Qmatey: an automated pipeline for fast exact matching-based alignment and strain-level taxonomic binning and profiling of metagenomes.

Metagenomics is a powerful tool for understanding organismal interactions; however, classification, profiling and detection of interactions at the strain level remain challenging. We present an automated pipeline, quantitative metagenomic alignment and taxonomic exact matching (Qmatey), that performs a fast exact matching-based alignment and integration of taxonomic binning and profiling. It interrogates large databases without using metagenome-assembled genomes, curated pan-genes or k-mer spectra that limit resolution. Qmatey minimizes misclassification and maintains strain level resolution by using only diagnostic reads as shown in the analysis of amplicon, quantitative reduced representation and shotgun sequencing datasets. Using Qmatey to analyze shotgun data from a synthetic community with 35% of the 26 strains at low abundance (0.01-0.06%), we revealed a remarkable 85-96% strain recall and 92-100% species recall while maintaining 100% precision. Benchmarking revealed that the highly ranked Kraken2 and KrakenUniq tools identified 2-4 more taxa (92-100% recall) than Qmatey but produced 315-1752 false positive taxa and high penalty on precision (1-8%). The speed, accuracy and precision of the Qmatey pipeline positions it as a valuable tool for broad-spectrum profiling and for uncovering biologically relevant interactions.

Genotype-by-environment interactions and local adaptation shape selection in the US National Chip Processing Trial.

KEY MESSAGE: We find evidence of selection for local adaptation and extensive genotype-by-environment interaction in the potato National Chip Processing Trial (NCPT). We present a novel method for dissecting the interplay between selection, local adaptation and environmental response in plant breeding schemes. Balancing local adaptation and the desire for widely adapted cultivars is challenging for plant breeders and makes genotype-by-environment interactions (GxE) an important target of selection. Selecting for GxE requires plant breeders to evaluate plants across multiple environments. One way breeders have accomplished this is to test advanced materials across many locations. Public potato breeders test advanced breeding material in the National Chip Processing Trial (NCPT), a public-private partnership where breeders from ten institutions submit advanced chip lines to be evaluated in up to ten locations across the country. These clones are genotyped and phenotyped for important agronomic traits. We used these data to interrogate the NCPT for GxE. Further, because breeders submitting clones to the NCPT select in a relatively small geographic range for the first 3 years of selection, we examined these data for evidence of incidental selection for local adaptation, and the alleles underlying it, using an environmental genome-wide association study (envGWAS). We found genomic regions associated with continuous environmental variables and discrete breeding programs, as well as regions of the genome potentially underlying GxE for yield.

A comparison of three automated root-knot nematode egg counting approaches using machine learning, image analysis, and a hybrid model.

Meloidogyne spp. (root-knot nematodes, RKN) are a major threat to a wide range of agricultural crops worldwide. Breeding crops for RKN resistance is an effective management strategy, yet assaying large numbers of breeding lines requires laborious bioassays that are time-consuming and require experienced researchers. In these bioassays, quantifying nematode eggs through manual counting is considered the current standard for quantifying establishing resistance in plant genotypes. Counting RKN eggs is highly laborious, and even experienced researchers are subject to fatigue or misclassification, leading to potential errors in phenotyping. Here, we present three automated egg counting models that rely on machine learning and image analysis to quantify RKN eggs extracted from tobacco and sweetpotato plants. The first method relied on convolutional neural networks trained using annotated images to identify eggs (M. enterolobii R2 = 0.899, M. incognita R2 = 0.927, M. javanica R2 = 0.886), while a second contour-based approach used image analysis to identify eggs from their morphological characteristics and did not rely on neural networks (M. enterolobii R2 = 0.977, M. incognita R2 = 0.990, M. javanica R2 = 0.924). A third hybrid model combined these approaches and was able to detect and count eggs nearly as well as human raters (M. enterolobii R2 = 0.985, M. incognita R2 = 0.992, M. javanica R2 = 0.983). These automated counting protocols have the potential to provide significant time and resource savings annually for breeders and nematologists, and may be broadly applicable to other nematode species.

ngsComposer: an automated pipeline for empirically based NGS data quality filtering.

