The tRNA regulome in neurodevelopmental and neuropsychiatric disease

Blaze, Jennifer; Akbarian, Schahram

doi:10.1038/s41380-022-01585-9

Cited by 20 publications

(12 citation statements)

References 133 publications

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“…Additionally, transfer-RNA (tRNA) metabolism shows significant enrichment for LIV DEGs, highlighting another energy dependent process important for initiating translation 58 . For tRNAs to interact with amino acids that will be incorporated into the polypeptide chain, they must first become charged via aminoacytlation, a process which requires ATP and is enriched among LIV DEGs across cell types but most significantly in oligodendrocytes 59 . The enrichment of energy-related processes in genes with increased abundance in living samples is reassuring based on the understanding that energy levels are depleted and cellular respiration is halted in the hypoxic perimortem and postmortem environment.…”

Section: Discussionmentioning

confidence: 99%

Characterizing cell type specific transcriptional differences between the living and postmortem human brain

Vornholt,

Liharska,

Cheng

et al. 2024

Preprint

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Single-nucleus RNA sequencing (snRNA-seq) is often used to define gene expression patterns characteristic of brain cell types as well as to identify cell type specific gene expression signatures of neurological and mental illnesses in postmortem human brains. As methods to obtain brain tissue from living individuals emerge, it is essential to characterize gene expression differences associated with tissue originating from either living or postmortem subjects using snRNA-seq, and to assess whether and how such differences may impact snRNA-seq studies of brain tissue. To address this, human prefrontal cortex single nuclei gene expression was generated and compared between 31 samples from living individuals and 21 postmortem samples. The same cell types were consistently identified in living and postmortem nuclei, though for each cell type, a large proportion of genes were differentially expressed between samples from postmortem and living individuals. Notably, estimation of cell type proportions by cell type deconvolution of pseudo-bulk data was found to be more accurate in samples from living individuals. To allow for future integration of living and postmortem brain gene expression, a model was developed that quantifies from gene expression data the probability a human brain tissue sample was obtained postmortem. These probabilities are established as a means to statistically account for the gene expression differences between samples from living and postmortem individuals. Together, the results presented here provide a deep characterization of both differences between snRNA-seq derived from samples from living and postmortem individuals, as well as qualify and account for their effect on common analyses performed on this type of data.

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Section: Discussionmentioning

confidence: 99%

Characterizing cell type specific transcriptional differences between the living and postmortem human brain

Vornholt,

Liharska,

Cheng

et al. 2024

Preprint

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“…AARS (human alanyl-tRNA synthetase) belongs to a family of tRNA synthases of the class II enzymes ( Rajendran et al, 2018 ). Multiple paths of the evidence (that is tRNA gene mutations, tRNA epitranscriptome, tRNA charging, and tRFs) support that various aspects of tRNA function and metabolism are linked to neurodevelopmental and neuropsychiatric disorders ( Legge et al, 2019 ; Blaze and Akbarian, 2022 ). FBXW7 encodes a member of the F-box protein subunit of an Skp1-Cul1-F-box protein (SCF)-type ubiquitin ligase complex and plays a principal role in the degradation of Notch family members ( Snyder et al, 2012 ).…”

Section: Discussionmentioning

confidence: 99%

DNA methylation signature of psychological resilience in young adults: Constructing a methylation risk score using a machine learning method

Hsieh²,

Yang³

et al. 2023

Front. Genet.

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Resilience is a process associated with the ability to recover from stress and adversity. We aimed to explore the resilience-associated DNA methylation signatures and evaluate the abilities of methylation risk scores to discriminate low resilience (LR) individuals. The study recruited 78 young adults and used Connor-Davidson Resilience Scale (CD-RISC) to divide them into low and high resilience groups. We randomly allocated all participants of two groups to the discovery and validation sets. We used the blood DNA of the subjects to conduct a genome-wide methylation scan and identify the significant methylation differences of CpG Sites in the discovery set. Moreover, the classification accuracy of the DNA methylation probes was confirmed in the validation set by real-time quantitative methylation-specific polymerase chain reaction. In the genome-wide methylation profiling between LR and HR individuals, seventeen significantly differentially methylated probes were detected. In the validation set, nine DNA methylation signatures within gene coding regions were selected for verification. Finally, three methylation probes [cg18565204 (AARS), cg17682313 (FBXW7), and cg07167608 (LINC01107)] were included in the final model of the methylation risk score for LR versus HR. These methylation risk score models of low resilience demonstrated satisfactory discrimination by logistic regression and support vector machine, with an AUC of 0.81 and 0.93, accuracy of 72.3% and 87.1%, sensitivity of 75%, and 87.5%, and specificity of 70% and 80%. Our findings suggest that methylation signatures can be utilized to identify individuals with LR and establish risk score models that may contribute to the field of psychology.

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“…The effect of tRNA modifications on the nervous system is an emerging aspect of neuroscience. More and more genes involved in tRNA modifications have been proved to be related to neurodevelopmental disorders [131], suggesting the increasing importance of tRNA modifications in human neural development. It is essential for us to know the functions of these tRNA modifying genes or enzymes, which will help us to realize their exact biological roles, and to develop new therapeutic strategies by controlling the expression of tRNA modifications related genes.…”

Section: Neurological Diseasesmentioning

confidence: 99%

tRNA Modifications and Modifying Enzymes in Disease, the Potential Therapeutic Targets

Cui¹,

Zhao²,

Jiang³

et al. 2023

Int. J. Biol. Sci.

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tRNA is one of the most conserved and abundant RNA species, which plays a key role during protein translation. tRNA molecules are post-transcriptionally modified by tRNA modifying enzymes. Since high-throughput sequencing technology has developed rapidly, tRNA modification types have been discovered in many research fields. In tRNA, numerous types of tRNA modifications and modifying enzymes have been implicated in biological functions and human diseases. In our review, we talk about the relevant biological functions of tRNA modifications, including tRNA stability, protein translation, cell cycle, oxidative stress, and immunity. We also explore how tRNA modifications contribute to the progression of human diseases. Based on previous studies, we discuss some emerging techniques for assessing tRNA modifications to aid in discovering different types of tRNA modifications.

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The tRNA regulome in neurodevelopmental and neuropsychiatric disease

Cited by 20 publications

References 133 publications

Characterizing cell type specific transcriptional differences between the living and postmortem human brain

Characterizing cell type specific transcriptional differences between the living and postmortem human brain

DNA methylation signature of psychological resilience in young adults: Constructing a methylation risk score using a machine learning method

tRNA Modifications and Modifying Enzymes in Disease, the Potential Therapeutic Targets

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