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      Whole-exome Sequencing for the Identification of Rare Variants in Primary Immunodeficiency Genes in Children With Sepsis: A Prospective, Population-based Cohort Study

      research-article
      1 , 2 , 3 , 4 , 5 , 1 , 2 , 6 , 7 , 8 , 9 , 10 , 8 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 17 , 4 , 18 , 19 , 1 , 2 , 1 , 2 , 20 , 21 , 22 , 23 , 8 , 8 , 8 , 10 , 4 , 1 , 2 , 24 , 4 , 25 , 26
      Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
      Oxford University Press
      child, exome sequencing, genomics, immunodeficiency, sepsis, variant, variants of uncertain significance

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          Abstract

          Background

          The role of primary immunodeficiencies (PID) in susceptibility to sepsis remains unknown. It is unclear whether children with sepsis benefit from genetic investigations. We hypothesized that sepsis may represent the first manifestation of underlying PID. We applied whole-exome sequencing (WES) to a national cohort of children with sepsis to identify rare, predicted pathogenic variants in PID genes.

          Methods

          We conducted a multicenter, population-based, prospective study including previously healthy children aged ≥28 days and <17 years admitted with blood culture-proven sepsis. Using a stringent variant filtering procedure, analysis of WES data was restricted to rare, predicted pathogenic variants in 240 PID genes for which increased susceptibility to bacterial infection has been reported.

          Results

          There were 176 children presenting with 185 sepsis episodes who underwent WES (median age, 52 months; interquartile range, 15.4–126.4). There were 41 unique predicted pathogenic PID variants (1 homozygous, 5 hemizygous, and 35 heterozygous) found in 35/176 (20%) patients, including 3/176 (2%) patients carrying variants that were previously reported to lead to PID. The variants occurred in PID genes across all 8 PID categories, as defined by the International Union of Immunological Societies. We did not observe a significant correlation between clinical or laboratory characteristics of patients and the presence or absence of PID variants.

          Conclusions

          Applying WES to a population-based cohort of previously healthy children with bacterial sepsis detected variants of uncertain significance in PID genes in 1 out of 5 children. Future studies need to investigate the functional relevance of these variants to determine whether variants in PID genes contribute to pediatric sepsis susceptibility.

          Abstract

          In this population-based cohort, whole-exome sequencing identified known and unknown, rare, predicted pathogenic variants in primary immunodeficiency genes in 1 of 5 children with proven sepsis. Future studies need to validate whether these variants contribute to sepsis susceptibility.

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          Most cited references40

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          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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            The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

            Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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              • Abstract: found
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              Is Open Access

              Fast and accurate long-read alignment with Burrows–Wheeler transform

              Motivation: Many programs for aligning short sequencing reads to a reference genome have been developed in the last 2 years. Most of them are very efficient for short reads but inefficient or not applicable for reads >200 bp because the algorithms are heavily and specifically tuned for short queries with low sequencing error rate. However, some sequencing platforms already produce longer reads and others are expected to become available soon. For longer reads, hashing-based software such as BLAT and SSAHA2 remain the only choices. Nonetheless, these methods are substantially slower than short-read aligners in terms of aligned bases per unit time. Results: We designed and implemented a new algorithm, Burrows-Wheeler Aligner's Smith-Waterman Alignment (BWA-SW), to align long sequences up to 1 Mb against a large sequence database (e.g. the human genome) with a few gigabytes of memory. The algorithm is as accurate as SSAHA2, more accurate than BLAT, and is several to tens of times faster than both. Availability: http://bio-bwa.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Journal
                Clin Infect Dis
                Clin Infect Dis
                cid
                Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
                Oxford University Press (US )
                1058-4838
                1537-6591
                15 November 2020
                18 March 2020
                18 March 2020
                : 71
                : 10
                : e614-e623
                Affiliations
                [1 ] Swiss Institute of Bioinformatics , Lausanne, Switzerland
                [2 ] Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne , Lausanne, Switzerland
                [3 ] Neonatal Intensive Care Unit, Fondazione Institute for Research, Hospitalization and Health Care (IRCCS) Policlinico San Matteo , Pavia, Italy
                [4 ] University Children’s Hospital Zurich and the Children’s Research Center , Zurich, Switzerland
                [5 ] University of Zurich , Zurich, Switzerland
                [6 ] Division of Genetics and Rheumatology, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
                [7 ] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT , Cambridge, Massachusetts, USA
                [8 ] Section of Paediatrics , Imperial College London , London, United Kingdom
                [9 ] Section of Virology , Imperial College London , London, United Kingdom
                [10 ] Department of Paediatrics, Bern University Hospital, Inselspital, University of Bern , Bern, Switzerland
                [11 ] Service of Neonatology, Department Woman-Mother-Child, and Infectious Diseases Service, Department of Medicine, Lausanne University Hospital , Lausanne, Switzerland
                [12 ] Department of Paediatrics, Children’s Hospital Lucerne , Lucerne, Switzerland
                [13 ] Paediatric Infectious Diseases Unit, Children’s Hospital of Geneva, University Hospitals of Geneva , Geneva, Switzerland
                [14 ] Infectious Diseases and Vaccinology, University of Basel Children’s Hospital , Basel, Switzerland
                [15 ] Children’s Hospital Aarau , Aarau, Switzerland
                [16 ] Children’s Hospital of Eastern Switzerland St. Gallen , St. Gallen, Switzerland
                [17 ] Department of Neonatology, University Hospital Zurich , Zurich, Switzerland
                [18 ] Department of Paediatrics, Cantonal Hospital Graubuenden , Chur, Switzerland
                [19 ] Institute of Social and Preventive Medicine, University of Bern , Bern, Switzerland
                [20 ] Translational Paediatrics and Infectious Diseases Section, Paediatrics Department , Santiago de Compostela, Spain
                [21 ] Instituto de Investigación Sanitaria de Santiago, Genetics, Vaccines, Infectious Diseases and Paediatrics Research Group , Santiago de Compostela, Spain
                [22 ] Academic Medical Center, Emma Children’s Hospital, University of Amsterdam , Amsterdam, The Netherlands
                [23 ] Institute of Molecular Biosciences, The University of Queensland , Brisbane, Australia
                [24 ] Precision Medicine Unit, Lausanne University Hospital , Lausanne, Switzerland
                [25 ] Paediatric Critical Care Research Group, Child Health Research Centre, The University of Queensland , Brisbane, Australia
                [26 ] Paediatric Intensive Care Unit, Queensland Children’s Hospital, Children’s Health Queensland , Brisbane, Australia
                Author notes
                Correspondence: L. J. Schlapbach, Paediatric Critical Care Research Group, Child Health Research Centre, The University of Queensland, South Brisbane QLD 4101 Australia ( l.schlapbach@ 123456uq.edu.au ).

                A.B. and J.T. contributed equally to this work.

                Article
                ciaa290
                10.1093/cid/ciaa290
                7744985
                32185379
                71c22e69-24f0-40f0-891b-d04800c78bb6
                © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 29 March 2019
                : 23 February 2020
                : 15 March 2020
                : 21 May 2020
                Page count
                Pages: 10
                Funding
                Funded by: Swiss National Science Foundation, DOI 10.13039/501100001711;
                Award ID: 342730_153158/1
                Categories
                Online Only Articles
                Major Articles
                AcademicSubjects/MED00290

                Infectious disease & Microbiology
                child,exome sequencing,genomics,immunodeficiency,sepsis,variant,variants of uncertain significance

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