New sequencing technologies and high-resolution microarray analysis have revealed genome-wide pervasive transcription in many eukaryotes, generating a large number of RNAs with no coding capacity. The focus of current debate is whether many of these ncRNAs (non-coding RNAs) are functional, and if so, what their function is. In this review, we describe recent discoveries in the field of ncRNAs in the yeast Saccharomyces cerevisiae. Newly identified ncRNAs in this budding yeast, their functions in gene regulation and possible mechanisms of action are discussed.
The craniofacial developmental disorder Burn-McKeown Syndrome (BMKS) is caused by biallelic variants in the pre-messenger RNA splicing factor gene TXNL4A/DIB1. The majority of affected individuals with BMKS have a 34 base pair deletion in the promoter region of one allele of TXNL4A combined with a loss-of-function variant on the other allele, resulting in reduced TXNL4A expression. However, it is unclear how reduced expression of this ubiquitously expressed spliceosome protein results in craniofacial defects during development. Here we reprogrammed peripheral mononuclear blood cells from a BMKS patient and her unaffected mother into induced pluripotent stem cells (iPSCs) and differentiated the iPSCs into induced neural crest cells (iNCCs), the key cell type required for correct craniofacial development. BMKS patient-derived iPSCs proliferated more slowly than both mother- and unrelated control-derived iPSCs, and RNA-Seq analysis revealed significant differences in gene expression and alternative splicing. Patient iPSCs displayed defective differentiation into iNCCs compared to maternal and unrelated control iPSCs, in particular a delay in undergoing an epithelial-to-mesenchymal transition (EMT). RNA-Seq analysis of differentiated iNCCs revealed widespread gene expression changes and mis-splicing in genes relevant to craniofacial and embryonic development that highlight a dampened response to WNT signalling, the key pathway activated during iNCC differentiation. Furthermore, we identified the mis-splicing of TCF7L2 exon 4, a key gene in the WNT pathway, as a potential cause of the downregulated WNT response in patient cells. Additionally, mis-spliced genes shared common sequence properties such as length, branch point to 3’ splice site (BPS-3’SS) distance and splice site strengths, suggesting that splicing of particular subsets of genes is particularly sensitive to changes in TXNL4A expression. Together, these data provide the first insight into how reduced TXNL4A expression in BMKS patients might compromise splicing and NCC function, resulting in defective craniofacial development in the embryo.
Pre-mRNA splicing is an essential step in gene expression that removes intron sequences efficiently and accurately to produce a mature mRNA for translation. It is the large and dynamic RNA-protein complex called the spliceosome that catalyzes intron removal. To carry out splicing the spliceosome not only needs to assemble correctly with the pre-mRNA but the spliceosome requires extensive remodelling of its RNA and protein components to execute the 2 steps of intron removal. Spliceosome remodelling is achieved through the action of ATPases that target both RNA and proteins to produce spliceosome conformations competent for each step of spliceosome activation, catalysis and disassembly. An increasing amount of research has pointed to the spliceosome associated NineTeen Complex (NTC) of proteins as targets for the action of a number of the spliceosomal ATPases during spliceosome remodelling. In this point-of-view article we present the latest findings on the changes in the NTC that occur following ATPase action that are required for spliceosome activation, catalysis and disassembly. We proposed that the NTC is one of the main targets of ATPase action during spliceosome remodelling required for pre-mRNA splicing.
Variable levels of gene expression between tissues complicates the use of RNA sequencing of patient biosamples to delineate the impact of genomic variants. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA sequencing. This overcomes limitations of using expression values alone as a metric to predict RNA-sequencing utility. We have derived a metric, minimum required sequencing depth (MRSD), that estimates the depth of sequencing required from RNA sequencing to achieve user-specified sequencing coverage of a gene, transcript, or group of genes. We applied MRSD across four human biosamples: whole blood, lymphoblastoid cell lines (LCLs), skeletal muscle, and cultured fibroblasts. MRSD has high precision (90.1%-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that fibroblasts, of these four biosamples, are the optimum source of RNA for 63.1% of gene panels. Using this approach, up to 67.8% of the variants of uncertain significance in ClinVar that are predicted to impact splicing could be assayed by RNA sequencing in at least one of the biosamples. We demonstrate the utility and benefits of MRSD as a metric to inform functional assessment of splicing aberrations, in particular in the context of Mendelian genetic disorders to improve diagnostic yield.
