The Role of Non-Coding RNAs in Neurodevelopmental Disorders

Zhang, Shuang-Feng; Gao, Jun; Liu, Chang‐Mei

doi:10.3389/fgene.2019.01033

Cited by 31 publications

(27 citation statements)

References 111 publications

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“…Some examples of ncRNAs and their influential roles in gene regulation or interference include small nuclear RNAs (snoRNAs; RNA splicing), small nucleolar RNAs (RNA modification), miRNAs (RNA degradation and/or translation inhibition), PIWI-interacting RNAs (piRNAs; gene silencing), Y-RNAs (DNA replication), transfer RNAs (tRNAs), and long non-coding RNAs (gene regulation) [ 6 ]. Furthermore, ncRNAs were previously shown to be differentially regulated in neurodegenerative diseases [ 7 ], while others have suggested that its rich repertoire within the human brain makes their involvement and dysregulation potentially crucial in the steps that lead to abnormal brain development and the etiology of neurodevelopmental disorders [ 1 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…The expression pattern of miRNAs is dynamically regulated during neurogenesis, neuronal differentiation, maintenance and function and overall brain development, making their involvement in neurodevelopmental processes of interest [ 1 , 9 ]. Studies have shown the critical role of alterations in miRNA regulation and signaling in many neurodevelopmental disorders, such as Fragile X syndrome, Rett Syndrome, Down Syndrome, and Prader-Willi Angelman Syndrome [ 8 ]. Since ASD has been associated with several of these conditions, it is interesting to investigate how miRNA dysregulation and/or expression patterns contribute.…”

Section: Introductionmentioning

confidence: 99%

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Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology

Salloum-Asfar

Elsayed

Elhag

et al. 2021

IJMS

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Autism spectrum disorder (ASD) is a multifaced neurodevelopmental disorder that becomes apparent during early childhood development. The complexity of ASD makes clinically diagnosing the condition difficult. Consequently, by identifying the biomarkers associated with ASD severity and combining them with clinical diagnosis, one may better factionalize within the spectrum and devise more targeted therapeutic strategies. Currently, there are no reliable biomarkers that can be used for precise ASD diagnosis. Consequently, our pilot experimental cohort was subdivided into three groups: healthy controls, individuals those that express severe symptoms of ASD, and individuals that exhibit mild symptoms of ASD. Using next-generation sequencing, we were able to identify several circulating non-coding RNAs (cir-ncRNAs) in plasma. To the best of our knowledge, this study is the first to show that miRNAs, piRNAs, snoRNAs, Y-RNAs, tRNAs, and lncRNAs are stably expressed in plasma. Our data identify cir-ncRNAs that are specific to ASD. Furthermore, several of the identified cir-ncRNAs were explicitly associated with either the severe or mild groups. Hence, our findings suggest that cir-ncRNAs have the potential to be utilized as objective diagnostic biomarkers and clinical targets.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology

Salloum-Asfar

Elsayed

Elhag

et al. 2021

IJMS

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“…Studies revealed the role of lncRNAs in immunity, specifically in proliferation, differentiation, and activation of immune cells [ 35 ], while their association with CNVs causing ASD is also being studied [ 36 ]. Moreover, microdeletion of snoRNA is associated with neurodevelopmental disorders such as Prader–Willi syndrome-like phenotype [ 37 ]. This highlights the contribution of these ncRNAs in the etiology of diseases and hence emphasizes the need to investigate how SVs might affect their function.…”

Section: Discussionmentioning

confidence: 99%

Long-Read Sequencing Improves the Detection of Structural Variations Impacting Complex Non-Coding Elements of the Genome