Next-generation sequencing (NGS) enables massively parallel acquisition of large-scale omics data; however, objective data quality filtering parameters are lacking. Although a useful metric, evidence reveals that platform-generated Phred values overestimate per-base quality scores. We have developed novel and empirically based algorithms that streamline NGS data quality filtering. The pipeline leverages known sequence motifs to enable empirical estimation of error rates, detection of erroneous base calls and removal of contaminating adapter sequence. The performance of motif-based error detection and quality filtering were further validated with read compression rates as an unbiased metric. Elevated error rates at read ends, where known motifs lie, tracked with propagation of erroneous base calls. Barcode swapping, an inherent problem with pooled libraries, was also effectively mitigated. The ngsComposer pipeline is suitable for various NGS protocols and platforms due to the universal concepts on which the algorithms are based.

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.

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.

Sweetpotato Root Development Influences Susceptibility to Black Rot Caused by the Fungal Pathogen Ceratocystis fimbriata.

Black rot of sweetpotato, caused by Ceratocystis fimbriata, is an important reemerging disease threatening sweetpotato production in the United States. This study assessed disease susceptibility of the storage root surface, storage root cambium, and slips (vine cuttings) of 48 sweetpotato cultivars, advanced breeding lines, and wild relative accessions. We also characterized the effect of storage root development on susceptibility to C. fimbriata. None of the cultivars examined at the storage root level were resistant, with most cultivars exhibiting similar levels of susceptibility. In storage roots, Jewel and Covington were the least susceptible and significantly different from White Bonita, the most susceptible cultivar. In the slip, significant differences in disease incidence were observed for above- and below-ground plant structures among cultivars, advanced breeding lines, and wild relative accessions. Burgundy and Ipomoea littoralis displayed less below-ground disease incidence compared with NASPOT 8, Sunnyside, and LSU-417, the most susceptible cultivars. Correlation of black rot susceptibility between storage roots and slips was not significant, suggesting that slip assays are not useful to predict resistance in storage roots. Immature, early-developing storage roots were comparatively more susceptible than older, fully developed storage roots. The high significant correlation between the storage root cross-section area and the cross-sectional lesion ratio suggests the presence of an unfavorable environment for C. fimbriata as the storage root develops. Incorporating applications of effective fungicides at transplanting and during early-storage root development when sweetpotato tissues are most susceptible to black rot infection may improve disease management efforts.

Screening Sweetpotato Genotypes for Resistance to a North Carolina Isolate of Meloidogyne enterolobii.

Potential resistance to the guava root-knot nematode, Meloidogyne enterolobii, in 91 selected sweetpotato (Ipomoea batatas [L.] Lam.) genotypes was evaluated in six greenhouse experiments. Ten thousand eggs of M. enterolobii were inoculated on each sweetpotato genotype grown in a 3:1 sand to soil mixture. Sixty days after inoculation, the percentage of total roots with nematode-induced galls was determined, and nematode eggs were extracted from roots. Significant differences (P < 0.001) between sweetpotato genotypes were found in all six tests for gall rating, total eggs, and eggs per gram of root. Resistant sweetpotato genotypes were calculated as final eggs per root system divided by the initial inoculum, where Pf/Pi < 1 (reproduction factor; final egg count divided by initial inoculum of 10,000 eggs), and statistical mean separations were confirmed by Fisher's least significant difference t test. Our results indicated that 19 out of 91 tested sweetpotato genotypes were resistant to M. enterolobii. Some of the susceptible genotypes included 'Covington,' 'Beauregard,' 'NCDM04-001', and 'Hernandez.' Some of the resistant sweetpotato genotypes included 'Tanzania,' 'Murasaki-29,' 'Bwanjule,' 'Dimbuka-Bukulula,' 'Jewel,' and 'Centennial.' Most of the 19 resistant sweetpotato genotypes supported almost no M. enterolobii reproduction, with <20 eggs/g root of M. enterolobii. A number of segregants from a 'Tanzania' × 'Beauregard' cross demonstrated strong resistance to M. enterolobii observed in the 'Tanzania' parent. In collaboration with North Carolina State University sweetpotato breeding program, several genotypes evaluated in these tests are being used to incorporate the observed resistance to M. enterolobii into commercial sweetpotato cultivars.

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.

Quantitative trait loci and differential gene expression analyses reveal the genetic basis for negatively associated ß-carotene and starch content in hexaploid sweetpotato [Ipomoea batatas (L.) Lam.].

