Targeted sequencing and <i>in vitro</i> splice assays shed light on <i>ABCA4</i>-associated retinopathies missing heritability

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Summary

The ABCA4 gene is the most frequently mutated Mendelian retinopathy-associated gene. Biallelic variants lead to a variety of phenotypes, however, for thousands of cases the underlying variants remain unknown. Here, we aim to shed further light on the missing heritability of ABCA4-associated retinopathy by analyzing a large cohort of macular dystrophy probands. A total of 858 probands were collected from 26 centers, of whom 722 carried no or one pathogenic ABCA4 variant, while 136 cases carried two ABCA4 alleles, one of which was a frequent mild variant, suggesting that deep-intronic variants (DIVs) or other cis-modifiers might have been missed. After single molecule molecular inversion probes (smMIPs)-based sequencing of the complete 128-kb ABCA4 locus, the effect of putative splice variants was assessed in vitro by midigene splice assays in HEK293T cells. The breakpoints of copy number variants (CNVs) were determined by junction PCR and Sanger sequencing. ABCA4 sequence analysis solved 207 of 520 (39.8%) naive or unsolved cases and 70 of 202 (34.7%) monoallelic cases, while additional causal variants were identified in 54 of 136 (39.7%) probands carrying two variants. Seven novel DIVs and six novel non-canonical splice site variants were detected in a total of 35 alleles and characterized, including the c.6283-321C>G variant leading to a complex splicing defect. Additionally, four novel CNVs were identified and characterized in five alleles. These results confirm that smMIPs-based sequencing of the complete ABCA4 gene provides a cost-effective method to genetically solve retinopathy cases and that several rare structural and splice altering defects remain undiscovered in Stargardt disease cases.

Abstract

ABCA4 sequence analysis in a heterogeneous cohort of ABCA4-associated retinopathy probands solved 277 of 722 (38.4%) cases, while additional variants were identified in 54 of 136 (39.7%) individuals known to already carry two variants. Additionally, complete ABCA4 locus sequencing lead to the identification of 13 novel splicing variants and four novel copy number variants.

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A method and server for predicting damaging missense mutations

Ivan Adzhubei, Steffen Schmidt, Leonid Peshkin … (2010)

To the Editor: Applications of rapidly advancing sequencing technologies exacerbate the need to interpret individual sequence variants. Sequencing of phenotyped clinical subjects will soon become a method of choice in studies of the genetic causes of Mendelian and complex diseases. New exon capture techniques will direct sequencing efforts towards the most informative and easily interpretable protein-coding fraction of the genome. Thus, the demand for computational predictions of the impact of protein sequence variants will continue to grow. Here we present a new method and the corresponding software tool, PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/), which is different from the early tool PolyPhen1 in the set of predictive features, alignment pipeline, and the method of classification (Fig. 1a). PolyPhen-2 uses eight sequence-based and three structure-based predictive features (Supplementary Table 1) which were selected automatically by an iterative greedy algorithm (Supplementary Methods). Majority of these features involve comparison of a property of the wild-type (ancestral, normal) allele and the corresponding property of the mutant (derived, disease-causing) allele, which together define an amino acid replacement. Most informative features characterize how well the two human alleles fit into the pattern of amino acid replacements within the multiple sequence alignment of homologous proteins, how distant the protein harboring the first deviation from the human wild-type allele is from the human protein, and whether the mutant allele originated at a hypermutable site2. The alignment pipeline selects the set of homologous sequences for the analysis using a clustering algorithm and then constructs and refines their multiple alignment (Supplementary Fig. 1). The functional significance of an allele replacement is predicted from its individual features (Supplementary Figs. 2–4) by Naïve Bayes classifier (Supplementary Methods). We used two pairs of datasets to train and test PolyPhen-2. We compiled the first pair, HumDiv, from all 3,155 damaging alleles with known effects on the molecular function causing human Mendelian diseases, present in the UniProt database, together with 6,321 differences between human proteins and their closely related mammalian homologs, assumed to be non-damaging (Supplementary Methods). The second pair, HumVar3, consists of all the 13,032 human disease-causing mutations from UniProt, together with 8,946 human nsSNPs without annotated involvement in disease, which were treated as non-damaging. We found that PolyPhen-2 performance, as presented by its receiver operating characteristic curves, was consistently superior compared to PolyPhen (Fig. 1b) and it also compared favorably with the three other popular prediction tools4–6 (Fig. 1c). For a false positive rate of 20%, PolyPhen-2 achieves the rate of true positive predictions of 92% and 73% on HumDiv and HumVar, respectively (Supplementary Table 2). One reason for a lower accuracy of predictions on HumVar is that nsSNPs assumed to be non-damaging in HumVar contain a sizable fraction of mildly deleterious alleles. In contrast, most of amino acid replacements assumed non-damaging in HumDiv must be close to selective neutrality. Because alleles that are even mildly but unconditionally deleterious cannot be fixed in the evolving lineage, no method based on comparative sequence analysis is ideal for discriminating between drastically and mildly deleterious mutations, which are assigned to the opposite categories in HumVar. Another reason is that HumDiv uses an extra criterion to avoid possible erroneous annotations of damaging mutations. For a mutation, PolyPhen-2 calculates Naïve Bayes posterior probability that this mutation is damaging and reports estimates of false positive (the chance that the mutation is classified as damaging when it is in fact non-damaging) and true positive (the chance that the mutation is classified as damaging when it is indeed damaging) rates. A mutation is also appraised qualitatively, as benign, possibly damaging, or probably damaging (Supplementary Methods). The user can choose between HumDiv- and HumVar-trained PolyPhen-2. Diagnostics of Mendelian diseases requires distinguishing mutations with drastic effects from all the remaining human variation, including abundant mildly deleterious alleles. Thus, HumVar-trained PolyPhen-2 should be used for this task. In contrast, HumDiv-trained PolyPhen-2 should be used for evaluating rare alleles at loci potentially involved in complex phenotypes, dense mapping of regions identified by genome-wide association studies, and analysis of natural selection from sequence data, where even mildly deleterious alleles must be treated as damaging. Supplementary Material 1

