A dominant negative mutation of GhMYB25-like alters cotton fiber initiation, reducing lint and fuzz.

Cotton (Gossypium hirsutum) fibers, vital natural textile materials, are single-cell trichomes that differentiate from the ovule epidermis. These fibers are categorized as lint (longer fibers useful for spinning) or fuzz (shorter, less useful fibers). Currently, developing cotton varieties with high lint yield but without fuzz remains challenging due to our limited knowledge of the molecular mechanisms underlying fiber initiation. This study presents the identification and characterization of a naturally occurring dominant negative mutation GhMYB25-like_AthapT, which results in a reduced lint and fuzzless phenotype. The GhMYB25-like_AthapT protein exerts its dominant negative effect by suppressing the activity of GhMYB25-like during lint and fuzz initiation. Intriguingly, the negative effect of GhMYB25-like_AthapT could be alleviated by high expression levels of GhMYB25-like. We also uncovered the role of GhMYB25-like in regulating the expression of key genes such as GhPDF2 (PROTODERMAL FACTOR 2), CYCD3; 1 (CYCLIN D3; 1) and PLD (Phospholipase D), establishing its significance as a pivotal transcription factor in fiber initiation. We identified other genes within this regulatory network, expanding our understanding of the determinants of fiber cell fate. These findings offer valuable insights for cotton breeding and contribute to our fundamental understanding of fiber development.

Multimodal deep learning approaches for single-cell multi-omics data integration.

Integrating single-cell multi-omics data is a challenging task that has led to new insights into complex cellular systems. Various computational methods have been proposed to effectively integrate these rapidly accumulating datasets, including deep learning. However, despite the proven success of deep learning in integrating multi-omics data and its better performance over classical computational methods, there has been no systematic study of its application to single-cell multi-omics data integration. To fill this gap, we conducted a literature review to explore the use of multimodal deep learning techniques in single-cell multi-omics data integration, taking into account recent studies from multiple perspectives. Specifically, we first summarized different modalities found in single-cell multi-omics data. We then reviewed current deep learning techniques for processing multimodal data and categorized deep learning-based integration methods for single-cell multi-omics data according to data modality, deep learning architecture, fusion strategy, key tasks and downstream analysis. Finally, we provided insights into using these deep learning models to integrate multi-omics data and better understand single-cell biological mechanisms.

Heterogeneous Analysis of Extracellular Vesicles for Osteosarcoma Diagnosis.

Osteosarcoma (OS) is the most prevalent primary tumor of bones, often diagnosed late with a poor prognosis. Currently, few effective biomarkers or diagnostic methods have been developed for early OS detection with high confidence, especially for metastatic OS. Tumor-derived extracellular vesicles (EVs) are emerging as promising biomarkers for early cancer diagnosis through liquid biopsy. Here, we report a plasmonic imaging-based biosensing technique, termed subpopulation protein analysis by single EV counting (SPASEC), for size-dependent EV subpopulation analysis. In our SPASEC platform, EVs are accurately sized and counted on plasmonic sensor chips coated with OS-specific antibodies. Subsequently, EVs are categorized into distinct subpopulations based on their sizes, and the membrane proteins of each size-dependent subpopulation are profiled. We measured the heterogeneous expression levels of the EV markers (CD63, BMP2, GD2, and N-cadherin) in each of the EV subsets from both OS cell lines and clinical plasma samples. Using the linear discriminant analysis (LDA) model, the combination of four markers is applied to classify the healthy donors (n = 37), nonmetastatic OS patients (n = 13), and metastatic patients (n = 12) with an area under the curve of 0.95, 0.92, and 0.99, respectively. SPASEC provides accurate EV sensing technology for early OS diagnosis.

Survey of prothioconazole sensitivity in Fusarium pseudograminearum isolates from Henan Province, China, and characterization of resistant laboratory mutants.