KEY MESSAGE: ß-Carotene content in sweetpotato is associated with the Orange and phytoene synthase genes; due to physical linkage of phytoene synthase with sucrose synthase, ß-carotene and starch content are negatively correlated. In populations depending on sweetpotato for food security, starch is an important source of calories, while ß-carotene is an important source of provitamin A. The negative association between the two traits contributes to the low nutritional quality of sweetpotato consumed, especially in sub-Saharan Africa. Using a biparental mapping population of 315 F1 progeny generated from a cross between an orange-fleshed and a non-orange-fleshed sweetpotato variety, we identified two major quantitative trait loci (QTL) on linkage group (LG) three (LG3) and twelve (LG12) affecting starch, ß-carotene, and their correlated traits, dry matter and flesh color. Analysis of parental haplotypes indicated that these two regions acted pleiotropically to reduce starch content and increase ß-carotene in genotypes carrying the orange-fleshed parental haplotype at the LG3 locus. Phytoene synthase and sucrose synthase, the rate-limiting and linked genes located within the QTL on LG3 involved in the carotenoid and starch biosynthesis, respectively, were differentially expressed in Beauregard versus Tanzania storage roots. The Orange gene, the molecular switch for chromoplast biogenesis, located within the QTL on LG12 while not differentially expressed was expressed in developing roots of the parental genotypes. We conclude that these two QTL regions act together in a cis and trans manner to inhibit starch biosynthesis in amyloplasts and enhance chromoplast biogenesis, carotenoid biosynthesis, and accumulation in orange-fleshed sweetpotato. Understanding the genetic basis of this negative association between starch and ß-carotene will inform future sweetpotato breeding strategies targeting sweetpotato for food and nutritional security.

Assessing Rate-Reducing Foliar Resistance to Anthracnose Crown Rot and Fruit Rot in Strawberry.

Anthracnose fruit rot and anthracnose crown rot (ACR) caused by two species complexes of the fungus referred to as Colletotrichum acutatum and Colletotrichum gloeosporioides, respectively, are major pathogens of strawberry in North Carolina. Anthracnose epidemics are common when susceptible cultivars and asymptomatic planting stocks carrying quiescent Colletotrichum infection or hemibiotrophic infection (HBI) are planted. The main objective of this study was to assess resistance to HBI and ACR in strawberry. Strawberry cultivars and breeding lines were spray inoculated with isolates of C. acutatum or C. gloeosporioides. Four epidemiological parameters providing estimates of rate-reducing resistance to HBI and ACR in strawberry cultivars and lines were evaluated in repeated experiments in controlled environments in a greenhouse. HBI severity, measured as the percentage of total leaf area covered by acervuli, was estimated visually and by image analysis. ACR severity was rated weekly for wilt symptoms, and relative area under disease progress curve scores were calculated for comparing strawberry cultivars and lines. Significant differences (P ≤ 0.005) in HBI severity were found among strawberry genotypes; however, the correlations were not remarkable between Colletotrichum species (r = 0.4251). Although significant variation in resistance was observed for ACR, this was also weakly correlated (r = 0.2430) with resistance to C. gloeosporioides HBI. Overall, rate-reducing resistance to HBI and ACR in strawberry identified in this study could be utilized in breeding programs to develop durable resistance to anthracnose in North Carolina.

Inheritance of Resistance to Colletotrichum gloeosporioides and C. acutatum in Strawberry.

Information on the inheritance of resistance to Colletotrichum gloeosporioides and C. acutatum hemibiotrophic infections (HBI) in strawberry leaf tissue and the genetic control of anthracnose crown rot (ACR) in crown tissue are relatively unknown. Six parental genotypes were crossed in a half-diallel mating design to generate 15 full-sib families. HBI and ACR experiments were conducted concurrently. Both seedlings and parental clones were inoculated with 1 × 106 conidia/ml of C. gloeosporioides or C. acutatum. Percent sporulating leaf area, wilt symptoms, and relative area under the disease progress curve were calculated to characterize resistance among genotypes and full-sib families. Low dominance/additive variance ratios for C. acutatum HBI (0.13) and C. gloeosporioides ACR (0.20) were observed, indicating additive genetic control of resistance to these traits. Heritability estimates were low for C. acutatum HBI (0.25) and C. gloeosporioides HBI (0.16) but moderate for C. gloeosporioides ACR (0.61). A high genetic correlation (rA = 0.98) between resistance to C. acutatum HBI and C. gloeosporioides HBI was observed, suggesting that resistance to these two Colletotrichum spp. may be controlled by common genes in strawberry leaf tissue. In contrast, negative genetic correlations between ACR and both HBI traits (rA = -0.85 and -0.61) suggest that resistance in crown tissue is inherited independently of resistance in leaf tissue in the populations tested. Overall, these findings provide valuable insight into the genetic basis of resistance, and the evaluation and deployment of resistance to HBIs and ACR in strawberry breeding programs.

