Multiple QTL Mapping in Autopolyploids: A Random-Effect Model Approach with Application in a Hexaploid Sweetpotato Full-Sib Population

Research and developmental strategies to hasten the improvement of orphan crops

To feed the world's expanding population, crop breeders need to increase agricultural productivity and expand major crops base. Orphan crops are indigenously important crops with great potential because they are climate resilient, highly nutritious, contain nutraceutical compounds, and can improve the livelihood of smallholder farmers and consumers, but they have received little or no scientific attention. This review article examines several research and developmental strategies for hastening the improvement of these crops so that they can effectively play their role in securing food and nutrition. The integration of both research and developmental approaches will open up modern opportunities for crop improvement. We summarized ways in which advanced tools in phenotyping and genotyping, using high-throughput processes, can be used to accelerate their improvement. Finally, we suggest roles the genebanks can play in improving orphan crops, as the utilization of plant genetic resources is important for the genetic improvement of a crop.

Comprehensive review of sweetpotato flavor compounds: Opportunities for developing consumer-preferred varieties

Flavor contributes significantly to consumer preferences of cooked sweetpotato. Sugars largely drive the sweet taste, while the volatile organic compounds (VOCs), mainly classified as alcohols, aldehydes, ketones, and terpenes, provide characteristic aromas and influence the overall perception of flavor. In this paper, we review sweetpotato VOCs identified in the literature from 1980 to 2024 and discuss the efforts to understand how these compounds influence sensory perception and consumer preferences. Over 400 VOCs have been identified in cooked sweetpotato with 76 known to be aroma-active. Most of these aroma-active compounds are generated from Maillard reactions, Strecker, lipid and carotenoid degradation, or thermal release of terpenes from glycosidic bonds during cooking. Suggested mechanisms of formation of these aroma-active compounds are described. However, specific VOCs that are responsible for different aromas and flavors in cooked sweetpotatoes are yet to be fully characterized. There are significant opportunities to further identify the key predictors of aroma and flavor attributes in sweetpotato, which can be used to enhance the quality of existing varieties and develop new ones using a wide range of genetic tools. This review summarizes 44 years of research aimed at identifying key aroma compounds in cooked sweetpotato and provides a roadmap for future studies to guide breeders in developing high-quality, consumer-preferred varieties.

Genome-wide associations of sweetpotato metabolites enhance genomic prediction and identify genes in metabolic and regulatory pathways

Global sweetpotato production is increasing due to its health benefits, including high levels of complex carbohydrates and bioactive compounds. To explore the genetic basis of carbohydrates and carotenoids, we conducted a genome-wide association study (GWAS) using diverse sweetpotato accessions, two decades of phenotypic data, and 252,975 dosage-based SNPs and INDELs. Our findings confirmed a negative correlation between dry matter and β-carotene and identified interconnected metabolic pathways regulating multiple traits. Notably, phytoene synthase, involved in carotene biosynthesis, was associated with dry matter. Other pathways linked to these traits include carbohydrate metabolism, cell wall modification, phosphate starvation, stress response, and flowering regulation. To evaluate the breeding potential of GWAS-assisted genomic prediction (GWABLUP), we found that the 500 top GWAS hits used for genomic prediction significantly enhanced predictive ability (PA) for six out of nine traits, improving PA by up to 6.7% to 15.9% compared to the Genomic Best Linear Unbiased Prediction (GBLUP), which utilized 41,551 and 500 markers, respectively. The best PA across traits ranged from 20.9% to 60.6%, with both additive and dominance effects playing an important role. Model selection, guided by resample model inclusion probability (RMIP), during GWABLUP and after each GWAS iteration typically yielded the highest PA. These results provide valuable insights for breeding strategies aimed at optimizing agronomic traits and addressing market demands for diverse value-added products.

