Although copy number variants (CNVs) are important in genomic medicine, CNVs have not been systematically assessed for many complex traits. Several large rare CNVs increase risk for schizophrenia (SCZ) and autism and often demonstrate pleiotropic effects; however, their frequencies in the general population and other complex traits are unknown. Genotyping large numbers of samples is essential for progress. Large cohorts from many different diseases are being genotyped using exome-focused arrays designed to detect uncommon or rare protein-altering sequence variation. Although these arrays were not designed for CNV detection, the hybridization intensity data generated in each experiment could, in principle, be used for gene-focused CNV analysis. Our goal was to evaluate the extent to which CNVs can be detected using data from one particular exome array (the Illumina Human Exome Bead Chip). We genotyped 9, 100 Swedish subjects (3, 962 cases with SCZ and 5, 138 controls) using both standard GWAS arrays and exome arrays. In comparison to CNVs detected using GWAS arrays, we observed high sensitivity and specificity for detecting genic CNVs ≥400 kb including known pathogentic CNVs along with replicating the literature finding that cases with SCZ had greater enrichment for genic CNVs. Our data confirm the association of SCZ with 16p11.2 duplications and 22q11.2 deletions and suggest a novel association with deletions at 11q12.2. Our results suggest the utility of exome focused arrays in surveying large genic CNVs in very large samples; and thereby open the door for new opportunities such as conducting well-powered CNV assessment and comparisons between different diseases. The use of a single platform also minimizes potential confounding factors that could impact accurate detection.
schizophrenia; copy number variation; structural variation; genotyping; Illumina; exome array
mRNA synthesis, processing, and destruction involve a complex series of molecular steps that are incompletely understood. Because the RNA intermediates in each of these steps have finite lifetimes, extensive mechanistic and dynamical information is encoded in total cellular RNA. Here we report the development of SnapShot-Seq, a set of computational methods that allow the determination of in vivo rates of pre-mRNA synthesis, splicing, intron degradation, and mRNA decay from a single RNA-Seq snapshot of total cellular RNA. SnapShot-Seq can detect in vivo changes in the rates of specific steps of splicing, and it provides genome-wide estimates of pre-mRNA synthesis rates comparable to those obtained via labeling of newly synthesized RNA. We used SnapShot-Seq to investigate the origins of the intrinsic bimodality of metazoan gene expression levels, and our results suggest that this bimodality is partly due to spillover of transcriptional activation from highly expressed genes to their poorly expressed neighbors. SnapShot-Seq dramatically expands the information obtainable from a standard RNA-Seq experiment.
De novo mutation plays an important role in Autism Spectrum Disorders (ASDs). Notably, pathogenic copy number variants (CNVs) are characterized by high mutation rates. We hypothesize that hypermutability is a property of ASD genes, and may also include nucleotide-substitution hotspots. We investigated global patterns of germline mutation by whole genome sequencing of monozygotic twins concordant for ASD and their parents. Mutation rates varied widely throughout the genome (by 100-fold) and could be explained by intrinsic characteristics of DNA sequence and chromatin structure. Dense clusters of mutations within individual genomes were attributable to compound mutation or gene conversion. Hypermutability was a characteristic of genes involved in ASD and other diseases. In addition, genes impacted by mutations in this study were associated with ASD in independent exome-sequencing datasets. Our findings suggest that regional hypermutation is a significant factor shaping patterns of genetic variation and disease risk in humans.
Large and rare copy number variants (CNVs) at several loci have been shown to increase risk for schizophrenia. Aiming to discover novel susceptibility CNV loci, we analyzed 6882 cases and 11 255 controls genotyped on Illumina arrays, most of which have not been used for this purpose before. We identified genes enriched for rare exonic CNVs among cases, and then attempted to replicate the findings in additional 14 568 cases and 15 274 controls. In a combined analysis of all samples, 12 distinct loci were enriched among cases with nominal levels of significance (P < 0.05); however, none would survive correction for multiple testing. These loci include recurrent deletions at 16p12.1, a locus previously associated with neurodevelopmental disorders (P = 0.0084 in the discovery sample and P = 0.023 in the replication sample). Other plausible candidates include non-recurrent deletions at the glutamate transporter gene SLC1A1, a CNV locus recently suggested to be involved in schizophrenia through linkage analysis, and duplications at 1p36.33 and CGNL1. A burden analysis of large (>500 kb), rare CNVs showed a 1.2% excess in cases after excluding known schizophrenia-associated loci, suggesting that additional susceptibility loci exist. However, even larger samples are required for their discovery.
