The human MAPT locus generates circular RNAs

Welden, Justin R.; Doorn, Jacob van; Nelson, Peter T.; Stamm, Stefan

doi:10.1016/j.bbadis.2018.04.023

Cited by 25 publications

(24 citation statements)

References 37 publications

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“…The MAPT gene generates the Tau protein. Using a PCR screen of RNA from human brain tissues, Welden et al showed that the MAPT locus generates circRNAs through a backsplicing mechanism, but the role of these circRNAs is still unclear 69 .…”

Section: Circrna In Alzheimer’s Diseasementioning

confidence: 99%

CircRNAs: role in human diseases and potential use as biomarkers

et al. 2021

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Circular RNAs (circRNAs) are a class of endogenous RNAs characterized by a covalent loop structure. In comparison to other types of RNAs, the abundance of circRNAs is relatively low but due to the circular configuration, their stability is very high. In addition, circRNAs display high degree of tissue specificity. The sponging activity of circRNAs toward microRNAs is the best-described mode of action of circRNAs. However, the ability of circRNAs to bind with specific proteins, as well as to encode short proteins, propose alternative functions. This review introduces the biogenesis of circRNAs and summarizes the roles played by circRNAs in human diseases. These include examples of their functional roles in several organ-specific cancers, such as head and neck and breast and lung cancers. In addition, we review potential functions of circRNAs in diabetes, cardiovascular, and neurodegenerative diseases. Recently, a growing number of studies have demonstrated involvement of circRNAs in a wide spectrum of signaling molecular pathways, but at the same time many different and controversial views on circRNAs role and function are emerging. We conclude by offering cellular homeostasis generated by networks comprising circular RNAs, other non-coding RNAs and RNA-binding proteins. Accordingly, it is predictable that circRNAs, due to their highly stable nature and remarkable tissue specificity, will emerge as reliable biomarkers of disease course and treatment efficacy.

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Section: Circrna In Alzheimer’s Diseasementioning

confidence: 99%

CircRNAs: role in human diseases and potential use as biomarkers

et al. 2021

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“…Genetic variation of circRNAs may affect diseases by modifying circRNA expression, evoking differential splicing, or distorting native binding sites for miRNAs. A recent study showed that the MAPT locus can generate circRNAs through back-splicing from exon 12 to exon 10 or 7 [111]. Formation of circRNA from exons 12 to 10 is influenced by trans-acting factors involved in exon 10 inclusion/skipping [111].…”

Section: Trends In Geneticsmentioning

confidence: 99%

“…A recent study showed that the MAPT locus can generate circRNAs through back-splicing from exon 12 to exon 10 or 7 [111]. Formation of circRNA from exons 12 to 10 is influenced by trans-acting factors involved in exon 10 inclusion/skipping [111]. When examined in the context of the FTLD-causing p.N279K mutation, which promotes exon 10 inclusion, the effect of some of these factors was influenced, resulting in differences in the levels of this circRNA [111].…”

Section: Trends In Geneticsmentioning

confidence: 99%

Uncovering the impact of noncoding variants in neurodegenerative brain diseases

et al. 2022

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Neurodegenerative brain diseases (NBDs) are characterized by cognitive decline and movement impairments caused by neuronal loss in different brain regions. A large fraction of the genetic heritability of NBDs is not explained by the current known mutations. Genome-wide association studies identified novel diseaserisk loci, adding to the genetic basis of NBDs. Many of the associated variants reside in noncoding regions with distinct molecular functions. Genetic variation in these regions can alter functions and contribute to disease pathogenesis. Here, we discuss noncoding variants associated with NBDs. Methods for better functional interpretation of noncoding variation will expand our knowledge of the genetic architecture of NBDs and broaden the routes for therapeutic strategies. Noncoding elements in brain neurodegenerationNeurodegenerative brain diseases (NBDs) are neuropathologically characterized by protein aggregates that prompt progressive deterioration and loss of synaptic function. Pathological hallmarks differ between diseases. The clinical presentation depends on the affected brain regions and includes a range of cognitive and movement impairments (Box 1). Most studies so far have focused on the coding part to identify the genetic cause of NBDs. However, only a part of the heritability of NBDs is explained by coding mutations in genes causally linked with each disease [1-4]. Genome-wide association studies (GWAS) (see Glossary) have identified common genetic variants associated with various NBDs. Approximately 16-36% and 28% of the heritability of Parkinson's disease (PD) and of Alzheimer's disease (AD), respectively, can be explained by GWAS variants [5,6]. A considerable fraction of the variants is located in noncoding genome regions ). Functional modeling of variants has revealed disease-related mechanisms and explained part of the missing genetic etiology.

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“…Integration analysis of transcription (protein-coding genes) and post-transcriptional (non-coding genes) regulation has proven to be a valuable strategy for studies of the genetic characteristics of various human complex diseases (Zhang et al, 2015; Arena et al, 2017). In a recent study, Welden et al found the human MAPT gene which produces the microtubule-associated protein Tau, generates circRNAs to contribute to AD (Welden et al, 2018). Piwecka et al (2017) demonstrated that loss of circRNA locus affected brain function.…”

Section: Introductionmentioning

confidence: 99%

Systematic Characterization of Circular RNA-Associated CeRNA Network Identified Novel circRNA Biomarkers in Alzheimer's Disease

Zhang

Bao

et al. 2019

Front. Bioeng. Biotechnol.

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Alzheimer's disease (AD), a degenerative disease of the central nervous system, is the most common form of dementia in old age. The complexity and behavior of circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) network remained poorly characterized in AD. The aim of this study was to elucidate the regulatory networks of dysregulated circRNAs from ceRNA view and identify potential risk circRNAs involved in AD pathogenesis. Consistent differentially expressed genes (CDEGs) were obtained using meta-analysis for multiple microarrays, and differentially expressed miRNAs (DEmiRs) were identified using empirical Bayes method. The circRNA-associated ceRNA network (cirCeNET) was constructed based on “ceRNA hypothesis” using an integrated system biology method. A total of 1,872 CDEGs and 48 DEmiRs were screened across different datasets. By mapping CDEGs and DEmiRs into the cirCeNET, an AD-related circRNA-associated ceRNA network (ADcirCeNET) was constructed, including 3,907 edges and 1,407 nodes (276 circRNAs, 14 miRNAs and 1,117 mRNAs). By prioritizing AD risk circRNA-associated ceRNAs, we found that the circRNA KIAA1586 occurred most frequently in the AD risk circRNA-associated ceRNAs and function as a ceRNA that operates by competitively binding three known AD-risk miRNAs. In silico functional analysis suggested that circRNA KIAA1586-related ceRNA network was significantly enriched in known AD-associated biological processes. Our study provided a global view and systematic dissection of circRNA-associated ceRNA network. The identified circRNA KIAA1586 may be a key risk factor involved in AD pathogenesis.

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The human MAPT locus generates circular RNAs

Cited by 25 publications

References 37 publications

CircRNAs: role in human diseases and potential use as biomarkers

CircRNAs: role in human diseases and potential use as biomarkers

Uncovering the impact of noncoding variants in neurodegenerative brain diseases

Systematic Characterization of Circular RNA-Associated CeRNA Network Identified Novel circRNA Biomarkers in Alzheimer's Disease

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