aBIOTECH最新文献

{"title":"<i>GmWOX1</i> regulates the mediolateral polarity of compound leaves in soybean.","authors":"Xuan Zhou, Dan Wang, Dongfa Wang, Mingzhu Sun, Shuifen Huang, Jing Yang, Xiaomin Ji, Weiyue Zhao, Jianghua Chen","doi":"10.1016/j.abiote.2025.100011","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100011","url":null,"abstract":"<p><p>The morphology of soybean (<i>Glycine max</i>) leaves is a key agricultural trait that determines the planting density and photosynthetic efficiency. In soybean-producing regions of Northern China, narrow-leaf varieties carrying loss-of-function mutations in the ​<i>Ln</i> ​gene are widely cultivated and have been incorporated into breeding programs, as the narrow-leaf trait enhances light-use efficiency under high-density planting conditions. However, the molecular mechanism underlying mediolateral axis development of soybean leaf is largely unknown. The WUSCHEL-RELATED HOMEOBOX transcription factor WOX1 plays a key role in mediolateral leaf development. Here, we identified four <i>WOX1</i> homologs in soybean and determined that <i>GmWOX1a</i> and <i>GmWOX1b</i> are specifically and highly expressed in the middle domain of the leaf primordium. Heterologous expression of <i>GmWOX1a</i> fully complemented the leaf defects of the <i>Nicotiana sylvestris lam1</i> mutant. <i>Gmwox1acd</i> and <i>Gmwox1bcd</i> triple mutant produced by gene editing exhibited narrow leaves and developmental abnormalities. However, <i>Gmwox1a, Gmwox1b,</i> and <i>Gmwox1cd</i> displayed no visibly altered phenotypes, suggesting functional redundancy among the <i>WOX1</i> homologs. These findings demonstrate that the four <i>WOX1</i> homologs redundantly regulate mediolateral axis development in soybean leaves, providing a basis for future studies on leaf morphology and soybean breeding.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100011"},"PeriodicalIF":5.0,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High levels of ADAR overexpression induce abundant and stochastic off-target RNA editing in rice protoplasts.","authors":"Shuai Yin, Shumin Li, Yang Yuan, Kabin Xie","doi":"10.1016/j.abiote.2025.100007","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100007","url":null,"abstract":"<p><p>Adenosine deaminase acting on RNA (ADAR) mediates adenosine-to-inosine (A-to-I) conversions, with its deaminase domain (ADARdd) acting as a core component of targeted RNA editing. However, the off-target effects of ADARdd remain poorly characterized in plants. Here, we demonstrate that high-level overexpression of ADARdd induces widespread off-target editing in rice protoplasts, an effect not observed in stable transgenic lines. From six biological replicates of ADARdd-overexpressing protoplasts, we identified 2794 off-target editing sites (OFTEs). These OFTEs exhibited stochastic distribution across mRNAs and low editing efficiency (20-40 %), contrasting sharply with the high-confidence editing sites in OsDRB1-ADARdd stable lines. We further identify risky endogenous promoters and establish an empirical expression threshold for ADARdd to minimize off-target editing. Our findings highlight that controlled ADARdd expression is essential for reliable RNA editing in plants, providing valuable guidance for enhancing the precision of plant RNA editing experiments.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100007"},"PeriodicalIF":5.0,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973391/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: FHBDSR-Net: automated measurement of diseased spikelet rate of Fusarium Head Blight on wheat spikes","authors":"Ze Wu,&nbsp;Haowei Zhao,&nbsp;Zeyu Chen,&nbsp;Yongqiang Suo,&nbsp;Seena Joseph,&nbsp;Xiaohui Yuan,&nbsp;Caixia Lan,&nbsp;Weizhen Liu","doi":"10.1007/s42994-025-00250-3","DOIUrl":"10.1007/s42994-025-00250-3","url":null,"abstract":"","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 4","pages":"831 - 831"},"PeriodicalIF":5.0,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42994-025-00250-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145595209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APTES: a high-throughput deep learning–based Arabidopsis phenotypic trait estimation system for individual leaves and siliques","authors":"Ruifang Zhai,&nbsp;Ning Tang,&nbsp;Zhi Liu,&nbsp;Sha Tao,&nbsp;Yupu Huang,&nbsp;Xue Jiang,&nbsp;Aobo Du,&nbsp;Jiashi Wang,&nbsp;Tao Luo,&nbsp;Jinbao Liu,&nbsp;Gina A. Garzon-Martınez,&nbsp;Fiona M. K. Corke,&nbsp;John H. Doonan,&nbsp;Wanneng Yang","doi":"10.1007/s42994-025-00239-y","DOIUrl":"10.1007/s42994-025-00239-y","url":null,"abstract":"<div><p>High-throughput