Genomic rearrangements are a common cause of human congenital abnormalities. However, their origin and consequences are poorly understood. We performed molecular analysis of two patients with congenital disease who carried de novo genomic rearrangements. We found that the rearrangements in both patients hit genes that are recurrently rearranged in cancer (ETV1, FOXP1, and microRNA cluster C19MC) and drive formation of fusion genes similar to those described in cancer. Subsequent analysis of a large set of 552 de novo germline genomic rearrangements underlying congenital disorders revealed enrichment for genes rearranged in cancer and overlap with somatic cancer breakpoints. Breakpoints of common (inherited) germline structural variations also overlap with cancer breakpoints but are depleted for cancer genes. We propose that the same genomic positions are prone to genomic rearrangements in germline and soma but that timing and context of breakage determines whether developmental defects or cancer are promoted.

With recent rapid advances in genomic technologies, precise delineation of structural chromosome rearrangements at the nucleotide level is becoming increasingly feasible. In this era of "next-generation cytogenetics" (i.e., an integration of traditional cytogenetic techniques and next-generation sequencing), a consensus nomenclature is essential for accurate communication and data sharing. Currently, nomenclature for describing the sequencing data of these aberrations is lacking. Herein, we present a system called Next-Gen Cytogenetic Nomenclature, which is concordant with the International System for Human Cytogenetic Nomenclature (2013). This system starts with the alignment of rearrangement sequences by BLAT or BLAST (alignment tools) and arrives at a concise and detailed description of chromosomal changes. To facilitate usage and implementation of this nomenclature, we are developing a program designated BLA(S)T Output Sequence Tool of Nomenclature (BOSToN), a demonstrative version of which is accessible online. A standardized characterization of structural chromosomal rearrangements is essential both for research analyses and for application in the clinical setting.

In addition to HLA genetic incompatibility, non-HLA difference between donor and recipients of transplantation leading to allograft rejection are now becoming evident. We aimed to create a unique genome-wide platform to facilitate genomic research studies in transplant-related studies. We designed a genome-wide genotyping tool based on the most recent human genomic reference datasets, and included customization for known and potentially relevant metabolic and pharmacological loci relevant to transplantation.

Persons with neurodevelopmental disorders or autism spectrum disorder (ASD) often harbor chromosomal microdeletions, yet the individual genetic contributors within these regions have not been systematically evaluated. We established a consortium of clinical diagnostic and research laboratories to accumulate a large cohort with genetic alterations of chromosomal region 2q23.1 and acquired 65 subjects with microdeletion or translocation. We sequenced translocation breakpoints; aligned microdeletions to determine the critical region; assessed effects on mRNA expression; and examined medical records, photos, and clinical evaluations. We identified a single gene, methyl-CpG-binding domain 5 (MBD5), as the only locus that defined the critical region. Partial or complete deletion of MBD5 was associated with haploinsufficiency of mRNA expression, intellectual disability, epilepsy, and autistic features. Fourteen alterations, including partial deletions of noncoding regions not typically captured or considered pathogenic by current diagnostic screening, disrupted MBD5 alone. Expression profiles and clinical characteristics were largely indistinguishable between MBD5-specific alteration and deletion of the entire 2q23.1 interval. No copy-number alterations of MBD5 were observed in 7878 controls, suggesting MBD5 alterations are highly penetrant. We surveyed MBD5 coding variations among 747 ASD subjects compared to 2043 non-ASD subjects analyzed by whole-exome sequencing and detected an association with a highly conserved methyl-CpG-binding domain missense variant, p.79Gly>Glu (c.236G>A) (p = 0.012). These results suggest that genetic alterations of MBD5 cause features of 2q23.1 microdeletion syndrome and that this epigenetic regulator significantly contributes to ASD risk, warranting further consideration in research and clinical diagnostic screening and highlighting the importance of chromatin remodeling in the etiology of these complex disorders.