Summary: zCall is a variant caller specifically designed for calling rare single-nucleotide polymorphisms from array-based technology. This caller is implemented as a post-processing step after a default calling algorithm has been applied. The algorithm uses the intensity profile of the common allele homozygote cluster to define the location of the other two genotype clusters. We demonstrate improved detection of rare alleles when applying zCall to samples that have both Illumina Infinium HumanExome BeadChip and exome sequencing data available.
Supplementary data are available at Bioinformatics online.
Tens of millions of base pairs of euchromatic human genome sequence, including many protein-coding genes, have no known location in the human genome. We describe an approach for localizing the human genome's missing pieces by utilizing the patterns of genome sequence variation created by population admixture. We mapped the locations of 70 scaffolds spanning four million base pairs of the human genome's unplaced euchromatic sequence, including more than a dozen protein-coding genes, and identified eight large novel inter-chromosomal segmental duplications. We find that most of these sequences are hidden in the genome's heterochromatin, particularly its pericentromeric regions. Many cryptic, pericentromeric genes are expressed in RNA and have been maintained intact for millions of years while their expression patterns diverged from those of paralogous genes elsewhere in the genome. We describe how knowledge of the locations of these sequences can inform disease association and genome biology studies.
Red blood cell, white blood cell, and platelet measures, including their count, sub-type and volume, are important diagnostic and prognostic clinical parameters for several human diseases. To identify novel loci associated with hematological traits, and compare the architecture of these phenotypes between ethnic groups, the CARe Project genotyped 49,094 single nucleotide polymorphisms (SNPs) that capture variation in ~2,100 candidate genes in DNA of 23,439 Caucasians and 7,112 African Americans from five population-based cohorts. We found strong novel associations between erythrocyte phenotypes and the glucose-6 phosphate dehydrogenase (G6PD) A-allele in African Americans (rs1050828, P < 2.0 × 10−13, T-allele associated with lower red blood cell count, hemoglobin, and hematocrit, and higher mean corpuscular volume), and between platelet count and a SNP at the tropomyosin-4 (TPM4) locus (rs8109288, P = 3.0 × 10−7 in Caucasians; P = 3.0 × 10−7 in African Americans, T-allele associated with lower platelet count). We strongly replicated many genetic associations to blood cell phenotypes previously established in Caucasians. A common variant of the α-globin (HBA2-HBA1) locus was associated with red blood cell traits in African Americans, but not in Caucasians (rs1211375, P < 7 × 10−8, A-allele associated with lower hemoglobin, mean corpuscular hemoglobin, and mean corpuscular volume). Our results show similarities but also differences in the genetic regulation of hematological traits in European- and African-derived populations, and highlight the role of natural selection in shaping these differences.
Hirschsprung disease (HSCR) is a congenital disorder characterized by aganglionosis of the distal intestine. To assess the contribution of copy number variants (CNVs) to HSCR, we analysed the data generated from our previous genome-wide association study on HSCR patients, whereby we identified NRG1 as a new HSCR susceptibility locus. Analysis of 129 Chinese patients and 331 ethnically matched controls showed that HSCR patients have a greater burden of rare CNVs (p = 1.50×10−5), particularly for those encompassing genes (p = 5.00×10−6). Our study identified 246 rare-genic CNVs exclusive to patients. Among those, we detected a NRG3 deletion (p = 1.64×10−3). Subsequent follow-up (96 additional patients and 220 controls) on NRG3 revealed 9 deletions (combined p = 3.36×10−5) and 2 de novo duplications among patients and two deletions among controls. Importantly, NRG3 is a paralog of NRG1. Stratification of patients by presence/absence of HSCR–associated syndromes showed that while syndromic–HSCR patients carried significantly longer CNVs than the non-syndromic or controls (p = 1.50×10−5), non-syndromic patients were enriched in CNV number when compared to controls (p = 4.00×10−6) or the syndromic counterpart. Our results suggest a role for NRG3 in HSCR etiology and provide insights into the relative contribution of structural variants in both syndromic and non-syndromic HSCR. This would be the first genome-wide catalog of copy number variants identified in HSCR.
Copy number variations (CNVs) are significant genetic risk factors in disease pathogenesis and represent an important portion of missing heritability for some human diseases, making their discovery essential for the identification of genes and risk factors for a wide range of diseases, including Hirschsprung disease (HSCR, congenital colon aganglionosis). Since the discovery of the major HSCR gene, RET, a number of rare mutations have been reported in RET and other genes involved in the development of the enteric nervous system. However, these mutations contribute to only a small proportion of the disease susceptibility. Taking advantage of the recent technical and methodological advances, we have examined the contribution of CNVs to the disease. We have found that HSCR patients are enriched with CNVs encompassing genes. In particular, we found that deletions of NRG3, a paralog of the previously identified HSCR–susceptibility gene NRG1, were associated with the HSCR phenotype.
