Dataset Information

Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants.

ABSTRACT: BACKGROUND:Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3'ss. RESULTS:We used a large set of constitutive and alternative human 3'ss collected from Ensembl (n?=?264,787 3'ss) and from in-house RNAseq experiments (n?=?51,986 3'ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3'ss (99.48 and 65.84% accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17%. CONCLUSIONS:Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3'ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area.

SUBMITTER: Leman R

PROVIDER: S-EPMC6988378 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants.

Leman Raphaël R Tubeuf Hélène H Raad Sabine S Tournier Isabelle I Derambure Céline C Lanos Raphaël R Gaildrat Pascaline P Castelain Gaia G Hauchard Julie J Killian Audrey A Baert-Desurmont Stéphanie S Legros Angelina A Goardon Nicolas N Quesnelle Céline C Ricou Agathe A Castera Laurent L Vaur Dominique D Le Gac Gérald G Ka Chandran C Fichou Yann Y Bonnet-Dorion Françoise F Sevenet Nicolas N Guillaud-Bataille Marine M Boutry-Kryza Nadia N Schultz Inès I Caux-Moncoutier Virginie V Rossing Maria M Walker Logan C LC Spurdle Amanda B AB Houdayer Claude C Martins Alexandra A Krieger Sophie S

BMC genomics 20200128 1

<h4>Background</h4>Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3'ss.<h4>Results</h4>We used a large set of cons ...[more]

PMID: 31992191

Similar Datasets

Project description:Malignant hyperthermia (MH) is a pharmacogenetic disorder of skeletal muscle metabolism characterized by generalized muscle rigidity, increased body temperature, rhabdomyolysis, hyperkalemia and severe metabolic acidosis. The underlying mechanism of MH involves excessive Ca2+ release from myotubes via the ryanodine receptor type 1 (RYR1) and the voltage-dependent L-type calcium channel (CACNA1S). As more than 300 variants of unknown significance have been detected to date, we examined whether freely available pathogenicity prediction tools are able to detect relevant MH causing variants. In this diagnostic accuracy study, blood samples from 235 individuals with a history of a clinical malignant hyperthermia or their close relatives were genetically screened for RYR1 variants of all 106 RYR1 exons and additionally for known variants of CACNA1S. In vitro contracture tests were conducted on muscle biopsies obtained from all individuals, independently of whether a pathogenic variant, a variant of unknown significance or no variant was detected. Comparisons were made to three established bioinformatic pathogenicity detection tools to identify the clinical impact of the variants of unknown significance. All detected genetic variants were tested for pathogenicity by three in silico approaches and compared to the in vitro contracture test. Sensitivity and specificity of exon screening of all individuals listed in our MH database was analyzed. Exon screening identified 97 (41%) of the 235 individuals as carriers of pathogenic variants. Variants of unknown significance were detected in 21 individuals. Variants of unknown significance were subdivided into 19 malignant-hyperthermia-susceptible individuals and 2 non-malignant-hyperthermia-susceptible individuals. All pathogenic variants as well as the malignant-hyperthermia-suspectible variants were correctly identified by the bioinformatic prediction tools. Sensitivity of in silico approaches ranged between 0.71 and 0.98 (Polyphen 0.94 [CI 95% 0.75; 0.99]; Sift 0.98 [CI 95% 0.81; 0.99]; MutationTaster 0.92 [CI 95% 0.75; 0.99]). Specificity differed depending on the used tool (Polphen 0.98 [CI 95% 0.32; 0.99]; Sift 0.98 [CI 95% 0.32; 0.99]; MutationTaster 0.00 [CI 95% 0.00; 0.60]). All pathogenic variants and variants of unknown significance were scored as probably damaging in individuals, demonstrating a high sensitivity. Specificity was very low in one of the three tested programs. However, due to potential genotype-phenotype discordance, bioinformatic prediction tools are currently of limited value in diagnosing pathogenicity of MH-susceptible variants.

Dataset Information

Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants.

Publications

Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets