A Non-Shedding Fruit Elaeis oleifera Palm Reveals Perturbations to Hormone Signaling, ROS Homeostasis, and Hemicellulose Metabolism.

The developmentally programmed loss of a plant organ is called abscission. This process is characterized by the ultimate separation of adjacent cells in the abscission zone (AZ). The discovery of an American oil palm (Elaeis oleifera) variant that does not shed its has allowed for the study of the mechanisms of ripe fruit abscission in this species. A comparative transcriptome analysis was performed to compare the fruit AZs of the non-shedding E. oleifera variant to an individual of the same progeny that sheds its ripe fruit normally. The study provides evidence for widespread perturbation to gene expression in the AZ of the non-shedding variant, compared to the normal fruit-shedding control, and offers insight into abscission-related functions. Beyond the genes with known or suspected roles during organ abscission or indehiscence that were identified, a list of genes with hormone-related functions, including ethylene, jasmonic acid, abscisic acid, cytokinin and salicylic acid, in addition to reactive oxygen species (ROS) metabolism, transcriptional responses and signaling pathways, was compiled. The results also allowed a comparison between the ripe fruit abscission processes of the African and American oil palm species at the molecular level and revealed commonalities with environmental stress pathways.

In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense.

Basal stem rot caused by Ganoderma boninense is the major threat to oil palm cultivation in Southeast Asia, which accounts for 80% of palm oil production worldwide, and this disease is increasing in Africa. The use of resistant planting material as part of an integrated pest management of this disease is one sustainable solution. However, breeding for Ganoderma resistance requires long-term and costly research, which could greatly benefit from marker-assisted selection (MAS). In this study, we evaluated the effectiveness of an in silico genetic mapping approach that took advantage of extensive data recorded in an ongoing breeding program. A pedigree-based QTL mapping approach applied to more than 10 years' worth of data collected during pre-nursery tests revealed the quantitative nature of Ganoderma resistance and identified underlying loci segregating in genetic diversity that is directly relevant for the breeding program supporting the study. To assess the consistency of QTL effects between pre-nursery and field environments, information was collected on the disease status of the genitors planted in genealogical gardens and modeled with pre-nursery-based QTL genotypes. In the field, individuals were less likely to be infected with Ganoderma when they carried more favorable alleles at the pre-nursery QTL. Our results pave the way for a MAS of Ganoderma resistant and high yielding planting material, and the provided proof-of-concept of this efficient and cost-effective approach could motivate similar studies based on diverse breeding programs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01246-9.

Mild drought in the vegetative stage induces phenotypic, gene expression, and DNA methylation plasticity in Arabidopsis but no transgenerational effects.

There is renewed interest in whether environmentally induced changes in phenotypes can be heritable. In plants, heritable trait variation can occur without DNA sequence mutations through epigenetic mechanisms involving DNA methylation. However, it remains unknown whether this alternative system of inheritance responds to environmental changes and if it can provide a rapid way for plants to generate adaptive heritable phenotypic variation. To assess potential transgenerational effects induced by the environment, we subjected four natural accessions of Arabidopsis thaliana together with the reference accession Col-0 to mild drought in a multi-generational experiment. As expected, plastic responses to drought were observed in each accession, as well as a number of intergenerational effects of the parental environments. However, after an intervening generation without stress, except for a very few trait-based parental effects, descendants of stressed and non-stressed plants were phenotypically indistinguishable irrespective of whether they were grown in control conditions or under water deficit. In addition, genome-wide analysis of DNA methylation and gene expression in Col-0 demonstrated that, while mild drought induced changes in the DNA methylome of exposed plants, these variants were not inherited. We conclude that mild drought stress does not induce transgenerational epigenetic effects.

Environmental and trophic determinism of fruit abscission and outlook with climate change in tropical regions.

