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Background and ObjectivesMitochondrial diseases (MDs) are the commonest group of heritable metabolic disorders. Phenotypic diversity can make molecular diagnosis challenging, and causative genetic variants may reside in either mitochondrial or nuclear DNA. A single comprehensive genetic diagnostic test would be highly useful and transform the field. We applied whole-genome sequencing (WGS) to evaluate the variant detection rate and diagnostic capacity of this technology with a view to simplifying and improving the MD diagnostic pathway.MethodsAdult patients presenting to a specialist MD clinic in Sydney, Australia, were recruited to the study if they satisfied clinical MD (Nijmegen) criteria. WGS was performed on blood DNA, followed by clinical genetic analysis for known pathogenic MD-associated variants and MD mimics.ResultsOf the 242 consecutive patients recruited, 62 participants had “definite,” 108 had “probable,” and 72 had “possible” MD classification by the Nijmegen criteria. Disease-causing variants were identified for 130 participants, regardless of the location of the causative genetic variants, giving an overall diagnostic rate of 53.7% (130 of 242). Identification of causative genetic variants informed precise treatment, restored reproductive confidence, and optimized clinical management of MD.DiscussionComprehensive bigenomic sequencing accurately detects causative genetic variants in affected MD patients, simplifying diagnosis, enabling early treatment, and informing the risk of genetic transmission.

Cerebral palsy (CP) is the most common cause of childhood physical disability, with incidence between 1/500 and 1/700 births in the developed world. Despite increasing evidence for a major contribution of genetics to CP aetiology, genetic testing is currently not performed systematically. We assessed the diagnostic rate of genome sequencing (GS) in a clinically unselected cohort of 150 singleton CP patients, with CP confirmed at >4 years of age. Clinical grade GS was performed on the proband and variants were filtered, and classified according to American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG-AMP) guidelines. Variants classified as pathogenic or likely pathogenic (P/LP) were further assessed for their contribution to CP. In total, 24.7% of individuals carried a P/LP variant(s) causing or increasing risk of CP, with 4.7% resolved by copy number variant analysis and 20% carrying single nucleotide or indel variants. A further 34.7% carried one or more rare, high impact variants of uncertain significance (VUS) in variation intolerant genes. Variants were identified in a heterogeneous group of genes, including genes associated with hereditary spastic paraplegia, clotting and thrombophilic disorders, small vessel disease, and other neurodevelopmental disorders. Approximately 1/2 of individuals were classified as likely to benefit from changed clinical management as a result of genetic findings. In addition, no significant association between genetic findings and clinical factors was detectable in this cohort, suggesting that systematic sequencing of CP will be required to avoid missed diagnoses.

ObjectiveTo assess the benefits and limitations of whole genome sequencing (WGS) compared to exome sequencing (ES) or multigene panel (MGP) in the molecular diagnosis of developmental and epileptic encephalopathies (DEE).MethodsWe performed WGS of 30 comprehensively phenotyped DEE patient trios that were undiagnosed after first-tier testing, including chromosomal microarray and either research ES (n = 15) or diagnostic MGP (n = 15).ResultsEight diagnoses were made in the 15 individuals who received prior ES (53%): 3 individuals had complex structural variants; 5 had ES-detectable variants, which now had additional evidence for pathogenicity. Eleven diagnoses were made in the 15 MGP-negative individuals (68%); the majority (n = 10) involved genes not included in the panel, particularly in individuals with postneonatal onset of seizures and those with more complex presentations including movement disorders, dysmorphic features, or multiorgan involvement. A total of 42% of diagnoses were autosomal recessive or X-chromosome linked.ConclusionWGS was able to improve diagnostic yield over ES primarily through the detection of complex structural variants (n = 3). The higher diagnostic yield was otherwise better attributed to the power of re-analysis rather than inherent advantages of the WGS platform. Additional research is required to assist in the assessment of pathogenicity of novel noncoding and complex structural variants and further improve diagnostic yield for patients with DEE and other neurogenetic disorders.

