The Long Read Transcriptome of Rice (Oryza sativa ssp. japonica var. Nipponbare) Reveals Novel Transcripts

Roles and regulatory patterns of protein isoforms in plant adaptation and development

Protein isoforms (PIs) play pivotal roles in regulating plant growth and development that confer adaptability to diverse environmental conditions. PIs are widely present in plants and generated through alternative splicing (AS), alternative polyadenylation (APA), alternative initiation (AI), and ribosomal frameshifting (RF) events. The widespread presence of PIs not only significantly increases the complexity of genomic information but also greatly enriches regulatory networks and enhances their flexibility. PIs may also play important roles in phenotypic diversity, ecological niche differentiation, and speciation, thereby increasing the dimensions of research in molecular ecology. However, PIs pose new challenges for the quantitative analysis, annotation, and identification of genetic regulatory mechanisms. Thus, focus on PIs make genomic and epigenomic studies both more powerful and more challenging. This review summarizes the origins, functions, regulatory patterns of isoforms, and the challenges they present for future research in molecular ecology and molecular biology.

The landscape of fusion transcripts in plants: a new insight into genome complexity

BACKGROUND

Fusion transcripts (FTs), generated by the fusion of genes at the DNA level or RNA-level splicing events significantly contribute to transcriptome diversity. FTs are usually considered unique features of neoplasia and serve as biomarkers and therapeutic targets for multiple cancers. The latest findings show the presence of FTs in normal human physiology. Several discrete reports mentioned the presence of fusion transcripts in planta, has important roles in stress responses, morphological alterations, or traits (e.g. seed size, etc.).

RESULTS

In this study, we identified 169,197 fusion transcripts in 2795 transcriptome datasets of Arabidopsis thaliana, Cicer arietinum, and Oryza sativa by using a combination of tools, and confirmed the translational activity of 150 fusion transcripts through proteomic datasets. Analysis of the FT junction sequences and their association with epigenetic factors, as revealed by ChIP-Seq datasets, demonstrated an organised process of fusion formation at the DNA level. We investigated the possible impact of three-dimensional chromatin conformation on intra-chromosomal fusion events by leveraging the Hi-C datasets with the incidence of fusion transcripts. We further utilised the long-read RNA-Seq datasets to validate the most reoccurring fusion transcripts in each plant species followed by further authentication through RT-PCR and Sanger sequencing.

CONCLUSIONS

Our findings suggest that a significant portion of fusion events may be attributed to alternative splicing during transcription, accounting for numerous fusion events without a proportional increase in the number of RNA pairs. Even non-nuclear DNA transcripts from mitochondria and chloroplasts can participate in intra- and inter-chromosomal fusion formation. Genes in close spatial proximity are more prone to undergoing fusion formation, especially in intra-chromosomal FTs. Most of the fusion transcripts may not undergo translation and serve as long non-coding RNAs. The low validation rate of FTs in plants indicated that the fusion transcripts are expressed at very low levels, like in the case of humans. FTs often originate from parental genes involved in essential biological processes, suggesting their relevance across diverse tissues and stress conditions. This study presents a comprehensive repository of fusion transcripts, offering valuable insights into their roles in vital physiological processes and stress responses.

PFusionDB: a comprehensive database of plant-specific fusion transcripts

Fusion transcripts (FTs) are well known cancer biomarkers, relatively understudied in plants. Here, we developed PFusionDB (www.nipgr.ac.in/PFusionDB), a novel plant-specific fusion-transcript database. It is a comprehensive repository of 80,170, 39,108, 83,330, and 11,500 unique fusions detected in 1280, 637, 697, and 181 RNA-Seq samples of Arabidopsis thaliana, Oryza sativa japonica, Oryza sativa indica, and Cicer arietinum respectively. Here, a total of 76,599 (Arabidopsis thaliana), 35,480 (Oryza sativa japonica), 72,099 (Oryza sativa indica), and 9524 (Cicer arietinum) fusion transcripts are non-recurrent i.e., only found in one sample. Identification of FTs was performed by using a total of five tools viz. EricScript-Plants, STAR-Fusion, TrinityFusion, SQUID, and MapSplice. At PFusionDB, available fundamental details of fusion events includes the information of parental genes, junction sequence, expression levels of fusion transcripts, breakpoint coordinates, strand information, tissue type, treatment information, fusion type, PFusionDB ID, and Sequence Read Archive (SRA) ID. Further, two search modules: 'Simple Search' and 'Advanced Search', along with a 'Browse' option to data download, are present for the ease of users. Three distinct modules viz. 'BLASTN', 'SW Align', and 'Mapping' are also available for efficient query sequence mapping and alignment to FTs. PFusionDB serves as a crucial resource for delving into the intricate world of fusion transcript in plants, providing researchers with a foundation for further exploration and analysis. Database URL: www.nipgr.ac.in/PFusionDB.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04132-1.

