Search

Competing Interests: Competing interests: Stephen Scherer reports royalties from Athena Diagnostics, Lineagen and Population Bio, and consulting fees from Population Bio and Deep Genomics. No other competing interests were declared.

Over the past 30 years (the timespan of a generation), advances in genomics technologies have revealed tremendous and unexpected variation in the human genome and have provided increasingly accurate answers to long-standing questions of how much genetic variation exists in human populations and to what degree the DNA complement changes between parents and offspring. Tracking the characteristics of these inherited and spontaneous (or de novo) variations has been the basis of the study of human genetic disease. From genome-wide microarray and next-generation sequencing scans, we now know that each human genome contains over 3 million single nucleotide variants when compared with the ~ 3 billion base pairs in the human reference genome, along with roughly an order of magnitude more DNA-approximately 30 megabase pairs (Mb)-being 'structurally variable', mostly in the form of indels and copy number changes. Additional large-scale variations include balanced inversions (average of 18 Mb) and complex, difficult-to-resolve alterations. Collectively, ~1% of an individual's genome will differ from the human reference sequence. When comparing across a generation, fewer than 100 new genetic variants are typically detected in the euchromatic portion of a child's genome. Driven by increasingly higher-resolution and higher-throughput sequencing technologies, newer and more accurate databases of genetic variation (for instance, more comprehensive structural variation data and phasing of combinations of variants along chromosomes) of worldwide populations will emerge to underpin the next era of discovery in human molecular genetics., (© The Author(s) 2021. Published by Oxford University Press.)

The advent of long-read sequencing offers a new assessment method of detecting genomic structural variation (SV) in numerous rare genetic diseases. For autism spectrum disorders (ASD) cases where pathogenic variants fail to be found in the protein-coding genic regions along chromosomes, we proposed a scalable workflow to characterize the risk factor of SVs impacting non-coding elements of the genome. We applied whole-genome sequencing on an Emirati family having three children with ASD using long and short-read sequencing technology. A series of analytical pipelines were established to identify a set of SVs with high sensitivity and specificity. At 15-fold coverage, we observed that long-read sequencing technology (987 variants) detected a significantly higher number of SVs when compared to variants detected using short-read technology (509 variants) ( p -value < 1.1020 × 10 -57 ). Further comparison showed 97.9% of long-read sequencing variants were spanning within the 1-100 kb size range ( p -value < 9.080 × 10 -67 ) and impacting over 5000 genes. Moreover, long-read variants detected 604 non-coding RNAs ( p -value < 9.02 × 10 -9 ), comprising 58% microRNA, 31.9% lncRNA, and 9.1% snoRNA. Even at low coverage, long-read sequencing has shown to be a reliable technology in detecting SVs impacting complex elements of the genome.

Tandem DNA repeats vary in the size and sequence of each unit (motif). When expanded, these tandem DNA repeats have been associated with more than 40 monogenic disorders 1 . Their involvement in disorders with complex genetics is largely unknown, as is the extent of their heterogeneity. Here we investigated the genome-wide characteristics of tandem repeats that had motifs with a length of 2-20 base pairs in 17,231 genomes of families containing individuals with autism spectrum disorder (ASD) 2,3 and population control individuals 4 . We found extensive polymorphism in the size and sequence of motifs. Many of the tandem repeat loci that we detected correlated with cytogenetic fragile sites. At 2,588 loci, gene-associated expansions of tandem repeats that were rare among population control individuals were significantly more prevalent among individuals with ASD than their siblings without ASD, particularly in exons and near splice junctions, and in genes related to the development of the nervous system and cardiovascular system or muscle. Rare tandem repeat expansions had a prevalence of 23.3% in children with ASD compared with 20.7% in children without ASD, which suggests that tandem repeat expansions make a collective contribution to the risk of ASD of 2.6%. These rare tandem repeat expansions included previously undescribed ASD-linked expansions in DMPK and FXN, which are associated with neuromuscular conditions, and in previously unknown loci such as FGF14 and CACNB1. Rare tandem repeat expansions were associated with lower IQ and adaptive ability. Our results show that tandem DNA repeat expansions contribute strongly to the genetic aetiology and phenotypic complexity of ASD.

Identification of genetic biomarkers associated with autism spectrum disorders (ASDs) could improve recurrence prediction for families with a child with ASD. Here, we describe clinical microarray findings for 253 longitudinally phenotyped ASD families from the Baby Siblings Research Consortium (BSRC), encompassing 288 infant siblings. By age 3, 103 siblings (35.8%) were diagnosed with ASD and 54 (18.8%) were developing atypically. Thirteen siblings have copy number variants (CNVs) involving ASD-relevant genes: 6 with ASD, 5 atypically developing, and 2 typically developing. Within these families, an ASD-related CNV in a sibling has a positive predictive value (PPV) for ASD or atypical development of 0.83; the Simons Simplex Collection of ASD families shows similar PPVs. Polygenic risk analyses suggest that common genetic variants may also contribute to ASD. CNV findings would have been pre-symptomatically predictive of ASD or atypical development in 11 (7%) of the 157 BSRC siblings who were eventually diagnosed clinically.