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is common, with a prevalence of 1/1000 and predominantly caused by disease-causing variants in PKD1 or PKD2. Clinical diagnosis is usually by age-dependent imaging criteria, which is challenging in patients with atypical clinical features, without family history, or younger age. However, there is increasing need for definitive diagnosis of ADPKD with new treatments available. Sequencing is complicated by six pseudogenes that share 97% homology to PKD1 and by recently identified phenocopy genes. Whole-genome sequencing can definitively diagnose ADPKD, but requires validation for clinical use. We initially performed a validation study, in which 42 ADPKD patients underwent sequencing of PKD1 and PKD2 by both whole-genome and Sanger sequencing, using a blinded, cross-over method. Whole-genome sequencing identified all PKD1 and PKD2 germline pathogenic variants in the validation study (sensitivity and specificity 100%). Two mosaic variants outside pipeline thresholds were not detected. We then examined the first 144 samples referred to a clinically-accredited diagnostic laboratory for clinical whole-genome sequencing, with targeted-analysis to a polycystic kidney disease gene-panel. In this unselected, diagnostic cohort (71 males :73 females), the diagnostic rate was 70%, including a diagnostic rate of 81% in patients with typical ADPKD (98% with PKD1/PKD2 variants) and 60% in those with atypical features (56% PKD1/PKD2; 44% PKHD1/HNF1B/GANAB/ DNAJB11/PRKCSH/TSC2). Most patients with atypical disease did not have clinical features that predicted likelihood of a genetic diagnosis. These results suggest clinicians should consider diagnostic genomics as part of their assessment in polycystic kidney disease, particularly in atypical disease.

The inherited retinal dystrophies (IRDs) are a clinically and genetically complex group of disorders primarily affecting the rod and cone photoreceptors or other retinal neuronal layers, with emerging therapies heralding the need for accurate molecular diagnosis. Targeted capture and panel-based strategies examining the partial or full exome deliver molecular diagnoses in many IRD families tested. However, approximately one in three families remain unsolved and unable to obtain personalised recurrence risk or access to new clinical trials or therapy. In this study, we investigated whole genome sequencing (WGS), focused assays and functional studies to assist with unsolved IRD cases and facilitate integration of these approaches to a broad molecular diagnostic clinical service. The WGS approach identified variants not covered or underinvestigated by targeted capture panel-based clinical testing strategies in six families. This included structural variants, with notable benefit of the WGS approach in repetitive regions demonstrated by a family with a hybrid gene and hemizygous missense variant involving the opsin genes, OPN1LW and OPN1MW. There was also benefit in investigation of the repetitive GC-rich ORF15 region of RPGR. Further molecular investigations were facilitated by focused assays in these regions. Deep intronic variants were identified in IQCB1 and ABCA4, with functional RNA based studies of the IQCB1 variant revealing activation of a cryptic splice acceptor site. While targeted capture panel-based methods are successful in achieving an efficient molecular diagnosis in a proportion of cases, this study highlights the additional benefit and clinical value that may be derived from WGS, focused assays and functional genomics in the highly heterogeneous IRDs.

Whole genome sequencing (WGS) improves Mendelian disorder diagnosis over whole exome sequencing (WES); however, additional diagnostic yields and costs remain undefined. We investigated differences between diagnostic and cost outcomes of WGS and WES in a cohort with suspected Mendelian disorders. WGS was performed in 38 WES-negative families derived from a 64 family Mendelian cohort that previously underwent WES. For new WGS diagnoses, contemporary WES reanalysis determined whether variants were diagnosable by original WES or unique to WGS. Diagnostic rates were estimated for WES and WGS to simulate outcomes if both had been applied to the 64 families. Diagnostic costs were calculated for various genomic testing scenarios. WGS diagnosed 34% (13/38) of WES-negative families. However, contemporary WES reanalysis on average 2 years later would have diagnosed 18% (7/38 families) resulting in a WGS-specific diagnostic yield of 19% (6/31 remaining families). In WES-negative families, the incremental cost per additional diagnosis using WGS following WES reanalysis was AU$36,710 (£19,407;US$23,727) and WGS alone was AU$41,916 (£22,159;US$27,093) compared to WES-reanalysis. When we simulated the use of WGS alone as an initial genomic test, the incremental cost for each additional diagnosis was AU$29,708 (£15,705;US$19,201) whereas contemporary WES followed by WGS was AU$36,710 (£19,407;US$23,727) compared to contemporary WES. Our findings confirm that WGS is the optimal genomic test choice for maximal diagnosis in Mendelian disorders. However, accepting a small reduction in diagnostic yield, WES with subsequent reanalysis confers the lowest costs. Whether WES or WGS is utilised will depend on clinical scenario and local resourcing and availability.

Background Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDXs) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions. Results Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60 × coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1, previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers. Conclusions Our WGS data provides a comprehensive genome sequencing resource of these models.

