Abstract Over the past decade there has been increasing interest in the use of microhaplotype markers in autopolyploid taxa. This has been driven by theoretical and observed improvements in signals of allelic dosage, linkage, and heritability. Yet, to date there has been little investigation into the suitability of microhaplotype markers for estimating kinship. Here, we develop the theory of kinship estimation from microhaplotypes, introduce the MCHap microhaplotype caller for autopolyploid populations, and apply these methods to a highly diverse germplasm population of mixed-ploidy Actinidia (kiwifruit and relatives). We find that microhaplotype-based kinship estimates are generally superior to equivalent single nucleotide variant based estimates. This is because microhaplotypes minimize the coalescent signal among alleles which may bias estimates within the context of a recent reference population. Hence, kinship estimates from microhaplotypes more accurately capture the recent demographic history of a population. These findings are supported by both coalescent simulations and the analysis of real data. Our findings are relevant to organisms of any ploidy, but most actionable in highly heterozygous taxa such as Actinidia .

In breeding programmes, accurate estimation of breeding values is crucial for selecting superior genotypes. Traditional methods rely on phenotypic observations and pedigree information to estimate variance components and heritability. However, pedigree errors can significantly affect the accuracy of these estimates, especially in long-lived perennial vines. This study evaluates the effect of pedigree errors on breeding value predictions in kiwiberry breeding and explores the benefits of using genomic selection. We applied Best Linear Unbiased Prediction (BLUP) to estimate breeding values for each genotype for a given trait. Four scenarios with varying degrees of alteration in pedigree-based relationship matrices were used to represent inaccurate relationships between genotypes. Pedigree-based breeding values were compared with genomic estimated breeding values for one vine-related and four fruit-related quantitative traits. The results showed that as the degree of altered population structure increased, the prediction accuracy of pedigree-based breeding values decreased. In contrast, genomic selection, which uses marker inheritance, maintained realised relationships between genotypes, making it a more robust method for predicting genetic merit. In kiwiberries, as in all species of the genus Actinidia, only female vines bear fruit. The genotypic merit of fruit-related traits in male genotypes can only be estimated indirectly. Marker-based predictions outperformed pedigree-based predictions, especially for genotypes without phenotypic observations, such as male siblings. This study reviewed the induced population structures and introduced genomic selection into the kiwiberry breeding programme. We demonstrated that genomic selection provides more accurate breeding values by capturing true genetic relationships and reducing the effects of misidentified relationships between individuals.

Disentangling genotype × environment (G×E) effects is critical to understand the performance of wheat across different environments. A framework for doing this was previously presented in a model that integrated knowledge of crop physiology and the Vrn gene feedback loop to explain and predict the time of anthesis. The aims of this study were: 1) provide an updated description of the Cereal Anthesis Molecular Phenology (CAMP) model; 2) to verify the model’s assumptions regarding the relationship between Vrn gene expression and the timing of phenological stages in a set of diverse genotypes and environments; 3) to use the CAMP model to establish a phenotyping strategy for use in genetic studies and model parameterisation. Six wheat genotypes with a range of cool temperature and photoperiod sensitivities were evaluated. Apical development, final leaf number (FLN) and temporal expression of Vrn1, Vrn2 and Vrn3 were compared with model predictions. There was a clear relationship between FLN responses to cool temperature and photoperiod, the timing of phenological events and the patterns of Vrn gene expression for all genotypes. There was general agreement between the temporal patterns of foliar gene expression observed with those assumed by CAMP, but some obvious discrepancies. These may be related to differences between gene expression in foliar (observed) and apical (assumed by the model) parts of the plant, or differences in the way observed and modelled gene expression are scaled. Overall, the model described all the observed development responses to environment and provides a basis for building quantitative predictions of field-based development from genotypic and environmental data. A protocol is presented for phenotyping wheat using FLN measured in specific combinations of temperature and photoperiod. It allows easy and unconfounded measure of key developmental phenotypes that clearly relate to the genetic make-up of the plants and underlying gene expression profiles. ### Competing Interest Statement The authors have declared no competing interest. Ministry of Business, Innovation and Employment (MBIE) Strategic Science Investment Fund, Sustainable Agro-ecosystems Grains Research and Development Corporation, National Phenology Initiative (ULA00011)

Allium crop breeding remains severely hindered due to the lack of high-quality reference genomes. Here we report high-quality chromosome-level genome assemblies for three key Allium crops (Welsh onion, garlic and onion), which are 11.17 Gb, 15.52 Gb and 15.78 Gb in size with the highest recorded contig N50 of 507.27 Mb, 109.82 Mb and 81.66 Mb, respectively. Beyond revealing the genome evolutionary process of Allium species, our pathogen infection experiments and comparative metabolomic and genomic analyses showed that genes encoding enzymes involved in the metabolic pathway of Allium -specific flavor compounds may have evolved from an ancient uncharacterized plant defense system widely existing in many plant lineages but extensively boosted in alliums. Using in situ hybridization and spatial RNA sequencing, we obtained an overview of cell-type categorization and gene expression changes associated with spongy mesophyll cell expansion during onion bulb formation, thus indicating the functional roles of bulb formation genes.

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.

DATA REPORT article Front. Genet., 16 May 2022Sec. Plant Genomics https://doi.org/10.3389/fgene.2022.852161

Commercially grown kiwifruit (genus Actinidia) are generally of two sub-species which have a base haploid genome of 29 chromosomes. The yellow-fleshed Actinidia chinensis var. chinensis, is either diploid (2n = 2x = 58) or tetraploid (2n = 4x = 116) and the green-fleshed cultivar A. chinensis var. deliciosa "Hayward," is hexaploid (2n = 6x = 174). Advances in breeding green kiwifruit could be greatly sped up by the use of molecular resources for more efficient and faster selection, for example using marker-assisted selection (MAS). The key genetic marker that has been implemented for MAS in hexaploid kiwifruit is for gender testing. The limited marker-trait association has been reported for other polyploid kiwifruit for fruit and production traits. We have constructed a high-density linkage map for hexaploid green kiwifruit using genotyping-by-sequence (GBS). The linkage map obtained consists of 3686 and 3940 markers organized in 183 and 176 linkage groups for the female and male parents, respectively. Both parental linkage maps are co-linear with the A. chinensis "Red5" reference genome of kiwifruit. The linkage map was then used for quantitative trait locus (QTL) mapping, and successfully identified QTLs for king flower number, fruit number and weight, dry matter accumulation, and storage firmness. These are the first QTLs to be reported and discovered for complex traits in hexaploid kiwifruit.

A combine harvester provides unique capabilities as a mobile sensing platform. This chapter aims to contribute to the advancement of on-combine sensor use for obtaining site-specific crop data by trying to convince potential users in the agricultural community of its value and accessibility. Today, mass/volume flow and electrical capacitance sensors are widely used for measuring grain yield and moisture. A variety of other sensors have been used in crop analysis and process control that include photoelectronic spectrometers for analysis of crop quality attributes as well as ultrasonic and laser sensors for quantifying aboveground biomass. Applications of this information include precision N management, post-harvest assessment of crop stress, grain segregation by protein concentration and mapping of late-season weed infestations. Barriers challenging wider adoption of on-combine sensing techniques include the need for (i) software for exploring multi-year yield data and constructing profit zones, (ii) inexpensive spectrometers for grain quality measurement and mapping, (iii) commercial firms offering services in spectroscopy, custom mapping and data fusion, (iv) stand-alone units with user interface and firmware for multi-sensor data collection, and (v) field studies demonstrating economic benefits of various applications of information from on-combine sensing.

