Comprehensive long-span paired-end-tag mapping reveals characteristic patterns of structural variations in epithelial cancer genomes

Deciphering complex breakage-fusion-bridge genome rearrangements with Ambigram

Breakage-fusion-bridge (BFB) is a complex rearrangement that leads to tumor malignancy. Existing models for detecting BFBs rely on the ideal BFB hypothesis, ruling out the possibility of BFBs entangled with other structural variations, that is, complex BFBs. We propose an algorithm Ambigram to identify complex BFB and reconstruct the rearranged structure of the local genome during the cancer subclone evolution process. Ambigram handles data from short, linked, long, and single-cell sequences, and optical mapping technologies. Ambigram successfully deciphers the gold- or silver-standard complex BFBs against the state-of-the-art in multiple cancers. Ambigram dissects the intratumor heterogeneity of complex BFB events with single-cell reads from melanoma and gastric cancer. Furthermore, applying Ambigram to liver and cervical cancer data suggests that the BFB mechanism may mediate oncovirus integrations. BFB also exists in noncancer genomics. Investigating the complete human genome reference with Ambigram suggests that the BFB mechanism may be involved in two genome reorganizations of Homo Sapiens during evolution. Moreover, Ambigram discovers the signals of recurrent foldback inversions and complex BFBs in whole genome data from the 1000 genome project, and congenital heart diseases, respectively.

HiSV: A control-free method for structural variation detection from Hi-C data

Structural variations (SVs) play an essential role in the evolution of human genomes and are associated with cancer genetics and rare disease. High-throughput chromosome capture (Hi-C) technology probed all genome-wide crosslinked chromatin to study the spatial architecture of chromosomes. Hi-C read pairs can span megabases, making the technology useful for detecting large-scale SVs. So far, the identification of SVs from Hi-C data is still in the early stages with only a few methods available. Especially, no algorithm has been developed that can detect SVs without control samples. Therefore, we developed HiSV (Hi-C for Structural Variation), a control-free method for identifying large-scale SVs from a Hi-C sample. Inspired by the single image saliency detection model, HiSV constructed a saliency map of interaction frequencies and extracted saliency segments as large-scale SVs. By evaluating both simulated and real data, HiSV not only detected all variant types, but also achieved a higher level of accuracy and sensitivity than existing methods. Moreover, our results on cancer cell lines showed that HiSV effectively detected eight complex SV events and identified two novel SVs of key factors associated with cancer development. Finally, we found that integrating the result of HiSV helped the WGS method to identify a total number of 94 novel SVs in two cancer cell lines.

A multi-platform reference for somatic structural variation detection

Accurate detection of somatic structural variation (SV) in cancer genomes remains a challenging problem. This is in part due to the lack of high-quality, gold-standard datasets that enable the benchmarking of experimental approaches and bioinformatic analysis pipelines. Here, we performed somatic SV analysis of the paired melanoma and normal lymphoblastoid COLO829 cell lines using four different sequencing technologies. Based on the evidence from multiple technologies combined with extensive experimental validation, we compiled a comprehensive set of carefully curated and validated somatic SVs, comprising all SV types. We demonstrate the utility of this resource by determining the SV detection performance as a function of tumor purity and sequence depth, highlighting the importance of assessing these parameters in cancer genomics projects. The truth somatic SV dataset as well as the underlying raw multi-platform sequencing data are freely available and are an important resource for community somatic benchmarking efforts.

Hi-C as a molecular rangefinder to examine genomic rearrangements

The mammalian genome is highly packed into the nucleus. Over the past decade, the development of Hi-C has contributed significantly to our understanding of the three-dimensional (3D) chromatin structure, uncovering the principles and functions of higher-order chromatin organizations. Recent studies have repositioned its property in spatial proximity measurement to address challenging problems in genome analyses including genome assembly, haplotype phasing, and the detection of genomic rearrangements. In particular, the power of Hi-C in detecting large-scale structural variations (SVs) in the cancer genome has been demonstrated, which is challenging to be addressed solely with short-read-based whole-genome sequencing analyses. In this review, we first provide a comprehensive view of Hi-C as an intuitive and effective SV detection tool. Then, we introduce recently developed bioinformatics tools utilizing Hi-C to investigate genomic rearrangements. Finally, we discuss the potential application of single-cell Hi-C to address the heterogeneity of genomic rearrangements and sub-population identification in the cancer genome.

Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions

Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.

