Case for genome sequencing in infants and children with rare, undiagnosed or genetic diseases
=============================================================================================

* David Bick
* Marilyn Jones
* Stacie L Taylor
* Ryan J Taft
* John Belmont

## Abstract

Up to 350 million people worldwide suffer from a rare disease, and while the individual diseases are rare, in aggregate they represent a substantial challenge to global health systems. The majority of rare disorders are genetic in origin, with children under the age of five disproportionately affected. As these conditions are difficult to identify clinically, genetic and genomic testing have become the backbone of diagnostic testing in this population. In the last 10 years, next-generation sequencing technologies have enabled testing of multiple disease genes simultaneously, ranging from targeted gene panels to exome sequencing (ES) and genome sequencing (GS). GS is quickly becoming a practical first-tier test, as cost decreases and performance improves. A growing number of studies demonstrate that GS can detect an unparalleled range of pathogenic abnormalities in a single laboratory workflow. GS has the potential to deliver unbiased, rapid and accurate molecular diagnoses to patients across diverse clinical indications and complex presentations. In this paper, we discuss clinical indications for testing and historical testing paradigms. Evidence supporting GS as a diagnostic tool is supported by superior genomic coverage, types of pathogenic variants detected, simpler laboratory workflow enabling shorter turnaround times, diagnostic and reanalysis yield, and impact on healthcare.

*   clinical genome sequencing
*   rare and undiagnosed
*   genetic testing
*   neonates
*   pediatric

## Introduction

In 2017, the Global Genes Project1 estimated that 350 million people worldwide suffer from a rare disease. These diseases are individually rare, but in aggregate they affect 4%–8% of the population.2 3 Our curation of >3800 rare diseases listed by Orphanet indicates that ~80% are genetic or have genetic subtypes (online supplementary file 2). Children comprise approximately half of those affected by a genetic disease and 30% of these children do not live past their fifth birthday.

### Supplementary data

[[jmedgenet-2019-106111supp002.pdf]](pending:yes) 

Medical and surgical management of birth defects and rare genetic diseases are disproportionately large contributors to paediatric hospitalisations and present an enormous challenge to patients and families as well as healthcare systems.4 Children with chronic complex conditions (defined by length of illness) had 11-fold greater hospitalisation charges compared with others in a retrospective study of US hospitalisations for children.5 In a study from Western Australia, patients with rare disease diagnoses constituted 2% of the population but accounted for 10.6% of total hospital charges.6 We recently conducted an analysis of US paediatric hospitalisation charges using data from 2012 and found that mean total costs were up to US$77 000 higher in neonates and US$17 000 in older children with rare disease–linked diagnostic codes, and that these had longer hospital stays and increased mortality.7 

Because specific genetic diseases can be difficult to recognise based on clinical features alone, the use of genetic testing in the paediatric population is critical for diagnosis and treatment. In this review article, we review the indications for genetic and genomic testing and then detail the testing technologies that are used. With this background, we review the literature supporting GS as a first-tier test in children focusing on diagnostic yield, time-to-diagnosis, patient care, health outcomes and health economic impact.

## Clinical indications for genetic and genomic testing

Identification of patients appropriate for genetic testing has evolved substantially in the last 25 years, coincident with the ability to easily and cost-effectively test for an increasing number of disorders. The American College of Medical Genetics and Genomics (ACMG) has published indications for cases in which the use of genomic sequencing approaches should be considered as well as a policy statement discussing the clinical use of aetiological diagnosis via genetic and genomic testing.8 Genetic and genomic sequencing approaches should be considered in the clinical diagnostic assessment in several scenarios including those in which a patient presents with a likely genetic disorder but a single genetic diagnosis or specific targeted testing is not obvious. Expanding on this idea, we suggest some additional general features of genetic disorders that non-specialists may use to help recognise when genomic testing may be appropriate (box 1).

Box 1. 
### Indications for genome sequencing

*   The phenotype or family history data strongly implicate a genetic aetiology, but the phenotype does not correspond with a specific disorder for which a genetic test targeting a specific gene is available on a clinical basis.

*   A clinical diagnosis of a disorder known to be caused by multiple genes (extensive locus heterogeneity).

*   Clinical features which are insufficient by themselves to make a clinical diagnosis, but that are known to be associated with multiple genetic disorders.

*   A clinical diagnosis of a known genetic disorder in which single gene or other targeted testing has been negative.

*   The patient has an atypical clinical course for the disease under consideration (eg, unexpected severity, duration, failure of response to therapy, idiosyncratic drug reaction).

*   Early onset of disorder typically seen in adulthood.

*   Rare and specific clinical or laboratory abnormalities (eg, laboratory test results far outside of expected ranges, rare anatomical variants, etc).

*   Atypical or complex combinations of clinical abnormalities or additional signs and symptoms not explained by a previous molecular diagnosis.

## Approaches to genetic testing

Prior to the introduction of next-generation sequencing (NGS), several technologies were used to identify the basis of genetic diseases. The oldest, G-banded karyotype analysis can detect structural and numerical chromosome aberrations as well as mosaicism. However, the diagnostic yield is limited because abnormalities below 5–10 megabases often go undetected.9 In the early 1990s, fluorescence in situ hybridisation (FISH) was developed. FISH detects genetic abnormalities below the threshold of the G-banded karyotype, facilitating the detection of submicroscopic events (eg, deletions adjacent to the telomeres) involved in disease. FISH, however, is constrained to assessment of chromosome regions that can be targeted by FISH probes and abnormalities below 50–300 kb cannot be detected.10 

Karyotype and FISH have largely been replaced by chromosomal microarray (CMA), which allows for simultaneous evaluation of all chromosomes for copy number imbalances and in some instances uniparental isodisomy.11 The use of CMA has revealed that submicroscopic cytogenetic abnormalities are significant contributors to birth defects and neonatal neurological disorders.12 CMA is often offered as a first-tier test in the assessment of children presenting with diseases thought to have a genetic basis, such as multiple congenital abnormalities and developmental delay (DD) with a detection rate between 15% and 20% depending on the clinical indication.13–15 There are differences among CMA platforms that affect the range of abnormalities detected. Arrays based on standard sets of single-nucleotide polymorphisms may have somewhat lower resolution for particular genes compared with custom array comparative genomic hybridisation but are superior for the detection of copy number variant (CNV) mosaicism as well as clinically important copy neutral abnormalities, including uniparental isodisomy and close consanguinity. CMA cannot detect balanced chromosomal rearrangements such as balanced translocation and inversions.16 Dideoxy (Sanger) sequencing, developed in 1977,17 examines short stretches of DNA for single nucleotide variants (SNVs), small insertions and small deletions.

The ACMG affirms that the definitive diagnosis of a genetic disease has clinical use for individuals.8 Given the potential use of a diagnosis, the limitations of these standard techniques is of great concern and presents a major obstacle to progress in the management of patients with suspected genetic disease. For example, the respective diagnostic yields for CMA for common disorders such as autism spectrum disorder (ASD) or DD in the paediatric population are, on average, quite low (9.3%–13.1%)18 19 and the diagnostic rates for individuals with other commonly encountered but phenotypically non-specific diseases (eg, non-syndromic birth defects) may be similar or even lower.20 

Time-to-diagnosis is an important metric to consider in children with rare genetic diseases, particularly critically ill neonates admitted to neonatal intensive care units and children admitted to other intensive care settings. Genetic disease may present fewer specific clinical features in this population and many neonates either die or are discharged before a diagnosis is obtained. Unfortunately, standard genetic testing strategies often involve a series of tests which can take weeks or sometimes months to complete. Diagnostic evaluation typically involves multiple specialist consultations, laboratory tests, imaging studies and tissue biopsies. The length of the diagnostic odyssey for rare diseases ranges from 5 to 7 years1 and for many is ultimately disappointing when a diagnosis is not achieved.21 

Genomic medicine today features information obtained from ES and GS in disease diagnosis and management. Large gene sequencing panels and ES via NGS have altered the way new disease-causing genes are discovered in addition to reducing the time-to-diagnosis.3 22 To date, ES has been used extensively in both clinical and research settings.23–26 Large-scale use of GS is also underway through the Undiagnosed Diseases Network,27 the 100,000 Genomes Project28 and other national programmes. Rapidly falling costs and faster time-to-results afforded by NGS have driven clinical adoption.29 The first use of NGS for rare disease research occurred with the identification of genes responsible for Freeman-Sheldon syndrome, Miller syndrome and Schinzel-Giedion syndrome,30 31 and its clinical use was demonstrated in a patient who received a life-saving bone marrow transplant following diagnosis with NGS.32 Now, more than 180 novel genes involved in rare diseases are added each year to the list of known disease-causing genes,3 30 but this pace of discovery may be reaching a plateau. Going forward, greater emphasis will be placed on the completeness of the genetic diagnostic evaluation (identification of all disease-causing alleles) for rare disorders that are difficult to detect using standard genetic testing techniques or that require a combination of tests. Because GS can close some of this gap, it shows exciting potential for efficiently solving a greater proportion of rare disease cases.

## Genome sequencing for genetic disease diagnosis

GS has the ability to identify a variety of molecular aetiologies for genetic disease. We reviewed the abstracts of >2000 publications focusing on 36 studies (see online supplementary file 1 for the list and selection methodology) that address the most important laboratory and clinical factors that influence efficacy in diagnosis.