Background: Recent advances in genomic technologies have facilitated genome-wide investigation of human genetic variations. However, most efforts have focused on the major populations, yet trio genomes of indigenous populations from Southeast Asia have been under-investigated., Results: We analyzed the whole-genome deep sequencing data (~ 30×) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81 × 10 - 8 - 1.33 × 10 - 8 , 1.0 × 10 - 9 - 2.9 × 10 - 9 , and ~ 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples., Conclusion: Our study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia.

Mutations within STXBP1 have been associated with a range of neurodevelopmental disorders implicating the pleotropic impact of this gene. Although the frequency of de novo mutations within STXBP1 for selective cohorts with early onset epileptic encephalopathy is more than 1%, there is no evidence for a hotspot within the gene. In this study, we analyzed the genomic context of de novo STXBP1 mutations to examine whether certain motifs indicated a greater risk of mutation. Through a comprehensive context analysis of 136 de novo /rare mutation (SNV/Indels) sites in this gene, strikingly 26.92% of all SNV mutations occurred within 5bp upstream or downstream of a 'GTA' motif ( P < 0.0005). This implies a genomic context modulated mutagenesis. Moreover, 51.85% (14 out of 27) of the 'GTA' mutations are splicing compared to 14.70% (20 out of 136) of all reported mutations within STXBP1 We also noted that 11 of these 14 'GTA' associated mutations are de novo in origin. Our analysis provides strong evidence of DNA motif modulated mutagenesis for STXBP1 de novo splicing mutations., (Copyright © 2018 Uddin et al.)

Background: The Personal Genome Project Canada is a comprehensive public data resource that integrates whole genome sequencing data and health information. We describe genomic variation identified in the initial recruitment cohort of 56 volunteers., Methods: Volunteers were screened for eligibility and provided informed consent for open data sharing. Using blood DNA, we performed whole genome sequencing and identified all possible classes of DNA variants. A genetic counsellor explained the implication of the results to each participant., Results: Whole genome sequencing of the first 56 participants identified 207 662 805 sequence variants and 27 494 copy number variations. We analyzed a prioritized disease-associated data set ( n = 1606 variants) according to standardized guidelines, and interpreted 19 variants in 14 participants (25%) as having obvious health implications. Six of these variants (e.g., in BRCA1 or mosaic loss of an X chromosome) were pathogenic or likely pathogenic. Seven were risk factors for cancer, cardiovascular or neurobehavioural conditions. Four other variants - associated with cancer, cardiac or neurodegenerative phenotypes - remained of uncertain significance because of discrepancies among databases. We also identified a large structural chromosome aberration and a likely pathogenic mitochondrial variant. There were 172 recessive disease alleles (e.g., 5 individuals carried mutations for cystic fibrosis). Pharmacogenomics analyses revealed another 3.9 potentially relevant genotypes per individual., Interpretation: Our analyses identified a spectrum of genetic variants with potential health impact in 25% of participants. When also considering recessive alleles and variants with potential pharmacologic relevance, all 56 participants had medically relevant findings. Although access is mostly limited to research, whole genome sequencing can provide specific and novel information with the potential of major impact for health care., Competing Interests: Competing interests: Stephen Scherer serves on the Scientific Advisory Committees of Population Bio and Deep Genomics. Sherilyn Bell, Jo-Anne Herbrick, Jennifer Howe, Ann Joseph-George, Barbara Kellam, Chao Lu, Jeffrey MacDonald, Christian Marshall, Thomas Nalpathamkalam, Rohan Patel, Tara Paton, Giovanna Pellecchia, Sergio Pereira, Miriam Reuter, Stephen Scherer, Lisa Strug, Wilson Sung, Bhooma Thiruvahindrapuram, Susan Walker, Zhuozhi Wang, John Wei, Joe Whitney, Richard Wintle and Ryan Yuen have received grants from Genome Canada/Ontario Genomics; Canada Foundation for Innovation; McLaughlin Centre, University of Toronto; the Government of Ontario, Canadian Institutes of Health Research (CIHR); and the The Hospital for Sick Children Foundation during the conduct of the study. James Ellis, Matthew Hildebrandt, Hin Lee, Peter Pasceri and Wei Wei have received a grant from the McLaughlin Centre, University of Toronto. Daniele Merico is an employee of Deep Genomics. Brett Trost has received a postdoctoral fellowship from CIHR. No other competing interests were declared., (© 2018 Joule Inc. or its licensors.)