Cancer and many other diseases are often driven by structural rearrangements in the patients. Their precise identification is necessary to understand evolution and cure for the disease. In this study, we have compared two sequencing technologies for the identification of structural variations i.e. Illumina’s short-reads and 10X Genomics linked-reads sequencing. Short-reads sequencing is already known to have high false discovery rate for structural variations, while, an unbiased performance evaluation of linked-reads sequencing is missing. Hence, we evaluate the performance of these two technologies using computational and PCR based methodologies. Moreover, we also present a statistical approach to increase their performance, supporting better detection of structural variations and thus further research into disease biology.

Breakage-Fusion-Bridge Events Trigger Complex Genome Rearrangements and Amplifications in Developmentally Arrested T Cell Lymphomas

To reveal the relative contribution of the recombination activating gene (RAG)1/2 nuclease to lymphomagenesis, we conducted a genome-wide analysis of T cell lymphomas from p53-deficient mice expressing or lacking RAG2. We found that while p53^−/− lymphoblastic T cells harbor primarily ectopic DNA deletions, Rag2^−/−p53^−/− T cell lymphomas display complex genomic rearrangements associated with amplification of the chromosomal location 9qA4-5.3. We show that this amplicon is generated by breakage-fusion-bridge during mitosis and arises distinctly in T cell lymphomas originating from an early progenitor stage. Notably, we report amplification of the corresponding syntenic region (11q23) in a subset of human leukemia leading to the overexpression of several cancer genes, including MLL/KMT2A. Our findings provide direct evidence that lymphocytes undergo malignant transformation through distinct genome architectural routes that are determined by both RAG-dependent and RAG-independent DNA damage and a block in cell development.

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Lymphomas from RAG2/p53- and p53-deficient mice bear distinct genome architectures

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Block in T cell development leads to 9qA4-5.3 rearrangements and amplifications

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Breakage-fusion-bridge events trigger 9qA4-5.3 aberrations in early T cell lymphomas

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The syntenic region 11q23 is amplified in some human hematological cancers

Mechanisms Underlying Recurrent Genomic Amplification in Human Cancers

Focal copy-number increases (genomic amplification) pinpoint oncogenic driver genes and therapeutic targets in cancer genomes. With the advent of genomic technologies, recurrent genomic amplification has been mapped throughout the genome. Recurrent amplification could be solely due to positive selection for the tumor-promoting effects of amplified gene products. Alternatively, recurrence could result from the susceptibility of the loci to amplification. Distinguishing between these possibilities requires a full understanding of the amplification mechanisms. Two mechanisms, the formation of double minute (DM) chromosomes and breakage-fusion-bridge (BFB) cycles, have been repeatedly linked to genomic amplification, and the impact of both mechanisms has been confirmed in cancer genomics data. We review the details of these mechanisms and discuss the mechanisms underlying recurrence.

Mammalian Systems Biotechnology Reveals Global Cellular Adaptations in a Recombinant CHO Cell Line

Effective development of host cells for therapeutic protein production is hampered by the poor characterization of cellular transfection. Here, we employed a multi-omics-based systems biotechnology approach to elucidate the genotypic and phenotypic differences between a wild-type and recombinant antibody-producing Chinese hamster ovary (CHO) cell line. At the genomic level, we observed extensive rearrangements in specific targeted loci linked to transgene integration sites. Transcriptional re-wiring of DNA damage repair and cellular metabolism in the antibody producer, via changes in gene copy numbers, was also detected. Subsequent integration of transcriptomic data with a genome-scale metabolic model showed a substantial increase in energy metabolism in the antibody producer. Metabolomics, lipidomics, and glycomics analyses revealed an elevation in long-chain lipid species, potentially associated with protein transport and secretion requirements, and a surprising stability of N-glycosylation profiles between both cell lines. Overall, the proposed knowledge-based systems biotechnology framework can further accelerate mammalian cell-line engineering in a targeted manner.

