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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., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being 'pathogenic' or 'benign' is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as 'pathogenic' or 'likely pathogenic'; one in five of these cases could lead to new or refined diagnoses., (© 2021. The Author(s).)

Defects in pre-mRNA splicing are frequently a cause of Mendelian disease. Despite the advent of next-generation sequencing, allowing a deeper insight into a patient's variant landscape, the ability to characterize variants causing splicing defects has not progressed with the same speed. To address this, recent years have seen a sharp spike in the number of splice prediction tools leveraging machine learning approaches, leaving clinical geneticists with a plethora of choices for in silico analysis. In this review, some basic principles of machine learning are introduced in the context of genomics and splicing analysis. A critical comparative approach is then used to describe seven recent machine learning-based splice prediction tools, revealing highly diverse approaches and common caveats. We find that, although great progress has been made in producing specific and sensitive tools, there is still much scope for personalized approaches to prediction of variant impact on splicing. Such approaches may increase diagnostic yields and underpin improvements to patient care.

The developmental disorder Burn‐McKeown Syndrome (BMKS) is characterised by choanal atresia and specific craniofacial features. BMKS is caused by biallelic variants in the pre‐messenger RNA splicing factor TXNL4A. Most patients have a loss‐of‐function variant in trans with a 34‐base pair (bp) deletion (type 1 Δ34) in the promoter region. Here, we identified two patients with BMKS. One individual has a TXNL4A c.93_94delCC, p.His32Argfs *21 variant combined with a type 1 Δ34 promoter deletion. The other has an intronic TXNL4A splice site variant (c.258‐3C>G) and a type 1 Δ34 promoter deletion. We show the c.258‐3C>G variant and a previously reported c.258‐2A>G variant, cause skipping of the final exon of TXNL4A in a minigene splicing assay. Furthermore, we identify putative transcription factor binding sites within the 56 bp of the TXNL4A promoter affected by the type 1 and type 2 Δ34 and use dual luciferase assays to identify a 22 bp repeated motif essential for TXNL4A expression within this promoter region. We propose that additional variants affecting critical transcription factor binding nucleotides within the 22 bp repeated motif could be relevant to BMKS aetiology. Finally, our data emphasises the need to analyse the non‐coding sequence in individuals where a single likely pathogenic coding variant is identified in an autosomal recessive disorder consistent with the clinical presentation. [ABSTRACT FROM AUTHOR]

Inherited retinal diseases (IRDs) are a diverse and variable group of rare human disorders. A large portion of the variability in phenotypic presentation associated with IRDs can be attributed to the specific gene carrying the disease-causing variation. The authors go on to demonstrate that variants in IRD genes may be modulated by the impact of other factors that alter the expression levels of these IRD genes. For example, their analyses show that 125 unique genomic variants are described in a disease database for I PRPF31 i , a gene known as a cause of autosomal dominant retinitis pigmentosa [[16]]. [Extracted from the article]

Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an essential, ubiquitously abundant protein involved in mRNA processing. Genetic variants in other members of the HNRNP family have been associated with neurodevelopmental disorders. Here, we describe 13 individuals with global developmental delay, intellectual disability, behavioral abnormalities, and subtle facial dysmorphology with heterozygous HNRNPC germline variants. Five of them bear an identical in-frame deletion of nine amino acids in the extreme C terminus. To study the effect of this recurrent variant as well as HNRNPC haploinsufficiency, we used induced pluripotent stem cells (iPSCs) and fibroblasts obtained from affected individuals. While protein localization and oligomerization were unaffected by the recurrent C-terminal deletion variant, total HNRNPC levels were decreased. Previously, reduced HNRNPC levels have been associated with changes in alternative splicing. Therefore, we performed a meta-analysis on published RNA-seq datasets of three different cell lines to identify a ubiquitous HNRNPC-dependent signature of alternative spliced exons. The identified signature was not only confirmed in fibroblasts obtained from an affected individual but also showed a significant enrichment for genes associated with intellectual disability. Hence, we assessed the effect of decreased and increased levels of HNRNPC on neuronal arborization and neuronal migration and found that either condition affects neuronal function. Taken together, our data indicate that HNRNPC haploinsufficiency affects alternative splicing of multiple intellectual disability-associated genes and that the developing brain is sensitive to aberrant levels of HNRNPC. Hence, our data strongly support the inclusion of HNRNPC to the family of HNRNP-related neurodevelopmental disorders. [Display omitted] We identified genetic variants of HNRNPC in 13 individuals with intellectual disability and global developmental delay. Through a meta-analysis of multiple cell types, we found that loss of HNRNPC affects alternative splicing, in particular of intellectual disability-associated genes. In vivo assays confirmed that neurodevelopment was affected by aberrant HNRNPC levels. [ABSTRACT FROM AUTHOR]