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Dynamics of tRNA fragments and their targets in aging mammalian brain.

ABSTRACT: Background: The progress of next-generation sequencing technologies has unveiled various non-coding RNAs that have previously been considered products of random degradation and attracted only minimal interest. Among small RNA families, microRNA (miRNAs) have traditionally been considered key post-transcriptional regulators. However, recent studies have reported evidence for widespread presence of fragments of tRNA molecules (tRFs) across a range of organisms and tissues, and of tRF involvement in Argonaute complexes. Methods:To elucidate potential tRF functionality, we compared available RNA sequencing datasets derived from the brains of young, mid-aged and old rats. Using sliding 7-mer windows along a tRF, we searched for putative seed sequences with high numbers of conserved complementary sites within 3' UTRs of 23 vertebrate genomes. We analyzed Gene Ontology term enrichment of predicted tRF targets and compared their transcript levels with targets of miRNAs in the context of age. Results and Discussion: We detected tRFs originating from 3'- and 5'-ends of tRNAs in rat brains at significant levels. These fragments showed dynamic changes: 3' tRFs monotonously increased with age, while 5' tRFs displayed less consistent patterns. Furthermore, 3' tRFs showed a narrow size range compared to 5' tRFs, suggesting a difference in their biogenesis mechanisms. Similar to our earlier results in Drosophila and compatible with other experimental findings, we found "seed" sequence locations on both ends of different tRFs. Putative targets of these fragments were found to be enriched in neuronal and developmental functions. Comparison of tRFs and miRNAs increasing in abundance with age revealed small, but distinct changes in brain target transcript levels for these two types of small RNA, with the higher proportion of tRF targets decreasing with age. We also illustrated the utility of tRF analysis for annotating tRNA genes in sequenced genomes.

SUBMITTER: Karaiskos S

PROVIDER: S-EPMC5224686 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Dynamics of tRNA fragments and their targets in aging mammalian brain.

Karaiskos Spyros S Grigoriev Andrey A

F1000Research 20161124

<i>Background: </i>The progress of next-generation sequencing technologies has unveiled various non-coding RNAs that have previously been considered products of random degradation and attracted only minimal interest. Among small RNA families, microRNA (miRNAs) have traditionally been considered key post-transcriptional regulators. However, recent studies have reported evidence for widespread presence of fragments of tRNA molecules (tRFs) across a range of organisms and tissues, and of tRF involv ...[more]

PMID: 28105302

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Project description:BackgroundtRNA-derived fragments (tRFs) are 14-40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. Many studies have shown that tRFs are associated with Argonaute (AGO) complexes and inhibit gene expression in the same manner as miRNAs. However, there are currently no tools for accurately predicting tRF target genes.MethodsWe used tRF-mRNA pairs identified by crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP to assess features that may participate in tRF targeting, including the sequence context of each site and tRF-mRNA interactions. We applied genetic algorithm (GA) to select key features and support vector machine (SVM) to construct tRF prediction models.ResultsWe first identified features that globally influenced tRF targeting. Among these features, the most significant were the minimum free folding energy (MFE), position 8 match, number of bases paired in the tRF-mRNA duplex, and length of the tRF, which were consistent with previous findings. Our constructed model yielded an area under the receiver operating characteristic (ROC) curve (AUC) = 0.980 (0.977-0.983) in the training process and an AUC = 0.847 (0.83-0.861) in the test process. The model was applied to all the sites with perfect Watson-Crick complementarity to the seed in the 3' untranslated region (3'-UTR) of the human genome. Seven of nine target/nontarget genes of tRFs confirmed by reporter assay were predicted. We also validated the predictions via quantitative real-time PCR (qRT-PCR). Thirteen potential target genes from the top of the predictions were significantly down-regulated at the mRNA levels by overexpression of the tRFs (tRF-3001a, tRF-3003a or tRF-3009a).ConclusionsPredictions can be obtained online, tRFTars, freely available at http://trftars.cmuzhenninglab.org:3838/tar/ , which is the first tool to predict targets of tRFs in humans with a user-friendly interface.

Project description:Prior studies applied single-cell approaches to explore gene expression changes in aged brains; however, they were limited by relatively shallow sampling of brain cell populations, and thus failed to characterize the detailed molecular signatures and dynamics of rare cell types associated with aging and diseases. Here, we set out to investigate the age-dependent transcriptional and chromatin dynamics across diverse brain cell types. With EasySci, an extensively improved single-cell combinatorial indexing strategy, we profiled ~1.5 million single-cell transcriptomes with full gene body coverage and ~400,000 single-cell chromatin accessibility profiles across mouse brains spanning different ages, genotypes, and both sexes. With a novel computational framework designed for characterizing cellular subtypes based on the expression of both genes and exons, we identified > 300 cell subtypes and deciphered the underlying molecular programs and spatial locations of rare cell types (e.g., pinealocytes, tanycytes). Leveraging the data, we generated a global readout of age-dependent cell population dynamics with great cellular subtype resolution, providing insights into expanded cell types (e.g., rare astrocytes and vascular leptomeningeal cells in olfactory bulb, reactive microglia and oligodendrocytes) and depleted cell types (e.g., neuronal progenitors, neuroblasts, committed oligodendrocyte precursors) in development and ageing. Furthermore, we explored cell-type-specific responses to genetic perturbations associated with Alzheimer’s disease and discovered rare cell types depleted (e.g., mt-Cytb+, mt-Rnr2+ choroid plexus epithelial cells) or enriched (e.g., Col25a1+ Ndrg1+ interbrain and midbrain neurons) in both AD models. Key findings are consistent between males and females, validated across the transcriptome, chromatin accessibility, and spatial analysis. In summary, these data comprise a rich resource for exploring cell-type-specific population dynamics and the underlying molecular mechanisms in the mammalian aging process.

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Dynamics of tRNA fragments and their targets in aging mammalian brain.

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Dynamics of tRNA fragments and their targets in aging mammalian brain.

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