Deep-HPI-pred: An R-Shiny applet for network-based classification and prediction of Host-Pathogen protein-protein interactions.

Host-pathogen interactions (HPIs) are vital in numerous biological activities and are intrinsically linked to the onset and progression of infectious diseases. HPIs are pivotal in the entire lifecycle of diseases: from the onset of pathogen introduction, navigating through the mechanisms that bypass host cellular defenses, to its subsequent proliferation inside the host. At the heart of these stages lies the synergy of proteins from both the host and the pathogen. By understanding these interlinking protein dynamics, we can gain crucial insights into how diseases progress and pave the way for stronger plant defenses and the swift formulation of countermeasures. In the framework of current study, we developed a web-based R/Shiny app, Deep-HPI-pred, that uses network-driven feature learning method to predict the yet unmapped interactions between pathogen and host proteins. Leveraging citrus and CLas bacteria training datasets as case study, we spotlight the effectiveness of Deep-HPI-pred in discerning Protein-protein interaction (PPIs) between them. Deep-HPI-pred use Multilayer Perceptron (MLP) models for HPI prediction, which is based on a comprehensive evaluation of topological features and neural network architectures. When subjected to independent validation datasets, the predicted models consistently surpassed a Matthews correlation coefficient (MCC) of 0.80 in host-pathogen interactions. Remarkably, the use of Eigenvector Centrality as the leading topological feature further enhanced this performance. Further, Deep-HPI-pred also offers relevant gene ontology (GO) term information for each pathogen and host protein within the system. This protein annotation data contributes an additional layer to our understanding of the intricate dynamics within host-pathogen interactions. In the additional benchmarking studies, the Deep-HPI-pred model has proven its robustness by consistently delivering reliable results across different host-pathogen systems, including plant-pathogens (accuracy of 98.4% and 97.9%), human-virus (accuracy of 94.3%), and animal-bacteria (accuracy of 96.6%) interactomes. These results not only demonstrate the model's versatility but also pave the way for gaining comprehensive insights into the molecular underpinnings of complex host-pathogen interactions. Taken together, the Deep-HPI-pred applet offers a unified web service for both identifying and illustrating interaction networks. Deep-HPI-pred applet is freely accessible at its homepage: https://cbi.gxu.edu.cn/shiny-apps/Deep-HPI-pred/ and at github: https://github.com/tahirulqamar/Deep-HPI-pred.

High-quality genome assemblies for two Australimusa bananas (Musa spp.) and insights into regulatory mechanisms of superior fiber properties.

Bananas (Musa spp.) are monocotyledonous plants with high genetic diversity in the Musaceae family that are cultivated mainly in tropical and subtropical countries. The fruits are a popular food, and the plants themselves have diverse uses. Four genetic groups (genomes) are thought to have contributed to current banana cultivars: Musa acuminata (A genome), Musa balbisiana (B genome), Musa schizocarpa (S genome), and species of the Australimusa section (T genome). However, the T genome has not been effectively explored. Here, we present the high-quality TT genomes of two representative accessions, Abaca (Musa textilis), with high-quality natural fiber, and Utafun (Musa troglodytarum, Fe'i group), with abundant ß-carotene. Both the Abaca and Utafun assemblies comprise 10 pseudochromosomes, and their total genome sizes are 613 Mb and 619 Mb, respectively. Comparative genome analysis revealed that the larger size of the T genome is likely attributable to rapid expansion and slow removal of transposons. Compared with those of Musa AA or BB accessions or sisal (Agava sisalana), Abaca fibers exhibit superior mechanical properties, mainly because of their thicker cell walls with a higher content of cellulose, lignin, and hemicellulose. Expression of MusaCesA cellulose synthesis genes peaks earlier in Abaca than in AA or BB accessions during plant development, potentially leading to earlier cellulose accumulation during secondary cell wall formation. The Abaca-specific expressed gene MusaMYB26, which is directly regulated by MusaMYB61, may be an important regulator that promotes precocious expression of secondary cell wall MusaCesAs. Furthermore, MusaWRKY2 and MusaNAC68, which appear to be involved in regulating expression of MusaLAC and MusaCAD, may at least partially explain the high accumulation of lignin in Abaca. This work contributes to a better understanding of banana domestication and the diverse genetic resources in the Musaceae family, thus providing resources for Musa genetic improvement.