Weed maps created late in the growing season are potentially useful in regions where late maturing weeds are problematic and need to be controlled before they produce seed. The objectives of this study were to (1) spatially characterize the population dynamics of predominant weed species and apply this information into quantifying the effect of treated and untreated weed infestations on wheat (Triticum aestivum L.) yields and (2) evaluate potential herbicide savings with post-harvest site-specific treatments. Multi-year grain yield and weed data were acquired at harvest in each of four years (2015–18) within a dryland production field (9.2 ha) in eastern Oregon. Abundance of weed species (2015) and percent cover of weed species (2016, 2017 and 2018) were visually estimated on a square grid based on dividing the field into 7-m2 cells. Spatial patterns in the weed community were subject to rapid change and depended on year, crop and weed control strategy. While tumble mustard (Sisymbrium altissimum) was the most predominant and competitive species, the spatial distribution of this weed and that of other species varied each year. Tumble mustard and prickly lettuce (Lactuca serriola) were equally problematic in spring wheat and winter wheat whereas Russian thistle (Salsola tragus) was problematic in spring wheat and downy brome (Bromus tectorum) in winter wheat. Potential savings from site-specific herbicide application varied from 10 to 95% based on percentage of field infested. Weed maps at harvest are useful for studying weed dynamics, identifying potentially herbicide-resistant weeds and planning site-specific weed management. Combined with yield maps, weed maps at harvest are also useful for explaining crop yield variability that is associated with weed competition and weed control in furtherance of integrated weed management strategies.

An on-combine, near infrared (NIR) spectrometer is now commercially available for mapping grain protein concentration (GPC) within farm fields. Costing > US$20,000, this specialized instrument may not be affordable for all producers. The objective of this study was to adapt and evaluate a moderately priced reflectance spectrometer ( < US$5500, Avantes AvaSpec ULS2048 x 16-USB2) for on-combine sensing of GPC. A "leave-one-out" cross-validation partial least square (PLS) regression model for GPC was developed for flowing grain with the spectrometer's probe-head attached to the lower end of an inclined trough. Good correlation (r(2) = 0.92) was observed between estimated and reference GPC in grain samples when NIR spectra (850-1040 nm) and GPC reference values were used for developing the PLS model. The NIR estimation achieved a standard error of < 5 g of protein kg(-1) of grain. An inexpensive external temperature control system was built that stabilized the temperature of the instrument's input/output converter board within 60 m of activation. Placed on a test stand machine with standard 12.5 cm diameter auger, the instrument predicted GPC to < 5 and < 10 g kg(-1) in two and three of four wheat cultivars thus indicating that the model produced on the trough may be applied into predicting GPC on a combine. When placed on a combine, the calibrated instrument produced a protein map that correlated well (r = 0.88) with a map derived from an expensive reflectance spectrometer (US$32,000, Polytec 1721). Thus, a relatively inexpensive NIR reflectance spectrometer may be adapted for mapping GPC across fields.

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.

BackgroundAngiosperm sex chromosomes, where present, are generally recently evolved. The key step in initiating the development of sex chromosomes from autosomes is the establishment of a sex-determining locus within a region of non-recombination. To better understand early sex chromosome evolution, it is important to determine the process by which recombination is suppressed around the sex determining genes. We have used the dioecious angiosperm kiwifruit Actinidia chinensis var. chinensis, which has an active-Y sex chromosome system, to study recombination rates around the sex locus, to better understand key events in the development of sex chromosomes.ResultsWe have confirmed the sex-determining region (SDR) in A. chinensis var. chinensis, using a combination of high density genetic mapping and fluorescent in situ hybridisation (FISH) of Bacterial Artificial Chromosomes (BACs) linked to the sex markers onto pachytene chromosomes. The SDR is a subtelomeric non-recombining region adjacent to the nucleolar organiser region (NOR). A region of restricted recombination of around 6Mbp in size in both male and female maps spans the SDR and covers around a third of chromosome 25.ConclusionsAs recombination is suppressed over a similar region between X chromosomes and between and X and Y chromosomes, we propose that recombination is suppressed in this region because of the proximity of the NOR and the centromere, with both the NOR and centromere suppressing recombination, and this predates suppressed recombination due to differences between X and Y chromosomes. Such regions of suppressed recombination in the genome provide an opportunity for the evolution of sex chromosomes, if a sex-determining locus develops there or translocates into this region.

