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Epitranscriptome constitutes a gene expression checkpoint in all living organisms. Nitrogen is an essential element for plant growth and development that influences gene expression at different levels such as epigenome, transcriptome, proteome, and metabolome. Therefore, our hypothesis is that changes in the epitranscriptome may regulate nitrogen metabolism. In this study, epitranscriptomic modifications caused by ammonium nutrition were monitored in maritime pine roots using Oxford Nanopore Technology. Transcriptomic responses mainly affected transcripts involved in nitrogen and carbon metabolism, defense, hormone synthesis/signaling, and translation. Global detection of epitranscriptomic marks was performed to evaluate this posttranscriptional mechanism in un/treated seedlings. Increased N6-methyladenosine (m6A) deposition in the 3’-UTR was observed in response to ammonium, which seems to be correlated with poly(A) lengths and changes in the relative abundance of the corresponding proteins. The results showed that m6A deposition and its dynamics seem to be important regulators of translation under ammonium nutrition. These findings suggest that protein translation is finely regulated through epitranscriptomic marks likely by changes in mRNA poly(A) length, transcript abundance and ribosome protein composition. An integration of multiomics data suggests that the epitranscriptome modulates responses to nutritional, developmental and environmental changes through buffering, filtering, and focusing the final products of gene expression.

Embryogenesis is a complex phase of conifer development involving hundreds of genes, and a proper understanding of this process is critical not only to produce embryos with different applied purposes but also for comparative studies with angiosperms. A global view of transcriptome dynamics during pine somatic and zygotic embryogenesis is currently missing. Here, we present a genome-wide transcriptome analysis of somatic and zygotic embryos at three developmental stages to identify conserved biological processes and gene functions during late embryogenesis. Most of the differences became more significant as the developmental process progressed from early to cotyledonary stages, and a higher number of genes were differentially expressed in somatic than in zygotic embryos. Metabolic pathways substantially affected included those involved in amino acid biosynthesis and utilization, and this difference was already observable at early developmental stages. Overall, this effect was found to be independent of the line (genotype) used to produce the somatic embryos. Additionally, transcription factors differentially expressed in somatic versus zygotic embryos were analyzed. Some potential hub regulatory genes were identified that can provide clues as to what transcription factors are controlling the process and to how the observed differences between somatic and zygotic embryogenesis in conifers could be regulated.

Background: Alternative Splicing (AS) is a post-transcriptional process that allows a single RNA to produce different mRNA variants and, in some cases, multiple proteins. Various processes, many yet to be discovered, regulate AS. This study focuses on regulation by RNA-binding proteins (RBPs), which are not only crucial for splicing regulation but also linked to cancer prognosis and are emerging as therapeutic targets for cancer treatment. CLIP-seq experiments help identify where RBPs bind on nascent transcripts, potentially revealing changes in splicing status that suggest causal relationships. Selecting specific RBPs for CLIP-seq experiments is often driven by a priori hypotheses. Results: We developed an algorithm to detect RBPs likely related to splicing changes between conditions by integrating several CLIP-seq databases and a differential splicing detection algorithm. This work refines a previous study by improving splicing event prediction, testing different enrichment statistics, and performing additional validation experiments. The new method provides more accurate predictions and is included in the Bioconductor package EventPointer 3.14. We tested the algorithm in four experiments involving knockdowns of seven different RBPs. The algorithm accurately assessed the statistical significance of these RBPs using only splicing alterations. Additionally, we applied the algorithm to study sixteen cancer types from The Cancer Genome Atlas (TCGA) and three from TARGET. We identified relationships between RBPs and various cancer types, including alterations in CREBBP and MBNL2 in adenocarcinomas of the lung, liver, prostate, rectum, stomach, and colon. Some of these findings are validated in the literature, while others are novel. Conclusions: The developed algorithm enhances the ability to predict and understand RBP-related splicing changes, offering more accurate predictions and novel insights into cancer-related splicing alterations. This work highlights the potential of RBPs as therapeutic targets and contributes to the broader understanding of their roles in cancer biology.