Time-course transcriptome analysis identifies rewiring patterns of transcriptional regulatory networks in rice under Rhizoctonia solani infection

ETENLNC: An end to end lncRNA identification and analysis framework to facilitate construction of known and novel lncRNA regulatory networks

Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-throughput platforms has opened possibilities to identify, predict, and functionally annotate lncRNAs. As a result, there is a growing demand for an integrative computational framework capable of identifying known lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding), a user-friendly, integrative, open-source, scalable, and modular computational framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC employs six stringent filtration steps to identify novel lncRNAs, performs differential expression analysis of mRNA and lncRNA transcripts, and predicts regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked ETENLNC against six existing tools and optimized it for desktop workstations and high-performance computing environments using data from three different species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.

Comparative Field Evaluation and Transcriptome Analysis Reveals that Chromosome Doubling Enhances Sheath Blight Resistance in Rice

Rice sheath blight, caused by Rhizoctonia solani Kihn (R. solani), poses a significant threat to rice production and quality. Autotetraploid rice, developed through chromosome doubling of diploid rice, holds great potential for enhancing biological and yield traits. However, its resistance to sheath blight in the field has remained unclear. In this study, the field resistance of 35 autotetraploid genotypes and corresponding diploids was evaluated across three environments from 2020 to 2021. The booting stage was optimal for inoculating period based on the inoculation and analysis of R. solani at five rice growth stages. We found autotetraploids generally exhibited lower disease scores than diploids, indicating enhanced resistance after chromosome doubling. Among the 35 genotypes, 16 (45.71%) displayed increased resistance, 2 (5.71%) showed decreased resistance, and 17 (48.57%) displayed unstable resistance in different sowing dates. All combinations of the genotype, environment and ploidy, including the genotype-environment-ploidy interaction, contributed significantly to field resistance. Chromosome doubling increased sheath blight resistance in most genotypes, but was also dependent on the genotype-environment interaction. To elucidate the enhanced resistance mechanism, RNA-seq revealed autotetraploid recruited more down-regulated differentially expressed genes (DEGs), additionally, more resistance-related DEGs, were down-regulated at 24 h post inoculation in autotetraploid versus diploid. The ubiquinone/terpenoid quinone and diterpenoid biosynthesis pathways may play key roles in ploidy-specific resistance mechanisms. In summary, our findings shed light on the understanding of sheath blight resistance mechanisms in autotetraploid rice.

OsEIL2 balances rice immune responses against (hemi)biotrophic and necrotrophic pathogens via the salicylic acid and jasmonic acid synergism

Plants typically activate distinct defense pathways against various pathogens. Heightened resistance to one pathogen often coincides with increased susceptibility to another pathogen. However, the underlying molecular basis of this antagonistic response remains unclear. Here, we demonstrate that mutants defective in the transcription factor ETHYLENE-INSENSITIVE 3-LIKE 2 (OsEIL2) exhibited enhanced resistance to the biotrophic bacterial pathogen Xanthomonas oryzae pv oryzae and to the hemibiotrophic fungal pathogen Magnaporthe oryzae, but enhanced susceptibility to the necrotrophic fungal pathogen Rhizoctonia solani. Furthermore, necrotroph-induced OsEIL2 binds to the promoter of OsWRKY67 with high affinity, leading to the upregulation of salicylic acid (SA)/jasmonic acid (JA) pathway genes and increased SA/JA levels, ultimately resulting in enhanced resistance. However, biotroph- and hemibiotroph-induced OsEIL2 targets OsERF083, resulting in the inhibition of SA/JA pathway genes and decreased SA/JA levels, ultimately leading to reduced resistance. Our findings unveil a previously uncharacterized defense mechanism wherein two distinct transcriptional regulatory modules differentially mediate immunity against pathogens with different lifestyles through the transcriptional reprogramming of phytohormone pathway genes.

Development of activation-tagged gain-of-functional mutants in indica rice line (BPT 5204) for sheath blight resistance

BACKGROUND

The development of sheath blight (ShB) resistance varieties has been a challenge for scientists for long time in rice. Activation tagging is an efficient gain-of-function mutation approach to create novel phenotypes and to identify their underlying genes. In this study, a mutant population was developed employing activation tagging in the recalcitrant indica rice (Oryza sativa L.) cv. BPT 5204 (Samba Mahsuri) through activation tagging.

