From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability

Anna Wedell,Anna Hammarsjö,Magnus Nordenskjöld,Måns Magnusson,Helena Malmgren,Claudia M.b Carvalho ,Emma Tham,Malin Kvarnung,Erik Iwarsson,Ameli Norling,Valtteri Wirta,Josephine Wincent,Kristina Lagerstedt‐Robinson ,Britt‐Marie Anderlid ,Johanna Lundin,Maria Pettersson,Peter Gustavsson,Giedré Grigelioniené ,Ellika Sahlin,Henrik Stranneheim,Olof Bjerin,Agne Liedén ,Sofia Ygberg,Jesper Eisfeldt,Maria Johansson‐Soller ,Patrik Georgii-Hemming,Marcel Martin,Daniel Nilsson

doi:10.1186/s13073-019-0675-1

Abstract

BackgroundSince different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test.MethodsWe analyzed three cohorts with short-read WGS: (i) a retrospective cohort with validated copy number variants (CNVs) (cohort 1, n = 68), (ii) individuals referred for monogenic multi-gene panels (cohort 2, n = 156), and (iii) 100 prospective, consecutive cases referred to our center for CMA (cohort 3). Bioinformatic tools developed include FindSV, SVDB, Rhocall, Rhoviz, and vcf2cytosure.ResultsFirst, we validated our structural variant (SV)-calling pipeline on cohort 1, consisting of three trisomies and 79 deletions and duplications with a median size of 850 kb (min 500 bp, max 155 Mb). All variants were detected. Second, we utilized the same pipeline in cohort 2 and analyzed with monogenic WGS panels, increasing the diagnostic yield to 8%. Next, cohort 3 was analyzed by both CMA and WGS. The WGS data was processed for large (> 10 kb) SVs genome-wide and for exonic SVs and SNVs in a panel of 887 genes linked to intellectual disability as well as genes matched to patient-specific Human Phenotype Ontology (HPO) phenotypes. This yielded a total of 25 pathogenic variants (SNVs or SVs), of which 12 were detected by CMA as well. We also applied short tandem repeat (STR) expansion detection and discovered one pathologic expansion in ATXN7. Finally, a case of Prader-Willi syndrome with uniparental disomy (UPD) was validated in the WGS data.Important positional information was obtained in all cohorts. Remarkably, 7% of the analyzed cases harbored complex structural variants, as exemplified by a ring chromosome and two duplications found to be an insertional translocation and part of a cryptic unbalanced translocation, respectively.ConclusionThe overall diagnostic rate of 27% was more than doubled compared to clinical microarray (12%). Using WGS, we detected a wide range of SVs with high accuracy. Since the WGS data also allowed for analysis of SNVs, UPD, and STRs, it represents a powerful comprehensive genetic test in a clinical diagnostic laboratory setting.

Highlights

Since different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test
The WGS data was processed for large (> 10 kb) structural variant (SV) genome-wide and for exonic SVs and SNVs in a panel of 887 genes linked to intellectual disability as well as genes matched to patient-specific Human Phenotype Ontology (HPO) phenotypes
TIDDIT identified a total of 39 deletions (83%), all of which were non-recurrent while CNVnator identified a total of 51 deletions (94%), including all recurrent deletions (Table 2)

Summary

Introduction

Since different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test. Chromosomal microarray analysis (CMA), either comparative genomic hybridization (CGH) or SNP arrays, has long been the first-tier test used to identify copy number variants (CNVs) in individuals with intellectual disability and neurodevelopmental disorders [10,11,12]. MPS-based assays have been increasingly used in rare disease diagnostics, because of their high throughput and cost effectiveness in screening multi-gene panels for hereditary disorders [13]. Depending on the specific clinical presentation and the preferences of the referring physician and the laboratory performing the test, other assays such as Gbanded karyotyping, fluorescence in situ hybridization (FISH), FMR1 CGG repeat expansion analysis, PCR-based single gene analysis, and whole-genome sequencing (WGS) may be performed [19]

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Results

Discussion

Conclusion