New Phytologist, 225(2020), 2048–2063, doi: 10.1111/nph.16272.
Since its publication, it has been brought to our attention that there are errors in the article by Yan et al. (2023). Some of the images in Figs 7, 8 & S11 were duplicated in error during the compilation of these figures. The correct Figs 7, 8 & S11, and the associated legends, are given below.
We apologize to our readers for these errors.
Corrected Figs 7, 8 & S11:
Authors for correspondence:
Zhengkun Qiu
Email:[email protected]
Bihao Cao
Email:[email protected]
Xiaoxi Liu
Email:[email protected]
{"title":"Corrigendum to: Anthocyanin Fruit encodes an R2R3-MYB transcription factor, SlAN2-like, activating the transcription of SlMYBATV to fine-tune anthocyanin content in tomato fruit","authors":"","doi":"10.1111/nph.20296","DOIUrl":"10.1111/nph.20296","url":null,"abstract":"<p><i>New Phytologist</i>, 225(2020), 2048–2063, doi: 10.1111/nph.16272.</p><p>Since its publication, it has been brought to our attention that there are errors in the article by Yan <i>et al</i>. (<span>2023</span>). Some of the images in Figs 7, 8 & S11 were duplicated in error during the compilation of these figures. The correct Figs 7, 8 & S11, and the associated legends, are given below.</p><p>We apologize to our readers for these errors.</p><p><b>Corrected Figs 7, 8 & S11:</b></p><p>Authors for correspondence:</p><p><i>Zhengkun Qiu</i></p><p><i>Email:</i> <span>[email protected]</span></p><p><i>Bihao Cao</i></p><p><i>Email:</i> <span>[email protected]</span></p><p><i>Xiaoxi Liu</i></p><p><i>Email:</i> <span>[email protected]</span></p>","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"245 2","pages":"914-916"},"PeriodicalIF":8.3,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/nph.20296","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142741052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gustavo A. Silva‐Arias, Edeline Gagnon, Surya Hembrom, Alexander Fastner, Muhammad Ramzan Khan, Remco Stam, Aurélien Tellier
SummaryUnderstanding the evolution of pathogen resistance genes (nucleotide‐binding site‐leucine‐rich repeats, NLRs) within a species requires a comprehensive examination of factors that affect gene loss and gain.We present a new reference genome of Solanum chilense, which leads to an increased number and more accurate annotation of NLRs. Using a target capture approach, we quantify the presence–absence variation (PAV) of NLR loci across 20 populations from different habitats. We build a rigorous pipeline to validate the identification of PAV of NLRs and then show that PAV is larger within populations than between populations, suggesting that maintenance of NLR diversity is linked to population dynamics.The amount of PAV appears not to be correlated with the NLR presence in gene clusters in the genome, but rather with the past demographic history of the species, with loss of NLRs in diverging (smaller) populations at the distribution edges. Finally, using a redundancy analysis, we find limited evidence of PAV being linked to environmental gradients.Our results suggest that random processes (genetic drift and demography) and weak positive selection for local adaptation shape the evolution of NLRs at the single nucleotide polymorphism and PAV levels in an outcrossing plant with high nucleotide diversity.
{"title":"Patterns of presence–absence variation of NLRs across populations of Solanum chilense are clade‐dependent and mainly shaped by past demographic history","authors":"Gustavo A. Silva‐Arias, Edeline Gagnon, Surya Hembrom, Alexander Fastner, Muhammad Ramzan Khan, Remco Stam, Aurélien Tellier","doi":"10.1111/nph.20293","DOIUrl":"https://doi.org/10.1111/nph.20293","url":null,"abstract":"Summary<jats:list list-type=\"bullet\"> <jats:list-item>Understanding the evolution of pathogen resistance genes (nucleotide‐binding site‐leucine‐rich repeats, NLRs) within a species requires a comprehensive examination of factors that affect gene loss and gain.</jats:list-item> <jats:list-item>We present a new reference genome of <jats:italic>Solanum chilense</jats:italic>, which leads to an increased number and more accurate annotation of NLRs. Using a target capture approach, we quantify the presence–absence variation (PAV) of NLR <jats:italic>loci</jats:italic> across 20 populations from different habitats. We build a rigorous pipeline to validate the identification of PAV of NLRs and then show that PAV is larger within populations than between populations, suggesting that maintenance of NLR diversity is linked to population dynamics.</jats:list-item> <jats:list-item>The amount of PAV appears not to be correlated with the NLR presence in gene clusters in the genome, but rather with the past demographic history of the species, with loss of NLRs in diverging (smaller) populations at the distribution edges. Finally, using a redundancy analysis, we find limited evidence of PAV being linked to environmental gradients.</jats:list-item> <jats:list-item>Our results suggest that random processes (genetic drift and demography) and weak positive selection for local adaptation shape the evolution of NLRs at the single nucleotide polymorphism and PAV levels in an outcrossing plant with high nucleotide diversity.