Multispectral airborne imagery in the field reveals genetic determinisms of morphological and transpiration traits of an apple tree hybrid population in response to water deficit

Multispectral Phenotyping and Genetic Analyses of Spring Appearance in Greening Plant, Phedimus spp

The change in appearance during the seasonal transitions in ornamental greening plants is an important characteristic. In particular, the early onset of green leaf color is a desirable trait for a cultivar. In this study, we established a method for phenotyping leaf color change by multispectral imaging and performed genetic analysis based on the phenotypes to clarify the potential of the approach in breeding greening plants. We performed multispectral phenotyping and quantitative trait locus (QTL) analysis of an F₁ population derived from 2 parental lines of Phedimus takesimensis, known to be a drought and heat-tolerant rooftop plant species. The imaging was conducted in April of 2019 and 2020 when dormancy breakage occurs and growth extension begins. Principal component analysis of 9 different wavelength values showed a high contribution from the first principal component (PC1), which captured variation in the visible light range. The high interannual correlation in PC1 and in the intensity of visible light indicated that the multispectral phenotyping captured genetic variation in the color of leaves. We also performed restriction site-associated DNA sequencing and obtained the first genetic linkage map of Phedimus spp. QTL analysis revealed 2 QTLs related to early dormancy breakage. Based on the genotypes of the markers underlying these 2 QTLs, the F₁ phenotypes with early (late) dormancy break, green (red or brown) leaves, and a high (low) degree of vegetative growth were classified. The results suggest the potential of multispectral phenotyping in the genetic dissection of seasonal leaf color changes in greening plants.

Image-Based High-Throughput Phenotyping in Horticultural Crops

Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

Applying molecular and genetic methods to trees and their fungal communities

Forests provide invaluable economic, ecological, and social services. At the same time, they are exposed to several threats, such as fragmentation, changing climatic conditions, or increasingly destructive pests and pathogens. Trees, the inherent species of forests, cannot be viewed as isolated organisms. Manifold (micro)organisms are associated with trees playing a pivotal role in forest ecosystems. Of these organisms, fungi may have the greatest impact on the life of trees. A multitude of molecular and genetic methods are now available to investigate tree species and their associated organisms. Due to their smaller genome sizes compared to tree species, whole genomes of different fungi are routinely compared. Such studies have only recently started in forest tree species. Here, we summarize the application of molecular and genetic methods in forest conservation genetics, tree breeding, and association genetics as well as for the investigation of fungal communities and their interrelated ecological functions. These techniques provide valuable insights into the molecular basis of adaptive traits, the impacts of forest management, and changing environmental conditions on tree species and fungal communities and can enhance tree-breeding cycles due to reduced time for field testing. It becomes clear that there are multifaceted interactions among microbial species as well as between these organisms and trees. We demonstrate the versatility of the different approaches based on case studies on trees and fungi. KEY POINTS: • Current knowledge of genetic methods applied to forest trees and associated fungi. • Genomic methods are essential in conservation, breeding, management, and research. • Important role of phytobiomes for trees and their ecosystems.

Contributions of leaf distribution and leaf functions to photosynthesis and water-use efficiency from leaf to canopy in apple: A comparison of interstocks and cultivars