BACKGROUND: Fusarium crown rot (FCR) is one of the most significant diseases limiting crop production in the Huanghuai wheat-growing region of China. Prothioconazole, a triazole sterol 14α-demethylation inhibitor (DMI) fungicide developed by the Bayer Crop Protection Company, is mainly registered for the prevention and control of wheat powdery mildew and stripe rust (China Pesticide Information Network). It is known to exhibit high activity against F. pseudograminearum, but further research, particularly regarding the potential for fungicide resistance, is required before it can be registered for the control of FCR in China. RESULTS: The current study found that the baseline sensitivity of 67 field isolates of F. pseudograminearum collected between 2019 and 2021 ranged between 0.016-2.974 µg/mL, with an average EC50 value of 1.191 ± 0.720 µg/mL (mean ± SD). Although none of the field isolates exhibited signs of resistance, three highly resistant mutants were produced by repeated exposure to prothioconazole under laboratory conditions. All of the mutants were found to exhibit significantly reduced growth rates on potato dextrose agar (PDA), as well as reduced levels of sporulation, which indicated that there was a fitness cost associated with the resistance. However, inoculation of wounded wheat coleoptiles revealed that the pathogenicity of the resistant mutants was little affected or actually increased. Molecular analysis of the genes corresponding to the prothioconazole target protein, FpCYP51 (FpCYP51A, FpCYP51B, and FpCYP51C), indicated that the resistant mutants contained three conserved substitutions (M63I, A205S, and I246V) that were present in the FpCYP51C sequence of all three mutants, as well as several non-conserved substations in their FpCYP51A and FpCYP51B sequences. Expression analysis revealed that the presence of prothioconazole (0.1 µg/mL) generally resulted in reduced expression of the three FpCYP51 genes, but that the three mutants exhibited more complex patterns of expression that differed in comparison to their parental isolates. The study found no evidence of cross-resistance between prothioconazole and any of the fungicides tested including three DMI fungicides tebuconazole, prochloraz, and flutriafol. CONCLUSIONS: Taken together these results not only provide new insight into the resistant mechanism and biological characteristics associated with prothioconazole resistance in F. pseudograminearum, but also strong evidence that prothioconazole could provide effective and sustained control of FCR, especially when applied in combination with other fungicides.

The complex hexaploid oil-Camellia genome traces back its phylogenomic history and multi-omics analysis of Camellia oil biosynthesis.

Oil-Camellia (Camellia oleifera), belonging to the Theaceae family Camellia, is an important woody edible oil tree species. The Camellia oil in its mature seed kernels, mainly consists of more than 90% unsaturated fatty acids, tea polyphenols, flavonoids, squalene and other active substances, which is one of the best quality edible vegetable oils in the world. However, genetic research and molecular breeding on oil-Camellia are challenging due to its complex genetic background. Here, we successfully report a chromosome-scale genome assembly for a hexaploid oil-Camellia cultivar Changlin40. This assembly contains 8.80 Gb genomic sequences with scaffold N50 of 180.0 Mb and 45 pseudochromosomes comprising 15 homologous groups with three members each, which contain 135 868 genes with an average length of 3936 bp. Referring to the diploid genome, intragenomic and intergenomic comparisons of synteny indicate homologous chromosomal similarity and changes. Moreover, comparative and evolutionary analyses reveal three rounds of whole-genome duplication (WGD) events, as well as the possible diversification of hexaploid Changlin40 with diploid occurred approximately 9.06 million years ago (MYA). Furthermore, through the combination of genomics, transcriptomics and metabolomics approaches, a complex regulatory network was constructed and allows to identify potential key structural genes (SAD, FAD2 and FAD3) and transcription factors (AP2 and C2H2) that regulate the metabolism of Camellia oil, especially for unsaturated fatty acids biosynthesis. Overall, the genomic resource generated from this study has great potential to accelerate the research for the molecular biology and genetic improvement of hexaploid oil-Camellia, as well as to understand polyploid genome evolution.

Letter to the editor: evaluating computational tools for lncRNA identification on independent datasets.

The authors of the BASiNET tool claim that the survey paper 'A systematic evaluation of computational tools for lncRNA identification' incorrectly evaluates the BASiNET tool. Here, we point out that the survey paper correctly evaluates the BASiNET tool and why the evaluation should not be carried out as BASiNET authors suggest.

Computational analyses of bacterial strains from shotgun reads.

Shotgun sequencing is routinely employed to study bacteria in microbial communities. With the vast amount of shotgun sequencing reads generated in a metagenomic project, it is crucial to determine the microbial composition at the strain level. This study investigated 20 computational tools that attempt to infer bacterial strain genomes from shotgun reads. For the first time, we discussed the methodology behind these tools. We also systematically evaluated six novel-strain-targeting tools on the same datasets and found that BHap, mixtureS and StrainFinder performed better than other tools. Because the performance of the best tools is still suboptimal, we discussed future directions that may address the limitations.

ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides.

