Detecting cryptic clinically relevant structural variation in exome-sequencing data increases diagnostic yield for developmental disorders

Exome sequencing of UK birth cohorts

Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights ranging from population genetics to applications across the social sciences. Here we present quality-controlled whole exome sequencing data from three UK birth cohorts: the Avon Longitudinal Study of Parents and Children (8,436 children and 3,215 parents), the Millenium Cohort Study (7,667 children and 6,925 parents) and Born in Bradford (8,784 children and 2,875 parents). The overall objective of this coordinated effort is to make the resulting high-quality data widely accessible to the global research community in a timely manner. We describe how the datasets were generated and subjected to quality control at the sample, variant and genotype level. We then present some preliminary analyses to illustrate the quality of the datasets and probe potential sources of bias. We introduce measures of ultra-rare variant burden to the variables available for researchers working on these cohorts, and show that the exome-wide burden of deleterious protein-truncating variants, S het burden, is associated with educational attainment and cognitive test scores. The whole exome sequence data from these birth cohorts (CRAM & VCF files) are available through the European Genome-Phenome Archive, and here we provide guidance for their use.

The Genomic Landscape of Wilson Disease in a Pan India Disease Cohort and Population-Scale Data

BACKGROUND

Wilson's disease (WD) results from pathogenic ATP7B gene variations, causing copper accumulation mainly in the liver, brain, and kidneys.

OBJECTIVES

In India, despite studies on ATP7B variants, WD often goes undiagnosed, with the prevalence, carrier rate, and mutation spectrum remaining unknown.

METHODS

A multicenter study examined genetic variations in WD among individuals of Indian origin via whole exome sequencing. The study used the InDelible structural variants calling pipeline and conducted molecular dynamic simulations on variants of uncertain significance (VUS) in ATP7B AlphaFold protein structures. Additionally, a high-throughput gene screening panel for WD was developed.

RESULTS

This study examined 128 clinically diagnosed cases of WD, revealing 74 genetically confirmed cases, 22 with ATP7B variants, and 32 without. Twenty-two novel ATP7B gene variants were identified, including a 322 bp deletion classified as a structural variant. Molecular dynamics simulations highlighted the potential deleterious effects of 11 ATP7B VUS. Gene burden analysis suggested associations with ANO8, LGR4, and CDC7. ATP7B gene hotspots for pathogenic variants were identified. Prevalence and carrier rates were determined as one in 18,678 and one in 67, respectively. A multiplex sequencing panel showed promise for accurate WD diagnosis.

CONCLUSIONS

This study offers crucial insights into WD's genetic variations and prevalence in India, addressing its underdiagnosis. It highlights the novel genetic variants in the ATP7B gene, the involvement of other genes, a scalable, cost-effective multiplex sequencing panel for WD diagnosis and management and promising advancements in WD care.

Structural variant calling and clinical interpretation in 6224 unsolved rare disease exomes

Structural variants (SVs), including large deletions, duplications, inversions, translocations, and more complex events have the potential to disrupt gene function resulting in rare disease. Nevertheless, current pipelines and clinical decision support systems for exome sequencing (ES) tend to focus on small alterations such as single nucleotide variants (SNVs) and insertions-deletions shorter than 50 base pairs (indels). Additionally, detection and interpretation of large copy-number variants (CNVs) are frequently performed. However, detection of other types of SVs in ES data is hampered by the difficulty of identifying breakpoints in off-target (intergenic or intronic) regions, which makes robust identification of SVs challenging. In this paper, we demonstrate the utility of SV calling in ES resulting in a diagnostic yield of 0.4% (23 out of 5825 probands) for a large cohort of unsolved patients collected by the Solve-RD consortium. Remarkably, 8 out of 23 pathogenic SV were not found by comprehensive read-depth-based CNV analysis, resulting in a 0.13% increased diagnostic value.