Linkage analysis and QTL mapping in a tetraploid russet mapping population of potato.

BACKGROUND: Genome-wide single nucleotide polymorphism (SNP) markers coupled with allele dosage information has emerged as a powerful tool for studying complex traits in cultivated autotetraploid potato (Solanum tuberosum L., 2n = 4× = 48). To date, this approach has been effectively applied to the identification of quantitative trait loci (QTLs) underlying highly heritable traits such as disease resistance, but largely unexplored for traits with complex patterns of inheritance. RESULTS: In this study, an F1 tetraploid russet mapping population (162 individuals) was evaluated for multiple quantitative traits over two years and two locations to identify QTLs associated with tuber sugar concentration, processing quality, vine maturity, and other high-value agronomic traits. We report the linkage maps for the 12 potato chromosomes and the QTL location with corresponding genetic models and candidate SNPs explaining the highest phenotypic variation for tuber quality and maturity related traits. Significant QTLs for tuber glucose concentration and tuber fry color were detected on chromosomes 4, 5, 6, 10, and 11. Collectively, these QTLs explained between 24 and 46% of the total phenotypic variation for tuber glucose and fry color, respectively. The QTL on chromosome 10 was associated with apoplastic invertases, with 'Premier Russet' contributing the favorable allele for fry processing quality. On chromosome 5, minor-effect QTLs for tuber glucose concentration and fry color co-localized with various major-effect QTLs, including vine maturity, growth habit, tuber shape, early blight (Altenaria tenuis), and Verticillium wilt (Verticillium spp.). CONCLUSIONS: Linkage analysis and QTL mapping in a russet mapping population (A05141) using SNP dosage information successfully identified favorable alleles and candidate SNPs for resistance to the accumulation of tuber reducing sugars. These novel markers have a high potential for the improvement of tuber processing quality. Moreover, the discovery of different genetic models for traits with overlapping QTLs at the maturity locus clearly suggests an independent genetic control.

Linkage map construction and QTL analysis for internal heat necrosis in autotetraploid potato.

KEY MESSAGE: A tetraploid potato population was mapped for internal heat necrosis (IHN) using the Infinium ® 8303 potato SNP array, and QTL for IHN were identified on chromosomes 1, 5, 9 and 12 that explained 28.21% of the variation for incidence and 25.3% of the variation for severity. This research represents a significant step forward in our understanding of IHN, and sets the stage for future research focused on testing the utility of these markers in additional breeding populations. Internal heat necrosis (IHN) is a significant non-pathogenic disorder of potato tubers and previous studies have identified AFLP markers linked to IHN susceptibility in the tetraploid, B2721 potato mapping population. B2721 consists of an IHN susceptible×resistant cross: Atlantic×B1829-5. We developed a next-generation SNP-based linkage map of this cross using the Infinium® 8303 SNP array and conducted additional QTL analyses of IHN susceptibility in the B2721 population. Using SNP dosage sensitive markers, linkage maps for both parents were simultaneously analyzed. The linkage map contained 3427 SNPs and totaled 1397.68 cM. QTL were detected for IHN on chromosomes 1, 5, 9, and 12 using LOD permutation thresholds and colocation of high LOD scores across multiple years. Genetic effects were modeled for each putative QTL. Markers associated with a QTL were regressed in models of effects for IHN incidence and severity for all years. In the full model, the SNP markers were shown to have significant effects for IHN (p < 0.0001), and explained 28.21% of the variation for incidence and 25.3% of the variation for severity. We were able to utilize SNP dosage information to identify and model the effects of putative QTL, and identify SNP loci associated with IHN resistance that need to be confirmed. This research represents a significant step forward in our understanding of IHN, and sets the stage for future research focused on testing the utility of these markers in additional breeding populations.

Genetic analysis and association of simple sequence repeat markers with storage root yield, dry matter, starch and ß-carotene content in sweetpotato.