Crohn disease is a complex, multigenic, chronic inflammatory bowel disease of uncertain etiology. Recent advances in genetics, including high-throughput single-nucleotide polymorphism typing platforms and deep sequencing technologies have begun to shed light upon disease predisposition and pathogenesis. Autophagy is emerging as a key player in both innate and adaptive immunity, as well as tissue homeostasis and development in the gut. Here we describe our recent studies into the Crohn disease-associated Immunity-Related GTPase family, M (IRGM) gene and our discovery of a large risk-conferring upstream deletion. We discuss the effects of this deletion upon expression levels of IRGM alleles and how tissue-specific expression might be affected by the promoter polymorphism. In addition, we comment upon the potential roles of IRGM in autophagy of intracellular pathogens, and the challenges ahead for further elucidating IRGM function.
Crohn disease; inflammation; infection; bacteria; host-pathogen interaction; innate immunity
Family studies of individual tissues have shown that gene expression traits are genetically heritable. Here, we investigate cis and trans components of heritability both within and across tissues by applying variance-components methods to 722 Icelanders from family cohorts, using identity-by-descent (IBD) estimates from long-range phased genome-wide SNP data and gene expression measurements for ∼19,000 genes in blood and adipose tissue. We estimate the proportion of gene expression heritability attributable to cis regulation as 37% in blood and 24% in adipose tissue. Our results indicate that the correlation in gene expression measurements across these tissues is primarily due to heritability at cis loci, whereas there is little sharing of trans regulation across tissues. One implication of this finding is that heritability in tissues composed of heterogeneous cell types is expected to be more dominated by cis regulation than in tissues composed of more homogeneous cell types, consistent with our blood versus adipose results as well as results of previous studies in lymphoblastoid cell lines. Finally, we obtained similar estimates of the cis components of heritability using IBD between unrelated individuals, indicating that transgenerational epigenetic inheritance does not contribute substantially to the “missing heritability” of gene expression in these tissue types.
An important goal in biology is to understand how genotype affects gene expression. Because gene expression varies across tissues, the relationship between genotype and gene expression may be tissue-specific. In this study, we used heritability approaches to study the regulation of gene expression in two tissue types, blood and adipose tissue, as well as the regulation of gene expression that is shared across these tissues. Heritability can be partitioned into cis and trans effects by assessing identity-by-descent (IBD) at the genomic location close to the expressed gene or genome-wide, respectively, and applying variance-components methods to partition the heritability of each gene. We estimated the proportion of gene expression heritability explained by cis regulation as 37% in blood and 24% in adipose tissue. Notably, the heritability shared across tissue types was primarily due to cis regulation. Thus, the relative contribution of cis versus trans regulation is expected to increase with the number of cell types present in the tissue being assayed, just as observed in our study and in a comparison to previous work on lymphoblastoid cell lines (LCL). We specifically ruled out a substantial contribution of transgenerational epigenetic inheritance to heritability of gene expression in these cohorts by repeating our heritability analyses using segments shared IBD in distantly related Icelanders.
Preterm birth is the major cause of neonatal death and serious morbidity. Most preterm births are due to spontaneous onset of labor without a known cause or effective prevention. Both maternal and fetal genomes influence the predisposition to spontaneous preterm birth (SPTB), but the susceptibility loci remain to be defined. We utilized a combination of unique population structures, family-based linkage analysis, and subsequent case-control association to identify a susceptibility haplotype for SPTB. Clinically well-characterized SPTB families from northern Finland, a subisolate founded by a relatively small founder population that has subsequently experienced a number of bottlenecks, were selected for the initial discovery sample. Genome-wide linkage analysis using a high-density single-nucleotide polymorphism (SNP) array in seven large northern Finnish non-consanginous families identified a locus on 15q26.3 (HLOD 4.68). This region contains the IGF1R gene, which encodes the type 1 insulin-like growth factor receptor IGF-1R. Haplotype segregation analysis revealed that a 55 kb 12-SNP core segment within the IGF1R gene was shared identical-by-state (IBS) in five families. A follow-up case-control study in an independent sample representing the more general Finnish population showed an association of a 6-SNP IGF1R haplotype with SPTB in the fetuses, providing further evidence for IGF1R as a SPTB predisposition gene (frequency in cases versus controls 0.11 versus 0.05, P = 0.001, odds ratio 2.3). This study demonstrates the identification of a predisposing, low-frequency haplotype in a multifactorial trait using a well-characterized population and a combination of family and case-control designs. Our findings support the identification of the novel susceptibility gene IGF1R for predisposition by the fetal genome to being born preterm.