</jats:list-item> </jats:list>","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"71 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<div>Cultivating knowledge to enable accurate estimates of soil carbon fluxes has never been more critical as we contend with climate change. Nevertheless, the incredible diversity of soil communities and the environmental conditions that they experience obfuscates this understanding. Many of these environmental scenarios are influenced by the widespread, human-caused disturbance that has characterized recent history (e.g. deforestation). Environmental restoration practices hold promise to recover some ecosystem functions and aid in climate change mitigation (e.g. by capturing and storing carbon in soil), but many questions remain about the factors that determine the efficacy of these practices. Plants drive the influx of carbon to the soil through above- and belowground litter and root exudates, while the processing of this carbon by soil organisms determines whether carbon persists in soil or is respired to the atmosphere. An immensely diverse, microscopic community of bacteria, fungi, and animals (e.g. nematodes, protists) influences these soil carbon dynamics through their metabolic processes and interactions with one another. Despite this theoretical understanding, quantitative evidence of how inter-organismal interactions determine carbon flow in soil remains difficult to interpret in the context of soil carbon accrual since these interactions are immensely complex and dynamic. A recent publication by Zhang <i>et al</i>. (<span>2024b</span>; doi: 10.1111/nph.20166) in <i>New Phytologist</i> addresses this challenge in a compelling way by considering the ecological strategies of plants and nematodes interactively to explain soil carbon dynamics across a gradient of environmental conditions. Their approach is particularly novel and valuable because they not only consider the interactions between plants and nematodes across a gradient of environmental disturban but also connect this to microbial carbon cycling to explain soil carbon content. <blockquote><p>‘…integrated plant and nematode ecological spectra explain more variation in soil carbon dynamics together, than either do alone.’</p> <div></div> </blockquote> </div> <p>Viewing organisms through the lens of their ecological strategies allows us to understand how they function within ecosystems and, thus, conceptualize their interactions with other organisms. Plant ecologists have pioneered this effort, cultivating a historic body of knowledge regarding trade-offs between plant traits across environmental gradients. For example, the leaf economics spectrum defines leaf traits like mass per unit area and leaf tissue nitrogen as indicative of plant investment strategy, varying across environmental conditions (Wright <i>et al</i>., <span>2004</span>). Such frameworks allow us to predict how plant communities may shift as ecosystems change, for instance following intense environmental disturbance. Soil ecologists have more recently sought to develop similar frameworks, identifying traits like b
{"title":"Toward understanding how cross-kingdom ecological strategies interactively influence soil carbon cycling","authors":"Jennifer L. Kane, Jie Hu, Binu Tripathi","doi":"10.1111/nph.20290","DOIUrl":"https://doi.org/10.1111/nph.20290","url":null,"abstract":"<div>Cultivating knowledge to enable accurate estimates of soil carbon fluxes has never been more critical as we contend with climate change. Nevertheless, the incredible diversity of soil communities and the environmental conditions that they experience obfuscates this understanding. Many of these environmental scenarios are influenced by the widespread, human-caused disturbance that has characterized recent history (e.g. deforestation). Environmental restoration practices hold promise to recover some ecosystem functions and aid in climate change mitigation (e.g. by capturing and storing carbon in soil), but many questions remain about the factors that determine the efficacy of these practices. Plants drive the influx of carbon to the soil through above- and belowground litter and root exudates, while the processing of this carbon by soil organisms determines whether carbon persists in soil or is respired to the atmosphere. An immensely diverse, microscopic community of bacteria, fungi, and animals (e.g. nematodes, protists) influences these soil carbon dynamics through their metabolic processes and interactions with one another. Despite this theoretical understanding, quantitative evidence of how inter-organismal interactions determine carbon flow in soil remains difficult to interpret in the context of soil carbon accrual since these interactions are immensely complex and dynamic. A recent publication by Zhang <i>et al</i>. (<span>2024b</span>; doi: 10.1111/nph.20166) in <i>New Phytologist</i> addresses this challenge in a compelling way by considering the ecological strategies of plants and nematodes interactively to explain soil carbon dynamics across a gradient of environmental conditions. Their approach is particularly novel and valuable because they not only consider the interactions between plants and nematodes across a gradient of environmental disturban but also connect this to microbial carbon cycling to explain soil carbon content. <blockquote><p>‘…integrated plant and nematode ecological spectra explain more variation in soil carbon dynamics together, than either do alone.’</p>\u0000<div></div>\u0000</blockquote>\u0000</div>\u0000<p>Viewing organisms through the lens of their ecological strategies allows us to understand how they function within ecosystems and, thus, conceptualize their interactions with other organisms. Plant ecologists have pioneered this effort, cultivating a historic body of knowledge regarding trade-offs between plant traits across environmental gradients. For example, the leaf economics spectrum defines leaf traits like mass per unit area and leaf tissue nitrogen as indicative of plant investment strategy, varying across environmental conditions (Wright <i>et al</i>., <span>2004</span>). Such frameworks allow us to predict how plant communities may shift as ecosystems change, for instance following intense environmental disturbance. Soil ecologists have more recently sought to develop similar frameworks, identifying traits like b","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"7 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142696625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farhad Masoomi‐Aladizgeh, Brian J. Atwell, Anowarul I. Bokshi, Rebecca J. Thistlethwaite, Ali Khoddami, Richard Trethowan, Daniel K. Y. Tan, Thomas H. Roberts