An AR-ERG transcriptional signature defined by long-range chromatin interactomes in prostate cancer cells

The aberrant activities of transcription factors such as the androgen receptor (AR) underpin prostate cancer development. While the AR cis-regulation has been extensively studied in prostate cancer, information pertaining to the spatial architecture of the AR transcriptional circuitry remains limited. In this paper, we propose a novel framework to profile long-range chromatin interactions associated with AR and its collaborative transcription factor, erythroblast transformation-specific related gene (ERG), using chromatin interaction analysis by paired-end tag (ChIA-PET). We identified ERG-associated long-range chromatin interactions as a cooperative component in the AR-associated chromatin interactome, acting in concert to achieve coordinated regulation of a subset of AR target genes. Through multifaceted functional data analysis, we found that AR-ERG interaction hub regions are characterized by distinct functional signatures, including bidirectional transcription and cotranscription factor binding. In addition, cancer-associated long noncoding RNAs were found to be connected near protein-coding genes through AR-ERG looping. Finally, we found strong enrichment of prostate cancer genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) at AR-ERG co-binding sites participating in chromatin interactions and gene regulation, suggesting GWAS target genes identified from chromatin looping data provide more biologically relevant findings than using the nearest gene approach. Taken together, our results revealed an AR-ERG-centric higher-order chromatin structure that drives coordinated gene expression in prostate cancer progression and the identification of potential target genes for therapeutic intervention.

Integrative detection and analysis of structural variation in cancer genomes

Structural variants (SVs) can contribute to oncogenesis through a variety of mechanisms. Despite their importance, the identification of SVs in cancer genomes remains challenging. Here, we present a framework that integrates optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole-genome sequencing to systematically detect SVs in a variety of normal or cancer samples and cell lines. We identify the unique strengths of each method and demonstrate that only integrative approaches can comprehensively identify SVs in the genome. By combining Hi-C and optical mapping, we resolve complex SVs and phase multiple SV events to a single haplotype. Furthermore, we observe widespread structural variation events affecting the functions of noncoding sequences, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel three-dimensional chromatin structural domains. Our results indicate that noncoding SVs may be underappreciated mutational drivers in cancer genomes.

The Tandem Duplicator Phenotype Is a Prevalent Genome-Wide Cancer Configuration Driven by Distinct Gene Mutations

The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian, and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 kb, 231 kb, and 1.7 Mb, respectively. TDPs with ∼11 kb TDs feature loss of TP53 and BRCA1. TDPs with ∼231 kb and ∼1.7 Mb TDs associate with CCNE1 pathway activation and CDK12 disruptions, respectively. We demonstrate that p53 and BRCA1 conjoint abrogation drives TDP induction by generating short-span TDP mammary tumors in genetically modified mice lacking them. Lastly, we show how TDs in TDP tumors disrupt heterogeneous combinations of tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers.

A Pan-Cancer Compendium of Genes Deregulated by Somatic Genomic Rearrangement across More Than 1,400 Cases

A systematic cataloging of genes affected by genomic rearrangement, using multiple patient cohorts and cancer types, can provide insight into cancer-relevant alterations outside of exomes. By integrative analysis of whole-genome sequencing (predominantly low pass) and gene expression data from 1,448 cancers involving 18 histopathological types in The Cancer Genome Atlas, we identified hundreds of genes for which the nearby presence (within 100 kb) of a somatic structural variant (SV) breakpoint is associated with altered expression. While genomic rearrangements are associated with widespread copy-number alteration (CNA) patterns, approximately 1,100 genes-including overexpressed cancer driver genes (e.g., TERT, ERBB2, CDK12, CDK4) and underexpressed tumor suppressors (e.g., TP53, RB1, PTEN, STK11)-show SV-associated deregulation independent of CNA. SVs associated with the disruption of topologically associated domains, enhancer hijacking, or fusion transcripts are implicated in gene upregulation. For cancer-relevant pathways, SVs considerably expand our understanding of how genes are affected beyond point mutation or CNA.

Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

Structural Variant Breakpoint Detection with novoBreak

Structural variations (SVs) are an important type of genomic variants and always play a critical role for cancer development and progression. In the cancer genomics era, detecting structural variations from short sequencing data is still challenging. We developed a novel algorithm, novoBreak (Chong et al. Nat Methods 14:65-67, 2017), which achieved the highest balanced accuracy (mean of sensitivity and precision) in the ICGC-TCGA DREAM 8.5 Somatic Mutation Calling Challenge. Here we describe detailed instructions of applying novoBreak ( https://github.com/czc/nb_distribution ), an open-source software, for somatic SVs detection. We also briefly introduce how to detect germline SVs using novoBreak pipeline and how to use the Workflow ( https://cgc.sbgenomics.com/public/apps#ZCHONG/novobreak-commit/novobreak-analysis/ ) of novoBreak on the Seven Bridges Cancer Genomics Cloud.