Schwannomatosis has been linked to germline mutations in the SMARCB1 and LZTR1 genes, and is frequently associated with pain.In a cohort study, we assessed the mutation status of 37 patients with clinically diagnosed schwannomatosis and compared to clinical data, whole body MRI (WBMRI), visual analog pain scale, and Short Form 36 (SF-36) bodily pain subscale.We identified a germline mutation in LZTR1 in 5 patients (13.5%) and SMARCB1 in 15 patients (40.5%), but found no germline mutation in 17 patients (45.9%). Peripheral schwannomas were detected in 3 LZTR1-mutant (60%) and 10 SMARCB1-mutant subjects (66.7%). Among those with peripheral tumors, the median tumor number was 4 in the LZTR1 group (median total body tumor volume 30 cc) and 10 in the SMARCB1 group (median volume 85cc), (P=.2915 for tumor number and P = .2289 for volume). mutation was associated with an increased prevalence of spinal schwannomas (100% vs 41%, P = .0197). The median pain score was 3.9/10 in the LZTR1 group and 0.5/10 in the SMARCB1 group (P = .0414), and SF-36 pain-associated quality of life was significantly worse in the LZTR1 group (P = .0106). Pain scores correlated with total body tumor volume (rho = 0.32471, P = .0499), but not with number of tumors (rho = 0.23065, P = .1696).We found no significant difference in quantitative tumor burden between mutational groups, but spinal schwannomas were more common in LZTR1-mutant patients. Pain was significantly higher in LZTR1-mutant than in SMARCB1-mutant patients, though spinal tumor location did not significantly correlate with pain. This suggests a possible genetic association with schwannomatosis-associated pain.

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC (sites VCF available via FTP at ftp.broadinstitute.org/pub/ExAC_release/release0.3/) to pinpoint genetic variation that contributes to variable disease predisposition across populations.

The 6%-9% risk of an untoward outcome previously established by Warburton for prenatally detected de novo balanced chromosomal rearrangements (BCRs) does not account for long-term morbidity. We performed long-term follow-up (mean 17 years) of a registry-based nationwide cohort of 41 individuals carrying a prenatally detected de novo BCR with normal first trimester screening/ultrasound scan. We observed a significantly higher frequency of neurodevelopmental and/or neuropsychiatric disorders than in a matched control group (19.5% versus 8.3%, p = 0.04), which was increased to 26.8% upon clinical follow-up. Chromosomal microarray of 32 carriers revealed no pathogenic imbalances, illustrating a low prognostic value when fetal ultrasound scan is normal. In contrast, mate-pair sequencing revealed disrupted genes (ARID1B, NPAS3, CELF4), regulatory domains of known developmental genes (ZEB2, HOXC), and complex BCRs associated with adverse outcomes. Seven unmappable autosomal-autosomal BCRs with breakpoints involving pericentromeric/heterochromatic regions may represent a low-risk group. We performed independent phenotype-aware and blinded interpretation, which accurately predicted benign outcomes (specificity = 100%) but demonstrated relatively low sensitivity for prediction of the clinical outcome in affected carriers (sensitivity = 45%-55%). This sensitivity emphasizes the challenges associated with prenatal risk prediction for long-term morbidity in the absence of phenotypic data given the still immature annotation of the morbidity genome and poorly understood long-range regulatory mechanisms. In conclusion, we upwardly revise the previous estimates of Warburton to a morbidity risk of 27% and recommend sequencing of the chromosomal breakpoints as the first-tier diagnostic test in pregnancies with a de novo BCR.

Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.

Despite improvements in genomics technology, the detection of structural variants (SVs) from short-read sequencing still poses challenges, particularly for complex variation. Here we analyse the genomes of two patients with congenital abnormalities using the MinION nanopore sequencer and a novel computational pipeline-NanoSV. We demonstrate that nanopore long reads are superior to short reads with regard to detection of de novo chromothripsis rearrangements. The long reads also enable efficient phasing of genetic variations, which we leveraged to determine the parental origin of all de novo chromothripsis breakpoints and to resolve the structure of these complex rearrangements. Additionally, genome-wide surveillance of inherited SVs reveals novel variants, missed in short-read data sets, a large proportion of which are retrotransposon insertions. We provide a first exploration of patient genome sequencing with a nanopore sequencer and demonstrate the value of long-read sequencing in mapping and phasing of SVs for both clinical and research applications.

Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous 'knockout' humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development.

Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson's disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns5-8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9, 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work10, confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.

Schizophrenia (SCZ) is a debilitating psychiatric disorder with a large genetic contribution; however, its neurodevelopmental substrates remain largely unknown. Modeling pathogenic processes in SCZ using human induced pluripotent stem cell-derived neurons (iNs) has emerged as a promising strategy. Copy number variants confer high genetic risk for SCZ, with duplication of the 16p11.2 locus increasing the risk 14.5-fold.