### Supplementary data

[[jmedgenet-2019-106111supp001.pdf]](pending:yes) 

### Genome sequencing provides a superior exome

ES enables interrogation of the approximately 1% to 1.5% of the human genome which is protein-coding. ES is widely used in both research and clinical practice, with studies showing improved diagnostic yield compared with historical approaches33 34 in patients with undiagnosed neurodevelopmental disorders,35 children with intellectual disability (ID),36 37 ASD18 and many others. There is increasing evidence, however, that ES cannot capture the complete range of pathogenic variation across the exome. For example, ES only covers approximately 98% of the exome and results from a recent study suggest that the current standard of 120× coverage for ES may be insufficient for consistent breadth of coverage across the exome.34 For genes that the ACMG recommend be evaluated for secondary findings, Meienberg *et al* showed that GS provided 100% coverage of ACMG genes versus 75% by ES due to incomplete exon coverage of a number of exons in ACMG genes.38 Further, the same study found that for RefSeq genes, 9% of the first exons were not covered by ES while GS provided complete coverage. Additional studies show that GS coverage and variant calling is less affected by GC content,38 has more complete coverage of exons39 40 and has more even coverage than ES. As a result GS requires lower average coverage to obtain the same accuracy in variant calling compared with ES.41 Additionally, GS has less dispersion in the distribution of allele coverage allowing higher accuracy in calling heterozygous positions compared with ES.42 

### Genome sequencing and detection of pathogenic variants

GS examines approximately 90% of the human genome43 offering a more comprehensive analysis than ES40 and a growing body of literature is demonstrating that GS can provide a molecular diagnosis in cases where ES did not (see online supplementary table 2 for examples).44–47 Intergenic and intronic pathogenic variants are growing in number and importance48 spanning from pathogenic SNVs to more complex variations.49 50 The detection of coding CNVs that are smaller than three exons may require GS because pathogenic single-exon CNVs are frequently missed by ES analyses.51 Further, balanced chromosomal rearrangements, importantly those with high recurrence risks (eg, insertion-translocations), are difficult to detect with CMA and ES, whereas they may be detected with GS.52 It should be noted that GS cannot detect all chromosomal abnormalities.53 GS data may be analysed to identify pathogenic repeat expansions54 and GS from libraries constructed using the Hi-C protocol or through other sequencing technologies can be used to produce a phased genome.55 For cases involving a recessive disorder, variants in *cis* can be distinguished from variants in *trans* obviating the need to test other family members to establish the phase of the variants. This technique can also detect chromosomal rearrangements.56 

### Supplementary data

[[jmedgenet-2019-106111supp003.pdf]](pending:yes) 

### Genome sequencing and mitochondrial disorders

Mitochondrial disorders are a phenotypically and genetically heterogeneous group of diseases making diagnosis particularly challenging. NGS-based tests of the mitochondrial genome can detect common and rare mitochondrial SNVs and deletions.57 NGS-based testing can also detect low levels of heteroplasmic changes which is difficult using conventional tests such as Sanger sequencing.57 58 NGS tests have been developed that evaluate both the mitochondrial genome and a panel of nuclear genes that cause mitochondrial disease in a single test.59 NGS-based mitochondrial genome analysis followed by ES can be effective. In one study, causative pathogenic variants in the mitochondrial genome were found in 20% of the patients while ES of nuclear genes found the aetiology in an additional 49% of the patients.58 GS data include both the mitochondrial genome and all of the data found in ES therefore making this a more efficient method to detect mitochondrial disorders.38 51 57 58 GS at 30–40× coverage, suitable for nuclear gene variant calling, results in 5000–9000× mitochondrial genome coverage and readily lends itself to mitochondrial SNV analysis >5% allele fraction (RJT, personal communication).

### Genome sequencing reduces time-to-diagnosis

In the paediatric and neonatal population with rare, undiagnosed or genetic disesease, reducing the time-to-diagnosis is important because the progression of disease can be rapid. There are approximately 4000 genes with a phenotype-causing mutation,60 and many present within the first 28 days of life. For neonatal intensive care unit admissions, serial genetic testing may be too slow for optimal clinical management. Additionally, the full clinical phenotype may not manifest in neonates given the early stage at which disease is suspected. Finally, a large degree of clinical and genetic heterogeneity is often noted in acutely ill neonates, which further contributes to the lack of a timely molecular diagnosis for suspected genetic diseases.

Recent technological developments in rapid GS have highlighted its use in children, particularly critically ill neonates. A few studies examining this population have reported time-to-diagnosis ranges of 5 to 8 days61 to as little as 19.5 hours.62 In these studies, the remarkable speed is due in part to advances in bioinformatics processes including the field-programmable gate array based pipeline and automation of the tertiary pipeline.63 In a direct comparison of GS with ES in children with undiagnosed neurodevelopmental disorders, Soden et al35 reported a significant difference between the two technologies wherein the time-to-diagnosis using rapid GS was significantly less than ES.

### Genome sequencing provides high diagnostic yield

Numerous studies have demonstrated the impact of NGS-based approaches on improved diagnostic yield. A recent systematic review comparing the diagnostic rates of NGS-based tests (ie, ES and GS) and CMA found that the former had significantly greater diagnostic use compared with the latter.43 Direct comparisons between the diagnostic yields of GS and ES are difficult to make as rates tend to vary based on a variety of factors including patient selection bias, clinical indication and the continual discovery of disease-causing variants (see table 1).24 Importantly, there are studies reporting higher diagnostic yield of GS over other tests (including standard genetic testing, CMA and ES) in children with severe intellectual disability,64 neurodevelopmental disorder,35 developmental delay of unknown aetiology,65 critically ill neonates61 66 and early infantile epileptic encephalopathy.46 

View this table:
[Table 1](http://jmg.bmj.com/content/56/12/783/T1)

Table 1 
Select studies illustrating the diagnostic variability of genetic and genomic testing.

### Genome sequencing and reanalysis

NGS has significantly increased the pace of discovery of new disease–gene relationships allowing for increased diagnostic yields when GS and ES are reanalysed at a later time. Reanalysis yields increase with both GS and ES; however, this increase is oftentimes more pronounced in GS cases due in part to the fact that GS offers better coverage of coding exons than ES.67 It is important to acknowledge that significant improvements in exon capture have allowed for increased detection of pathogenic variants with ES. However, the argument can be made that obtaining a comprehensive data set with GS initially would negate the need to repeat ES with those technological improvements.

### Clinical use of genomic testing

In its narrowest sense, clinical use refers to the ability of a screening or diagnostic test to prevent or ameliorate adverse health outcomes such as mortality, morbidity or disability through the adoption of efficacious treatments conditioned on test results.68 Achieving a genetic diagnosis in children is important because it can lead to early and informed disease management and in some cases a life-saving intervention. For example, identification of two compound heterozygous deletions in a premature baby with refractory hypotension and anuria (a condition that is typically lethal) with NGS-targeted gene panels led to a treatment regimen that improved renal function such that only mild residual chronic renal failure symptoms were present later in life.69 Similarly, classification of epileptic seizures at the molecular level via genetic diagnosis can inform which antiepileptic treatment will produce the best results70 and sometimes reverse epileptogenic abnormalities.71 The clinical use of ES has been established,72 as evidenced by patients with epileptic encephalopathy in which physical therapy practices were altered and ineffective feeding behaviours were discontinued following diagnosis via ES.14 

A growing number of studies have demonstrated the clinical use of GS. For example, in a small, retrospective study of critically ill infants that received diagnosis with rapid GS, 65% reported immediate clinical usefulness of the diagnosis, 20% received a diagnosis with strongly favourable effects on disease management and 30% began palliative care.61 73 Another study examined a clinically heterogeneous paediatric cohort in which diagnosis with GS had a significant impact on clinical care beyond genetic testing and included changes in disease management based on published management guidelines, case reports or known function of the involved genes.65 Similarly, in children with neurodevelopmental disorders of unknown aetiology, 49% reported a change in clinical care or impression of pathophysiology following diagnosis with GS.35 While each of the studies were small or moderate in size (n≤119), the data build on the established clinical use of ES. An increasing number of studies focus on the use of GS as a first-tier test, rather than a last resort solution demonstrating its clinical use.44 65 73 As more GS studies appear, the clinical use of GS versus ES will become clear.

### Health economic impact of genome sequencing

The duration of the diagnostic odyssey is closely related to healthcare costs. For patients with rare and undiagnosed genetic disease, the cost of a standard diagnostic work-up is high, as additional tests, procedures, some requiring general anaesthesia, and specialist consultations are required when prior analyses fail to provide a diagnosis. For example, one study of children with neurodevelopmental disorders in the USA estimated that the cost of tests prior to receiving an NGS-based diagnosis was US$19 100.35 Thus, a comprehensive NGS-based approach is more cost-effective than iterative single-gene testing. A recent microcosting study showed that a genomic sequencing care pathway, where genomic sequencing is performed when genetic disease is initially suspected, can provide an efficient and economical approach to arriving at a diagnosis saving healthcare dollars.74 Incorporation of ES earlier in the diagnostic journey resulted in an incremental cost savings of US$6838 per additional diagnosis compared with the standard diagnostic pathway in children suspected of having a monogenic disorder.75 Likewise, ES achieved more conclusive diagnoses than did the standard care pathway without incurring higher costs in a group of children with complex neurological disorders of suspected genetic origin.76 Cost of care estimates from a recent Undiagnosed Disease Network (UDN) study suggest that the UDN approach (in which 74% of diagnoses were made with ES or GS) has the potential to be cost-effective by avoiding an expensive diagnostic odyssey. For example, prior to acceptance to the UDN, the average cost of care was US$305 428 while the average cost of the UDN evaluation was US$18 903, representing 6% of the total cost.27 

The cost of GS is currently higher than ES; however, it is important to keep in mind the advantages of GS (eg, detection of trinucleotide repeat diseases, CNVs, disorders of the mitochondrial genome) and therefore the added value of GS. In a microcosting study of children with ASD, the estimated cost of GS ($C2857) was more than that of CMA ($C744) and ES ($C1655). The study points out that automation of GS allows many samples to be simultaneously processed resulting in reduced labour time compared with ES.77 The authors noted that the higher cost of GS was largely due to greater bioinformatics demand. Technological improvements in bioinformatics automation and interpretation are predicted to bring the cost of GS closer to that of ES.

