Identification of co-located QTLs and genomic regions affecting grapevine cluster architecture

Grapevine gray mold disease: infection, defense and management

Grapevine (Vitis vinifera L.,) is among the world's leading fruit crops. The production of grapes is severely affected by many diseases including gray mold, caused by the necrotrophic fungus Botrytis cinerea. Although all Vitis species can be hosts for B. cinerea, V. vinifera are particularly susceptible. Accordingly, this disease poses a significant threat to the grape industry and causes substantial economic losses. Development of resistant V. vinifera cultivars has progressed from incidental selection by farmers, to targeted selection through the use of statistics and experimental design, to the employment of genetic and genomic data. Emerging technologies such as marker-assisted selection and genetic engineering have facilitated the development of cultivars that possess resistance to B. cinerea. A promising method involves using the CRISPR/Cas9 system to induce targeted mutagenesis and develop genetically modified non-transgenic crops. Hence, scientists are now engaged in the active pursuit of identifying genes associated with susceptibility and resistance. This review focuses on the known mechanisms of interaction between the B. cinerea pathogen and its grapevine host. It also explores innate immune systems that have evolved in V. vinifera, with the objective of facilitating the rapid development of resistant grapevine cultivars.

Segment Anything for Comprehensive Analysis of Grapevine Cluster Architecture and Berry Properties

Grape cluster architecture and compactness are complex traits influencing disease susceptibility, fruit quality, and yield. Evaluation methods for these traits include visual scoring, manual methodologies, and computer vision, with the latter being the most scalable approach. Most of the existing computer vision approaches for processing cluster images often rely on conventional segmentation or machine learning with extensive training and limited generalization. The Segment Anything Model (SAM), a novel foundation model trained on a massive image dataset, enables automated object segmentation without additional training. This study demonstrates out-of-the-box SAM's high accuracy in identifying individual berries in 2-dimensional (2D) cluster images. Using this model, we managed to segment approximately 3,500 cluster images, generating over 150,000 berry masks, each linked with spatial coordinates within their clusters. The correlation between human-identified berries and SAM predictions was very strong (Pearson's r2 = 0.96). Although the visible berry count in images typically underestimates the actual cluster berry count due to visibility issues, we demonstrated that this discrepancy could be adjusted using a linear regression model (adjusted R 2 = 0.87). We emphasized the critical importance of the angle at which the cluster is imaged, noting its substantial effect on berry counts and architecture. We proposed different approaches in which berry location information facilitated the calculation of complex features related to cluster architecture and compactness. Finally, we discussed SAM's potential integration into currently available pipelines for image generation and processing in vineyard conditions.

Dissecting the complex genetic basis of pre- and post-harvest traits in Vitis vinifera L. using genome-wide association studies

Addressing the pressing challenges in agriculture necessitates swift advancements in breeding programs, particularly for perennial crops like grapevines. Moving beyond the traditional biparental quantitative trait loci (QTL) mapping, we conducted a genome-wide association study (GWAS) encompassing 588 Vitis vinifera L. cultivars from a Chilean breeding program, spanning three seasons and testing 13 key yield-related traits. A strong candidate gene, Vitvi11g000454, located on chromosome 11 and related to plant response to biotic and abiotic stresses through jasmonic acid signaling, was associated with berry width and holds potential for enhancing berry size in grape breeding. We also mapped novel QTL associated with post-harvest traits across chromosomes 2, 4, 9, 11, 15, 18, and 19, broadening our grasp on the genetic intricacies dictating fruit post-harvest behavior, including decay, shriveling, and weight loss. Leveraging gene ontology annotations, we drew parallels between traits and scrutinized candidate genes, laying a robust groundwork for future trait-feature identification endeavors in plant breeding. We also highlighted the importance of carefully considering the choice of the response variable in GWAS analyses, as the use of best linear unbiased estimators (BLUEs) corrections in our study may have led to the suppression of some common QTL in grapevine traits. Our results underscore the imperative of pioneering non-destructive evaluation techniques for long-term conservation traits, offering grape breeders and cultivators insights to improve post-harvest table grape quality and minimize waste.