Grafting has been widely used in horticulture to induce dwarfing and avoid stress-derived limitations on plant growth and yield by affecting plant architecture and leaf functions. However, the respective effects on plant photosynthesis and water use efficiency (WUE) of leaf distribution and functions that depend on both rootstock and scion have not been fully elucidated. This study aimed to (i) clarify the scion × interstock impacts on the variability of leaf photosynthetic traits and WUE, and (ii) decipher the respective effects of leaf distribution and functions on canopy photosynthesis and WUE (WUEc). Leaf gas exchange over light gradients and responses to light, CO₂, temperature, and vapor pressure deficit were measured in two apple cultivars, 'Liquan Fuji' ('Fuji') and 'Regal Gala' ('Gala'), grafted onto rootstocks combined with interstocks: a vigorous (VV, 'Qinguan'), or a dwarf one (VD, M26). The 3D architecture-based RATP model was parameterized to estimate the canopy photosynthesis rate (A_c ), transpiration rate (E _c), and WUEc. Then, virtual scenarios were used to compare the relative contributions of cultivar and interstock to canopy A _c, E _c, and WUE _c. These scenarios changed the leaf distribution and functions of either cultivar or interstock. At the leaf scale, VD trees had significantly higher leaf nitrogen per area but a lower maximum carboxylation rate and dark respiration in both cultivars. In parallel with higher leaf stomatal conductance (g_s ) and transpiration in VD 'Fuji' and similar g_s in VD 'Gala', VD trees showed significantly lower leaf photosynthesis rate and WUE than VV trees. However, lower leaf photosynthetic capacities in VD trees were compensated at the canopy scale, with A _c and WUE _c for 'Fuji' significantly improved in VD trees under both sunny and cloudy conditions, and for 'Gala' significantly improved in VD trees under cloudy conditions compared with VV trees. Switching scenarios highlighted that 'Gala' leaf functions and distribution and VD leaf distributions enhanced A _c and WUE _c simultaneously, irrespective of weather conditions. Up-scaling leaf gas exchange to the canopy scale by utilizing 3D architecture-based modeling and reliable measurements of tree architecture and leaf functional traits provides insights to explore the influence of genetic materials and tree management practices.

Fine-tuning of SUMOylation modulates drought tolerance of apple

SUMOylation is involved in various aspects of plant biology, including drought stress. However, the relationship between SUMOylation and drought stress tolerance is complex; whether SUMOylation has a crosstalk with ubiquitination in response to drought stress remains largely unclear. In this study, we found that both increased and decreased SUMOylation led to increased survival of apple (Malus × domestica) under drought stress: both transgenic MdSUMO2A overexpressing (OE) plants and MdSUMO2 RNAi plants exhibited enhanced drought tolerance. We further confirmed that MdDREB2A is one of the MdSUMO2 targets. Both transgenic MdDREB2A OE and MdDREB2A^K192R OE plants (which lacked the key site of SUMOylation by MdSUMO2A) were more drought tolerant than wild-type plants. However, MdDREB2A^K192R OE plants had a much higher survival rate than MdDREB2A OE plants. We further showed SUMOylated MdDREB2A was conjugated with ubiquitin by MdRNF4 under drought stress, thereby triggering its protein degradation. In addition, MdRNF4 RNAi plants were more tolerant to drought stress. These results revealed the molecular mechanisms that underlie the relationship of SUMOylation with drought tolerance and provided evidence for the tight control of MdDREB2A accumulation under drought stress mediated by SUMOylation and ubiquitination.

Tetraploidy in Citrus wilsonii Enhances Drought Tolerance via Synergistic Regulation of Photosynthesis, Phosphorylation, and Hormonal Changes

Polyploidy varieties have been reported to exhibit higher stress tolerance relative to their diploid relatives, however, the underlying molecular and physiological mechanisms remain poorly understood. In this study, a batch of autotetraploid Citrus wilsonii were identified from a natural seedling population, and these tetraploid seedlings exhibited greater tolerance to drought stress than their diploids siblings. A global transcriptome analysis revealed that a large number of genes involved in photosynthesis response were enriched in tetraploids under drought stress, which was consistent with the changes in photosynthetic indices including Pn, gs, Tr, Ci, and chlorophyll contents. Compared with diploids, phosphorylation was also modified in the tetraploids after drought stress, as detected through tandem mass tag (TMT)-labeled proteomics. Additionally, tetraploids prioritized the regulation of plant hormone signal transduction at the transcriptional level after drought stress, which was also demonstrated by increased levels of IAA, ABA, and SA and reduced levels of GA3 and JA. Collectively, our results confirmed that the synergistic regulation of photosynthesis response, phosphorylation modification and plant hormone signaling resulted in drought tolerance of autotetraploid C. wilsonii germplasm.

