Pub Date : 2025-02-01DOI: 10.1016/j.pbi.2024.102670
J. Vladimir Torres-Rodríguez , Delin Li , James C. Schnable
Transcriptome-wide association studies (TWAS) complement genome-wide association studies (GWAS) by using gene expression data to link specific genes to phenotypes. This review examines 37 TWAS studies across eight plant species, evaluating the impact of methodological choices on outcomes using maize and soybean datasets. Large sample sizes and synchronized sample collection for gene expression measurement appear to significantly increase power for discovering gene-phenotype linkages, while matching tissue, stage, and environment may matter much less than previously believed, making it feasible to reuse large and well-collected expression datasets across multiple studies. The development of statistical approaches and computational tools specifically optimized for plant TWAS data will ultimately be needed, but further potential remains to adapt advances developed in GWAS to TWAS contexts.
{"title":"Evolving best practices for transcriptome-wide association studies accelerate discovery of gene-phenotype links","authors":"J. Vladimir Torres-Rodríguez , Delin Li , James C. Schnable","doi":"10.1016/j.pbi.2024.102670","DOIUrl":"10.1016/j.pbi.2024.102670","url":null,"abstract":"<div><div>Transcriptome-wide association studies (TWAS) complement genome-wide association studies (GWAS) by using gene expression data to link specific genes to phenotypes. This review examines 37 TWAS studies across eight plant species, evaluating the impact of methodological choices on outcomes using maize and soybean datasets. Large sample sizes and synchronized sample collection for gene expression measurement appear to significantly increase power for discovering gene-phenotype linkages, while matching tissue, stage, and environment may matter much less than previously believed, making it feasible to reuse large and well-collected expression datasets across multiple studies. The development of statistical approaches and computational tools specifically optimized for plant TWAS data will ultimately be needed, but further potential remains to adapt advances developed in GWAS to TWAS contexts.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"83 ","pages":"Article 102670"},"PeriodicalIF":8.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142767329","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}
Pub Date : 2025-02-01DOI: 10.1016/j.pbi.2024.102672
Serena Agnes Qiao, Ronelle Roth
Extracellular vesicles (EVs) are membrane-delimited nanoparticles found in every kingdom of life and are known to mediate cell–cell communication in animal systems through the trafficking of proteins and nucleic acids. Research into plant and microbial EVs suggests that these have similar transport capacity, and moreover are able to mediate signalling not only within an organism but also between organisms, acting between plants and their microbial partners in cross-kingdom signalling. Here, we review recent research exploring the roles of these EVs, both plant and microbial, highlighting emerging trends of functional conservation between species and across kingdoms, complemented by the heterogeneity of EV subpopulations at the organism level that places EVs as powerful regulatory mechanisms in plant biotic interactions.
{"title":"Messenger and message: Uncovering the roles, rhythm and regulation of extracellular vesicles in plant biotic interactions","authors":"Serena Agnes Qiao, Ronelle Roth","doi":"10.1016/j.pbi.2024.102672","DOIUrl":"10.1016/j.pbi.2024.102672","url":null,"abstract":"<div><div>Extracellular vesicles (EVs) are membrane-delimited nanoparticles found in every kingdom of life and are known to mediate cell–cell communication in animal systems through the trafficking of proteins and nucleic acids. Research into plant and microbial EVs suggests that these have similar transport capacity, and moreover are able to mediate signalling not only within an organism but also between organisms, acting between plants and their microbial partners in cross-kingdom signalling. Here, we review recent research exploring the roles of these EVs, both plant and microbial, highlighting emerging trends of functional conservation between species and across kingdoms, complemented by the heterogeneity of EV subpopulations at the organism level that places EVs as powerful regulatory mechanisms in plant biotic interactions.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"83 ","pages":"Article 102672"},"PeriodicalIF":8.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142902676","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}
Pub Date : 2024-11-27DOI: 10.1016/j.pbi.2024.102671
Yunfei Hu , Dan Wang , Xiaohua Zhang , Xiaodong Lv , Bo Li
Enhancing crop salt tolerance through genetics and genomics is important for food security. It is environmentally friendly and cost-effective in maintaining crop production in farmlands affected by soil salinization and can also facilitate the utilization of marginal saline land. Despite the limited success achieved so far, it is becoming possible to bridge the gap between fundamental research and crop breeding owing to a deeper understanding of plant salt tolerance at both physiological and molecular levels. Therefore, we review the recent key progress in identifying the molecular mechanisms contributing to plant salt tolerance with a focus on balancing growth and salt resilience. With the accruing knowledge and the rapidly evolving tools (e.g. genome editing and artificial intelligence), it is reasonable to expect the future salt-tolerant crops in a few decades.