SVachra: a tool to identify genomic structural variation in mate pair sequencing data containing inward and outward facing reads

Background

Characterization of genomic structural variation (SV) is essential to expanding the research and clinical applications of genome sequencing. Reliance upon short DNA fragment paired end sequencing has yielded a wealth of single nucleotide variants and internal sequencing read insertions-deletions, at the cost of limited SV detection. Multi-kilobase DNA fragment mate pair sequencing has supplemented the void in SV detection, but introduced new analytic challenges requiring SV detection tools specifically designed for mate pair sequencing data. Here, we introduce SVachra – Structural Variation Assessment of CHRomosomal Aberrations, a breakpoint calling program that identifies large insertions-deletions, inversions, inter- and intra-chromosomal translocations utilizing both inward and outward facing read types generated by mate pair sequencing.

Results

We demonstrate SVachra’s utility by executing the program on large-insert (Illumina Nextera) mate pair sequencing data from the personal genome of a single subject (HS1011). An additional data set of long-read (Pacific BioSciences RSII) was also generated to validate SV calls from SVachra and other comparison SV calling programs. SVachra exhibited the highest validation rate and reported the widest distribution of SV types and size ranges when compared to other SV callers.

Conclusions

SVachra is a highly specific breakpoint calling program that exhibits a more unbiased SV detection methodology than other callers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4021-y) contains supplementary material, which is available to authorized users.

Personalized genome sequencing coupled with iPSC technology identifies GTDC1 as a gene involved in neurodevelopmental disorders

The cellular and molecular mechanisms underlying neurodevelopmental conditions such as autism spectrum disorders have been studied intensively for decades. The ability to generate patient-specific induced pluripotent stem cells (iPSCs) now offers a novel strategy for modelling human diseases. Recent studies have reported the derivation of iPSCs from patients with neurological disorders. The key challenge remains the demonstration of disease-related phenotypes and the ability to model the disease. Here we report a case study with signs of neurodevelopmental disorders (NDDs) harbouring chromosomal rearrangements that were sequenced using long-insert DNA paired-end tag (DNA-PET) sequencing approach. We identified the disruption of a specific gene, GTDC1. By deriving iPSCs from this patient and differentiating them into neural progenitor cells (NPCs) and neurons we dissected the disease process at the cellular level and observed defects in both NPCs and neuronal cells. We also showed that disruption of GTDC1 expression in wild type human NPCs and neurons showed a similar phenotype as patient's iPSCs. Finally, we utilized a zebrafish model to demonstrate a role for GTDC1 in the development of the central nervous system. Our findings highlight the importance of combining sequencing technologies with the iPSC technology for NDDs modelling that could be applied for personalized medicine.

Global analysis of somatic structural genomic alterations and their impact on gene expression in diverse human cancers

Tumor genomes are mosaics of somatic structural variants (SVs) that may contribute to the activation of oncogenes or inactivation of tumor suppressors, for example, by altering gene copy number amplitude. However, there are multiple other ways in which SVs can modulate transcription, but the general impact of such events on tumor transcriptional output has not been systematically determined. Here we use whole-genome sequencing data to map SVs across 600 tumors and 18 cancers, and investigate the relationship between SVs, copy number alterations (CNAs), and mRNA expression. We find that 34% of CNA breakpoints can be clarified structurally and that most amplifications are due to tandem duplications. We observe frequent swapping of strong and weak promoters in the context of gene fusions, and find that this has a measurable global impact on mRNA levels. Interestingly, several long noncoding RNAs were strongly activated by this mechanism. Additionally, SVs were confirmed in telomere reverse transcriptase (TERT) upstream regions in several cancers, associated with elevated TERT mRNA levels. We also highlight high-confidence gene fusions supported by both genomic and transcriptomic evidence, including a previously undescribed paired box 8 (PAX8)-nuclear factor, erythroid 2 like 2 (NFE2L2) fusion in thyroid carcinoma. In summary, we combine SV, CNA, and expression data to provide insights into the structural basis of CNAs as well as the impact of SVs on gene expression in tumors.

