Current opinion in plant biology最新文献

英文中文

Engineering rice genomes towards green super rice 改造水稻基因组，打造绿色超级稻

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-25 DOI: 10.1016/j.pbi.2024.102664

Jianwei Zhang , Jian Che , Yidan Ouyang

Rice, cultivated for millennia across diverse geographical regions, has witnessed tremendous advancements in recent decades, epitomized by the emergence of Green Super Rice. These efforts aim to address challenges such as climate change, pest and disease threats, and sustainable agriculture. Driven by the advent of multiomics big data, breakthroughs in genomic tools and resources, hybrid rice breeding techniques, and the extensive utilization of green genes, rice genomes are undergoing delicate modifications to produce varieties with high yield, superior quality, enhanced nutrient efficiency, and resilience to pests and environmental stresses, leading to the development of green agriculture in China. Additionally, the utilization of wild relatives and the promotion of genomic breeding approaches have further enriched our understanding of rice improvement. In the future, international efforts to develop next-generation green rice varieties remain both challenging and imperative for the whole community.

水稻在不同的地理区域栽培了数千年，近几十年来取得了巨大进步，绿色超级稻的出现就是一个缩影。这些努力旨在应对气候变化、病虫害威胁和可持续农业等挑战。在多组学大数据、基因组工具和资源的突破、杂交水稻育种技术以及绿色基因的广泛利用的推动下，水稻基因组正在经历微妙的改造，以培育出高产、优质、养分利用率高、抗病虫害和环境胁迫能力强的品种，从而带动中国绿色农业的发展。此外，野生近缘植物的利用和基因组育种方法的推广也进一步丰富了我们对水稻改良的认识。未来，国际社会在培育下一代绿色水稻品种方面的努力既充满挑战，又势在必行。

引用次数: 0

Light and high temperatures control epigenomic and epitranscriptomic events in Arabidopsis 光照和高温控制拟南芥的表观基因组和表观转录组事件

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-24 DOI: 10.1016/j.pbi.2024.102668

Tianyuan Xu, Eirini Patitaki, Anna Zioutopoulou, Eirini Kaiserli

Light and temperature are two key environmental factors that control plant growth and adaptation by influencing biomolecular events. This review highlights the latest milestones on the role of light and high temperatures in modulating the epigenetic and epitranscriptomic landscape of Arabidopsis to trigger developmental and adaptive responses to a changing environment. Recent discoveries on how light and high temperature signals are integrated in the nucleus to modulate gene expression are discussed, as well as highlighting research gaps and future perspectives in further understanding how to promote plant resilience in times of climate change.

光照和温度是通过影响生物分子事件来控制植物生长和适应的两个关键环境因素。本综述重点介绍了光照和高温在调节拟南芥表观遗传学和表观转录组图谱以引发对不断变化的环境的发育和适应性反应方面所起作用的最新阶段性成果。文章讨论了最近关于光照和高温信号如何在细胞核中整合以调节基因表达的发现，并强调了在进一步了解如何促进植物在气候变化时期的恢复力方面的研究差距和未来前景。

引用次数: 0

The gene function prediction challenge: Large language models and knowledge graphs to the rescue 基因功能预测挑战：大型语言模型和知识图谱的拯救。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-22 DOI: 10.1016/j.pbi.2024.102665

Rohan Shawn Sunil, Shan Chun Lim, Manoj Itharajula, Marek Mutwil

Elucidating gene function is one of the ultimate goals of plant science. Despite this, only ∼15 % of all genes in the model plant Arabidopsis thaliana have comprehensively experimentally verified functions. While bioinformatical gene function prediction approaches can guide biologists in their experimental efforts, neither the performance of the gene function prediction methods nor the number of experimental characterization of genes has increased dramatically in recent years. In this review, we will discuss the status quo and the trajectory of gene function elucidation and outline the recent advances in gene function prediction approaches. We will then discuss how recent artificial intelligence advances in large language models and knowledge graphs can be leveraged to accelerate gene function predictions and keep us updated with scientific literature.