When comparing the cost of GS and ES, it is important to consider the cost drivers for the different technologies: greater than 90% of the cost of GS is directly related to sequencing; with ES, the cost is mainly due to the DNA capture assay and associated labour.39 Over time, sequencing costs have greatly decreased,39 so performing GS early on in the diagnostic pathway may prove to be a less expensive alternative to performing CMA and later ES in certain disease populations.

### Incidental and secondary findings

There are important ethical implications associated with the clinical application of ES and GS, particularly in children. ES and GS frequently identify incidental or secondary findings—genetic variants of potential importance to the child or family that are unrelated to the diseases for which the testing is performed.78 Reporting incidental findings is controversial and has resulted in sometimes-conflicting policy recommendations.79 Some groups suggest returning pathogenic variants from a list of medically actionable genes with findings currently lacking an available therapeutic intervention left unreported. Others recommend offering pathogenic findings in treatable and untreatable disorders as well as carrier status for recessive diseases.80 This discussion is particularly relevant in the paediatric population as they are not considered legally competent when screened but will gain competence as they grow older.81 The fact that many adults choose not to have genetic testing when offered82 raises important concerns regarding future autonomy and privacy protection; however, an in-depth analysis of these issues is beyond the scope of this review.

The large number of variants that result from ES and GS represents a significant challenge to their use in routine clinical practice. Both commercial and laboratory-developed informatics tools have been developed that filter out all but a few hundred variants for manual review. Still, this can result in a time-consuming task.83 Informatics tools that ingest phenotypic information to generate a candidate gene list are appearing.84 Combining tools that filter variants with one that proposes a gene list should significantly reduce analysis time.

## Conclusions and future directions

In this review, we have investigated the evidence for GS as a first-line tool for the diagnosis of rare and undiagnosed genetic diseases. GS provides high diagnostic rates across a variety of molecular aetiologies and can reduce the length of the diagnostic odyssey—both of which have positive downstream health-economic benefits. Receiving a molecular diagnosis also has profound psychosocial impact on patients as well as their families as they can give a name to the disease and connect the family with other similarly affected patients.85 Finally, receiving a definitive diagnosis enables the use of disease-specific genetic counselling services that can influence both family planning and, in some cases, palliative care.86 

The use of GS as a first-tier test rather than a ‘last resort’ would be beneficial to many populations, especially critically ill neonates where a rapid diagnosis is essential. Future research should explore the diseases and presentations in which rapid GS has the most diagnostic effectiveness and is most likely to affect acute disease management. There are far fewer publications using NGS-based diagnostic tools in the adult population. Adult patients seeking diagnosis of a suspected genetic disease presents increased diagnostic challenges because additional factors, such as ageing and environmental exposures, require critical consideration.87 

Beyond rare Mendelian diseases, GS provides opportunities going forward to identify mosaicism,88 genetic disease modifiers,89 pharmacogenomic variants,90 uniparental disomy,91 polygenic risk scores,92 infectious diseases,93 blood groups,94 HLA genotypes95 and ancestry,96 many of which cannot be determined from ES.

Finally, the diagnostic yield of GS is expected to increase with the development of novel bioinformatics methods and with the growing detection and understanding of disease-causing variants in non-coding regions. In paediatric patients with rare and undiagnosed diseases, clinical implementation of GS as a first-line test has the potential to increase diagnostic yields, reduce the time to diagnosis and positively impact the clinical care pathway.

## Acknowledgments

The authors thank Kirsten Curnow for her editorial review and Kathy Rader for assistance with manuscript submission.

## Footnotes

*   Contributors DB, MJ, RJT and JB were involved in the planning and developing of the main conceptual ideas. DB and ST conducted the literature searches and provided an initial draft with critical input from MJ, RJT and JB. All authors provided feedback and contributed to the final version of the manuscript.

*   Competing interests DB: Envision Genomics—stock; Smith Family Clinic LLC—billing for care; Clinical Services Laboratory LLC—fee for clinical analysis; Genomics England—scientific advisory board. MJ: nothing to disclose. ST: current employee and shareholder of Illumina. RJT: current employee and shareholder of Illumina. JB: current employee and shareholder of Illumina.

*   Provenance and peer review Not commissioned; externally peer reviewed.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: [http://creativecommons.org/licenses/by-nc/4.0/](http://creativecommons.org/licenses/by-nc/4.0/).

## References

1.  GlobalGenesProject. Rare diseases: facts and statistics., 2017. Available: [https://globalgenesorg/rare-diseases-facts-statistics/](https://globalgenesorg/rare-diseases-facts-statistics/) 
    
    

2.   Baird PA , Anderson TW , Newcombe HB , Lowry RB . Genetic disorders in children and young adults: a population study. Am J Hum Genet 1988;42:677–93.
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=3358420&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=A1988N143800003&link_type=ISI) 

3.   Boycott KM , Vanstone MR , Bulman DE , MacKenzie AE . Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nat Rev Genet 2013;14:681–91.[doi:10.1038/nrg3555](http://dx.doi.org/10.1038/nrg3555) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/nrg3555&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=23999272&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

4.   McCandless SE , Brunger JW , Cassidy SB . The burden of genetic disease on inpatient care in a children's hospital. Am J Hum Genet 2004;74:121–7.[doi:10.1086/381053](http://dx.doi.org/10.1086/381053) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1086/381053&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=14681831&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000187723500011&link_type=ISI) 

5.   Simon TD , Berry J , Feudtner C , Stone BL , Sheng X , Bratton SL , Dean JM , Srivastava R . Children with complex chronic conditions in inpatient hospital settings in the United States. Pediatrics 2010;126:647–55.[doi:10.1542/peds.2009-3266](http://dx.doi.org/10.1542/peds.2009-3266) 
    
    [Abstract/FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTA6InBlZGlhdHJpY3MiO3M6NToicmVzaWQiO3M6OToiMTI2LzQvNjQ3IjtzOjQ6ImF0b20iO3M6MjU6Ii9qbWVkZ2VuZXQvNTYvMTIvNzgzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

6.   Walker CE , Mahede T , Davis G , Miller LJ , Girschik J , Brameld K , Sun W , Rath A , Aymé S , Zubrick SR , Baynam GS , Molster C , Dawkins HJS , Weeramanthri TS . The collective impact of rare diseases in Western Australia: an estimate using a population-based cohort. Genet Med 2017;19:546–52.[doi:10.1038/gim.2016.143](http://dx.doi.org/10.1038/gim.2016.143) 
    
    

7.   Gonzaludo N , Belmont JW , Gainullin VG , Taft RJ . Estimating the burden and economic impact of pediatric genetic disease. Genet Med 2018;18.[doi:10.1038/s41436-018-0398-5](http://dx.doi.org/10.1038/s41436-018-0398-5) 
    
    

8.  ACMG Board of Directors. Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics. Genet Med 2015;17:505–7.[doi:10.1038/gim.2015.41](http://dx.doi.org/10.1038/gim.2015.41) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/gim.2015.41&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25764213&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

9.   Shaffer LG , Bejjani BA . Medical applications of array CGH and the transformation of clinical cytogenetics. Cytogenet Genome Res 2006;115:303–9.[doi:10.1159/000095928](http://dx.doi.org/10.1159/000095928) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1159/000095928&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=17124414&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000242391500015&link_type=ISI) 

10.  Beliveau BJ , Joyce EF , Apostolopoulos N , Yilmaz F , Fonseka CY , McCole RB , Chang Y , Li JB , Senaratne TN , Williams BR , Rouillard J-M , Wu C-t . Versatile design and synthesis platform for visualizing genomes with Oligopaint FISH probes. Proceedings of the National Academy of Sciences 2012;109:21301–6.[doi:10.1073/pnas.1213818110](http://dx.doi.org/10.1073/pnas.1213818110) 
    
    [Abstract/FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMjoiMTA5LzUyLzIxMzAxIjtzOjQ6ImF0b20iO3M6MjU6Ii9qbWVkZ2VuZXQvNTYvMTIvNzgzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

11.  Tucker T , Schlade-Bartusiak K , Eydoux P , Nelson TN , Brown L . Uniparental disomy: can SNP array data be used for diagnosis? Genet Med 2012 (published Online First: 2012/04/28).
    
    

12.  Shaffer LG , Kashork CD , Saleki R , Rorem E , Sundin K , Ballif BC , Bejjani BA . Targeted genomic microarray analysis for identification of chromosome abnormalities in 1500 consecutive clinical cases. J Pediatr 2006;149:98–102.[doi:10.1016/j.jpeds.2006.02.006](http://dx.doi.org/10.1016/j.jpeds.2006.02.006) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1016/j.jpeds.2006.02.006&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=16860135&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000239352000025&link_type=ISI) 

13.  Miller DT , Adam MP , Aradhya S , Biesecker LG , Brothman AR , Carter NP , Church DM , Crolla JA , Eichler EE , Epstein CJ , Faucett WA , Feuk L , Friedman JM , Hamosh A , Jackson L , Kaminsky EB , Kok K , Krantz ID , Kuhn RM , Lee C , Ostell JM , Rosenberg C , Scherer SW , Spinner NB , Stavropoulos DJ , Tepperberg JH , Thorland EC , Vermeesch JR , Waggoner DJ , Watson MS , Martin CL , Ledbetter DH . Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet 2010;86:749–64.[doi:10.1016/j.ajhg.2010.04.006](http://dx.doi.org/10.1016/j.ajhg.2010.04.006) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1016/j.ajhg.2010.04.006&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=20466091&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000278045300011&link_type=ISI) 

14.  Joshi C , Kolbe DL , Mansilla MA , Mason SO , Smith RJH , Campbell CA . Reducing the cost of the diagnostic odyssey in early onset epileptic encephalopathies. BioMed Research International 2016;2016:1–8.[doi:10.1155/2016/6421039](http://dx.doi.org/10.1155/2016/6421039) 
    