TP53 intron 1 hotspot rearrangements are specific to sporadic osteosarcoma and can cause Li-Fraumeni syndrome

Somatic mutations of TP53 are among the most common in cancer and germline mutations of TP53 (usually missense) can cause Li-Fraumeni syndrome (LFS). Recently, recurrent genomic rearrangements in intron 1 of TP53 have been described in osteosarcoma (OS), a highly malignant neoplasm of bone belonging to the spectrum of LFS tumors. Using whole-genome sequencing of OS, we found features of TP53 intron 1 rearrangements suggesting a unique mechanism correlated with transcription. Screening of 288 OS and 1,090 tumors of other types revealed evidence for TP53 rearrangements in 46 (16%) OS, while none were detected in other tumor types, indicating this rearrangement to be highly specific to OS. We revisited a four-generation LFS family where no TP53 mutation had been identified and found a 445 kb inversion spanning from the TP53 intron 1 towards the centromere. The inversion segregated with tumors in the LFS family. Cancers in this family had loss of heterozygosity, retaining the rearranged allele and resulting in TP53 expression loss. In conclusion, intron 1 rearrangements cause p53-driven malignancies by both germline and somatic mechanisms and provide an important mechanism of TP53 inactivation in LFS, which might in part explain the diagnostic gap of formerly classified “TP53 wild-type” LFS.

The tandem duplicator phenotype as a distinct genomic configuration in cancer

Next-generation sequencing studies have revealed genome-wide structural variation patterns in cancer, such as chromothripsis and chromoplexy, that do not engage a single discernable driver mutation, and whose clinical relevance is unclear. We devised a robust genomic metric able to identify cancers with a chromotype called tandem duplicator phenotype (TDP) characterized by frequent and distributed tandem duplications (TDs). Enriched only in triple-negative breast cancer (TNBC) and in ovarian, endometrial, and liver cancers, TDP tumors conjointly exhibit tumor protein p53 (TP53) mutations, disruption of breast cancer 1 (BRCA1), and increased expression of DNA replication genes pointing at rereplication in a defective checkpoint environment as a plausible causal mechanism. The resultant TDs in TDP augment global oncogene expression and disrupt tumor suppressor genes. Importantly, the TDP strongly correlates with cisplatin sensitivity in both TNBC cell lines and primary patient-derived xenografts. We conclude that the TDP is a common cancer chromotype that coordinately alters oncogene/tumor suppressor expression with potential as a marker for chemotherapeutic response.

Translating genomic research into clinical practice: promise and pitfalls

Breast cancer is a heterogeneous disease associated with variable clinical outcomes despite standard local therapy for the primary tumor and systemic adjuvant therapy to prevent distant recurrence. Management decisions are typically made using classical prognostic and predictive clinicopathologic factors, and more recently gene expression profiling assays are commonly used in practice. Recent advances in genomic sequencing-often referred to collectively as next-generation sequencing (NGS)-have facilitated more in-depth evaluation of the cancer genome than could be afforded by the initial generation of gene expression studies, including DNA single nucleotide variants, small insertions and deletions, structural alterations, and copy number alterations (CNAs). In addition, this information has been integrated with other molecular profiling methods of processes that affect gene transcription (e.g., epigenetic, microRNA) and protein expression-the ultimate readout of the genetic code. Although NGS has provided new insights on the classification of breast cancer and identified potential predictive biomarkers and novel targets, there are formidable logistical and scientific obstacles that must be addressed before the promise of this technology is fully realized.

Many obesity-associated SNPs strongly associate with DNA methylation changes at proximal promoters and enhancers

BACKGROUND

The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles.

METHODS

We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n = 121-133) and an additional dataset in subcutaneous and visceral fat (n = 149).

RESULTS

We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts.

CONCLUSIONS

Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits.

Acute Sleep Loss Induces Tissue-Specific Epigenetic and Transcriptional Alterations to Circadian Clock Genes in Men

CONTEXT

Shift workers are at increased risk of metabolic morbidities. Clock genes are known to regulate metabolic processes in peripheral tissues, eg, glucose oxidation.

OBJECTIVE

This study aimed to investigate how clock genes are affected at the epigenetic and transcriptional level in peripheral human tissues following acute total sleep deprivation (TSD), mimicking shift work with extended wakefulness.

INTERVENTION

In a randomized, two-period, two-condition, crossover clinical study, 15 healthy men underwent two experimental sessions: x sleep (2230-0700 h) and overnight wakefulness. On the subsequent morning, serum cortisol was measured, followed by skeletal muscle and subcutaneous adipose tissue biopsies for DNA methylation and gene expression analyses of core clock genes (BMAL1, CLOCK, CRY1, PER1). Finally, baseline and 2-h post-oral glucose load plasma glucose concentrations were determined.

