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

Harnessing clonal gametes in hybrid crops to engineer polyploid genomes

Heterosis boosts crop yield; however, harnessing additional progressive heterosis in polyploids is challenging for breeders. We bioengineered a 'mitosis instead of meiosis' (MiMe) system that generates unreduced, clonal gametes in three hybrid tomato genotypes and used it to establish polyploid genome design. Through the hybridization of MiMe hybrids, we generated '4-haplotype' plants that encompassed the complete genetics of their four inbred grandparents, providing a blueprint for exploiting polyploidy in crops.

Potato and sweetpotato breeding at the international potato center: approaches, outcomes and the way forward

Root and tuber crop breeding is at the front and center of CIP's science program, which seeks to develop and disseminate sustainable agri-food technologies, information and practices to serve objectives including poverty alleviation, income generation, food security and the sustainable use of natural resources. CIP was established in 1971 in Peru, which is part of potato's center of origin and diversity, with an initial mandate on potato and expanding to include sweetpotato in 1986. Potato and sweetpotato are among the top 10 most consumed food staples globally and provide some of the most affordable sources of energy and vital nutrients. Sweetpotato plays a key role in securing food for many households in Africa and South Asia, while potato is important worldwide. Both crops grow in a range of conditions with relatively few inputs and simple agronomic techniques. Potato is adapted to the cooler environments, while sweetpotato grows well in hot climates, and hence, the two crops complement each other. Germplasm enhancement (pre-breeding), the development of new varieties and building capacity for breeding and variety testing in changing climates with emphasis on adaptation, resistance, nutritional quality and resource-use efficiency are CIP's central activities with significant benefits to the poor. Investments in potato and sweetpotato breeding and allied disciplines at CIP have resulted in the release of many varieties some of which have had documented impact in the release countries. Partnership with diverse types of organizations has been key to the centers way of working toward improving livelihoods through crop production in the global South.

Breeding Cultivars for Resistance to the African Sweetpotato Weevils, Cylas puncticollis and Cylas brunneus, in Uganda: A Review of the Current Progress

In sub-Saharan Africa, sweetpotato weevils are the major pests of cultivated sweetpotato, causing estimated losses of between 60% and 100%, primarily during dry spells. The predominantly cryptic feeding behavior of Cylas spp. within their roots makes their control difficult, thus, host plant resistance is one of the most promising lines of protection against these pests. However, limited progress has been made in cultivar breeding for weevil resistance, partly due to the complex hexaploid genome of sweetpotato, which complicates conventional breeding, in addition to the limited number of genotypes with significant levels of resistance for use as sources of resistance. Pollen sterility, cross incompatibility, and poor seed set and germination in sweetpotato are also common challenges in improving weevil resistance. The accurate phenotyping of sweetpotato weevil resistance to enhance the efficiency of selection has been equally difficult. Genomics-assisted breeding, though in its infancy stages in sweetpotato, has a potential application in overcoming some of these barriers. However, it will require the development of more genomic infrastructure, particularly single-nucleotide polymorphism markers (SNPs) and robust next-generation sequencing platforms, together with relevant statistical procedures for analyses. With the recent advances in genomics, we anticipate that genomic breeding for sweetpotato weevil resistance will be expedited in the coming years. This review sheds light on Uganda's efforts, to date, to breed against the Cylas puncticollis (Boheman) and Cylas brunneus (Fabricius) species of African sweetpotato weevil.

Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)

In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs' heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01419-8.

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.

Exploring and exploiting genetics and genomics for sweetpotato improvement: Status and perspectives

Sweetpotato (Ipomoea batatas (L.) Lam.) is one of the most important root crops cultivated worldwide. Because of its adaptability, high yield potential, and nutritional value, sweetpotato has become an important food crop, particularly in developing countries. To ensure adequate crop yields to meet increasing demand, it is essential to enhance the tolerance of sweetpotato to environmental stresses and other yield-limiting factors. The highly heterozygous hexaploid genome of I. batatas complicates genetic studies and limits improvement of sweetpotato through traditional breeding. However, application of next-generation sequencing and high-throughput genotyping and phenotyping technologies to sweetpotato genetics and genomics research has provided new tools and resources for crop improvement. In this review, we discuss the genomics resources that are available for sweetpotato, including the current reference genome, databases, and available bioinformatics tools. We systematically review the current state of knowledge on the polyploid genetics of sweetpotato, including studies of its origin and germplasm diversity and the associated mapping of important agricultural traits. We then outline the conventional and molecular breeding approaches that have been applied to sweetpotato. Finally, we discuss future goals for genetic studies of sweetpotato and crop improvement via breeding in combination with state-of-the-art multi-omics approaches such as genomic selection and gene editing. These approaches will advance and accelerate genetic improvement of this important root crop and facilitate its sustainable global production.