Two haplotype-resolved genome assemblies for AAB allotriploid bananas provide insights into banana subgenome asymmetric evolution and Fusarium wilt control.

Bananas (Musa spp.) are one of the world's most important fruit crops and play a vital role in food security for many developing countries. Most banana cultivars are triploids derived from inter- and intraspecific hybridizations between the wild diploid ancestor species Musa acuminate (AA) and M. balbisiana (BB). We report two haplotype-resolved genome assemblies of the representative AAB-cultivated types, Plantain and Silk, and precisely characterize ancestral contributions by examining ancestry mosaics across the genome. Widespread asymmetric evolution is observed in their subgenomes, which can be linked to frequent homologous exchange events. We reveal the genetic makeup of triploid banana cultivars and verify that subgenome B is a rich source of disease resistance genes. Only 58.5% and 59.4% of Plantain and Silk genes, respectively, are present in all three haplotypes, with >50% of genes being differentially expressed alleles in different subgenomes. We observed that the number of upregulated genes in Plantain is significantly higher than that in Silk at one-week post-inoculation with Fusarium wilt tropical race 4 (Foc TR4), which confirms that Plantain can initiate defense responses faster than Silk. Additionally, we compared genomic and transcriptomic differences among the genes related to carotenoid synthesis and starch metabolism between Plantain and Silk. Our study provides resources for better understanding the genomic architecture of cultivated bananas and has important implications for Musa genetics and breeding.

Comparative genomics profiling revealed multi-stress responsive roles of the CC-NBS-LRR genes in three mango cultivars.

The nucleotide-binding site-leucine-rich repeat (NBS-LRR) gene family is the largest group of disease resistance (R) genes in plants and is active in response to viruses, bacteria, and fungi usually involved in effector-triggered immunity (ETI). Pangenome-wide studies allow researchers to analyze the genetic diversity of multiple species or their members simultaneously, providing a comprehensive understanding of the evolutionary relationships and diversity present among them. The draft pan-genome of three Mangifera indica cultivars (Alphonso, Hong Xiang Ya, and Tommy atkins) was constructed and Presence/absence variants (PAVs) were filtered through the ppsPCP pipeline. As a result, 2823 genes and 5907 PAVs from H. Xiang Ya, and 1266 genes and 2098 PAVs from T. atkins were added to the reference genome. For the identification of CC-NBS-LRR (CNL) genes in these mango cultivars, this draft pan-genome study has successfully identified 47, 27, and 36 members in Alphonso, H. Xiang Ya, and T. atkins respectively. The phylogenetic analysis divided MiCNL proteins into four distinct subgroups. All MiCNL genes are unevenly distributed on chromosomes. Both tandem and segmental duplication events played a significant role in the expansion of the CNL gene family. These genes contain cis-elements related to light, stress, hormone, and development. The analysis of protein-protein interactions (PPI) revealed that MiCNL proteins interacted with other defense-responsive proteins. Gene Ontology (GO) analysis indicated that MiCNL genes play a role in defense mechanisms within the organism. The expression level of the identified genes in fruit peel was observed under disease and cold stress which showed that Mi_A_CNL13 and 14 were up-regulated while Mi_A_CNL15, 25, 30, 31, and 40 were down-regulated in disease stress. On the other hand, Mi_A_CNL2, 14, 41, and 45 were up-regulated and Mi_A_CNL47 is down-regulated in cold stress. Subsequently, the Random Forest (RF) classifier was used to assess the multi-stress response of MiCNLs. It was found that Mi_A_CNL14 is a gene that responds to multiple stress conditions. The CNLs have similar protein structures which show that they are involved in the same function. The above findings provide a foundation for a deeper understanding of the functional characteristics of the mango CNL gene family.

Highly Efficient Light-Emitting Diodes Based on Self-Assembled Colloidal Quantum Wells.

Nanocrystal-based light-emitting diodes (Nc-LEDs) have immense potential for next-generation high-definition displays and lighting applications. They offer numerous advantages, such as low cost, high luminous efficiency, narrow emission, and long lifetime. However, the external quantum efficiency (EQE) of Nc-LEDs, typically employing isotropic nanocrystals, is limited by the out-coupling factor. Here efficient, bright, and long lifetime red Nc-LEDs based on anisotropic nanocrystals of colloidal quantum wells (CQWs) are demonstrated. Through modification of the substrate's surface properties and control of the interactions among CQWs, a self-assembled layer with an exceptionally high distribution of in-plane transitions dipole moment of 95%, resulting in an out-coupling factor of 37% is successfully spin-coated. The devices exhibit a remarkable peak EQE of 26.9%, accompanied by a maximum brightness of 55 754 cd m-2 and a long operational lifetime (T95 @100 cd m-2 ) over 15 000 h. These achievements represent a significant advancement compared to previous studies on Nc-LEDs incorporating anisotropic nanocrystals. The work is expected to provide a general self-assembly strategy for enhancing the light extraction efficiency of Nc-LEDs based on anisotropic nanocrystals.

