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Brown planthopper (BPH) is the most destructive insect pest of rice. Drought is the most detrimental environmental stress. BPH infestation causes adaxial leaf-rolling and bulliform cells (BCs) shrinkage similar to drought. The BC-related abaxially curled leaf1 (ACL1) gene negatively regulates BPH resistance and drought tolerance, with decreased cuticular wax in the gain-of-function mutant ACL1-D. ACL1 shows an epidermis-specific expression. The TurboID system and multiple biochemical assays reveal that ACL1 interacts with the epidermal-characteristic rice outermost cell-specific (ROC) proteins. ROC4 and ROC5 positively regulate BPH resistance and drought tolerance through modulating cuticular wax and BCs, respectively. Overexpression of ROC4 and ROC5 both rescue ACL1-D mutant in various related phenotypes. ACL1 competes with ROC4/ROC5 in homo-dimer and hetero-dimer formation, and interacts with the repressive TOPLESS-related proteins. Altogether, we illustrate that ACL1–ROC4/5 complexes synergistically mediate drought tolerance and BPH resistance through regulating cuticular wax content and BC development in rice, a mechanism that might facilitate BPH-resistant breeding. Brown planthopper is a rice-specific piercing-sucking pest. This study reveals that ACL1-ROC4/5 complexes regulate both brown planthopper resistance and drought tolerance in rice through modulating bulliform cell development and cuticular wax content. [ABSTRACT FROM AUTHOR]

Manipulating grain size demonstrates great potential for yield promotion in cereals since it is tightly associated with grain weight. Several pathways modulating grain size have been elaborated in rice, but possible crosstalk between the ingredients is rarely studied. OsmiR396 negatively regulates grain size through targeting OsGRF4 (GS2) and OsGRF8, and proves to be multi-functioning. Here we showed that expression of GS3 gene, a Gγ-protein encoding gene, that negatively regulates grain size, was greatly down-regulated in the young embryos of MIM396, GRF8OE and GS2OE plants, indicating possible regulation of GS3 gene by OsmiR396/GRF module. Meanwhile, multiple biochemical assays proved possible transcriptional regulation of OsGRF4 and OsGRF8 proteins on GS3 gene. Further genetic relation analysis revealed tight genetic association between not only OsmiR396 and GS3 gene, but also GS2 and GS3 gene. Moreover, we revealed possible regulation of GS2 on four other grain size-regulating G protein encoding genes. Thus, the OsmiR396 pathway and the G protein pathway cross talks to regulate grain size. Therefore, we established a bridge linking the miRNA-transcription factors pathway and the G-protein signaling pathway that regulates grain size in rice. [ABSTRACT FROM AUTHOR]

Leaf morphology is a crucial agronomic characteristic of rice that influences crop yield directly. One primary cause of rice leaf rolling can be attributed to alterations in bulliform cells. Several HD-ZIP IV genes have been identified to be epidemical characterized and function in leaf rolling in rice. Still others need to be studied to fully understand the overall function of HD-ZIP IV family. Among the nine ROC genes encoding HD-ZIP IV family transcription factors in rice, ROC1 exhibits the highest expression in the leaves. Overexpression of ROC1 decreased the size of bulliform cells, and thus resulted in adaxially rolled leaves. To the contrary, knockout of ROC1 (ROC1KO) through Crispr-cas9 system enlarged bulliform cells, and thus led to abaxially rolled leaves. Moreover, ROC1KO plants were sensitive to drought. ROC1 could form homodimers on its own, and heterodimers with ROC5 and ROC8 respectively. Compared to ROC1KO plants, leaves of the ROC1 and ROC8 double knocked out plants (ROC1/8DKO) were more severely rolled abaxially due to enlarged bulliform cells, and ROC1/8DKO plants were more drought sensitive. However, overexpression of ROC8 could not restore the abaxial leaf phenotype of ROC1KO plants. Therefore, we proved that ROC1, a member of the HD-ZIP IV family, regulated leaf rolling and drought stress response through tight association with ROC5 and ROC8. [ABSTRACT FROM AUTHOR]

Background: The brown planthopper (BPH) is a kind of piercing-sucking insect specific to rice, with the damage tops the list of pathogens and insects in recent years. microRNAs (miRNAs) are pivotal regulators of plant–environment interactions, while the mechanism underlying their function against insects is largely unknown. Results: Here, we confirmed that OsmiR319, an ancient and conserved miRNA, negatively regulated resistance to BPHs, with overexpression of OsmiR319 susceptible to BPH, while suppression of OsmiR319 resistant to BPH in comparison with wild type. Meanwhile, we identified several targets of OsmiR319 that may mediate BPH resistance. Among them, OsPCF5 was the most obviously induced by BPH feeding, and over expression of OsPCF5 was resistance to BPH. In addition, various biochemical assays verified that OsPCF5 interacted with several MYB proteins, such as OsMYB22, OsMYB30, and OsMYB30C.Genetically, we revealed that both OsMYB22 and OsMYB30C positively regulated BPH resistance. Genetic interaction analyses confirmed that OsMYB22 and OsMYB30C both function in the same genetic pathway with OsmiR319b to mediate BPH resistance. Conclusions: Altogether, we revealed that OsPCF5 regulates BPH resistance via association with several MYB proteins downstream of OsmiR319, these MYB proteins might function as regulators of BPH resistance through regulating the phenylpropane synthesis. [ABSTRACT FROM AUTHOR]

Abstract: In the silkworm Bombyx mori, non-susceptibility to the Zhenjiang (China) strain of the densonucleosis virus (DNV-Z) is controlled by the recessive gene nsd-Z (non-susceptible to DNV-Z), which is located [...]

