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in Agriculture
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E-mail: naomi.ori@mail.huji.ac.il

 

Publications

2023
Poppenwimer, T. ; Mayrose, I. ; DeMalach, N. . Revising The Global Biogeography Of Annual And Perennial Plants. 2023. Publisher's VersionAbstract
There are two main life cycles in plants—annual and perennial1,2. These life cycles are associated with different traits that determine ecosystem function3,4. Although life cycles are textbook examples of plant adaptation to different environments, we lack comprehensive knowledge regarding their global distributional patterns. Here we assembled an extensive database of plant life cycle assignments of 235,000 plant species coupled with millions of georeferenced datapoints to map the worldwide biogeography of these plant species. We found that annual plants are half as common as initially thought5–8, accounting for only 6% of plant species. Our analyses indicate that annuals are favoured in hot and dry regions. However, a more accurate model shows that the prevalence of annual species is driven by temperature and precipitation in the driest quarter (rather than yearly means), explaining, for example, why some Mediterranean systems have more annuals than desert systems. Furthermore, this pattern remains consistent among different families, indicating convergent evolution. Finally, we demonstrate that increasing climate variability and anthropogenic disturbance increase annual favourability. Considering future climate change, we predict an increase in annual prevalence for 69% of the world’s ecoregions by 2060. Overall, our analyses raise concerns for ecosystem services provided by perennial plants, as ongoing changes are leading to a higher proportion of annual plants globally.
Bacher, H. ; Montagu, A. ; Herrmann, I. ; Walia, H. ; Schwartz, N. ; Peleg, Z. . Stress-Induced Deeper Rooting Introgression Enhances Wheat Yield Under Terminal Drought. Journal of Experimental Botany 2023, 74, 4862-4874. Publisher's VersionAbstract
Water scarcity is the primary environmental constraint affecting wheat growth and production and is increasingly exacerbated due to climatic fluctuation, which jeopardizes future food security. Most breeding efforts to improve wheat yields under drought have focused on above-ground traits. Root traits are closely associated with various drought adaptability mechanisms, but the genetic variation underlying these traits remains untapped, even though it holds tremendous potential for improving crop resilience. Here, we examined this potential by re-introducing ancestral alleles from wild emmer wheat (Triticum turgidum ssp. dicoccoides) and studied their impact on root architecture diversity under terminal drought stress. We applied an active sensing electrical resistivity tomography approach to compare a wild emmer introgression line (IL20) and its drought-sensitive recurrent parent (Svevo) under field conditions. IL20 exhibited greater root elongation under drought, which resulted in higher root water uptake from deeper soil layers. This advantage initiated at the pseudo-stem stage and increased during the transition to the reproductive stage. The increased water uptake promoted higher gas exchange rates and enhanced grain yield under drought. Overall, we show that this presumably ‘lost’ drought-induced mechanism of deeper rooting profile can serve as a breeding target to improve wheat productiveness under changing climate.
Adejimi, O. E. ; Sadhasivam, G. ; Schmilovitch, Z. 'ev; Shapiro, O. H. ; Herrmann, I. . Applying Hyperspectral Transmittance For Inter-Genera Classification Of Cyanobacterial And Algal Cultures. Algal Research 2023, 71, 103067. Publisher's VersionAbstract
In the mass production systems of microalgal species, it is important to ensure the safety and quality of the biomass and product. This requires effective monitoring tools that are sensitive, rapid and simple to use. In this study, hyperspectral transmittance spectroscopy (HTS) was applied for the detection, cell density quantification and classification of algal and cyanobacterial species. A database of HTS data was assembled from samples of seven algal and cyanobacterial species at different cell densities and used for quantifying and classifying the species, using chemometric and machine learning algorithms. The results obtained showed the ability to quantify the species with a detection limit of 104 cells/mL for the support vector machine models applied, and classify the species at concentrations >105 cells/mL. The current study suggests that HTS is applicable for cell density quantification. HTS was used to distinguish between cell cultures of cyanobacteria and algae and was further able to distinguish between cyanobacteria species as well as algal species. In addition, reducing the dimensions (number of spectral bands) of HTS data using feature selection and aggregation improved the classification accuracy. Thus, HTS is recommended as an effective tool for monitoring and management of microalgal bioreactors.