Molecular markers are needed for enhancing the development of elite sweetpotato (Ipomoea batatas (L.) Lam) cultivars with a wide range of commercially important traits in sub-Saharan Africa. This study was conducted to estimate the heritability and determine trait correlations of storage root yield, dry matter, starch and ß-carotene content in a cross between 'New Kawogo' × 'Beauregard'. The study was also conducted to identify simple sequence repeat (SSR) markers associated with these traits. A total of 287 progeny and the parents were evaluated for two seasons at three sites in Uganda and genotyped with 250 SSR markers. Broad sense heritability (H2) for storage root yield, dry matter, starch and ß-carotene content were 0.24, 0.68, 0.70 and 0.90, respectively. Storage root ß-carotene content was negatively correlated with dry matter (r = -0.59, P < 0.001) and starch (r = -0.93, P < 0.001) content, while storage root yield was positively correlated with dry matter (r = 0.57, P = 0.029) and starch (r = 0.41, P = 0.008) content. Through logistic regression, a total of 12, 4, 6 and 8 SSR markers were associated with storage root yield, dry matter, starch and ß-carotene content, respectively. The SSR markers used in this study may be useful for quantitative trait loci analysis and selection for these traits in future.

Conventional breeding, marker-assisted selection, genomic selection and inbreeding in clonally propagated crops: a case study for cassava.

Consolidates relevant molecular and phenotypic information on cassava to demonstrate relevance of heterosis, and alternatives to exploit it by integrating different tools. Ideas are useful to other asexually reproduced crops. Asexually propagated crops offer the advantage that all genetic effects can be exploited in farmers' production fields. However, non-additive effects complicate selection because, while influencing the performance of the materials under evaluation, they cannot be transmitted efficiently to the following cycle of selection. Cassava can be used as a model crop for asexually propagated crops because of its diploid nature and the absence of (known) incompatibility effects. New technologies such as genomic selection (GS), use of inbred progenitors based on doubled haploids and induction of flowering can be employed for accelerating genetic gains in cassava. Available information suggests that heterosis, non-additive genetic effects and within-family variation are relatively large for complex traits such as fresh root yield, moderate for dry matter or starch content in the roots, and low for defensive traits (pest and disease resistance) and plant architecture. The present article considers the potential impact of different technologies for maximizing gains for key traits in cassava, and highlights the advantages of integrating them. Exploiting heterosis would be optimized through the implementation of reciprocal recurrent selection. The advantages of using inbred progenitors would allow shifting the current cassava phenotypic recurrent selection method into line improvement, which in turn would allow designing outstanding hybrids rather than finding them by trial and error.

Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato.

Plant-insect interactions are often influenced by host- or insect-associated metagenomic community members. The relative abundance of insects and the microbes that modulate their interactions were obtained from sweetpotato (Ipomoea batatas) leaf-associated metagenomes using quantitative reduced representation sequencing and strain/species-level profiling with the Qmatey software. Positive correlations were found between whitefly (Bemisia tabaci) and its endosymbionts (Candidatus Hamiltonella defensa, Candidatus Portiera aleyrodidarum, and Rickettsia spp.) and negative correlations with nitrogen-fixing bacteria that implicate nitric oxide in sweetpotato-whitefly interaction. Genome-wide associations using 252 975 dosage-based markers, and metagenomes as a covariate to reduce false positive rates, implicated ethylene and cell wall modification in sweetpotato-whitefly interaction. The predictive abilities (PA) for whitefly and Ocypus olens abundance were high in both populations (68%-69% and 33.3%-35.8%, respectively) and 69.9% for Frankliniella occidentalis. The metagBLUP (gBLUP) prediction model, which fits the background metagenome-based Cao dissimilarity matrix instead of the marker-based relationship matrix (G-matrix), revealed moderate PA (35.3%-49.1%) except for O. olens (3%-10.1%). A significant gain in PA after modeling the metagenome as a covariate (gGBLUP, ≤11%) confirms quantification accuracy and that the metagenome modulates phenotypic expression and might account for the missing heritability problem. Significant gains in PA were also revealed after fitting allele dosage (≤17.4%) and dominance effects (≤4.6%). Pseudo-diploidized genotype data underperformed for dominance models. Including segregation-distorted loci (SDL) increased PA by 6%-17.1%, suggesting that traits associated with fitness cost might benefit from the inclusion of SDL. Our findings confirm the holobiont theory of host-metagenome co-evolution and underscore its potential for breeding within the context of G × G × E interactions.

Heterotic gains, transgressive segregation and fitness cost of sweetpotato weevil resistance expression in a partial diallel cross of sweetpotato.