MOTIVATION: Plant Small Secreted Peptides (SSPs) play an important role in plant growth, development, and plant-microbe interactions. Therefore, the identification of SSPs is essential for revealing the functional mechanisms. Over the last few decades, machine learning-based methods have been developed, accelerating the discovery of SSPs to some extent. However, existing methods highly depend on handcrafted feature engineering, which easily ignores the latent feature representations and impacts the predictive performance. RESULTS: Here, we propose ExamPle, a novel deep learning model using Siamese network and multi-view representation for the explainable prediction of the plant SSPs. Benchmarking comparison results show that our ExamPle performs significantly better than existing methods in the prediction of plant SSPs. Also, our model shows excellent feature extraction ability. Importantly, by utilizing in silicomutagenesis experiment, ExamPle can discover sequential characteristics and identify the contribution of each amino acid for the predictions. The key novel principle learned by our model is that the head region of the peptide and some specific sequential patterns are strongly associated with the SSPs' functions. Thus, ExamPle is expected to be a useful tool for predicting plant SSPs and designing effective plant SSPs. AVAILABILITY AND IMPLEMENTATION: Our codes and datasets are available at https://github.com/Johnsunnn/ExamPle.

Regulation of carbohydrate metabolism during anther development in a thermo-sensitive genic male-sterile wheat line.

Bainong sterility (BNS) is a thermo-sensitive genic male sterile wheat line, characterised by anther fertility transformation in response to low temperature (LT) stress during meiosis, the failure of vacuole decomposition and the absence of starch accumulation in sterile bicellular pollen. Our study demonstrates that the late microspore (LM) stage marks the transition from the anther growth to anther maturation phase, characterised by the changes in anther structure, carbohydrate metabolism and the main transport pathway of sucrose (Suc). Fructan is a main storage polysaccharide in wheat anther, and its synthesis and remobilisation are crucial for anther development. Moreover, the process of pollen amylogenesis and the fate of the large vacuole in pollen are closely intertwined with fructan synthesis and remobilisation. LT disrupts the normal physiological metabolism of BNS anthers during meiosis, particularly affecting carbohydrate metabolism, thus determining the fate of male gametophytes and pollen abortion. Disruption of fructan synthesis and remobilisation regulation serves as a decisive event that results in anther abortion. Sterile pollen exhibits common traits of pollen starvation and impaired starch accumulation due to the inhibition of apoplastic transport starting from the LM stage, which is regulated by cell wall invertase TaIVR1 and Suc transporter TaSUT1.

Analysis of complete hydatidiform mole in one twin using traditional and molecular techniques.

A pregnant woman with hydatidiform mole in one twin was misdiagnosed as one of the twins with embryonic arrest. She chose to terminate the pregnancy and developed distant lung metastasis. After chemotherapy, she eventually recovered. This article systematically analyzes the diagnosis and treatment of hydatidiform mole in one twin to increase the awareness and reduce misdiagnosis of the disease.

Testing the Associations Between Attachment Anxiety, Relational Aggression and Depressive Symptoms in Romantic Relationships: Actor-Partner Interdependence Model and Actor-Partner Interdependence Mediator Model.

Emerging adulthood is a pivotal period for romantic relationships, yet the specific mechanisms through which attachment anxiety influences relationship dynamics and psychological outcomes in this phase are poorly understood. Particularly, in the context of romantic dyads, understanding how partners' behaviors and emotional patterns reciprocally influence each other remains underexplored. This study utilizes the Actor-Partner Interdependence Model and Actor-Partner Interdependence Mediator Model to explore the relationship between attachment anxiety,relational aggression (both perpetration and victimization), and depressive symptoms among emerging adults. A sample of 138 mixed-sex emerging adulthood couples from China, was recruited (Mage = 21.40, SD = 2.54; 50% female, 62.6% reporting that this relationship was ongoing for more than a year). Attachment anxiety significantly predicted relational aggression in both partners, with male attachment anxiety also significantly predicted female relational aggression. Significant indirect effects of both partners' relational aggression perpetration and victimization on their own and each other's relationship between attachment anxiety and depressive symptoms. These findings contribute to understanding the intricate dynamics of attachment anxiety and relational aggression in romantic relationships during emerging adulthood, emphasizing the need for targeted interventions to mitigate these risks.

A pilot study of multi-antigen stimulated cell therapy-I plus camrelizumab and apatinib in patients with advanced bone and soft-tissue sarcomas.