Analysis of genetic diversity and population structure among cultivated potato clones from Korea and global breeding programs

Characterizing the genetic diversity and population structure of breeding materials is essential for breeding to improve crop plants. The potato is an important non-cereal food crop worldwide, but breeding potatoes remains challenging owing to their auto-tetraploidy and highly heterozygous genome. We evaluated the genetic structure of a 110-line Korean potato germplasm using the SolCAP 8303 single nucleotide polymorphism (SNP) Infinium array and compared it with potato clones from other countries to understand the genetic landscape of cultivated potatoes. Following the tetraploid model, we conducted population structure analysis, revealing three subpopulations represented by two Korean potato groups and one separate foreign potato group within 110 lines. When analyzing 393 global potato clones, country/region-specific genetic patterns were revealed. The Korean potato clones exhibited higher heterozygosity than those from Japan, the United States, and other potato landraces. We also employed integrated extended haplotype homozygosity (iHS) and cross-population extended haplotype homozygosity (XP-EHH) to identify selection signatures spanning candidate genes associated with biotic and abiotic stress tolerance. Based on the informativeness of SNPs for dosage genotyping calls, 10 highly informative SNPs discriminating all 393 potatoes were identified. Our results could help understanding a potato breeding history that reflects regional adaptations and distinct market demands.

Genome-Based Genotype × Environment Prediction Enhances Potato (Solanum tuberosum L.) Improvement Using Pseudo-Diploid and Polysomic Tetraploid Modeling

Potato breeding must improve its efficiency by increasing the reliability of selection as well as identifying a promising germplasm for crossing. This study shows the prediction accuracy of genomic-estimated breeding values for several potato (Solanum tuberosum L.) breeding clones and the released cultivars that were evaluated at three locations in northern and southern Sweden for various traits. Three dosages of marker alleles [pseudo-diploid (A), additive tetrasomic polyploidy (B), and additive-non-additive tetrasomic polyploidy (C)] were considered in the genome-based prediction models, for single environments and multiple environments (accounting for the genotype-by-environment interaction or G × E), and for comparing two kernels, the conventional linear, Genomic Best Linear Unbiased Prediction (GBLUP) (GB), and the non-linear Gaussian kernel (GK), when used with the single-kernel genetic matrices of A, B, C, or when employing two-kernel genetic matrices in the model using the kernels from B and C for a single environment (models 1 and 2, respectively), and for multi-environments (models 3 and 4, respectively). Concerning the single site analyses, the trait with the highest prediction accuracy for all sites under A, B, C for model 1, model 2, and for GB and GK methods was tuber starch percentage. Another trait with relatively high prediction accuracy was the total tuber weight. Results show an increase in prediction accuracy of model 2 over model 1. Non-linear Gaussian kernel (GK) did not show any clear advantage over the linear kernel GBLUP (GB). Results from the multi-environments had prediction accuracy estimates (models 3 and 4) higher than those obtained from the single-environment analyses. Model 4 with GB was the best method in combination with the marker structure B for predicting most of the tuber traits. Most of the traits gave relatively high prediction accuracy under this combination of marker structure (A, B, C, and B-C), and methods GB and GK combined with the multi-environment with G × E model.

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.

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.

Rapid identification of mutations caused by fast neutron bombardment in Medicago truncatula

BACKGROUND

Fast neutron bombardment (FNB) is a very effective approach for mutagenesis and has been widely used in generating mutant libraries in many plant species. The main type of mutations of FNB mutants are deletions of DNA fragments ranging from few base pairs to several hundred kilobases, thus usually leading to the null mutation of genes. Despite its efficiency in mutagenesis, identification of the mutation sites is still challenging in many species. The traditional strategy of positional cloning is very effective in identifying the mutation but time-consuming. With the availability of genome sequences, the array-based comparative genomic hybridization (CGH) method has been developed to detect the mutation sites by comparing the signal intensities of probes between wild-type and mutant plants. Though CGH method is effective in detecting copy number variations (CNVs), the resolution and coverage of CGH probes are not adequate to identify mutations other than CNVs.