Abstract Purpose To develop a comprehensive analysis framework to identify pre-messenger RNA splicing mutations in the context of rare disease. Methods We assessed ‘variants of uncertain significance’ through six in-silico prioritization strategies. Firstly, through comparison to functional analyses, we determined the precise effect on splicing of variants identified through clinical multi-disciplinary meetings. Next, we calculated the sensitivity of in-silico prioritization strategies to distinguish known splicing mutations from common variation (>2% in allele frequency in gnomAD) within relevant disease genes. These approaches defined an accurate in-silico strategy for variant prioritization, which we retrospectively applied to a large cohort of 2783 individuals who had previously received genomic testing for rare genomic disorders. We assessed the clinical impact of such prioritization strategies alongside routine diagnostic testing strategies. Results We identified 21 variants that potentially impacted splicing, and used cell based splicing assays to identify those variants which disrupted normal splicing. These findings underpinned new molecular diagnoses for 14 individuals. This process established that the use of pre-defined thresholds from a machine learning splice prediction algorithm, SpliceAI, was the most efficient method for variant prioritization, with a positive predictive value of 86%. We analysed 1,346,744 variants identified through diagnostic testing for 2783 individuals and observed that splicing variant prioritization strategies would improve clarity in clinical analysis for 15% of the individuals surveyed. Prioritized variants could provide new molecular diagnoses or provide additional support for molecular diagnosis for up to 81 individuals within our cohort. Conclusion We present an in-silico and functional analysis framework for the assessment of variants impacting pre-messenger RNA splicing which is applicable across monogenic disorders. Incorporation of these strategies improves clarity in diagnostic reporting, increases diagnostic yield and, with the advent of targeted treatment strategies, can directly alter patient clinical management. Key Highlights We establish an in-silico and functional analysis framework for the incorporation of splice variant assessment into diagnostic testing that is applicable across monogenic disorders. After assessment of six distinct variant prioritization strategies, we concluded that SpliceAI was the best method to accurately identify genomic variation disrupting normal pre-mRNA splicing. We determined this through (i) functional assessment of novel ‘variants of uncertain significance’ described in this study, and (ii) calculation of sensitivity and specificity for prioritization strategies to distinguish known splicing mutations from common variants in the general population. We describe novel disease-causing variants with support from cell based functional assays which underpin autosomal recessive, autosomal dominant and X-linked Mendelian disorders. This includes variants which are deeply intronic, within the nearby splice region of canonical splice sites and variants which activate cryptic splice sites within the protein-coding regions of genes. We integrated the best performing variant prioritization strategy alongside clinical diagnostic testing for 2783 individuals referred to a well-established targeted gene panel test available through the UK National Health Service. We show that integration of such strategies will increase accuracy and clarity of diagnostic reporting, including the identification of variants which could provide new diagnoses and new carrier findings for referred individuals. Functional assessment is essential for accurate clinical assessment of variants disrupting pre-mRNA splicing. We show through cell based functional assessments that variants impacting splicing may have complex impacts on pre-mRNA splicing, which may cause multiple interpretable consequences according to ACMG guidelines.
Pre-mRNA splicing is executed by the spliceosome, a complex of small nuclear RNAs (snRNAs) and numerous proteins. One such protein, 15.5K/Snu13p, is associated with the spliceosomal U4/U6.U5 tri-snRNP and box C/D small nucleolar ribonucleoprotein particles (snoRNPs), which act during preribosomal RNA (rRNA) processing. As such, it is the first splicing factor to be identified in two functionally distinct particles. 15.5K binds to an internal helix–bulge–helix (K-turn) structure in the U4 snRNA and two such structures in the U3 snoRNA. Previous work has concentrated on the structural basis of the interaction of 15.5K with the RNAs and has been carried out in vitro. Here we present a functional analysis of Snu13p in vivo, using a galactose inducible SNU13 strain to investigate the basis of three lethal mutations in Saccharomyces cerevisiae . Two are point mutations that map to the RNA-binding domain, and the third is a C-terminal deletion. These mutations result in accumulation of unspliced pre-mRNA, confirming a role for Snu13p in pre-mRNA splicing. In addition, these mutants also display rRNA processing defects that are variable in nature. Analysis of one mutant in the RNA-binding domain reveals a reduction in the levels of the U4 snRNA, U6 snRNA, and box C/D snoRNAs, but not H/ACA snoRNAs, supporting a role for Snu13p in accumulation and/or maintenance of specific RNAs. The mutations in the RNA-binding domain exhibit differential binding to the U4 snRNA and U3 snoRNA in vitro, suggesting that there are differences in the mode of interaction of Snu13p with these two RNAs.
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