Unraveling the genetic architecture of blueberry fruit quality traits: major loci control organic acid content while more complex genetic mechanisms control texture and sugar content

BACKGROUND

Fruit quality traits, including taste, flavor, texture, and shelf-life, have emerged as important breeding priorities in blueberry (Vaccinium corymbosum). Organic acids and sugars play crucial roles in the perception of blueberry taste/flavor, where low and high consumer liking are correlated with high organic acids and high sugars, respectively. Blueberry texture and appearance are also critical for shelf-life quality and consumers' willingness-to-pay. As the genetic mechanisms that determine these fruit quality traits remain largely unknown, in this study, an F1 mapping population was used to perform quantitative trait loci (QTL) mapping for pH, titratable acidity (TA), organic acids, total soluble solids (TSS), sugars, fruit size, and texture at harvest and/or post-storage and weight loss.

RESULTS

Twenty-eight QTLs were detected for acidity-related parameters (pH, TA, and organic acid content). Six QTLs for pH, TA, and citric acid, two for quinic acid, and two for shikimic acid with major effects were consistently detected across two years on the same genomic regions on chromosomes 3, 4, and 5, respectively. Putative candidate genes for these QTLs were also identified using comparative transcriptomic analysis. No QTL was detected for malic acid content, TSS, or individual sugar content. A total of 146 QTLs with minor effects were identified for texture- and size-related parameters. With a few exceptions, these QTLs were generally inconsistent over years and post-storage, indicating a highly quantitative nature.

CONCLUSIONS

Our findings enhance the understanding of the genetic basis underlying fruit quality traits in blueberry and guide future work to exploit DNA-informed selection strategies in blueberry breeding programs. The major-effect QTLs identified for acidity-related fruit characteristics could be potential targets to develop DNA markers for marker-assisted selection (MAS). On the other hand, genomic selection may be a more suitable approach than MAS when targeting fruit texture, sugars, or size.

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.

Discovery of a major QTL for resistance to the guava root-knot nematode (Meloidogyne enterolobii) in 'Tanzania', an African landrace sweetpotato (Ipomoea batatas)

Sweetpotato, Ipomoea batatas (L.) Lam. (2n = 6x = 90), is among the world's most important food crops and is North Carolina's most important vegetable crop. The recent introduction of Meloidogyne enterolobii poses a significant economic threat to North Carolina's sweetpotato industry and breeding resistance into new varieties has become a high priority for the US sweetpotato industry. Previous studies have shown that 'Tanzania', a released African landrace, is resistant to M. enterolobii. We screened the biparental sweetpotato mapping population, 'Tanzania' x 'Beauregard', for resistance to M. enterolobii by inoculating 246 full-sibs with 10,000 eggs each under greenhouse conditions. 'Tanzania', the female parent, was highly resistant, while 'Beauregard' was highly susceptible. Our bioassays exhibited strong skewing toward resistance for three measures of resistance: reproductive factor, eggs per gram of root tissue, and root gall severity ratings. A 1:1 segregation for resistance suggested a major gene conferred M. enterolobii resistance. Using a random-effect multiple interval mapping model, we identified a single major QTL, herein designated as qIbMe-4.1, on linkage group 4 that explained 70% of variation in resistance to M. enterolobii. This study provides a new understanding of the genetic basis of M. enterolobii resistance in sweetpotato and represents a major step towards the identification of selectable markers for nematode resistance breeding.

A locus-dependent mixed inheritance in the segmental allohexaploid sweetpotato (Ipomoea batatas [L.] Lam)

Two interrelated aspects of the sweetpotato genome, its polyploid origin and inheritance type, remain uncertain. We recently proposed a segmental allohexaploid sweetpotato and thus sought to clarify its inheritance type by direct analyses of homoeolog segregations at selected single-copy loci. For such analyses, we developed a digital quantitative PCR genotyping method using one nondiscriminatory and three discriminatory probes for each selected locus to discriminate and quantify three homoeolog-differentiating variation types (homoeolog-types) in genomic DNA samples for genotype fitting and constructed a F2 population for segregation analyses. We confirmed inter-subgenomic distinctions of three identified homoeolog-types at each of five selected loci by their interspecific differentiations among 14 species in Ipomoea section batatas and genotyped the loci in 549 F2 lines, selected F1 progenies, and their founding parents. Segregation and genotype analyses revealed a locus-dependent mixed inheritance (disomic, polysomic, and intermediate types) of the homoeolog-types at 4 loci in the F2 population, displaying estimated disomic-inheritance frequencies of 0, 2.72%, 14.52%, and 36.92%, and probably in the F1 population too. There were also low-frequency non-hexaploid F1 and F2 genotypes that were probably derived from double-reduction recombination or partially unreduced gametes, and F2 genotypes of apparent aneuploids/dysploids with neopolyploid-like frequencies. Additional analyses of homoeolog-type genotypes at the 5 loci in 46 lines from various regions revealed locus-dependent selection biases, favoring genotypes having more of one homoeolog-type, i.e. more of di- or homogenized homoeolog-type composition, and one-direction ploidy trending among apparent aneuploids/dysploids. These inheritance features pointed to an evolving segmental allohexaploid sweetpotato impacted by selection biases.