The impact of inversions across 33,924 families with rare disease from a national genome sequencing project

Detection of structural variants (SVs) is currently biased toward those that alter copy number. The relative contribution of inversions toward genetic disease is unclear. In this study, we analyzed genome sequencing data for 33,924 families with rare disease from the 100,000 Genomes Project. From a database hosting >500 million SVs, we focused on 351 genes where haploinsufficiency is a confirmed disease mechanism and identified 47 ultra-rare rearrangements that included an inversion (24 bp to 36.4 Mb, 20/47 de novo). Validation utilized a number of orthogonal approaches, including retrospective exome analysis. RNA-seq data supported the respective diagnoses for six participants. Phenotypic blending was apparent in four probands. Diagnostic odysseys were a common theme (>50 years for one individual), and targeted analysis for the specific gene had already been performed for 30% of these individuals but with no findings. We provide formal confirmation of a European founder origin for an intragenic MSH2 inversion. For two individuals with complex SVs involving the MECP2 mutational hotspot, ambiguous SV structures were resolved using long-read sequencing, influencing clinical interpretation. A de novo inversion of HOXD11-13 was uncovered in a family with Kantaputra-type mesomelic dysplasia. Lastly, a complex translocation disrupting APC and involving nine rearranged segments confirmed a clinical diagnosis for three family members and resolved a conundrum for a sibling with a single polyp. Overall, inversions play a small but notable role in rare disease, likely explaining the etiology in around 1/750 families across heterogeneous clinical cohorts.

New whole-genome alignment tools are needed for tapping into plant diversity

Genome alignment is one of the most foundational methods for genome sequence studies. With rapid advances in sequencing and assembly technologies, these newly assembled genomes present challenges for alignment tools to meet the increased complexity and scale. Plant genome alignment is technologically challenging because of frequent whole-genome duplications (WGDs) as well as chromosome rearrangements and fractionation, high nucleotide diversity, widespread structural variation, and high transposable element (TE) activity causing large proportions of repeat elements. We summarize classical pairwise and multiple genome alignment (MGA) methods, and highlight techniques that are widely used or are being developed by the plant research community. We also outline the remaining challenges for precise genome alignment and the interpretation of alignment results in plants.

In-Depth Genomic Analysis: The New Challenge in Congenital Heart Disease

The use of next-generation sequencing has provided new insights into the causes and mechanisms of congenital heart disease (CHD). Examinations of the whole exome sequence have detected detrimental gene variations modifying single or contiguous nucleotides, which are characterised as pathogenic based on statistical assessments of families and correlations with congenital heart disease, elevated expression during heart development, and reductions in harmful protein-coding mutations in the general population. Patients with CHD and extracardiac abnormalities are enriched for gene classes meeting these criteria, supporting a common set of pathways in the organogenesis of CHDs. Single-cell transcriptomics data have revealed the expression of genes associated with CHD in specific cell types, and emerging evidence suggests that genetic mutations disrupt multicellular genes essential for cardiogenesis. Metrics and units are being tracked in whole-genome sequencing studies.

Severity of Autism Spectrum Disorder Symptoms Associated with de novo Variants and Pregnancy-Induced Hypertension

Genetic factors, particularly, de novo variants (DNV), and an environment factor, exposure to pregnancy-induced hypertension (PIH), were reported to be associated with risk of autism spectrum disorder (ASD); however, how they jointly affect the severity of ASD symptom is unclear. We assessed the severity of core ASD symptoms affected by functional de novo variants or PIH. We selected phenotype data from Simon's Simplex Collection database, used genotypes from previous studies, and created linear regression models. We found that ASD patients carrying DNV with PIH exposure had increased adaptive and cognitive ability, decreased social problems, and enhanced repetitive behaviors; however, there was no difference in patients without DNV between those with or without PIH exposure. In addition, the DNV genes carried by patients exposed to PIH were enriched in ubiquitin-dependent proteolytic processes, highlighting how candidate genes in pathways and environments interact. The results indicate the joint contribution of DNV and PIH to ASD.

Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES.