SummaryThe development of male gametes, vital to sexual reproduction in crops, requires meiosis followed by successive mitotic cell divisions of haploid cells. The formation of viable pollen is especially vulnerable to abiotic stress, with consequences both for yield and for grain quality. An understanding of key molecular responses when specific stages during pollen development are subjected to stress (e.g. heat) is possible only when sampling is carefully informed by developmental biology. Traditionally, morphological characteristics have been commonly used in cereals as ‘indicators’ of male reproductive stages. We argue that these morphological attributes are strongly influenced by genotype and genotype–environment interactions and cannot be used reliably to define developmental events during microsporogenesis and microgametogenesis. Furthermore, asynchronous development along the axis of a single inflorescence calls for selective sampling of individual florets to define specific reproductive stages accurately. We therefore propose guidelines to standardise the sampling of cells during male reproductive development, particularly when interrogating the impact of stress on susceptible meiosis. Improved knowledge of development will largely negate the variability imposed by genotype, environment and asynchronous development of florets. Highlighting the subtleties required for sampling and investigation of male reproductive stages will make the selection of abiotic stress‐tolerant cereal genotypes more reliable.
{"title":"Pinpointing the timing of meiosis: a critical factor in evaluating the impact of abiotic stresses on the fertility of cereal crops","authors":"Farhad Masoomi‐Aladizgeh, Brian J. Atwell, Anowarul I. Bokshi, Rebecca J. Thistlethwaite, Ali Khoddami, Richard Trethowan, Daniel K. Y. Tan, Thomas H. Roberts","doi":"10.1111/nph.20297","DOIUrl":"https://doi.org/10.1111/nph.20297","url":null,"abstract":"SummaryThe development of male gametes, vital to sexual reproduction in crops, requires meiosis followed by successive mitotic cell divisions of haploid cells. The formation of viable pollen is especially vulnerable to abiotic stress, with consequences both for yield and for grain quality. An understanding of key molecular responses when specific stages during pollen development are subjected to stress (e.g. heat) is possible only when sampling is carefully informed by developmental biology. Traditionally, morphological characteristics have been commonly used in cereals as ‘indicators’ of male reproductive stages. We argue that these morphological attributes are strongly influenced by genotype and genotype–environment interactions and cannot be used reliably to define developmental events during microsporogenesis and microgametogenesis. Furthermore, asynchronous development along the axis of a single inflorescence calls for selective sampling of individual florets to define specific reproductive stages accurately. We therefore propose guidelines to standardise the sampling of cells during male reproductive development, particularly when interrogating the impact of stress on susceptible meiosis. Improved knowledge of development will largely negate the variability imposed by genotype, environment and asynchronous development of florets. Highlighting the subtleties required for sampling and investigation of male reproductive stages will make the selection of abiotic stress‐tolerant cereal genotypes more reliable.","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"25 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ylva Lekberg, Jan Jansa, David Johnson, Paul Milham, Chad Penn, Benjamin P. Colman
<p>A recent paper about carbon and phosphorus (P) transfer between arbuscular mycorrhizal (AM) fungi and plants (Lekberg <i>et al</i>., <span>2024</span>) was cited by Spohn & Wanek (<span>2025</span>; pp. 443–445, in this issue) to highlight potential pitfalls of using P radioisotopes (in this case <sup>32</sup>P, although equally relevant for <sup>33</sup>P as they behave similarly; Frossard <i>et al</i>., <span>2011</span>). Specifically, the paper by Spohn & Wanek (<span>2025</span>) states that without knowing the specific activity in soil solution (i.e. the ratio of <sup>32</sup>P : <sup>31</sup>P), the conclusion in Lekberg <i>et al</i>. (<span>2024</span>) that more P was delivered by AM fungi in high-P than low-P soils may not be valid if the three low-P soils sorbed more <sup>32</sup>P. We agree with Spohn & Wanek (<span>2025</span>) that tracer experiments should be interpreted with caution, and we appreciate the opportunity to explore some of the pitfalls highlighted in that paper in more detail.