BACKGROUND: Cell-based  immunotherapy shows the therapeutic potential in sarcomas, in addition to angiogenesis-targeted tyrosine kinase inhibitor (TKI) and immune checkpoint inhibitor (ICI). Multi-antigen stimulated cell therapy-I (MASCT-I) technology is a sequential immune cell therapy for cancer, which composes of multiple antigen-loaded dendritic cell (DC) vaccines followed by the adoptive transfer of anti-tumor effector T-cells. METHODS: In this phase 1 study, we assessed MASCT-I plus camrelizumab (an ICI against PD-1) and apatinib (a highly selective TKI targeting VEGFR2) in patients with unresectable recurrent or metastatic bone and soft-tissue sarcoma after at least one line of prior systemic therapy. One MASCT-I course consisted of 3 DC subcutaneous injections, followed by 3 active T cell infusions administered 18-27 days after each DC injection. In schedule-I group, 3 DC injections were administered with a 28-day interval in all courses; in schedule-II group, 3 DC injections were administered with a 7-day interval in the first course and with a 28-day interval thereafter. All patients received intravenous camrelizumab 200 mg every 3 weeks and oral apatinib 250 mg daily. RESULTS: From October 30, 2019, to August 12, 2021, 19 patients were enrolled and randomly assigned to schedule-I group (n = 9) and schedule-II group (n = 10). Of the 19 patients, 11 (57.9%) experienced grade 3 or 4 treatment-related adverse events. No treatment-related deaths occurred. Patients in schedule-II group showed similar objective response rate (ORR) with those in schedule-I group (30.0% versus 33.3%) but had higher disease control rate (DCR; 90.0% versus 44.4%) and longer median progression-free survival (PFS; 7.7 versus 4.0 months). For the 13 patients with soft-tissue sarcomas, the ORR was 30.8%, DCR was 76.9%, and median PFS was 12.9 months; for the 6 patients with osteosarcomas, the ORR was 33.3%, the DCR was 50.0%, and median PFS was 5.7 months. CONCLUSIONS: Overall, MASCT-I plus camrelizumab and apatinib was safe and showed encouraging efficacy in advanced bone and soft-tissue sarcoma, and schedule-II administration method was recommended. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04074564.

Interpretation of deep learning in genomics and epigenomics.

Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies towards understanding the underlying molecular and cellular mechanisms. Deep neural networks (DNNs) have recently gained popularity in various types of genomic and epigenomic studies due to their capabilities in utilizing large-scale high-throughput bioinformatics data and achieving high accuracy in predictions and classifications. However, DNNs are often challenged by their potential to explain the predictions due to their black-box nature. In this review, we present current development in the model interpretation of DNNs, focusing on their applications in genomics and epigenomics. We first describe state-of-the-art DNN interpretation methods in representative machine learning fields. We then summarize the DNN interpretation methods in recent studies on genomics and epigenomics, focusing on current data- and computing-intensive topics such as sequence motif identification, genetic variations, gene expression, chromatin interactions and non-coding RNAs. We also present the biological discoveries that resulted from these interpretation methods. We finally discuss the advantages and limitations of current interpretation approaches in the context of genomic and epigenomic studies. Contact:xiaoman@mail.ucf.edu, haihu@cs.ucf.edu.

A systematic evaluation of the computational tools for lncRNA identification.

The computational identification of long non-coding RNAs (lncRNAs) is important to study lncRNAs and their functions. Despite the existence of many computation tools for lncRNA identification, to our knowledge, there is no systematic evaluation of these tools on common datasets and no consensus regarding their performance and the importance of the features used. To fill this gap, in this study, we assessed the performance of 17 tools on several common datasets. We also investigated the importance of the features used by the tools. We found that the deep learning-based tools have the best performance in terms of identifying lncRNAs, and the peptide features do not contribute much to the tool accuracy. Moreover, when the transcripts in a cell type were considered, the performance of all tools significantly dropped, and the deep learning-based tools were no longer as good as other tools. Our study will serve as an excellent starting point for selecting tools and features for lncRNA identification.

Computational annotation of miRNA transcription start sites.

MOTIVATION: MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation. RESULTS: In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes. CONTACT: xiaoman@mail.ucf.edu, haihu@cs.ucf.edu.

Efficacy and safety of fruquintinib as third- or further-line therapy for patients with advanced bone and soft tissue sarcoma: a multicenter retrospective study.