phenotyping of growth kinetics and organ size in the model plant <i>Arabidopsis thaliana</i> requires rapid and precise methods for trait estimation. To address this need, we developed the Arabidopsis Phenotypic Trait Estimation System, APTES, an open-access, high-throughput program that uses computer vision and deep learning to extract 64 leaf traits and 64 silique traits from photographs. The enhanced segmentation model Cascade Mask Region-based Convolutional Neural Network (Mask R-CNN) achieved precision (measure of positive prediction accuracy), recall (sensitivity in detection), and F1 score values (harmonic mean of precision and recall) of 0.965, 0.958, and 0.961, respectively, for individual leaf segmentation. These metrics demonstrated a consistent improvement of approximately 1 percentage point over the baseline model. For silique segmentation, our enhanced DetectoRS model for silique segmentation attained precision, recall, and F1 scores of 0.954, 0.930, and 0.942, respectively. Notably, precision increased by 1%, while the F1 score improved by 2 percentage points. Trait parameters were automatically calculated with coefficient of determination values for leaf and silique traits ranging from 0.776 to 0.976 and mean absolute percentage error values from 1.89% to 7.90%. We phenotyped 166 Arabidopsis accessions, using APTES, and subjected the resulting values to a genome-wide association study (GWAS), revealing 1,042 single-nucleotide polymorphisms (SNPs) as being significantly associated with 18 leaf and silique traits, and one significant SNP on chromosome 3 linked to silique number. Furthermore, we validated APTES across other public Arabidopsis databases and other plant species, with segmentation results demonstrating its applicability across diverse datasets. In conclusion, APTES is a valuable automated tool for leaf and silique segmentation and trait estimation, which should offer benefits to the broader plant science community.</p></div>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 4","pages":"744 - 762"},"PeriodicalIF":5.0,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42994-025-00239-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145595152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-transcriptional gene regulation in plants.","authors":"Mengshi Wu, Danling Zhu, Zhe Wu","doi":"10.1016/j.abiote.2025.100006","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100006","url":null,"abstract":"<p><p>The essence of life lies in the precise regulation of genetic information flow, namely, the central dogma, with gene transcription playing a pivotal role as the starting point. For a living cell, it is not only essential via transcription to synthesize the RNA but also to ensure its timely processing, packaging, and sorting, thereby determining its distinct fate, such as nuclear retention, export, translation, or degradation. Initially observed in yeast and animals, and more recently in plants, a large amount of evidence indicates that RNA processing and protein-RNA packaging occur largely concomitantly with transcription, a phenomenon known as co-transcriptional gene regulation. Increasing evidence suggests that this mechanism provides extensive regulatory potential for gene expression. It not only ensures timely RNA processing, thus determining the fate of RNA, but may also influence the transcription dynamics of RNA polymerase II (Pol II) and the chromatin environment. In this review, we highlight recent advances in understanding co-transcriptional gene regulation in the model plant <i>Arabidopsis thaliana</i>, focusing on Pol II dynamics post-initiation and their interplay with RNA-processing events such as capping, splicing, 3' end processing, protein-RNA interactions, and RNA fate determination. By comparing these findings with progress in other model systems, we discuss the unique characteristics of co-transcriptional gene regulation in plants and its potential biological significance. Additionally, we introduce recent key discoveries at the <i>FLOWERING LOCUS C</i> (<i>FLC</i>) gene under warm conditions, which exemplify how co-transcriptional RNA processing influences the chromatin environment and leads to long-term regulatory impacts. Finally, we provide perspectives on yet-unanswered key questions related to co-transcriptional gene regulation in plants.