Preterm birth is the major cause of infant deaths and life-long neurologic and cardiopulmonary morbidity. More than 10% of births in the United States occur prematurely, and the rate is increasing without known effective prevention. Previous premature birth increases the risk 3-fold in subsequent pregnancies. We report here, for the first time to our knowledge, a genome-wide study on susceptibility to spontaneous preterm birth in singleton pregnancies. To detect novel regions of the genome associated with preterm birth, we performed linkage analysis on seven carefully selected large families with recurrent spontaneous premature births. When we studied the fetuses, evidence was found for linkage of a region on chromosome 15 with spontaneous preterm birth, with the highest linkage signals occurring within a single gene, IGF1R. Evidence of the involvement of this gene in the etiology of preterm birth was further strengthened by subsequent haplotype segregation analysis and case-control analysis of an independent patient population. The IGF1R gene encodes insulin-like growth factor receptor 1 (IGF-1R), an important protein that potentially regulates signaling cascades involved in the onset of labor. Our analyses are unique in providing evidence that fetal IGF1R influences the risk of spontaneous preterm labor, leading to preterm birth.
Investigators have linked rare copy number variation (CNVs) to neuropsychiatric diseases, such as schizophrenia. One hypothesis is that CNV events cause disease by affecting genes with specific brain functions. Under these circumstances, we expect that CNV events in cases should impact brain-function genes more frequently than those events in controls. Previous publications have applied “pathway” analyses to genes within neuropsychiatric case CNVs to show enrichment for brain-functions. While such analyses have been suggestive, they often have not rigorously compared the rates of CNVs impacting genes with brain function in cases to controls, and therefore do not address important confounders such as the large size of brain genes and overall differences in rates and sizes of CNVs. To demonstrate the potential impact of confounders, we genotyped rare CNV events in 2,415 unaffected controls with Affymetrix 6.0; we then applied standard pathway analyses using four sets of brain-function genes and observed an apparently highly significant enrichment for each set. The enrichment is simply driven by the large size of brain-function genes. Instead, we propose a case-control statistical test, cnv-enrichment-test, to compare the rate of CNVs impacting specific gene sets in cases versus controls. With simulations, we demonstrate that cnv-enrichment-test is robust to case-control differences in CNV size, CNV rate, and systematic differences in gene size. Finally, we apply cnv-enrichment-test to rare CNV events published by the International Schizophrenia Consortium (ISC). This approach reveals nominal evidence of case-association in neuronal-activity and the learning gene sets, but not the other two examined gene sets. The neuronal-activity genes have been associated in a separate set of schizophrenia cases and controls; however, testing in independent samples is necessary to definitively confirm this association. Our method is implemented in the PLINK software package.
Specific rare deletion and duplication events in the genome have now been shown to be associated with neuropsychiatric diseases such as 16p11.2 to autism and 22q11.21 to schizophrenia. However, controversy remains as to whether rare events impacting certain pathways as a group increase the risk of disease, and if so, what those pathways are. Other studies have used standard gene-set enrichment approaches to demonstrate that events discovered in cases contain more genes in neuro-developmental pathways than would be expected by chance. However, these analyses do not explicitly compare the relative enrichment in cases to any enrichment that may also be present in controls. Therefore, they can be confounded by the large size of brain genes or by larger size or frequency of CNVs in cases. Here we propose a case-control statistical test to assess whether a key pathway is differentially impacted by CNVs in cases compared to controls. Our approach is robust to skewed gene sizes and case-control differences in CNV rate and size.
Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Tetralogy of Fallot (TOF), the most common severe congenital heart malformation, occurs sporadically, without other anomaly, and from unknown cause in 70% of cases. A genome-wide survey of 114 TOF patients and their unaffected parents identified 11 de novo copy number variants (CNVs) that were absent or extremely rare (<0.1%) in 2,265 controls. A second, independent TOF cohort (n = 398) was then examined for additional CNVs at these loci. In 1% (5/512, p = 0.0002, OR = 22.3) of non-syndromic sporadic TOF cases we identified CNVs at chromosome 1q21.1. Recurrent CNVs were also identified at 3p25.1, 7p21.3 and 22q11.2. CNVs in a single TOF case occurred at six loci, two that encode known (NOTCH1, JAG1) disease genes. Our data predicts that at least 10% (4.5–15.5, 95% CI) of sporadic, non-syndromic TOF reflects de novo CNVs and implicates mutations within these loci as etiologic in other cases of TOF.