Zemach, I. ; Alseekh, S. ; Tadmor-Levi, R. ; Fisher, J. ; Torgeman, S. ; Trigerman, S. ; Nauen, J. ; Hayut, S. Filler; Mann, V. ; Rochsar, E. ; et al. Multi-Year Field Trials Provide A Massive Repository Of Trait Data On A Highly Diverse Population Of Tomato And Uncover Novel Determinants Of Tomato Productivity. The Plant JournalThe Plant JournalPlant J 2023, n/a. Publisher's VersionAbstract
SUMMARY Tomato (Solanum lycopersicum) is a prominent fruit with rich genetic resources for crop improvement. By using a phenotype-guided screen of over 7900 tomato accessions from around the world, we identified new associations for complex traits such as fruit weight and total soluble solids (Brix). Here, we present the phenotypic data from several years of trials. To illustrate the power of this dataset we use two case studies. First, evaluation of color revealed allelic variation in phytoene synthase 1 that resulted in differently colored or even bicolored fruit. Secondly, in view of the negative relationship between fruit weight and Brix, we pre-selected a subset of the collection that includes high and low Brix values in each category of fruit size. Genome-wide association analysis allowed us to detect novel loci associated with total soluble solid content and fruit weight. In addition, we developed eight F2 biparental intraspecific populations. Furthermore, by taking a phenotype-guided approach we were able to isolate individuals with high Brix values that were not compromised in terms of yield. In addition, the demonstration of novel results despite the high number of previous genome-wide association studies of these traits in tomato suggests that adoption of a phenotype-guided pre-selection of germplasm may represent a useful strategy for finding target genes for breeding.
Torgeman, S. ; Zamir, D. . Epistatic Qtls For Yield Heterosis In Tomato. Proceedings of the National Academy of SciencesProceedings of the National Academy of Sciences 2023, 120, e2205787119. Publisher's VersionAbstract
Controlled population development and genome-wide association studies have proven powerful in uncovering genes and alleles underlying complex traits. An underexplored dimension of such studies is the phenotypic contribution of nonadditive interactions between quantitative trait loci (QTLs). Capturing of such epistasis in a genome-wide manner requires very large populations to represent replicated combinations of loci whose interactions determine phenotypic outcomes. Here, we dissect epistasis using a densely genotyped population of 1,400 backcross inbred lines (BILs) between a modern processing tomato inbred (Solanum lycopersicum) and the Lost Accession (LA5240) of a distant, green-fruited, drought-tolerant wild species, Solanum pennellii. The homozygous BILs, each harboring an average of 11 introgressions and their hybrids with the recurrent parents, were phenotyped for tomato yield components. Population-wide mean yield of the BILs was less than 50% of that of their hybrids (BILHs). All the homozygous introgressions across the genome reduced yield relative to recurrent parent, while several QTLs of the BILHs independently improved productivity. Analysis of two QTL scans showed 61 cases of less-than-additive interactions and 19 cases of more-than-additive interactions. Strikingly, a single epistatic interaction involving S. pennellii QTLs on chromosomes 1 and 7, that independently did not affect yield, increased fruit yield by 20 to 50% in the double introgression hybrid grown in irrigated and dry fields over a period of 4 y. Our work demonstrates the power of large, interspecific controlled population development to uncover hidden QTL phenotypes and how rare epistatic interactions can improve crop productivity via heterosis.Controlled population development and genome-wide association studies have proven powerful in uncovering genes and alleles underlying complex traits. An underexplored dimension of such studies is the phenotypic contribution of nonadditive interactions between quantitative trait loci (QTLs). Capturing of such epistasis in a genome-wide manner requires very large populations to represent replicated combinations of loci whose interactions determine phenotypic outcomes. Here, we dissect epistasis using a densely genotyped population of 1,400 backcross inbred lines (BILs) between a modern processing tomato inbred (Solanum lycopersicum) and the Lost Accession (LA5240) of a distant, green-fruited, drought-tolerant wild species, Solanum pennellii. The homozygous BILs, each harboring an average of 11 introgressions and their hybrids with the recurrent parents, were phenotyped for tomato yield components. Population-wide mean yield of the BILs was less than 50% of that of their hybrids (BILHs). All the homozygous introgressions across the genome reduced yield relative to recurrent parent, while several QTLs of the BILHs independently improved productivity. Analysis of two QTL scans showed 61 cases of less-than-additive interactions and 19 cases of more-than-additive interactions. Strikingly, a single epistatic interaction involving S. pennellii QTLs on chromosomes 1 and 7, that independently did not affect yield, increased fruit yield by 20 to 50% in the double introgression hybrid grown in irrigated and dry fields over a period of 4 y. Our work demonstrates the power of large, interspecific controlled population development to uncover hidden QTL phenotypes and how rare epistatic interactions can improve crop productivity via heterosis.