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100006"},"PeriodicalIF":5.0,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plant base editing: a decade of progress and future applications.","authors":"Ruixiang Zhang, Zhiye Zheng, Guangzhou Li, Xinglei Zheng, Liying Su, Xudong Yuan, Tie Li, Jiantao Tan, Dongchang Zeng, Shaocun Zhang, Jialin Liu, Haochun Shen, Nan Chai, Yao-Guang Liu, Qinlong Zhu","doi":"10.1016/j.abiote.2025.100003","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100003","url":null,"abstract":"<p><p>Base editors derived from clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) systems are widely used for genomic studies in both plants and animals. The broad applicability and safety of base-editing approaches have garnered considerable attention from the research community, and there could be ways to further enhance targeting efficiency and target window range. However, the complex classification and diverse functionalities of base editors pose challenges to their effective utilization and improvement. In this review, we discuss technical principles characterizing various types of base editors, including cytosine base editors (CBEs), adenine base editors (ABEs), dual base editors (DBEs), thymine base editors (TBEs), and guanine base editors (GBEs), among others, which employ distinct mechanisms and DNA repair pathways. We also describe current optimization strategies to assist researchers in improving the deployment of these tools under specific conditions. Finally, we comprehensively analyze the practical applications and advantages of base editors, offering a clear view of their development, their previous and potential applications, and how to select the appropriate tools for specific purposes.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100003"},"PeriodicalIF":5.0,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing artificial intelligence to decode the rhizosphere microbiome.","authors":"Juan Ma, Jiangfang Qiao, Yanyong Cao, Zeqiang Cheng","doi":"10.1016/j.abiote.2025.100005","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100005","url":null,"abstract":"<p><p>The rhizosphere microbiome plays crucial roles in plant health by regulating nutrient cycling and enhancing stress resilience. However, due to its complexity, the rhizosphere microbiome is quite challenging to analyze using conventional approaches. Recent advances in artificial intelligence (AI) offer unprecedented opportunities to decipher intricate microbial interactions and leverage their potential for crop breeding. In this review, we assess AI methodologies derived from human microbiome studies that address foundational data challenges, including high dimensionality, compositionality, and sparsity. Next, we examine the uses of these methods for the functional prediction of microbial traits. We then shift our focus to the rhizosphere, exploring AI-driven approaches for predictive modeling of rhizosphere dynamics, integrating plant phenotypic and microbiome data, and designing synthetic microbial communities (SynComs). Finally, we discuss the major challenges and future prospects of using AI in rhizosphere microbiome research. Specifically, we propose an emerging AI paradigm that integrates complementary inside-out (hologenome-based genomic selection) and outside-in (SynCom design) strategies, powered by transformative technologies such as federated learning, large language models, digital twins, and autonomous AI agents. This review underscores the potential for AI to revolutionize microbiome science and crop improvement.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100005"},"PeriodicalIF":5.0,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances and applications in sequencing-based pathogen surveillance.","authors":"Hao Luo, Yao Wang, Huiyu Hou, Junbo Yang, Yong-Xin Liu","doi":"10.1016/j.abiote.2025.100004","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100004","url":null,"abstract":"<p><p>The ongoing emergence of infectious diseases necessitates cutting-edge diagnostic methodologies. Traditional diagnostic methods are constrained by limited range, lengthy processing times, and inadequate sensitivity. High-throughput sequencing technologies, particularly multiplex polymerase chain reaction (PCR)-based targeted sequencing, have emerged as transformative tools for pathogen detection, offering enhanced sensitivity, specificity, and cost efficiency. However, challenges in primer design, such as dimerization and bias, limit the effectiveness of these approaches. This review explores advances in sequencing technologies, emphasizing the roles of culturomics, metagenomics, and metatranscriptomics in pathogen discovery. We spotlight innovative strategies for error-tolerant primer design that address existing limitations by balancing coverage and specificity, thereby optimizing the multiplex PCR process. Furthermore, integration of artificial intelligence enhances the precision and scalability of sequencing, enabling real-time diagnostics. Collectively, these advances offer promising pathways to bolster global health, food security, and ecological resilience through robust and sustainable pathogen-detection systems.