An integrated map of structural variation in 2,504 human genomes

© 2015 Macmillan Publishers Limited. All rights reserved. Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association

Device Thrombogenicity Emulation: A Novel Method for Optimizing Mechanical Circulatory Support Device Thromboresistance

Mechanical circulatory support (MCS) devices provide both short and long term hemodynamic support for advanced heart failure patients. Unfortunately these devices remain plagued by thromboembolic complications associated with chronic platelet activation – mandating complex, lifelong anticoagulation therapy. To address the unmet need for enhancing the thromboresistance of these devices to extend their long term use, we developed a universal predictive methodology entitled Device Thrombogenicity Emulation (DTE) that facilitates optimizing the thrombogenic performance of any MCS device – ideally to a level that may obviate the need for mandatory anticoagulation

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk

Disparity between Maternal and Paternal Contributions to Inherited Risk for Autism

The genetic basis of autism is known to consist of de novo and inherited loss of function mutations in haploinsufficient genes. It is thought that inherited risk primarily derives from mothers, believed to be due to an increased tolerance for risk alleles. However, the distinct contributions of each parent to inherited risk for autism has not been explored in depth. We investigated paternal and maternal contributions to autism by analyzing the transmission of private deletions in coding and cis-regulatory (CRE-SVs) regions of functionally constrained genes in whole genomes of 10,015 individuals (2650 families). We then extended our transmission distortion analysis to encompass of loss of function single nucleotide variants (SNVs) and insertion/deletion (INDELs), as well as private potentially pathogenic missense mutations. Our goal is to untangle distinct modes of inheritance for autism risk, hypothesizing that fathers and mothers carry distinct risk contributions. We report that mothers and fathers over-transmit loss of function variants within functionally constrained coding regions. However, fathers but not mothers tended to over-transmit damaging CRE-SVs and missense variants to affected offspring. When we test the segregation of loss of function variants stratified by sex of the offspring, we find that most of the genetic risk to sons is derived from the father, which is not consistent with the previous female protective effect model. Our work demonstrates that inherited damaging variants comprise a significant component of missing heritability for autism with fathers contributing a substantial amount of risk

Disparity between Maternal and Paternal Contributions to Inherited Risk for Autism

The genetic basis of autism is known to consist of de novo and inherited loss of function mutations in haploinsufficient genes. It is thought that inherited risk primarily derives from mothers, believed to be due to an increased tolerance for risk alleles. However, the distinct contributions of each parent to inherited risk for autism has not been explored in depth. We investigated paternal and maternal contributions to autism by analyzing the transmission of private deletions in coding and cis-regulatory (CRE-SVs) regions of functionally constrained genes in whole genomes of 10,015 individuals (2650 families). We then extended our transmission distortion analysis to encompass of loss of function single nucleotide variants (SNVs) and insertion/deletion (INDELs), as well as private potentially pathogenic missense mutations. Our goal is to untangle distinct modes of inheritance for autism risk, hypothesizing that fathers and mothers carry distinct risk contributions. We report that mothers and fathers over-transmit loss of function variants within functionally constrained coding regions. However, fathers but not mothers tended to over-transmit damaging CRE-SVs and missense variants to affected offspring. When we test the segregation of loss of function variants stratified by sex of the offspring, we find that most of the genetic risk to sons is derived from the father, which is not consistent with the previous female protective effect model. Our work demonstrates that inherited damaging variants comprise a significant component of missing heritability for autism with fathers contributing a substantial amount of risk

Pathogenicity and functional impact of non-frameshifting insertion/deletion variation in the human genome.

Differentiation between phenotypically neutral and disease-causing genetic variation remains an open and relevant problem. Among different types of variation, non-frameshifting insertions and deletions (indels) represent an understudied group with widespread phenotypic consequences. To address this challenge, we present a machine learning method, MutPred-Indel, that predicts pathogenicity and identifies types of functional residues impacted by non-frameshifting insertion/deletion variation. The model shows good predictive performance as well as the ability to identify impacted structural and functional residues including secondary structure, intrinsic disorder, metal and macromolecular binding, post-translational modifications, allosteric sites, and catalytic residues. We identify structural and functional mechanisms impacted preferentially by germline variation from the Human Gene Mutation Database, recurrent somatic variation from COSMIC in the context of different cancers, as well as de novo variants from families with autism spectrum disorder. Further, the distributions of pathogenicity prediction scores generated by MutPred-Indel are shown to differentiate highly recurrent from non-recurrent somatic variation. Collectively, we present a framework to facilitate the interrogation of both pathogenicity and the functional effects of non-frameshifting insertion/deletion variants. The MutPred-Indel webserver is available at http://mutpred.mutdb.org/