DeMalach, N. ; Kigel, J. ; Sternberg, M. . Contrasting Dynamics Of Seed Banks And Standing Vegetation Of Annuals And Perennials Along A Rainfall Gradient. 2023, 58, 125718. Publisher's VersionAbstract
The soil seed bank is a major component of plant communities. However, long-term analyses of the dynamics of the seed bank and the ensuing vegetation are rare. Here, we studied the dynamics in plant communities with high dominance of annuals in Mediterranean, semiarid, and arid ecosystems for nine consecutive years. For annuals, we hypothesized that the density of the seed bank would be more stable than the density of the standing herbaceous vegetation. Moreover, we predicted that differences in temporal variability between the seed bank and the vegetation would increase with aridity, where year-to-year rainfall variability is higher. We found that the temporal variability at the population level (assessed as the standard deviation of the loge-transformed density) of the nine dominant annuals in each site did not differ between the seed bank and the ensuing vegetation in any of the sites. For the total density of annuals, patterns depended on aridity. In the Mediterranean site, the temporal variability was similar in the seed bank and the vegetation (0.40 vs. 0.40). Still, in the semiarid and arid sites, variability in the seed bank was lower than in the vegetation (0.49 vs. 1.01 and 0.63 vs. 1.38, respectively). This difference between the population-level patterns and the total density of annuals can be related to the lower population synchrony in their seed bank. In contrast, for the herbaceous perennials (all species combined), the seed bank variability was higher than in the vegetation. Overall, our results highlight the role of the seed bank in buffering the annual vegetation density with increasing climatic uncertainty typical in aridity gradients. This role is crucial under the increasing uncertainty imposed by climatic change in the region.
Avneri, A. ; Aharon, S. ; Brook, A. ; Atsmon, G. ; Smirnov, E. ; Sadeh, R. ; Abbo, S. ; Peleg, Z. ; Herrmann, I. ; Bonfil, D. J. ; et al. Uas-Based Imaging For Prediction Of Chickpea Crop Biophysical Parameters And Yield. 2023, 205, 107581. Publisher's VersionAbstract
Chickpea (Cicer arietinum L.) is a key legume crop grown in many semi-arid areas. Traditionally, chickpea is a rainfed spring crop, but in certain countries it has become an irrigated crop. The main objective of this study was to evaluate the ability of Unmanned Aerial Systems (UAS) imaging platform with an integrated RGB camera to provide estimations of leaf area index (LAI), biomass, and yield for chickpea during the irrigation period. Two field trials were conducted in 2019 and 2020, in which chickpea plants were subjected to five and six irrigation regimes, respectively. Eight vegetation indexes (VIs) and three morphological parameters were estimated from the RGB images. In parallel, biomass was determined, LAI was measured manually, and yield was determined at full maturity. In total, 294 plant samples were acquired and analyzed over the two years. Firstly, each of the VIs and morphological parameters were correlated separately against the two biophysical parameters and yield. Then, all the VIs and morphological parameters were analyzed together, and two statistical models, partial least squares regression (PLS-R) and support vector machine (SVM); were used to predict biomass and LAI. The yield was predicted using multi-linear regression (MLR). When each index or morphological parameter was analyzed separately, plant height and some of the VIs provided adequate predictions of the biophysical parameters in 2019 (R2 values ≥ 0.50) but failed (R2 values ≤ 0.25) in 2020. The integration of the VIs with the morphological parameters and the use of PLS-R and SVM models increased the accuracy level for both biophysical parameters (R2 ranged from 0.31 to 0.96) and mitigated the lack of consistency between the years. The SVM model was superior to the PLS-R model in both biophysical parameters. The R2 values for the combined 2019 and 2020 biomass model increased, at the model-testing stage, from 0.62 to 0.96 and the RMSE values dropped from 1778 to 490 kg ha−1. The ability of the SVM model to estimate chickpea biomass and LAI can provide convenient support for different management decisions, including timing and amount of irrigation and harvest date.
