Mammalian tissues display a remarkable complexity of splicing patterns. Nevertheless, only few examples of tissue-specific splicing regulators are known. Herein, we characterize a novel splicing regulator named RBM11, which contains an RNA Recognition Motif (RRM) at the amino terminus and a region lacking known homology at the carboxyl terminus. RBM11 is selectively expressed in brain, cerebellum and testis, and to a lower extent in kidney. RBM11 mRNA levels fluctuate in a developmentally regulated manner, peaking perinatally in brain and cerebellum, and at puberty in testis, in concomitance with differentiation events occurring in neurons and germ cells. Deletion analysis indicated that the RRM of RBM11 is required for RNA binding, whereas the carboxyl terminal region permits nuclear localization and homodimerization. RBM11 is localized in the nucleoplasm and enriched in SRSF2-containing splicing speckles. Transcription inhibition/release experiments and exposure of cells to stress revealed a dynamic movement of RBM11 between nucleoplasm and speckles, suggesting that its localization is affected by the transcriptional status of the cell. Splicing assays revealed a role for RBM11 in the modulation of alternative splicing. In particular, RBM11 affected the choice of alternative 5' splice sites in BCL-X by binding to specific sequences in exon 2 and antagonizing the SR protein SRSF1. Thus, our findings identify RBM11 as a novel tissue-specific splicing factor with potential implication in the regulation of alternative splicing during neuron and germ cell differentiation.
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http://dx.doi.org/10.1093/nar/gkr819 | DOI Listing |
Nat Genet
January 2025
Calico Life Sciences LLC, South San Francisco, CA, USA.
Sequence-based machine-learning models trained on genomics data improve genetic variant interpretation by providing functional predictions describing their impact on the cis-regulatory code. However, current tools do not predict RNA-seq expression profiles because of modeling challenges. Here, we introduce Borzoi, a model that learns to predict cell-type-specific and tissue-specific RNA-seq coverage from DNA sequence.
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View Article and Find Full Text PDFCell Death Dis
January 2025
Institute of Biophysical Chemistry and Center for Biomolecular Magnetic Resonance, Goethe University, 60438, Frankfurt, Germany.
The transcription factor p63 is expressed in many different isoforms as a result of differential promoter use and splicing. Some of these isoforms have very specific physiological functions in the development and maintenance of epithelial tissues and surveillance of genetic integrity in oocytes. The ASPP family of proteins is involved in modulating the transcriptional activity of the p53 protein family members, including p63.
View Article and Find Full Text PDFCrit Rev Oncol Hematol
January 2025
Institute of Human Genetics, Jena University Hospital, Jena, Germany; Urology and Nephrology Research Center, Research Institute for Urology and Nephrology, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address:
Circular RNAs (circRNAs) have emerged as critical regulators in cancer biology, contributing to various cancer hallmarks, including cell proliferation, apoptosis, metastasis, and drug resistance. Defined by their covalently closed loop structure, circRNAs possess unique characteristics like high stability, abundance, and tissue-specific expression. These non-coding RNAs function through mechanisms such as miRNA sponging, interactions with RNA-binding proteins (RBPs), and modulating transcription and splicing.
View Article and Find Full Text PDFNucleic Acids Res
December 2024
Department of Pathology & Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
RNA sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases that hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local splicing variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest.
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