</p><p>Sorption of inorganic orthophosphate (H<sub>2</sub>PO<sub>4</sub><sup>−</sup> and HPO<sub>4</sub><sup>2−</sup>) – the main P form taken up by plants, fungi, and prokaryotes from soil solution (Bucher, <span>2007</span>) – is determined by pH, organic matter, hydrous oxides of aluminum and iron, and calcium carbonate (Frossard <i>et al</i>., <span>1995</span>; Daly <i>et al</i>., <span>2001</span>; Barrow, <span>2017</span>). In Lekberg <i>et al</i>. (<span>2024</span>), soils were collected from two regions, one with high-P availability and one with low-P availability. In both regions, soils were classified as fine to gravely, loamy Mollisols, and neither soil pH (6.80 ± 0.38 vs 6.53 ± 0.38, means ± SE) nor organic matter concentrations (4.50 ± 0.69% and 5.03 ± 2.00%) differed (<i>P</i> > 0.5) between the high-P and low-P soils, respectively. Total organic P stocks also did not differ significantly between the high-P and low-P soils (1178 ± 302 and 684 ± 79 mg kg<sup>−1</sup>) and the strong regional difference in P availability based on Bray 1 extractions were likely due to soil mineralogy.</p><p>There is another reason why differences in sorption likely did not influence results in Lekberg <i>et al</i>. (<span>2024</span>). One of the main assumptions of plant–soil–isotope experiments is that the concentration of the isotope-tracer must be negligible compared to that of the nonlabelled nutrient in solution. If the amount of <sup>32</sup>P added is similar to <sup>31</sup>P, the solution and solid-phase P equilibrium is disrupted and net sorption of total and <sup>32</sup>P will occur. The solution concentration where no net sorption or desorption occurs in soil is known as the ‘equilibrium P concentration at net zero sorption’ (EPC<sub>0</sub>). Specific to each soil, EPC<sub>0</sub> depends on the same variables that determine sorption, as well as P desorption kinetics, and microbial P immobilization and release. A rec
{"title":"Tracing phosphorus from soil through mycorrhizal fungi to plants","authors":"Ylva Lekberg, Jan Jansa, David Johnson, Paul Milham, Chad Penn, Benjamin P. Colman","doi":"10.1111/nph.20217","DOIUrl":"10.1111/nph.20217","url":null,"abstract":"<p>A recent paper about carbon and phosphorus (P) transfer between arbuscular mycorrhizal (AM) fungi and plants (Lekberg <i>et al</i>., <span>2024</span>) was cited by Spohn & Wanek (<span>2025</span>; pp. 443–445, in this issue) to highlight potential pitfalls of using P radioisotopes (in this case <sup>32</sup>P, although equally relevant for <sup>33</sup>P as they behave similarly; Frossard <i>et al</i>., <span>2011</span>). Specifically, the paper by Spohn & Wanek (<span>2025</span>) states that without knowing the specific activity in soil solution (i.e. the ratio of <sup>32</sup>P : <sup>31</sup>P), the conclusion in Lekberg <i>et al</i>. (<span>2024</span>) that more P was delivered by AM fungi in high-P than low-P soils may not be valid if the three low-P soils sorbed more <sup>32</sup>P. We agree with Spohn & Wanek (<span>2025</span>) that tracer experiments should be interpreted with caution, and we appreciate the opportunity to explore some of the pitfalls highlighted in that paper in more detail.</p><p>Sorption of inorganic orthophosphate (H<sub>2</sub>PO<sub>4</sub><sup>−</sup> and HPO<sub>4</sub><sup>2−</sup>) – the main P form taken up by plants, fungi, and prokaryotes from soil solution (Bucher, <span>2007</span>) – is determined by pH, organic matter, hydrous oxides of aluminum and iron, and calcium carbonate (Frossard <i>et al</i>., <span>1995</span>; Daly <i>et al</i>., <span>2001</span>; Barrow, <span>2017</span>). In Lekberg <i>et al</i>. (<span>2024</span>), soils were collected from two regions, one with high-P availability and one with low-P availability. In both regions, soils were classified as fine to gravely, loamy Mollisols, and neither soil pH (6.80 ± 0.38 vs 6.53 ± 0.38, means ± SE) nor organic matter concentrations (4.50 ± 0.69% and 5.03 ± 2.00%) differed (<i>P</i> > 0.5) between the high-P and low-P soils, respectively. Total organic P stocks also did not differ significantly between the high-P and low-P soils (1178 ± 302 and 684 ± 79 mg kg<sup>−1</sup>) and the strong regional difference in P availability based on Bray 1 extractions were likely due to soil mineralogy.</p><p>There is another reason why differences in sorption likely did not influence results in Lekberg <i>et al</i>. (<span>2024</span>). One of the main assumptions of plant–soil–isotope experiments is that the concentration of the isotope-tracer must be negligible compared to that of the nonlabelled nutrient in solution. If the amount of <sup>32</sup>P added is similar to <sup>31</sup>P, the solution and solid-phase P equilibrium is disrupted and net sorption of total and <sup>32</sup>P will occur. The solution concentration where no net sorption or desorption occurs in soil is known as the ‘equilibrium P concentration at net zero sorption’ (EPC<sub>0</sub>). Specific to each soil, EPC<sub>0</sub> depends on the same variables that determine sorption, as well as P desorption kinetics, and microbial P immobilization and release. A rec","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"245 2","pages":"446-449"},"PeriodicalIF":8.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/nph.20217","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jayson Sia, Wei Zhang, Mingxi Cheng, Paul Bogdan, David E. Cook
This study investigated the generalizability of Arabidopsis thaliana immune responses across diverse pathogens, including Botrytis cinerea, Sclerotinia sclerotiorum, and Pseudomonas syringae, using a data-driven, machine learning approach.