2022
Panda, S. ; Jozwiak, A. ; Sonawane, P. D. ; Szymanski, J. ; Kazachkova, Y. ; Vainer, A. ; Kilambi, H. V. ; Almekias-Siegl, E. ; Dikaya, V. ; Bocobza, S. ; et al. Steroidal Alkaloids Defence Metabolism And Plant Growth Are Modulated By The Joint Action Of Gibberellin And Jasmonate Signalling. New Phytologist 2022, 233, 1220-1237. Publisher's VersionAbstract
Summary Steroidal glycoalkaloids (SGAs) are protective metabolites constitutively produced by Solanaceae species. Genes and enzymes generating the vast structural diversity of SGAs have been largely identified. Yet, mechanisms of hormone pathways coordinating defence (jasmonate; JA) and growth (gibberellin; GA) controlling SGAs metabolism remain unclear. We used tomato to decipher the hormonal regulation of SGAs metabolism during growth vs defence tradeoff. This was performed by genetic and biochemical characterisation of different JA and GA pathways components, coupled with in vitro experiments to elucidate the crosstalk between these hormone pathways mediating SGAs metabolism. We discovered that reduced active JA results in decreased SGA production, while low levels of GA or its receptor led to elevated SGA accumulation. We showed that MYC1 and MYC2 transcription factors mediate the JA/GA crosstalk by transcriptional activation of SGA biosynthesis and GA catabolism genes. Furthermore, MYC1 and MYC2 transcriptionally regulate the GA signalling suppressor DELLA that by itself interferes in JA-mediated SGA control by modulating MYC activity through protein–protein interaction. Chemical and fungal pathogen treatments reinforced the concept of JA/GA crosstalk during SGA metabolism. These findings revealed the mechanism of JA/GA interplay in SGA biosynthesis to balance the cost of chemical defence with growth.
Shohat, H. ; Cheriker, H. ; Cohen, A. ; Weiss, D. . Tomato Aba-Importing Transporter 1.1 Inhibits Seed Germination Under High Salinity Conditions. Plant Physiology 2022. Publisher's VersionAbstract
The plant hormone abscisic acid (ABA) plays a central role in the regulation of seed maturation and dormancy. ABA also restrains germination under abiotic-stress conditions. Here, we show in tomato (Solanum lycopersicum) that the ABA importer ABA-IMPORTING TRANSPORTER 1.1 (AIT1.1/NPF4.6) has a role in radicle emergence under salinity conditions. AIT1.1 expression was upregulated following seed imbibition, and CRISPR/Cas9-derived ait1.1 mutants exhibited faster radicle emergence, increased germination and partial resistance to ABA. AIT1.1 was highly expressed in the endosperm, but not in the embryo, and ait1.1 isolated embryos did not show resistance to ABA. On the other hand, loss of AIT1.1 activity promoted the expression of endosperm-weakening-related genes, and seed-coat scarification eliminated the promoting effect of ait1.1 on radicle emergence. Therefore, we propose that imbibition-induced AIT1.1 expression in the micropylar endosperm mediates ABA-uptake into micropylar cells to restrain endosperm weakening. While salinity conditions strongly inhibited wild-type M82 seed germination, high salinity had a much weaker effect on ait1.1 germination. We suggest that AIT1.1 evolved to inhibit germination under unfavorable conditions, such as salinity. Unlike other ABA mutants, ait1.1 exhibited normal seed longevity, and therefore, the ait1.1 allele may be exploited to improve seed germination in crops.
