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      Whole-Exome Sequencing in the molecular diagnosis of individuals with congenital anomalies of kidney and urinary tract and identification of a new causative gene

      research-article
      , MD, FACMG 1 , 2 , 3 , 4 , , MBS, MS 1 , 2 , 4 , , PhD 5 , , PhD 1 , , PhD 1 , , PhD 1 , , MD 3 , 4 , , MS 5 , , MS 5 , , MD 4 , 6 , , MD 4 , 6 , , MD 4 , 6 , , MD 4 , 6 , , MD 4 , 6 , , MD 4 , 6 , , MD, PhD 1 , 4 , , PhD 1 , , MD 4 , 6 , , MD, PhD 4 , 6 , , MD, MPH 7 , , MS 7 , , MD, PhD 8 , , MD 9 , , MS 9 , , MD, PhD 1 , 4 , , MD, PhD 1 , 4 , , MS 1 , , MD 1 , 4 , 10 , , MD 3 , 4 , , PhD 1 , 5 , , MD, PhD 1 , 4 , , MD 3 , 4 , , MD 1 , , MD 4 , 6 , , MD, PhD 1 , 4 , 5 , 11 , , PhD 2 , 3 , 12
      Genetics in medicine : official journal of the American College of Medical Genetics
      CAKUT, WES, FOXP1, PAX2, HNF1B, EYA1

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          Abstract

          Purpose

          To investigate the utility of whole-exome sequencing (WES) to define a molecular diagnosis in patients clinically diagnosed with congenital anomalies of kidney and urinary tract (CAKUT).

          Methods

          WES was performed in 62 families with CAKUT. WES data were analyzed for Single Nucleotide Variants (SNVs) in 35 known CAKUT genes, putatively deleterious sequence changes in new candidate genes, and potentially disease-associated copy-number variants (CNVs).

          Results

          In approximately 5% of families, pathogenic SNVs were identified in PAX2, HNF1B, and EYA1. Observed phenotypes in these families expand the current understanding about the role of these genes in CAKUT. Four pathogenic CNVs were also identified using two CNV detection tools. In addition, we found one deleterious de novo SNV in FOXP1 among the 62 families with CAKUT. Database of clinical BMGL laboratory was queried and seven additional unrelated individuals with novel de novo SNVs in FOXP1 were identified. Six of these 8 individuals with FOXP1 SNVs, have syndromic urinary tract defects, implicating this gene in urinary tract development.

          Conclusion

          We conclude that WES can be used to identify the molecular etiology (SNVs, CNVs) in a subset of individuals with CAKUT. WES can also help identify novel CAKUT genes.

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          Most cited references24

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          Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

          The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
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            Copy number variation detection and genotyping from exome sequence data

            While exome sequencing is readily amenable to single-nucleotide variant discovery, the sparse and nonuniform nature of the exome capture reaction has hindered exome-based detection and characterization of genic copy number variation. We developed a novel method using singular value decomposition (SVD) normalization to discover rare genic copy number variants (CNVs) as well as genotype copy number polymorphic (CNP) loci with high sensitivity and specificity from exome sequencing data. We estimate the precision of our algorithm using 122 trios (366 exomes) and show that this method can be used to reliably predict (94% overall precision) both de novo and inherited rare CNVs involving three or more consecutive exons. We demonstrate that exome-based genotyping of CNPs strongly correlates with whole-genome data (median r 2 = 0.91), especially for loci with fewer than eight copies, and can estimate the absolute copy number of multi-allelic genes with high accuracy (78% call level). The resulting user-friendly computational pipeline, CoNIFER ( co py n umber i nference f rom e xome r eads), can reliably be used to discover disruptive genic CNVs missed by standard approaches and should have broad application in human genetic studies of disease.
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              An integrative variant analysis suite for whole exome next-generation sequencing data

              Background Whole exome capture sequencing allows researchers to cost-effectively sequence the coding regions of the genome. Although the exome capture sequencing methods have become routine and well established, there is currently a lack of tools specialized for variant calling in this type of data. Results Using statistical models trained on validated whole-exome capture sequencing data, the Atlas2 Suite is an integrative variant analysis pipeline optimized for variant discovery on all three of the widely used next generation sequencing platforms (SOLiD, Illumina, and Roche 454). The suite employs logistic regression models in conjunction with user-adjustable cutoffs to accurately separate true SNPs and INDELs from sequencing and mapping errors with high sensitivity (96.7%). Conclusion We have implemented the Atlas2 Suite and applied it to 92 whole exome samples from the 1000 Genomes Project. The Atlas2 Suite is available for download at http://sourceforge.net/projects/atlas2/. In addition to a command line version, the suite has been integrated into the Genboree Workbench, allowing biomedical scientists with minimal informatics expertise to remotely call, view, and further analyze variants through a simple web interface. The existing genomic databases displayed via the Genboree browser also streamline the process from variant discovery to functional genomics analysis, resulting in an off-the-shelf toolkit for the broader community.
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                Author and article information

                Journal
                9815831
                22061
                Genet Med
                Genet. Med.
                Genetics in medicine : official journal of the American College of Medical Genetics
                1098-3600
                1530-0366
                11 August 2016
                22 September 2016
                23 March 2017
                : 10.1038/gim.2016.131
                Affiliations
                [1 ] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
                [2 ] Center for Reproductive Medicine, Baylor College of Medicine, Houston, TX, USA
                [3 ] Scott Department of Urology, Baylor College of Medicine, Houston, TX, USA
                [4 ] Texas Children's Hospital, Houston, TX, USA
                [5 ] Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
                [6 ] Renal Section, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
                [7 ] Johns Hopkins Children's Center, Institute of Genetic Medicine, Baltimore, MD, USA
                [8 ] NYS Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA
                [9 ] Sanford Children's Hospital, Sioux Falls, SD, USA
                [10 ] Department of Ophthalmology, Baylor College of Medicine, Houston, TX, USA
                [11 ] Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
                [12 ] Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
                Author notes
                Corresponding author: Mir Reza Bekheirnia, MD, FACMG, Assistant Professor, Department of Molecular and Human Genetics; K12 Scholar, Department of Urology, Texas Children's Hospital, Address: Texas Children's Hospital, 1102 Bates St., Suite# 245, Houston, TX 77030 , USA, Tel: 832-824-4227, Fax: 832-825-9330, bekheirn@ 123456bcm.edu
                Article
                NIHMS807719
                10.1038/gim.2016.131
                5362362
                27657687
                06a0f96a-45a4-4b52-8594-6014ec5d69a2

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                Genetics
                cakut,wes,foxp1,pax2,hnf1b,eya1
                Genetics
                cakut, wes, foxp1, pax2, hnf1b, eya1

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