Transcriptome-wide N6-methyladenosine profiling reveals growth-defense trade-offs in the response of rice to brown planthopper (Nilaparvata lugens) infestation

BACKGROUND

N6-Methyladenosine (m6A) is a common messenger RNA (mRNA) modification that affects various physiological processes in stress responses. However, the role of m6A modifications in plants responses to herbivore stress remains unclear.

RESULTS

Here, we found that an infestation of brown planthopper (Nilaparvata lugens) female adults enhanced the resistance of rice to N. lugens. The m6A methylome analysis of N. lugens-infested and uninfested rice samples was performed to explore the interaction between rice and N. lugens. The m6A methylation mainly occurred in genes that were actively expressed in rice following N. lugens infestation, while an analysis of the whole-genomic mRNA distribution of m6A showed that N. lugens infestation caused an overall decrease in the number of m6A methylation sites across the chromosomes. The m6A methylation of genes involved in the m6A modification machinery and several defense-related phytohormones (jasmonic acid and salicylic acid) pathways was increased in N. lugens-infested rice compared to that in uninfested rice. In contrast, m6A modification levels of growth-related phytohormone (auxin and gibberellin) biosynthesis-related genes were significantly attenuated during N. lugens infestation, accompanied by the down-regulated expression of these transcripts, indicating that rice growth was restricted during N. lugens attack to rapidly optimize resource allocation for plant defense. Integrative analysis of the differential patterns of m6A methylation and the corresponding transcripts showed a positive correlation between m6A methylation and transcriptional regulation.

CONCLUSION

The m6A modification is an important strategy for regulating the expression of genes involved in rice defense and growth during rice-N. lugens interactions. These findings provide new ideas for formulating strategies to control herbivorous pests. © 2024 Society of Chemical Industry.

Exploring the hidden hot world of long non-coding RNAs in thermophilic fungus using a robust computational pipeline

Long noncoding RNAs (lncRNAs) are versatile RNA molecules recently identified as key regulators of gene expression in response to environmental stress. Our primary focus in this study was to develop a robust computational pipeline for identifying structurally identical lncRNAs across replicates from publicly available bulk RNA-seq datasets. In order to demonstrate the effectiveness of the pipeline, we utilized the transcriptome of the thermophilic fungus Thermothelomyces thermophilus and assessed the expression pattern of lncRNAs in conjunction with Heat Shock Proteins (HSP), a well-known protein family critical for the cell's response to high temperatures. Our findings demonstrate that the identification of structurally identical transcripts among replicates in this thermophilic fungus ensures the reliability and accuracy of RNA studies, contributing to the validity of biological interpretations. Furthermore, the majority of lncRNAs exhibited a distinct expression pattern compared to HSPs. Our study contributes to advancing the understanding of the biological mechanisms comprising lncRNAs in thermophilic fungi.

SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms

The emergence of long-read RNA sequencing (lrRNA-seq) has provided an unprecedented opportunity to analyze transcriptomes at isoform resolution. However, the technology is not free from biases, and transcript models inferred from these data require quality control and curation. In this study, we introduce SQANTI3, a tool specifically designed to perform quality analysis on transcriptomes constructed using lrRNA-seq data. SQANTI3 provides an extensive naming framework to describe transcript model diversity in comparison to the reference transcriptome. Additionally, the tool incorporates a wide range of metrics to characterize various structural properties of transcript models, such as transcription start and end sites, splice junctions, and other structural features. These metrics can be utilized to filter out potential artifacts. Moreover, SQANTI3 includes a Rescue module that prevents the loss of known genes and transcripts exhibiting evidence of expression but displaying low-quality features. Lastly, SQANTI3 incorporates IsoAnnotLite, which enables functional annotation at the isoform level and facilitates functional iso-transcriptomics analyses. We demonstrate the versatility of SQANTI3 in analyzing different data types, isoform reconstruction pipelines, and sequencing platforms, and how it provides novel biological insights into isoform biology. The SQANTI3 software is available at https://github.com/ConesaLab/SQANTI3 .

High-quality reference transcriptome construction improves RNA-seq quantification in Oryza sativa indica

The Reference Transcriptomic Dataset (RTD) is an accurate and comprehensive collection of transcripts originating from a given organism. It holds the key to precise transcript quantification and downstream analysis of differential expressions and regulations. Currently, transcriptome annotations for most crop plants are far from complete. For example, Oryza sativa indica (O. sativa indica) is reported to have 40,759 transcripts in the Ensembl database without alternative transcript isoforms and alternative splicing (AS) events. To generate a high-quality RTD, we conducted RNA sequencing of rice leaf samples collected at various time points during Rhizoctonia solani infection. The obtained reads were analyzed by adopting the recently developed computational analysis pipeline to assemble the RTD with increased transcript and AS diversity for O. sativa indica (IndicaRTD). After stringent quality filtering, the newly constructed transcriptome annotation was comprised of 122,968 non-redundant transcripts from 53,695 genes. This study identified many novel transcripts compared to Ensembl deposited data that are important for regulating molecular and physiological processes in the plant system. Currently, the assembled IndicaRTD must allow fast quantification of transcript and gene expression with high precision.