Chromosome 22q11.2 microdeletions impart a high but incomplete risk for schizophrenia. Possible mechanisms include genome-wide effects of DGCR8 haploinsufficiency. In a proof-of-principle study to assess the power of this model, we used high-quality, whole-genome sequencing of nine individuals with 22q11.2 deletions and extreme phenotypes (schizophrenia, or no psychotic disorder at age >50 years). The schizophrenia group had a greater burden of rare, damaging variants impacting protein-coding neurofunctional genes, including genes involved in neuron projection (nominal P = 0.02, joint burden of three variant types). Variants in the intact 22q11.2 region were not major contributors. Restricting to genes affected by a DGCR8 mechanism tended to amplify between-group differences. Damaging variants in highly conserved long intergenic noncoding RNA genes also were enriched in the schizophrenia group (nominal P = 0.04). The findings support the 22q11.2 deletion model as a threshold-lowering first hit for schizophrenia risk. If applied to a larger and thus better-powered cohort, this appears to be a promising approach to identify genome-wide rare variants in coding and noncoding sequence that perturb gene networks relevant to idiopathic schizophrenia. Similarly designed studies exploiting genetic models may prove useful to help delineate the genetic architecture of other complex phenotypes., (Copyright © 2015 Merico et al.)

Copy number variation (CNV) has been recognized as a major contributor to human genome diversity. It plays an important role in determining phenotypes and has been associated with a number of common and complex diseases. However CNV data from diverse populations is still limited. Here we report the first investigation of CNV in the indigenous populations from Peninsular Malaysia. We genotyped 34 Negrito genomes from Peninsular Malaysia using the Affymetrix SNP 6.0 microarray and identified 48 putative novel CNVs, consisting of 24 gains and 24 losses, of which 5 were identified in at least 2 unrelated samples. These CNVs appear unique to the Negrito population and were absent in the DGV, HapMap3 and Singapore Genome Variation Project (SGVP) datasets. Analysis of gene ontology revealed that genes within these CNVs were enriched in the immune system (GO:0002376), response to stimulus mechanisms (GO:0050896), the metabolic pathways (GO:0001852), as well as regulation of transcription (GO:0006355). Copy number gains in CNV regions (CNVRs) enriched with genes were significantly higher than the losses (P value <0.001). In view of the small population size, relative isolation and semi-nomadic lifestyles of this community, we speculate that these CNVs may be attributed to recent local adaptation of Negritos from Peninsular Malaysia.

Over the past decade, the Database of Genomic Variants (DGV; http://dgv.tcag.ca/) has provided a publicly accessible, comprehensive curated catalogue of structural variation (SV) found in the genomes of control individuals from worldwide populations. Here, we describe updates and new features, which have expanded the utility of DGV for both the basic research and clinical diagnostic communities. The current version of DGV consists of 55 published studies, comprising >2.5 million entries identified in >22,300 genomes. Studies included in DGV are selected from the accessioned data sets in the archival SV databases dbVar (NCBI) and DGVa (EBI), and then further curated for accuracy and validity. The core visualization tool (gbrowse) has been upgraded with additional functions to facilitate data analysis and comparison, and a new query tool has been developed to provide flexible and interactive access to the data. The content from DGV is regularly incorporated into other large-scale genome reference databases and represents a standard data resource for new product and database development, in particular for copy number variation testing in clinical labs. The accurate cataloguing of variants in DGV will continue to enable medical genetics and genome sequencing research.

There is increasing evidence that the phenotypic effects of genomic sequence variants are best understood in terms of variant haplotypes rather than as isolated polymorphisms. Haplotype analysis is also critically important for uncovering population histories and for the study of evolutionary genetics. Although the sequencing of individual human genomes to reveal personal collections of sequence variants is now well established, there has been slower progress in the phasing of these variants into pairs of haplotypes along each pair of chromosomes. Here, we have developed a distinct approach to haplotyping that can yield chromosome-length haplotypes, including the vast majority of heterozygous single-nucleotide polymorphisms (SNPs) in an individual human genome. This approach exploits the haploid nature of sperm cells and employs a combination of genotyping and low-coverage sequencing on a short-read platform. In addition to generating chromosome-length haplotypes, the approach can directly identify recombination events (averaging 1.1 per chromosome) with a median resolution of <100 kb.