Machine learning models were trained to predict disease development from early transcriptional responses. Feature selection techniques based on network science and topology were used to train models employing only a fraction of the transcriptome. Machine learning models trained on one pathosystem where then validated by predicting disease development in new pathosystems.
The identified feature selection gene sets were enriched for pathways related to biotic, abiotic, and stress responses, though the specific genes involved differed between feature sets. This suggests common immune responses to diverse pathogens that operate via different gene sets.
The study demonstrates that machine learning can uncover both established and novel components of the plant's immune response, offering insights into disease resistance mechanisms. These predictive models highlight the potential to advance our understanding of multigenic outcomes in plant immunity and can be further refined for applications in disease prediction.
{"title":"Machine learning-based identification of general transcriptional predictors for plant disease","authors":"Jayson Sia, Wei Zhang, Mingxi Cheng, Paul Bogdan, David E. Cook","doi":"10.1111/nph.20264","DOIUrl":"10.1111/nph.20264","url":null,"abstract":"<div>\u0000 \u0000 <p>\u0000 </p><ul>\u0000 \u0000 <li>This study investigated the generalizability of <i>Arabidopsis thaliana</i> immune responses across diverse pathogens, including <i>Botrytis cinerea</i>, <i>Sclerotinia sclerotiorum</i>, and <i>Pseudomonas syringae</i>, using a data-driven, machine learning approach.</li>\u0000 \u0000 <li>Machine learning models were trained to predict disease development from early transcriptional responses. Feature selection techniques based on network science and topology were used to train models employing only a fraction of the transcriptome. Machine learning models trained on one pathosystem where then validated by predicting disease development in new pathosystems.</li>\u0000 \u0000 <li>The identified feature selection gene sets were enriched for pathways related to biotic, abiotic, and stress responses, though the specific genes involved differed between feature sets. This suggests common immune responses to diverse pathogens that operate via different gene sets.</li>\u0000 \u0000 <li>The study demonstrates that machine learning can uncover both established and novel components of the plant's immune response, offering insights into disease resistance mechanisms. These predictive models highlight the potential to advance our understanding of multigenic outcomes in plant immunity and can be further refined for applications in disease prediction.</li>\u0000 </ul>\u0000 </div>","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"245 2","pages":"785-806"},"PeriodicalIF":8.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<h2> Introduction</h2> <p>Several researchers have highlighted the potential of microbial inoculants to advance sustainable agriculture (Elnahal <i>et al</i>., <span>2022</span>; O'Callagha<i>n et al</i>., <span>2022</span>). Among microbial inoculants, arbuscular mycorrhizal (AM) fungi have garnered attention for their ability to enhance soil health and plant fitness. AM fungi can increase plant growth through enhanced access to limiting soil resources, improve plant defense against herbivores and pathogens, increase tolerance to drought and salinity stress, and increase carbon sequestration (Reynolds <i>et al</i>., <span>2006</span>; Bennett <i>et al</i>., <span>2009</span>; Ji & Bever, <span>2016</span>). With this promise, the commercial market for AM inoculants is rapidly growing, approaching 995 million USD globally (Mordor Intelligence, <span>2024</span>). AM inoculants, often referred to as ‘endomycorrhizal’ inoculants on commercial product labels, are easily and widely available in many regions of the world.