    

15.  Howell KB , Kornberg AJ , Harvey AS , Ryan MM , Mackay MT , Freeman JL , Rodriguez Casero MV , Collins KJ , Hayman M , Mohamed A , Ware TL , Clark D , Bruno DL , Burgess T , Slater H , McGillivray G , Leventer RJ . High resolution chromosomal microarray in undiagnosed neurological disorders. J Paediatr Child Health 2013;49:716–24.[doi:10.1111/jpc.12256](http://dx.doi.org/10.1111/jpc.12256) 
    
    

16.  Zepeda-Mendoza CJ , Ibn-Salem J , Kammin T , Harris DJ , Rita D , Gripp KW , MacKenzie JJ , Gropman A , Graham B , Shaheen R , Alkuraya FS , Brasington CK , Spence EJ , Masser-Frye D , Bird LM , Spiegel E , Sparkes RL , Ordulu Z , Talkowski ME , Andrade-Navarro MA , Robinson PN , Morton CC . Computational prediction of position effects of apparently balanced human chromosomal rearrangements. The American Journal of Human Genetics 2017;101:206–17.[doi:10.1016/j.ajhg.2017.06.011](http://dx.doi.org/10.1016/j.ajhg.2017.06.011) 
    
    

17.  Sanger F , Air GM , Barrell BG , Brown NL , Coulson AR , Fiddes JC , Hutchison CA , Slocombe PM , Smith M . Nucleotide sequence of bacteriophage φX174 DNA. Nature 1977;265:687–95.[doi:10.1038/265687a0](http://dx.doi.org/10.1038/265687a0) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/265687a0&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=870828&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=A1977CW61200017&link_type=ISI) 

18.  Tammimies K , Marshall CR , Walker S , Kaur G , Thiruvahindrapuram B , Lionel AC , Yuen RKC , Uddin M , Roberts W , Weksberg R , Woodbury-Smith M , Zwaigenbaum L , Anagnostou E , Wang Z , Wei J , Howe JL , Gazzellone MJ , Lau L , Sung WWL , Whitten K , Vardy C , Crosbie V , Tsang B , D’Abate L , Tong WWL , Luscombe S , Doyle T , Carter MT , Szatmari P , Stuckless S , Merico D , Stavropoulos DJ , Scherer SW , Fernandez BA . Molecular diagnostic yield of chromosomal microarray analysis and whole-exome sequencing in children with autism spectrum disorder. JAMA 2015;314:895–903.[doi:10.1001/jama.2015.10078](http://dx.doi.org/10.1001/jama.2015.10078) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1001/jama.2015.10078&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=26325558&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

19.  Coulter ME , Miller DT , Harris DJ , Hawley P , Picker J , Roberts AE , Sobeih MM , Irons M . Chromosomal microarray testing influences medical management. Genetics in Medicine 2011;13:770–6.[doi:10.1097/GIM.0b013e31821dd54a](http://dx.doi.org/10.1097/GIM.0b013e31821dd54a) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1097/GIM.0b013e31821dd54a&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=21716121&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

20.  Warburton D , Ronemus M , Kline J , Jobanputra V , Williams I , Anyane-Yeboa K , Chung W , Yu L , Wong N , Awad D , Yu C-yu , Leotta A , Kendall J , Yamrom B , Lee Y-ha , Wigler M , Levy D . The contribution of de novo and rare inherited copy number changes to congenital heart disease in an unselected sample of children with conotruncal defects or hypoplastic left heart disease. Hum Genet 2014;133:11–27.[doi:10.1007/s00439-013-1353-9](http://dx.doi.org/10.1007/s00439-013-1353-9) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1007/s00439-013-1353-9&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=23979609&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

21.  Eurodis . EurodisCare2: survey of diagnostic delays, 8 diseases. Europe 2015.
    
    

22.  Bhattacharjee A , Sokolsky T , Wyman SK , Reese MG , Puffenberger E , Strauss K , Morton H , Parad RB , Naylor EW . Development of DNA confirmatory and high-risk diagnostic testing for newborns using targeted next-generation DNA sequencing. Genet Med 2015;17:337–47.[doi:10.1038/gim.2014.117](http://dx.doi.org/10.1038/gim.2014.117) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/gim.2014.117&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25255367&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

23.  Zhu X , Petrovski S , Xie P , Ruzzo EK , Lu Y-F , McSweeney KM , Ben-Zeev B , Nissenkorn A , Anikster Y , Oz-Levi D , Dhindsa RS , Hitomi Y , Schoch K , Spillmann RC , Heimer G , Marek-Yagel D , Tzadok M , Han Y , Worley G , Goldstein J , Jiang Y-H , Lancet D , Pras E , Shashi V , McHale D , Need AC , Goldstein DB . Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios. Genet Med 2015;17:774–81.[doi:10.1038/gim.2014.191](http://dx.doi.org/10.1038/gim.2014.191) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/gim.2014.191&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25590979&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

24.  Retterer K , Juusola J , Cho MT , Vitazka P , Millan F , Gibellini F , Vertino-Bell A , Smaoui N , Neidich J , Monaghan KG , McKnight D , Bai R , Suchy S , Friedman B , Tahiliani J , Pineda-Alvarez D , Richard G , Brandt T , Haverfield E , Chung WK , Bale S . Clinical application of whole-exome sequencing across clinical indications. Genet Med 2016;18:696–704.[doi:10.1038/gim.2015.148](http://dx.doi.org/10.1038/gim.2015.148) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/gim.2015.148&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=26633542&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

25.  Thevenon J , Duffourd Y , Masurel-Paulet A , Lefebvre M , Feillet F , El Chehadeh-Djebbar S , St-Onge J , Steinmetz A , Huet F , Chouchane M , Darmency-Stamboul V , Callier P , Thauvin-Robinet C , Faivre L , Rivière JB . Diagnostic odyssey in severe neurodevelopmental disorders: toward clinical whole-exome sequencing as a first-line diagnostic test. Clin Genet 2016;89:700–7.[doi:10.1111/cge.12732](http://dx.doi.org/10.1111/cge.12732) 
    
    

26.  Meng L , Pammi M , Saronwala A , Magoulas P , Ghazi AR , Vetrini F , Zhang J , He W , Dharmadhikari AV , Qu C , Ward P , Braxton A , Narayanan S , Ge X , Tokita MJ , Santiago-Sim T , Dai H , Chiang T , Smith H , Azamian MS , Robak L , Bostwick BL , Schaaf CP , Potocki L , Scaglia F , Bacino CA , Hanchard NA , Wangler MF , Scott D , Brown C , Hu J , Belmont JW , Burrage LC , Graham BH , Sutton VR , Craigen WJ , Plon SE , Lupski JR , Beaudet AL , Gibbs RA , Muzny DM , Miller MJ , Wang X , Leduc MS , Xiao R , Liu P , Shaw C , Walkiewicz M , Bi W , Xia F , Lee B , Eng CM , Yang Y , Lalani SR . Use of exome sequencing for infants in intensive care units: ascertainment of severe single-gene disorders and effect on medical management. JAMA Pediatr 2017;171:e173438.
    
    

27.  Splinter K , Adams DR , Bacino CA , Bellen HJ , Bernstein JA , Cheatle-Jarvela AM , Eng CM , Esteves C , Gahl WA , Hamid R , Jacob HJ , Kikani B , Koeller DM , Kohane IS , Lee BH , Loscalzo J , Luo X , McCray AT , Metz TO , Mulvihill JJ , Nelson SF , Palmer CGS , Phillips JA , Pick L , Postlethwait JH , Reuter C , Shashi V , Sweetser DA , Tifft CJ , Walley NM , Wangler MF , Westerfield M , Wheeler MT , Wise AL , Worthey EA , Yamamoto S , Ashley EA , Undiagnosed Diseases Network . Effect of genetic diagnosis on patients with previously undiagnosed disease. N Engl J Med 2018;379:2131–9.[doi:10.1056/NEJMoa1714458](http://dx.doi.org/10.1056/NEJMoa1714458) 
    
    

28.  Barwell JG , O’Sullivan RBG , Mansbridge LK , Lowry JM , Dorkins HR . Challenges in implementing genomic medicine: the 100,000 Genomes Project. Journal of Translational Genetics and Genomics 2018;2:2–10.[doi:10.20517/jtgg.2018.17](http://dx.doi.org/10.20517/jtgg.2018.17) 
    
    

29.  Wilkinson DJC , Barnett C , Savulescu J , Newson AJ . Genomic intensive care: should we perform genome testing in critically ill newborns? Arch Dis Child Fetal Neonatal Ed 2016;101:F94–F98.[doi:10.1136/archdischild-2015-308568](http://dx.doi.org/10.1136/archdischild-2015-308568) 
    
    [FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6MTM6ImZldGFsbmVvbmF0YWwiO3M6NToicmVzaWQiO3M6OToiMTAxLzIvRjk0IjtzOjQ6ImF0b20iO3M6MjU6Ii9qbWVkZ2VuZXQvNTYvMTIvNzgzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

30.  Hoischen A , van Bon BWM , Gilissen C , Arts P , van Lier B , Steehouwer M , de Vries P , de Reuver R , Wieskamp N , Mortier G , Devriendt K , Amorim MZ , Revencu N , Kidd A , Barbosa M , Turner A , Smith J , Oley C , Henderson A , Hayes IM , Thompson EM , Brunner HG , de Vries BBA , Veltman JA . De novo mutations of SETBP1 cause Schinzel-Giedion syndrome. Nat Genet 2010;42:483–5.[doi:10.1038/ng.581](http://dx.doi.org/10.1038/ng.581) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/ng.581&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=20436468&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000278081500009&link_type=ISI) 