阐明基因功能是植物科学的终极目标之一。尽管如此，在模式植物拟南芥（Arabidopsis thaliana）的所有基因中，只有 15% 的基因的功能得到了全面的实验验证。虽然生物信息学的基因功能预测方法可以指导生物学家的实验工作，但近年来基因功能预测方法的性能和基因的实验表征数量都没有显著增加。在这篇综述中，我们将讨论基因功能阐释的现状和发展轨迹，并概述基因功能预测方法的最新进展。然后，我们将讨论如何利用最近在大型语言模型和知识图谱方面取得的人工智能进展来加速基因功能预测，并让我们及时了解科学文献的最新进展。

引用次数: 0

Advancing plant single-cell genomics with foundation models 利用基础模型推进植物单细胞基因组学。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-22 DOI: 10.1016/j.pbi.2024.102666

Tran N. Chau , Xuan Wang , John M. McDowell , Song Li

Single-cell genomics, combined with advanced AI models, hold transformative potential for understanding complex biological processes in plants. This article reviews deep-learning approaches in single-cell genomics, focusing on foundation models, a type of large-scale, pretrained, multi-purpose generative AI models. We explore how these models, such as Generative Pre-trained Transformers (GPT), Bidirectional Encoder Representations from Transformers (BERT), and other Transformer-based architectures, are applied to extract meaningful biological insights from diverse single-cell datasets. These models address challenges in plant single-cell genomics, including improved cell-type annotation, gene network modeling, and multi-omics integration. Moreover, we assess the use of Generative Adversarial Networks (GANs) and diffusion models, focusing on their capacity to generate high-fidelity synthetic single-cell data, mitigate dropout events, and handle data sparsity and imbalance. Together, these AI-driven approaches hold immense potential to enhance research in plant genomics, facilitating discoveries in crop resilience, productivity, and stress adaptation.

单细胞基因组学与先进的人工智能模型相结合，为了解植物的复杂生物过程带来了变革性的潜力。本文回顾了单细胞基因组学中的深度学习方法，重点关注基础模型，这是一种大规模、预训练、多用途的生成式人工智能模型。我们探讨了这些模型，如生成预训练变换器（GPT）、变换器双向编码器表征（BERT）和其他基于变换器的架构，是如何应用于从各种单细胞数据集中提取有意义的生物学见解的。这些模型解决了植物单细胞基因组学的难题，包括改进细胞类型注释、基因网络建模和多组学整合。此外，我们还评估了生成式对抗网络（GANs）和扩散模型的使用情况，重点关注它们生成高保真合成单细胞数据、减少丢失事件以及处理数据稀疏性和不平衡性的能力。这些人工智能驱动的方法具有巨大的潜力，可以共同加强植物基因组学研究，促进作物抗逆性、生产力和胁迫适应性方面的发现。

{"title":"Advancing plant single-cell genomics with foundation models","authors":"Tran N. Chau , Xuan Wang , John M. McDowell , Song Li","doi":"10.1016/j.pbi.2024.102666","DOIUrl":"10.1016/j.pbi.2024.102666","url":null,"abstract":"<div><div>Single-cell genomics, combined with advanced AI models, hold transformative potential for understanding complex biological processes in plants. This article reviews deep-learning approaches in single-cell genomics, focusing on foundation models, a type of large-scale, pretrained, multi-purpose generative AI models. We explore how these models, such as Generative Pre-trained Transformers (GPT), Bidirectional Encoder Representations from Transformers (BERT), and other Transformer-based architectures, are applied to extract meaningful biological insights from diverse single-cell datasets. These models address challenges in plant single-cell genomics, including improved cell-type annotation, gene network modeling, and multi-omics integration. Moreover, we assess the use of Generative Adversarial Networks (GANs) and diffusion models, focusing on their capacity to generate high-fidelity synthetic single-cell data, mitigate dropout events, and handle data sparsity and imbalance. Together, these AI-driven approaches hold immense potential to enhance research in plant genomics, facilitating discoveries in crop resilience, productivity, and stress adaptation.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"82 ","pages":"Article 102666"},"PeriodicalIF":8.3,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensing host and environmental cues by fungal GPCRs 真菌 GPCR 感知宿主和环境线索。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-19 DOI: 10.1016/j.pbi.2024.102667

Cong Jiang , Aliang Xia , Daiying Xu , Jin-Rong Xu

G protein-coupled receptors (GPCRs) represent the largest superfamily of cell surface membrane receptors in eukaryotes. Unlike plants, fungi do not have receptor kinases or receptor-like kinases. Instead, GPCRs play critical roles in fungi to sense signals crucial for their survival and interspecies interactions to activate downstream cAMP and mitogen-activated protein kinase pathways via heterotrimeric G proteins. Some fungal GPCRs have relatively conserved roles in nutrient sensing and pheromone recognition to facilitate growth and sexual reproduction. For fungal pathogens with expanded families of classical or fungal-specific GPCRs, including those with the CFEM (common in fungal extracellular membrane) domain, distinctive GPCRs are involved in recognizing different signals from their hosts and surroundings. Although only a few ligands recognized by fungal GPCRs have been identified, recent studies have advanced our knowledge of GPCR biology in plant pathogenic and nematode-trapping fungi.

