marker map. It works well for various population designs with ≥30 offspring per parent and for sequences with read depth as low as 10x. PolyOrigin was further evaluated using an autotetraploid potato dataset with a 3 × 3 half-diallel mating design. In conclusion, PolyOrigin opens up exciting new possibilities for haplotype analysis in tetraploid breeding populations.

Quantitative Trait Locus Mapping for Common Scab Resistance in a Tetraploid Potato Full-Sib Population

Despite the negative impact of common scab (Streptomyces spp.) on the potato industry, little is known about the genetic architecture of resistance to this bacterial disease in the crop. We evaluated a mapping population (∼150 full sibs) derived from a cross between two tetraploid potatoes ('Atlantic' × B1829-5) in three environments (MN11, PA11, ME12) under natural common scab pressure. Three measures to common scab reaction, namely percentage of scabby tubers and disease area and lesion indices, were found to be highly correlated (>0.76). Because of the large environmental effect, heritability values were zero for all three traits in MN11, but moderate to high in PA11 and ME12 (∼0.44 to 0.79). We identified a single quantitative trait locus (QTL) for lesion index in PA11, ME12, and joint analyses on linkage group 3, explaining ∼22 to 30% of the total variation. The identification of QTL haplotypes and candidate genes contributing to disease resistance can support genomics-assisted breeding approaches in the crop.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Scalable bias-corrected linkage disequilibrium estimation under genotype uncertainty

Linkage disequilibrium (LD) estimates are often calculated genome-wide for use in many tasks, such as SNP pruning and LD decay estimation. However, in the presence of genotype uncertainty, naive approaches to calculating LD have extreme attenuation biases, incorrectly suggesting that SNPs are less dependent than in reality. These biases are particularly strong in polyploid organisms, which often exhibit greater levels of genotype uncertainty than diploids. A principled approach using maximum likelihood estimation with genotype likelihoods can reduce this bias, but is prohibitively slow for genome-wide applications. Here, we present scalable moment-based adjustments to LD estimates based on the marginal posterior distributions of the genotypes. We demonstrate, on both simulated and real data, that these moment-based estimators are as accurate as maximum likelihood estimators, but are almost as fast as naive approaches based only on posterior mean genotypes. This opens up bias-corrected LD estimation to genome-wide applications. In addition, we provide standard errors for these moment-based estimators. All methods discussed in this manuscript are implemented in the ldsep package, available on the Comprehensive R Archive Network ( https://cran.r-project.org/package=ldsep ).

Revelation of candidate genes and molecular mechanism of reproductive seasonality in female rohu (Labeo rohita Ham.) by RNA sequencing

BACKGROUND

Carp fish, rohu (Labeo rohita Ham.) is important freshwater aquaculture species of South-East Asia having seasonal reproductive rhythm. There is no holistic study at transcriptome level revealing key candidate genes involved in such circannual rhythm regulated by biological clock genes (BCGs). Seasonality manifestation has two contrasting phases of reproduction, i.e., post-spawning resting and initiation of gonadal activity appropriate for revealing the associated candidate genes. It can be deciphered by RNA sequencing of tissues involved in BPGL (Brain-Pituitary-Gonad-Liver) axis controlling seasonality. How far such BCGs of this fish are evolutionarily conserved across different phyla is unknown. Such study can be of further use to enhance fish productivity as seasonality restricts seed production beyond monsoon season.

RESULT

A total of ~ 150 Gb of transcriptomic data of four tissues viz., BPGL were generated using Illumina TruSeq. De-novo assembled BPGL tissues revealed 75,554 differentially expressed transcripts, 115,534 SSRs, 65,584 SNPs, 514 pathways, 5379 transcription factors, 187 mature miRNA which regulates candidate genes represented by 1576 differentially expressed transcripts are available in the form of web-genomic resources. Findings were validated by qPCR. This is the first report in carp fish having 32 BCGs, found widely conserved in fish, amphibian, reptile, birds, prototheria, marsupials and placental mammals. This is due to universal mechanism of rhythmicity in response to environment and earth rotation having adaptive and reproductive significance.

CONCLUSION

This study elucidates evolutionary conserved mechanism of photo-periodism sensing, neuroendocrine secretion, metabolism and yolk synthesis in liver, gonadal maturation, muscular growth with sensory and auditory perception in this fish. Study reveals fish as a good model for research on biological clock besides its relevance in reproductive efficiency enhancement.

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.

Global multi-environment resistance QTL for foliar late blight resistance in tetraploid potato with tropical adaptation

The identification of environmentally stable and globally predictable resistance to potato late blight is challenged by the clonal and polyploid nature of the crop and the rapid evolution of the pathogen. A diversity panel of tetraploid potato germplasm bred for multiple resistance and quality traits was genotyped by genotyping by sequencing (GBS) and evaluated for late blight resistance in three countries where the International Potato Center (CIP) has established breeding work. Health-indexed, in vitro plants of 380 clones and varieties were distributed from CIP headquarters and tuber seed was produced centrally in Peru, China, and Ethiopia. Phenotypes were recorded following field exposure to local isolates of Phytophthora infestans. QTL explaining resistance in four experiments conducted across the three countries were identified in chromosome IX, and environment-specific QTL were found in chromosomes III, V, and X. Different genetic models were evaluated for prediction ability to identify best performing germplasm in each and all environments. The best prediction ability (0.868) was identified with the genomic best linear unbiased predictors (GBLUPs) when using the diploid marker data and QTL-linked markers as fixed effects. Genotypes with high levels of resistance in all environments were identified from the B3, LBHT, and B3-LTVR populations. The results show that many of the advanced clones bred in Peru for high levels of late blight resistance maintain their resistance in Ethiopia and China, suggesting that the centralized selection strategy has been largely successful.