Pseudomonas syringae pv. actinidiae (Psa) Biovar 3, a virulent, canker-inducing pathogen is an economic threat to the kiwifruit ( Actinidia spp.) industry worldwide. The commercially grown diploid (2 x ) A. chinensis var. chinensis is more susceptible to Psa than tetraploid and hexaploid kiwifruit. However information on the genetic loci modulating Psa resistance in kiwifruit is not available. Here we report mapping of quantitative trait loci (QTLs) regulating tolerance to Psa in a diploid kiwifruit population, derived from a cross between an elite Psa-susceptible ‘Hort16A’ and a tolerant male breeding parent P1. Using high-density genetic maps and intensive phenotyping, we identified a single QTL for Psa tolerance on Linkage Group (LG) 27 of ‘Hort16A’ revealing 16-19% phenotypic variance and candidate alleles for susceptibility and tolerance at this loci. In addition, six minor QTLs were identified in P1 on distinct LGs, exerting 4-9% variance. Complete tolerance in the F1 population is attained by additive effects from ‘Hort16A’ and P1 QTLs providing evidence that divergent genetic pathways fend-off virulent Psa strain. Two different bioassays further identified new QTLs for tissue-specific responses to Psa. Transcriptome analysis of Psa-tolerant and susceptible genotypes in field revealed hallmarks of basal defense and provided candidate RNA-biomarkers for screening Psa tolerance.

During analysis of kiwifruit derived from hybrids between the high vitamin C (ascorbic acid; AsA) species Actinidia eriantha and A. chinensis, we observed bimodal segregation of fruit AsA concentration suggesting major gene segregation. To test this hypothesis, we performed whole-genome sequencing on pools of hybrid genotypes with either high or low AsA fruit. Pool-GWAS (genome-wide association study) revealed a single Quantitative Trait Locus (QTL) spanning more than 5 Mbp on chromosome 26, which we denote as qAsA26.1. A co-dominant PCR marker was used to validate this association in four diploid (A. chinensis × A. eriantha) × A. chinensis backcross families, showing that the A. eriantha allele at this locus increases fruit AsA levels by 250 mg/100 g fresh weight. Inspection of genome composition and recombination in other A. chinensis genetic maps confirmed that the qAsA26.1 region bears hallmarks of suppressed recombination. The molecular fingerprint of this locus was examined in leaves of backcross validation families by RNA sequencing (RNASEQ). This confirmed strong allelic expression bias across this region as well as differential expression of transcripts on other chromosomes. This evidence suggests that the region harbouring qAsA26.1 constitutes a supergene, which may condition multiple pleiotropic effects on metabolism.

Ability to conduct molecular analyses in Allium species was previously limited by the power of available technologies to sample very large heterozygous genomes in a cost-effective manner. The emergence of third-generation long-read sequencing technologies, coupled with maturing strategies for population genomics in non-model systems provides exciting opportunities for Allium crops. Now that these technical advances have removed major barriers to progress, it is necessary to consider the horticultural resources to which we can apply such technologies. This will hasten delivery of genetics tools that will ultimately benefit breeders, farmers, and consumers of Allium vegetables. Here, we describe progress to date in Allium mapping, with an emphasis on onion, and review approaches used on other non-model systems that could be applied. We also present strategies we have developed over the past decade to establish genetic stocks for onion suited to modern population genomics analyses.

Bulb onion ( Allium cepa L.) is a challenging subject for experimental studies because of its slow growth, genetic heterogeneity, and sensitivity to environmental and biotic stresses. Sharing of common germplasm and controlled propagation practices has underpinned research on model plants, such as Arabidopsis and tomato, but not in onion. To encourage wider evaluation of onion for physiological and molecular studies in controlled environments, we describe the growing practices we have developed over two decades of research on adaptive and nutrient assimilation traits. Key aspects covered include choice of germplasm, propagation media, nutrition, and environmental control. Adopting common onion genetics and cultivation techniques across laboratories will allow researchers to answer deeper research questions and increase the reproducibility of the research.