Fruit abscission facilitates the optimal conditions and timing of seed dispersal. Environmental regulation of tropical fruit abscission has received little attention, even though climate change may have its strongest impacts in tropical regions. In this study, oil palm fruit abscission was monitored during multiple years in the Benin Republic to take advantage of the climatic seasonality and the continuous fruit production by this species. An innovative multivariable statistical method was used to identify the best predictors of fruit abscission among a set of climate and ecophysiological variables, and the stage of inflorescence and fruit bunch development when the variables are perceived. The effects of climate scenarios on fruit abscission were then predicted based on the calibrated model. We found complex regulation takes place at specific stages of inflorescence and bunch development, even long before the fruit abscission zone is competent to execute abscission. Among the predictors selected, temperature variations during inflorescence and fruit bunch development are major determinants of the fruit abscission process. Furthermore, the timing of ripe fruit drop is determined by temperature in combination with the trophic status. Finally, climate simulations revealed that the abscission process is robust and is more affected by seasonal variations than by extreme scenarios. Our investigations highlighted the central function of the abscission zone as the sensor of environmental signals during reproductive development. Coupling ecophysiological and statistical modeling was an efficient approach to disentangle this complex environmental regulation.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana.

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

Evaluation of spatio-temporal Bayesian models for the spread of infectious diseases in oil palm.

In the field of epidemiology, studies are often focused on mapping diseases in relation to time and space. Hierarchical modeling is a common flexible and effective tool for modeling problems related to disease spread. In the context of oil palm plantations infected by the fungal pathogen Ganoderma boninense, we propose and compare two spatio-temporal hierarchical Bayesian models addressing the lack of information on propagation modes and transmission vectors. We investigate two alternative process models to study the unobserved mechanism driving the infection process. The models help gain insight into the spatio-temporal dynamic of the infection by identifying a genetic component in the disease spread and by highlighting a spatial component acting at the end of the experiment. In this challenging context, we propose models that provide assumptions on the unobserved mechanism driving the infection process while making short-term predictions using ready-to-use software.

Genomic preselection with genotyping-by-sequencing increases performance of commercial oil palm hybrid crosses.

BACKGROUND: There is great potential for the genetic improvement of oil palm yield. Traditional progeny tests allow accurate selection but limit the number of individuals evaluated. Genomic selection (GS) could overcome this constraint. We estimated the accuracy of GS prediction of seven oil yield components using A × B hybrid progeny tests with almost 500 crosses for training and 200 crosses for independent validation. Genotyping-by-sequencing (GBS) yielded +5000 single nucleotide polymorphisms (SNPs) on the parents of the crosses. The genomic best linear unbiased prediction method gave genomic predictions using the SNPs of the training and validation sets and the phenotypes of the training crosses. The practical impact was illustrated by quantifying the additional bunch production of the crosses selected in the validation experiment if genomic preselection had been applied in the parental populations before progeny tests. RESULTS: We found that prediction accuracies for cross values plateaued at 500 to 2000 SNPs, with high (0.73) or low (0.28) values depending on traits. Similar results were obtained when parental breeding values were predicted. GS was able to capture genetic differences within parental families, requiring at least 2000 SNPs with less than 5% missing data, imputed using pedigrees. Genomic preselection could have increased the selected hybrids bunch production by more than 10%. CONCLUSIONS: Finally, preselection for yield components using GBS is the first possible application of GS in oil palm. This will increase selection intensity, thus improving the performance of commercial hybrids. Further research is required to increase the benefits from GS, which should revolutionize oil palm breeding.

Identification of Ganoderma Disease Resistance Loci Using Natural Field Infection of an Oil Palm Multiparental Population.