DNA sample contamination is a major issue in clinical and research applications of whole genome and exome sequencing. Even modest levels of contamination can substantially affect the overall quality of variant calls and lead to widespread genotyping errors. Currently, popular tools for estimating the contamination level use short-read data (BAM/CRAM files), which are expensive to store and manipulate and often not retained or shared widely. We propose a new metric to estimate DNA sample contamination from variant-level whole genome and exome sequence data, CHARR, Contamination from Homozygous Alternate Reference Reads, which leverages the infiltration of reference reads within homozygous alternate variant calls. CHARR uses a small proportion of variant-level genotype information and thus can be computed from single-sample gVCFs or callsets in VCF or BCF formats, as well as efficiently stored variant calls in Hail VDS format. Our results demonstrate that CHARR accurately recapitulates results from existing tools with substantially reduced costs, improving the accuracy and efficiency of downstream analyses of ultra-large whole genome and exome sequencing datasets.

Mitochondrial DNA (mtDNA) is a maternally inherited, high-copy-number genome required for oxidative phosphorylation1. Heteroplasmy refers to the presence of a mixture of mtDNA alleles in an individual and has been associated with disease and ageing. Mechanisms underlying common variation in human heteroplasmy, and the influence of the nuclear genome on this variation, remain insufficiently explored. Here we quantify mtDNA copy number (mtCN) and heteroplasmy using blood-derived whole-genome sequences from 274,832 individuals and perform genome-wide association studies to identify associated nuclear loci. Following blood cell composition correction, we find that mtCN declines linearly with age and is associated with variants at 92 nuclear loci. We observe that nearly everyone harbours heteroplasmic mtDNA variants obeying two principles: (1) heteroplasmic single nucleotide variants tend to arise somatically and accumulate sharply after the age of 70 years, whereas (2) heteroplasmic indels are maternally inherited as mixtures with relative levels associated with 42 nuclear loci involved in mtDNA replication, maintenance and novel pathways. These loci may act by conferring a replicative advantage to certain mtDNA alleles. As an illustrative example, we identify a length variant carried by more than 50% of humans at position chrM:302 within a G-quadruplex previously proposed to mediate mtDNA transcription/replication switching2,3. We find that this variant exerts cis-acting genetic control over mtDNA abundance and is itself associated in-trans with nuclear loci encoding machinery for this regulatory switch. Our study suggests that common variation in the nuclear genome can shape variation in mtCN and heteroplasmy dynamics across the human population.

No abstract available

The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5-10 hours to process a full exome sequence and $30 and 3-8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2.

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.

Structural variation (SV) is a significant component of the genetic etiology of both neurodevelopmental and psychiatric disorders; however, routine guidelines for clinical genetic screening have been established only in the former category. Genome-wide chromosomal microarray (CMA) can detect genomic imbalances such as copy-number variants (CNVs), but balanced chromosomal abnormalities (BCAs) still require karyotyping for clinical detection. Moreover, submicroscopic BCAs and subarray threshold CNVs are intractable, or cryptic, to both CMA and karyotyping. Here, we performed whole-genome sequencing using large-insert jumping libraries to delineate both cytogenetically visible and cryptic SVs in a single test among 30 clinically referred youth representing a range of severe neuropsychiatric conditions. We detected 96 SVs per person on average that passed filtering criteria above our highest-confidence resolution (6,305 bp) and an additional 111 SVs per genome below this resolution. These SVs rearranged 3.8 Mb of genomic sequence and resulted in 42 putative loss-of-function (LoF) or gain-of-function mutations per person. We estimate that 80% of the LoF variants were cryptic to clinical CMA. We found myriad complex and cryptic rearrangements, including a "paired" duplication (360 kb, 169 kb) that flanks a 5.25 Mb inversion that appears in 7 additional cases from clinical CNV data among 47,562 individuals. Following convergent genomic profiling of these independent clinical CNV data, we interpreted three SVs to be of potential clinical significance. These data indicate that sequence-based delineation of the full SV mutational spectrum warrants exploration in youth referred for neuropsychiatric evaluation and clinical diagnostic SV screening more broadly.

There is great variation in drug-response phenotypes, and a "one size fits all" paradigm for drug delivery is flawed. Pharmacogenomics is the study of how human genetic information impacts drug response, and it aims to improve efficacy and reduced side effects. In this article, we provide an overview of pharmacogenetics, including pharmacokinetics (PK), pharmacodynamics (PD), gene and pathway interactions, and off-target effects. We describe methods for discovering genetic factors in drug response, including genome-wide association studies (GWAS), expression analysis, and other methods such as chemoinformatics and natural language processing (NLP). We cover the practical applications of pharmacogenomics both in the pharmaceutical industry and in a clinical setting. In drug discovery, pharmacogenomics can be used to aid lead identification, anticipate adverse events, and assist in drug repurposing efforts. Moreover, pharmacogenomic discoveries show promise as important elements of physician decision support. Finally, we consider the ethical, regulatory, and reimbursement challenges that remain for the clinical implementation of pharmacogenomics.

As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences.