Motivation: Fast and accurate quality control is essential for studies involving next-generation sequencing data. Whilst numerous tools exist to quantify QC metrics, there is no common approach to flexibly integrate these across tools and large sample sets. Assessing analysis results across an entire project can be time consuming and error prone; batch effects and outlier samples can easily be missed in the early stages of analysis.Results: We present MultiQC, a tool to create a single report visualising output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC can plot data from many common bioinformatics tools and is built to allow easy extension and customization.Availability and implementation: MultiQC is available with an GNU GPLv3 license on GitHub, the Python Package Index and Bioconda. Documentation and example reports are available at http://multiqc.infoContact: phil.ewels@scilifelab.se

Mutations in interferon regulatory factor 6 (IRF6) account for ∼70% of cases of Van der Woude syndrome (VWS), the most common syndromic form of cleft lip and palate. In 8 of 45 VWS-affected families lacking a mutation in IRF6, we found coding mutations in grainyhead-like 3 (GRHL3). According to a zebrafish-based assay, the disease-associated GRHL3 mutations abrogated periderm development and were consistent with a dominant-negative effect, in contrast to haploinsufficiency seen in most VWS cases caused by IRF6 mutations. In mouse, all embryos lacking Grhl3 exhibited abnormal oral periderm and 17% developed a cleft palate. Analysis of the oral phenotype of double heterozygote (Irf6(+/-);Grhl3(+/-)) murine embryos failed to detect epistasis between the two genes, suggesting that they function in separate but convergent pathways during palatogenesis. Taken together, our data demonstrated that mutations in two genes, IRF6 and GRHL3, can lead to nearly identical phenotypes of orofacial cleft. They supported the hypotheses that both genes are essential for the presence of a functional oral periderm and that failure of this process contributes to VWS.

Background We report the findings from 4437 individuals (3219 patients and 1218 relatives) who have been analyzed by whole genome sequencing (WGS) at the Genomic Medicine Center Karolinska-Rare Diseases (GMCK-RD) since mid-2015. GMCK-RD represents a long-term collaborative initiative between Karolinska University Hospital and Science for Life Laboratory to establish advanced, genomics-based diagnostics in the Stockholm healthcare setting. Methods Our analysis covers detection and interpretation of SNVs, INDELs, uniparental disomy, CNVs, balanced structural variants, and short tandem repeat expansions. Visualization of results for clinical interpretation is carried out in Scout—a custom-developed decision support system. Results from both singleton (84%) and trio/family (16%) analyses are reported. Variant interpretation is done by 15 expert teams at the hospital involving staff from three clinics. For patients with complex phenotypes, data is shared between the teams. Results Overall, 40% of the patients received a molecular diagnosis ranging from 19 to 54% for specific disease groups. There was heterogeneity regarding causative genes (n = 754) with some of the most common ones being COL2A1 (n = 12; skeletal dysplasia), SCN1A (n = 8; epilepsy), and TNFRSF13B (n = 4; inborn errors of immunity). Some causative variants were recurrent, including previously known founder mutations, some novel mutations, and recurrent de novo mutations. Overall, GMCK-RD has resulted in a large number of patients receiving specific molecular diagnoses. Furthermore, negative cases have been included in research studies that have resulted in the discovery of 17 published, novel disease-causing genes. To facilitate the discovery of new disease genes, GMCK-RD has joined international data sharing initiatives, including ClinVar, UDNI, Beacon, and MatchMaker Exchange. Conclusions Clinical WGS at GMCK-RD has provided molecular diagnoses to over 1200 individuals with a broad range of rare diseases. Consolidation and spread of this clinical-academic partnership will enable large-scale national collaboration.