Begum

Albanna

Bankapur

et al. 2021

IJMS

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The advent of long-read sequencing offers a new assessment method of detecting genomic structural variation (SV) in numerous rare genetic diseases. For autism spectrum disorders (ASD) cases where pathogenic variants fail to be found in the protein-coding genic regions along chromosomes, we proposed a scalable workflow to characterize the risk factor of SVs impacting non-coding elements of the genome. We applied whole-genome sequencing on an Emirati family having three children with ASD using long and short-read sequencing technology. A series of analytical pipelines were established to identify a set of SVs with high sensitivity and specificity. At 15-fold coverage, we observed that long-read sequencing technology (987 variants) detected a significantly higher number of SVs when compared to variants detected using short-read technology (509 variants) (p-value < 1.1020 × 10−57). Further comparison showed 97.9% of long-read sequencing variants were spanning within the 1–100 kb size range (p-value < 9.080 × 10−67) and impacting over 5000 genes. Moreover, long-read variants detected 604 non-coding RNAs (p-value < 9.02 × 10−9), comprising 58% microRNA, 31.9% lncRNA, and 9.1% snoRNA. Even at low coverage, long-read sequencing has shown to be a reliable technology in detecting SVs impacting complex elements of the genome.

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“…In addition to alteration of protein-coding transcripts, abnormalities in splicing patterns as well as ncRNA profiles have been shown in individuals with various psychiatric disorders including ASD (Gandal et al, 2018 ). Specific ncRNA species such as micro RNAs (miRNAs), small nucleolar RNAs, and lncRNAs are involved in psychiatric disorders by regulating transcriptional and translational systems (Zhang et al, 2019 ). Abnormal alternative splicing is also associated with neurodevelopmental disorders (Zhang et al, 2016 ; Gandal et al, 2018 ); for instance, Rbfox1 is a transcription regulator that controls alternative splicing and its mutation is associated with ASD (Wamsley et al, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Profiling of Gene Expression in the Cerebral Cortex and Striatum of BTBRTF/ArtRbrc Mice Compared to C57BL/6J Mice

Mizuno

Hirota

Ishii

et al. 2020

Front. Cell. Neurosci.

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Mouse line BTBR T+ Iptr3tf/J (hereafter referred as to BTBR/J) is a mouse strain that shows lower sociability compared to the C57BL/6J mouse strain (B6) and thus is often utilized as a model for autism spectrum disorder (ASD). In this study, we utilized another subline, BTBRTF/ArtRbrc (hereafter referred as to BTBR/R), and analyzed the associated brain transcriptome compared to B6 mice using microarray analysis, quantitative RT-PCR analysis, various bioinformatics analyses, and in situ hybridization. We focused on the cerebral cortex and the striatum, both of which are thought to be brain circuits associated with ASD symptoms. The transcriptome profiling identified 1,280 differentially expressed genes (DEGs; 974 downregulated and 306 upregulated genes, including 498 non-coding RNAs [ncRNAs]) in BTBR/R mice compared to B6 mice. Among these DEGs, 53 genes were consistent with ASD-related genes already established. Gene Ontology (GO) enrichment analysis highlighted 78 annotations (GO terms) including DNA/chromatin regulation, transcriptional/translational regulation, intercellular signaling, metabolism, immune signaling, and neurotransmitter/synaptic transmission-related terms. RNA interaction analysis revealed novel RNA–RNA networks, including 227 ASD-related genes. Weighted correlation network analysis highlighted 10 enriched modules including DNA/chromatin regulation, neurotransmitter/synaptic transmission, and transcriptional/translational regulation. Finally, the behavioral analyses showed that, compared to B6 mice, BTBR/R mice have mild but significant deficits in social novelty recognition and repetitive behavior. In addition, the BTBR/R data were comprehensively compared with those reported in the previous studies of human subjects with ASD as well as ASD animal models, including BTBR/J mice. Our results allow us to propose potentially important genes, ncRNAs, and RNA interactions. Analysis of the altered brain transcriptome data of the BTBR/R and BTBR/J sublines can contribute to the understanding of the genetic underpinnings of autism susceptibility.

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The Role of Non-Coding RNAs in Neurodevelopmental Disorders

Cited by 31 publications

References 111 publications

Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology

Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology

Long-Read Sequencing Improves the Detection of Structural Variations Impacting Complex Non-Coding Elements of the Genome

Comprehensive Profiling of Gene Expression in the Cerebral Cortex and Striatum of BTBRTF/ArtRbrc Mice Compared to C57BL/6J Mice

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