Our previous studies indicated that tomato miR482b could negatively regulate the resistance of tomato to Phytophthora infestans and the expression of miR482b was decreased after inoculation with P. infestans. However, the mechanism by which the accumulation of miR482b is suppressed remains unclear. In this study, we wrote a program to identify 89 long noncoding RNA (lncRNA)-originated endogenous target mimics (eTMs) for 46 miRNAs from our RNA-Seq data. Three tomato lncRNAs, lncRNA23468, lncRNA01308 and lncRNA13262, contained conserved eTM sites for miR482b. When lncRNA23468 was overexpressed in tomato, miR482b expression was significantly decreased, and the expression of the target genes, NBS-LRRs, was significantly increased, resulting in enhanced resistance to P. infestans. Silencing lncRNA23468 in tomato led to the increased accumulation of miR482b and decreased accumulation of NBS-LRRs, as well as reduced resistance to P. infestans. In addition, the accumulation of both miR482b and NBS-LRRs was not significantly changed in tomato plants that overexpressed lncRNA23468 with a mutated eTM site. Based on the VIGS system, a target gene of miR482b, Solyc02g036270.2, was silenced. The disease symptoms of the VIGS-Solyc02g036270.2 tomato plants were in accordance with those of tomato plants in which lncRNA23468 was silenced after inoculation with P. infestans. More severe disease symptoms were found in the modified plants than in the control plants. Our results demonstrate that lncRNAs functioning as eTMs may modulate the effects of miRNAs in tomato and provide insight into how the lncRNA23468-miR482b-NBS-LRR module regulates tomato resistance to P. infestans.

Our previous studies indicated that tomato WRKY1 transcription factor acts as a positive regulator during tomato resistance to Phytophthora infestans. However, the molecular mechanism of WRKY1-mediated resistance regulation remains unclear. Here, we used a comparative transcriptome analysis between wild-type and WRKY1-overexpressing tomato plants to identify differentially expressed genes (DEGs) and long noncoding RNAs (DELs), and we examined long non-coding RNA (lncRNA)-gene networks. The promoter sequences of the upregulated DEGs and DELs were analyzed. Among 1073 DEGs and 199 DELs, 1 kb 5 0upstream regions of 59 DEGs and 22 DELs contain the W-box, the target sequence of the WRKY1. The results of promoterÀb-glucuronidase (GUS) fusion and yeast one-hybrid assay showed that lncRNA33732 was activated by WRKY1 through sequence-specific interactions with the W-box element in its promoter. The overexpression and silencing analysis of lncRNA33732 in tomato showed that lncRNA33732 acts as a positive regulator and enhanced tomato resistance to P. infestans by induction of the expression of respiratory burst oxidase (RBOH) and increase in the accumulation of H 2 O 2 . When the expression of RBOH gene was inhibited in tomato plants, H 2 O 2 accumulation decreased and resistance were impaired. These findings suggest that lncRNA33732 activated by WRKY1 induces RBOH expression to increase H 2 O 2 accumulation in early defense reaction of tomato to P. infestans attack. Our results provide insights into the WRKY1ÀlncR-NA33732ÀRBOH module involved in the regulation of H 2 O 2 accumulation and resistance to P. infestans, as well as provide candidates to enhance broad-spectrum resistance to pathogens in tomato.

No abstract

MYB49-overexpressing tomato plants showed significant resistance to Phytophthora infestans and tolerance to drought and salt stresses. This finding reveals the potential application of tomato MYB49 in future molecular breeding. Biotic and abiotic stresses severely reduce the productivity of tomato worldwide. Therefore, it is necessary to find key genes to simultaneously improve plant resistance to pathogens and tolerance to various abiotic stresses. In this study, based on homologous relationships with Arabidopsis R2R3-MYBs (AtMYBs) involved in responses to biotic and abiotic stresses, we identified a total of 24 R2R3-MYB transcription factors in the tomato genome. Among these tomato R2R3-MYBs, MYB49 (Solyc10g008700.1) was clustered into subgroup 11 by phylogenetic analysis, and its expression level was significantly induced after treatment with P. infestans, NaCl and PEG6000. Overexpression of MYB49 in tomato significantly enhanced the resistance of tomato to P. infestans, as evidenced by decreases in the number of necrotic cells, sizes of lesion, abundance of P. infestans, and disease index. Likewise, MYB49-overexpressing transgenic tomato plants also displayed increased tolerance to drought and salt stresses. Compared to WT plants, the accumulation of reactive oxygen species (ROS), malonaldehyde content, and relative electrolyte leakage was decreased, and peroxidase activity, superoxide dismutase activity, chlorophyll content, and photosynthetic rate were increased in MYB49-overexpressing tomato plants under P. infestans, salt or drought stress. These results suggested that tomato MYB49, as a positive regulator, could enhance the capacity to scavenge ROS, inhibit cell membrane damage and cell death, and protect chloroplasts, resulting in an improvement in resistance to P. infestans and tolerance to salt and drought stresses, and they provide a candidate gene for tomato breeding to enhance biotic stress resistance and abiotic stress tolerance.