Evaluation of Malus Germplasm Identifies Genetic Sources of Powdery Mildew and Frogeye Leaf Spot Resistance for Apple Breeding

Apple is an important fruit crop of temperate regions. The narrow genetic base of commercially cultivated apples has resulted in its vulnerability to a large number of fungal, bacterial, and viral pathogens. Apple breeders are always seeking new sources of resistance within the cross-compatible Malus species that can be deployed into elite genetic backgrounds. We have evaluated resistance to two major fungal diseases of apples: powdery mildew and frogeye leaf spot, using a germplasm collection of 174 Malus accessions to identify novel sources of genetic resistance. In 2020 and 2021, we evaluated these accessions for the incidence and severity of powdery mildew and frogeye leaf spot diseases at Cornell AgriTech, Geneva, New York, in a partially managed orchard. The severity and incidence of powdery mildew and frogeye leaf spot, as well as weather parameters were recorded in June, July, and August. Total incidence of powdery mildew and frogeye leaf spot infections increased from 33 to 38%, and 56 to 97% in 2020 and 2021, respectively. Our analysis showed that relative humidity and precipitation correlate with powdery mildew and frogeye leaf spot susceptibility. The predictor variables with highest impact to the variability of powdery mildew were accessions and relative humidity in May. A total of 65 Malus accessions were found to be resistant to powdery mildew, and only one accession showed moderate resistance to frogeye leaf spot. Several of these accessions belong to Malus hybrid species and domesticated apples and can therefore be potential sources of novel resistance alleles for apple breeding.

Review: Status and prospects of association mapping in grapevine

Thanks to current advances in sequencing technologies, novel bioinformatics tools, and efficient modeling solutions, association mapping has become a widely accepted approach to unravel the link between genotype and phenotype diversity in numerous crops. In grapevine, this strategy has been used in the last decades to understand the genetic basis of traits of agronomic interest (fruit quality, crop yield, biotic and abiotic resistance), of special relevance nowadays to improve crop resilience to cope with future climate scenarios. Genome-wide association studies have identified many putative causative loci for different traits, some of them overlapping well-known causal genes identified by conventional quantitative trait loci studies in biparental progenies, and/or validated by functional approaches. In addition, candidate-gene association studies have been useful to pinpoint the causal mutation underlying phenotypic variation for several traits of high interest in breeding programs (like berry color, seedlessness, and muscat flavor), information that has been used to develop highly informative and useful markers already in use in marker-assisted selection processes. Thus, association mapping has proved to represent a valuable step towards high quality and sustainable grape production. This review summarizes current applications of association mapping in grapevine research and discusses future prospects in view of current viticulture challenges.

Genetic variation and association analyses identify genes linked to fruit set-related traits in grapevine

Grapevine is one of the most valuable fruit crops in the world. Adverse environmental conditions reduce fruit quality and crop yield, so understanding the genetic and molecular mechanisms determining crop yield components is essential to optimize grape production. The analysis of a diverse collection of grapevine cultivars allowed us to evaluate the relationship between fruit set-related components of yield, including the incidence of reproductive disorders such as coulure and millerandage. The collection displayed a great phenotypic variation that we surveyed in a genetics association study using 15,309 single nucleotide polymorphisms (SNPs) detected in the sequence of 289 candidate genes scattered across the 19 grapevine linkage groups. After correcting statistical models for population structure and linkage disequilibrium effects, 164 SNPs from 34 of these genes were found to associate with fruit set-related traits, supporting a complex polygenic determinism. Many of them were found in the sequence of different putative MADS-box transcription factors, a gene family related with plant reproductive development control. In addition, we observed an additive effect of some of the associated SNPs on the phenotype, suggesting that advantageous alleles from different loci could be pyramided to generate superior cultivars with optimized fruit production.

Somatic variants for seed and fruit set in grapevine

BACKGROUND

Grapevine reproductive development has direct implications on yield. It also impacts on berry and wine quality by affecting traits like seedlessness, berry and bunch size, cluster compactness and berry skin to pulp ratio. Seasonal fluctuations in yield, fruit composition and wine attributes, which are largely driven by climatic factors, are major challenges for worldwide table grape and wine industry. Accordingly, a better understanding of reproductive processes such as gamete development, fertilization, seed and fruit set is of paramount relevance for managing yield and quality. With the aim of providing new insights into this field, we searched for clones with contrasting seed content in two germplasm collections.