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.

Identification of QTL associated with plant vine characteristics and infection response to late blight, early blight, and Verticillium wilt in a tetraploid potato population derived from late blight-resistant Palisade Russet

Potato late blight (causal agent Phytophthora infestans) is a disease of potatoes with economic importance worldwide. Control is primarily through field monitoring and the application of fungicides. Control of late blight with fungicides and host plant resistance is difficult, with documented cases of such control measures failing with the advent of new pathotypes of P. infestans. To better understand host plant resistance and to develop more durable late blight resistance, Quantitative Trait Locus/Loci (QTL) analysis was conducted on a tetraploid mapping population derived from late blight-resistant potato cultivar Palisade Russet. Additionally, QTL analyses for other traits such as Verticillium wilt and early blight resistance, vine size and maturity were performed to identify a potential relationship between multiple traits and prepare genetic resources for molecular markers useful in breeding programs. For this, one hundred ninety progenies from intercrossing Palisade Russet with a late blight susceptible breeding clone (ND028673B-2Russ) were assessed. Two parents and progenies were evaluated over a two-year period for response to infection by the US-8 genotype of P. infestans in inoculated field screenings in Corvallis, Oregon. In Aberdeen, Idaho, the same mapping population was also evaluated for phenotypic response to early blight and Verticillium wilt, and vine size and maturity in a field over a two-year period. After conducting QTL analyses with those collected phenotype data, it was observed that chromosome 5 has a significant QTL for all five traits. Verticillium wilt and vine maturity QTL were also observed on chromosome 1, and vine size QTL was also found on chromosomes 3 and 10. An early blight QTL was also detected on chromosome 2. The QTL identified in this study have the potential for converting into breeder-friendly molecular markers for marker-assisted selection.

QTL discovery for resistance to black spot and cercospora leaf spot, and defoliation in two interconnected F1 bi-parental tetraploid garden rose populations

Garden roses are an economically important horticultural crop worldwide, and two major fungal pathogens, black spot (Diplocarpon rosae F.A. Wolf) and cercospora leaf spot of rose (Rosisphaerella rosicola Pass.), affect both the health and ornamental value of the plant. Most studies on black spot disease resistance have focused on diploid germplasm, and little work has been performed on cercospora leaf spot resistance. With the use of newly developed software tools for autopolyploid genetics, two interconnected tetraploid garden rose F1 populations (phenotyped over the course of 3 years) were used for quantitative trait locus (QTL) analysis of black spot and cercospora leaf spot resistance as well as plant defoliation. QTLs for black spot resistance were mapped to linkage groups (LGs) 1-6. QTLs for cercospora resistance and susceptibility were found in LGs 1, 4, and 5 and for defoliation in LGs 1, 3, and 5. The major locus on LG 5 for black spot resistance coincides with the previously discovered Rdr4 locus inherited from Rosa L. 'Radbrite' (Brite Eyes™), the common parent used in these mapping populations. This work is the first report of any QTL for cercospora resistance/susceptibility in tetraploid rose germplasm and the first report of defoliation QTL in roses. A major QTL for cercospora susceptibility coincides with the black spot resistance QTL on LG 5 (Rdr4). A major cercospora resistance QTL was found on LG 1. These populations provide a genetic resource that will further the knowledge base of rose genetics as more traits are studied. Studying more traits from these populations will allow for the stacking of various QTLs for desirable traits.

