A comprehensive framework for prioritizing variants in exome sequencing studies of Mendelian diseases

Li, Miaoxin; Gui, Hongsheng; Kwan, Johnny S. H.; Bao, Suying; Sham, Pak C.

doi:10.1093/nar/gkr1257

Cited by 236 publications

(213 citation statements)

References 29 publications

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“…The rare variants were defined as the variants with a MAF of ≤0.01 in any of the databases in the 1000 Genomes Project (all population, Asian population, European population, and African population) and ESP6500. We defined the deleterious variants as the loss-offunction (stopgain, frameshift insertion, and frameshift deletion) variants, nonframeshift INDELs, or missense variants that are predicted to be damaging by KGGSEq (21). KGGSeq combines the prediction scores from five algorithms (SIFT, Polyphen-2, LRT, MutationTaster, and PhyloP) by the logistic regression method to estimate a probability of a variant being pathogenic.…”

Section: Methodsmentioning

confidence: 99%

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Whole-exome sequencing identifies MST1R as a genetic susceptibility gene in nasopharyngeal carcinoma

Dai

Zheng

Cheung

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Multiple factors, including host genetics, environmental factors, and Epstein-Barr virus (EBV) infection, contribute to nasopharyngeal carcinoma (NPC) development. To identify genetic susceptibility genes for NPC, a whole-exome sequencing (WES) study was performed in 161 NPC cases and 895 controls of Southern Chinese descent. The gene-based burden test discovered an association between macrophage-stimulating 1 receptor (MST1R) and NPC. We identified 13 independent cases carrying the MST1R pathogenic heterozygous germ-line variants, and 53.8% of these cases were diagnosed with NPC aged at or even younger than 20 y, indicating that MST1R germline variants are relevant to disease early-age onset (EAO) (age of ≤20 y). In total, five MST1R missense variants were found in EAO cases but were rare in controls (EAO vs. control, 17.9% vs.

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Section: Methodsmentioning

confidence: 99%

“…They are located at the evolutionally conserved residues (SI Appendix, Fig. S4) and are predicted to be pathogenic by KGGSEq (21). Out of five variants identified in the EAO cases, two variants (c.G979A:p.A327T and c.G917A: p.R306H) are only 62 bp apart.…”

Section: Gene-level Analysis Identified the Association Of Mst1r Delementioning

confidence: 99%

Whole-exome sequencing identifies MST1R as a genetic susceptibility gene in nasopharyngeal carcinoma

Dai

Zheng

Cheung

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…GATK version 2.4.7 (Broad Institute, Cambridge, MA, USA) with the UnifiedGenotyper algorithm was applied for variant calling including all steps mentioned in the best practice pipeline. 11 KGG-seq 12 was used for annotation of detected variants, but in-house scripts were applied for filtering based on family pedigree and intersections.…”

Section: Exome Sequencingmentioning

confidence: 99%

Congenital protein losing enteropathy: an inborn error of lipid metabolism due to DGAT1 mutations

et al. 2016

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Protein-losing enteropathy (PLE) is a clinical disorder of protein loss from the gastrointestinal system that results in hypoproteinemia and malnutrition. This condition is associated with a wide range of gastrointestinal disorders. Recently, a unique syndrome of congenital PLE associated with biallelic mutations in the DGAT1 gene has been reported in a single family. We hypothesize that mutations in this gene are responsible for undiagnosed cases of PLE in infancy. Here we investigated three children in two families presenting with severe diarrhea, hypoalbuminemia and PLE, using clinical studies, homozygosity mapping, and exome sequencing. In one family, homozygosity mapping using SNP arrays revealed the DGAT1 gene as the best candidate gene for the proband. Sequencing of all the exons including flanking regions and promoter regions of the gene identified a novel homozygous missense variant, p.(Leu295Pro), in the highly conserved membrane-bound O-acyl transferase (MBOAT) domain of the DGAT1 protein. Expression studies verified reduced amounts of DGAT1 in patient fibroblasts. In a second family, exome sequencing identified a previously reported splice site mutation in intron 8. These cases of DGAT1 deficiency extend the molecular and phenotypic spectrum of PLE, suggesting a re-evaluation of the use of DGAT1 inhibitors for metabolic disorders including obesity and diabetes.

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“…The prediction scores of some of these methods have been compiled in the dbNSFP database for all known protein coding genome positions 4 . Besides, Li and colleagues proposed to combine five of them in a logistic regression framework 5 in order to globally improve predictive performance in comparison with individual scores. The idea of this contribution is twofold.…”

Section: Introductionmentioning

confidence: 99%

“…The idea of this contribution is twofold. First, we propose to combine the scores of different functional predictors using a machine learning method (random forest) that should be more suited to the nature of the problem than the logistic regression framework of Li and colleagues 5 . The performance of this method will be compared to the five models taken separately, to a logistic regression framework and to the recently published CADD method 6 .…”

Section: Introductionmentioning

confidence: 99%

Rfpred: A Random Forest Approach for Prediction of Missense Variants in Human Exome

Jabot–Hanin

Varet²,

Torès

et al. 2016

Preprint

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Exome sequencing is becoming a standard tool for gene mapping of genetic diseases. Given the vast amount of data generated by Next Generation Sequencing techniques, identification of disease causal variants is like finding a needle in a haystack. The impact assessment and the prioritization of potential pathogenic variants are expected to reduce work in biological validation, which is long and costly. One of the possible approaches to determine the most probable deleterious variants in individual exomes is to use protein function alteration prediction. We propose in this paper to use a machine learning approach, the random forest to build a new meta-score based on five previously described scores (SIFT, Polyphen2, LRT, PhyloP and MutationTaster) and compiled in the dbNSFP database. The functional meta-score was trained on a dataset of 61 500 non-synonymous Single Nucleotide Polymorphisms (SNPs). The random forest method (rfPred) appears to be globally better than each of the classifiers separately or in combination in a logistic regression model, and better than a newly described score (CADD) on independent validation sets. RfPred scores have been pre-calculated for all the possible non-synonymous SNPs of human exome and are freely accessible at the web-server http://www.sbim.fr/rfPred/

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A comprehensive framework for prioritizing variants in exome sequencing studies of Mendelian diseases

Cited by 236 publications

References 29 publications

Whole-exome sequencing identifies MST1R as a genetic susceptibility gene in nasopharyngeal carcinoma

Whole-exome sequencing identifies MST1R as a genetic susceptibility gene in nasopharyngeal carcinoma

Congenital protein losing enteropathy: an inborn error of lipid metabolism due to DGAT1 mutations

Rfpred: A Random Forest Approach for Prediction of Missense Variants in Human Exome

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