RESULTS

We identified eight variant pairs that seemingly differ only in seed-related characteristics while showing identical genotype when tested with the GrapeReSeq_Illumina_20K_SNP_chip and several microsatellites. We performed multi-year observations on seed and fruit set deriving from different pollination treatments, with special emphasis on the pair composed by Sangiovese and its seedless variant locally named Corinto Nero. The pollen of Corinto Nero failed to germinate in vitro and gave poor berry set when used to pollinate other varieties. Most berries from both open- and cross-pollinated Corinto Nero inflorescences did not contain seeds. The genetic analysis of seedlings derived from occasional Corinto Nero normal seeds revealed that the few Corinto Nero functional gametes are mostly unreduced. Moreover, three genotypes, including Sangiovese and Corinto Nero, were unexpectedly found to develop fruits without pollen contribution and occasionally showed normal-like seeds. Five missense single nucleotide polymorphisms were identified between Corinto Nero and Sangiovese from transcriptomic data.

CONCLUSIONS

Our observations allowed us to attribute a seedlessness type to some variants for which it was not documented in the literature. Interestingly, the VvAGL11 mutation responsible for Sultanina stenospermocarpy was also discovered in a seedless mutant of Gouais Blanc. We suggest that Corinto Nero parthenocarpy is driven by pollen and/or embryo sac defects, and both events likely arise from meiotic anomalies. The single nucleotide polymorphisms identified between Sangiovese and Corinto Nero are suitable for testing as traceability markers for propagated material and as functional candidates for the seedless phenotype.

Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot

Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms and resistance loci against the necrotrophic pathogen are known. Since long, breeders are mostly selecting phenotypically for loose grape bunches, which is recently the most evident trait to decrease the infection risk of Botrytis bunch rot. This study focused on plant phenomics of multiple traits by applying fast sensor technologies to measure berry impedance (Z _REL ), berry texture, and 3D bunch architecture. As references, microscopic determined cuticle thickness (MS _CT ) and infestation of grapes with Botrytis bunch rot were used. Z _REL hereby is correlated to grape bunch density OIV204 (r = -0.6), cuticle thickness of berries (r = 0.61), mean berry diameter (r = -0.63), and Botrytis bunch rot (r = -0.7). However, no correlation between Z _REL and berry maturity or berry texture was observed. In comparison to the category of traditional varieties (mostly susceptible), elite breeding lines show an impressive increased Z _REL value (+317) and a 1-μm thicker berry cuticle. Quantitative trait loci (QTLs) on LGs 2, 6, 11, 15, and 16 were identified for Z _REL and berry texture explaining a phenotypic variance of between 3 and 10.9%. These QTLs providing a starting point for the development of molecular markers. Modeling of Z _REL and berry texture to predict Botrytis bunch rot resilience revealed McFadden R ² = 0.99. Taken together, this study shows that in addition to loose grape bunch architecture, berry diameter, Z _REL , and berry texture values are probably additional parameters that could be used to identify and select Botrytis-resilient wine grape varieties. Furthermore, grapevine breeding will benefit from these reliable methodologies permitting high-throughput screening for additional resilience traits of mechanical and physical barriers to Botrytis bunch rot. The findings might also be applicable to table grapes and other fruit crops like tomato or blueberry.

Differential expression of transcription factor- and further growth-related genes correlates with contrasting cluster architecture in Vitis vinifera 'Pinot Noir' and Vitis spp. genotypes

Grapevine (Vitis vinifera L.) is an economically important crop that needs to comply with high quality standards for fruit, juice and wine production. Intense plant protection is required to avoid fungal damage. Grapevine cultivars with loose cluster architecture enable reducing protective treatments due to their enhanced resilience against fungal infections, such as Botrytis cinerea-induced gray mold. A recent study identified transcription factor gene VvGRF4 as determinant of pedicel length, an important component of cluster architecture, in samples of two loose and two compact quasi-isogenic 'Pinot Noir' clones. Here, we extended the analysis to 12 differently clustered 'Pinot Noir' clones from five diverse clonal selection programs. Differential gene expression of these clones was studied in three different locations over three seasons. Two phenotypically opposite clones were grown at all three locations and served for standardization. Data were correlated with the phenotypic variation of cluster architecture sub-traits. A set of 14 genes with consistent expression differences between loosely and compactly clustered clones-independent from season and location-was newly identified. These genes have annotations related to cellular growth, cell division and auxin metabolism and include two more transcription factor genes, PRE6 and SEP1-like. The differential expression of VvGRF4 in relation to loose clusters was exclusively found in 'Pinot Noir' clones. Gene expression studies were further broadened to phenotypically contrasting F1 individuals of an interspecific cross and OIV reference varieties of loose cluster architecture. This investigation confirmed PRE6 and six growth-related genes to show differential expression related to cluster architecture over genetically divergent backgrounds.