BackgroundCoenzyme Q is an essential mitochondrial electron carrier, redox cofactor and a potent antioxidant in the majority of cellular membranes. Coenzyme Q deficiency has been associated with a range of metabolic diseases, as well as with some drug treatments and ageing.MethodsWe used whole exome sequencing (WES) to investigate patients with inherited metabolic diseases and applied a novel ultra-pressure liquid chromatography—mass spectrometry approach to measure coenzyme Q in patient samples.ResultsWe identified a homozygous missense mutation in the COQ7 gene in a patient with complex mitochondrial deficiency, resulting in severely reduced coenzyme Q levels We demonstrate that the coenzyme Q analogue 2,4-dihydroxybensoic acid (2,4DHB) was able to specifically bypass the COQ7 deficiency, increase cellular coenzyme Q levels and rescue the biochemical defect in patient fibroblasts.ConclusionWe report the first patient with primary coenzyme Q deficiency due to a homozygous COQ7 mutation and a potentially beneficial treatment using 2,4DHB.

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.

BackgroundThere is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance.ResultsA total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization.ConclusionsThe CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.

BackgroundMassively parallel DNA sequencing (MPS) has the potential to revolutionize diagnostics, in particular for monogenic disorders. Inborn errors of metabolism (IEM) constitute a large group of monogenic disorders with highly variable clinical presentation, often with acute, nonspecific initial symptoms. In many cases irreversible damage can be reduced by initiation of specific treatment, provided that a correct molecular diagnosis can be rapidly obtained. MPS thus has the potential to significantly improve both diagnostics and outcome for affected patients in this highly specialized area of medicine.ResultsWe have developed a conceptually novel approach for acute MPS, by analysing pulsed whole genome sequence data in real time, using automated analysis combined with data reduction and parallelization. We applied this novel methodology to an in-house developed customized work flow enabling clinical-grade analysis of all IEM with a known genetic basis, represented by a database containing 474 disease genes which is continuously updated. As proof-of-concept, two patients were retrospectively analysed in whom diagnostics had previously been performed by conventional methods. The correct disease-causing mutations were identified and presented to the clinical team after 15 and 18 hours from start of sequencing, respectively. With this information available, correct treatment would have been possible significantly sooner, likely improving outcome.ConclusionsWe have adapted MPS to fit into the dynamic, multidisciplinary work-flow of acute metabolic medicine. As the extent of irreversible damage in patients with IEM often correlates with timing and accuracy of management in early, critical disease stages, our novel methodology is predicted to improve patient outcome. All procedures have been designed such that they can be implemented in any technical setting and to any genetic disease area. The strategy conforms to international guidelines for clinical MPS, as only validated disease genes are investigated and as clinical specialists take responsibility for translation of results. As follow-up in patients without any known IEM, filters can be lifted and the full genome investigated, after genetic counselling and informed consent.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-1090) contains supplementary material, which is available to authorized users.

Skeletal ciliopathies are a heterogenous group of disorders with overlapping clinical and radiographic features including bone dysplasia and internal abnormalities. To date, pathogenic variants in at least 30 genes, coding for different structural cilia proteins, are reported to cause skeletal ciliopathies. Here, we summarize genetic and phenotypic features of 34 affected individuals from 29 families with skeletal ciliopathies. Molecular diagnostic testing was performed using massively parallel sequencing (MPS) in combination with copy number variant (CNV) analyses and in silico filtering for variants in known skeletal ciliopathy genes. We identified biallelic disease-causing variants in seven genes: DYNC2H1, KIAA0753, WDR19, C2CD3, TTC21B, EVC, and EVC2. Four variants located in non-canonical splice sites of DYNC2H1, EVC, and KIAA0753 led to aberrant splicing that was shown by sequencing of cDNA. Furthermore, CNV analyses showed an intragenic deletion of DYNC2H1 in one individual and a 6.7 Mb de novo deletion on chromosome 1q24q25 in another. In five unsolved cases, MPS was performed in family setting. In one proband we identified a de novo variant in PRKACA and in another we found a homozygous intragenic deletion of IFT74, removing the first coding exon and leading to expression of a shorter message predicted to result in loss of 40 amino acids at the N-terminus. These findings establish IFT74 as a new skeletal ciliopathy gene. In conclusion, combined single nucleotide variant, CNV and cDNA analyses lead to a high yield of genetic diagnoses (90%) in a cohort of patients with skeletal ciliopathies.