Golan, E. ; Peleg, Z. ; Tietel, Z. ; Erel, R. . Sesame Response To Nitrogen Management Under Contrasting Water Availabilities. Oil Crop Science 2022, 7, 166-173. Publisher's VersionAbstract
Sesame is mainly cultivated under traditional, low-input agro-systems. Recent breeding developments promoted the modernization and mechanization of sesame cultivation. However, only a few articles have been published concerning fertilization requirements for both modern and traditional agro-systems. In field trials at two locations, we determined the response of irrigated sesame to nitrogen (N). Three promising sesame lines were tested combining two irrigation levels with four N levels. At a high irrigation level, N had a significant effect on growth, branching, and consequently, seed yield exceeding two-ton ha−1. A high N doze was accompanied by a decrease in the photosynthetic rate and leaf water potential. The δ13C confirmed lower stomatal conductance under high N treatments. Under deficit irrigation, the N level had a minor effect on the monitored parameters, indicating N fertilization was not efficient. Seed oil content was negatively correlated with seed N concentration. Our results question the necessity of N application when water is limited, as N fertilization promotes vigorous development that rapidly depletes soil water. Thus, water availability should be considered when developing an N management strategy. For high-yielding agro-systems, roughly 80–120 ​kg ​ha−1 N is required for optimal yield, bearing in mind the negative association between seed-N and oil content.
Sabag, I. ; Bi, Y. ; Peleg, Z. ; Morota, G. . Multi-Environment Analysis Enhances Genomic Prediction Accuracy Of Agronomic Traits In Sesame. bioRxiv 2022. Publisher's VersionAbstract
Sesame is an ancient oilseed crop containing many valuable nutritional components. Recently, the demand for sesame seeds and their products has increased worldwide, making it necessary to enhance the development of high-yielding cultivars. One approach to enhance genetic gain in breeding programs is genomic selection. However, studies on genomic selection and genomic prediction in sesame are limited. In this study, we performed genomic prediction for agronomic traits using the phenotypes and genotypes of a sesame diversity panel grown under Mediterranean climatic conditions over two growing seasons. We aimed to assess the accuracy of prediction for nine important agronomic traits in sesame using single- and multi-environment analyses. In single-environment analysis, genomic best linear unbiased prediction, BayesB, BayesC, and reproducing kernel Hilbert spaces models showed no substantial differences. The average prediction accuracy of the nine traits across these models ranged from 0.39-0.79 for both growing seasons. In the multi-environment analysis, the marker-by-environment interaction model, which decomposed the marker effects into components shared across environments and environment-specific deviations, improved the prediction accuracies for all traits by 15%\-58% compared to the single-environment model, particularly when borrowing information from other environments was made possible. Our results showed that single-environment analysis produced moderate-to-high genomic prediction accuracy for agronomic traits in sesame. The multi-environment analysis further enhanced this accuracy by exploiting marker-by-environment interaction. We concluded that genomic prediction using multi-environmental trial data could improve efforts for breeding cultivars adapted to the semi-arid Mediterranean climate.Competing Interest StatementThe authors have declared no competing interest.
Modrego, A. ; Pasternak, T. ; Omary, M. ; Albacete, A. ; Cano, A. ; Pérez-Pérez, J. M. ; Efroni, I. . Mapping Of The Classical Mutation Rosette Highlights A Role For Calcium In Wound-Induced Rooting. Plant Cell Physiol 2022, pcac163. Publisher's VersionAbstract
Removal of the root system induces the formation of new roots from the remaining shoot. This process is primarily controlled by the phytohormone auxin, which interacts with other signals in a yet unresolved manner. Here, we study the classical tomato mutation rosette (ro), which lacks shoot-borne roots. ro plants were severely inhibited in forming wound-induced roots and have reduced auxin transport rates. We mapped ro to the tomato ortholog of the Arabidopsis thaliana BIG and the mammalians UBR4/p600. RO/BIG is a large protein of unknown biochemical function. In A. thaliana, BIG was implicated in regulating auxin transport and calcium homeostasis. We show that exogenous calcium inhibits wound-induced root formation in tomato and A. thaliana ro/big mutants. Exogenous calcium antagonized the root-promoting effects of the auxin IAA but not of 2,4-D, an auxin analog that is not recognized by the polar transport machinery, and accumulation of the auxin transporter PIN1 was sensitive to calcium levels in the ro/big mutants. Consistent with a role for calcium in mediating auxin transport, both ro/big mutants and calcium-treated wild-type plants were hypersensitive to treatment with polar auxin transport inhibitors. Subcellular localization of BIG suggests that, like its mammalian ortholog, it is associated with the endoplasmic reticulum (ER). Analysis of subcellular morphology revealed that ro/big mutants exhibited disruption in cytoplasmic streaming. We suggest that RO/BIG maintain auxin flow by stabilizing PIN membrane localization, possibly by attenuating the inhibitory effect of Ca2+ on cytoplasmic streaming.