</p> <p>Despite the optimism surrounding microbial inoculants, global studies have revealed inconsistencies with commercial products, including instances of crop mortality, unlabeled fertilizers, and nonviability (Corkidi <i>et al</i>., <span>2004</span>; Tarbell & Koske, <span>2007</span>; Faye <i>et al</i>., <span>2013</span>; Duell <i>et al</i>., <span>2022</span>; M. Salomon <i>et al</i>., <span>2022</span>; Koziol <i>et al</i>., <span>2024</span>). The benefits of commercial products can be limited by their narrow inclusion of the same four to five species, with many containing a single AM fungus in the <i>Rhizophagus</i> genus (Basiru <i>et al</i>., <span>2020</span>), despite evidence that a more diverse AM fungal consortium may increase crop growth (Magnoli & Bever, <span>2023</span>), nutrient uptake (Reynolds <i>et al</i>., <span>2006</span>), and other benefits. Concerns regarding product mislabeling and contamination by fungal pathogens further highlight the potential risks associated with these products (Tarbell & Koske, <span>2007</span>; Vahter <i>et al</i>., <span>2023</span>). The lack of accountability for product viability is compounded by scientific assessments that often do not report product identities, although some do (Wiseman <i>et al</i>., <span>2009</span>; Faye <i>et al</i>., <span>2020</span>), making it a challenge for both the inoculant industry and for users to be informed on product quality concerns. Regulatory frameworks for mycorrhizal inoculants remain limited in many regions (Carrazco <i>et al</i>., <span>2024</span>; M. J. Salomon <i>et al</i>., <span>2022</span>), exacerbating challenges related to product viability and identity of mycorrhizal fungi in products. The United States fully lacks regulations on the import/export of mycorrhizal fungal products or quality control, despite the United States having a 25% share in the mycorrhizal inoculant industry, representing 249 million
{"title":"Meta-analysis reveals globally sourced commercial mycorrhizal inoculants fall short","authors":"Liz Koziol, Thomas P. McKenna, James D. Bever","doi":"10.1111/nph.20278","DOIUrl":"https://doi.org/10.1111/nph.20278","url":null,"abstract":"<h2> Introduction</h2>\u0000<p>Several researchers have highlighted the potential of microbial inoculants to advance sustainable agriculture (Elnahal <i>et al</i>., <span>2022</span>; O'Callagha<i>n et al</i>., <span>2022</span>). Among microbial inoculants, arbuscular mycorrhizal (AM) fungi have garnered attention for their ability to enhance soil health and plant fitness. AM fungi can increase plant growth through enhanced access to limiting soil resources, improve plant defense against herbivores and pathogens, increase tolerance to drought and salinity stress, and increase carbon sequestration (Reynolds <i>et al</i>., <span>2006</span>; Bennett <i>et al</i>., <span>2009</span>; Ji & Bever, <span>2016</span>). With this promise, the commercial market for AM inoculants is rapidly growing, approaching 995 million USD globally (Mordor Intelligence, <span>2024</span>). AM inoculants, often referred to as ‘endomycorrhizal’ inoculants on commercial product labels, are easily and widely available in many regions of the world.</p>\u0000<p>Despite the optimism surrounding microbial inoculants, global studies have revealed inconsistencies with commercial products, including instances of crop mortality, unlabeled fertilizers, and nonviability (Corkidi <i>et al</i>., <span>2004</span>; Tarbell & Koske, <span>2007</span>; Faye <i>et al</i>., <span>2013</span>; Duell <i>et al</i>., <span>2022</span>; M. Salomon <i>et al</i>., <span>2022</span>; Koziol <i>et al</i>., <span>2024</span>). The benefits of commercial products can be limited by their narrow inclusion of the same four to five species, with many containing a single AM fungus in the <i>Rhizophagus</i> genus (Basiru <i>et al</i>., <span>2020</span>), despite evidence that a more diverse AM fungal consortium may increase crop growth (Magnoli & Bever, <span>2023</span>), nutrient uptake (Reynolds <i>et al</i>., <span>2006</span>), and other benefits. Concerns regarding product mislabeling and contamination by fungal pathogens further highlight the potential risks associated with these products (Tarbell & Koske, <span>2007</span>; Vahter <i>et al</i>., <span>2023</span>). The lack of accountability for product viability is compounded by scientific assessments that often do not report product identities, although some do (Wiseman <i>et al</i>., <span>2009</span>; Faye <i>et al</i>., <span>2020</span>), making it a challenge for both the inoculant industry and for users to be informed on product quality concerns. Regulatory frameworks for mycorrhizal inoculants remain limited in many regions (Carrazco <i>et al</i>., <span>2024</span>; M. J. Salomon <i>et al</i>., <span>2022</span>), exacerbating challenges related to product viability and identity of mycorrhizal fungi in products. The United States fully lacks regulations on the import/export of mycorrhizal fungal products or quality control, despite the United States having a 