Machine learning algorithm for precise prediction of 2’-O-methylation (Nm) sites from experimental RiboMethSeq datasets

The essential roles of small non-coding RNAs and RNA modifications in normal and malignant hematopoiesis

Hematopoietic stem cells (HSCs) developing from mesoderm during embryogenesis are important for the blood circulatory system and immune system. Many factors such as genetic factors, chemical exposure, physical radiation, and viral infection, can lead to the dysfunction of HSCs. Hematological malignancies (involving leukemia, lymphoma, and myeloma) were diagnosed in more than 1.3 million people globally in 2021, taking up 7% of total newly-diagnosed cancer patients. Although many treatments like chemotherapy, bone marrow transplantation, and stem cell transplantation have been applied in clinical therapeutics, the average 5-year survival rate for leukemia, lymphoma, and myeloma is about 65%, 72%, and 54% respectively. Small non-coding RNAs play key roles in a variety of biological processes, including cell division and proliferation, immunological response and cell death. With the development of technologies in high-throughput sequencing and bioinformatic analysis, there is emerging research about modifications on small non-coding RNAs, as well as their functions in hematopoiesis and related diseases. In this study, we summarize the updated information of small non-coding RNAs and RNA modifications in normal and malignant hematopoiesis, which sheds lights into the future application of HSCs into the treatment of blood diseases.

RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication

Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications (RMs) and multiple human diseases, but distinguishing the functional or disease-related single nucleotide variants (SNVs) from the majority of 'silent' variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetic variants and RMs concerning human disease pathogenesis. In this work, we present RMDisease v2.0, an updated database with expanded coverage. Using deep learning models and from 873 819 experimentally validated RM sites, we identified a total of 1 366 252 RM-associated variants that may affect (add or remove an RM site) 16 different types of RNA modifications (m6A, m5C, m1A, m5U, Ψ, m6Am, m7G, A-to-I, ac4C, Am, Cm, Um, Gm, hm5C, D and f5C) in 20 organisms (human, mouse, rat, zebrafish, maize, fruit fly, yeast, fission yeast, Arabidopsis, rice, chicken, goat, sheep, pig, cow, rhesus monkey, tomato, chimpanzee, green monkey and SARS-CoV-2). Among them, 14 749 disease- and 2441 trait-associated genetic variants may function via the perturbation of epitranscriptomic markers. RMDisease v2.0 should serve as a useful resource for studying the genetic drivers of phenotypes that lie within the epitranscriptome layer circuitry, and is freely accessible at: www.rnamd.org/rmdisease2.

Quantification of substoichiometric modification reveals global tsRNA hypomodification, preferences for angiogenin-mediated tRNA cleavage, and idiosyncratic epitranscriptomes of human neuronal cell-lines

Modification of tRNA is an integral part of the epitranscriptome with a particularly pronounced potential to generate diversity in RNA expression. Eukaryotic tRNA contains modifications in up to 20% of their nucleotides, but not all sites are always fully modified. Combinations and permutations of partially modified sites in tRNAs can generate a plethora of tRNA isoforms, termed modivariants. Here, we investigate the stoichiometry of incompletely modified sites in tRNAs from human cell lines for their information content. Using a panel of RNA modification mapping methods, we assess the stoichiometry of sites that contain the modifications 5-methylcytidine (m5C), 2'-O-ribose methylation (Nm), 3-methylcytidine (m3C), 7-methylguanosine (m7G), and Dihydrouridine (D). We discovered that up to 75% of sites can be incompletely modified and that the differential modification status of a cellular tRNA population holds information that allows to discriminate e.g. different cell lines. As a further aspect, we investigated potential causal connectivity between tRNA modification and its processing into tRNA fragments (tiRNAs and tRFs). Upon exposure of cultured living cells to cell-penetrating angiogenin, the modification patterns of the corresponding RNA populations was changed. Importantly, we also found that tsRNAs were significantly less modified than their parent tRNAs at numerous sites, suggesting that tsRNAs might derive chiefly from hypomodified tRNAs.