Even with significant advances in technology, few studies of structural variation have yet resolved to the level of the precise nucleotide junction. We examined the sequence of 408,532 gains, 383,804 losses, and 166 inversions from the first sequenced personal genome, to quantify the relative proportion of mutational mechanisms. Among small variants (<1 kb), we observed that 72.6% of them were associated with nonhomologous processes and 24.9% with microsatellites events. Medium-size variants (<10 kb) were commonly related to minisatellites (25.8%) and retrotransposons (24%), whereas 46.2% of large variants (>10 kb) were associated with nonallelic homologous recombination. We genotyped eight new breakpoint-resolved inversions at (3q26.1, Xp11.22, 7q11.22, 16q23.1, 4q22.1, 1q31.3, 6q27, and 16q24.1) in human populations to elucidate the structure of these presumed benign variants. Three of these inversions (3q26.1, 7q11.22, and 16q23.1) were accompanied by unexpected complex rearrangements. In particular, the 16q23.1 inversion and an accompanying deletion would create conjoined chymotrypsinogen genes (CTRB1 and CTRB2), disrupt their gene structure, and exhibit differentiated allelic frequencies among populations. Also, two loci (Xp11.3 and 6q27) of potential reference assembly orientation errors were found. This study provides a thorough account of formation mechanisms for structural variants, and reveals a glimpse of the dynamic structure of inversions., (© 2012 WILEY PERIODICALS, INC.)

Medulloblastoma, the most common malignant paediatric brain tumour, is currently treated with nonspecific cytotoxic therapies including surgery, whole-brain radiation, and aggressive chemotherapy. As medulloblastoma exhibits marked intertumoural heterogeneity, with at least four distinct molecular variants, previous attempts to identify targets for therapy have been underpowered because of small samples sizes. Here we report somatic copy number aberrations (SCNAs) in 1,087 unique medulloblastomas. SCNAs are common in medulloblastoma, and are predominantly subgroup-enriched. The most common region of focal copy number gain is a tandem duplication of SNCAIP, a gene associated with Parkinson's disease, which is exquisitely restricted to Group 4α. Recurrent translocations of PVT1, including PVT1-MYC and PVT1-NDRG1, that arise through chromothripsis are restricted to Group 3. Numerous targetable SCNAs, including recurrent events targeting TGF-β signalling in Group 3, and NF-κB signalling in Group 4, suggest future avenues for rational, targeted therapy.

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude., Competing Interests: The authors have declared that no competing interests exist.

Structural variations of DNA greater than 1 kilobase in size account for most bases that vary among human genomes, but are still relatively under-ascertained. Here we use tiling oligonucleotide microarrays, comprising 42 million probes, to generate a comprehensive map of 11,700 copy number variations (CNVs) greater than 443 base pairs, of which most (8,599) have been validated independently. For 4,978 of these CNVs, we generated reference genotypes from 450 individuals of European, African or East Asian ancestry. The predominant mutational mechanisms differ among CNV size classes. Retrotransposition has duplicated and inserted some coding and non-coding DNA segments randomly around the genome. Furthermore, by correlation with known trait-associated single nucleotide polymorphisms (SNPs), we identified 30 loci with CNVs that are candidates for influencing disease susceptibility. Despite this, having assessed the completeness of our map and the patterns of linkage disequilibrium between CNVs and SNPs, we conclude that, for complex traits, the heritability void left by genome-wide association studies will not be accounted for by common CNVs.

During the past five years, copy number variation (CNV) has emerged as a highly prevalent form of genomic variation, bridging the interval between long-recognised microscopic chromosomal alterations and single-nucleotide changes. These genomic segmental differences among humans reflect the dynamic nature of genomes, and account for both normal variations among us and variations that predispose to conditions of medical consequence. Here, we place CNVs into their historical and medical contexts, focusing on how these variations can be recognised, documented, characterised and interpreted in clinical diagnostics. We also discuss how they can cause disease or influence adaptation to an environment. Various clinical exemplars are drawn out to illustrate salient characteristics and residual enigmas of CNVs, particularly the complexity of the data and information associated with CNVs relative to that of single-nucleotide variation. The potential is immense for CNVs to explain and predict disorders and traits that have long resisted understanding. However, creative solutions are needed to manage the sudden and overwhelming burden of expectation for laboratories and clinicians to assay and interpret these complex genomic variations as awareness permeates medical practice. Challenges remain for understanding the relationship between genomic changes and the phenotypes that might be predicted and prevented by such knowledge.