Summary Long non‐coding RNAs (lncRNAs) are involved in the resistance of plants to infection by pathogens via interactions with microRNAs (miRNAs). Long non‐coding RNAs are cleaved by miRNAs to produce phased small interfering RNAs (phasiRNAs), which, as competing endogenous RNAs (ceRNAs), function as decoys for mature miRNAs, thus inhibiting their expression, and contain pre‐miRNA sequences to produce mature miRNAs. However, whether lncRNAs and miRNAs mediate other molecular mechanisms during plant resistance to pathogens is unknown. In this study, as a positive regulator, Sl‐lncRNA15492 from tomato (Solanum lycopersicum Zaofen No. 2) plants affected tomato resistance to Phytophthora infestans. Gain‐ and loss‐of‐function experiments and RNA ligase‐mediated 5′‐amplification of cDNA ends (RLM‐5′ RACE) also revealed that Sl‐miR482a was negatively involved in tomato resistance by targeting Sl‐NBS‐LRR genes and that silencing of Sl‐NBS‐LRR1 decreased tomato resistance. Sl‐lncRNA15492 inhibited the expression of mature Sl‐miR482a, whose precursor was located within the antisense sequence of Sl‐lncRNA15492. Further degradome analysis and additional RLM‐5′ RACE experiments verified that mature Sl‐miR482a could also cleave Sl‐lncRNA15492. These results provide a mechanism by which lncRNAs might inhibit precursor miRNA expression through antisense strands of lncRNAs, and demonstrate that Sl‐lncRNA15492 and Sl‐miR482a mutually inhibit the maintenance of Sl‐NBS‐LRR1 homeostasis during tomato resistance to P. infestans.

Hypoxia, which is an important factor that mediates tumor progression and poor treatment response, is particularly associated with tumor chemoresistance. However, the molecular mechanisms underlying hypoxia-induced colorectal cancer chemoresistance remain unclear. The present study aimed to explore the mechanism underlying hypoxia-induced chemotherapy resistance in LOVO colorectal cancer cells. LOVO cells were cultured in a hypoxic environment simulated by cobalt chloride (CoCl2), which is a chemical inducer of hypoxia-inducible factor-1α (HIF-1α). HIF-1α is a transcription factor that has an important role in tumor cell adaptation to hypoxia, and controls the expression of several genes. Various CoCl2 concentrations are often used to simulate degrees of hypoxia. In the present study, following treatment with CoCl2, an MTT assay was conducted to determine the growth and drug sensitivity of LOVO cells. Reverse transcription-polymerase chain reaction and western blotting were used to detect the mRNA and protein expression levels of HIF-1α and factors associated with chemotherapy resistance, including multidrug resistance protein (MRP) and multidrug resistant 1 (MDR1), which encodes the major transmembrane efflux transporter P-glycoprotein (P-gp). In addition, the expression levels of apoptosis-related proteins, including B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax) and Bcl-2-associated agonist of cell death (Bad) were detected by western blotting. Flow cytometry (FCM) was used to visually observe Adriamycin (ADR) accumulation and retention, thus analyzing intracellular drug transportation in cells under hypoxic and normoxic conditions. CoCl2-simulated hypoxia was able to inhibit tumor cell proliferation, and upregulate the expression levels of HIF-1α, MDR1/P-gp and MRP. In addition, proapoptotic members of the Bcl-2 protein family, Bax and Bad, were downregulated. The anti-apoptotic member Bcl-2 exhibited no significant change in expression, whereas the ratio of Bcl-2/Bax was increased. Results of FCM demonstrated that the intracellular retention of ADR was significantly decreased in the hypoxia group cells. In conclusion, the present study revealed that a CoCl2-simulated hypoxic microenvironment was able to effectively induce chemoresistance and reduce apoptosis in LOVO cells.

Unsupervised domain adaptation facilitates the unlabeled target domain relying on well-established source domain information. The conventional methods forcefully reducing the domain discrepancy in the latent space will result in the destruction of intrinsic data structure. To balance the mitigation of domain gap and the preservation of the inherent structure, we propose a Bi-Directional Generation domain adaptation model with consistent classifiers interpolating two intermediate domains to bridge source and target domains. Specifically, two cross-domain generators are employed to synthesize one domain conditioned on the other. The performance of our proposed method can be further enhanced by the consistent classifiers and the cross-domain alignment constraints. We also design two classifiers which are jointly optimized to maximize the consistency on target sample prediction. Extensive experiments verify that our proposed model outperforms the state-of-the-art on standard cross domain visual benchmarks.

A fundamental and challenging problem in deep learning is catastrophic forgetting, i.e. the tendency of neural networks to fail to preserve the knowledge acquired from old tasks when learning new tasks. This problem has been widely investigated in the research community and several Incremental Learning (IL) approaches have been proposed in the past years. While earlier works in computer vision have mostly focused on image classification and object detection, more recently some IL approaches for semantic segmentation have been introduced. These previous works showed that, despite its simplicity, knowledge distillation can be effectively employed to alleviate catastrophic forgetting. In this paper, we follow this research direction and, inspired by recent literature on contrastive learning, we propose a novel distillation framework, Uncertainty-aware Contrastive Distillation (UCD). In a nutshell, UCD is operated by introducing a novel distillation loss that takes into account all the images in a mini-batch, enforcing similarity between features associated to all the pixels from the same classes, and pulling apart those corresponding to pixels from different classes. In order to mitigate catastrophic forgetting, we contrast features of the new model with features extracted by a frozen model learned at the previous incremental step. Our experimental results demonstrate the advantage of the proposed distillation technique, which can be used in synergy with previous IL approaches, and leads to state-of-art performance on three commonly adopted benchmarks for incremental semantic segmentation. The code is available at https://github.com/ygjwd12345/UCD.