Introduction Dystonia is a clinically and genetically heterogeneous disorder and a genetic cause is often difficult to elucidate. This is the first study to use whole genome sequencing (WGS) to investigate dystonia in a large sample of affected individuals. Methods WGS was performed on 111 probands with heterogenous dystonia phenotypes. We performed analysis for coding and non-coding variants, copy number variants (CNVs), and structural variants (SVs). We assessed for an association between dystonia and 10 known dystonia risk variants. Results A genetic diagnosis was obtained for 11.7% (13/111) of individuals. We found that a genetic diagnosis was more likely in those with an earlier age at onset, younger age at testing, and a combined dystonia phenotype. We identified pathogenic/likely-pathogenic variants in ADCY5 (n = 1), ATM (n = 1), GNAL (n = 2), GLB1 (n = 1), KMT2B (n = 2), PRKN (n = 2), PRRT2 (n = 1), SGCE (n = 2), and THAP1 (n = 1). CNVs were detected in 3 individuals. We found an association between the known risk variant ARSG rs11655081 and dystonia (p = 0.003). Conclusion A genetic diagnosis was found in 11.7% of individuals with dystonia. The diagnostic yield was higher in those with an earlier age of onset, younger age at testing, and a combined dystonia phenotype. WGS may be particularly relevant for dystonia given that it allows for the detection of CNVs, which accounted for 23% of the genetically diagnosed cases.

Inherited disorders of spasticity or ataxia exist on a spectrum with overlapping causative genes and phenotypes. We investigated the use of whole-genome sequencing (WGS) to detect a genetic cause when considering this spectrum of disorders as a single group. We recruited 18 Korean individuals with spastic paraplegia with or without cerebellar ataxia in whom common causes of hereditary cerebellar ataxia and hereditary spastic paraplegia had been excluded. We performed WGS with analysis for single nucleotide variants, small insertions and deletions, copy number variants (CNVs), structural variants (SVs) and intronic variants. Disease-relevant variants were identified in ABCD1 (n = 3), CAPN1 (n = 2), NIPA1 (n = 1) and PLA2G6 (n = 1) for 7/18 patients (38.9%). A 'reverse phenotyping' approach was used to clarify the diagnosis in individuals with PLA2G6 and ABCD1 variants. One of the ABCD1 disease-relevant variants was detected on analysis for intronic variants. No CNV or SV causes were found. The two males with ABCD1 variants were initiated on monitoring for adrenal dysfunction. This is one of only a few studies to analyse spastic-ataxias as a continuous spectrum using a single approach. The outcome was improved diagnosis of unresolved cases for which common genetic causes had been excluded. This includes the detection of ABCD1 variants which had management implications. Therefore, WGS may be particularly relevant to diagnosing spastic ataxias given the large number of genes associated with this condition and the relatively high diagnostic yield.

Mitochondrial diseases can be caused by pathogenic variants in nuclear or mitochondrial DNA-encoded genes that often lead to multisystemic symptoms and can have any mode of inheritance. Using a single test, Genome Sequencing (GS) can effectively identify variants in both genomes, but it has not yet been universally used as a first-line approach to diagnosing mitochondrial diseases due to related costs and challenges in data analysis. In this article, we report three patients with mitochondrial disease molecularly diagnosed through GS performed on DNA extracted from blood to demonstrate different diagnostic advantages of this technology, including the detection of a low-level heteroplasmic pathogenic variant, an intragenic nuclear DNA deletion, and a large mtDNA deletion. Current technical improvements and cost reductions are likely to lead to an expanded routine diagnostic usage of GS and of the complementary “Omic” technologies in mitochondrial diseases.

Whole genome sequencing (WGS) has the potential to outperform clinical microarrays for the detection of structural variants (SV) including copy number variants (CNVs), but has been challenged by high false positive rates. Here we present ClinSV, a WGS based SV integration, annotation, prioritization, and visualization framework, which identified 99.8% of simulated pathogenic ClinVar CNVs > 10 kb and 11/11 pathogenic variants from matched microarrays. The false positive rate was low (1.5–4.5%) and reproducibility high (95–99%). In clinical practice, ClinSV identified reportable variants in 22 of 485 patients (4.7%) of which 35–63% were not detectable by current clinical microarray designs. ClinSV is available at https://github.com/KCCG/ClinSV.