Background: Several genomes have now been sequenced, with millions of genetic variants annotated. While significant progress has been made in mapping single nucleotide polymorphisms (SNPs) and small (<10 bp) insertion/deletions (indels), the annotation of larger structural variants has been less comprehensive. It is still unclear to what extent a typical genome differs from the reference assembly, and the analysis of the genomes sequenced to date have shown varying results for copy number variation (CNV) and inversions., Results: We have combined computational re-analysis of existing whole genome sequence data with novel microarray-based analysis, and detect 12,178 structural variants covering 40.6 Mb that were not reported in the initial sequencing of the first published personal genome. We estimate a total non-SNP variation content of 48.8 Mb in a single genome. Our results indicate that this genome differs from the consensus reference sequence by approximately 1.2% when considering indels/CNVs, 0.1% by SNPs and approximately 0.3% by inversions. The structural variants impact 4,867 genes, and >24% of structural variants would not be imputed by SNP-association., Conclusions: Our results indicate that a large number of structural variants have been unreported in the individual genomes published to date. This significant extent and complexity of structural variants, as well as the growing recognition of their medical relevance, necessitate they be actively studied in health-related analyses of personal genomes. The new catalogue of structural variants generated for this genome provides a crucial resource for future comparison studies.

Momentum around the era of genomic medicine is building, and with it, anticipation of the benefits that whole genome analysis (personalized or individualized genomics) will bring for the provision of health care. These technologies have the potential to revolutionize genetic diagnosis; however, the expansive data generated can lead to complex or unexpected findings, sometimes complicating clinical utility and patient benefit. Here, we use our experience with whole genome scanning microarrays, an early instance of whole genome analysis already in clinical use, to highlight fundamental challenges raised by these technologies and to discuss their medical, ethical, legal and social implications. We discuss issues that physicians and healthcare professionals will face, in particular, as the resolution of testing further increases toward full genome sequence determination. We emphasize that addressing these issues now, and starting to evolve our healthcare systems in response, will be pivotal in avoiding harms and realizing the promise of these new technologies.

Two developments have sparked new directions in the genetics-to-genomics transition for research and medical applications: the advance of whole-genome assays by array or DNA sequencing technologies, and the discovery among human genomes of extensive submicroscopic genomic structural variation, including copy number variation. For health care to benefit from interpretation of genomic data, we need to know how these variants contribute to the phenotype of the individual. Research is revealing the spectrum, both in size and complexity, of structural genotypic variation, and its association with a broad range of human phenotypes. Genomic disorders associated with relatively large, recurrent contiguous variants have been recognized for some time, as have certain Mendelian traits associated with functional disruption of single genes by structural variation. More recent examples from phenotype- and genotype-driven studies demonstrate a greater level of complexity, with evidence of incremental dosage effects, gene interaction networks, buffering and modifiers, and position effects. Mechanisms underlying such variation are emerging to provide a handle on the bulk of human variation, which is associated with complex traits and adaptive potential. Interpreting genotypes for personalized health care and communicating knowledge to the individual will be significant challenges for genomics professionals.

DNA copy number variations (CNVs) are a significant and ubiquitous source of inherited human genetic variation. However, the importance of CNVs to cancer susceptibility and tumor progression has not yet been explored. Li-Fraumeni syndrome (LFS) is an autosomal dominantly inherited disorder characterized by a strikingly increased risk of early-onset breast cancer, sarcomas, brain tumors and other neoplasms in individuals harboring germline TP53 mutations. Known genetic determinants of LFS do not fully explain the variable clinical phenotype in affected family members. As part of a wider study of CNVs and cancer, we conducted a genome-wide profile of germline CNVs in LFS families. Here, by examining DNA from a large healthy population and an LFS cohort using high-density oligonucleotide arrays, we show that the number of CNVs per genome is well conserved in the healthy population, but strikingly enriched in these cancer-prone individuals. We found a highly significant increase in CNVs among carriers of germline TP53 mutations with a familial cancer history. Furthermore, we identified a remarkable number of genomic regions in which known cancer-related genes coincide with CNVs, in both LFS families and healthy individuals. Germline CNVs may provide a foundation that enables the more dramatic chromosomal changes characteristic of TP53-related tumors to be established. Our results suggest that screening families predisposed to cancer for CNVs may identify individuals with an abnormally high number of these events.

Presented here is a genome sequence of an individual human. It was produced from approximately 32 million random DNA fragments, sequenced by Sanger dideoxy technology and assembled into 4,528 scaffolds, comprising 2,810 million bases (Mb) of contiguous sequence with approximately 7.5-fold coverage for any given region. We developed a modified version of the Celera assembler to facilitate the identification and comparison of alternate alleles within this individual diploid genome. Comparison of this genome and the National Center for Biotechnology Information human reference assembly revealed more than 4.1 million DNA variants, encompassing 12.3 Mb. These variants (of which 1,288,319 were novel) included 3,213,401 single nucleotide polymorphisms (SNPs), 53,823 block substitutions (2-206 bp), 292,102 heterozygous insertion/deletion events (indels)(1-571 bp), 559,473 homozygous indels (1-82,711 bp), 90 inversions, as well as numerous segmental duplications and copy number variation regions. Non-SNP DNA variation accounts for 22% of all events identified in the donor, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. Using a novel haplotype assembly strategy, we were able to span 1.5 Gb of genome sequence in segments >200 kb, providing further precision to the diploid nature of the genome. These data depict a definitive molecular portrait of a diploid human genome that provides a starting point for future genome comparisons and enables an era of individualized genomic information.