PURPOSE: Fruquintinib is an oral small-molecule angiogenesis inhibitor, markedly specifically inhibited vascular endothelial growth factor 2 (VEGFR2). This retrospective study aimed to evaluate the safety and efficacy of fruquintinib, or in combination with immunotherapy or chemotherapy in patients with bone and soft tissue sarcoma (STS), who have failed at least secondary-line treatment. PATIENTS AND METHODS: We performed a retrospective analysis of advanced bone and STS patients who received fruquintinib containing third- or further-line therapy in Shanghai Jiao Tong University Affiliated Sixth People's and the Affiliated Hospital of Jiangxi University of Traditional Chiese Medicine from September 2019 to February 2022. All of them had accepted at least anthracyclines-based chemotherapy. For the experimental group, 25 cases, the patients took a basic dose of fruquintinib 3-5 mg once a day for 21 days per 4 weeks as a cycle until the disease progression or intolerable toxicity. The other 20 patients in the control group received the best supportive care. The patients were evaluated by computed tomography (CT) or MRI once 2 months or symptoms worse. The DCR, progression-free survival (PFS), and adverse reactions of the drug were recorded and reviewed. RESULTS: The DCR in patients receiving fruquintinib therapy was 80.0%. The median PFS (mPFS) in the fruquintinib-containing therapy group was significantly longer than that in the control group (4.8 vs. 1.4 months; P < 0.001). The mPFS in the fruquintinib group, the fruquintinib-OI group and the fruquintinib-chemotherapy group were 3.2 months [95% confidence interval (CI), 2.0-7.9], 4.9 months (95% CI, 3.0-9.9) and 4.2 months (95% CI, 2.6-6.6) respectively, all of them were longer than the mPFS of 1.4 months (95% CI, 0.3-2.5) in the control group ( P < 0.001). CONCLUSION: Fruquintinib was reported for the first time to have favorable efficacy and safety as an optional treatment for patients with advanced bone and STS who failed in multi-line therapies.

An oncolytic herpes simplex virus type 1 strain expressing a single-chain variable region antibody fragment against PD-1 and a PI3K inhibitor synergize to elicit antitumor immunity in ovarian cancer.

Due to recurrence and resistance to chemotherapy, the current standard therapeutics are not fully effective against ovarian cancer. Therefore, we aimed to find an effective approach to improve the prognosis and therapy of ovarian cancer. NG34ScFvPD-1 is a modified oncolytic herpes simplex virus NG34 strain that expresses a single-chain antibody against programmed cell death protein 1 (PD-1) (ScFvPD-1). We assessed its efficacy and its regulatory mechanism in a mouse model of ovarian cancer. Enzyme-linked immunosorbent assay and western blot techniques were used to measure protein expression. Oncolysis caused by NG34ScFvPD-1 was examined using cytotoxicity and replication assays. The mechanism by which NG34ScFvPD-1 regulates apoptosis of ovarian cancer cells in vitro was also evaluated. We assessed the antitumor immunity and therapeutic potency of NG34ScFvPD-1 in combination with a phosphoinositide 3-kinase (PI3K) inhibitor. We found that NG34ScFvPD-1-infected ovarian cancer cells expressed and secreted ScFvPD-1, which bound mouse PD-1. The insertion of the ScFvPD-1 sequence did not inhibit the oncolytic activity of NG34ScFvPD-1, which induced apoptosis of ovarian cancer cells via the caspase-dependent pathway in vitro and activated the PI3K/AKT signaling pathway. Synergy was observed between NG34ScFvPD-1 and a PI3K inhibitor, and the combination was able to suppress tumor development, to prolong survival, and to elicit potent antitumor immunity. Thus, inhibition of PI3K enhanced the potent antitumor immunity induced by NG34ScFvPD-1 against ovarian cancer.

Knowledge, attitudes, practices and associated factors regarding high output stoma of ileostomy among colorectal surgical nurses: a multicentre cross-sectional study.