31.  SB N , Buckingham KJ , Lee C , Bigham AW , Tabor HK , Dent KM , Huff CD , Shannon PT , Jabs EW , Nickerson DA , Shendure J , Bamshad MJ . Exome sequencing identifies the cause of a Mendelian disorder. Nat Genet 2010;42:30–5.
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/ng.499&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=19915526&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000273055100013&link_type=ISI) 

32.  Worthey EA , Mayer AN , Syverson GD , Helbling D , Bonacci BB , Decker B , Serpe JM , Dasu T , Tschannen MR , Veith RL , Basehore MJ , Broeckel U , Tomita-Mitchell A , Arca MJ , Casper JT , Margolis DA , Bick DP , Hessner MJ , Routes JM , Verbsky JW , Jacob HJ , Dimmock DP . Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease. Genet Med 2011;13:255–62.[doi:10.1097/GIM.0b013e3182088158](http://dx.doi.org/10.1097/GIM.0b013e3182088158) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1097/GIM.0b013e3182088158&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=21173700&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000287694800014&link_type=ISI) 

33.  Yang Y , Muzny DM , Reid JG , Bainbridge MN , Willis A , Ward PA , Braxton A , Beuten J , Xia F , Niu Z , Hardison M , Person R , Bekheirnia MR , Leduc MS , Kirby A , Pham P , Scull J , Wang M , Ding Y , Plon SE , Lupski JR , Beaudet AL , Gibbs RA , Eng CM . Clinical whole-exome sequencing for the diagnosis of mendelian disorders. N Engl J Med 2013;369:1502–11.[doi:10.1056/NEJMoa1306555](http://dx.doi.org/10.1056/NEJMoa1306555) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1056/NEJMoa1306555&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=24088041&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000328101700007&link_type=ISI) 

34.  Kong SW , Lee IH , Liu X , Hirschhorn JN , Mandl KD . Measuring coverage and accuracy of whole-exome sequencing in clinical context. Genet Med 2018 (published Online First: 2018/05/24).
    
    

35.  Soden SE , Saunders CJ , Willig LK , Farrow EG , Smith LD , Petrikin JE , LePichon J-B , Miller NA , Thiffault I , Dinwiddie DL , Twist G , Noll A , Heese BA , Zellmer L , Atherton AM , Abdelmoity AT , Safina N , Nyp SS , Zuccarelli B , Larson IA , Modrcin A , Herd S , Creed M , Ye Z , Yuan X , Brodsky RA , Kingsmore SF . Effectiveness of exome and genome sequencing guided by acuity of illness for diagnosis of neurodevelopmental disorders. Sci Transl Med 2014;6:265ra168–265.[doi:10.1126/scitranslmed.3010076](http://dx.doi.org/10.1126/scitranslmed.3010076) 
    
    [Abstract/FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTE6InNjaXRyYW5zbWVkIjtzOjU6InJlc2lkIjtzOjE0OiI2LzI2NS8yNjVyYTE2OCI7czo0OiJhdG9tIjtzOjI1OiIvam1lZGdlbmV0LzU2LzEyLzc4My5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

36.  Rump P , Jazayeri O , van Dijk-Bos KK , Johansson LF , van Essen AJ , Verheij JBGM , Veenstra-Knol HE , Redeker EJW , Mannens MMAM , Swertz MA , Alizadeh BZ , van Ravenswaaij-Arts CMA , Sinke RJ , Sikkema-Raddatz B . Whole-exome sequencing is a powerful approach for establishing the etiological diagnosis in patients with intellectual disability and microcephaly. BMC Med Genomics 2015;9.[doi:10.1186/s12920-016-0167-8](http://dx.doi.org/10.1186/s12920-016-0167-8) 
    
    

37.  Vissers LELM , Gilissen C , Veltman JA . Genetic studies in intellectual disability and related disorders. Nat Rev Genet 2016;17:9–18.[doi:10.1038/nrg3999](http://dx.doi.org/10.1038/nrg3999) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/nrg3999&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=26503795&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

38.  Meienberg J , Bruggmann R , Oexle K , Matyas G . Clinical sequencing: is WGS the better WES? Hum Genet 2016;135:359–62.[doi:10.1007/s00439-015-1631-9](http://dx.doi.org/10.1007/s00439-015-1631-9) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1007/s00439-015-1631-9&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=26742503&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

39.  Belkadi A , Bolze A , Itan Y , Cobat A , Vincent QB , Antipenko A , Shang L , Boisson B , Casanova J-L , Abel L . Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc Natl Acad Sci USA 2015;112:5473–8.[doi:10.1073/pnas.1418631112](http://dx.doi.org/10.1073/pnas.1418631112) 
    
    [Abstract/FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMToiMTEyLzE3LzU0NzMiO3M6NDoiYXRvbSI7czoyNToiL2ptZWRnZW5ldC81Ni8xMi83ODMuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

40.  Sanghvi RV , Buhay CJ , Powell BC , Tsai EA , Dorschner MO , Hong CS , Lebo MS , Sasson A , Hanna DS , McGee S , Bowling KM , Cooper GM , Gray DE , Lonigro RJ , Dunford A , Brennan CA , Cibulskis C , Walker K , Carneiro MO , Sailsbery J , Hindorff LA , Robinson DR , Santani A , Sarmady M , Rehm HL , Biesecker LG , Nickerson DA , Hutter CM , Garraway L , Muzny DM , Wagle N . Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers.. Genet Med 2017 (published Online First: 2017/11/17).
    
    

41.  Meynert AM , Ansari M , FitzPatrick DR , Taylor MS . Variant detection sensitivity and biases in whole genome and exome sequencing. BMC Bioinformatics 2014;15.[doi:10.1186/1471-2105-15-247](http://dx.doi.org/10.1186/1471-2105-15-247) 
    
    

42.  Lelieveld SH , Spielmann M , Mundlos S , Veltman JA , Gilissen C . Comparison of exome and genome sequencing technologies for the complete capture of protein-coding regions. Human Mutation 2015;36:815–22.[doi:10.1002/humu.22813](http://dx.doi.org/10.1002/humu.22813) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1002/humu.22813&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25973577&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

43.  Clark MM , Stark Z , Farnaes L , Tan TY , White SM , Dimmock D , Kingsmore SF . Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases. npj Genomic Med 2018;3.[doi:10.1038/s41525-018-0053-8](http://dx.doi.org/10.1038/s41525-018-0053-8) 
    
    

44.  Lionel AC , Costain G , Monfared N , Walker S , Reuter MS , Hosseini SM , Thiruvahindrapuram B , Merico D , Jobling R , Nalpathamkalam T , Pellecchia G , Sung WWL , Wang Z , Bikangaga P , Boelman C , Carter MT , Cordeiro D , Cytrynbaum C , Dell SD , Dhir P , Dowling JJ , Heon E , Hewson S , Hiraki L , Inbar-Feigenberg M , Klatt R , Kronick J , Laxer RM , Licht C , MacDonald H , Mercimek-Andrews S , Mendoza-Londono R , Piscione T , Schneider R , Schulze A , Silverman E , Siriwardena K , Snead OC , Sondheimer N , Sutherland J , Vincent A , Wasserman JD , Weksberg R , Shuman C , Carew C , Szego MJ , Hayeems RZ , Basran R , Stavropoulos DJ , Ray PN , Bowdin S , Meyn MS , Cohn RD , Scherer SW , Marshall CR . Improved diagnostic yield compared with targeted gene sequencing panels suggests a role for whole-genome sequencing as a first-tier genetic test. Genet Med 2017 (published Online First: 2017/08/05).
    
    

45.  Alfares A , Aloraini T , Subaie LA , Alissa A , Qudsi AA , Alahmad A , Mutairi FA , Alswaid A , Alothaim A , Eyaid W , Albalwi M , Alturki S , Alfadhel M . Whole-genome sequencing offers additional but limited clinical utility compared with reanalysis of whole-exome sequencing. Genet Med 2018 (published Online First: 2018/03/23).
    
    

46.  Ostrander BEP , Butterfield RJ , Pedersen BS , Farrell AJ , Layer RM , Ward A , Miller C , DiSera T , Filloux FM , Candee MS , Newcomb T , Bonkowsky JL , Marth GT , Quinlan AR . Whole-genome analysis for effective clinical diagnosis and gene discovery in early infantile epileptic encephalopathy. npj Genomic Med 2018;3.[doi:10.1038/s41525-018-0061-8](http://dx.doi.org/10.1038/s41525-018-0061-8) 
    
    

47.  Brewer MH , Chaudhry R , Qi J , Kidambi A , Drew AP , Menezes MP , Ryan MM , Farrar MA , Mowat D , Subramanian GM , Young HK , Zuchner S , Reddel SW , Nicholson GA , Kennerson ML . Whole genome sequencing identifies a 78 kb insertion from chromosome 8 as the cause of Charcot-Marie-Tooth neuropathy CMTX3. PLoS Genet 2016;12:e1006177.[doi:10.1371/journal.pgen.1006177](http://dx.doi.org/10.1371/journal.pgen.1006177) 
    
    

48.  Vaz-Drago R , Custódio N , Carmo-Fonseca M . Deep intronic mutations and human disease. Hum Genet 2017;136:1093–111.[doi:10.1007/s00439-017-1809-4](http://dx.doi.org/10.1007/s00439-017-1809-4) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1007/s00439-017–1809-4&link_type=DOI) 