25% share in the mycorrhizal inoculant industry, representing 249 million","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"19 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142678220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Radioisotopes can be used to quantify element fluxes in ecosystems, such as plant phosphorus uptake from soil. On the occasion of a recent publication (Lekberg <i>et al</i>., <span>2024</span>), this article briefly explains some challenges in the determination of element fluxes based on radioisotope labeling experiments along with strategies to avoid potential pitfalls. The intention of this contribution is to foster progress in the understanding of element fluxes in ecosystems based on the use of isotopes.</p><p>Radioisotopes can be used in quantitative and nonquantitative studies (for a review, see Frossard <i>et al</i>., <span>2011</span>). In nonquantitative studies, radioisotopes are often used to demonstrate that specific elements or molecules move among different compartments, for instance among cells or organs. Using this approach, it has been shown that mycorrhizal fungi transport elements from soil or a specific soil compartment to a plant. By contrast, other studies use radioisotopes to quantify the magnitude of an element flux. In these quantitative studies, the radioisotope is used as a tracer (i.e. a traceable proportion of the element in the studied system).</p><p>If an isotope is used as a tracer to quantify an element flux, rather than the flux of the tracer itself, it is essential to know the ratio of the amount of this isotope to the total amount of the element in the labeled pool (for a review see Di <i>et al</i>., <span>1997</span>). This is not a unique precondition in the use of radioisotopes. The same applies also when stable isotopes are used to trace fluxes. The difference is that radioisotopes are determined based on their radioactivity (for instance, <sup>32</sup>P activity) using scintillation counting, while stable isotopes are determined as the ratio of the added heavy isotope relative to the abundant light isotope of the element (for instance, the <sup>15</sup>N : <sup>14</sup>N ratio) using isotope ratio mass spectrometry. Thus, when using radioisotopes to trace element fluxes, it is necessary to determine not only the amount of the radioisotope (based on its radioactivity) but also the amount of the nonlabeled (or total) element in the system, in separate measurements.</p><p>If radioactive phosphorus, for instance <sup>32</sup>P, is added to a soil as phosphate, a large part of it will adsorb to soil minerals, while the remaining part will be taken up by microorganisms. The fraction of <sup>32</sup>P that remains plant-available in the soil (which can be as little as 1% of the added amount) will be strongly diluted by nonlabeled phosphorus (for a review see Bünemann, <span>2015</span>). The plant will take up the radioisotope together with nonlabeled phosphorus from the plant-available pool, and the ratio of radiophosphorus : nonlabeled phosphorus (called specific activity) that is taken up can vary strongly among soils (Fig. 1). Hence, the amount of radioisotope in the plant by itself has only limited value
{"title":"Quantifying element fluxes using radioisotopes","authors":"Marie Spohn, Wolfgang Wanek","doi":"10.1111/nph.20203","DOIUrl":"10.1111/nph.20203","url":null,"abstract":"<p>Radioisotopes can be used to quantify element fluxes in ecosystems, such as plant phosphorus uptake from soil. On the occasion of a recent publication (Lekberg <i>et al</i>., <span>2024</span>), this article briefly explains some challenges in the determination of element fluxes based on radioisotope labeling experiments along with strategies to avoid potential pitfalls. The intention of this contribution is to foster progress in the understanding of element fluxes in ecosystems based on the use of isotopes.</p><p>Radioisotopes can be used in quantitative and nonquantitative studies (for a review, see Frossard <i>et al</i>., <span>2011</span>). In nonquantitative studies, radioisotopes are often used to demonstrate that specific elements or molecules move among different compartments, for instance among cells or organs. Using this approach, it has been shown that mycorrhizal fungi transport elements from soil or a specific soil compartment to a plant. By contrast, other studies use radioisotopes to quantify the magnitude of an element flux. In these quantitative studies, the radioisotope is used as a tracer (i.e. a traceable proportion of the element in the studied system).