MAIN OUTCOME MEASURES

In adipose tissue, acute sleep deprivation vs sleep increased methylation in the promoter of CRY1 (+4%; P = .026) and in two promoter-interacting enhancer regions of PER1 (+15%; P = .036; +9%; P = .026). In skeletal muscle, TSD vs sleep decreased gene expression of BMAL1 (-18%; P = .033) and CRY1 (-22%; P = .047). Concentrations of serum cortisol, which can reset peripheral tissue clocks, were decreased (2449 ± 932 vs 3178 ± 723 nmol/L; P = .039), whereas postprandial plasma glucose concentrations were elevated after TSD (7.77 ± 1.63 vs 6.59 ± 1.32 mmol/L; P = .011).

CONCLUSIONS

Our findings demonstrate that a single night of wakefulness can alter the epigenetic and transcriptional profile of core circadian clock genes in key metabolic tissues. Tissue-specific clock alterations could explain why shift work may disrupt metabolic integrity as observed herein.

Contralateral breast cancer can represent a metastatic spread of the first primary tumor: determination of clonal relationship between contralateral breast cancers using next-generation whole genome sequencing

INTRODUCTION

By convention, a contralateral breast cancer (CBC) is treated as a new primary tumor, independent of the first cancer (BC1). Although there have been indications that the second tumor (BC2) sometimes may represent a metastatic spread of BC1, this has never been conclusively shown. We sought to apply next-generation sequencing to determine a "genetic barcode" for each tumor and reveal the clonal relationship of CBCs.

METHODS

Ten CBC patients with detailed clinical information and available fresh frozen tumor tissue were studied. Using low-coverage whole genome DNA-sequencing data for each tumor, chromosomal rearrangements were enumerated and copy number profiles were generated. Comparisons between tumors provided an estimate of clonal relatedness for tumor pairs within individual patients.

RESULTS

Between 15-256 rearrangements were detected in each tumor (median 87). For one patient, 76 % (68 out of 90) of the rearrangements were shared between BC1 and BC2, highly consistent with what has been seen for true primary-metastasis pairs (>50 %) and thus confirming a common clonal origin of the two tumors. For most of the remaining cases, BC1 and BC2 had similarly low overlap as unmatched randomized pairs of tumors from different individuals, suggesting the CBC to represent a new independent primary tumor.

CONCLUSION

Using rearrangement fingerprinting, we show for the first time with certainty that a contralateral BC2 can represent a metastatic spread of BC1. Given the poor prognosis of a generalized disease compared to a new primary tumor, these women need to be identified at diagnosis of CBC for appropriate determination of treatment. Our approach generates a promising new method to assess clonal relationship between tumors. Additional studies are required to confirm the frequency of CBCs representing metastatic events.

Integrated sequence and expression analysis of ovarian cancer structural variants underscores the importance of gene fusion regulation

Background

Genomic rearrangements or structural variants (SVs) are one of the most common classes of mutations in cancer.

Methods

An integrated DNA sequencing and transcriptional profiling (RNA sequence and microarray gene expression data) analysis was performed on six ovarian cancer patient samples. Matched sets of control (whole blood) samples from these same patients were used to distinguish cancer SVs of germline origin from those arising somatically in the cancer cell lineage.

Results

We detected 10,034 ovarian cancer SVs (5518 germline derived; 4516 somatically derived) at base-pair level resolution. Only 11 % of these variants were shown to have the potential to form gene fusions and, of these, less than 20 % were detected at the transcriptional level.

Conclusions

Collectively our results are consistent with the view that gene fusions and other SVs can be significant factors in the onset and progression of ovarian cancer. The results further indicate that it may not only be the occurrence of these variants in cancer but their regulation that contributes to their biological and clinical significance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0118-9) contains supplementary material, which is available to authorized users.

