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<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>RNA-sequencing of patient biosamples is a promising approach to delineate the impact of genomic variants on splicing, but variable gene expression between tissues complicates selection of appropriate tissues. Relative expression level is often used as a metric to predict RNA-sequencing utility. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA-sequencing, overcoming some issues with using expression values alone.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>We derive a novel metric, <jats:italic>Minimum Required Sequencing Depth</jats:italic> (MRSD), for all genes across three human biosamples (whole blood, lymphoblastoid cell lines (LCLs) and skeletal muscle). MRSD estimates the depth of sequencing required from RNA-sequencing to achieve user-specified sequencing coverage of a gene, transcript or group of genes of interest. MRSD predicts levels of splice junction coverage with high precision (90.1-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that LCLs are the optimum source of RNA, of the three investigated biosamples, for 69.3% of gene panels. Our approach demonstrates that up to 59.4% of variants of uncertain significance in ClinVar predicted to impact splicing could be functionally assayed by RNA-sequencing in at least one of the investigated biosamples.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>We demonstrate the power of MRSD as a metric to inform choice of appropriate biosamples for the functional assessment of splicing aberrations. We apply MRSD in the context of Mendelian genetic disorders and illustrate its benefits over expression-based approaches. We anticipate that the integration of MRSD into clinical pipelines will improve variant interpretation and, ultimately, diagnostic yield.</jats:p></jats:sec>

Original publication

DOI

10.1101/2021.03.19.21253973

Type

Journal article

Publisher

Cold Spring Harbor Laboratory

Publication Date

20/03/2021