Incorporating CNV analysis improves the yield of exome sequencing for rare monogenic disorders-an important consideration for resource-constrained settings

Exome sequencing (ES) is a recommended first-tier diagnostic test for many rare monogenic diseases. It allows for the detection of both single-nucleotide variants (SNVs) and copy number variants (CNVs) in coding exonic regions of the genome in a single test, and this dual analysis is a valuable approach, especially in limited resource settings. Single-nucleotide variants are well studied; however, the incorporation of copy number variant analysis tools into variant calling pipelines has not been implemented yet as a routine diagnostic test, and chromosomal microarray is still more widely used to detect copy number variants. Research shows that combined single and copy number variant analysis can lead to a diagnostic yield of up to 58%, increasing the yield with as much as 18% from the single-nucleotide variant only pipeline. Importantly, this is achieved with the consideration of computational costs only, without incurring any additional sequencing costs. This mini review provides an overview of copy number variant analysis from exome data and what the current recommendations are for this type of analysis. We also present an overview on rare monogenic disease research standard practices in resource-limited settings. We present evidence that integrating copy number variant detection tools into a standard exome sequencing analysis pipeline improves diagnostic yield and should be considered a significantly beneficial addition, with relatively low-cost implications. Routine implementation in underrepresented populations and limited resource settings will promote generation and sharing of CNV datasets and provide momentum to build core centers for this niche within genomic medicine.

Identifying the genetic causes of developmental disorders and intellectual disability in Africa: a systematic literature review

Objective: Genetic variants cause a significant portion of developmental disorders and intellectual disabilities (DD/ID), but clinical and genetic heterogeneity makes identification challenging. Compounding the issue is a lack of ethnic diversity in studies into the genetic aetiology of DD/ID, with a dearth of data from Africa. This systematic review aimed to comprehensively describe the current knowledge from the African continent on this topic. Method: Applicable literature published up until July 2021 was retrieved from PubMed, Scopus and Web of Science databases, following PRISMA guidelines, focusing on original research reports on DD/ID where African patients were the focus of the study. The quality of the dataset was assessed using appraisal tools from the Joanna Briggs Institute, whereafter metadata was extracted for analysis. Results: A total of 3,803 publications were extracted and screened. After duplicate removal, title, abstract and full paper screening, 287 publications were deemed appropriate for inclusion. Of the papers analysed, a large disparity was seen between work emanating from North Africa compared to sub-Saharan Africa, with North Africa dominating the publications. Representation of African scientists on publications was poorly balanced, with most research being led by international researchers. There are very few systematic cohort studies, particularly using newer technologies, such as chromosomal microarray and next-generation sequencing. Most of the reports on new technology data were generated outside Africa. Conclusion: This review highlights how the molecular epidemiology of DD/ID in Africa is hampered by significant knowledge gaps. Efforts are needed to produce systematically obtained high quality data that can be used to inform appropriate strategies to implement genomic medicine for DD/ID on the African continent, and to successfully bridge healthcare inequalities.

Genomic Diagnosis of Rare Pediatric Disease in the United Kingdom and Ireland

BACKGROUND

Pediatric disorders include a range of highly penetrant, genetically heterogeneous conditions amenable to genomewide diagnostic approaches. Finding a molecular diagnosis is challenging but can have profound lifelong benefits.

METHODS

We conducted a large-scale sequencing study involving more than 13,500 families with probands with severe, probably monogenic, difficult-to-diagnose developmental disorders from 24 regional genetics services in the United Kingdom and Ireland. Standardized phenotypic data were collected, and exome sequencing and microarray analyses were performed to investigate novel genetic causes. We developed an iterative variant analysis pipeline and reported candidate variants to clinical teams for validation and diagnostic interpretation to inform communication with families. Multiple regression analyses were performed to evaluate factors affecting the probability of diagnosis.