Omary, M. ; Matosevich, R. ; Efroni, I. . Systemic Control Of Plant Regeneration And Wound Repair. New Phytologist 2022, n/a. Publisher's VersionAbstract
Summary Plants have a broad capacity to regenerate damaged organs. The study of wounding in multiple developmental systems has uncovered many of the molecular properties underlying plants' competence for regeneration at the local cellular level. However, in nature, wounding is rarely localized to one place, and plants need to coordinate regeneration responses at multiple tissues with environmental conditions and their physiological state. Here, we review the evidence for systemic signals that regulate regeneration on a plant-wide level. We focus on the role of auxin and sugars as short‑ and long-range signals in natural wounding contexts and discuss the varied origin of these signals in different regeneration scenarios. Together, this evidence calls for a broader, system-wide view of plant regeneration competence.
Berger, K. ; Machwitz, M. ; Kycko, M. ; Kefauver, S. C. ; Van Wittenberghe, S. ; Gerhards, M. ; Verrelst, J. ; Atzberger, C. ; van der Tol, C. ; Damm, A. ; et al. Multi-Sensor Spectral Synergies For Crop Stress Detection And Monitoring In The Optical Domain: A Review. 2022, 280, 113198. Publisher's VersionAbstract
Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under short-term, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.
Peleg, Z. ; Abbo, S. ; Gopher, A. . When Half Is More Than The Whole: Wheat Domestication Syndrome Reconsidered. Evolutionary ApplicationsEvolutionary ApplicationsEvol Appl 2022, n/a. Publisher's VersionAbstract
Abstract Two opposing models currently dominate Near Eastern plant domestication research. The core area-one event model depicts a knowledge-based, conscious, geographically centered, rapid single-event domestication, while the protracted-autonomous model emphasizes a non-centered, millennia-long process based on unconscious dynamics. The latter model relies, in part, on quantitative depictions of diachronic changes (in archaeological remains) in proportions of spikelet shattering to non-shattering, towards full dominance of the non-shattering (domesticated) phenotypes in cultivated cereal populations. Recent wild wheat genome assembly suggests that shattering and non-shattering spikelets may originate from the same (individual) genotype. Therefore, their proportions among archaeobotanical assemblages cannot reliably describe the presumed protracted-selection dynamics underlying wheat domestication. This calls for a reappraisal of the ?domestication syndrome? concept associated with cereal domestication.
Feuer, E. ; Zimran, G. ; Shpilman, M. ; Mosquna, A. . A Modified Yeast Two-Hybrid Platform Enables Dynamic Control Of Expression Intensities To Unmask Properties Of Protein–Protein Interactions. ACS Synthetic BiologyACS Synthetic Biology 2022. Publisher's VersionAbstract
The yeast two-hybrid (Y2H) assay is widely used for protein–protein interaction characterization due to its simplicity and accessibility. However, it may mask changes in affinity caused by mutations or ligand activation due to signal saturation. To overcome this drawback, we modified the Y2H system to have tunable protein expression by introducing a fluorescent reporter and a pair of synthetic inducible transcription factors to regulate the expression of interacting components. We found that the application of inducers allowed us to adjust the concentrations of interacting proteins to avoid saturation and observe interactions otherwise masked in the canonical Y2H assay, such as the abscisic acid-mediated increase in affinity of monomeric abscisic acid receptors to the coreceptor. When applied in future studies, our modified system may provide a more accurate characterization of protein–protein interactions.The yeast two-hybrid (Y2H) assay is widely used for protein–protein interaction characterization due to its simplicity and accessibility. However, it may mask changes in affinity caused by mutations or ligand activation due to signal saturation. To overcome this drawback, we modified the Y2H system to have tunable protein expression by introducing a fluorescent reporter and a pair of synthetic inducible transcription factors to regulate the expression of interacting components. We found that the application of inducers allowed us to adjust the concentrations of interacting proteins to avoid saturation and observe interactions otherwise masked in the canonical Y2H assay, such as the abscisic acid-mediated increase in affinity of monomeric abscisic acid receptors to the coreceptor. When applied in future studies, our modified system may provide a more accurate characterization of protein–protein interactions.