Tree architecture, light interception and water-use related traits are controlled by different genomic regions in an apple tree core collection

Tree architecture shows large genotypic variability, but how this affects water-deficit responses is poorly understood. To assess the possibility of reaching ideotypes with adequate combinations of architectural and functional traits in the face of climate change, we combined high-throughput field phenotyping and genome-wide association studies (GWAS) on an apple tree (Malus domestica) core-collection. We used terrestrial light detection and ranging (T-LiDAR) scanning and airborne multispectral and thermal imagery to monitor tree architecture, canopy shape, light interception, vegetation indices and transpiration on 241 apple cultivars submitted to progressive field soil drying. GWAS was performed with single nucleotide polymorphism (SNP)-by-SNP and multi-SNP methods. Large phenotypic and genetic variability was observed for all traits examined within the collection, especially canopy surface temperature in both well-watered and water deficit conditions, suggesting control of water loss was largely genotype-dependent. Robust genomic associations revealed independent genetic control for the architectural and functional traits. Screening associated genomic regions revealed candidate genes involved in relevant pathways for each trait. We show that multiple allelic combinations exist for all studied traits within this collection. This opens promising avenues to jointly optimize tree architecture, light interception and water use in breeding strategies. Genotypes carrying favourable alleles depending on environmental scenarios and production objectives could thus be targeted.

Abscisic acid homeostasis is mediated by feedback regulation of MdMYB88 and MdMYB124

The phytohormone abscisic acid (ABA) is involved in various plant processes. In response to drought stress, plants quickly accumulate ABA, but the regulatory mechanism of ABA accumulation is largely unknown, especially in woody plants. In this study, we report that MdMYB88 and MdMYB124 are myeloblastosis (MYB) transcription factors critical for ABA accumulation in apple trees (Malus x domestica) following drought, and this regulation is negatively controlled by ABA. MdMYB88 and MdMYB124 positively regulate leaf water transpiration, photosynthetic capacity, and stress endurance in apple trees under drought conditions. MdMYB88 and MdMYB124 regulate the expression of biosynthetic and catabolic genes of ABA, as well as drought- and ABA- responsive genes. MdMYB88 associates with promoter regions of the ABA biosynthetic gene 9-cis-epoxycarotenoid dioxygenase 3 (NCED3). Finally, expression of MdMYB88 and MdMYB124 is repressed by ABA. Our results identify a feedback regulation of MdMYB88 and MdMYB124 in modulating ABA homeostasis in apple trees.

Multi-scale high-throughput phenotyping of apple architectural and functional traits in orchard reveals genotypic variability under contrasted watering regimes

Despite previous reports on the genotypic variation of architectural and functional traits in fruit trees, phenotyping large populations in the field remains challenging. In this study, we used high-throughput phenotyping methods on an apple tree core-collection (1000 individuals) grown under contrasted watering regimes. First, architectural phenotyping was achieved using T-LiDAR scans for estimating convex and alpha hull volumes and the silhouette to total leaf area ratio (STAR). Second, a semi-empirical index (I PL) was computed from chlorophyll fluorescence measurements, as a proxy for leaf photosynthesis. Last, thermal infrared and multispectral airborne imaging was used for computing canopy temperature variations, water deficit, and vegetation indices. All traits estimated by these methods were compared to low-throughput in planta measurements. Vegetation indices and alpha hull volumes were significantly correlated with tree leaf area and trunk cross sectional area, while I PL values showed strong correlations with photosynthesis measurements collected on an independent leaf dataset. By contrast, correlations between stomatal conductance and canopy temperature estimated from airborne images were lower, emphasizing discrepancies across measurement scales. High heritability values were obtained for almost all the traits except leaf photosynthesis, likely due to large intra-tree variation. Genotypic means were used in a clustering procedure that defined six classes of architectural and functional combinations. Differences between groups showed several combinations between architectural and functional traits, suggesting independent genetic controls. This study demonstrates the feasibility and relevance of combining multi-scale high-throughput methods and paves the way to explore the genetic bases of architectural and functional variations in woody crops in field conditions.