BACKGROUND:To facilitate faster phenotyping of onions (Allium cepa L.), Fourier-transform mid infrared (FT-MIR) spectroscopy with partial least squares (PLS) regression modelling was evaluated for the determination of pungency (pyruvate), sweetness (free sugars) and fructan in juice samples (n = 605) expressed from bulbs from breeding populations.RESULTS:Fourier-transform infrared (FTIR) spectra (range 1700-900 cm-1 ) were obtained from droplets (30 μL) of unprocessed juice. Goodness-of-fit (r2 ) and prediction errors (standard error of cross validation) for optimal PLS models were: soluble solids (0.997, 0.1 °Brix), pyruvate [0.825, 0.8 μmol g-1 fresh weight (FW)], fructan (0.98, 1.9 mg g-1 FW), glucose (0.941, 1.1 mg g-1 FW), fructose (0.967, 1.0 mg g-1 FW) and sucrose (0.919, 1.7 mg g-1 FW). FTIR models for industry sweetness indices based on glucose or sucrose equivalents were also developed. Because of its very low concentration (0.8-12 μmol g-1 FW) relative to other compounds, pyruvate was the weakest model developed. Fructan could be determined spectroscopically without the need for enzymatic digestion.CONCLUSIONS:All of the chemometric models developed are acceptable for screening purposes. Those for soluble solids, fructan and fructose are also suitable for routine analysis. FT-MIR can therefore be utilised for the simultaneous determination of pungency, sweetness and fructan in this crop. © 2018 Society of Chemical Industry.

Background: Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164 Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models. Results: A second genome of an A. chinensis (genotype Red5) was fully sequenced. This new sequence resulted in a 554.0 Mb assembly with all but 6 Mb assigned to pseudo-chromosomes. Pseudo-chromosomal comparisons showed a considerable number of translocation events have occurred following a whole genome duplication (WGD) event some consistent with centromeric Robertsonian-like translocations. RNA sequencing data from 12 tissues and ab initio analysis informed a genome-wide manual annotation, using the WebApollo tool. In total, 33,044 gene loci represented by 33,123 isoforms were identified, named and tagged for quality of evidential support. Of these 3114 (9.4%) were identical to a protein within 'Hongyang' The Kiwifruit Information Resource (KIR v2). Some proportion of the differences will be varietal polymorphisms. However, as most computationally predicted Red5 models required manual re-annotation this proportion is expected to be small. The quality of the new gene models was tested by fully sequencing 550 cloned 'Hort16A' cDNAs and comparing with the predicted protein models for Red5 and both the original 'Hongyang' assembly and the revised annotation from KIR v2. Only 48.9% and 63.5% of the cDNAs had a match with 90% identity or better to the original and revised 'Hongyang' annotation, respectively, compared with 90.9% to the Red5 models. Conclusions: Our study highlights the need to take a cautious approach to draft genomes and computationally predicted genes. Our use of the manual annotation tool WebApollo facilitated manual checking and correction of gene models enabling improvement of computational prediction. This utility was especially relevant for certain types of gene families such as the EXPANSIN like genes. Finally, this high quality gene set will supply the kiwifruit and general plant community with a new tool for genomics and other comparative analysis.

Next-generation-sequencing (NGS) technologies now enable researchers to readily survey genetic variation in any crop or context. Although global genotyping is becoming routine, the targeted validation of selected variants for marker-aided selection (MAS) or other diagnostic applications remains challenging. In this paper, we survey our experiences and strategies for automating PCR marker design in non-model crop genomes. Recent enhancements in reproducible document authoring, software and environment management and genomic data programming have made the Python ecosystem well suited to the development of scalable toolkits for marker design.

During evolution, plant genomes have undergone duplications, deletions and rearrangements resulting in a wide variation in genome size and number of gene family members between different species. The variation in gene families is an important mechanism for adaptation to different environmental conditions. Allium species, such as bulb onion (Allium cepa), have a large unsequenced genome. However, high throughput transcriptome sequencing datasets are now available which provide an efficient way to identify the genes present in different Allium species. With this knowledge, strategies to accelerate physiological and genetic analysis for enhanced breeding can be developed. In this chapter, we will describe how RNA sequencing is providing a better understanding of Allium genetics and survey the diversity of gene families involved in bulbing, flowering, male fertility, flavonoid biosynthesis and sulphur assimilation in bulb onion. In general, we found that onion has a similar number of gene family members to other monocots, such as rice, which have much smaller genomes. This is consistent with the large genome size of Allium being due to a massive expansion of repetitive DNA.