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Hysenaj, G.

Publications and source records attributed to Hysenaj, G..

4 recordsLinked to original sources

An anciently diverged family of RNA binding proteins maintain correct splicing of ultra-long exons through cryptic splice site repression.

We previously showed that the germ cell specific nuclear protein RBMXL2 represses cryptic splicing patterns during meiosis and is required for male fertility. RBMXL2 evolved from the X-linked RBMX gene, which is silenced during meiosis due to sex chromosome inactivation. It has been unknown whether RBMXL2 provides a direct replacement for RBMX in meiosis, or whether RBMXL2 evolved to deal with the transcriptionally permissive environment of meiosis. Here we find that RBMX primarily operates as a splicing repressor in somatic cells, and specifically regulates a distinct class of exons that exceed the median human exon size. RBMX protein-RNA interactions are enriched within ultra-long exons, particularly within genes involved in genome stability, and repress the selection of cryptic splice sites that would compromise gene function. These similarities in overall function suggested that RBMXL2 might replace the function of RBMX during meiosis. To test this prediction we carried out inducible expression of RBMXL2 and the more distantly related RBMY protein in somatic cells, finding each could rescue aberrant patterns of RNA processing caused by RBMX depletion. The C-terminal disordered domain of RBMXL2 is sufficient to rescue proper splicing control after RBMX depletion. Our data indicate that RBMX and RBMXL2 have parallel roles in somatic tissues and the germline that must have been conserved for at least 200 million years of mammalian evolution. We propose RBMX family proteins are particularly important for the splicing inclusion of some ultra-long exons with increased intrinsic susceptibility to cryptic splice site selection.

molecular biology↗

RBMX enables productive RNA processing of ultra-long exons important for genome stability

Previously we showed that the germline-specific RNA binding protein RBMXL2 is essential for male meiosis where it represses cryptic splicing patterns (1). Here we find that its ubiquitously expressed paralog RBMX helps underpin human genome stability by preventing non-productive splicing. In particular, RBMX blocks selection of aberrant splice and polyadenylation sites within some ultra-long exons that would interfere with genes needed for normal replication fork activity. Target exons include within the ETAA1 (Ewings Tumour Associated 1) gene, where RBMX collaborates with its interaction partner Tra2{beta} to enable full-length exon inclusion by blocking selection of an aberrant 3 splice site. Our data reveal a novel group of RNA processing targets potently repressed by RBMX, and help explain why RBMX is associated with gene expression networks in cancer, replication and sensitivity to genotoxic drugs.

molecular biology↗

Androgen-regulated transcription of ESRP2 drives alternative splicing patterns in prostate cancer

Prostate is the most frequent cancer in men. Prostate cancer progression is driven by androgen steroid hormones, and delayed by androgen deprivation therapy (ADT). Androgens control transcription by stimulating androgen receptor (AR) activity, yet also control pre-mRNA splicing through less clear mechanisms. Here we find androgens regulate splicing through AR-mediated transcriptional control of the epithelial-specific splicing regulator ESRP2. Both ESRP2 and its close paralog ESRP1 are highly expressed in primary prostate cancer. Androgen stimulation induces splicing switches in many endogenous ESRP2-controlled mRNA isoforms, including a key splicing switch in the metastatic regulator FLNB which is associated with disease relapse. ESRP2 expression in clinical prostate cancer is repressed by ADT, which may thus inadvertently dampen epithelial splice programmes. Supporting this, FLNB splicing was reciprocally switched by the AR antagonist bicalutamide (Casodex(R)). Our data reveal a new mechanism of splicing control in prostate cancer with important implications for metastatic disease progression.\n\nKey pointsO_LITranscriptional regulation of ESRP2 by the androgen receptor controls splice isoform patterns in prostate cancer cells.\nC_LIO_LISplicing switches regulated by the androgen-ESRP2 axis include a splice isoform in the FLNB gene that is a known metastatic driver.\nC_LIO_LIBoth ESRP1 and ESRP2 are highly expressed in prostate cancer tissue.\nC_LIO_LIEctopic expression of ESRP1 and 2 inhibits prostate cancer cell growth.\nC_LIO_LIBy repressing ESRP2 expression androgen deprivation therapy (ADT) may dampen epithelial splicing programmes to inadvertently prime disease progression towards metastasis.\nC_LI

molecular biology↗

Fast and accurate differential splicing analysis across multiple conditions with replicates

Multiple approaches have been proposed to study differential splicing from RNA sequencing (RNA-seq) data1, including the analysis of transcript isoforms2,3, clusters of splice-junctions4,5, alternative splicing events6-8 and exonic regions9. However, many challenges remain unsolved, including the limitation in speed, the computing capacity and storage requirements, the constraints in the number of reads needed to achieve sufficient accuracy, and the lack of robust methods to account for variability between replicates and for analyses across multiple conditions. We present here a significant extension of SUPPA8 to enable streamlined analysis of differential splicing across multiple conditions, taking into account biological variability. We show that SUPPA differential splicing analysis achieves high accuracy using extensive experimental and simulated data compared to other methods; and shows higher accuracy at low sequencing depth, with short read lengths, and using replicas with unbalanced depth, which has important implications for the cost-effective use of RNA-seq data for splicing analysis. We also validate the analysis of multiple conditions with SUPPA by studying differential splicing during iPS-cell to neuron differentiation and during erythroblast differentiation, providing support for the applicability of SUPPA for the robust analysis of differential splicing beyond binary comparisons.

bioinformatics↗