PURPOSE: High output stoma(HOS) is one of the most common complications after ileostomy, leading to fluid and electrolyte disturbances and renal dysfunction, and increasing the risk of readmission. Routine health education for HOS should be provided, and nurses, as the primary educators, should have adequate knowledge and skills in this area. However, there is a paucity of research on the knowledge and practice of HOS management. This study used the Knowledge, Attitude and Behavioural Practice Model to assess the management of HOS by colorectal surgery nurses and to explore the factors that influence it. METHOD: Using a multi-centre, cross-sectional study design, 398 colorectal surgery nurses from 6 hospitals in 6 cities in 6 provinces were surveyed using a structured electronic questionnaire to assess general information and knowledge, attitudes and management practices and training needs related to HOS of ileostomy. RESULTS: Colorectal surgery nurses' knowledge and practice of HOS was low. The presence or absence of training is an important factor influencing nurses' knowledge, attitudes and practice, with most nurses having no training and stoma specialist nurses scoring relatively high on knowledge and practice. CONCLUSIONS: Nurses play a very important role in the management of HOS, but this study shows that the current level of knowledge and practice of HOS among colorectal surgery nurses is concerning, and whether or not they have received training is the most critical influencing factor; therefore, training related to HOS is urgently needed.

The effectiveness of health education based on the 5Ts for teach-back on oral nutritional supplements compliance of post-discharge patients after surgery for gastric cancer: a randomized controlled trial.

OBJECTIVE: This study aims to explore the 5Ts teach-back(5Ts) to improve oral nutritional supplements (ONS) compliance of discharged patients after gastric cancer surgery. SETTING AND METHODS: Patients were recruited from the Bethune First Hospital of Jilin University. The patients were randomly assigned to 5Ts (n = 54) and routine health education (n = 54). Weekly ONS compliance was collected by "weekly ONS diary." ONS knowledge, health literacy, and health education satisfaction were collected at baseline and 5 weeks after discharge. Chi-square test, Mann-Whitney U test, and T test were used for data analysis. RESULTS: At the end of the intervention, there were 41 and 40 patients in intervention and control group. 5Ts significantly improve ONS compliance, ONS knowledge level (P = 0.000), health literacy level (P = 0.011), and health education satisfaction (P = 0.009) of patients. At the end of follow-up, there were 30 and 27 patients in two groups, and no significant difference in ONS compliance (P = 0.728). CONCLUSION: The 5Ts can significantly improve patients' ONS compliance and the effect of health education. TRIAL REGISTRATION NUMBER: This prospective trial was registered in the Chinese Clinical Trial Registry at ChiCTR2000040986 ( http://www.chictr.org.cn ). PATIENT OR PUBLIC CONTRIBUTION: Jia Wang and Haiyan Hu contributed to the performance of the study, analysis and interpretation the data, and drafted the manuscript; Jianan Sun and Qing Zhang contributed to the supervision of the study and interpreted the data; Zhiming Chen contributed to the analysis and interpretation the data; Qiuchen Wang contributed to the performance of the study and revised the manuscript; Mingyue Zhu contributed to interpretation the data; Jiannan Yao contributed to revise the manuscript; Hua Yuan and Xiuying Zhang contributed to the conception of the study, performed the study, interpreted the data, and significantly revised the manuscript. All authors screened the final version of the manuscript.

MicroRNA Expression Profiles in Response to Phytophthora infestans and Oidium neolycopersici and Functional Identification of sly-miR397 in Tomato.

Late blight and powdery mildew are two widespread tomato diseases caused by Phytophthora infestans and Oidium neolycopersici, respectively, which reduce the quantity and quality of tomato. MicroRNAs (miRNAs) play critical roles in tomato resistance to various pathogens. Investigating the function of miRNAs is of great significance in controlling tomato diseases. To identify potential miRNAs involved in the interaction of tomato with P. infestans or O. neolycopersici, we analyzed the expression profiles of small RNAs in tomato leaves infected with these two pathogens using RNA-seq technology. A total of 330 and 288 miRNAs exhibited differences in expression levels after exposure to P. infestans and O. neolycopersici, respectively. One hundred and forty-six commonly differentially expressed (DE) miRNAs responsive to P. infestans and O. neolycopersici infestation were detected, including 10 commonly known conserved DE miRNAs and 136 novel miRNAs. Among these known DE miRNAs, sly-miR397 was strongly downregulated in response to P. infestans or O. neolycopersici infection. Silencing of sly-miR397 resulted in enhanced tolerance to the pathogens, whereas overexpression of sly-miR397 showed increased susceptibility. Furthermore, changes in sly-miR397 expression could also affect expression levels of pathogenesis-related genes and reactive oxygen species-scavenging genes, leading to altered necrotic cells and H2O2 levels. In addition, the number of lateral branches significantly changed in transgenic plants. Taken together, our results provide potential miRNA resources for further research of miRNA-disease associations and indicates that sly-miR397 acts as a negative regulator of disease resistance and influences lateral branch development in tomato.