Mutations in the X chromosomal tRNA 2'‑O‑methyltransferase FTSJ1 cause intellectual disability (ID). Although the gene is ubiquitously expressed affected individuals present no consistent clinical features beyond ID. In order to study the pathological mechanism involved in the aetiology of FTSJ1 deficiency-related cognitive impairment, we generated and characterized an Ftsj1 deficient mouse line based on the gene trapped stem cell line RRD143. Apart from an impaired learning capacity these mice presented with several statistically significantly altered features related to behaviour, pain sensing, bone and energy metabolism, the immune and the hormone system as well as gene expression. These findings show that Ftsj1 deficiency in mammals is not phenotypically restricted to the brain but affects various organ systems. Re-examination of ID patients with FTSJ1 mutations from two previously reported families showed that several features observed in the mouse model were recapitulated in some of the patients. Though the clinical spectrum related to Ftsj1 deficiency in mouse and man is variable, we suggest that an increased pain threshold may be more common in patients with FTSJ1 deficiency. Our findings demonstrate novel roles for Ftsj1 in maintaining proper cellular and tissue functions in a mammalian organism.

The role of the tRNA methyltransferase FTSJ1 in the brain is largely unknown. We analyzed whether FTSJ1-deficient mice (KO) displayed altered neuronal plasticity. We explored open field behavior (10 KO mice (aged 22–25 weeks)) and 11 age-matched control littermates (WT) and examined mean layer thickness (7 KO; 6 WT) and dendritic spines (5 KO; 5 WT) in the hippocampal area CA1 and the dentate gyrus. Furthermore, long-term potentiation (LTP) within area CA1 was investigated (5 KO; 5 WT), and mass spectrometry (MS) using CA1 tissue (2 each) was performed. Compared to controls, KO mice showed a significant reduction in the mean thickness of apical CA1 layers. Dendritic spine densities were also altered in KO mice. Stable LTP could be induced in the CA1 area of KO mice and remained stable at for at least 1 h, although at a lower level as compared to WTs, while MS data indicated differential abundance of several proteins, which play a role in neuronal plasticity. FTSJ1 has an impact on neuronal plasticity in the murine hippocampal area CA1 at the morphological and physiological levels, which, in conjunction with comparable changes in other cortical areas, might accumulate in disturbed learning and memory functions.

C-mannosylation is a modification of tryptophan residues with a single mannose and can affect protein folding, secretion, and/or function. To date, only a few proteins have been demonstrated to be C-mannosylated, and studies that globally assess protein C-mannosylation are scarce. To interrogate the C-mannosylome of human induced pluripotent stem cells, we compared the secretomes of CRISPR-Cas9 mutants lacking either the C-mannosyltransferase DPY19L1 or DPY19L3 to WT human induced pluripotent stem cells using MS-based quantitative proteomics. The secretion of numerous proteins was reduced in these mutants, including that of A Disintegrin And Metalloproteinase with ThromboSpondin Motifs 16 (ADAMTS16), an extracellular protease that was previously reported to be essential for optic fissure fusion in zebrafish eye development. To test the functional relevance of this observation, we targeted dpy19l1 or dpy19l3 in embryos of the Japanese rice fish medaka (Oryzias latipes) by CRISPR-Cas9. We observed that targeting of dpy19l3 partially caused defects in optic fissure fusion, called coloboma. We further showed in a cellular model that DPY19L1 and DPY19L3 mediate C-mannosylation of a recombinantly expressed thrombospondin type 1 repeat of ADAMTS16 and thereby support its secretion. Taken together, our findings imply that DPY19L3-mediated C-mannosylation is involved in eye development by assisting secretion of the extracellular protease ADAMTS16.

Non-coding RNA (ncRNA) classes take over important housekeeping and regulatory functions and are quite heterogeneous in terms of length, sequence conservation and secondary structure. High-throughput sequencing reveals that the expressed novel ncRNAs and their classification are important to understand cell regulation and identify potential diagnostic and therapeutic biomarkers. To improve the classification of ncRNAs, we investigated different approaches of utilizing primary sequences and secondary structures as well as the late integration of both using machine learning models, including different neural network architectures. As input, we used the newest version of RNAcentral, focusing on six ncRNA classes, including lncRNA, rRNA, tRNA, miRNA, snRNA and snoRNA. The late integration of graph-encoded structural features and primary sequences in our MncR classifier achieved an overall accuracy of >97%, which could not be increased by more fine-grained subclassification. In comparison to the actual best-performing tool ncRDense, we had a minimal increase of 0.5% in all four overlapping ncRNA classes on a similar test set of sequences. In summary, MncR is not only more accurate than current ncRNA prediction tools but also allows the prediction of long ncRNA classes (lncRNAs, certain rRNAs) up to 12.000 nts and is trained on a more diverse ncRNA dataset retrieved from RNAcentral.