Polyploid SNP Genotyping Using the MassARRAY System

Molecular marker discovery and genotyping are major challenges in polyploid breeding programs incorporating molecular biology tools. In this context, this work describes a method for single nucleotide polymorphism (SNP) genotyping in polyploid crops using matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry, the MassARRAY System.

High-density linkage map construction in an autotetraploid blueberry population and detection of quantitative trait loci for anthocyanin content

Highbush blueberry (Vaccinium corymbosum, 2n = 4x = 48) is the most cultivated type of blueberry, both in New Zealand and overseas. Its perceived nutritional value is conferred by phytonutrients, particularly anthocyanins. Identifying the genetic mechanisms that control the biosynthesis of these metabolites would enable faster development of cultivars with improved fruit qualities. Here, we used recently released tools for genetic mapping in autotetraploids to build a high-density linkage map in highbush blueberry and to detect quantitative trait loci (QTLs) for fruit anthocyanin content. Genotyping was performed by target sequencing, with ∼18,000 single nucleotide polymorphism (SNP) markers being mapped into 12 phased linkage groups (LGs). Fruits were harvested when ripe for two seasons and analyzed with high-performance liquid chromatography-mass spectrometry (HPLC-MS): 25 different anthocyanin compounds were identified and quantified. Two major QTLs that were stable across years were discovered, one on LG2 and one on LG4, and the underlying candidate genes were identified. Interestingly, the presence of anthocyanins containing acylated sugars appeared to be under strong genetic control. Information gained in this study will enable the design of molecular markers for marker-assisted selection and will help build a better understanding of the genetic control of anthocyanin biosynthesis in this crop.

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.

Rose Rosette Disease Resistance Loci Detected in Two Interconnected Tetraploid Garden Rose Populations

Rose rosette disease (RRD), caused by the Rose rosette emaravirus (RRV), is a major threat to the garden rose industry in the United States. There has been limited work on the genetics of host plant resistance to RRV. Two interconnected tetraploid garden rose F1 biparental mapping populations were created to develop high-quality tetraploid rose linkage maps that allowed the discovery of RRD resistance quantitative trait loci (QTLs) on linkage groups (LGs) 5, 6, and 7. These QTLs individually accounted for around 18-40% of the phenotypic variance. The locus with the greatest effect on partial resistance was found in LG 5. Most individuals with the LG 5 QTL were in the simplex configuration; however, two individuals were duplex (likely due to double reduction). Identification of resistant individuals and regions of interest can help the development of diagnostic markers for marker-assisted selection in a breeding program.

Genetic Dissection of Early Blight Resistance in Tetraploid Potato

Early blight, caused by the fungus Alternaria solani, is one of the most economically important diseases of potatoes worldwide. We previously identified a tetraploid potato clone, B0692-4, which is resistant to early blight. To dissect the genetic basis of early blight resistance in this clone, a full-sib tetraploid potato population including 241 progenies was derived from a cross between B0692-4 and a susceptible cultivar, Harley Blackwell, in this study. The population was evaluated for foliage resistance against early blight in field trials in Pennsylvania in 2018 and 2019 and relative area under the disease progress curve (rAUDPC) was determined. The distribution of rAUDPC ranged from 0.016 to 0.679 in 2018, and from 0.017 to 0.554 in 2019. Broad sense heritability for resistance, as measured as rAUDPC, was estimated as 0.66-0.80. The population was also evaluated for foliar maturity in field trials in Maine in 2018 and 2020. A moderate negative correlation between rAUDPC and foliar maturity was detected in both years. A genetic linkage map covering a length of 1469.34 cM with 9124 SNP markers was used for mapping quantitative trait loci (QTL) for rAUDPC and foliar maturity. In 2018, three QTLs for early blight were detected; two of them on chromosome 5 overlapped with QTLs for maturity, and one of them on chromosome 7 was independent of maturity QTL. In 2019, six QTLs for early blight were detected; two QTLs on chromosome 5 overlapped with QTLs for maturity, and the other four QTLs did not overlap with QTLs for maturity. The identification of these QTLs provides new insight into the genetic basis of early blight resistance and may serve as sources for marker-assisted selection for early blight resistance breeding.