G 蛋白偶联受体（GPCR）是真核生物中最大的细胞表面膜受体超家族。与植物不同，真菌没有受体激酶或类似受体的激酶。相反，GPCR 在真菌中发挥着关键作用，它们能感知对真菌生存和种间相互作用至关重要的信号，并通过异三聚 G 蛋白激活下游 cAMP 和有丝分裂原激活蛋白激酶通路。一些真菌 GPCR 在营养传感和信息素识别方面具有相对保守的作用，可促进生长和有性生殖。对于经典或真菌特异性 GPCR 家族扩大的真菌病原体，包括具有 CFEM（真菌胞外膜常见）结构域的真菌病原体，独特的 GPCR 参与识别来自宿主和周围环境的不同信号。虽然真菌 GPCR 识别的配体为数不多，但最近的研究增进了我们对植物致病真菌和线虫诱捕真菌 GPCR 生物学的了解。

引用次数: 0

Grass awns: Morphological diversity arising from developmental constraint 禾本科植物的芒：发育限制带来的形态多样性。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-16 DOI: 10.1016/j.pbi.2024.102663

Annis Richardson , Heather Jones , Madelaine Bartlett

Grasses dominate agriculturally and ecologically. One hypothesized driver of this dominance is grasses' facility for grain dispersal and rapid seedling establishment. Dispersal and establishment are aided by the awned lemma - a modified bract associated with grass flowers. Awns have diverse forms, many proposed functions, and have been gained and lost repeatedly in grass evolution. Here we hypothesize that the evolution of awn emergence is underpinned by deep conservation of developmental genes. Awns are likely homologous to leaf blades. Because leaf blades are essential, every grass species likely has a latent developmental program available for awn development. This developmental program may be repeatedly reactivated in lemmas, resulting in the frequent appearance of awns. Because awns are inessential, they can be lost and modified without dire consequences to fitness, resulting in the frequent loss and diversity of awns. Replicated awn evolution reveals how developmental conservation can potentiate the evolution of diversity. Awns also present a powerful opportunity to dissect mechanisms of leaf development.

禾本科植物在农业和生态学上都占主导地位。据推测，禾本科植物之所以占据主导地位，是因为它们具有传播谷物和快速育苗的能力。芒状外稃--一种与禾本科植物花朵相关的改良苞片--有助于禾本科植物的传播和成苗。芒的形式多种多样，功能也多种多样，并在禾本科植物的进化过程中反复增减。在这里，我们假设芒的出现是由发育基因的深度保护所支撑的。芒很可能与叶片同源。由于叶片是必不可少的，因此每个草种都可能有一个潜在的发育程序，可用于芒的发育。这种发育程序可能会在外稃中反复重新激活，从而导致芒的频繁出现。由于芒是非必需的，因此可以丢失和修改，而不会对适应性造成严重后果，从而导致芒的频繁丢失和多样性。芒的重复进化揭示了发育保护是如何促进多样性进化的。芒还提供了一个剖析叶片发育机制的绝佳机会。

{"title":"Grass awns: Morphological diversity arising from developmental constraint","authors":"Annis Richardson , Heather Jones , Madelaine Bartlett","doi":"10.1016/j.pbi.2024.102663","DOIUrl":"10.1016/j.pbi.2024.102663","url":null,"abstract":"<div><div>Grasses dominate agriculturally and ecologically. One hypothesized driver of this dominance is grasses' facility for grain dispersal and rapid seedling establishment. Dispersal and establishment are aided by the awned lemma - a modified bract associated with grass flowers. Awns have diverse forms, many proposed functions, and have been gained and lost repeatedly in grass evolution. Here we hypothesize that the evolution of awn emergence is underpinned by deep conservation of developmental genes. Awns are likely homologous to leaf blades. Because leaf blades are essential, every grass species likely has a latent developmental program available for awn development. This developmental program may be repeatedly reactivated in lemmas, resulting in the frequent appearance of awns. Because awns are inessential, they can be lost and modified without dire consequences to fitness, resulting in the frequent loss and diversity of awns. Replicated awn evolution reveals how developmental conservation can potentiate the evolution of diversity. Awns also present a powerful opportunity to dissect mechanisms of leaf development.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"82 ","pages":"Article 102663"},"PeriodicalIF":8.3,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

New perspectives of post-GWAS analyses: From markers to causal genes for more precise crop breeding GWAS 后分析的新视角：从标记到因果基因，实现更精确的作物育种。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-15 DOI: 10.1016/j.pbi.2024.102658

