Deciphering and prediction of plant dynamics under field conditions

Response and inversion of skewness parameters to meteorological factors based on RGB model of leaf color digital image

In the natural environment, complex and changeable meteorological factors can influence changes in the internal physiology and phenotype of crops. It is important to learn how to convert complex meteorological factor stimuli into plant perception phenotypes when analyzing the biological data obtained under the natural field condition. We restored the true gradation distribution of leaf color, which is also known as the skewed distribution of color scale, and obtained 20 multi-dimensional color gradation skewness-distribution (CGSD) parameters based on the leaf color skewness parameter system. Furthermore, we analyzed the correlation between the five corresponding meteorological factors and canopy CGSD parameters of peppers growing in a greenhouse and cabbages growing in an open air environment, built response model and inversion mode of leaf color to meteorological factors. Based on the analysis, we find a new method for correlating complex environmental problems with multi-dimensional parameters. This study provides a new idea for building a correlation model that uses leaf color as a bridge between meteorological factors and plants internal physiological state.

Gene-by-environment interactions in plants: Molecular mechanisms, environmental drivers, and adaptive plasticity

Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

The translatability of genetic networks from model to crop species: lessons from the past and perspectives for the future

Comparative analyses of growth-regulatory mechanisms between Arabidopsis and maize revealed that even when the gene space is conserved, the translation of knowledge from model species to crops is not trivial. Based on these insights, we formulate future opportunities to improve the interpretation of curiosity-driven research towards crop improvement.

Response of Poplar Leaf Transcriptome to Changed Management and Environmental Conditions in Pure and Mixed with Black Locust Stands

Mixed cropping in short rotation coppice can be an alternative to monocultures. To design optimized mixtures, field trials are needed. Poplar, as an economically important and fast-growing species, and black locust, as a nitrogen-fixing species, are promising candidates for such studies. RNA sequencing (RNA-seq) was used to monitor effects of mixed and pure cultivations on the gene expression of poplar along with growth measurements during 2017 and 2018. Both biomass production and leaf transcriptomes revealed a strong competition pressure of black locust and the abiotic environment on poplar trees. Gene expression differed between the two study sites and pure and mixed stands. Shading effects from black locust caused the downregulation of photosynthesis and upregulation of shade avoidance genes in mixed stands in 2017. As a result of higher light availability after cutting black locust, plant organ development genes were upregulated in mixed stands in 2018. Drought conditions during the summer of 2018 and competition for water between the two species caused the upregulation of drought stress response genes in mixed stands and at the unfavorable growing site. Further investigations are required to discover the mechanisms of interspecific competition and to develop stand designs, which could increase the success and productivity of mixed plantations.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here 'POP6'), whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. Tc derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (gs) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.

Synthesis and Secretion of Isoflavones by Field-Grown Soybean

Isoflavones play important roles in rhizosphere plant-microbe interactions. Daidzein and genistein secreted by soybean roots induce the symbiotic interaction with rhizobia and may modulate rhizosphere interactions with microbes. Yet despite their important roles, little is known about the biosynthesis, secretion and fate of isoflavones in field-grown soybeans. Here, we analyzed isoflavone contents and the expression of isoflavone biosynthesis genes in field-grown soybeans. In roots, isoflavone contents and composition did not change with crop growth, but the expression of UGT4, an isoflavone-specific 7-O-glucosyltransferase, and of ICHG (isoflavone conjugates hydrolyzing beta-glucosidase) was decreased during the reproductive stages. Isoflavone contents were higher in rhizosphere soil than in bulk soil during both vegetative and reproductive stages, and were comparable in the rhizosphere soil between these two stages. We analyzed the degradation dynamics of daidzein and its glucosides to develop a model for predicting rhizosphere isoflavone contents from the amount of isoflavones secreted in hydroponic culture. Conjugates of daidzein were degraded much faster than daidzein, with degradation rate constants of 8.51 d-1 for malonyldaidzin and 11.6 d-1 for daidzin, vs. 9.15 × 10-2 d-1 for daidzein. The model suggested that secretion of isoflavones into the rhizosphere is higher during vegetative stages than during reproductive stages in field-grown soybean.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F₂ partially inbred population (termed here 'POP6'), whose F₁ was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (T_c) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. T_c derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (g_s) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.

Metabolic Consequences of Infection of Grapevine (Vitis vinifera L.) cv. "Modra frankinja" with Flavescence Dorée Phytoplasma

Flavescence dorée, caused by the quarantine phytoplasma FDp, represents the most devastating of the grapevine yellows diseases in Europe. In an integrated study we have explored the FDp-grapevine interaction in infected grapevines of cv. "Modra frankinja" under natural conditions in the vineyard. In FDp-infected leaf vein-enriched tissues, the seasonal transcriptional profiles of 14 genes selected from various metabolic pathways showed an FDp-specific plant response compared to other grapevine yellows and uncovered a new association of the SWEET17a vacuolar transporter of fructose with pathogens. Non-targeted metabolome analysis from leaf vein-enriched tissues identified 22 significantly changed compounds with increased levels during infection. Several metabolites corroborated the gene expression study. Detailed investigation of the dynamics of carbohydrate metabolism revealed significant accumulation of sucrose and starch in the mesophyll of FDp-infected leaves, as well as significant up-regulation of genes involved in their biosynthesis. In addition, infected leaves had high activities of ADP-glucose pyrophosphorylase and, more significantly, sucrose synthase. The data support the conclusion that FDp infection inhibits phloem transport, resulting in accumulation of carbohydrates and secondary metabolites that provoke a source-sink transition and defense response status.

Envirotyping for deciphering environmental impacts on crop plants

Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.

Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

DOI:http://dx.doi.org/10.7554/eLife.08411.001

Plants need to be able to sense and respond to changes in temperature, light levels and other aspects of their environment. One way in which plants can rapidly respond to these changes is to modify how genes involved in growth and other processes are expressed. Therefore, understanding how this happens may help us to improve the ability of crops to grow when exposed to drought or other extreme environmental conditions.

Most previous studies into the effect of the environment on plant gene expression have been carried out under controlled conditions in a laboratory. These findings cannot reflect the full range of gene expression patterns that occur in the natural environment, where multiple factors (e.g. sunlight, water, nutrients) may vary at the same time. Therefore, it is important to also analyze the effect of fluctuations in multiple environmental factors in more complex field experiments.

Plessis et al. developed mathematical models to analyze the gene expression patterns of rice plants grown in the tropical environment of the Philippines using two different farming practices. One field of rice was flooded and constantly supplied with fresh water (referred to as the irrigated field), while the other field was dry and only received water from rainfall (the rainfed field). The experiments show that temperature and levels of sunlight (including UV radiation) have a strong impact on gene expression in the rice plants. Short-term variations in temperature and sunlight levels also have the most consistent effect across the different fields and seasons tested. However, for many genes, the plants grown in the irrigated field responded to the changes in environmental conditions in a different way to the plants grown in the rainfed field.

Further analysis identified groups of genes whose expression combined responses to several environmental factors at the same time. For example, certain genes that responded to increases in sunlight in the absence of drought responded to both sunlight levels and the shortage of water when a drought occurred. The next step is to test more types of environments and climates to be able to predict gene expression responses under future climatic conditions.

DOI:http://dx.doi.org/10.7554/eLife.08411.002