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.

QTL mapping in outbred tetraploid (and diploid) diallel populations

Over the last decade, multiparental populations have become a mainstay of genetics research in diploid species. Our goal was to extend this paradigm to autotetraploids by developing software for quantitative trait locus (QTL) mapping in connected F1 populations derived from a set of shared parents. For QTL discovery, phenotypes are regressed on the dosage of parental haplotypes to estimate additive effects. Statistical properties of the model were explored by simulating half-diallel diploid and tetraploid populations with different population sizes and numbers of parents. Across scenarios, the number of progeny per parental haplotype (pph) largely determined the statistical power for QTL detection and accuracy of the estimated haplotype effects. Multiallelic QTL with heritability 0.2 were detected with 90% probability at 25 pph and genome-wide significance level 0.05, and the additive haplotype effects were estimated with over 90% accuracy. Following QTL discovery, the software enables a comparison of models with multiple QTL and nonadditive effects. To illustrate, we analyzed potato tuber shape in a half-diallel population with three tetraploid parents. A well-known QTL on chromosome 10 was detected, for which the inclusion of digenic dominance lowered the Deviance Information Criterion (DIC) by 17 points compared to the additive model. The final model also contained a minor QTL on chromosome 1, but higher-order dominance and epistatic effects were excluded based on the DIC. In terms of practical impacts, the software is already being used to select offspring based on the effect and dosage of particular haplotypes in breeding programs.

Linkage and QTL mapping for tuber shape and specific gravity in a tetraploid mapping population of potato representing the russet market class

BACKGROUND

Tuber shape and specific gravity (dry matter) are important agronomic traits in potato processing and impact production costs, quality, and consistency of the final processed food products such as French fries and potato chips. In this study, linkage and QTL mapping were performed for these two traits to allow for the implementation of marker-assisted selection to facilitate breeding efforts in the russet market class. Two parents, Rio Grande Russet (female) and Premier Russet (male) and their 205 F1 progenies were initially phenotyped for tuber shape and specific gravity in field trials conducted in Idaho and North Carolina in 2010 and 2011, with specific gravity also being measured in Minnesota in 2011. Progenies and parents were previously genotyped using the Illumina SolCAP Infinium 8303 Potato SNP array, with ClusterCall and MAPpoly (R-packages) subsequently used for autotetraploid SNP calling and linkage mapping in this study. The 12 complete linkage groups and phenotypic data were then imported into QTLpoly, an R-package designed for polyploid QTL analyses.

RESULTS

Significant QTL for tuber shape were detected on chromosomes 4, 7, and 10, with heritability estimates ranging from 0.09 to 0.36. Significant tuber shape QTL on chromosomes 4 and 7 were specific to Idaho and North Carolina environments, respectively, whereas the QTL on chromosome 10 was significant regardless of growing environment. Single marker analyses identified alleles in the parents associated with QTL on chromosomes 4, 7, and 10 that contributed to significant differences in tuber shape among progenies. Significant QTL were also identified for specific gravity on chromosomes 1 and 5 with heritability ranging from 0.12 to 0.21 and were reflected across environments.

CONCLUSION

Fully automated linkage mapping and QTL analysis were conducted to identify significant QTL for tuber shape and dry matter in a tetraploid mapping population representing the russet market class. The findings are important for the development of molecular markers useful to potato breeders for marker-assisted selection for the long tuber shape and acceptable dry matter required by the potato industry within this important market class.

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.

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

Motivation

The investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms vary phenotypically. However, many important crop species are polyploid (carrying more than two copies of each chromosome), requiring specialized tools for such analyses. Moreover, deciphering meiotic processes at higher ploidy levels is not straightforward, but is necessary to understand the reproductive dynamics of these species, or uncover potential barriers to their genetic improvement.