Ivana Kaňovská, Jana Biová, Mária Škrabišová

Crop breeding advancement is hindered by the imperfection of methods to reveal genes underlying key traits. Genome-wide Association Study (GWAS) is one such method, identifying genomic regions linked to phenotypes. Post-GWAS analyses predict candidate genes and assist in causative mutation (CM) recognition. Here, we assess post-GWAS approaches, address limitations in omics data integration and stress the importance of evaluating associated variants within a broader context of publicly available datasets. Recent advances in bioinformatics tools and genomic strategies for CM identification and allelic variation exploration are reviewed. We discuss the role of markers and marker panel development for more precise breeding. Finally, we highlight the perspectives and challenges of GWAS-based CM prediction for complex quantitative traits.

由于揭示关键性状基因的方法不完善，农作物育种的进展受到阻碍。全基因组关联研究（GWAS）就是这样一种方法，它能确定与表型相关的基因组区域。全基因组关联研究（GWAS）后分析可预测候选基因，并帮助识别致病突变（CM）。在此，我们将评估后GWAS方法，解决omics数据整合的局限性，并强调在更广泛的公开数据集背景下评估相关变异的重要性。我们回顾了用于 CM 鉴定和等位基因变异探索的生物信息学工具和基因组策略的最新进展。我们还讨论了标记的作用以及为实现更精确育种而进行的标记组开发。最后，我们强调了基于 GWAS 的复杂数量性状 CM 预测的前景和挑战。

引用次数: 0

Beat the heat: Breeding, genomics, and gene editing for high nighttime temperature tolerance in rice 战胜高温利用育种、基因组学和基因编辑技术提高水稻对夜间高温的耐受性。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-14 DOI: 10.1016/j.pbi.2024.102659

Vibha Srivastava, Christian De Guzman, Samuel B. Fernandes

High nighttime temperature (HNT) is a major obstacle in rice production worldwide. It severely impacts spikelet fertility and induces grain chalk, the two undesirable factors leading to yield and quality decline in rice. Recently, major efforts have been undertaken to understand the genetic mechanisms underlying HNT tolerance. Here, we highlight phenotypic diversity and recent studies on breeding, genomics, and gene editing targeting this trait. These studies point to the challenges in the process as HNT tolerance has so far been found only in non-adapted varieties, and no known modern cultivar bred in the United States is able to withstand exposure to HNT during the reproductive stage. At the same time, identification of the tolerant genotypes enabled genomics, opened up tortuous but promising approaches for breeding, and showed a path for gene editing towards HNT tolerance. The recent advances have set a strong foundation for addressing this current and looming threat.

夜间高温（HNT）是全球水稻生产的一个主要障碍。它严重影响小穗的结实率，并诱发谷粒垩白，这两个不良因素导致水稻产量和品质下降。最近，人们开始努力了解水稻耐受 HNT 的遗传机制。在此，我们将重点介绍表型多样性以及针对这一性状的育种、基因组学和基因编辑方面的最新研究。这些研究指出了这一过程中的挑战，因为迄今为止只在非适应性品种中发现了 HNT 耐受性，而且在美国培育的已知现代栽培品种中，没有一个能在生殖阶段耐受 HNT 暴露。与此同时，耐受性基因型的鉴定促成了基因组学的发展，为育种开辟了曲折但充满希望的途径，并为基因编辑走向耐受 HNT 的道路指明了方向。最近取得的进展为解决目前这一迫在眉睫的威胁奠定了坚实的基础。

引用次数: 0

Gene regulatory networks in abiotic stress responses via single-cell sequencing and spatial technologies: Advances and opportunities 通过单细胞测序和空间技术研究非生物胁迫反应中的基因调控网络：进展与机遇。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-13 DOI: 10.1016/j.pbi.2024.102662

Mukesh Jain

Understanding intricate gene regulatory networks (GRNs) orchestrating responses to abiotic stresses is crucial for enhancing climate resilience in crop plants. Recent advancements in single-cell and spatial technologies have revolutionized our ability to dissect the GRNs at unprecedented resolution. Here, we explore the progress, challenges, and opportunities these state-of-the-art technologies offer in delineating the cellular intricacies of plant responses to abiotic stress. Using scRNA-seq, the transcriptome landscape of individual plant cells along with their lineages and regulatory interactions can be unraveled. Moreover, coupling scRNA-seq with spatial transcriptomics provides spatially resolved gene expression and insights into cell-to-cell interactions. In addition, the chromatin accessibility assays can discover the regulatory regions governing abiotic stress responses. An integrated multi-omics approach can facilitate discovery of cell-type-specific GRNs to reveal the key components that coordinate adaptive responses to different stresses. These potential regulatory factors can be harnessed for genetic engineering to enhance stress resilience in crop plants.