Multi-parental populations are promising tools for identifying quantitative disease resistance loci. Stem rot caused by Ganoderma boninense is a major threat to palm oil production, with yield losses of up to 80% prompting premature replantation of palms. There is evidence of genetic resistance sources, but the genetic architecture of Ganoderma resistance has not yet been investigated. This study aimed to identify Ganoderma resistance loci using an oil palm multi-parental population derived from nine major founders of ongoing breeding programs. A total of 1200 palm trees of the multi-parental population was planted in plots naturally infected by Ganoderma, and their health status was assessed biannually over 25 yr. The data were treated as survival data, and modeled using the Cox regression model, including a spatial effect to take the spatial component in the spread of Ganoderma into account. Based on the genotypes of 757 palm trees out of the 1200 planted, and on pedigree information, resistance loci were identified using a random effect with identity-by-descent kinship matrices as covariance matrices in the Cox model. Four Ganoderma resistance loci were identified, two controlling the occurrence of the first Ganoderma symptoms, and two the death of palm trees, while favorable haplotypes were identified among a major gene pool for ongoing breeding programs. This study implemented an efficient and flexible QTL mapping approach, and generated unique valuable information for the selection of oil palm varieties resistant to Ganoderma disease.

Identification of Nitrogen Consumption Genetic Variants in Yeast Through QTL Mapping and Bulk Segregant RNA-Seq Analyses.

Saccharomyces cerevisiae is responsible for wine must fermentation. In this process, nitrogen represents a limiting nutrient and its scarcity results in important economic losses for the wine industry. Yeast isolates use different strategies to grow in poor nitrogen environments and their genomic plasticity enables adaptation to multiple habitats through improvements in nitrogen consumption. Here, we used a highly recombinant S. cerevisiae multi-parent population (SGRP-4X) derived from the intercross of four parental strains of different origins to identify new genetic variants responsible for nitrogen consumption differences during wine fermentation. Analysis of 165 fully sequenced F12 segregants allowed us to map 26 QTL in narrow intervals for 14 amino acid sources and ammonium, the majority of which represent genomic regions previously unmapped for these traits. To complement this strategy, we performed Bulk segregant RNA-seq (BSR-seq) analysis in segregants exhibiting extremely high and low ammonium consumption levels. This identified several QTL overlapping differentially expressed genes and refined the gene candidate search. Based on these approaches, we were able to validate ARO1, PDC1, CPS1, ASI2, LYP1, and ALP1 allelic variants underlying nitrogen consumption differences between strains, providing evidence of many genes with small phenotypic effects. Altogether, these variants significantly shape yeast nitrogen consumption with important implications for evolution, ecological, and quantitative genomics.

Mixed model approach for IBD-based QTL mapping in a complex oil palm pedigree.

BACKGROUND: Elaeis guineensis is the world's leading source of vegetable oil, and the demand is still increasing. Oil palm breeding would benefit from marker-assisted selection but genetic studies are scarce and inconclusive. This study aims to identify genetic bases of oil palm production using a pedigree-based approach that is innovative in plant genetics. RESULTS: A quantitative trait locus (QTL) mapping approach involving two-step variance component analysis was employed using phenotypic data on 30852 palms from crosses between more than 300 genotyped parents of two heterotic groups. Genome scans were performed at parental level by modeling QTL effects as random terms in linear mixed models with identity-by-descent (IBD) kinship matrices. Eighteen QTL regions controlling production traits were identified among a large genetically diversified sample from breeding program. QTL patterns depended on the genetic origin, with only one region shared between heterotic groups. Contrasting effects of QTLs on bunch number and weights reflected the close negative correlation between the two traits. CONCLUSIONS: The pedigree-based approach using data from ongoing breeding programs is a powerful, relevant and economic approach to map QTLs. Genetic determinisms contributing to heterotic effects have been identified and provide valuable information for orienting oil palm breeding strategies.

Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis.

cis- and trans-acting factors affect gene expression and responses to environmental conditions. However, for most plant systems, we lack a comprehensive map of these factors and their interaction with environmental variation. Here, we examined allele-specific expression (ASE) in an F1 hybrid to study how alleles from two Arabidopsis thaliana accessions affect gene expression. To investigate the effect of the environment, we used drought stress and developed a variance component model to estimate the combined genetic contributions of cis- and trans-regulatory polymorphisms, environmental factors, and their interactions. We quantified ASE for 11,003 genes, identifying 3318 genes with consistent ASE in control and stress conditions, demonstrating that cis-acting genetic effects are essentially robust to changes in the environment. Moreover, we found 1618 genes with genotype x environment (GxE) interactions, mostly cis x E interactions with magnitude changes in ASE. We found fewer trans x E interactions, but these effects were relatively less robust across conditions, showing more changes in the direction of the effect between environments; this confirms that trans-regulation plays an important role in the response to environmental conditions. Our data provide a detailed map of cis- and trans-regulation and GxE interactions in A. thaliana, laying the ground for mechanistic investigations and studies in other plants and environments.

Phenotyping the kinematics of leaf development in flowering plants: recommendations and pitfalls.

Leaves of flowering plants are produced from the shoot apical meristem at regular intervals and they grow according to a developmental program that is determined by both genetic and environmental factors. Detailed frameworks for multiscale dynamic analyses of leaf growth have been developed in order to identify and interpret phenotypic differences caused by either genetic or environmental variations. They revealed that leaf growth dynamics are non-linearly and nonhomogeneously distributed over the lamina, in the leaf tissues and cells. The analysis of the variability in leaf growth, and its underlying processes, has recently gained momentum with the development of automated phenotyping platforms that use various technologies to record growth at different scales and at high throughput. These modern tools are likely to accelerate the characterization of gene function and the processes that underlie the control of shoot development. Combined with powerful statistical analyses, trends have emerged that may have been overlooked in low throughput analyses. However, in many examples, the increase in throughput allowed by automated platforms has led to a decrease in the spatial and/or temporal resolution of growth analyses. Concrete examples presented here indicate that simplification of the dynamic leaf system, without consideration of its spatial and temporal context, can lead to important misinterpretations of the growth phenotype.

Phenoscope: an automated large-scale phenotyping platform offering high spatial homogeneity.

Increased phenotyping accuracy and throughput are necessary to improve our understanding of quantitative variation and to be able to deconstruct complex traits such as those involved in growth responses to the environment. Still, only a few facilities are known to handle individual plants of small stature for non-destructive, real-time phenotype acquisition from plants grown in precisely adjusted and variable experimental conditions. Here, we describe Phenoscope, a high-throughput phenotyping platform that has the unique feature of continuously rotating 735 individual pots over a table. It automatically adjusts watering and is equipped with a zenithal imaging system to monitor rosette size and expansion rate during the vegetative stage, with automatic image analysis allowing manual correction. When applied to Arabidopsis thaliana, we show that rotating the pots strongly reduced micro-environmental disparity: heterogeneity in evaporation was cut by a factor of 2.5 and the number of replicates needed to detect a specific mild genotypic effect was reduced by a factor of 3. In addition, by controlling a large proportion of the micro-environmental variance, other tangible sources of variance become noticeable. Overall, Phenoscope makes it possible to perform large-scale experiments that would not be possible or reproducible by hand. When applied to a typical quantitative trait loci (QTL) mapping experiment, we show that mapping power is more limited by genetic complexity than phenotyping accuracy. This will help to draw a more general picture as to how genetic diversity shapes phenotypic variation.

DNA fingerprinting and new tools for fine-scale discrimination of Arabidopsis thaliana accessions.