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Animal models of necrotizing enterocolitis: review of the literature and state of the art

Adrienne Sulistyo, Abidur Rahman, George Biouss … (2018)

Abstract Necrotizing enterocolitis (NEC) remains the leading cause of gastrointestinal surgical emergency in preterm neonates. Over the last five decades, a variety of experimental models have been developed to study the pathophysiology of this disease and to test the effectiveness of novel therapeutic strategies. Experimental NEC is mainly modeled in neonatal rats, mice and piglets. In this review, we focus on these experimental models and discuss the major advantages and disadvantages of each. We also briefly discuss other models that are not as widely used but have contributed to our current knowledge of NEC.

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Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

Prateek Kumar, Steven Henikoff, Pauline C. Ng … (2009)

The effect of genetic mutation on phenotype is of significant interest in genetics. The type of genetic mutation that causes a single amino acid substitution (AAS) in a protein sequence is called a non-synonymous single nucleotide polymorphism (nsSNP). An nsSNP could potentially affect the function of the protein, subsequently altering the carrier's phenotype. This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function. To assess the effect of a substitution, SIFT assumes that important positions in a protein sequence have been conserved throughout evolution and therefore substitutions at these positions may affect protein function. Thus, by using sequence homology, SIFT predicts the effects of all possible substitutions at each position in the protein sequence. The protocol typically takes 5-20 min, depending on the input. SIFT is available as an online tool (http://sift.jcvi.org).

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Author and article information

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Zelia Corradi

Journal

Journal ID (nlm-ta): HGG Adv

Journal ID (iso-abbrev): HGG Adv

Title: Human Genetics and Genomics Advances

Publisher: Elsevier

ISSN (Electronic): 2666-2477

Publication date PMC-release: 12 September 2023

Publication date Collection: 12 October 2023

Publication date (Electronic): 12 September 2023

Volume: 4

Issue: 4

Electronic Location Identifier: 100237

Affiliations

[1 ]Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

[2 ]Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands

[3 ]The School of Genetics & Microbiology, Trinity College Dublin, Dublin, Ireland

[4 ]Department of Ophthalmology, Radboud University Medical Center, Nijmegen, the Netherlands

[5 ]Blueprint Genetics, Espoo, Finland

[6 ]Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands

[7 ]Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands

[8 ]Institute of Molecular & Clinical Ophthalmology, Basel, Switzerland

[9 ]Research Unit for Rare Diseases, Department of Paediatrics and Adolescent Medicine, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic

[10 ]Department of Ophthalmology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic

[11 ]Institute of Human Genetics, University of Regensburg, Regensburg, Germany

[12 ]Institute of Clinical Human Genetics, University Hospital Regensburg, Regensburg, Germany

[13 ]Department of Precision Medicine, University of Campania “Luigi Vanvitelli,” Naples and Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy

[14 ]Department of Ophthalmology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel

[15 ]Department of Ophthalmology, Columbia University, New York, NY, USA

[16 ]Department of Pathology & Cell Biology, Columbia University, New York, NY, USA

[17 ]University Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, 59000 Lille, France

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[∗ ]Corresponding author zelia.corradi@ 123456radboudumc.nl

[18]

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Publisher Item ID: S2666-2477(23)00069-6 Publisher ID: 100237

DOI: 10.1016/j.xhgg.2023.100237

PMC ID: 10534262

PubMed ID: 37705246

SO-VID: 778f9a37-bf49-47f7-b492-fc47b6eb6bb4

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This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Targeted sequencing and in vitro splice assays shed light on ABCA4-associated retinopathies missing heritability

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Glossa: a journal of general linguistics

Most cited references 46

A method and server for predicting damaging missense mutations

Animal models of necrotizing enterocolitis: review of the literature and state of the art

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

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