{"title":"Current progress in deciphering the molecular mechanisms underlying plant salt tolerance","authors":"Yunfei Hu , Dan Wang , Xiaohua Zhang , Xiaodong Lv , Bo Li","doi":"10.1016/j.pbi.2024.102671","DOIUrl":"10.1016/j.pbi.2024.102671","url":null,"abstract":"<div><div>Enhancing crop salt tolerance through genetics and genomics is important for food security. It is environmentally friendly and cost-effective in maintaining crop production in farmlands affected by soil salinization and can also facilitate the utilization of marginal saline land. Despite the limited success achieved so far, it is becoming possible to bridge the gap between fundamental research and crop breeding owing to a deeper understanding of plant salt tolerance at both physiological and molecular levels. Therefore, we review the recent key progress in identifying the molecular mechanisms contributing to plant salt tolerance with a focus on balancing growth and salt resilience. With the accruing knowledge and the rapidly evolving tools (e.g. genome editing and artificial intelligence), it is reasonable to expect the future salt-tolerant crops in a few decades.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"83 ","pages":"Article 102671"},"PeriodicalIF":8.3,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142720488","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}
Pub Date : 2024-11-26DOI: 10.1016/j.pbi.2024.102669
Namra Ali, Shubhangi Singh, Rohini Garg
Genome editing tools could precisely and efficiently target plant genomes leading to the development of improved crops. Besides editing the coding regions, researchers can employ editing technologies to target specific gene regulatory elements or modify epigenetic marks associated with distal regulatory regions, thereby regulating gene expression in crops. This review outlines several prominent genome editing technologies, including CRISPR-Cas9, TALENs, and ZFNs and recent advancements. The applications for genome and epigenome editing especially of regulatory regions in crop plants is also discussed, including efforts to enhance abiotic stress tolerance, yield, disease resistance and plant phenotype. Additionally, the review addresses the potential of epigenetic modifications, such as DNA methylation and histone modifications, to alter gene expression for crop improvement. Finally, the limitations and future scope of utilizing various genome editing tools to manipulate regulatory elements for gene regulation to unlock the full potential of these tools in plant breeding has been discussed.
基因组编辑工具可以精确有效地针对植物基因组进行编辑，从而开发出改良作物。除了编辑编码区，研究人员还可以利用编辑技术针对特定的基因调控元件或修改与远端调控区相关的表观遗传标记，从而调控作物中的基因表达。本综述概述了几种著名的基因组编辑技术，包括 CRISPR-Cas9、TALENs 和 ZFNs 以及最新进展。还讨论了基因组和表观基因组编辑的应用，特别是作物植物中调控区的编辑，包括提高非生物胁迫耐受性、产量、抗病性和植物表型。此外，综述还探讨了表观遗传修饰（如 DNA 甲基化和组蛋白修饰）在改变基因表达以改良作物方面的潜力。最后，还讨论了利用各种基因组编辑工具操纵基因调控元件的局限性和未来范围，以充分释放这些工具在植物育种中的潜力。
{"title":"Unlocking crops’ genetic potential: Advances in genome and epigenome editing of regulatory regions","authors":"Namra Ali, Shubhangi Singh, Rohini Garg","doi":"10.1016/j.pbi.2024.102669","DOIUrl":"10.1016/j.pbi.2024.102669","url":null,"abstract":"<div><div>Genome editing tools could precisely and efficiently target plant genomes leading to the development of improved crops. Besides editing the coding regions, researchers can employ editing technologies to target specific gene regulatory elements or modify epigenetic marks associated with distal regulatory regions, thereby regulating gene expression in crops. This review outlines several prominent genome editing technologies, including CRISPR-Cas9, TALENs, and ZFNs and recent advancements. The applications for genome and epigenome editing especially of regulatory regions in crop plants is also discussed, including efforts to enhance abiotic stress tolerance, yield, disease resistance and plant phenotype. Additionally, the review addresses the potential of epigenetic modifications, such as DNA methylation and histone modifications, to alter gene expression for crop improvement. Finally, the limitations and future scope of utilizing various genome editing tools to manipulate regulatory elements for gene regulation to unlock the full potential of these tools in plant breeding has been discussed.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"83 ","pages":"Article 102669"},"PeriodicalIF":8.3,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142720489","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}
Pub Date : 2024-11-25DOI: 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.
{"title":"Engineering rice genomes towards green super rice","authors":"Jianwei Zhang , Jian Che , Yidan Ouyang","doi":"10.1016/j.pbi.2024.102664","DOIUrl":"10.1016/j.pbi.2024.102664","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"82 ","pages":"Article 102664"},"PeriodicalIF":8.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703697","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}
Pub Date : 2024-11-24DOI: 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.
{"title":"Light and high temperatures control epigenomic and epitranscriptomic events in Arabidopsis","authors":"Tianyuan Xu, Eirini Patitaki, Anna Zioutopoulou, Eirini Kaiserli","doi":"10.1016/j.pbi.2024.102668","DOIUrl":"10.1016/j.pbi.2024.102668","url":null,"abstract":"<div><div>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 <em>Arabidopsis</em> 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.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"83 ","pages":"Article 102668"},"PeriodicalIF":8.3,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699709","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}
Pub Date : 2024-11-22DOI: 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.
{"title":"The gene function prediction challenge: Large language models and knowledge graphs to the rescue","authors":"Rohan Shawn Sunil, Shan Chun Lim, Manoj Itharajula, Marek Mutwil","doi":"10.1016/j.pbi.2024.102665","DOIUrl":"10.1016/j.pbi.2024.102665","url":null,"abstract":"<div><div>Elucidating gene function is one of the ultimate goals of plant science. Despite this, only ∼15 % of all genes in the model plant <em>Arabidopsis thaliana</em> 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.</div></div>","PeriodicalId":11003,"journal":{"name":"Current opinion in plant biology","volume":"82 ","pages":"Article 102665"},"PeriodicalIF":8.3,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695162","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}
Pub Date : 2024-11-22DOI: 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.
{"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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号