Mg-Diffusion of ZnO-Based Electron-Transport Layers for Highly Conductive Quantum-Dot Light-Emitting Diodes.

Quantum-dot light-emitting diodes (QLEDs) show great potential in next-generation display and lighting technologies. Further reducing the resistances of the high-efficiency QLEDs is critical to improving their luminous efficiencies and lowering their power consumption. However, wet-chemistry methods to improve the conductivities of ZnO-based electron-transport layers (ETLs) often lead to trade-offs in the external quantum efficiencies (EQEs) of QLEDs. Here, we report a facile approach toward highly conductive QLEDs by in situ diffusion of Mg atoms into the ZnO-based ETLs. We demonstrate that thermally evaporated Mg can spread deep into the ZnO-based ETL with a long penetration length, generating oxygen vacancies that promote the electron-transport properties. The Mg-diffused ETLs enhance the conductivities and luminous efficiencies of state-of-the-art QLEDs without sacrificing the EQEs. This strategy is applied to QLEDs with various optical architectures, leading to significant enhancements in the current densities, luminances, and luminous efficiencies. We expect that our method could be extended to other solution-processed LEDs using ZnO-based ETLs.

Ribosome profiling reveals the translational landscape and allele-specific translational efficiency in rice.

Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs. Many studies have revealed translational regulation in plants in response to various environmental stimuli. However, there have been no studies documenting the comprehensive landscape of translational regulation and allele-specific translational efficiency in multiple plant tissues, especially those of rice, a main staple crop that feeds nearly half of the world's population. Here we used RNA sequencing and ribosome profiling data to analyze the transcriptome and translatome of an elite hybrid rice, Shanyou 63 (SY63), and its parental varieties Zhenshan 97 and Minghui 63. The results revealed that gene expression patterns varied more among tissues than among varieties at the transcriptional and translational levels. We identified 3392 upstream open reading frames (uORFs), and the uORF-containing genes were enriched in transcription factors. Only 668 of 13 492 long non-coding RNAs could be translated into peptides. Finally, we discovered numerous genes with allele-specific translational efficiency in SY63 and demonstrated that some cis-regulatory elements may contribute to allelic divergence in translational efficiency. Overall, these findings may improve our understanding of translational regulation in rice and provide information for molecular breeding research.

Target-Specific Machine Learning Scoring Function Improved Structure-Based Virtual Screening Performance for SARS-CoV-2 Drugs Development.

Leveraging machine learning has been shown to improve the accuracy of structure-based virtual screening. Furthermore, a tremendous amount of empirical data is publicly available, which further enhances the performance of the machine learning approach. In this proof-of-concept study, the 3CLpro enzyme of SARS-CoV-2 was used. Structure-based virtual screening relies heavily on scoring functions. It is widely accepted that target-specific scoring functions may perform more effectively than universal scoring functions in real-world drug research and development processes. It would be beneficial to drug discovery to develop a method that can effectively build target-specific scoring functions. In the current study, the bindingDB database was used to retrieve experimental data. Smina was utilized to generate protein-ligand complexes for the extraction of InteractionFingerPrint (IFP) and SimpleInteractionFingerPrint SIFP fingerprints via the open drug discovery tool (oddt). The present study found that randomforestClassifier and randomforestRegressor performed well when used with the above fingerprints along the Molecular ACCess System (MACCS), Extended Connectivity Fingerprint (ECFP4), and ECFP6. It was found that the area under the precision-recall curve was 0.80, which is considered a satisfactory level of accuracy. In addition, our enrichment factor analysis indicated that our trained scoring function ranked molecules correctly compared to smina's generic scoring function. Further molecular dynamics simulations indicated that the top-ranked molecules identified by our developed scoring function were highly stable in the active site, supporting the validity of our developed process. This research may provide a template for developing target-specific scoring functions against specific enzyme targets.