Zimran, G. ; Feuer, E. ; Pri-Tal, O. ; Shpilman, M. ; Mosquna, A. . Directed Evolution Of Herbicide Biosensors In A Fluorescence-Activated Cell-Sorting-Compatible Yeast Two-Hybrid Platform. ACS Synthetic BiologyACS Synthetic Biology 2022. Publisher's VersionAbstract
Developing sensory modules for specific molecules of interest represents a fundamental challenge in synthetic biology and its applications. A somewhat generalizable approach for this challenge is demonstrated here by evolving a naturally occurring chemically induced heterodimer into a genetically encoded sensor for herbicides. The interaction between PYRABACTIN-RESISTANT-like receptors and type-2C protein phosphatases is induced by abscisic acid─a small-molecule hormone in plants. We considered abscisic acid receptors as a potential scaffold for the development of biosensors because of past successes in their engineering, a structurally defined ligand cavity and the availability of large-scale assays for their activation. A panel of 475 receptor variants, mutated at ligand-proximal residues, was screened for activation by 37 herbicides from several classes. Twelve compounds activated at least one member of the mutant panel. To facilitate the subsequent improvement of herbicide receptors through directed evolution, we engineered a yeast two-hybrid platform optimized for sequential positive and negative selection using fluorescence-activated cell sorting. By utilizing this system, we were able to isolate receptors with low nanomolar sensitivity and a broad dynamic range in sensing a ubiquitous group of chloroacetamide herbicides. Aside from its possible applicative value, this work lays down conceptual groundwork and provides infrastructure for the future development of biosensors through directed evolution.Developing sensory modules for specific molecules of interest represents a fundamental challenge in synthetic biology and its applications. A somewhat generalizable approach for this challenge is demonstrated here by evolving a naturally occurring chemically induced heterodimer into a genetically encoded sensor for herbicides. The interaction between PYRABACTIN-RESISTANT-like receptors and type-2C protein phosphatases is induced by abscisic acid─a small-molecule hormone in plants. We considered abscisic acid receptors as a potential scaffold for the development of biosensors because of past successes in their engineering, a structurally defined ligand cavity and the availability of large-scale assays for their activation. A panel of 475 receptor variants, mutated at ligand-proximal residues, was screened for activation by 37 herbicides from several classes. Twelve compounds activated at least one member of the mutant panel. To facilitate the subsequent improvement of herbicide receptors through directed evolution, we engineered a yeast two-hybrid platform optimized for sequential positive and negative selection using fluorescence-activated cell sorting. By utilizing this system, we were able to isolate receptors with low nanomolar sensitivity and a broad dynamic range in sensing a ubiquitous group of chloroacetamide herbicides. Aside from its possible applicative value, this work lays down conceptual groundwork and provides infrastructure for the future development of biosensors through directed evolution.
Grünzweig, J. ; De Boeck, H. J. ; Rey, A. ; Santos, M. J. ; Adam, O. ; Bahn, M. ; Belnap, J. ; Deckmyn, G. ; Dekker, S. C. ; Flores, O. ; et al. Dryland Mechanisms Could Widely Control Ecosystem Functioning In A Drier And Warmer World. 2022. Publisher's VersionAbstract
Responses of terrestrial ecosystems to climate change have been explored in many regions worldwide. While continued drying and warming may alter process rates and deteriorate the state and performance of ecosystems, it could also lead to more fundamental changes in the mechanisms governing ecosystem functioning. Here we argue that climate change will induce unprecedented shifts in these mechanisms in historically wetter climatic zones, towards mechanisms currently prevalent in dry regions, which we refer to as ‘dryland mechanisms’. We discuss 12 dryland mechanisms affecting multiple processes of ecosystem functioning, including vegetation development, water flow, energy budget, carbon and nutrient cycling, plant production and organic matter decomposition. We then examine mostly rare examples of the operation of these mechanisms in non-dryland regions where they have been considered irrelevant at present. Current and future climate trends could force microclimatic conditions across thresholds and lead to the emergence of dryland mechanisms and their increasing control over ecosystem functioning in many biomes on Earth.