One of the main strengths of Arabidopsis thaliana as a model species is the impressive number of public resources available to the scientific community. Exploring species genetic diversity--and therefore adaptation--relies on collections of individuals from natural populations taken from diverse environments. Nevertheless, due to a few mislabeling events or genotype mixtures, some variants available in stock centers have been misidentified, causing inconsistencies and limiting the potential of genetic analyses. To improve the identification of natural accessions, we genotyped 1311 seed stocks from our Versailles Arabidopsis Stock Center and from other collections to determine their molecular profiles at 341 single nucleotide polymorphism markers. These profiles were used to compare genotypes at both the intra- and inter-accession levels. We confirmed previously described inconsistencies and revealed new ones, and suggest likely identities for accessions whose lineage had been lost. We also developed two new tools: a minimal fingerprint computation to quickly verify the identity of an accession, and an optimized marker set to assist in the identification of unknown or mixed accessions. These tools are available on a dedicated web interface called ANATool (https://www.versailles.inra.fr/ijpb/crb/anatool) that provides a simple and efficient means to verify or determine the identity of A. thaliana accessions in any laboratory, without the need for any specific or expensive technology.

New insights into the control of endoreduplication: endoreduplication could be driven by organ growth in Arabidopsis leaves.

Enormous progress has been achieved understanding the molecular mechanisms regulating endoreduplication. By contrast, how this process is coordinated with the cell cycle or cell expansion and contributes to overall growth in multicellular systems remains unclear. A holistic approach was used here to give insight into the functional links between endoreduplication, cell division, cell expansion, and whole growth in the Arabidopsis (Arabidopsis thaliana) leaf. Correlative analyses, quantitative genetics, and structural equation modeling were applied to a large data set issued from the multiscale phenotyping of 200 genotypes, including both genetically modified lines and recombinant inbred lines. All results support the conclusion that endoreduplication in leaf cells could be controlled by leaf growth itself. More generally, leaf growth could act as a "hub" that drives cell division, cell expansion, and endoreduplication in parallel. In many cases, this strategy allows compensations that stabilize leaf area even when one of the underlying cellular processes is limiting.

PHENOPSIS DB: an information system for Arabidopsis thaliana phenotypic data in an environmental context.

BACKGROUND: Renewed interest in plant×environment interactions has risen in the post-genomic era. In this context, high-throughput phenotyping platforms have been developed to create reproducible environmental scenarios in which the phenotypic responses of multiple genotypes can be analysed in a reproducible way. These platforms benefit hugely from the development of suitable databases for storage, sharing and analysis of the large amount of data collected. In the model plant Arabidopsis thaliana, most databases available to the scientific community contain data related to genetic and molecular biology and are characterised by an inadequacy in the description of plant developmental stages and experimental metadata such as environmental conditions. Our goal was to develop a comprehensive information system for sharing of the data collected in PHENOPSIS, an automated platform for Arabidopsis thaliana phenotyping, with the scientific community. DESCRIPTION: PHENOPSIS DB is a publicly available (URL: http://bioweb.supagro.inra.fr/phenopsis/) information system developed for storage, browsing and sharing of online data generated by the PHENOPSIS platform and offline data collected by experimenters and experimental metadata. It provides modules coupled to a Web interface for (i) the visualisation of environmental data of an experiment, (ii) the visualisation and statistical analysis of phenotypic data, and (iii) the analysis of Arabidopsis thaliana plant images. CONCLUSIONS: Firstly, data stored in the PHENOPSIS DB are of interest to the Arabidopsis thaliana community, particularly in allowing phenotypic meta-analyses directly linked to environmental conditions on which publications are still scarce. Secondly, data or image analysis modules can be downloaded from the Web interface for direct usage or as the basis for modifications according to new requirements. Finally, the structure of PHENOPSIS DB provides a useful template for the development of other similar databases related to genotype×environment interactions.

What does Arabidopsis natural variation teach us (and does not teach us) about adaptation in plants?

Sessile organisms such as plants have to develop adaptive responses to face environmental change. In Arabidopsis thaliana populations, natural variation for stress responses have been observed at different levels of integration and the genetic bases of those variations have been analysed using two strategies: classical linkage and association (LD) mapping. The strength of Arabidopsis resides in the huge amount of genomic data and molecular tools available leading to the identification of many polymorphisms responsible for phenotypic variation. Remaining limitations to clearly understand how Arabidopsis adapts to its environment, that is the complexity of the genetic architecture and the lack of ecological data, should be partially solved thanks to the development of new methods and the acquisition of new data.