49.  Andersson R , Gebhard C , Miguel-Escalada I , Hoof I , Bornholdt J , Boyd M , Chen Y , Zhao X , Schmidl C , Suzuki T , Ntini E , Arner E , Valen E , Li K , Schwarzfischer L , Glatz D , Raithel J , Lilje B , Rapin N , Bagger FO , Jørgensen M , Andersen PR , Bertin N , Rackham O , Burroughs AM , Baillie JK , Ishizu Y , Shimizu Y , Furuhata E , Maeda S , Negishi Y , Mungall CJ , Meehan TF , Lassmann T , Itoh M , Kawaji H , Kondo N , Kawai J , Lennartsson A , Daub CO , Heutink P , Hume DA , Jensen TH , Suzuki H , Hayashizaki Y , Müller F , Forrest ARR , Carninci P , Rehli M , Sandelin A . An atlas of active enhancers across human cell types and tissues. Nature 2014;507:455–61.[doi:10.1038/nature12787](http://dx.doi.org/10.1038/nature12787) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/nature12787&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=24670763&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000333402000032&link_type=ISI) 

50.  Maurano MT , Humbert R , Rynes E , Thurman RE , Haugen E , Wang H , Reynolds AP , Sandstrom R , Qu H , Brody J , Shafer A , Neri F , Lee K , Kutyavin T , Stehling-Sun S , Johnson AK , Canfield TK , Giste E , Diegel M , Bates D , Hansen RS , Neph S , Sabo PJ , Heimfeld S , Raubitschek A , Ziegler S , Cotsapas C , Sotoodehnia N , Glass I , Sunyaev SR , Kaul R , Stamatoyannopoulos JA . Systematic localization of common disease-associated variation in regulatory DNA. Science 2012;337:1190–5.[doi:10.1126/science.1222794](http://dx.doi.org/10.1126/science.1222794) 
    
    [Abstract/FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEzOiIzMzcvNjA5OS8xMTkwIjtzOjQ6ImF0b20iO3M6MjU6Ii9qbWVkZ2VuZXQvNTYvMTIvNzgzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

51.  Gambin T , Akdemir ZC , Yuan B , Gu S , Chiang T , Carvalho CMB , Shaw C , Jhangiani S , Boone PM , Eldomery MK , Karaca E , Bayram Y , Stray-Pedersen A , Muzny D , Charng WL , Bahrambeigi V , Belmont JW , Boerwinkle E , Beaudet AL , Gibbs RA , Lupski JR . Homozygous and hemizygous CNV detection from exome sequencing data in a Mendelian disease cohort. Nucleic Acids Res 2017;45:1633–48.
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1093/nar/gkw1237&link_type=DOI) 

52.  Dong Z , Wang H , Chen H , Jiang H , Yuan J , Yang Z , Wang W-J , Xu F , Guo X , Cao Y , Zhu Z , Geng C , Cheung WC , Kwok YK , Yang H , Leung TY , Morton CC , Cheung SW , Choy KW . Identification of balanced chromosomal rearrangements previously unknown among participants in the 1000 Genomes Project: implications for interpretation of structural variation in genomes and the future of clinical cytogenetics. Genet Med 2018;20:697–707.[doi:10.1038/gim.2017.170](http://dx.doi.org/10.1038/gim.2017.170) 
    
    

53.  Hochstenbach R , van Binsbergen E , Schuring-Blom H , Buijs A , Ploos van Amstel HK . A survey of undetected, clinically relevant chromosome abnormalities when replacing postnatal karyotyping by whole genome sequencing. European Journal of Medical Genetics 2018 (published Online First: 2018/09/25).[doi:10.1016/j.ejmg.2018.09.010](http://dx.doi.org/10.1016/j.ejmg.2018.09.010) 
    
    

54.  Dolzhenko E , van Vugt JJFA , Shaw RJ , Bekritsky MA , van Blitterswijk M , Narzisi G , Ajay SS , Rajan V , Lajoie BR , Johnson NH , Kingsbury Z , Humphray SJ , Schellevis RD , Brands WJ , Baker M , Rademakers R , Kooyman M , Tazelaar GHP , van Es MA , McLaughlin R , Sproviero W , Shatunov A , Jones A , Al Khleifat A , Pittman A , Morgan S , Hardiman O , Al-Chalabi A , Shaw C , Smith B , Neo EJ , Morrison K , Shaw PJ , Reeves C , Winterkorn L , Wexler NS , Housman DE , Ng CW , Li AL , Taft RJ , van den Berg LH , Bentley DR , Veldink JH , Eberle MA . Detection of long repeat expansions from PCR-free whole-genome sequence data. Genome Res. 2017;27:1895–903.[doi:10.1101/gr.225672.117](http://dx.doi.org/10.1101/gr.225672.117) 
    
    [Abstract/FREE Full Text](http://jmg.bmj.com/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NjoiZ2Vub21lIjtzOjU6InJlc2lkIjtzOjEwOiIyNy8xMS8xODk1IjtzOjQ6ImF0b20iO3M6MjU6Ii9qbWVkZ2VuZXQvNTYvMTIvNzgzLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

55.  Mostovoy Y , Levy-Sakin M , Lam J , Lam ET , Hastie AR , Marks P , Lee J , Chu C , Lin C , Džakula Željko , Cao H , Schlebusch SA , Giorda K , Schnall-Levin M , Wall JD , Kwok P-Y . A hybrid approach for de novo human genome sequence assembly and phasing. Nat Methods 2016;13:587–90.[doi:10.1038/nmeth.3865](http://dx.doi.org/10.1038/nmeth.3865) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/nmeth.3865&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=27159086&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

56.  Steininger A , Ebert G , Becker BV , Assaf C , Möbs M , Schmidt CA , Grabarczyk P , Jensen LR , Przybylski GK , Port M , Kuss AW , Ullmann R . Genome-wide analysis of interchromosomal interaction probabilities reveals chained translocations and overrepresentation of translocation breakpoints in genes in a cutaneous T-cell lymphoma cell line. Front. Oncol. 2018;8.[doi:10.3389/fonc.2018.00183](http://dx.doi.org/10.3389/fonc.2018.00183) 
    
    

57.  Calvo SE , Compton AG , Hershman SG , Lim SC , Lieber DS , Tucker EJ , Laskowski A , Garone C , Liu S , Jaffe DB , Christodoulou J , Fletcher JM , Bruno DL , Goldblatt J , Dimauro S , Thorburn DR , Mootha VK . Molecular diagnosis of infantile mitochondrial disease with targeted next-generation sequencing. Sci Transl Med 2012;4.[doi:10.1126/scitranslmed.3003310](http://dx.doi.org/10.1126/scitranslmed.3003310) 
    
    

58.  Theunissen TEJ , Nguyen M , Kamps R , Hendrickx AT , Sallevelt SCEH , Gottschalk RWH , Calis CM , Stassen APM , de Koning B , Mulder-Den Hartog ENM , Schoonderwoerd K , Fuchs SA , Hilhorst-Hofstee Y , de Visser M , Vanoevelen J , Szklarczyk R , Gerards M , de Coo IFM , Hellebrekers DMEI , Smeets HJM . Whole exome sequencing is the preferred strategy to identify the genetic defect in patients with a probable or possible mitochondrial cause. Front Genet 2018;9.[doi:10.3389/fgene.2018.00400](http://dx.doi.org/10.3389/fgene.2018.00400) 
    
    

59.  Abicht A , Scharf F , Kleinle S , Schon U , Holinski-Feder E , Horvath R , Benet-Pages A , Diebold I . Mitochondrial and nuclear disease panel (Mito-aND-Panel): combined sequencing of mitochondrial and nuclear DNA by a cost-effective and sensitive NGS-based method. Mol Genet Genomic Med 2018 (published Online First: 2018/11/09).
    
    

60. OMIM. OMIM gene map statistics, 2018. Available: [https://www.omim.org/statistics/geneMap](https://www.omim.org/statistics/geneMap) [Accessed November 2018].
    
    

61.  Willig LK , Petrikin JE , Smith LD , Saunders CJ , Thiffault I , Miller NA , Soden SE , Cakici JA , Herd SM , Twist G , Noll A , Creed M , Alba PM , Carpenter SL , Clements MA , Fischer RT , Hays JA , Kilbride H , McDonough RJ , Rosterman JL , Tsai SL , Zellmer L , Farrow EG , Kingsmore SF . Whole-genome sequencing for identification of mendelian disorders in critically ill infants: a retrospective analysis of diagnostic and clinical findings. The Lancet Respiratory Medicine 2015;3:377–87.[doi:10.1016/S2213-2600(15)00139-3](http://dx.doi.org/10.1016/S2213-2600(15)00139-3) 
    
    

62.  Saunders CJ , Miller NA , Soden SE , Dinwiddie DL , Noll A , Alnadi NA , Andraws N , Patterson ML , Krivohlavek LA , Fellis J , Humphray S , Saffrey P , Kingsbury Z , Weir JC , Betley J , Grocock RJ , Margulies EH , Farrow EG , Artman M , Safina NP , Petrikin JE , Hall KP , Kingsmore SF . Rapid whole-genome sequencing for genetic disease diagnosis in neonatal intensive care units. Science Translational Medicine 2012;4.[doi:10.1126/scitranslmed.3004041](http://dx.doi.org/10.1126/scitranslmed.3004041) 
    
    

63.  Miller NA , Farrow EG , Gibson M , Willig LK , Twist G , Yoo B , Marrs T , Corder S , Krivohlavek L , Walter A , Petrikin JE , Saunders CJ , Thiffault I , Soden SE , Smith LD , Dinwiddie DL , Herd S , Cakici JA , Catreux S , Ruehle M , Kingsmore SF . A 26-hour system of highly sensitive whole genome sequencing for emergency management of genetic diseases. Genome Med 2015;7.[doi:10.1186/s13073-015-0221-8](http://dx.doi.org/10.1186/s13073-015-0221-8) 
    
    

64.  Gilissen C , Hehir-Kwa JY , Thung DT , van de Vorst M , van Bon BWM , Willemsen MH , Kwint M , Janssen IM , Hoischen A , Schenck A , Leach R , Klein R , Tearle R , Bo T , Pfundt R , Yntema HG , de Vries BBA , Kleefstra T , Brunner HG , Vissers LELM , Veltman JA . Genome sequencing identifies major causes of severe intellectual disability. Nature 2014;511:344–7.[doi:10.1038/nature13394](http://dx.doi.org/10.1038/nature13394) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/nature13394&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=24896178&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000338992200035&link_type=ISI) 