There has been an explosion of data describing newly recognized structural variants in the human genome. In the flurry of reporting, there has been no standard approach to collecting the data, assessing its quality or describing identified features. This risks becoming a rampant problem, in particular with respect to surveys of copy number variation and their application to disease studies. Here, we consider the challenges in characterizing and documenting genomic structural variants. From this, we derive recommendations for standards to be adopted, with the aim of ensuring the accurate presentation of this form of genetic variation to facilitate ongoing research.

Extensive studies are currently being performed to associate disease susceptibility with one form of genetic variation, namely, single-nucleotide polymorphisms (SNPs). In recent years, another type of common genetic variation has been characterized, namely, structural variation, including copy number variants (CNVs). To determine the overall contribution of CNVs to complex phenotypes, we have performed association analyses of expression levels of 14,925 transcripts with SNPs and CNVs in individuals who are part of the International HapMap project. SNPs and CNVs captured 83.6% and 17.7% of the total detected genetic variation in gene expression, respectively, but the signals from the two types of variation had little overlap. Interrogation of the genome for both types of variants may be an effective way to elucidate the causes of complex phenotypes and disease in humans.

Recent reports indicate that copy number variations (CNVs) within the human genome contribute to nucleotide diversity to a larger extent than single nucleotide polymorphisms (SNPs). In addition, the contribution of CNVs to human disease susceptibility may be greater than previously expected, although a complete understanding of the phenotypic consequences of CNVs is incomplete. We have recently reported a comprehensive view of CNVs among 270 HapMap samples using high-density SNP genotyping arrays and BAC array CGH. In this report, we describe a novel algorithm using Affymetrix GeneChip Human Mapping 500K Early Access (500K EA) arrays that identified 1203 CNVs ranging in size from 960 bp to 3.4 Mb. The algorithm consists of three steps: (1) Intensity pre-processing to improve the resolution between pairwise comparisons by directly estimating the allele-specific affinity as well as to reduce signal noise by incorporating probe and target sequence characteristics via an improved version of the Genomic Imbalance Map (GIM) algorithm; (2) CNV extraction using an adapted SW-ARRAY procedure to automatically and robustly detect candidate CNV regions; and (3) copy number inference in which all pairwise comparisons are summarized to more precisely define CNV boundaries and accurately estimate CNV copy number. Independent testing of a subset of CNVs by quantitative PCR and mass spectrometry demonstrated a >90% verification rate. The use of high-resolution oligonucleotide arrays relative to other methods may allow more precise boundary information to be extracted, thereby enabling a more accurate analysis of the relationship between CNVs and other genomic features.

Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs and intermediate-sized variants (ISVs). However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized (<50 kb) variants. Here we show that genome assembly comparison is a robust approach for identification of all classes of genetic variation. Through comparison of two human assemblies (Celera's R27c compilation and the Build 35 reference sequence), we identified megabases of sequence (in the form of 13,534 putative non-SNP events) that were absent, inverted or polymorphic in one assembly. Database comparison and laboratory experimentation further demonstrated overlap or validation for 240 variable regions and confirmed >1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.

This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published "Golden Path," and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.

Copy number variation (CNV) of DNA sequences is functionally significant but has yet to be fully ascertained. We have constructed a first-generation CNV map of the human genome through the study of 270 individuals from four populations with ancestry in Europe, Africa or Asia (the HapMap collection). DNA from these individuals was screened for CNV using two complementary technologies: single-nucleotide polymorphism (SNP) genotyping arrays, and clone-based comparative genomic hybridization. A total of 1,447 copy number variable regions (CNVRs), which can encompass overlapping or adjacent gains or losses, covering 360 megabases (12% of the genome) were identified in these populations. These CNVRs contained hundreds of genes, disease loci, functional elements and segmental duplications. Notably, the CNVRs encompassed more nucleotide content per genome than SNPs, underscoring the importance of CNV in genetic diversity and evolution. The data obtained delineate linkage disequilibrium patterns for many CNVs, and reveal marked variation in copy number among populations. We also demonstrate the utility of this resource for genetic disease studies.

DNA copy number variation has long been associated with specific chromosomal rearrangements and genomic disorders, but its ubiquity in mammalian genomes was not fully realized until recently. Although our understanding of the extent of this variation is still developing, it seems likely that, at least in humans, copy number variants (CNVs) account for a substantial amount of genetic variation. Since many CNVs include genes that result in differential levels of gene expression, CNVs may account for a significant proportion of normal phenotypic variation. Current efforts are directed toward a more comprehensive cataloging and characterization of CNVs that will provide the basis for determining how genomic diversity impacts biological function, evolution, and common human diseases.