The ERECTA gene controls spatial and temporal patterns of epidermal cell number and size in successive developing leaves of Arabidopsis thaliana.

BACKGROUND AND AIMS: ERECTA has been identified as a pleiotropic regulator of developmental and physiological processes in Arabidopsis thaliana. Previous work demonstrated a role for ERECTA in the control of compensation between epidermal cell expansion and division in leaves. METHODS: In this work, spatial and temporal analyses of epidermal cell division and expansion were performed on successive developing vegetative leaves of Arabidopsis thaliana in both ERECTA and erecta lines, LER and Ler, respectively, to understand how the ERECTA gene regulates compensation between these two processes. KEY RESULTS: The loss of ERECTA function leads to a low cell expansion rate in all zones of a leaf and in all successive leaves of a plant. This low cell expansion rate is counterbalanced by an increase in the duration of cell division. As a consequence, the ERECTA mutation eliminates the tip to base cellular gradient generally observed in the leaf epidermis and also flattens the heteroblastic changes in epidermal cell area and number within a rosette. Ablation of floral buds eliminates the heteroblastic changes in cellular patterns in an ERECTA-dependent manner. CONCLUSIONS: The results provide a detailed description of changes in leaf growth dynamics and cellular variables in both LER and Ler. Altogether they suggest that ERECTA influences leaf cellular development in relation to whole plant ontogeny.

Keep on growing under drought: genetic and developmental bases of the response of rosette area using a recombinant inbred line population.

Variation in leaf development caused by water deficit was analysed in 120 recombinant inbred lines derived from two Arabidopsis thaliana accessions, Ler and An-1. Main effect quantitative trait loci (QTLs) and QTLs in epistatic interactions were mapped for the responses of rosette area, leaf number and leaf 6 area to water deficit. An epistatic interaction between two QTLs affected the response of whole rosette area and individual leaf area but only with effects in well-watered condition. A second epistatic interaction between two QTLs controlled the response of rosette area and leaf number with specific effects in the water deficit condition. These effects were validated by generating and phenotyping new appropriate lines. Accordingly, a low reduction of rosette area was observed for lines with a specific allelic combination at the two interacting QTLs. This low reduction was accompanied by an increase in leaf number with a lengthening of the vegetative phase and a low reduction in individual leaf area with low reductions in epidermal cell area and number. Statistical analyses suggested that responses of epidermal cell area and number to water deficit in individual leaves were partly caused by delay in flowering time and reduction in leaf emergence rate, respectively.

Genetic analysis identifies quantitative trait loci controlling rosette mineral concentrations in Arabidopsis thaliana under drought.

Rosettes of 25 Arabidopsis thaliana accessions and an Antwerp-1 (An-1) x Landsberg erecta (Ler) population of recombinant inbred lines (RILs) grown in optimal watering conditions (OWC) and water deficit conditions (WDC) were analysed for mineral concentrations to identify genetic loci involved in adaptation of mineral homeostasis to drought stress. Correlations between mineral concentrations were determined for accessions and a quantitative trait locus (QTL) analysis was performed for the RIL population. Plant growth and rosette mineral contents strongly decreased in WDC compared with OWC. Mineral concentrations also generally decreased, except for phosphorus (P), which remained constant, and potassium (K), which increased. Large variations in mineral concentrations were observed among accessions, mostly correlated with total rosette leaf area. Mineral concentration QTLs were identified in the RIL population, but only a few were common for both conditions. Clusters of mineral concentration QTLs often cosegregated with dry weight QTLs. Water deficit has a strong effect on rosette mineral status. This is genetically determined and seems largely a pleiotropic effect of the reduction in growth. The low number of common mineral concentration QTLs, shared among different RIL populations, tissues and conditions in Arabidopsis, suggests that breeding for robust, mineral biofortified crops will be complex.