了解协调非生物胁迫反应的复杂基因调控网络（GRN）对于提高作物植物的气候适应能力至关重要。单细胞和空间技术的最新进展彻底改变了我们以前所未有的分辨率剖析基因调控网络的能力。在此，我们将探讨这些先进技术在描述植物对非生物胁迫的复杂细胞反应方面所取得的进展、面临的挑战和带来的机遇。利用 scRNA-seq，可以揭示单个植物细胞的转录组图谱及其谱系和调控相互作用。此外，scRNA-seq 与空间转录组学的结合可提供空间解析的基因表达，并深入了解细胞间的相互作用。此外，染色质可及性测定还能发现非生物胁迫反应的调控区域。综合多组学方法有助于发现细胞类型特异性 GRN，揭示协调对不同胁迫的适应性反应的关键成分。这些潜在的调控因子可用于基因工程，以提高作物的抗逆性。

{"title":"Gene regulatory networks in abiotic stress responses via single-cell sequencing and spatial technologies: Advances and opportunities","authors":"Mukesh Jain","doi":"10.1016/j.pbi.2024.102662","DOIUrl":"10.1016/j.pbi.2024.102662","url":null,"abstract":"<div><div>Understanding intricate gene regulatory networks (GRNs) orchestrating responses to abiotic stresses is crucial for enhancing climate resilience in crop plants. Recent advancements in single-cell and spatial technologies have revolutionized our ability to dissect the GRNs at unprecedented resolution. Here, we explore the progress, challenges, and opportunities these state-of-the-art technologies offer in delineating the cellular intricacies of plant responses to abiotic stress. Using scRNA-seq, the transcriptome landscape of individual plant cells along with their lineages and regulatory interactions can be unraveled. Moreover, coupling scRNA-seq with spatial transcriptomics provides spatially resolved gene expression and insights into cell-to-cell interactions. In addition, the chromatin accessibility assays can discover the regulatory regions governing abiotic stress responses. An integrated multi-omics approach can facilitate discovery of cell-type-specific GRNs to reveal the key components that coordinate adaptive responses to different stresses. These potential regulatory factors can be harnessed for genetic engineering to enhance stress resilience in crop plants.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"82 ","pages":"Article 102662"},"PeriodicalIF":8.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The root extracellular trap; a complex and dynamic biomatrix network essential for plant protection 根细胞外捕获器；一个复杂而动态的生物基质网络，对植物保护至关重要。

IF 8.3 2区生物学 Q1 PLANT SCIENCES

Current opinion in plant biology

Pub Date : 2024-11-12 DOI: 10.1016/j.pbi.2024.102656

Azeddine Driouich , Marie-Laure Follet Gueye , Maïté Vicré , John P. Moore

Plants have evolved a number of defense mechanisms to protect themselves against biotic stresses. Each cell, tissue, and organ is able to perceive and fight off attackers using a combination of chemical and physical defense mechanisms. Root cells employ similar defense response patterning. They develop immune responses upon pathogen attack and release a variety of compounds able to defend the root proper as well as the entire plant body. Currently, one of the most effective mechanisms of root defense involves the root extracellular trap (RET) that is produced at the tip of the root. The RET consists of root cap–derived cells embedded in mucilaginous secretions containing cell wall–derived polysaccharides, defense-related (glyco)proteins, phytoalexins, histones, and extracellular DNA (eDNA). The RET network plays a central role in root immunity and fulfills biological functions similar to those performed by neutrophil extracellular traps in mammals.

植物进化出了许多防御机制来保护自己免受生物压力。每个细胞、组织和器官都能通过化学和物理防御机制的组合来感知和击退攻击者。根细胞也采用类似的防御反应模式。它们在受到病原体攻击时会产生免疫反应，并释放出多种化合物来保护根部和整个植物体。目前，最有效的根系防御机制之一是在根尖产生的根细胞外捕获物（RET）。RET 由根帽衍生细胞组成，内嵌粘液分泌物，其中含有细胞壁衍生多糖、防御相关（糖）蛋白、植物毒素、组蛋白和细胞外 DNA（eDNA）。RET 网络在根系免疫中发挥着核心作用，其生物功能与哺乳动物中性粒细胞胞外捕获器的功能类似。

引用次数: 0

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Current opinion in plant biology

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