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Germline pathogenic variants in DNMT3A were recently described in patients with overgrowth, obesity, behavioral, and learning difficulties ( D NMT3A O vergrowth S yndrome/DOS). Somatic mutations in the DNMT3A gene are also the most common cause of clonal hematopoiesis, and can initiate acute myeloid leukemia (AML). Using whole genome bisulfite sequencing, we studied DNA methylation in peripheral blood cells of 11 DOS patients and found a focal, canonical hypomethylation phenotype, which is most severe with the dominant negative DNMT3A R882H mutation. A germline mouse model expressing the homologous Dnmt3a R878H mutation phenocopies most aspects of the human DOS syndrome, including the methylation phenotype and an increased incidence of spontaneous hematopoietic malignancies, suggesting that all aspects of this syndrome are caused by this mutation. Germline mutations in the DNMT3A gene can cause an overgrowth syndrome associated with behavioural and hematopoietic phenotypes. Here the authors describe a mouse model of this syndrome that recapitulates many of these features, including conserved alterations in DNA methylation in the blood cells of both species.

In lung adenocarcinoma, canonical EML4-ALK inversion results in a fusion protein with a constitutively active ALK kinase domain. Evidence of ALK rearrangement occurs in a minority (2–7%) of lung adenocarcinoma, and only ~60% of these patients will respond to targeted ALK inhibition by drugs such as crizotinib and ceritinib. Clinically, targeted anti-ALK therapy is often initiated based on evidence of an ALK genomic rearrangement detected by fluorescence in situ hybridization (FISH) of interphase cells in formalin-fixed, paraffin-embedded tissue sections. At the genomic level, however, ALK rearrangements are heterogeneous, with multiple potential breakpoints in EML4, and alternate fusion partners. Using next-generation sequencing of DNA and RNA together with ALK immunohistochemistry, we comprehensively characterized genomic breakpoints in 33 FISH-positive lung adenocarcinomas. Of these 33 cases, 29 (88%) had detectable DNA level ALK rearrangements involving EML4, KIF5B, or non-canonical partners including ASXL2, ATP6V1B1, PRKAR1A, and SPDYA. A subset of 12 cases had material available for RNA-Seq. Of these, eight of eight (100%) cases with DNA rearrangements showed ALK fusion transcripts from RNA-Seq; three of four cases (75%) without detectable DNA rearrangements were similarly negative by RNA-Seq, and one case was positive by RNA-Seq but negative by DNA next-generation sequencing. By immunohistochemistry, 17 of 19 (89%) tested cases were clearly positive for ALK protein expression; the remaining cases had no detectable DNA level rearrangement or had a non-canonical rearrangement not predicted to form a fusion protein. Survival analysis of patients treated with targeted ALK inhibitors demonstrates a significant difference in mean survival between patients with next-generation sequencing confirmed EML4-ALK rearrangements, and those without (20.6 months vs 5.4 months, P<0.01). Together, these data demonstrate abundant genomic heterogeneity among ALK-rearranged lung adenocarcinoma, which may account for differences in treatment response with targeted ALK inhibitors.

Leukemias are currently subclassified based on the presence of recurrent cytogenetic abnormalities and gene mutations. These molecular findings are the basis for risk-adapted therapy; however, such data are generally obtained by disparate methods in the clinical laboratory, and often rely on low-resolution techniques such as fluorescent in situ hybridization. Using targeted next generation sequencing, we demonstrate that the full spectrum of prognostically significant gene mutations including translocations, single nucleotide variants (SNVs), and insertions/deletions (indels) can be identified simultaneously in multiplexed sequence data. As proof of concept, we performed hybrid capture using a panel of 20 genes implicated in leukemia prognosis (covering a total of 1 Mbp) from five leukemia cell lines including K562, NB4, OCI-AML3, kasumi-1, and MV4–11. Captured DNA was then sequenced in multiplex on an Illumina HiSeq. Using an analysis pipeline based on freely available software we correctly identified DNA-level translocations in three of the three cell lines where translocations were covered by our capture probes. Furthermore, we found all published gene mutations in commonly tested genes including NPM1, FLT3, and KIT. The same methodology was applied to DNA extracted from the bone marrow of a patient with acute myeloid leukemia, and identified a t(9;11) translocation with single base accuracy as well other gene mutations. These results indicate that targeted next generation sequencing can be successfully applied in the clinical laboratory to identify a full spectrum of DNA mutations ranging from SNVs and indels to translocations. Such methods have the potential to both greatly streamline and improve the accuracy of DNA-based diagnostics.

