The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Cytoplasmic Rbfox1 Regulates the Expression of Synaptic and Autism-Related Genes
Open accessAbstract
Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate the function of cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that Rbfox1 bound predominantly to introns in nascent RNA, while cytoplasmic Rbox1 bound to 3' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and Rbfox1 and miRNA binding sites overlapped significantly. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease.
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“We also find significant enrichment of splicing changes in targets of two RNA binding proteins that regulate synaptic transmission and whose targets are implicated in both ASD and SCZ, the neuronal splicing regulator RBFOX1 (FDR=5.16×10−11) (32) and the fragile X mental retardation protein (FMRP) (FDR=3.10×10−21) (33).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [32]
In the citing paper
“Experiments in mouse indicate that RBFOX1 has distinct nuclear and cytoplasmic isoforms with differing functions, the nuclear isoform primarily regulating pre-mRNA alternative splicing, and the cytoplasmic isoform binding to the 3’ UTR to stabilize target transcripts involved in regulation of neuronal excitability (28, 32, 58, 60).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [32]
In the citing paper
“Here, we find that isoM17 shows greater enrichment for nuclear RBFOX1 targets (Fig 6C), whereas isoM2 shows stronger overlap with cytoplasmic targets (32).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [32]
In the citing paper
“the protein encoded by RBFOX1 regulates the expression of 15 of the top 40 ranked genes (the probability of this event is p = 3.4e−05) [70].”
From An integrated analysis of genes and functional pathways for aggression in human and rodent models (2019) · cites this paper as [70]
In the citing paper
“many RNA-binding proteins controlling splicing choices also affect the choice of poly-A site and can also be found in the cytoplasm, where they control the translation or stability of target transcripts through binding in 3′ UTRs197”
From The neurogenetics of alternative splicing (2016) · cites this paper as [197]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
MicroRNAs: Target Recognition and Regulatory Functions
Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.01.002 · Cited by 20,068
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556
Strong association of de novo copy number mutations with autism
Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T., Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J., et al. (2007) · Science · doi:10.1126/science.1138659 · Cited by 2,795
Self-citationFMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism
Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., et al. (2011) · Cell · doi:10.1016/j.cell.2011.06.013 · Cited by 2,072
Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
Voineagu, I., Wang, X., Johnston, P., Lowe, J. K., Tian, Y., Horvath, S., Mill, J., Cantor, R. M., Blencowe, B. J., & Geschwind, D. H. (2011) · Nature · doi:10.1038/nature10110 · Cited by 1,874 · cited 24×
“Three of these coexpression modules, devM13, devM16, and devM17, were enriched for the GO term of synaptic transmission, as well as ASD susceptibility genes (Parikshak et al., 2013).”
BackgroundResultInfluentialSelf-citationXie, X., Lu, J., Kulbokas, E. J., Golub, T. R., Mootha, V., Lindblad-Toh, K., Lander, E. S., & Kellis, M. (2005) · Nature · doi:10.1038/nature03441 · Cited by 1,872
The molecular basis of CaMKII function in synaptic and behavioural memory
Lisman, J., Schulman, H., & Cline, H. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn753 · Cited by 1,860
Argonaute HITS-CLIP decodes microRNA–mRNA interaction maps
Chi, S. W., Zang, J. B., Mele, A., & Darnell, R. B. (2009) · Nature · doi:10.1038/nature08170 · Cited by 1,791
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Mukherjee, A., & Nongthomba, U. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.02.626327 · Cited by 1
Murphy, M. D., Krick, K. S., Zhang, S., & Heller, E. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.24.666631 · Cited by 1
Lipscombe, D., & Soto, E. J. L. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.026
Faisal, M. S., Büsche, G., Schlué, J., Kreipe, H. H., Lehmann, U., & Bartels, S. (2018) · Annals of Hematology · doi:10.1007/s00277-018-3478-3
A Genome-Scale Analysis of Alternative Splicing Regulation by Splicing Factors in C. elegans
Tan, J. H. (2018) · TSpace (University of Toronto)
Functional impact of alternative splicing in vertebrate proteomes across tissues and cell types
Rodríguez, T., & Javier, J. (2018) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Genomics of major depressive disorder
Levinson, D. F. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813176-3.00016-x
Dysregulated Translation in Autism Spectrum Disorder
Santini, E., & Borgkvist, A. (2020) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190686307.013.24
Peart, N. J., Hwang, J. Y., Vallières, M. Q., Sears, M. J., Yang, Y., Stoilov, P., Barash, Y., Park, J. W., & Carstens, R. P. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3868490