65.  Stavropoulos DJ , Merico D , Jobling R , Bowdin S , Monfared N , Thiruvahindrapuram B , Nalpathamkalam T , Pellecchia G , Yuen RKC , Szego MJ , Hayeems RZ , Shaul RZ , Brudno M , Girdea M , Frey B , Alipanahi B , Ahmed S , Babul-Hirji R , Porras RB , Carter MT , Chad L , Chaudhry A , Chitayat D , Doust SJ , Cytrynbaum C , Dupuis L , Ejaz R , Fishman L , Guerin A , Hashemi B , Helal M , Hewson S , Inbar-Feigenberg M , Kannu P , Karp N , Kim RH , Kronick J , Liston E , MacDonald H , Mercimek-Mahmutoglu S , Mendoza-Londono R , Nasr E , Nimmo G , Parkinson N , Quercia N , Raiman J , Roifman M , Schulze A , Shugar A , Shuman C , Sinajon P , Siriwardena K , Weksberg R , Yoon G , Carew C , Erickson R , Leach RA , Klein R , Ray PN , Meyn MS , Scherer SW , Cohn RD , Marshall CR . Whole-genome sequencing expands diagnostic utility and improves clinical management in paediatric medicine. npj Genomic Med 2016;1.[doi:10.1038/npjgenmed.2015.12](http://dx.doi.org/10.1038/npjgenmed.2015.12) 
    
    

66.  Petrikin JE , Cakici JA , Clark MM , Willig LK , Sweeney NM , Farrow EG , Saunders CJ , Thiffault I , Miller NA , Zellmer L , Herd SM , Holmes AM , Batalov S , Veeraraghavan N , Smith LD , Dimmock DP , Leeder JS , Kingsmore SF . The NSIGHT1-randomized controlled trial: rapid whole-genome sequencing for accelerated etiologic diagnosis in critically ill infants. npj Genomic Med 2018;3.[doi:10.1038/s41525-018-0045-8](http://dx.doi.org/10.1038/s41525-018-0045-8) 
    
    

67.  Hiatt SM , Amaral MD , Bowling KM , Finnila CR , Thompson ML , Gray DE , Lawlor JMJ , Cochran JN , Bebin EM , Brothers KB , East KM , Kelley WV , Lamb NE , Levy SE , Lose EJ , Neu MB , Rich CA , Simmons S , Myers RM , Barsh GS , Cooper GM . Systematic reanalysis of genomic data improves quality of variant interpretation. Clin Genet 2018;94:174–8.[doi:10.1111/cge.13259](http://dx.doi.org/10.1111/cge.13259) 
    
    

68.  Grosse SD , Khoury MJ . What is the clinical utility of genetic testing? Genet Med 2006;8:448–50.[doi:10.1097/01.gim.0000227935.26763.c6](http://dx.doi.org/10.1097/01.gim.0000227935.26763.c6) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1097/01.gim.0000227935.26763.c6&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=16845278&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000239180300008&link_type=ISI) 

69.  Richer J , Daoud H , Geier P , Jarinova O , Carson N , Feberova J , Nadya BF , Unrau J , Bareke E , Khatchadourian K , Bulman DE , Majewski J , Boycott KM , Dyment DA . Resolution of refractory hypotension and anuria in a premature newborn with loss-of-function of ACE. Am. J. Med. Genet. 2015;167:1654–8.[doi:10.1002/ajmg.a.37067](http://dx.doi.org/10.1002/ajmg.a.37067) 
    
    

70.  Pisano T , Numis AL , Heavin SB , Weckhuysen S , Angriman M , Suls A , Podesta B , Thibert RL , Shapiro KA , Guerrini R , Scheffer IE , Marini C , Cilio MR . Early and effective treatment of KCNQ2 encephalopathy. Epilepsia 2015;56:685–91.[doi:10.1111/epi.12984](http://dx.doi.org/10.1111/epi.12984) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1111/epi.12984&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25880994&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

71.  Dilena R , Striano P , Traverso M , Viri M , Cristofori G , Tadini L , Barbieri S , Romeo A , Zara F . Dramatic effect of levetiracetam in early-onset epileptic encephalopathy due to STXBP1 mutation. Brain and Development 2016;38:128–31.[doi:10.1016/j.braindev.2015.07.002](http://dx.doi.org/10.1016/j.braindev.2015.07.002) 
    
    

72.  Kuperberg M , Lev D , Blumkin L , Zerem A , Ginsberg M , Linder I , Carmi N , Kivity S , Lerman-Sagie T , Leshinsky-Silver E . Utility of whole exome sequencing for genetic diagnosis of previously undiagnosed pediatric neurology patients. J Child Neurol 2016;31:1534–9.[doi:10.1177/0883073816664836](http://dx.doi.org/10.1177/0883073816664836) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1177/0883073816664836&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=27572814&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

73.  Farnaes L , Hildreth A , Sweeney NM , Clark MM , Chowdhury S , Nahas S , Cakici JA , Benson W , Kaplan RH , Kronick R , Bainbridge MN , Friedman J , Gold JJ , Ding Y , Veeraraghavan N , Dimmock D , Kingsmore SF . Rapid whole-genome sequencing decreases infant morbidity and cost of hospitalization. npj Genomic Med 2018;3.[doi:10.1038/s41525-018-0049-4](http://dx.doi.org/10.1038/s41525-018-0049-4) 
    
    

74.  Sabatini LM , Mathews C , Ptak D , Doshi S , Tynan K , Hegde MR , Burke TL , Bossler AD . Genomic sequencing procedure microcosting analysis and health economic cost-impact analysis: a report of the Association for Molecular Pathology. J Mol Diagn 2016;18:319–28.
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1016/j.jmoldx.2015.11.010&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=27080370&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

75.  Tan TY , Dillon OJ , Stark Z , Schofield D , Alam K , Shrestha R , Chong B , Phelan D , Brett GR , Creed E , Jarmolowicz A , Yap P , Walsh M , Downie L , Amor DJ , Savarirayan R , McGillivray G , Yeung A , Peters H , Robertson SJ , Robinson AJ , Macciocca I , Sadedin S , Bell K , Oshlack A , Georgeson P , Thorne N , Gaff C , White SM , Impact D . Diagnostic impact and cost-effectiveness of whole-exome sequencing for ambulant children with suspected monogenic conditions. JAMA Pediatr 2017;171:855–62.[doi:10.1001/jamapediatrics.2017.1755](http://dx.doi.org/10.1001/jamapediatrics.2017.1755) 
    
    

76.  Vissers LELM , van Nimwegen KJM , Schieving JH , Kamsteeg E-J , Kleefstra T , Yntema HG , Pfundt R , van der Wilt GJ , Krabbenborg L , Brunner HG , van der Burg S , Grutters J , Veltman JA , Willemsen MAAP . A clinical utility study of exome sequencing versus conventional genetic testing in pediatric neurology. Genet Med 2017;19:1055–63.[doi:10.1038/gim.2017.1](http://dx.doi.org/10.1038/gim.2017.1) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=28333917&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

77.  Tsiplova K , Zur RM , Marshall CR , Stavropoulos DJ , Pereira SL , Merico D , Young EJ , Sung WWL , Scherer SW , Ungar WJ . A microcosting and cost-consequence analysis of clinical genomic testing strategies in autism spectrum disorder. Genet Med 2017.
    
    

78.  Webber EM , Hunter JE , Biesecker LG , Buchanan AH , Clarke EV , Currey E , Dagan-Rosenfeld O , Lee K , Lindor NM , Martin CL , Milosavljevic A , Mittendorf KF , Muessig KR , O'Daniel JM , Patel RY , Ramos EM , Rego S , Slavotinek AM , Sobriera NLM , Weaver MA , Williams MS , Evans JP , Goddard KAB . Evidence-based assessments of clinical actionability in the context of secondary findings: updates from ClinGen's Actionability Working Group. Human Mutation 2018;39:1677–85.[doi:10.1002/humu.23631](http://dx.doi.org/10.1002/humu.23631) 
    
    

79.  Green RC , Berg JS , Grody WW , Kalia SS , Korf BR , Martin CL , McGuire AL , Nussbaum RL , O’Daniel JM , Ormond KE , Rehm HL , Watson MS , Williams MS , Biesecker LG . ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med 2013;15:565–74.[doi:10.1038/gim.2013.73](http://dx.doi.org/10.1038/gim.2013.73) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/gim.2013.73&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=23788249&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

80.  Bick D , Fraser PC , Gutzeit MF , Harris JM , Hambuch TM , Helbling DC , Jacob HJ , Kersten JN , Leuthner SR , May T , North PE , Prisco SZ , Schuler BA , Shimoyama M , Strong KA , Van Why SK , Veith R , Verbsky J , Weborg AM , Wilk BM , Willoughby RE , Worthey EA , Dimmock DP . Successful application of whole genome sequencing in a medical genetics clinic. J Pediatr Genet 2017;6:61–76.
    
    

81.  Friedman JM , Bombard Y , Cornel MC , Fernandez CV , Junker AK , Plon SE , Stark Z , Knoppers BM . Genome-wide sequencing in acutely ill infants: genomic medicine's critical application? Genet Med 2018 (published Online First: 2018/06/14).
    
