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      Phenotype-Driven Virtual Panel Is an Effective Method to Analyze WES Data of Neurological Disease

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          Abstract

          Objective: Whole Exome Sequencing (WES) is an effective diagnostic method for complicated and multi-system involved rare diseases. However, annotation and analysis of the WES result, especially for single case analysis still remain a challenge. Here, we introduce a method called phenotype-driven designing “virtual panel” to simplify the procedure and assess the diagnostic rate of this method.

          Methods: WES was performed in samples of 30 patients, core phenotypes of probands were then extracted and inputted into an in-house software, “Mingjian” to calculate and generate associated gene list of a virtual panel. Mingjian is a self-updating genetic disease computer supportive diagnostic system that based on the databases of HPO, OMIM, HGMD. The virtual panel that generated by Mingjian system was then used to filter and annotate candidate mutations. Sanger sequencing and co-segregation analysis among the family were then used to confirm the filtered mutants.

          Result: We first used phenotype-driven designing “virtual panel” to analyze the WES data of a patient whose core phenotypes are ataxia, seizures, esotropia, puberty and gonadal disorders, and global developmental delay. Two mutations, c.430T > C and c.640G > C in PMM2 were identified by this method. This result was also confirmed by Sanger sequencing among the family. The same analysing method was then used in the annotation of WES data of other 29 neurological rare disease patients. The diagnostic rate was 65.52%, which is significantly higher than the diagnostic rate before.

          Conclusion: Phenotype-driven designing virtual panel could achieve low-cost individualized analysis. This method may decrease the time-cost of annotation, increase the diagnostic efficiency and the diagnostic rate.

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          Most cited references25

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          Analysis of genetic inheritance in a family quartet by whole-genome sequencing.

          We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of approximately 1.1 x 10(-8) per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.
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            Diagnostic clinical genome and exome sequencing.

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              Disease gene identification strategies for exome sequencing.

              Next generation sequencing can be used to search for Mendelian disease genes in an unbiased manner by sequencing the entire protein-coding sequence, known as the exome, or even the entire human genome. Identifying the pathogenic mutation amongst thousands to millions of genomic variants is a major challenge, and novel variant prioritization strategies are required. The choice of these strategies depends on the availability of well-phenotyped patients and family members, the mode of inheritance, the severity of the disease and its population frequency. In this review, we discuss the current strategies for Mendelian disease gene identification by exome resequencing. We conclude that exome strategies are successful and identify new Mendelian disease genes in approximately 60% of the projects. Improvements in bioinformatics as well as in sequencing technology will likely increase the success rate even further. Exome sequencing is likely to become the most commonly used tool for Mendelian disease gene identification for the coming years.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                09 January 2019
                2018
                : 9
                : 1529
                Affiliations
                [1] 1Department of Neurology, Beijing Children’s Hospital, National Centre for Children’s Health, Capital Medical University , Beijing, China
                [2] 2Running Gene Inc. , Beijing, China
                Author notes

                Edited by: Tieliu Shi, East China Normal University, China

                Reviewed by: Olimpia Musumeci, Università degli Studi di Messina, Italy; Zhiping Liu, Augusta University, United States

                *Correspondence: Xu Wang, zfwx05@ 123456126.com

                These authors have contributed equally to this work

                This article was submitted to Translational Pharmacology, a section of the journal Frontiers in Pharmacology

                Article
                10.3389/fphar.2018.01529
                6333749
                30687093
                c09ac0ae-d4c9-4e92-be70-c8be67dc3112
                Copyright © 2019 Wang, Shen, Fang, Ding, Zhang, Cao and An.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 July 2018
                : 13 December 2018
                Page count
                Figures: 10, Tables: 5, Equations: 0, References: 38, Pages: 11, Words: 0
                Categories
                Pharmacology
                Methods

                Pharmacology & Pharmaceutical medicine
                wes,phenotype-driven,virtual panel,rare disease,annotation
                Pharmacology & Pharmaceutical medicine
                wes, phenotype-driven, virtual panel, rare disease, annotation

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