Yotova, A. Y., Kassel, L., Kögler, M., Kurt, B., Reif, A., Slattery, D. A., & O’Leary, A. (2021) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2021.10.050
Matalkah, F. K., Jeong, B., Sheridan, M., Horstick, E. J., Ramamurthy, V., & Stoilov, P. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.09.483688
Budimirovic, D. B. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735846837.793561048
Matalkah, F. K. (2022) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.11594
(2022) · Society for Neuroscience eBooks · doi:10.1523/hon.012008
PKR activation-induced mitochondrial dysfunction in HIV-transgenic mice with nephropathyPreprint
Yoshida, T., Latt, K. Z., Rosenberg, A. Z., Santo, B. A., Myakala, K., Ishimoto, Y., Zhao, Y., Shrivastav, S., Jones, B. A., Yang, X., et al. (2024) · eLife · doi:10.7554/elife.91260.2
Yotova, A. Y. (2024) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · doi:10.21248/gups.85791
Yoshida, T., Latt, K. Z., Rosenberg, A. Z., et al. (2024) · eLife · doi:10.7554/elife.91260.3.sa2
Yoshida, T., Latt, K. Z., Rosenberg, A. Z., Santo, B. A., Myakala, K., Ishimoto, Y., Zhao, Y., Shrivastav, S., Jones, B. A., Yang, X., et al. (2024) · eLife · doi:10.7554/elife.91260.3.sa0
Yoshida, T., Latt, K. Z., Rosenberg, A. Z., et al. (2024) · eLife · doi:10.7554/elife.91260.3.sa1
PKR activation-induced mitochondrial dysfunction in HIV-transgenic mice with nephropathyPreprint
Yoshida, T., Latt, K. Z., Rosenberg, A. Z., Santo, B. A., Myakala, K., Ishimoto, Y., Zhao, Y., Shrivastav, S., Jones, B. A., Yang, X., et al. (2024) · eLife · doi:10.7554/elife.91260.3
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Debnath, O., Berger, H., Detjen, K. M., Kirchner, P., Marinoni, I., Eichhorn, I., Bolduan, F., Conrad, T., Horst, D. A., Eils, R., et al. (2026) · Communications Biology · doi:10.1038/s42003-026-10692-0
Zhang, J., Zhang, H., Qin, T., Zhai, Y., Xiao, J., & Lu, F. (2025) · Research Square · doi:10.21203/rs.3.rs-7334393/v1
Do, H., Kim, D., Jappelli, R., Yang, H., Jeon, Y.-S., Son, G., Ju, M., Son, J.-H., Ahn, I., Lim, C. K., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.01.679670
Self-citationHopkins, L. N., Avgan, N., Sutherland, H. G. E., Fernandez, F., Knowles, E. E. M., Haupt, L. M., Blangero, J., Glahn, D. C., Shum, D., Lea, R. A., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-32828-8
Modest rescue of RBFOX1 splicing function attenuates Huntington’s disease features
Lozano-Muñoz, D., Elorza, A., Lucas-Santamaría, M., Santos‐Galindo, M., Parras, A., & Lucas, J. J. (2026) · Molecular Medicine · doi:10.1186/s10020-026-01471-y
RNP granule remodelling in response to neuronal activity
Formicola, N. (2019) · theses.fr (ABES) · doi:10.70675/5f6fe960z260az4408zb7c1zdd55221dc856
Adel, M. R., Antón-Galindo, E., Freudenberg, F., Cormand, B., & Fernàndez‐Castillo, N. (2026) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2026.111712
Nongenetic Mechanisms of Animal Evolution
Cabej, N. R. (2026) · Springer eBooks · doi:10.1007/978-3-032-24295-2_27
Lui, M., Minuti, A., D’Angiolini, S., Scuruchi, M., Silvestro, S., & Artimagnella, O. (2026) · Genes · doi:10.3390/genes17060692
Nonsense-mediated mRNA decay and associated splicing patterns in neurodevelopmental disorders
Anisimova, P. E., Filat’eva, A. E., Tarabykin, V. S., & Kondakova, E. (2026) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2026.1914793
Estévez‐Arias, B., Segarra‐Casas, A., Seoane, P., Romo, L., Polavarapu, K., Nectoux, J., Caballero‐Ávila, M., Austin-Tse, C. A., Konyukh, M., Obeid, K., et al. (2026) · Annals of Neurology · doi:10.1002/ana.78381
Metadata
- Authors
- Lee, J.-A., Damianov, A., Lin, C.-H., Fontes, M., Parikshak, N. N., Anderson, E. S., Geschwind, D. H., Black, D. L., & Martin, K. C.
- Affiliations
- University of California, Los Angeles (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Martin, Kelsey C.
- ORCID
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 89
- Issue
- 1
- Pages
- 113-128
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC4858412
- OpenAlex
- W2190411440
- Cited by
- 232
- References
- 65
- Citations by year
- 2026: 10 · 2025: 17 · 2024: 26 · 2023: 22 · 2022: 24 · 2021: 18 · 2020: 31 · 2019: 20 · 2018: 27 · 2017: 19 · 2016: 18
- FWCI
- 9.26
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (4f30ag033993-03)
- National Institute on Aging (F30 AG033993, 4F30AG033993)
- National Institute of Mental Health (F30MH099886, R21MH101684)
- National Institute of General Medical Sciences (R01GM084317)
- National Institute of Neurological Disorders and Stroke (R01NS045324)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50HD055784)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Keywords
- RBFOX1, autism spectrum disorder, synaptic genes, alternative splicing, RNA-binding proteins, mRNA stability, translation (biology), 3' untranslated region, microRNA binding sites, cortical development, gene expression profiling
- MeSH terms
- RNA Splicing Factors, Animals, Autistic Disorder, Brain, Cytoplasm, Estriol, Humans, Mice, Inbred C57BL, Neurons, RNA, Messenger, RNA-Binding Proteins, Alternative Splicing, Gene Expression Profiling
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