The latest progresses of experimental biology have generated a large number of data with different formats and lengths. Deep learning is an ideal tool to deal with complex datasets, but its inherent "black box" nature needs more interpretability. At the same time, traditional interpretable machine learning methods, such as linear regression or random forest, could only deal with numerical features instead of modular features often encountered in the biological field. Here, we present MultiCapsNet (https://github.com/wanglf19/MultiCapsNet), a new deep learning model built on CapsNet and scCapsNet, which possesses the merits such as easy data integration and high model interpretability. To demonstrate the ability of this model as an interpretable classifier to deal with modular inputs, we test MultiCapsNet on three datasets with different data type and application scenarios. Firstly, on the labeled variant call dataset, MultiCapsNet shows a similar classification performance with neural network model, and provides importance scores for data sources directly without an extra importance determination step required by the neural network model. The importance scores generated by these two models are highly correlated. Secondly, on single cell RNA sequence (scRNA-seq) dataset, MultiCapsNet integrates information about protein-protein interaction (PPI), and protein-DNA interaction (PDI). The classification accuracy of MultiCapsNet is comparable to the neural network and random forest model. Meanwhile, MultiCapsNet reveals how each transcription factor (TF) or PPI cluster node contributes to classification of cell type. Thirdly, we made a comparison between MultiCapsNet and SCENIC. The results show several cell type relevant TFs identified by both methods, further proving the validity and interpretability of the MultiCapsNet. [ABSTRACT FROM AUTHOR]

Abstract Background Brown planthopper (BPH), Nilaparvata lugens Stål, is one of the most destructive insect pests of rice. The molecular responses of plants to sucking insects resemble responses to pathogen infection. However, the molecular mechanism of BPH-resistance in rice remains unclear. Transcription factors (TF) are up-stream regulators of various genes that bind to specific DNA sequences, thereby controlling the transcription from DNA to mRNA. They are key regulators for transcriptional expression in biological processes, and are probably involved in the BPH-induced pathways in resistant rice varieties. Results We conducted a microarray experiment to analyze TF genes related to BPH resistance in a Sri Lankan rice cultivar, Rathu Heenati (RHT). We compared the expression profiles of TF genes in RHT with those of the susceptible rice cultivar Taichun Native 1 (TN1). We detected 2038 TF genes showing differential expression signals between the two rice varieties. Of these, 442 TF genes were probably related to BPH-induced resistance in RHT and TN1, and 229 may be related to constitutive resistance only in RHT. These genes showed a fold change (FC) of more than 2.0 (P10, there were 37 induced TF genes and 26 constitutive resistance TF genes. Of these, 13 were probably involved in BPH-induced resistance, and 8 in constitutive resistance to BPH in RHT. Conclusions We explored the molecular mechanism of resistance to BPH in rice by comparing expressions of TF genes between RHT and TN1. We speculate that the level of gene repression, especially for early TF genes, plays an important role in the defense response. The fundamental point of the resistance strategy is that plants protect themselves by reducing their metabolic level to inhibit feeding by BPH and prevent damage from water and nutrient loss. We have selected 21 TF genes related to BPH resistance for further analyses to understand the molecular responses to BPH feeding in rice.

Abstract Background Bombyx mori, the domesticated silkworm, is a well-studied model insect with great economic and scientific significance. Although more than 400 mutations have been described in silkworms, most have not been identified, especially those affecting economically-important traits. Simple sequence repeats (SSRs) are effective and economical tools for mapping traits and genetic improvement. The current SSR linkage map is of low density and contains few polymorphisms. The purpose of this work was to develop a dense and informative linkage map that would assist in the preliminary mapping and dissection of quantitative trait loci (QTL) in a variety of silkworm strains. Results Through an analysis of > 50,000 genotypes across new mapping populations, we constructed two new linkage maps covering 27 assigned chromosomes and merged the data with previously reported data sets. The integrated consensus map contains 692 unique SSR sites, improving the density from 6.3 cM in the previous map to 4.8 cM. We also developed 497 confirmed neighboring markers for corresponding low-polymorphism sites, with 244 having polymorphisms. Large-scale statistics on the SSR type were suggestive of highly efficient markers, based upon which we searched 16,462 available genomic scaffolds for SSR loci. With the newly constructed map, we mapped single-gene traits, the QTL of filaments, and a number of ribosomal protein genes. Conclusion The integrated map produced in this study is a highly efficient genetic tool for the high-throughput mapping of single genes and QTL. Compared to previous maps, the current map offers a greater number of markers and polymorphisms; thus, it may be used as a resource for marker-assisted breeding.