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100004"},"PeriodicalIF":5.0,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NLRSeek: A reannotation-based pipeline for mining missing NLR genes in sequenced genomes.","authors":"Mengda Wang, Xiaowei Fu, Li Yin, Yi Zhao, Qingjie Yang, Xuteng Ye, Jun Cheng, Daolong Dou, Jinding Liu, Gan Ai","doi":"10.1016/j.abiote.2025.100001","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100001","url":null,"abstract":"<p><p>Nucleotide-binding leucine-rich repeat (NLR) proteins function as receptors and signaling factors in plant immune systems. Identifying the genes encoding NLR proteins in genomic sequences provides crucial information for breeding disease-resistant crops. However, NLR proteins are frequently misannotated during automated proteome prediction and downstream identification tools that rely on proteomic data struggle to recover these missing NLRs. To address this problem, we developed NLRSeek (https://github.com/Wang-Mengda/NLRSeek), a genome reannotation-based pipeline for NLR identification. This workflow integrates <i>de novo</i> detection of NLR loci at the genome level with targeted genome reannotation, systematically reconciling these results with existing annotations to produce a comprehensive set of NLR predictions. Our pipeline identified a larger number of NLRs than other NLR annotation tools: even in the well-annotated model plant <i>Arabidopsis thaliana</i>, NLRSeek identified a previously unannotated NLR gene whose expression and translation were confirmed by transcriptome and ribosome-profiling data. The NLRSeek pipeline showed particularly strong performance for non-model species with incomplete annotations. For example, in the yam species <i>Dioscorea zingiberensis</i>, <i>Dioscorea tokoro</i>, and <i>Dioscorea dumetorum</i>, NLRSeek identified 33.8 ​%-127.5 ​% more NLR genes than conventional methods. Importantly, 45.1 ​% of the newly annotated NLRs exhibited detectable expression, suggesting that they are true genes that were previously overlooked. Analysis of the newly identified sequences revealed that NLRs have undergone expansion in <i>D. zingiberensis</i> through tandem duplication, an insight that was not attainable using previous NLR annotation tools. Our novel NLR identification pipeline may reveal untapped genetic resources for engineering disease-resistant crops.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100001"},"PeriodicalIF":5.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection technologies for RNA modifications and their applications in plants.","authors":"Jiayin Du, WingTing Cheung, Lixing Zhang, Pingxian Zhang, Guanqun Wang","doi":"10.1016/j.abiote.2025.100002","DOIUrl":"https://doi.org/10.1016/j.abiote.2025.100002","url":null,"abstract":"<p><p>Chemical modifications of RNA molecules play diverse regulatory roles in gene expression by influencing RNA biogenesis, stability, and translation. Emerging evidence indicates that RNA modifications in plants have functional significance for enhancing crop performance, stress resistance, and agricultural productivity. Recent advances in quantitative mapping of RNA modifications at the single-base level have highlighted the critical roles of RNA modifications in regulating RNA metabolism and translation in mammals. However, our understanding of the regulatory roles of these chemical modifications at the single-base level remains limited in plants, hindering deeper insights into their biological significance. This gap can be attributed to the limited use of advanced base-resolution detection technologies in plant research. Here, we systematically review both conventional and base-resolution methods that have been used to detect RNA modifications in mammals and plants. We highlight the implications of RNA modifications at the single-base level, and discuss how modification levels could be manipulated during crop improvement and breeding to regulate RNA metabolism and translation without altering amino acid sequences.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"7 1","pages":"100002"},"PeriodicalIF":5.0,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12973405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}