</p><p>If an isotope is used as a tracer to quantify an element flux, rather than the flux of the tracer itself, it is essential to know the ratio of the amount of this isotope to the total amount of the element in the labeled pool (for a review see Di <i>et al</i>., <span>1997</span>). This is not a unique precondition in the use of radioisotopes. The same applies also when stable isotopes are used to trace fluxes. The difference is that radioisotopes are determined based on their radioactivity (for instance, <sup>32</sup>P activity) using scintillation counting, while stable isotopes are determined as the ratio of the added heavy isotope relative to the abundant light isotope of the element (for instance, the <sup>15</sup>N : <sup>14</sup>N ratio) using isotope ratio mass spectrometry. Thus, when using radioisotopes to trace element fluxes, it is necessary to determine not only the amount of the radioisotope (based on its radioactivity) but also the amount of the nonlabeled (or total) element in the system, in separate measurements.</p><p>If radioactive phosphorus, for instance <sup>32</sup>P, is added to a soil as phosphate, a large part of it will adsorb to soil minerals, while the remaining part will be taken up by microorganisms. The fraction of <sup>32</sup>P that remains plant-available in the soil (which can be as little as 1% of the added amount) will be strongly diluted by nonlabeled phosphorus (for a review see Bünemann, <span>2015</span>). The plant will take up the radioisotope together with nonlabeled phosphorus from the plant-available pool, and the ratio of radiophosphorus : nonlabeled phosphorus (called specific activity) that is taken up can vary strongly among soils (Fig. 1). Hence, the amount of radioisotope in the plant by itself has only limited value ","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"245 2","pages":"443-445"},"PeriodicalIF":8.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/nph.20203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引言 植物与昆虫食草动物共存和相互作用已有 4 亿年之久（Ehrlich & Raven, 1964; Labandeira & Currano, 2013），这种相互作用影响着植物性状、种群动态甚至群落稳定性的进化（Myers & Sarfraz, 2017; De-la-Cruz et al.）事实上，植物与食草动物之间的相互作用会相互影响各自的进化轨迹--食草动物对植物施加选择性压力，导致反食草防御系统的进化和多样化；反过来，对食草动物的进化反应也会改变植物与食草动物相互作用的生态条件（Agrawal 等人，2006 年）。这种生态进化反馈回路可能发生在人类介导的压力形式背景下，如与农业制度、城市化和气候变化相关的压力（Turcotte 等人，2017 年；Hamann 等人，2021 年；Santangelo 等人，2022 年）。然而，这些人类介导的压力因素如何改变植物与食草动物之间的相互作用，进而改变植物与其昆虫食草动物之间更广泛的生态进化动态，仍然是我们知识中的一大空白。化学除草剂是一种相对新颖的人类介导选择形式，用于农业生态系统控制和根除杂草植物（Shaner，2014 年）。不幸的是，植物很快就适应了除草剂的使用；迄今为止，有数百种杂草被认为对某种形式的除草剂具有抗性或耐受性（Baucom & Mauricio, 2004; Vila-Aiub 等人, 2009; Délye 等人, 2013）。大多数针对天然杂草和除草剂使用的研究都会考察植物种群中抗性或耐受性进化的某些方面--无论是关注抗性或耐受性的频率，还是防御特征的遗传基础，抑或是与除草剂防御相关的潜在适应成本（Baucom，2019 年）。考虑除草剂对杂草群落中食草昆虫或传粉昆虫等非目标生物影响的研究要少得多（Motta 等人，2018 年，2020 年）。虽然一些研究已经探讨了除草剂暴露如何直接影响昆虫的发育、适应性和免疫反应（Schneider 等人，2009 年；Baglan 等人，2018 年；Capinera，2018 年；Smith 等人，2021 年），但对除草剂间接影响的潜在可能性--即除草剂暴露会改变或改变植物的某些方面，进而影响昆虫或其他群落成员（Fuchs 等人，2021 年）--的了解却较少。这是一个明显的知识空白，因为植物化学、生理和物候会因接触除草剂而直接改变（Baucom 等人，2008 年；Londo 等人，2014 年；de Freitas-Silva 等人，2022 年）；此外，植物大小和交配系统的某些方面也会随着除草剂抗性而进化（Van Etten 等人，2016 年；Kuester 等人，2017 年）。这些变化中的每一种--无论是因接触除草剂而导致的性状变化，还是因与除草剂抗性相关的进化而导致的性状改变--都有可能干扰植物与昆虫食草动物、授粉者和其他生物之间的既定互动关系。例如，在耐草甘膦的甜菜（Beta vulgaris）中，施用草甘膦会导致食草动物桃蚜（Myzus persicae）的增加（Dewar 等人，2000 年）。同样，暴露于低剂量除草剂麦草畏（dicamba）的绒毛草（Abutilon theophrasti）显示，以韧皮部为食的银叶粉虱（Bemisia tabaci）数量增加（Johnson & Baucom, 2022）。此外，在水稻上施用四种除草剂（2,4-D、Command、Newpath、Ricebeaux）会适度但不同程度地影响消耗组织的稻水象鼻虫（Lissorhoptrus oryzophilus）的数量水平以及茎蛀甲虫造成的草食危害（Kraus & Stout，2019 年）。暴露于除草剂的植物和昆虫食草动物经历的这种食草变化的后果通常是未知的。例如，施用除草剂导致的食草动物数量增加是否会给植物种群带来比正常情况下更大的选择性压力？或者是否会导致不同类型的取食，从而可能以意想不到的方式影响植物和食草动物种群/群落的抗药性轨迹？同时，植物也有可能在防御除草剂和食草动物之间进行权衡，这可能会限制其中任一性状水平的提高（Simms &amp; Rausher, 1987）。事实上，在组成型抗食草动物防御和诱导型抗食草动物防御之间已经发现了权衡（Koricheva et al.
{"title":"Herbicidal interference: glyphosate drives both the ecology and evolution of plant–herbivore interactions","authors":"Grace M. Zhang, Regina S. Baucom","doi":"10.1111/nph.20238","DOIUrl":"10.1111/nph.20238","url":null,"abstract":"<p>\u0000 </p>","PeriodicalId":214,"journal":{"name":"New Phytologist","volume":"245 2","pages":"807-817"},"PeriodicalIF":8.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/nph.20238","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142678219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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