Boosting performance of Co-free Li-rich cathode material through regulating the anionic activity by means of the strong TaO bonding.

Benefiting from the extra contribution of O redox, Co-free Li-rich layered oxides (LRNMO) can satisfy the requirement of high specific capacities. However, during the high-voltage charging process, lattice oxygen being oxidized to O- or O2 leads to a gradual transition of the structure from layered to spinel phase, capacity and voltage decline, hindering the practical application of LRNMO in the lithium-ion battery. Here, a surface modification strategy of Li1.2Ni0.32Mn0.48O2-δ doped with Ta5+ ions is proposed, in which the Ta5+ ions occupy the lithium sites of the lattice structure on the surface layer of LRNMO and form a Ta2O5 coating layer. The modified electrode exhibits excellent rate performance and cycling stability, with 94.9% and 85.5% capacity retention rate and voltage retention rate, respectively, after 200 cycles at 1C. Moreover, the initial coulomb efficiency and ionic conductivity of the modified electrode are also apparently enhanced. Simultaneously, the decreased Li/Ni mixing degree of the modified electrode reflects the improvement of the structural stability. Therefore, the modification strategy through strong metal-oxygen bonding to integrate the surface structure to regulate the oxygen activity provides a new direction for the design of high energy density Co-free Li-rich cathode materials.

Evolution Analyses of CAMTA Transcription Factor in Plants and Its Enhancing Effect on Cold-tolerance.

The calmodulin binding transcription activator (CAMTA) is a transcription factor that is widely present in eukaryotes with conserved structure. It contributes to the response to biotic and abiotic stresses and promotes the growth and development of plants. Although previous studies have investigated the number and function of CAMTAs in some species, there is still a lack of comprehensive understanding of the evolutionary process, phylogenetic relationship, expression patterns, and functions of CAMTAs in plants. Here we identified 465 CMATA genes from 112 plants and systematically studied the origin of CAMTA family, gene expansion, functional differentiation, gene structure, and conservative motif distribution. Based on these analyses, we presented the evidence that CAMTA family was originated from chlorophyta, and we speculated that CAMTA might experience obvious structure variation during its early evolution, and that the number of CAMTA genes might gradually increase in higher plants. To reveal potential functions of CAMTA genes, we analyzed the expression patterns of 12 representative species and found significant species specificity, tissue specificity, and developmental stage specificity of CAMTAs. The results also indicated that the CAMTA genes might promote the maturation and senescence. The expression levels and regulatory networks of CAMTAs revealed that CAMTAs could enhance cold tolerance of rice by regulating carbohydrate metabolism-related genes to accumulate carbohydrates or by modulating target genes together with other transcription factors. Our study provides an insight into the molecular evolution of CAMTA family and lays a foundation for further study of related biological functions.

Two gap-free reference genomes and a global view of the centromere architecture in rice.

Rice (Oryza sativa), a major staple throughout the world and a model system for plant genomics and breeding, was the first crop genome sequenced almost two decades ago. However, reference genomes for all higher organisms to date contain gaps and missing sequences. Here, we report the assembly and analysis of gap-free reference genome sequences for two elite O. sativa xian/indica rice varieties, Zhenshan 97 and Minghui 63, which are being used as a model system for studying heterosis and yield. Gap-free reference genomes provide the opportunity for a global view of the structure and function of centromeres. We show that all rice centromeric regions share conserved centromere-specific satellite motifs with different copy numbers and structures. In addition, the similarity of CentO repeats in the same chromosome is higher than across chromosomes, supporting a model of local expansion and homogenization. Both genomes have over 395 non-TE genes located in centromere regions, of which ∼41% are actively transcribed. Two large structural variants at the end of chromosome 11 affect the copy number of resistance genes between the two genomes. The availability of the two gap-free genomes lays a solid foundation for further understanding genome structure and function in plants and breeding climate-resilient varieties.

Analysis of Rice Transcriptome Reveals the LncRNA/CircRNA Regulation in Tissue Development.