    

82.  Sweeny K , Ghane A , Legg AM , Huynh HP , Andrews SE . Predictors of genetic testing decisions: a systematic review and critique of the literature. J Genet Counsel 2014;23:263–88.[doi:10.1007/s10897-014-9712-9](http://dx.doi.org/10.1007/s10897-014-9712-9) 
    
    

83.  Tagliafico E , Bernardis I , Grasso M , D’Apice MR , Lapucci C , Botta A , Giachino DF , Marinelli M , Primignani P , Russo S , Sani I , Seia M , Fini S , Rimessi P , Tenedini E , Ravani A , Genuardi M , Ferlini A , on behalf of the Molecular Genetics Working Group of the Italian Society of Human Genetics, SIGU . Workload measurement for molecular genetics laboratory: a survey study. Plos One 2018;13:e0206855.[doi:10.1371/journal.pone.0206855](http://dx.doi.org/10.1371/journal.pone.0206855) 
    
    

84.  Deisseroth CA , Birgmeier J , Bodle EE , Kohler JN , Matalon DR , Nazarenko Y , Genetti CA , Brownstein CA , Schmitz-Abe K , Schoch K , Cope H , Signer R , Martinez-Agosto JA , Shashi V , Beggs AH , Wheeler MT , Bernstein JA , Bejerano G . ClinPhen extracts and prioritizes patient phenotypes directly from medical records to expedite genetic disease diagnosis. Genet Med 2018;377.[doi:10.1038/s41436-018-0381-1](http://dx.doi.org/10.1038/s41436-018-0381-1) 
    
    

85.  Boeldt DL , Cheung C , Ariniello L , Darst BF , Topol S , Schork NJ , Philis-Tsimikas A , Torkamani A , Fortmann AL , Bloss CS . Patient perspectives on whole-genome sequencing for undiagnosed diseases. Personalized Medicine 2017;14:17–25.[doi:10.2217/pme-2016-0050](http://dx.doi.org/10.2217/pme-2016-0050) 
    
    

86.  Petrikin JE , Willig LK , Smith LD , Kingsmore SF . Rapid whole genome sequencing and precision neonatology. Semin Perinatol 2015;39:623–31.[doi:10.1053/j.semperi.2015.09.009](http://dx.doi.org/10.1053/j.semperi.2015.09.009) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1053/j.semperi.2015.09.009&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=26521050&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

87.  Wright CF , FitzPatrick DR , Firth HV . Paediatric genomics: diagnosing rare disease in children. Nat Rev Genet 2018;19:253–68.[doi:10.1038/nrg.2017.116](http://dx.doi.org/10.1038/nrg.2017.116) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/nrg.2017.116&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=29398702&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

88.  Huang AY , Zhang Z , Ye AY , Dou Y , Yan L , Yang X , Zhang Y , Wei L . MosaicHunter: accurate detection of postzygotic single-nucleotide mosaicism through next-generation sequencing of unpaired, trio, and paired samples. Nucleic Acids Res 2017;45:e76.[doi:10.1093/nar/gkx024](http://dx.doi.org/10.1093/nar/gkx024) 
    
    

89.  Pizzo L , Jensen M , Polyak A , Rosenfeld JA , Mannik K , Krishnan A , McCready E , Pichon O , Le Caignec C , Van Dijck A , Pope K , Voorhoeve E , Yoon J , Stankiewicz P , Cheung SW , Pazuchanics D , Huber E , Kumar V , Kember RL , Mari F , Curro A , Castiglia L , Galesi O , Avola E , Mattina T , Fichera M , Mandara L , Vincent M , Nizon M , Mercier S , Beneteau C , Blesson S , Martin-Coignard D , Mosca-Boidron AL , Caberg JH , Bucan M , Zeesman S , Nowaczyk MJM , Lefebvre M , Faivre L , Callier P , Skinner C , Keren B , Perrine C , Prontera P , Marle N , Renieri A , Reymond A , Kooy RF , Isidor B , Schwartz C , Romano C , Sistermans E , Amor DJ , Andrieux J , Girirajan S . Rare variants in the genetic background modulate cognitive and developmental phenotypes in individuals carrying disease-associated variants. Genet Med 2018 (published Online First: 2018/09/08).
    
    

90.  Moyer AM , Caraballo PJ . The challenges of implementing pharmacogenomic testing in the clinic. Expert Review of Pharmacoeconomics & Outcomes Research 2017;17:567–77.[doi:10.1080/14737167.2017.1385395](http://dx.doi.org/10.1080/14737167.2017.1385395) 
    
    

91.  Gross A , Ajay SS , Rajan V , Brown C , Bluske K , Burns N , Chawla A , Coffey AJ , Malhotra A , Scocchia A , Thorpe E , Dzidic N , Hovanes K , Sahoo T , Dolzhenko E , Lajoie B , Khouzam A , Chowdhury S , Belmont J , Roller E , Ivakhno S , Tanner S , McEachern J , Hambuch T , Eberle M , Hagelstrom RT , Bentley DR , Perry DL , Taft RJ . Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease. bioRxiv 2018.
    
    

92.  Khera AV , Chaffin M , Aragam KG , Haas ME , Roselli C , Choi SH , Natarajan P , Lander ES , Lubitz SA , Ellinor PT , Kathiresan S . Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet 2018;50:1219–24.[doi:10.1038/s41588-018-0183-z](http://dx.doi.org/10.1038/s41588-018-0183-z) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1038/s41588-018–0183-z&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=30104762&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

93.  Wilson MR , Naccache SN , Samayoa E , Biagtan M , Bashir H , Yu G , Salamat SM , Somasekar S , Federman S , Miller S , Sokolic R , Garabedian E , Candotti F , Buckley RH , Reed KD , Meyer TL , Seroogy CM , Galloway R , Henderson SL , Gern JE , DeRisi JL , Chiu CY . Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med 2014;370:2408–17.[doi:10.1056/NEJMoa1401268](http://dx.doi.org/10.1056/NEJMoa1401268) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1056/NEJMoa1401268&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=24896819&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 
    
    [Web of Science](http://jmg.bmj.com/lookup/external-ref?access_num=000337353000009&link_type=ISI) 

94.  Flower R , Roulis E , Hyland C . Whole-genome sequencing algorithm for blood-group typing. Lancet Haematol 2018;5:e233–4.[doi:10.1016/S2352-3026(18)30064-4](http://dx.doi.org/10.1016/S2352-3026(18)30064-4) 
    
    

95.  Hayashi S , Yamaguchi R , Mizuno S , Komura M , Miyano S , Nakagawa H , Imoto S . ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data. BMC Genomics 2018;19.[doi:10.1186/s12864-018-5169-9](http://dx.doi.org/10.1186/s12864-018-5169-9) 
    
    

96.  Popejoy AB , Ritter DI , Crooks K , Currey E , Fullerton SM , Hindorff LA , Koenig B , Ramos EM , Sorokin EP , Wand H , Wright MW , Zou J , Gignoux CR , Bonham VL , Plon SE , Bustamante CD , Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group (ADWG) . The clinical imperative for inclusivity: race, ethnicity, and ancestry (REA) in genomics. Hum Mutat 2018;39:1713–20.[doi:10.1002/humu.23644](http://dx.doi.org/10.1002/humu.23644) 
    
    

97.  Lee H , Deignan JL , Dorrani N , Strom SP , Kantarci S , Quintero-Rivera F , Das K , Toy T , Harry B , Yourshaw M , Fox M , Fogel BL , Martinez-Agosto JA , Wong DA , Chang VY , Shieh PB , Palmer CGS , Dipple KM , Grody WW , Vilain E , Nelson SF . Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA 2014;312:1880–7.[doi:10.1001/jama.2014.14604](http://dx.doi.org/10.1001/jama.2014.14604) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1001/jama.2014.14604&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25326637&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

98.  Yang Y , Muzny DM , Xia F , Niu Z , Person R , Ding Y , Ward P , Braxton A , Wang M , Buhay C , Veeraraghavan N , Hawes A , Chiang T , Leduc M , Beuten J , Zhang J , He W , Scull J , Willis A , Landsverk M , Craigen WJ , Bekheirnia MR , Stray-Pedersen A , Liu P , Wen S , Alcaraz W , Cui H , Walkiewicz M , Reid J , Bainbridge M , Patel A , Boerwinkle E , Beaudet AL , Lupski JR , Plon SE , Gibbs RA , Eng CM . Molecular findings among patients referred for clinical whole-exome sequencing. JAMA 2014;312:1870–9.[doi:10.1001/jama.2014.14601](http://dx.doi.org/10.1001/jama.2014.14601) 
    
    [CrossRef](http://jmg.bmj.com/lookup/external-ref?access_num=10.1001/jama.2014.14601&link_type=DOI) 
    
    [PubMed](http://jmg.bmj.com/lookup/external-ref?access_num=25326635&link_type=MED&atom=%2Fjmedgenet%2F56%2F12%2F783.atom) 

99.  Wright CF , Fitzgerald TW , Jones WD , Clayton S , McRae JF , van Kogelenberg M , King DA , Ambridge K , Barrett DM , Bayzetinova T , Bevan AP , Bragin E , Chatzimichali EA , Gribble S , Jones P , Krishnappa N , Mason LE , Miller R , Morley KI , Parthiban V , Prigmore E , Rajan D , Sifrim A , Swaminathan GJ , Tivey AR , Middleton A , Parker M , Carter NP , Barrett JC , Hurles ME , FitzPatrick DR , Firth HV . Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. The Lancet 2015;385:1305–14.[doi:10.1016/S0140-6736(14)61705-0](http://dx.doi.org/10.1016/S0140-6736(14)61705-0) 
    
    

100. van Diemen CC , Kerstjens-Frederikse WS , Bergman KA , de Koning TJ , Sikkema-Raddatz B , van der Velde JK , Abbott KM , Herkert JC , Löhner K , Rump P , Meems-Veldhuis MT , Neerincx PBT , Jongbloed JDH , van Ravenswaaij-Arts CM , Swertz MA , Sinke RJ , van Langen IM , Wijmenga C . Rapid targeted genomics in critically ill newborns. Pediatrics 2017;140.[doi:10.1542/peds.2016-2854](http://dx.doi.org/10.1542/peds.2016-2854)