VviUCC1 Nucleotide Diversity, Linkage Disequilibrium and Association with Rachis Architecture Traits in Grapevine

Cluster compactness is a trait with high agronomic relevance, affecting crop yield and grape composition. Rachis architecture is a major component of cluster compactness determinism, and is a target trait toward the breeding of grapevine varieties less susceptible to pests and diseases. Although its genetic basis is scarcely understood, a preliminary result indicated a possible involvement of the VviUCC1 gene. The aim of this study was to characterize the VviUCC1 gene in grapevine and to test the association between the natural variation observed for a series of rachis architecture traits and the polymorphisms detected in the VviUCC1 sequence. This gene encodes an uclacyanin plant-specific cell-wall protein involved in fiber formation and/or lignification processes. A high nucleotide diversity in the VviUCC1 gene promoter and coding regions was observed, but no critical effects were predicted in the protein domains, indicating a high level of conservation of its function in the cultivated grapevine. After correcting statistical models for genetic stratification and linkage disequilibrium effects, marker-trait association results revealed a series of single nucleotide polymorphisms (SNPs) significantly associated with cluster compactness and rachis traits variation. Two of them (Y-984 and K-88) affected two common cis-transcriptional regulatory elements, suggesting an effect on phenotype via gene expression regulation. This work reinforces the interest of further studies aiming to reveal the functional effect of the detected VviUCC1 variants on grapevine rachis architecture.

Impact of Rootstock, Clonal Selection, and Berry Size of Vitis vinifera sp. Riesling on the Formation of TDN, Vitispiranes, and Other Volatile Compounds

The C₁₃-norisoprenoid aroma compounds 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) and biosynthetically related vitispirane (VS) are important contributors to the varietal aroma of Riesling wines and are released from glycosidically bound carotenoid breakdown products during bottle aging. TDN is appreciated by numerous winemakers, particularly in aged Riesling wines. Higher levels of TDN, however, are perceived as a "petrol" off-flavor, which is expected to increase due to ongoing climate change. Wines produced from the same Riesling clone, which was grafted on six different rootstocks, varied significantly throughout two vintages in respect to their concentrations of free and bound TDN and VS as well as other volatiles. Over three vintages, the same compounds differed significantly among wines made from eight Riesling clones grafted on the same rootstock. Genetically determined loose grape clusters favored the formation of TDN and yielded wines of stronger sensory petrol intensity. Berry size, however, had no relevant impact on TDN and VS formation.

Mutations in the miR396 binding site of the growth-regulating factor gene VvGRF4 modulate inflorescence architecture in grapevine

Bunch rot caused by Botrytis cinerea infections is a notorious problem in grapevine cultivation. To produce high quality fruits, grapevine plants are treated with fungicides, which is cost intensive and harmful to the environment. Conversely, loose cluster bunches show a considerably enhanced physical resilience to bunch diseases. With the aim to identify genetic determinants that modulate the development of bunch architecture, we have compared loose and compact 'Pinot noir' clones. Loose cluster architecture was found to be correlated with increased berry size, elongated rachis and elongated pedicels. Using transcriptome analysis in combination with whole genome sequencing, we have identified a growth-regulating factor gene, VvGRF4, upregulated and harbours heterozygous mutations in the loose cluster clones. At late stages of inflorescence development, the mRNA pools of loose cluster clones contain predominantly mRNAs derived from the mutated alleles, which are resistant to miR396 degradation. Expression of the VvGRF4 gene and its mutated variants in Arabidopsis demonstrates that it promotes pedicel elongation. Taken together, VvGRF4 modulates bunch architecture in grapevine 'Pinot noir' clones. This trait can be introduced into other cultivars using marker-assisted breeding or CRISPR-Cas9 technology. Related growth-regulating factors or other genes of the same pathway may have similar functions.