Apple whole genome sequences: recent advances and new prospects

In 2010, a major scientific milestone was achieved for tree fruit crops: publication of the first draft whole genome sequence (WGS) for apple (Malus domestica). This WGS, v1.0, was valuable as the initial reference for sequence information, fine mapping, gene discovery, variant discovery, and tool development. A new, high quality apple WGS, GDDH13 v1.1, was released in 2017 and now serves as the reference genome for apple. Over the past decade, these apple WGSs have had an enormous impact on our understanding of apple biological functioning, trait physiology and inheritance, leading to practical applications for improving this highly valued crop. Causal gene identities for phenotypes of fundamental and practical interest can today be discovered much more rapidly. Genome-wide polymorphisms at high genetic resolution are screened efficiently over hundreds to thousands of individuals with new insights into genetic relationships and pedigrees. High-density genetic maps are constructed efficiently and quantitative trait loci for valuable traits are readily associated with positional candidate genes and/or converted into diagnostic tests for breeders. We understand the species, geographical, and genomic origins of domesticated apple more precisely, as well as its relationship to wild relatives. The WGS has turbo-charged application of these classical research steps to crop improvement and drives innovative methods to achieve more durable, environmentally sound, productive, and consumer-desirable apple production. This review includes examples of basic and practical breakthroughs and challenges in using the apple WGSs. Recommendations for "what's next" focus on necessary upgrades to the genome sequence data pool, as well as for use of the data, to reach new frontiers in genomics-based scientific understanding of apple.

Mapping QTLs for water-use efficiency reveals the potential candidate genes involved in regulating the trait in apple under drought stress

BACKGROUND

Improvement of water-use efficiency (WUE) can effectively reduce production losses caused by drought stress. A better understanding of the genetic determination of WUE in crops under drought stress has great potential value for developing cultivars adapted to arid regions. To identify the genetic loci associated with WUE and reveal genes responsible for the trait in apple, we aim to map the quantitative trait loci (QTLs) for carbon isotope composition, the proxy for WUE, applying two contrasting irrigating regimes over the two-year experiment and search for the candidate genes encompassed in the mapped QTLs.

RESULTS

We constructed a high-density genetic linkage map with 10,172 markers of apple, using single nucleotide polymorphism (SNP) markers obtained through restriction site-associated DNA sequencing (RADseq) and a final segregating population of 350 seedlings from the cross of Honeycrisp and Qinguan. In total, 33 QTLs were identified for carbon isotope composition in apple under both well-watered and drought-stressed conditions. Three QTLs were stable over 2 years under drought stress on linkage groups LG8, LG15 and LG16, as validated by Kompetitive Allele-Specific PCR (KASP) assays. In those validated QTLs, 258 genes were screened according to their Gene Ontology functional annotations. Among them, 28 genes were identified, which exhibited significant responses to drought stress in 'Honeycrisp' and/or 'Qinguan'. These genes are involved in signaling, photosynthesis, response to stresses, carbohydrate metabolism, protein metabolism and modification, hormone metabolism and transport, transport, respiration, transcriptional regulation, and development regulation. They, especially those for photoprotection and relevant signal transduction, are potential candidate genes connected with WUE regulation in drought-stressed apple.

CONCLUSIONS

We detected three stable QTLs for carbon isotope composition in apple under drought stress over 2 years, and validated them by KASP assay. Twenty-eight candidate genes encompassed in these QTLs were identified. These stable genetic loci and series of genes provided here serve as a foundation for further studies on marker-assisted selection of high WUE and regulatory mechanism of WUE in apple exposed to drought conditions, respectively.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γ _g ) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γ _g and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.