BACKGROUND: Long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) can play important roles in many biological processes. However, no study of the influence of epigenetics factors or the 3D structure of the genome in their regulation is available in plants. RESULTS: In the current analysis, we identified a total of 15,122 lncRNAs and 7902 circRNAs in three tissues (root, leaf and panicle) in the rice varieties Minghui 63, Zhenshan 97 and their hybrid Shanyou 63. More than 73% of these lncRNAs and parental genes of circRNAs (P-circRNAs) are shared among Oryza sativa with high expression specificity. We found that, compared with protein-coding genes, the loci of these lncRNAs have higher methylation levels and the loci of circRNAs tend to locate in the middle of genes with high CG and CHG methylation. Meanwhile, the activated lncRNAs and P-circRNAs are mainly transcribed from demethylated regions containing CHH methylation. In addition, ~ 53% lncRNAs and ~ 15% P-circRNAs are associated with transposable elements (TEs), especially miniature inverted-repeat transposable elements and RC/Helitron. We didn't find correlation between the expression of lncRNAs and histone modifications; however, we found that the binding strength and interaction of RNAPII significantly affects lncRNA expression. Interestingly, P-circRNAs tend to combine active histone modifications. Finally, we found that lncRNAs and circRNAs acting as competing-endogenous RNAs have the potential to regulate the expression of genes, such as osa-156 l-5p (related to yield) and osa-miR444a-3p (related to N/P metabolism) confirmed through dual-luciferase reporter assays, with important roles in the growth and development of rice, laying a foundation for future rice breeding analyses. CONCLUSIONS: In conclusion, our study comprehensively analyzed the important regulatory roles of lncRNA/circRNA in the tissue development of Indica rice from multiple perspectives.

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches.

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world's population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.

Selection of a subspecies-specific diterpene gene cluster implicated in rice disease resistance.

Diterpenoids are the major group of antimicrobial phytoalexins in rice1,2. Here, we report the discovery of a rice diterpenoid gene cluster on chromosome 7 (DGC7) encoding the entire biosynthetic pathway to 5,10-diketo-casbene, a member of the monocyclic casbene-derived diterpenoids. We revealed that DGC7 is regulated directly by JMJ705 through methyl jasmonate-mediated epigenetic control3. Functional characterization of pathway genes revealed OsCYP71Z21 to encode a casbene C10 oxidase, sought after for the biosynthesis of an array of medicinally important diterpenoids. We further show that DGC7 arose relatively recently in the Oryza genus, and that it was partly formed in Oryza rufipogon and positively selected for in japonica during domestication. Casbene-synthesizing enzymes that are functionally equivalent to OsTPS28 are present in several species of Euphorbiaceae but gene tree analysis shows that these and other casbene-modifying enzymes have evolved independently. As such, combining casbene-modifying enzymes from these different families of plants may prove effective in producing a diverse array of bioactive diterpenoid natural products.

Pan-genome: A promising resource for noncoding RNA discovery in plants.

Plant genomes contain both protein-coding and noncoding sequences including transposable elements (TEs) and noncoding RNAs (ncRNAs). The ncRNAs are recognized as important elements that play fundamental roles in the structural organization and function of plant genomes. Despite various hypotheses, TEs are believed to be a major precursor of ncRNAs. Transposable elements are also prime factors that cause genomic variation among members of a species. Hence, TEs pose a major challenge in the discovery and analysis of ncRNAs. With the increase in the number of sequenced plant genomes, it is now accepted that a single reference genome is insufficient to represent the complete genomic diversity and contents of a species, and exploring the pan-genome of a species is critical. In this review, we summarize the recent progress in the field of plant pan-genomes. We also discuss TEs and their roles in ncRNA biogenesis and present our perspectives on the application of pan-genomes for the discovery of ncRNAs to fully explore and exploit their biological roles in plants.

ppsPCP: a plant presence/absence variants scanner and pan-genome construction pipeline.

SUMMARY: Since the idea of pan-genomics emerged several tools and pipelines have been introduced for prokaryotic pan-genomics. However, not a single comprehensive pipeline has been reported which could overcome multiple challenges associated with eukaryotic pan-genomics. To aid the eukaryotic pan-genomic studies, here we present ppsPCP pipeline which is designed for eukaryotes especially for plants. It is capable of scanning presence/absence variants (PAVs) and constructing a fully annotated pan-genome. We believe with these unique features of PAV scanning and building a pan-genome together with its annotation, ppsPCP will be useful for plant pan-genomic studies and aid researchers to study genetic/phenotypic variations and genomic diversity. AVAILABILITY AND IMPLEMENTATION: The ppsPCP is freely available at github DOI: https://doi.org/10.5281/zenodo.2567390 and webpage http://cbi.hzau.edu.cn/ppsPCP/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.