Merkel cell carcinoma is a highly aggressive cutaneous neuroendocrine tumor that has been associated with Merkel cell polyomavirus in up to 80% of cases. Merkel cell polyomavirus is believed to influence pathogenesis, at least in part, through expression of the large T antigen, which includes a retinoblastoma protein-binding domain. However, there appears to be significant clinical and morphological overlap between polyomavirus-positive and polyomavirus-negative Merkel cell carcinoma cases. Although much of the recent focus of Merkel cell carcinoma pathogenesis has been on polyomavirus, the pathogenesis of polyomavirus-negative cases is still poorly understood. We hypothesized that there are underlying human somatic mutations that unify Merkel cell carcinoma pathogenesis across polyomavirus status, and to investigate we performed whole exome sequencing on five polyomavirus-positive cases and three polyomavirus-negative cases. We found that there were no significant differences in the overall number of single-nucleotide variations, copy number variations, insertion/deletions, and chromosomal rearrangements when comparing polyomavirus-positive to polyomavirus-negative cases. However, we did find that the retinoblastoma pathway genes harbored a high number of mutations in Merkel cell carcinoma. Furthermore, the retinoblastoma gene (RB1) was found to have nonsense truncating protein mutations in all three polyomavirus-negative cases; no such mutations were found in the polyomavirus-positive cases. In all eight cases, the retinoblastoma pathway dysregulation was confirmed by immunohistochemistry. Although polyomavirus-positive Merkel cell carcinoma is believed to undergo retinoblastoma dysregulation through viral large T antigen expression, our findings demonstrate that somatic mutations in polyomavirus-negative Merkel cell carcinoma lead to retinoblastoma dysregulation through an alternative pathway. This novel finding suggests that the retinoblastoma pathway dysregulation leads to an overlapping Merkel cell carcinoma phenotype and that oncogenesis occurs through either a polyomavirus-dependent (viral large T antigen expression) or polyomavirus-independent (host somatic mutation) mechanism.

Context.—Most current proficiency testing challenges for next-generation sequencing assays are methods-based proficiency testing surveys that use DNA from characterized reference samples to test both the wet-bench and bioinformatics/dry-bench aspects of the tests. Methods-based proficiency testing surveys are limited by the number and types of mutations that either are naturally present or can be introduced into a single DNA sample. Objective.—To address these limitations by exploring a model of in silico proficiency testing in which sequence data from a single well-characterized specimen are manipulated electronically. Design.—DNA from the College of American Pathologists reference genome was enriched using the Illumina TruSeq and Life Technologies AmpliSeq panels and sequenced on the MiSeq and Ion Torrent platforms, respectively. The resulting data were mutagenized in silico and 26 variants, including single-nucleotide variants, deletions, and dinucleotide substitutions, were added at variant allele fractions (VAFs) from 10% to 50%. Participating clinical laboratories downloaded these files and analyzed them using their clinical bioinformatics pipelines. Results.—Laboratories using the AmpliSeq/Ion Torrent and/or the TruSeq/MiSeq participated in the 2 surveys. On average, laboratories identified 24.6 of 26 variants (95%) overall and 21.4 of 22 variants (97%) with VAFs greater than 15%. No false-positive calls were reported. The most frequently missed variants were single-nucleotide variants with VAFs less than 15%. Across both challenges, reported VAF concordance was excellent, with less than 1% median absolute difference between the simulated VAF and mean reported VAF. Conclusions.—The results indicate that in silico proficiency testing is a feasible approach for methods-based proficiency testing, and demonstrate that the sensitivity and specificity of current next-generation sequencing bioinformatics across clinical laboratories are high.

Objectives: To evaluate the extent of human-to-human specimen contamination in clinical next-generation sequencing (NGS) data. Methods: Using haplotype analysis to detect specimen admixture, with orthogonal validation by short tandem repeat analysis, we determined the rate of clinically significant (>5%) DNA contamination in clinical NGS data from 296 consecutive cases. Haplotype analysis was performed using read haplotypes at common, closely spaced single-nucleotide polymorphisms in low linkage disequilibrium in the population, which were present in regions targeted by the clinical assay. Percent admixture was estimated based on frequencies of the read haplotypes at loci that showed evidence for contamination. Results: We identified nine (3%) cases with at least 5% DNA admixture. Three cases were bone marrow transplant patients known to be chimeric. Six admixed cases were incidents of contamination, and the rate of contamination was strongly correlated with DNA yield from the tissue specimen. Conclusions: Human-human specimen contamination occurs in clinical NGS testing. Tools for detecting contamination in NGS sequence data should be integrated into clinical bioinformatics pipelines, especially as laboratories trend toward using smaller amounts of input DNA and reporting lower frequency variants. This study provides one estimate of the rate of clinically significant human-human specimen contamination in clinical NGS testing.

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power. Exome-wide sequencing studies of populations in Finland identified 26 deleterious alleles associated with 64 quantitative traits that are clinically relevant to cardiovascular and metabolic diseases.

Background Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). Results We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10 −8 ), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 × 10 −8 ), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 × 10 −21 ) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition. Conclusion These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.

Background The Long Life Family Study (LLFS) is an international study to identify the genetic components of various healthy aging phenotypes. We hypothesized that pedigree-specific rare variants at longevity-associated genes could have a similar functional impact on healthy phenotypes. Methods We performed custom hybridization capture sequencing to identify the functional variants in 464 candidate genes for longevity or the major diseases of aging in 615 pedigrees (4,953 individuals) from the LLFS, using a multiplexed, custom hybridization capture. Variants were analyzed individually or as a group across an entire gene for association to aging phenotypes using family based tests. Results We found significant associations to three genes and nine single variants. Most notably, we found a novel variant significantly associated with exceptional survival in the 3’ UTR OBFC1 in 13 individuals from six pedigrees. OBFC1 (chromosome 10) is involved in telomere maintenance, and falls within a linkage peak recently reported from an analysis of telomere length in LLFS families. Two different algorithms for single gene associations identified three genes with an enrichment of variation that was significantly associated with three phenotypes ( GSK3B with the Healthy Aging Index, NOTCH1 with diastolic blood pressure and TP53 with serum HDL). Conclusions Sequencing analysis of family-based associations for age-related phenotypes can identify rare or novel variants.

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph’s ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome. Constructing genome graphs directly from genome assemblies overcomes single-reference bias.