METHODS AND RESULTS

In this study, we have generated more than 1000 activation tagged lines in indica rice, from these mutant population 38 (GFP- RFP+) stable Ds plants were generated through germinal transposition at T2 generation based on molecular analysis and seeds selected on hygromycin (50 mg/L) containing medium segregation analyses confirmed that the transgene inherited as mendelian segregation ratio of 3:1 (3 resistant: 1 susceptible). Of them, five stable activation tagged Ds lines (M-Ds-1, M-Ds-2, M-Ds-3, M-Ds-4 and M-Ds-5) were selected based on phenotypic observation through screening for sheath blight (ShB) resistance caused by fungal pathogen Rhizoctonia solani (R. solani),. Among them, M-Ds-3 and M-Ds-5 lines showed significant resistance for ShB over other tagged lines and wild type (WT) plants. Furthermore, analysed for launch pad insertion through TAIL-PCR results and mapped on corresponding rice chromosomes. Flanking sequence and gene expression analysis revealed that the upregulation of glycoside hydrolase-OsGH or similar to Class III chitinase homologue (LOC_Os08g40680) in M-Ds-3 and a hypothetical protein gene (LOC_Os01g55000) in M-Ds-5 are potential candidate genes for sheath blight resistance in rice.

CONCLUSION

In the present study, we developed Ac-Ds based ShB resistance gain-of-functional mutants through activation tagging in rice. These activation tagged mutant lines can be excellent sources for the development of ShB resistant cultivars in rice.

Predicting rice diseases using advanced technologies at different scales: present status and future perspectives

The past few years have witnessed significant progress in emerging disease detection techniques for accurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focus on image processing techniques using machine learning (ML) and deep learning (DL) models related to multi-scale rice diseases. Furthermore, we summarize applications of different detection techniques, including genomic, physiological, and biochemical approaches. In addition, we also present the state-of-the-art in contemporary optical sensing applications of pathogen-plant interaction phenotypes. This review serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice crops through ML and DL models.

Cytological observation and transcriptome analysis reveal dynamic changes of Rhizoctonia solani colonization on leaf sheath and different genes recruited between the resistant and susceptible genotypes in rice

Sheath blight, caused by Rhizoctonia solani, is a big threat to the global rice production. To characterize the early development of R. solani on rice leaf and leaf sheath, two genotypes, GD66 (a resistant genotype) and Lemont (a susceptible genotype), were observed using four cytological techniques: the whole-mount eosin B-staining confocal laser scanning microscopy (WE-CLSM), stereoscopy, fluorescence microscopy, and plastic semi-thin sectioning after in vitro inoculation. WE-CLSM observation showed that, at 12 h post-inoculation (hpi), the amount of hyphae increased dramatically on leaf and sheath surface, the infection cushions occurred and maintained at a huge number from about 18 to 36 hpi, and then the infection cushions disappeared gradually from about 42 to 72 hpi. Interestingly, R. solani could not only colonize on the abaxial surfaces of leaf sheath but also invade the paraxial side of the leaf sheath, which shows a different behavior from that of leaf. RNA sequencing detected 6,234 differentially expressed genes (DEGs) for Lemont and 7,784 DEGs for GD66 at 24 hpi, and 2,523 DEGs for Lemont and 2,719 DEGs for GD66 at 48 hpi, suggesting that GD66 is recruiting more genes in fighting against the pathogen. Among DEGs, resistant genes, such as OsRLCK5, Xa21, and Pid2, displayed higher expression in the resistant genotype than the susceptible genotype at both 24 and 48 hpi, which were validated by quantitative reverse transcription-PCR. Our results indicated that the resistance phenotype of GD66 was the consequence of recruiting a series of resistance genes involved in different regulatory pathways. WE-CLSM is a powerful technique for uncovering the mechanism of R. solani invading rice and for detecting rice sheath blight-resistant germplasm.