Zellweger syndrome spectrum disorders are caused by mutations in any of at least 12 different PEX genes. This includes PEX16, an important regulator of peroxisome biogenesis. Using whole genome sequencing, we detected previously unreported, biallelic variants in PEX16 [NM_004813.2:c.658G>A, p.(Ala220Thr) and NM_004813.2:c.830G>A, p.(Arg277Gln)] in an individual with leukodystrophy, spastic paraplegia, cerebellar ataxia, and craniocervical dystonia with normal plasma very long chain fatty acids. Using olfactory-neurosphere derived cells, a population of neural stem cells, we showed patient cells had reduced peroxisome density and increased peroxisome size, replicating previously reported findings in PEX16 cell lines. Along with alterations in peroxisome morphology, patient cells also had impaired peroxisome function with reduced catalase activity. Furthermore, patient cells had reduced oxidative stress levels after exposure to hydrogen-peroxide (H2O2), which may be a result of compensation by H2O2 metabolising enzymes other than catalase to preserve peroxisome-related cell functions. Our findings of impaired catalase activity and altered oxidative stress response are novel. Our study expands the phenotype of PEX16 mutations by including dystonia and provides further insights into the pathological mechanisms underlying PEX16-associated disorders. Additional studies of the full spectrum of peroxisomal dysfunction could improve our understanding of the mechanism underlying PEX16-associated disorders. Keywords: Whole genome sequencing, PEX16, Peroxisomes, Leukodystrophy, Dystonia

Background Whole genome sequencing (WGS) is a comprehensive genetic testing approach that reports most types of nucleotide variants. Objectives This study sought to assess WGS for hypertrophic cardiomyopathy (HCM) in which prior genetic testing did not establish a molecular diagnosis, and as a first-line genetic test. Methods WGS was performed on 58 unrelated patients with HCM, 14 affected family members, and 2 unaffected parents of a severely affected proband. The authors searched for nucleotide variants in coding regions of 184 candidate cardiac hypertrophy genes. They also searched for nucleotide variants in deep intronic regions that alter RNA splicing, large genomic rearrangements, and mitochondrial genome variants. RNA analysis was performed to validate splice-altering variants. Results The authors found a pathogenic or likely pathogenic variant in 9 of 46 families (20%) for which prior genetic testing was inconclusive. Three families had variants in genes not included in prior genetic testing. One family had a pathogenic variant that was filtered out with prior exome sequencing. Five families had pathogenic variants in noncoding regions, including 4 with deep intronic variants that activate novel splicing, and 1 mitochondrial genome variant. As a first-line genetic test, WGS identified a pathogenic variant in 5 of 12 families (42%) that had never received prior genetic testing. Conclusions WGS identified additional genetic causes of HCM over targeted gene sequencing approaches. Extending genetic screening to deep intronic regions identified pathogenic variants in 9% of gene-elusive HCM. These findings translate to more accurate diagnosis and management in HCM families.

Background The German Shepherd Dog (GSD) is one of the most common breeds on earth and has been bred for its utility and intelligence. It is often first choice for police and military work, as well as protection, disability assistance, and search-and-rescue. Yet, GSDs are well known to be susceptible to a range of genetic diseases that can interfere with their training. Such diseases are of particular concern when they occur later in life, and fully trained animals are not able to continue their duties. Findings Here, we provide the draft genome sequence of a healthy German Shepherd female as a reference for future disease and evolutionary studies. We generated this improved canid reference genome (CanFam_GSD) utilizing a combination of Pacific Bioscience, Oxford Nanopore, 10X Genomics, Bionano, and Hi-C technologies. The GSD assembly is ∼80 times as contiguous as the current canid reference genome (20.9 vs 0.267 Mb contig N50), containing far fewer gaps (306 vs 23,876) and fewer scaffolds (429 vs 3,310) than the current canid reference genome CanFamv3.1. Two chromosomes (4 and 35) are assembled into single scaffolds with no gaps. BUSCO analyses of the genome assembly results show that 93.0% of the conserved single-copy genes are complete in the GSD assembly compared with 92.2% for CanFam v3.1. Homology-based gene annotation increases this value to ∼99%. Detailed examination of the evolutionarily important pancreatic amylase region reveals that there are most likely 7 copies of the gene, indicative of a duplication of 4 ancestral copies and the disruption of 1 copy. Conclusions GSD genome assembly and annotation were produced with major improvement in completeness, continuity, and quality over the existing canid reference. This resource will enable further research related to canine diseases, the evolutionary relationships of canids, and other aspects of canid biology.

