MRSD: A quantitative approach for assessing suitability of RNA-seq in the investigation of mis-splicing in Mendelian disease.
MRSD: A quantitative approach for assessing suitability of RNA-seq in the investigation of mis-splicing in Mendelian disease.
复制标题
DOI:
10.1016/j.ajhg.2021.12.014
复制
发表时间:
2022-02-03
影响因子:
9.8
通讯作者:
Ellingford JM
中科院分区:
文献类型:
--
作者:
Rowlands CF;Taylor A;Rice G;Whiffin N;Hall HN;Newman WG;Black GCM;kConFab Investigators;O'Keefe RT;Hubbard S;Douglas AGL;Baralle D;Briggs TA;Ellingford JM
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.
登录
查看更多内容
影响因子:
17.1
作者:
Cummings BB;Marshall JL;Tukiainen T;Lek M;Donkervoort S;Foley AR;Bolduc V;Waddell LB;Sandaradura SA;O'Grady GL;Estrella E;Reddy HM;Zhao F;Weisburd B;Karczewski KJ;O'Donnell-Luria AH;Birnbaum D;Sarkozy A;Hu Y;Gonorazky H;Claeys K;Joshi H;Bournazos A;Oates EC;Ghaoui R;Davis MR;Laing NG;Topf A;Genotype-Tissue Expression Consortium;Kang PB;Beggs AH;North KN;Straub V;Dowling JJ;Muntoni F;Clarke NF;Cooper ST;Bönnemann CG;MacArthur DG
通讯作者:
MacArthur DG
影响因子:
8.8
作者:
Aicher, Joseph K.;Jewell, Paul;Bhoj, Elizabeth J.
通讯作者:
Bhoj, Elizabeth J.
影响因子:
82.9
作者:
Fresard, Laure;Smail, Craig;Dyment, David
通讯作者:
Dyment, David
影响因子:
4
作者:
Johnston, Jennifer J.;Williamson, Kathleen A.;Biesecker, Leslie G.
通讯作者:
Biesecker, Leslie G.
影响因子:
16.6
作者:
Buskin A;Zhu L;Chichagova V;Basu B;Mozaffari-Jovin S;Dolan D;Droop A;Collin J;Bronstein R;Mehrotra S;Farkas M;Hilgen G;White K;Pan KT;Treumann A;Hallam D;Bialas K;Chung G;Mellough C;Ding Y;Krasnogor N;Przyborski S;Zwolinski S;Al-Aama J;Alharthi S;Xu Y;Wheway G;Szymanska K;McKibbin M;Inglehearn CF;Elliott DJ;Lindsay S;Ali RR;Steel DH;Armstrong L;Sernagor E;Urlaub H;Pierce E;Lührmann R;Grellscheid SN;Johnson CA;Lako M
通讯作者:
Lako M