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.

Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding

Blueberry (Vaccinium corymbosum and hybrids) is a specialty crop with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to expanding production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on recurrent phenotypic selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberry breeding cycles are costly and time consuming, which results in low genetic gains per unit of time. Motivated by applying molecular markers for a more accurate selection in the early stages of breeding, we performed pioneering genomic selection studies and optimization for its implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based genotyping and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic selection studies and showed for the first time its application in an independent validation set. In this paper, our contribution is three-fold: (i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; (ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; (iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for using genomic selection in blueberry, with the potential to be applied to other polyploid species of a similar background.

Genome editing of polyploid crops: prospects, achievements and bottlenecks

Plant breeding aims to develop improved crop varieties. Many crops have a polyploid and often highly heterozygous genome, which may make breeding of polyploid crops a real challenge. The efficiency of traditional breeding based on crossing and selection has been improved by using marker-assisted selection (MAS), and MAS is also being applied in polyploid crops, which helps e.g. for introgression breeding. However, methods such as random mutation breeding are difficult to apply in polyploid crops because there are multiple homoeologous copies (alleles) of each gene. Genome editing technology has revolutionized mutagenesis as it enables precisely selecting targets. The genome editing tool CRISPR/Cas is especially valuable for targeted mutagenesis in polyploids, as all alleles and/or copies of a gene can be targeted at once. Even multiple genes, each with multiple alleles, may be targeted simultaneously. In addition to targeted mutagenesis, targeted replacement of undesirable alleles by desired ones may become a promising application of genome editing for the improvement of polyploid crops, in the near future. Several examples of the application of genome editing for targeted mutagenesis are described here for a range of polyploid crops, and achievements and bottlenecks are highlighted.

A tetrasomic inheritance model and likelihood-based method for mapping quantitative trait loci in autotetraploid species

Dissecting the genetic architecture of quantitative traits in autotetraploid species is a methodologically challenging task, but a pivotally important goal for breeding globally important food crops, including potato and blueberry, and ornamental species such as rose. Mapping quantitative trait loci (QTLs) is now a routine practice in diploid species but is far less advanced in autotetraploids, largely due to a lack of analytical methods that account for the complexities of tetrasomic inheritance. We present a novel likelihood-based method for QTL mapping in outbred segregating populations of autotetraploid species. The method accounts properly for sophisticated features of gene segregation and recombination in an autotetraploid meiosis. It may model and analyse molecular marker data with or without allele dosage information, such as that from microarray or sequencing experiments. The method developed outperforms existing bivalent-based methods, which may fail to model and analyse the full spectrum of experimental data, in the statistical power of QTL detection, and accuracy of QTL location, as demonstrated by an intensive simulation study and analysis of data sets collected from a segregating population of potato (Solanum tuberosum). The study enables QTL mapping analysis to be conducted in autotetraploid species under a rigorous tetrasomic inheritance model.

Association mapping reveals novel genomic regions controlling some root and stolon traits in tetraploid potato (Solanum tuberosum L.)

Tuber crops have measurable biological variation in root and stolon phenotyping and thus may be utilized to identify genomic regions associated with these variations. This is the first comprehensive association mapping study related to potato root and stolon traits. A diverse panel of 192 tetraploid potato (Solanum tuberosum L.) genotypes were grown in aeroponics to reveal a biologically significant variation and detection of genomic regions associated with the root and stolon traits. Phenotyping of root traits was performed by image analysis software "WinRHIZO" (a root scanning method), and stolon traits was measured manually, while SolCAP 25K potato array was used for genotyping. Significant variation was observed between the potato genotypes for root and stolon traits along with high heritabilities (0.80 in TNS to 0.95 in SL). For marker-trait associations, Q + K linear mixed model was implemented and 50 novel genomic regions were detected. Significantly associated SNPs with stolon traits were located on chr 4, chr 6, chr 7, chr 9, chr 11 and chr 12, while those linked to root traits on chr 1, chr 2, chr 3, chr 9, chr 11, and chr 12. Structure and PCA analysis grouped genotypes into four sub-populations disclosing population genetic diversity. LD decay was observed at 2.316 Mbps (r 2 = 0.29) in the population. The identified SNPs were associated with genes performing vital functions such as root signaling and signal transduction in stress environments (GT-2 factors, protein kinases SAPK2-like and protein phosphatases "StPP1"), transcriptional and post-transcriptional gene regulation (RNA-binding proteins), sucrose synthesis and transporter families (UGPase, Sus3, SuSy, and StSUT1) and PVY resistance (Ry sto). The findings of our study can be employed in future breeding programs for improvement in potato production.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02727-6.