Sahoo, M. M. ; Perach, O. ; Shachter, A. ; Gonda, I. ; Porwal, A. ; Dudai, N. ; Herrmann, I. . Spectral Estimation Of Carnosic Acid Content In In Vivo Rosemary Plants. 2022, 187, 115292. Publisher's VersionAbstract
Rosemary (Salvia rosmarinus (L.) Schleid., Handb. syn. Rosmarinus officinalis L.) extracts are widely used as natural preservatives due to their antimicrobial and antioxidant properties, which are attributed to the phenolic diterpenoid carnosic acid (CA). Growers are rewarded based on CA content in their rosemary leaf harvested. Conventional methods for estimating leaf CA content are destructive and often time-consuming. This preliminary study presents a spectral non-destructive approach for in vivo estimation of CA content in different rosemary cultivars based on the reflectance spectra of their canopy. The proposed approach is based on the characteristic rosemary absorption features along the visible and shortwave infrared spectral regions at 550 nm, 1200 nm, and 1690 nm, respectively, attributed to leaf color, the oxygen-hydrogen bond bending in water molecules, and distinctive carbon-hydrogen bond features typical for terpenes and phenolic compounds. Correlations between measured CA content by high-performance liquid chromatography (HPLC) and leaf reflectance spectra, normalized spectral indices, and latent components obtained by genetic algorithm-based partial least squares regression (GA-PLSR) were assessed using data collected from 79 rosemary cultivars. The GA-PLSR model successfully predicted the CA content among the various cultivars, further providing evidence of high weightage to the above-mentioned absorption features also obtained from two best-wavelength combination selections. Randomly selected canopy spectra were used to calibrate and simultaneously cross-validate 100 iterations, using the ‘leave-k-out’ approach. The root mean squared error (RMSE) obtained for calibration and cross-validation were 0.86% and 1.15% CA content from the dry leaf matter, and the residual prediction deviation (RPD) were reported to be 2.71 and 2.05, respectively. This work will set the stage for precise planning of harvesting time to ensure increased yield and income for the farmers and improved utilization of resources.
Qi, M. ; DeMalach, N. ; Dong, Y. ; Zhang, H. ; Sun, T. . Coexistence Under Hierarchical Resource Exploitation: The Role Of The R*-Preemption Trade-Off. The American NaturalistThe American Naturalist 2022, 000 - 000. Publisher's VersionAbstract
AbstractResource competition theory predicts coexistence and exclusion patterns based on species? R*s, the minimum resource values required for a species to persist. A central assumption of the theory is that all species have equal access to resources. However, many systems are characterized by preemption exploitation, where some species deplete resources before their competitors can access them (e.g., asymmetric light competition, contest competition among animals). We hypothesized that coexistence under preemption requires an R*-preemption trade-off?that is, the species with the priority access should have a higher R* (lower ?efficiency?). Thus, we developed an extension of resource competition theory to investigate partial and total preemption (in the latter, the preemptor is unaffected by species with lower preemption rank). We found that an R*-preemption trade-off is a necessary condition for coexistence in all models. Moreover, under total preemption, the trade-off alone is sufficient for coexistence. In contrast, under partial preemption, more conditions are needed, which restricts the parameter space of coexistence. Finally, we discuss the implications of our finding for seemingly distinct trade-offs, which we view as special cases of the R*-preemption trade-off. These trade-offs include the digger-grazer trade-off, the competition-colonization trade-off, and trade-offs related to light competition between trees and understories.AbstractResource competition theory predicts coexistence and exclusion patterns based on species? R*s, the minimum resource values required for a species to persist. A central assumption of the theory is that all species have equal access to resources. However, many systems are characterized by preemption exploitation, where some species deplete resources before their competitors can access them (e.g., asymmetric light competition, contest competition among animals). We hypothesized that coexistence under preemption requires an R*-preemption trade-off?that is, the species with the priority access should have a higher R* (lower ?efficiency?). Thus, we developed an extension of resource competition theory to investigate partial and total preemption (in the latter, the preemptor is unaffected by species with lower preemption rank). We found that an R*-preemption trade-off is a necessary condition for coexistence in all models. Moreover, under total preemption, the trade-off alone is sufficient for coexistence. In contrast, under partial preemption, more conditions are needed, which restricts the parameter space of coexistence. Finally, we discuss the implications of our finding for seemingly distinct trade-offs, which we view as special cases of the R*-preemption trade-off. These trade-offs include the digger-grazer trade-off, the competition-colonization trade-off, and trade-offs related to light competition between trees and understories.