Heterosis-exploiting breeding schemes are currently under consideration as a means of accelerating genetic gains in sweetpotato (Ipomoea batatas) breeding. This study was aimed at establishing heterotic gains, fitness costs and transgressive segregation associated with sweetpotato weevil (SPW) resistance in a partial diallel cross of sweetpotato. A total of 1896 clones were tested at two sites, for two seasons each in Uganda. Data on weevil severity (WED), weevil incidence (WI), storage root yield (SRY) and dry matter content (DM) were obtained. Best linear unbiased predictors (BLUPs) for each clone across environments were used to estimate heterotic gains and for regression analyses to establish relationships between key traits. In general, low mid-parent heterotic gains were detected with the highest favorable levels recorded for SRY (14.7%) and WED (- 7.9%). About 25% of the crosses exhibited desirable and significant mid-parent heterosis for weevil resistance. Over 16% of the clones displayed superior transgressive segregation, with the highest percentages recorded for SRY (21%) and WED (18%). A yield penalty of 10% was observed to be associated with SPW resistance whereas no decline in DM was detected in relation to the same. Chances of improving sweetpotato through exploiting heterosis in controlled crosses using parents of mostly similar background are somewhat minimal, as revealed by the low heterotic gains. The yield penalty detected due to SPW resistance suggests that a trade-off may be necessary between maximizing yields and developing weevil-resistant cultivars if the current needs for this crop are to be met in weevil-prone areas.

Genotype-independent plant transformation.

Plant transformation and regeneration remain highly species- and genotype-dependent. Conventional hormone-based plant regeneration via somatic embryogenesis or organogenesis is tedious, time-consuming, and requires specialized skills and experience. Over the last 40 years, significant advances have been made to elucidate the molecular mechanisms underlying embryogenesis and organogenesis. These pioneering studies have led to a better understanding of the key steps and factors involved in plant regeneration, resulting in the identification of crucial growth and developmental regulatory genes that can dramatically improve regeneration efficiency, shorten transformation time, and make transformation of recalcitrant genotypes possible. Co-opting these regulatory genes offers great potential to develop innovative genotype-independent genetic transformation methods for various plant species, including specialty crops. Further developing these approaches has the potential to result in plant transformation without the use of hormones, antibiotics, selectable marker genes, or tissue culture. As an enabling technology, the use of these regulatory genes has great potential to enable the application of advanced breeding technologies such as genetic engineering and gene editing for crop improvement in transformation-recalcitrant crops and cultivars. This review will discuss the recent advances in the use of regulatory genes in plant transformation and regeneration, and their potential to facilitate genotype-independent plant transformation and regeneration.

Genetic diversity, population structure, and selection of breeder germplasm subsets from the USDA sweetpotato (Ipomoea batatas) collection.

Sweetpotato (Ipomoea batatas) is the sixth most important food crop and plays a critical role in maintaining food security worldwide. Support for sweetpotato improvement research in breeding and genetics programs, and maintenance of sweetpotato germplasm collections is essential for preserving food security for future generations. Germplasm collections seek to preserve phenotypic and genotypic diversity through accession characterization. However, due to its genetic complexity, high heterogeneity, polyploid genome, phenotypic plasticity, and high flower production variability, sweetpotato genetic characterization is challenging. Here, we characterize the genetic diversity and population structure of 604 accessions from the sweetpotato germplasm collection maintained by the United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Plant Genetic Resources Conservation Unit (PGRCU) in Griffin, Georgia, United States. Using the genotyping-by-sequencing platform (GBSpoly) and bioinformatic pipelines (ngsComposer and GBSapp), a total of 102,870 polymorphic SNPs with hexaploid dosage calls were identified from the 604 accessions. Discriminant analysis of principal components (DAPC) and Bayesian clustering identified six unique genetic groupings across seven broad geographic regions. Genetic diversity analyses using the hexaploid data set revealed ample genetic diversity among the analyzed collection in concordance with previous analyses. Following population structure and diversity analyses, breeder germplasm subsets of 24, 48, 96, and 384 accessions were established using K-means clustering with manual selection to maintain phenotypic and genotypic diversity. The genetic characterization of the PGRCU sweetpotato germplasm collection and breeder germplasm subsets developed in this study provide the foundation for future association studies and serve as precursors toward phenotyping studies aimed at linking genotype with phenotype.