Pairwise linkage disequilibrium estimation for polyploids

Many tasks in statistical genetics involve pairwise estimation of linkage disequilibrium (LD). The study of LD in diploids is mature. However, in polyploids, the field lacks a comprehensive characterization of LD. Polyploids also exhibit greater levels of genotype uncertainty than diploids, yet no methods currently exist to estimate LD in polyploids in the presence of such genotype uncertainty. Furthermore, most LD estimation methods do not quantify the level of uncertainty in their LD estimates. Our study contains three major contributions. (i) We characterize haplotypic and composite measures of LD in polyploids. These composite measures of LD turn out to be functions of common statistical measures of association. (ii) We derive procedures to estimate haplotypic and composite LD in polyploids in the presence of genotype uncertainty. We do this by estimating LD directly from genotype likelihoods, which may be obtained from many genotyping platforms. (iii) We derive standard errors of all LD estimators that we discuss. We validate our methods on both real and simulated data. Our methods are implemented in the R package ldsep, available on the Comprehensive R Archive Network https://cran.r-project.org/package=ldsep.

Sampling Variation of RAD-Seq Data from Diploid and Tetraploid Potato (Solanum tuberosum L.)

The new sequencing technology enables identification of genome-wide sequence-based variants at a population level and a competitively low cost. The sequence variant-based molecular markers have motivated enormous interest in population and quantitative genetic analyses. Generation of the sequence data involves a sophisticated experimental process embedded with rich non-biological variation. Statistically, the sequencing process indeed involves sampling DNA fragments from an individual sequence. Adequate knowledge of sampling variation of the sequence data generation is one of the key statistical properties for any downstream analysis of the data and for implementing statistically appropriate methods. This paper reports a thorough investigation on modeling the sampling variation of the sequence data from the optimized RAD-seq (Restriction sit associated DNA sequencing) experiments with two parents and their offspring of diploid and autotetraploid potato (Solanum tuberosum L.). The analysis shows significant dispersion in sampling variation of the sequence data over that expected under multinomial distribution as widely assumed in the literature and provides statistical methods for modeling the variation and calculating the model parameters, which may be easily implemented in real sequence datasets. The optimized design of RAD-seq experiments enabled effective control of presentation of undesirable chloroplast DNA and RNA genes in the sequence data generated.

Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus

BACKGROUND

Brassica napus is an important oilseed crop cultivated worldwide. During domestication and breeding of B. napus, flowering time has been a target of selection because of its substantial impact on yield. Here we use double digest restriction-site associated DNA sequencing (ddRAD) to investigate the genetic basis of flowering in B. napus. An F2 mapping population was derived from a cross between an early-flowering spring type and a late-flowering winter type.

RESULTS

Flowering time in the mapping population differed by up to 25 days between individuals. High genotype error rates persisted after initial quality controls, as suggested by a genotype discordance of ~ 12% between biological sequencing replicates. After genotype error correction, a linkage map spanning 3981.31 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trait locus (QTL) on chromosome C2 was detected, covering eight flowering time genes including FLC.

CONCLUSIONS

These findings demonstrate the effectiveness of the ddRAD approach to sample the B. napus genome. Our results also suggest that ddRAD genotype error rates can be higher than expected in F2 populations. Quality filtering and genotype correction and imputation can substantially reduce these error rates and allow effective linkage mapping and QTL analysis.

Sequencing depth and genotype quality: accuracy and breeding operation considerations for genomic selection applications in autopolyploid crops

KEY MESSAGE

Polypoid crop breeders can balance resources between density and sequencing depth, dosage information and fewer highly informative SNPs recommended, non-additive models and QTL advantages on prediction dependent on trait architecture. The autopolyploid nature of potato and sweetpotato ensures a wide range of meiotic configurations and linkage phases leading to complex gene-action and pose problems in genotype data quality and genomic selection analyses. We used a 315-progeny biparental F1 population of hexaploid sweetpotato and a diversity panel of 380 tetraploid potato, genotyped using different platforms to answer the following questions: (i) do polyploid crop breeders need to invest more for additional sequencing depth? (ii) how many markers are required to make selection decisions? (iii) does considering non-additive genetic effects improve predictive ability (PA)? (iv) does considering dosage or quantitative trait loci (QTL) offer significant improvement to PA? Our results show that only a small number of highly informative single nucleotide polymorphisms (SNPs; ≤ 1000) are adequate for prediction in the type of populations we analyzed. We also show that considering dosage information and models considering only additive effects had the best PA for most traits, while the comparative advantage of considering non-additive genetic effects and including known QTL in the predictive model depended on trait architecture. We conclude that genomic selection can help accelerate the rate of genetic gains in potato and sweetpotato. However, application of genomic selection should be considered as part of optimizing the entire breeding program. Additionally, since the predictions in the current study are based on single populations, further studies on the effects of haplotype structure and inheritance on PA should be studied in actual multi-generation breeding populations.