Combination of an Automated 3D Field Phenotyping Workflow and Predictive Modelling for High-Throughput and Non-Invasive Phenotyping of Grape Bunches

In grapevine breeding, loose grape bunch architecture is one of the most important selection traits, contributing to an increased resilience towards Botrytis bunch rot. Grape bunch architecture is mainly influenced by the berry number, berry size, the total berry volume, and bunch width and length. For an objective, precise, and high-throughput assessment of these architectural traits, the 3D imaging sensor Artec® Spider was applied to gather dense point clouds of the visible side of grape bunches directly in the field. Data acquisition in the field is much faster and non-destructive in comparison to lab applications but results in incomplete point clouds and, thus, mostly incomplete phenotypic values. Therefore, lab scans of whole bunches (360°) were used as ground truth. We observed strong correlations between field and lab data but also shifts in mean and max values, especially for the berry number and total berry volume. For this reason, the present study is focused on the training and validation of different predictive regression models using 3D data from approximately 2000 different grape bunches in order to predict incomplete bunch traits from field data. Modeling concepts included simple linear regression and machine learning-based approaches. The support vector machine was the best and most robust regression model, predicting the phenotypic traits with an R2 of 0.70–0.91. As a breeding orientated proof-of-concept, we additionally performed a Quantitative Trait Loci (QTL)-analysis with both the field modeled and lab data. All types of data resulted in joint QTL regions, indicating that this innovative, fast, and non-destructive phenotyping method is also applicable for molecular marker development and grapevine breeding research.

Characterizing 3D inflorescence architecture in grapevine using X-ray imaging and advanced morphometrics: implications for understanding cluster density

Inflorescence architecture provides the scaffold on which flowers and fruits develop, and consequently is a primary trait under investigation in many crop systems. Yet the challenge remains to analyse these complex 3D branching structures with appropriate tools. High information content datasets are required to represent the actual structure and facilitate full analysis of both the geometric and the topological features relevant to phenotypic variation in order to clarify evolutionary and developmental inflorescence patterns. We combined advanced imaging (X-ray tomography) and computational approaches (topological and geometric data analysis and structural simulations) to comprehensively characterize grapevine inflorescence architecture (the rachis and all branches without berries) among 10 wild Vitis species. Clustering and correlation analyses revealed unexpected relationships, for example pedicel branch angles were largely independent of other traits. We identified multivariate traits that typified species, which allowed us to classify species with 78.3% accuracy, versus 10% by chance. Twelve traits had strong signals across phylogenetic clades, providing insight into the evolution of inflorescence architecture. We provide an advanced framework to quantify 3D inflorescence and other branched plant structures that can be used to tease apart subtle, heritable features for a better understanding of genetic and environmental effects on plant phenotypes.

A novel high-density grapevine (Vitis vinifera L.) integrated linkage map using GBS in a half-diallel population

A half-diallel population involving five elite grapevine cultivars was generated and genotyped by GBS, and highly-informative segregation data was used to construct a high-density genetic map for Vitis vinifera L. Grapevine is one of the most relevant fruit crops in the world. Deeper genetic knowledge could assist modern grapevine breeding programs to develop new wine grape varieties able to face climate change effects. To assist in the rapid identification of markers for crop yield components, grape quality traits and adaptation potential, we generated a large Vitis vinifera L. population (N = 624) by crossing five red wine cultivars in a half-diallel scheme, which was subsequently sequenced by an efficient GBS procedure. A high number of fully informative genetic variants was detected using a novel mapping approach capable of reconstructing local haplotypes from adjacent biallelic SNPs, which were subsequently used to construct the densest consensus genetic map available for the cultivated grapevine to date. This 1378.3-cM map integrates 10 bi-parental consensus maps and orders 4437 markers in 3353 unique positions on 19 chromosomes. Markers are well distributed all along the grapevine reference genome, covering up to 98.8% of its genomic sequence. Additionally, a good agreement was observed between genetic and physical orders, adding confidence in the quality of this map. Collectively, our results pave the way for future genetic studies (such as fine QTL mapping) aimed to understand the complex relationship between genotypic and phenotypic variation in the cultivated grapevine. In addition, the method used (which efficiently delivers a high number of fully informative markers) could be of interest to other outbred organisms, notably perennial fruit crops.