We performed whole genome sequencing (WGS) in nine families from India with early-onset hereditary spastic paraplegia (HSP). We obtained a genetic diagnosis in 4/9 (44 %) families within known HSP genes (DDHD2 and CYP2U1), as well as perixosomal biogenesis disorders (PEX16) and GM1 gangliosidosis (GLB1). In the remaining patients, no candidate structural variants, copy number variants or predicted splice variants affecting an extended candidate gene list were identified. Our findings demonstrate the efficacy of using WGS for diagnosing early-onset HSP, particularly in consanguineous families (4/6 diagnosed), highlighting that two of the diagnoses would not have been made using a targeted approach. Electronic supplementary material The online version of this article (doi:10.1007/s10048-016-0495-z) contains supplementary material, which is available to authorized users.

Purpose: We evaluated whole-genome sequencing (WGS) as an alternative to multi-gene panel sequencing (PS) for genetic testing in dilated cardiomyopathy (DCM). Methods: Forty-two patients with familial DCM underwent PS and WGS, and detection rates of rare single nucleotide variants and small insertions/deletions in panel genes were compared. Loss-of-function variants in 406 cardiac-enriched genes were evaluated, and an assessment of structural variation was performed. Results: WGS provided broader and more uniform coverage than PS, with high concordance for rare variant detection in panel genes. WGS identified all PS-identified pathogenic or likely-pathogenic variants as well as two additional likely-pathogenic variants: one was missed by PS due to low coverage, the other was a known disease-causing variant in a gene not included on the panel. No loss-of-function variants in the extended gene set met clinical criteria for pathogenicity. One BAG3 structural variant was classified as pathogenic. Conclusions – Our data support the use of WGS for genetic testing in DCM, with high variant detection accuracy and a capacity to identify structural variants. WGS provides an opportunity to go beyond suites of established disease genes, but the incremental yield of clinically-actionable variants is limited by a paucity of genetic and functional evidence for DCM association.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic kidney disorder and is due to disease-causing variants in PKD1 or PKD2. Strong genotype-phenotype correlation exists although diagnostic sequencing is not part of routine clinical practice. This is because PKD1 bears 97.7% sequence similarity with six pseudogenes, requiring laborious and error-prone long-range PCR and Sanger sequencing to overcome. We hypothesised that whole-genome sequencing (WGS) would be able to overcome the problem of this sequence homology, because of 150 bp, paired-end reads and avoidance of capture bias that arises from targeted sequencing. We prospectively recruited a cohort of 28 unique pedigrees with ADPKD phenotype. Standard DNA extraction, library preparation and WGS were performed using Illumina HiSeq X and variants were classified following standard guidelines. Molecular diagnosis was made in 24 patients (86%), with 100% variant confirmation by current gold standard of long-range PCR and Sanger sequencing. We demonstrated unique alignment of sequencing reads over the pseudogene-homologous region. In addition to identifying function-affecting single-nucleotide variants and indels, we identified single- and multi-exon deletions affecting PKD1 and PKD2, which would have been challenging to identify using exome sequencing. We report the first use of WGS to diagnose ADPKD. This method overcomes pseudogene homology, provides uniform coverage, detects all variant types in a single test and is less labour-intensive than current techniques. This technique is translatable to a diagnostic setting, allows clinicians to make better-informed management decisions and has implications for other disease groups that are challenged by regions of confounding sequence homology.

Background The generation and analysis of high-throughput sequencing data are becoming a major component of many studies in molecular biology and medical research. Illumina's Genome Analyzer (GA) and HiSeq instruments are currently the most widely used sequencing devices. Here, we comprehensively evaluate properties of genomic HiSeq and GAIIx data derived from two plant genomes and one virus, with read lengths of 95 to 150 bases. Results We provide quantifications and evidence for GC bias, error rates, error sequence context, effects of quality filtering, and the reliability of quality values. By combining different filtering criteria we reduced error rates 7-fold at the expense of discarding 12.5% of alignable bases. While overall error rates are low in HiSeq data we observed regions of accumulated wrong base calls. Only 3% of all error positions accounted for 24.7% of all substitution errors. Analyzing the forward and reverse strands separately revealed error rates of up to 18.7%. Insertions and deletions occurred at very low rates on average but increased to up to 2% in homopolymers. A positive correlation between read coverage and GC content was found depending on the GC content range. Conclusions The errors and biases we report have implications for the use and the interpretation of Illumina sequencing data. GAIIx and HiSeq data sets show slightly different error profiles. Quality filtering is essential to minimize downstream analysis artifacts. Supporting previous recommendations, the strand-specificity provides a criterion to distinguish sequencing errors from low abundance polymorphisms.