RESULTS

A total of 13,449 probands were included in the analyses. On average, we reported 1.0 candidate variant per parent-offspring trio and 2.5 variants per singleton proband. Using clinical and computational approaches to variant classification, we made a diagnosis in approximately 41% of probands (5502 of 13,449). Of 3599 probands in trios who received a diagnosis by clinical assertion, approximately 76% had a pathogenic de novo variant. Another 22% of probands (2997 of 13,449) had variants of uncertain significance in genes that were strongly linked to monogenic developmental disorders. Recruitment in a parent-offspring trio had the largest effect on the probability of diagnosis (odds ratio, 4.70; 95% confidence interval [CI], 4.16 to 5.31). Probands were less likely to receive a diagnosis if they were born extremely prematurely (i.e., 22 to 27 weeks' gestation; odds ratio, 0.39; 95% CI, 0.22 to 0.68), had in utero exposure to antiepileptic medications (odds ratio, 0.44; 95% CI, 0.29 to 0.67), had mothers with diabetes (odds ratio, 0.52; 95% CI, 0.41 to 0.67), or were of African ancestry (odds ratio, 0.51; 95% CI, 0.31 to 0.78).

CONCLUSIONS

Among probands with severe, probably monogenic, difficult-to-diagnose developmental disorders, multimodal analysis of genomewide data had good diagnostic power, even after previous attempts at diagnosis. (Funded by the Health Innovation Challenge Fund and Wellcome Sanger Institute.).

A collection of read depth profiles at structural variant breakpoints

SWaveform, a newly created open genome-wide resource for read depth signal in the vicinity of structural variant (SV) breakpoints, aims to boost development of computational tools and algorithms for discovery of genomic rearrangement events from sequencing data. SVs are a dominant force shaping genomes and substantially contributing to genetic diversity. Still, there are challenges in reliable and efficient genotyping of SVs from whole genome sequencing data, thus delaying translation into clinical applications and wasting valuable resources. SWaveform includes a database containing ~7 M of read depth profiles at SV breakpoints extracted from 911 sequencing samples generated by the Human Genome Diversity Project, generalised patterns of the signal at breakpoints, an interface for navigation and download, as well as a toolbox for local deployment with user's data. The dataset can be of immense value to bioinformatics and engineering communities as it empowers smooth application of intelligent signal processing and machine learning techniques for discovery of genomic rearrangement events and thus opens the floodgates for development of innovative algorithms and software.

Detection of Small CYP11B1 Deletions and One Founder Chimeric CYP11B2/CYP11B1 Gene in 11β-Hydroxylase Deficiency

OBJECTIVE

11β-Hydroxylase deficiency (11β-OHD) caused by mutations in the CYP11B1 gene is the second most common form of congenital adrenal hyperplasia. Both point mutations and genomic rearrangements of CYP11B1 are important causes of 11β-OHD. However, the high degree of sequence identity between CYP11B1 and its homologous gene CYP11B2, presents unique challenges for molecular diagnosis of suspected 11β-OHD. The aim of this study was to detect the point mutation, indel, small deletion of CYP11B1 and chimeric CYP11B2/CYP11B1 gene in a one-tube test, improving the genetic diagnosis of 11β-OHD.

METHODS

Optimized custom-designed target sequencing strategy was performed in three patients with suspected 11β-OHD, in which both the coverage depth of paired-end reads and the breakpoint information of split reads from sequencing data were analysed in order to detect genomic rearrangements covering CYP11B1. Long-range PCR was peformed to validate the speculated CYP11B1 rearrangements with the breakpoint-specifc primers.

RESULTS

Using the optimized target sequencing approach, we detected two intragenic/intergenic deletions of CYP11B1 and one chimeric CYP11B2/CYP11B1 gene from three suspected patients with 11β-OHD besides three pathogenic heterozygous point mutation/indels. Furthermore, we mapped the precise breakpoint of this chimeric CYP11B2/CYP11B1 gene located on chr8:143994517 (hg19) and confirmed it as a founder rearrangement event in the Chinese population.

CONCLUSIONS

Our optimized target sequencing approach improved the genetic diagnosis of 11β-OHD.