Advances in genome scanning technologies are revealing that copy number variants (CNVs) and polymorphisms, ranging from a few kilobases to several megabases in size, are present in genomes at frequencies much greater than previously known. Discoveries of additional forms of genomic variation, including inversions, insertions, deletions and complex rearrangements, are also occurring at an increased rate. Along with CNVs, these sequence alterations are collectively known as structural variants, and their discovery has had an immediate impact on the interpretation of basic research and clinical diagnostic data. This paper discusses different methods, experimental strategies and technologies that are currently available to study copy number variation and other structural variants in the human genome.

The first wave of information from the analysis of the human genome revealed SNPs to be the main source of genetic and phenotypic human variation. However, the advent of genome-scanning technologies has now uncovered an unexpectedly large extent of what we term 'structural variation' in the human genome. This comprises microscopic and, more commonly, submicroscopic variants, which include deletions, duplications and large-scale copy-number variants - collectively termed copy-number variants or copy-number polymorphisms - as well as insertions, inversions and translocations. Rapidly accumulating evidence indicates that structural variants can comprise millions of nucleotides of heterogeneity within every genome, and are likely to make an important contribution to human diversity and disease susceptibility.

The discovery of an abundance of copy number variants (CNVs; gains and losses of DNA sequences >1 kb) and other structural variants in the human genome is influencing the way research and diagnostic analyses are being designed and interpreted. As such, comprehensive databases with the most relevant information will be critical to fully understand the results and have impact in a diverse range of disciplines ranging from molecular biology to clinical genetics. Here, we describe the development of bioinformatics resources to facilitate these studies. The Database of Genomic Variants (http://projects.tcag.ca/variation/) is a comprehensive catalogue of structural variation in the human genome. The database currently contains 1,267 regions reported to contain copy number variation or inversions in apparently healthy human cases. We describe the current contents of the database and how it can serve as a resource for interpretation of array comparative genomic hybridization (array CGH) and other DNA copy imbalance data. We also present the structure of the database, which was built using a new data modeling methodology termed Cross-Referenced Tables (XRT). This is a generic and easy-to-use platform, which is strong in handling textual data and complex relationships. Web-based presentation tools have been built allowing publication of XRT data to the web immediately along with rapid sharing of files with other databases and genome browsers. We also describe a novel tool named eFISH (electronic fluorescence in situ hybridization) (http://projects.tcag.ca/efish/), a BLAST-based program that was developed to facilitate the choice of appropriate clones for FISH and CGH experiments, as well as interpretation of results in which genomic DNA probes are used in hybridization-based experiments., (Copyright (c) 2006 S. Karger AG, Basel.)

Human chromosome 7 is arguably amongst the most comprehensively characterized segments of the human genome. By microscopic examination, it belongs to the medium-sized group C submetacentric class, and historical studies involving chromosome-length measurements estimated that it accounts for approximately 5.3% of the human genome (or 160 Mb). Early successes in molecular genetics led to the identification of some of its biomedically important genes, including the T-cell receptor and homeobox families as well as the erythropoietin and cystic fibrosis genes. The Human Genome Project brought chromosome 7-specific and genome-wide initiatives, generating a wealth of genomic resources that have revealed the presence of over 350 disease-associated genes. Two distinct assemblies of the chromosome 7 sequence have been generated-one based largely on mapped large-insert clones and the other based on an integrated whole-genome shotgun sequencing strategy. These two sequences are mainly identical (<1% difference), and both estimate the unit length of chromosome 7 to be just over 158 Mb, remarkably similar to the originally predicted size. Systematic annotation efforts have anchored to the sequence, amongst many features, over 900 known genes and some 1000 other gene structures, as well as over 650 chromosomal breakpoints identified in patients with characterized phenotypic differences. Chromosome 7 has also been shown to contain the highest content of intra-autosomal segmental duplications in the human genome. The orthologous regions of roughly 22 Mb of chromosome 7 are currently being sequenced in multiple other vertebrate species. Examining these comparative sequence data, in conjunction with the other accumulating genomic information about these regions and the rest of the chromosome, should provide a model for the next generation of structural and functional analyses of the human genome.

We identified 255 loci across the human genome that contain genomic imbalances among unrelated individuals. Twenty-four variants are present in > 10% of the individuals that we examined. Half of these regions overlap with genes, and many coincide with segmental duplications or gaps in the human genome assembly. This previously unappreciated heterogeneity may underlie certain human phenotypic variation and susceptibility to disease and argues for a more dynamic human genome structure.

