Development and Validation of Clinical Whole-Exome and Whole-Genome Sequencing for Detection of Germline Variants in Inherited Disease

Context.-With the decrease in the cost of sequencing, the clinical testing paradigm has shifted from single gene to gene panel and now whole-exome and whole-genome sequencing. Clinical laboratories are rapidly implementing next-generation sequencing-based whole-exome and whole-genome sequencing. Because a large number of targets are covered by whole-exome and whole-genome sequencing, it is critical that a laboratory perform appropriate validation studies, develop a quality assurance and quality control program, and participate in proficiency testing. Objective.-To provide recommendations for wholeexome and whole-genome sequencing assay design, validation, and implementation for the detection of germline variants associated in inherited disorders. Data Sources.-An example of trio sequencing, filtration and annotation of variants, and phenotypic consideration to arrive at clinical diagnosis is discussed. Conclusions.-It is critical that clinical laboratories planning to implement whole-exome and whole-genome sequencing design and validate the assay to specifications and ensure adequate performance prior to implementation. Test design specifications, including variant filtering and annotation, phenotypic consideration, guidance on consenting options, and reporting of incidental findings, are provided. These are important steps a laboratory must take to validate and implement whole-exome and whole-genome sequencing in a clinical setting for germline variants in inherited disorders

Whole-genome sequencing

The costs of whole-genome sequencing have rapidly decreased, and it is being increasingly deployed in large-scale clinical research projects and introduced into routine clinical care. This will lead to rapid diagnoses for patients with genetic disease but also introduces uncertainty because of the diversity of human genomes and the potential difficulties in annotating new genetic variants for individual patients and families. Here we outline the steps in organising whole-genome sequencing for patients in the neurology clinic and emphasise that close liaison between the clinician and the laboratory is essential

Whole-genome sequencing shows that patient-to-patient transmission rarely accounts for acquisition of Staphylococcus aureus in an intensive care unit

BACKGROUND  Strategies to prevent Staphylococcus aureus infection in hospitals focus on patient-to-patient transmission. We used whole-genome sequencing to investigate the role of colonized patients as the source of new S. aureus acquisitions, and the reliability of identifying patient-to-patient transmission using the conventional approach of spa typing and overlapping patient stay. METHODS Over 14 months, all unselected patients admitted to an adult intensive care unit (ICU) were serially screened for S. aureus. All available isolates (n = 275) were spa typed and underwent whole-genome sequencing to investigate their relatedness at high resolution. RESULTS Staphylococcus aureus was carried by 185 of 1109 patients sampled within 24 hours of ICU admission (16.7%); 59 (5.3%) patients carried methicillin-resistant S. aureus (MRSA). Forty-four S. aureus (22 MRSA) acquisitions while on ICU were detected. Isolates were available for genetic analysis from 37 acquisitions. Whole-genome sequencing indicated that 7 of these 37 (18.9%) were transmissions from other colonized patients. Conventional methods (spa typing combined with overlapping patient stay) falsely identified 3 patient-to-patient transmissions (all MRSA) and failed to detect 2 acquisitions and 4 transmissions (2 MRSA). CONCLUSIONS Only a minority of S. aureus acquisitions can be explained by patient-to-patient transmission. Whole-genome sequencing provides the resolution to disprove transmission events indicated by conventional methods and also to reveal otherwise unsuspected transmission events. Whole-genome sequencing should replace conventional methods for detection of nosocomial S. aureus transmission

Comparison of variant calling methods for whole genome sequencing data in dairy cattle

Accurate identification of SNPs from next-generation sequencing data is crucial for high-quality downstream analysis. Whole genome sequence data of 65 key ancestors of genotyped Swiss dairy populations were available for investigation (24 billion reads, 96.8% mapped to UMD31, 12x coverage). Four publically available variant calling programmes were assessed and different levels of pre-calling handling for each method were tested and compared. SNP concordance was examined with Illumina’s BovineHD Genotyping BeadChip®. Depending on variant calling software used, between 16,894,054 and 22,048,382 SNP were identified (multi-sample calling). A total of 14,644,310 SNP were identified by all four variant callers (multi-sample calling). InDel counts ranged from 1,997,791 to 2,857,754; 1,708,649 InDels were identified by all four variant callers. A minimum of pre-calling data handling resulted in the highest non-reference sensitivity and the lowest non-reference discrepancy rates

Whole genome sequencing of Plasmodium falciparum from dried blood spots using selective whole genome amplification

BACKGROUND: Translating genomic technologies into healthcare applications for the malaria parasite Plasmodium falciparum has been limited by the technical and logistical difficulties of obtaining high quality clinical samples from the field. Sampling by dried blood spot (DBS) finger-pricks can be performed safely and efficiently with minimal resource and storage requirements compared with venous blood (VB). Here, the use of selective whole genome amplification (sWGA) to sequence the P. falciparum genome from clinical DBS samples was evaluated, and the results compared with current methods that use leucodepleted VB. METHODS: Parasite DNA with high (>95%) human DNA contamination was selectively amplified by Phi29 polymerase using short oligonucleotide probes of 8-12 mers as primers. These primers were selected on the basis of their differential frequency of binding the desired (P. falciparum DNA) and contaminating (human) genomes. RESULTS: Using sWGA method, clinical samples from 156 malaria patients, including 120 paired samples for head-to-head comparison of DBS and leucodepleted VB were sequenced. Greater than 18-fold enrichment of P. falciparum DNA was achieved from DBS extracts. The parasitaemia threshold to achieve >5× coverage for 50% of the genome was 0.03% (40 parasites per 200 white blood cells). Over 99% SNP concordance between VB and DBS samples was achieved after excluding missing calls. CONCLUSION: The sWGA methods described here provide a reliable and scalable way of generating P. falciparum genome sequence data from DBS samples. The current data indicate that it will be possible to get good quality sequence on most if not all drug resistance loci from the majority of symptomatic malaria patients. This technique overcomes a major limiting factor in P. falciparum genome sequencing from field samples, and paves the way for large-scale epidemiological applications

Direct Whole-Genome Sequencing of Cutaneous Strains of Haemophilus ducreyi.

Haemophilus ducreyi, which causes chancroid, has emerged as a cause of pediatric skin disease. Isolation of H. ducreyi in low-income settings is challenging, limiting phylogenetic investigation. Next-generation sequencing demonstrates that cutaneous strains arise from class I and II H. ducreyi clades and that class II may represent a distinct subspecies

Linear-Time Superbubble Identification Algorithm for Genome Assembly

DNA sequencing is the process of determining the exact order of the nucleotide bases of an individual's genome in order to catalogue sequence variation and understand its biological implications. Whole-genome sequencing techniques produce masses of data in the form of short sequences known as reads. Assembling these reads into a whole genome constitutes a major algorithmic challenge. Most assembly algorithms utilize de Bruijn graphs constructed from reads for this purpose. A critical step of these algorithms is to detect typical motif structures in the graph caused by sequencing errors and genome repeats, and filter them out; one such complex subgraph class is a so-called superbubble. In this paper, we propose an O(n+m)-time algorithm to detect all superbubbles in a directed acyclic graph with n nodes and m (directed) edges, improving the best-known O(m log m)-time algorithm by Sung et al