Results

Here, we present polyqtlR, a novel software tool to facilitate such analyses in (auto)polyploid crops. It performs QTL interval mapping in F₁ populations of outcrossing polyploids of any ploidy level using identity-by-descent probabilities. The allelic composition of discovered QTL can be explored, enabling favourable alleles to be identified and tracked in the population. Visualization tools within the package facilitate this process, and options to include genetic co-factors and experimental factors are included. Detailed information on polyploid meiosis including prediction of multivalent pairing structures, detection of preferential chromosomal pairing and location of double reduction events can be performed.

Availabilityand implementation

polyqtlR is freely available from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polyqtlR.

Supplementary information

Supplementary data are available at Bioinformatics online.

A statistical framework for QTL hotspot detection

Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.

Discovery of a major QTL for root-knot nematode (Meloidogyne incognita) resistance in cultivated sweetpotato (Ipomoea batatas)

Utilizing a high-density integrated genetic linkage map of hexaploid sweetpotato, we discovered a major dominant QTL for root-knot nematode (RKN) resistance and modeled its effects. This discovery is useful for development of a modern sweetpotato breeding program that utilizes marker-assisted selection and genomic selection approaches for faster genetic gain of RKN resistance. The root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) causes significant storage root quality reduction and yields losses in cultivated sweetpotato [Ipomoea batatas (L.) Lam.]. In this study, resistance to RKN was examined in a mapping population consisting of 244 progenies derived from a cross (TB) between 'Tanzania,' a predominant African landrace cultivar with resistance to RKN, and 'Beauregard,' an RKN susceptible major cultivar in the USA. We performed quantitative trait loci (QTL) analysis using a random-effect QTL mapping model on the TB genetic map. An RKN bioassay incorporating potted cuttings of each genotype was conducted in the greenhouse and replicated five times over a period of 10 weeks. For each replication, each genotype was inoculated with ca. 20,000 RKN eggs, and root-knot galls were counted ~62 days after inoculation. Resistance to RKN in the progeny was highly skewed toward the resistant parent, exhibiting medium to high levels of resistance. We identified one major QTL on linkage group 7, dominant in nature, which explained 58.3% of the phenotypic variation in RKN counts. This work represents a significant step forward in our understanding of the genetic architecture of RKN resistance and sets the stage for future utilization of genomics-assisted breeding in sweetpotato breeding programs.

The recombination landscape and multiple QTL mapping in a Solanum tuberosum cv. 'Atlantic'-derived F1 population

There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato, Solanum tuberosum (2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F₁ population (n = 156) derived from a cross involving 'Atlantic', a widely grown chipping variety in the USA. A fully integrated genetic map with 4285 single nucleotide polymorphisms, spanning 1630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0~72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2~39.2%). Seven traits were evaluated over four years (2006-8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified with co-located QTL for maturity, plant yield, specific gravity, and internal heat necrosis resistance evaluated over different years. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.

Genome-wide identification of agronomically important genes in outcrossing crops using OutcrossSeq

Many important crops (e.g., tuber, root, and tree crops) are cross-pollinating. For these crops, no inbred lines are available for genetic study and breeding because they are self-incompatible, clonally propagated, or have a long generation time, making the identification of agronomically important genes difficult, particularly in crops with a complex autopolyploid genome. In this study, we developed a method, OutcrossSeq, for mapping agronomically important loci in outcrossing crops based on whole-genome low-coverage resequencing of a large genetic population, and designed three computation algorithms in OutcrossSeq for different types of outcrossing populations. We applied OutcrossSeq to a tuberous root crop (sweet potato, autopolyploid), a tree crop (walnut tree, highly heterozygous diploid), and hybrid crops (double-cross populations) to generate high-density genotype maps for the outcrossing populations, which enable precise identification of genomic loci underlying important agronomic traits. Candidate causative genes at these loci were detected based on functional clues. Taken together, our results indicate that OutcrossSeq is a robust and powerful method for identifying agronomically important genes in heterozygous species, including polyploids, in a cost-efficient way. The OutcrossSeq software and its instruction manual are available for downloading at www.xhhuanglab.cn/tool/OutcrossSeq.html.

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.

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.