Our previous study described the amplification of a genomic sequence containing exon 9 of CFTR in the human genome. Here we report that this CFTR sequence is part of a large duplicated sequence unit, provisionally named LCR7-20. Through successive screening of two human chromosome 7-specific cosmid libraries to construct a cosmid contig, we assembled two sequenced BAC clones into a single contig containing a prototypic LCR7-20 unit. Subsequent searches of existing human genome sequences identified additional six copies of LCR7-20-like sequences with more than 90% sequence homology. Additional genomic clones containing LCR7-20-like sequences were then isolated from total genomic BAC and PAC libraries. Restriction fragment analysis and limited sequencing data indicated that there could be around 30 copies of LCR7-20-like sequences in the human genome and that the average region of homology could extend over 120 kb. As indicated by fluorescence in situ hybridization analysis, LCR7-20-like sequences are dispersed on different chromosomes, mainly in the centromeric and pericentromeric regions, and some may exist in tandem copies. Our study also indicates that many genomic regions containing LCR7-20's either have been misassembled or are missing in current versions of the human genome sequence.

Background: Previous studies have suggested that recent segmental duplications, which are often involved in chromosome rearrangements underlying genomic disease, account for some 5% of the human genome. We have developed rapid computational heuristics based on BLAST analysis to detect segmental duplications, as well as regions containing potential sequence misassignments in the human genome assemblies., Results: Our analysis of the June 2002 public human genome assembly revealed that 107.4 of 3,043.1 megabases (Mb) (3.53%) of sequence contained segmental duplications, each with size equal or more than 5 kb and 90% identity. We have also detected that 38.9 Mb (1.28%) of sequence within this assembly is likely to be involved in sequence misassignment errors. Furthermore, we have identified a significant subset (199,965 of 2,327,473 or 8.6%) of single-nucleotide polymorphisms (SNPs) in the public databases that are not true SNPs but are potential paralogous sequence variants., Conclusion: Using two distinct computational approaches, we have identified most of the sequences in the human genome that have undergone recent segmental duplications. Near-identical segmental duplications present a major challenge to the completion of the human genome sequence. Potential sequence misassignments detected in this study would require additional efforts to resolve.

We have explored the National Center for Biotechnology Information (NCBI) single nucleotide polymorphisms (SNPs) database for a correlation between the density of putative SNPs, as well as SNPs that map to different chromosomal locations (ambiguously mapped SNPs), and segmental duplications of DNA in chromosome regions involved in genomic disorders. A high density of SNPs (14.4 and 12.4 SNPs per kb) was detected in the low copy repeats (LCRs) responsible for the chromosome 17p12 duplication and deletion that cause peripheral neuropathies. None of the SNPs at the PMP22 gene were ambiguously mapped, but 93% of the SNPs at LCRs mapped on both LCR copies, indicating that they are in fact variants in paralogous sequences. Similarly, a high SNP density was found in the LCR regions flanking the neurofibromatosis type 1 (NF1) gene, with 80% of SNPs mapping on both LCR copies. A high density of SNPs was found within LCR sequences involved in the deletions that mediate contiguous gene syndromes on chromosomes 7q11, 15q11-q13 and 22q11. We have analyzed the whole sequence of chromosome 22, which contains 14% of ambiguously mapped SNPs, and have found a good correlation between these SNPs and segmental duplications detected by BLAST analysis. We have identified several segments of ambiguously mapped SNPs, four corresponding to LCRs involved in the chromosome 22q11 microdeletion syndromes. Our data indicate that most SNPs in LCR segments are in fact paralogous sequence variants (PSVs), and suggest that a significant proportion of the SNPs in the NCBI database correspond to PSVs within segmental duplications of the human genome sequence.

The chromosome localizations for 159 gene and DNA segments have been refined to one of five intervals in the 7q21-132 region through hybridization analysis with a panel of somatic cell hybrid lines. Seventy-two of these chromosome 7 markers are also mapped on common or overlapping yeast artificial chromosome (YAC) clones. In addition, the breakpoints of chromosome rearrangement contained in five of the somatic cell hybrid lines have been defined by flanking probes within YAC contigs. To provide a framework for further mapping of the 7q21-q32 region, we have established the physical order of a set of reference markers: cen-(COL1A2-D7S15-CYP3A4-PON)-D7S456-(brea kpoint contained in cell hybrid 1EF2/3/K017)-GUSB-D7S186-ASL-(PGY1-PGY3 -GNB2-EPO-ACHE)-D7S238-(proximal breakpoint in GM1059-Rag5)-D7S240-(CUTL1-PLANH1)-(breakp oints in 1CF2/5/K016 and 2068Rag22-2)-(PRKAR2B-D7S13)-LAMB1-(breakpoint in JSR-17S)-DLD-D7S16-MET-WNT2-CFTR-D7S8-tel.