Assigning single clinical features to their disease-locus in large deletions: the example of chromosome 1q23-25 deletion syndrome
18 Jun 2020-Vol. 4, Iss: 3, pp 114-132
TL;DR: To overcome the problem of incomplete penetrance, an algorithm is developed that is applied to the deletion region 1q23.3-q25, which contains three SROs, each contributing to the abnormal phenotype without clearly distinguishing between the different malformations.
Abstract: Aim: Assigning a disease-locus within the shortest regions of overlap (SRO) shared by deleted/duplicated subjects presenting this disease is a robust mapping approach, although the presence of different malformation traits and their attendance only in a part of the affected subjects can hinder the interpretation. To overcome the problem of incomplete penetrance, we developed an algorithm that we applied to the deletion region 1q23.3-q25, which contains three SROs, each contributing to the abnormal phenotype without clearly distinguishing between the different malformations. We describe six new subjects, including a healthy father and his daughter, with 1q23.3-q25 deletion of different sizes. The aim of this study was to correlate specific abnormal traits to the haploinsufficiency of specific gene/putative regulatory elements. Methods: Merging cases with those in the literature, we considered four traits, namely intellectual disability (ID), microcephaly, short-hands/feet, and brachydactyly, and conceived a mathematical model to predict with what probability the haploinsufficiency of a specific portion of the deletion region is associated with one of the four
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26 Nov 2020
TL;DR: Translational aspects in neurodevelopmental disorders are studied to help understand the role of language in the development of autistic children.
Abstract: © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Translational aspects in neurodevelopmental disorders
7 citations
Cites methods from "Assigning single clinical features ..."
...More classical genotype-phenotype studies are shown in two examples: “Spectrum of MECP2 mutations in Indian females with Rett Syndrome - a large cohort study” and “Assigning single clinical features to their disease-locus in large deletions: the example of chromosome 1q23-25 deletion syndrome”([7,8])....
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TL;DR: In this paper , a probabilistic model was developed to better delineate the role of hemizygosity of specific regions in selected traits by leveraging information both from penetrant and non- penetrant deletions.
Abstract: Abstract Background Individuals with the 2p15p16.1 microdeletion syndrome share a complex phenotype including neurodevelopmental delay, brain malformations, microcephaly, and autistic behavior. The analysis of the shortest region of overlap (SRO) between deletions in ~ 40 patients has led to the identification of two critical regions and four strongly candidate genes ( BCL11A, REL, USP34 and XPO1 ). However, the delineation of their role in the occurrence of specific traits is hampered by their incomplete penetrance. Objective To better delineate the role of hemizygosity of specific regions in selected traits by leveraging information both from penetrant and non − penetrant deletions. Methods Deletions in patients that do not present a specific trait cannot contribute to delineate the SROs. We recently developed a probabilistic model that, by considering also the non − penetrant deletions, allows a more reliable assignment of peculiar traits to specific genomic segments. We apply this method adding two new patients to the published cases. Results Our results delineate an intricate pattern of genotype − phenotype correlation where BCL11A emerges as the main gene for autistic behavior while USP34 and/or XPO1 haploinsufficiency are mainly associated with microcephaly, hearing loss and IUGR. BCL11A, USP34 and XPO1 genes are broadly related with brain malformations albeit with distinct patterns of brain damage. Conclusions The observed penetrance of deletions encompassing different SROs and that predicted when considering each single SRO as acting independently, may reflect a more complex model than the additive one. Our approach may improve the genotype/phenotype correlation and may help to identify specific pathogenic mechanisms in contiguous gene syndromes.
References
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TL;DR: 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.
Abstract: 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.
20,557 citations
"Assigning single clinical features ..." refers methods in this paper
...ANNOVAR software tool([13]) and then filtered according to their predicted effects and allele frequencies in the available public databases (dbSNP http://www....
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TL;DR: This unit describes how to use BWA and the Genome Analysis Toolkit to map genome sequencing data to a reference and produce high‐quality variant calls that can be used in downstream analyses.
Abstract: This unit describes how to use BWA and the Genome Analysis Toolkit (GATK) to map genome sequencing data to a reference and produce high-quality variant calls that can be used in downstream analyses. The complete workflow includes the core NGS data processing steps that are necessary to make the raw data suitable for analysis by the GATK, as well as the key methods involved in variant discovery using the GATK.
5,150 citations
"Assigning single clinical features ..." refers methods in this paper
...org/gatk/)([11]), including base quality score recalibration, indel realignment, duplicate removal, and SNP, and insertions/deletion (INDEL) identification were used according to the recommendations of GATK best practices([12])....
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TL;DR: Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes.
781 citations
TL;DR: A protocol to use the ANNOVAR (ANNOtate VARiation) software to facilitate fast and easy variant annotations, including gene-based, region-based and filter-based annotations on a variant call format (VCF) file generated from human genomes.
Abstract: This protocol describes how to annotate genomic variants using either the ANNOVAR software or the web-based wANNOVAR tool. Recent developments in sequencing techniques have enabled rapid and high-throughput generation of sequence data, democratizing the ability to compile information on large amounts of genetic variations in individual laboratories. However, there is a growing gap between the generation of raw sequencing data and the extraction of meaningful biological information. Here, we describe a protocol to use the ANNOVAR (ANNOtate VARiation) software to facilitate fast and easy variant annotations, including gene-based, region-based and filter-based annotations on a variant call format (VCF) file generated from human genomes. We further describe a protocol for gene-based annotation of a newly sequenced nonhuman species. Finally, we describe how to use a user-friendly and easily accessible web server called wANNOVAR to prioritize candidate genes for a Mendelian disease. The variant annotation protocols take 5–30 min of computer time, depending on the size of the variant file, and 5–10 min of hands-on time. In summary, through the command-line tool and the web server, these protocols provide a convenient means to analyze genetic variants generated in humans and other species.
654 citations
"Assigning single clinical features ..." refers methods in this paper
...org/gatk/)([11]), including base quality score recalibration, indel realignment, duplicate removal, and SNP, and insertions/deletion (INDEL) identification were used according to the recommendations of GATK best practices([12])....
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Harvard University1, University of North Carolina at Chapel Hill2, University of Texas at Austin3, VU University Amsterdam4, Broad Institute5, Icahn School of Medicine at Mount Sinai6, Cardiff University7, Stanford University8, Federal University of São Paulo9, University of Pennsylvania10, University of Helsinki11, University of Illinois at Urbana–Champaign12, University of California, Los Angeles13, Centre for Addiction and Mental Health14, University Medical Center Groningen15, Universidade Federal do Rio Grande do Sul16, King's College London17, University of Edinburgh18, University of Oslo19, Lundbeck20, Indiana University21, Veterans Health Administration22, State University of New York Upstate Medical University23, Yale University24, University of Florida25, VA Boston Healthcare System26, Virginia Commonwealth University27, Maine Medical Center28, University of California, Berkeley29, University of Queensland30
TL;DR: A meta-analysis of genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders.
Abstract: Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.
346 citations