QTL Mapping for Resistance to Cankers Induced by Pseudomonas syringae pv. actinidiae (Psa) in a Tetraploid Actinidia chinensis Kiwifruit Population

Polyploidy is a key driver of significant evolutionary changes in plant species. The genus Actinidia (kiwifruit) exhibits multiple ploidy levels, which contribute to novel fruit traits, high yields and resistance to the canker-causing dieback disease incited by Pseudomonas syringae pv. actinidiae (Psa) biovar 3. However, the genetic mechanism for resistance to Psa observed in polyploid kiwifruit is not yet known. In this study we performed detailed genetic analysis of a tetraploid Actinidia chinensis var. chinensis population derived from a cross between a female parent that exhibits weak tolerance to Psa and a highly Psa-resistant male parent. We used the capture-sequencing approach across the whole kiwifruit genome and generated the first ultra-dense maps in a tetraploid kiwifruit population. We located quantitative trait loci (QTLs) for Psa resistance on these maps. Our approach to QTL mapping is based on the use of identity-by-descent trait mapping, which allowed us to relate the contribution of specific alleles from their respective homologues in the male and female parent, to the control of Psa resistance in the progeny. We identified genes in the diploid reference genome whose function is suggested to be involved in plant defense, which underly the QTLs, including receptor-like kinases. Our study is the first to cast light on the genetics of a polyploid kiwifruit and suggest a plausible mechanism for Psa resistance in this species.

Genetic Mapping in Autohexaploid Sweet Potato with Low-Coverage NGS-Based Genotyping Data

Next-generation sequencing (NGS)-based genotyping methods can generate numerous genetic markers in a single experiment and have contributed to plant genetic mapping. However, for high precision genetic analysis, the complicated genetic segregation mode in polyploid organisms requires high-coverage NGS data and elaborate analytical algorithms. In the present study, we propose a simple strategy for the genetic mapping of polyploids using low-coverage NGS data. The validity of the strategy was investigated using simulated data. Previous studies indicated that accurate allele dosage estimation from low-coverage NGS data (read depth < 40) is difficult. Therefore, we used allele dosage probabilities calculated from read counts in association analyses to detect loci associated with phenotypic variations. The allele dosage probabilities showed significant detection power, although higher allele dosage estimation accuracy resulted in higher detection power. On the contrary, differences in the segregation patterns between the marker and causal genes resulted in a drastic decrease in detection power even if the marker and casual genes were in complete linkage and the allele dosage estimation was accurate. These results indicated that the use of a larger number of markers is advantageous, even if the accuracy of allele dosage estimation is low. Finally, we applied the strategy for the genetic mapping of autohexaploid sweet potato (Ipomoea batatas) populations to detect loci associated with agronomic traits. Our strategy could constitute a cost-effective approach for preliminary experiments done performed to large-scale studies.

High-Resolution Linkage Map and QTL Analyses of Fruit Firmness in Autotetraploid Blueberry

Blueberry (Vaccinium corymbosum and hybrids) is an autotetraploid crop whose commercial relevance has been growing steadily during the last 20 years. However, the ever-increasing cost of labor for hand-picking blueberry is one main constraint in competitive marketing of the fruit. Machine harvestability is, therefore, a key trait for the blueberry industry. Understanding the genetic architecture of traits related to machine harvestability through Quantitative Trait Loci (QTL) mapping is the first step toward implementation of molecular breeding for faster genetic gains. Despite recent advances in software development for autotetraploid genetic mapping, a high-resolution map is still not available for blueberry. In this study, we crafted a map for autotetraploid low-chill highbush blueberry containing 11,292 SNP markers and a total size of 1,953.97 cM (average density of 5.78 markers/cM). This map was subsequently used to perform QTL analyses in 2-year field trials for a trait crucial to machine harvesting: fruit firmness. Preliminary insights were also sought for single evaluations of firmness retention after cold storage, and fruit detachment force traits. Significant QTL peaks were identified for all the traits and overlapping QTL intervals were detected for firmness across the years. We found low-to-moderate QTL effects explaining the phenotypic variance, which suggest a quantitative nature of these traits. The QTL intervals were further speculated for putative gene repertoire. Altogether, our findings provide the basis for future fine-mapping and molecular breeding efforts for machine harvesting in blueberry.