Transplantation and pregnancy, in which two diploid genomes reside in one body, can each lead to diseases in which immune cells from one individual target antigens encoded in the other’s genome. One such disease, graft-versus-host disease (GVHD) after hematopoetic stem cell transplantation (HSCT, or bone marrow transplant), is common even after transplants between HLA-identical siblings, indicating that cryptic histocompatibility loci exist outside the HLA locus. The immune system of an individual whose genome is homozygous for a gene deletion can recognize epitopes encoded by that gene as alloantigens. Analyzing common gene deletions in three HSCT cohorts (1,345 HLA-identical sibling donor-recipient pairs), we found that risk of acute GVHD was greater (OR = 2.5 [95%CI, 1.4–4.6]) when donor and recipient were mismatched for homozygous deletion of UGT2B17, a gene expressed in GVHD-affected tissues and giving rise to multiple histocompatibility antigens. Human genome structural variation merits investigation as a potential mechanism in diseases of alloimmunity.
Accurate and complete measurement of single nucleotide (SNP) and copy number (CNV) variants, both common and rare, will be required to understand the role of genetic variation in disease. We present Birdsuite, a four-stage analytical framework instantiated in software for deriving integrated and mutually consistent copy number and SNP genotypes. The method sequentially assigns copy number across regions of common copy number polymorphisms (CNPs), calls genotypes of SNPs, identifies rare CNVs via a hidden Markov model (HMM), and generates an integrated sequence and copy number genotype at every locus (for example, including genotypes such as A-null, AAB and BBB in addition to AA, AB and BB calls). Such genotypes more accurately depict the underlying sequence of each individual, reducing the rate of apparent mendelian inconsistencies. The Birdsuite software is applied here to data from the Affymetrix SNP 6.0 array. Additionally, we describe a method, implemented in PLINK, to utilize these combined SNP and CNV genotypes for association testing with a phenotype.
Following recent success in genome-wide association studies, a critical focus of human genetics is to understand how genetic variation at implicated loci influences cellular and disease processes. Crohn’s disease (CD) is associated with SNPs around IRGM1,2, but coding-sequence variation has been excluded as a source of this association2. We identified a common, 20-kb deletion polymorphism, immediately upstream of IRGM and in perfect linkage disequilibrium (r2 = 1.0) with the most strongly CD-associated SNP, that causes IRGM to segregate in the population with two distinct upstream sequences. The deletion (CD risk) and reference (CD protective) haplotypes of IRGM showed distinct expression patterns. Manipulation of IRGM expression levels modulated cellular autophagy of internalized bacteria, a process implicated in CD. These results suggest that the CD association at IRGM arises from an alteration in IRGM regulation that affects the efficacy of autophagy and identify a common deletion polymorphism as a likely causal variant.
Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10−8): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2)1. We used ‘long-range haplotype’ methods, which were developed to identify alleles segregating in a population that have undergone recent selection2, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population: LARGE and DMD, both related to infection by the Lassa virus3, in West Africa; SLC24A5 and SLC45A2, both involved in skin pigmentation4,5, in Europe; and EDAR and EDA2R, both involved in development of hair follicles6, in Asia.
Genetic variation among individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single nucleotide changes. Here we explore variation on an intermediate scale—particularly insertions, deletions and inversions affecting from a few thousand to a few million base pairs. We employed a clone-based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1,695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number between individuals. Complete sequencing of 261 structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high-resolution sequence map of human structural variation—a standard for genotyping platforms and a prelude to future individual genome sequencing projects.
DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.
In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.
Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.
Thy-1, a glycosylphosphatidylinositol-linked integral membrane protein of the immunoglobulin superfamily, is a component of both large dense-core and small clear vesicles in PC12 cells. A majority of this protein, formerly recognized only on the plasma membrane of neurons, is localized to regulated secretory vesicles. Thy-1 is also present in synaptic vesicles in rat central nervous system. Experiments on permeabilized PC12 cells demonstrate that antibodies against Thy-1 inhibit the regulated release of neurotransmitter; this inhibition appears to be independent of any effect on the Ca2+ channel. These findings suggest Thy-1 is an integral component of many types of regulated secretory vesicles, and plays an important role in the regulated vesicular release of neurotransmitter at the synapse.