RESULTS

We report a new strategy and pipeline to sensitively identify the mutation sites of FNB mutants by combining deep-coverage whole-genome sequencing (WGS), polymorphism calling, and customized filtering in Medicago truncatula. Initially, we performed a bulked sequencing for a FNB white nodule (wn) mutant and its wild-type like plants derived from a backcross population. Following polymorphism calling and filtering, validation by manual check and Sanger sequencing, we identified that SymCRK is the causative gene of white nodule mutant. We also sequenced an individual FNB mutant yellow leaves 1 (yl1) and wild-type plant. We identified that ETHYLENE-DEPENDENT GRAVITROPISM-DEFICIENT AND YELLOW-GREEN 1 (EGY1) is the candidate gene for M. truncatula yl1 mutant.

CONCLUSION

Our results demonstrated that the method reported here is rather robust in identifying the mutation sites for FNB mutants.

Breeding Progress for Vitamin A, Iron and Zinc Biofortification, Drought Tolerance, and Sweetpotato Virus Disease Resistance in Sweetpotato

Sweetpotato is a resilient food crop with great potential to contribute to reduced hunger in the world. Sweetpotato shows significant potential to contribute to reducing the Global Hunger Index, which reflects deficiencies in calories and micronutrients based on the components of hunger, undernourishment, under-five mortality rate, stunting and wasting. Its genetic diversity has been harnessed through breeding to increase vitamin A, iron, and zinc content, virus resistance and climate resilience for the world's food needs. Africa and India are the most food-insecure regions. The main objectives of this research were to: provide information and a knowledge base on sweetpotato breeding in Africa for biofortification of vitamin A, iron, and zinc, drought tolerance and virus resistance; recommend procedures for generating new breeding populations and varieties; and develop new tools, technologies and methods for sweetpotato improvement. The research was implemented between 2009 and 2020 in 14 collaborating African countries using introduced and local genotypes. The redesigned accelerated breeding scheme resulted in increased genetic gains for vitamin A, iron, zinc contents and virus resistance, and the release by sub-Saharan African countries of 158 varieties; 98 of them orange-fleshed; 55 varieties bred by an accelerated breeding scheme; 27 drought-tolerant and two with enhanced iron and zinc content. Our experience has demonstrated that through the use of more optimized, standardized and collaborative breeding procedures by breeding programs across Africa, it is possible to speed official sweetpotato variety release and contribute to reducing the severe micronutrient deficiencies on the continent.

Development of a Panel of Genotyping-in-Thousands by Sequencing in Capsicum

Genotyping by sequencing (GBS) enables genotyping of multiple loci at low cost. However, the single nucleotide polymorphisms (SNPs) revealed by GBS tend to be randomly distributed between individuals, limiting their direct comparisons without applying the various filter options to obtain a comparable dataset of SNPs. Here, we developed a panel of a multiplex targeted sequencing method, genotyping-in-thousands by sequencing (GT-seq), to genotype SNPs in Capsicum spp. Previously developed Fluidigm^® SNP markers were converted to GT-seq markers and combined with new GT-seq markers developed using SNP information obtained through GBS. We then optimized multiplex PCR conditions: we obtained the highest genotyping rate when the first PCR consisted of 25 cycles. In addition, we determined that 101 primer pairs performed best when amplifying target sequences of 79 bp. We minimized interference of multiplex PCR by primer dimer formation using the PrimerPooler program. Using our GT-seq pipeline on Illumina Miseq and Nextseq platforms, we genotyped up to 1,500 (Miseq) and 1,300 (Nextseq) samples for the optimum panel size of 100 loci. To allow the genotyping of Capsicum species, we designed 332 informative GT-seq markers from Fluidigm SNP markers and GBS-derived SNPs. This study illustrates the first application of GT-seq in crop plants. The GT-seq marker set developed here will be a useful tool for molecular breeding of peppers in the future.