The Obesity-Linked Gene Nudt3 Drosophila Homolog Aps Is Associated With Insulin Signaling

Several genome-wide association studies have linked the Nudix hydrolase family member nucleoside diphosphate-linked moiety X motif 3 (NUDT3) to obesity. However, the manner of NUDT3 involvement in obesity is unknown, and NUDT3 expression, regulation, and signaling in the central nervous system has not been studied. We performed an extensive expression analysis in mice, as well as knocked down the Drosophila NUDT3 homolog Aps in the nervous system, to determine its effect on metabolism. Detailed in situ hybridization studies in the mouse brain revealed abundant Nudt3 mRNA and protein expression throughout the brain, including reward- and feeding-related regions of the hypothalamus and amygdala, whereas Nudt3 mRNA expression was significantly up-regulated in the hypothalamus and brainstem of food-deprived mice. Knocking down Aps in the Drosophila central nervous system, or a subset of median neurosecretory cells, known as the insulin-producing cells (IPCs), induces hyperinsulinemia-like phenotypes, including a decrease in circulating trehalose levels as well as significantly decreasing all carbohydrate levels under starvation conditions. Moreover, lowering Aps IPC expression leads to a decreased ability to recruit these lipids during starvation. Also, loss of neuronal Aps expression caused a starvation susceptibility phenotype while inducing hyperphagia. Finally, the loss of IPC Aps lowered the expression of Akh, Ilp6, and Ilp3, genes known to be inhibited by insulin signaling. These results point toward a role for this gene in the regulation of insulin signaling, which could explain the robust association with obesity in humans.

Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed.

The Diverse Effects of Complex Chromosome Rearrangements and Chromothripsis in Cancer Development

In recent years, enormous progress has been made with respect to the identification of somatic mutations that contribute to cancer development. Mutation types range from small substitutions to large structural genomic rearrangements, including complex reshuffling of the genome. Sets of mutations in individual cancer genomes may show specific signatures, which can be provoked by both exogenous and endogenous forces. One of the most remarkable mutation patterns observed in human cancers involve massive rearrangement of just a few chromosomal regions. This phenomenon has been termed chromothripsis and appears widespread in a multitude of cancer types. Chromothripsis provides a way for cancer to rapidly evolve through a one-off massive change in genome structure as opposed to a gradual process of mutation and selection. This chapter focuses on the origin, prevalence and impact of chromothripsis and related complex genomic rearrangements during cancer development.

Comprehensive characterization of the genomic alterations in human gastric cancer

Gastric cancer is one of the most prevalent and aggressive cancers worldwide, and its molecular mechanism remains largely elusive. Here we report the genomic landscape in primary gastric adenocarcinoma of human, based on the complete genome sequences of five pairs of cancer and matching normal samples. In total, 103,464 somatic point mutations, including 407 nonsynonymous ones, were identified and the most recurrent mutations were harbored by Mucins (MUC3A and MUC12) and transcription factors (ZNF717, ZNF595 and TP53). 679 genomic rearrangements were detected, which affect 355 protein-coding genes; and 76 genes show copy number changes. Through mapping the boundaries of the rearranged regions to the folded three-dimensional structure of human chromosomes, we determined that 79.6% of the chromosomal rearrangements happen among DNA fragments in close spatial proximity, especially when two endpoints stay in a similar replication phase. We demonstrated evidences that microhomology-mediated break-induced replication was utilized as a mechanism in inducing ∼40.9% of the identified genomic changes in gastric tumor. Our data analyses revealed potential integrations of Helicobacter pylori DNA into the gastric cancer genomes. Overall a large set of novel genomic variations were detected in these gastric cancer genomes, which may be essential to the study of the genetic basis and molecular mechanism of the gastric tumorigenesis.

Functional chromatin features are associated with structural mutations in cancer

BACKGROUND

Structural mutations (SMs) play a major role in cancer development. In some cancers, such as breast and ovarian, DNA double-strand breaks (DSBs) occur more frequently in transcribed regions, while in other cancer types such as prostate, there is a consistent depletion of breakpoints in transcribed regions. Despite such regularity, little is understood about the mechanisms driving these effects. A few works have suggested that protein binding may be relevant, e.g. in studies of androgen receptor binding and active chromatin in specific cell types. We hypothesized that this behavior might be general, i.e. that correlation between protein-DNA binding (and open chromatin) and breakpoint locations is common across divergent cancers.

RESULTS

We investigated this hypothesis by comprehensively analyzing the relationship among 457 ENCODE protein binding ChIP-seq experiments, 125 DnaseI and 24 FAIRE experiments, and 14,600 SMs from 8 diverse cancer datasets covering 147 samples. In most cancers, including breast and ovarian, we found enrichment of protein binding and open chromatin in the vicinity of SM breakpoints at distances up to 200 kb. Furthermore, for all cancer types we observed an enhanced enrichment in regions distant from genes when compared to regions proximal to genes, suggesting that the SM-induction mechanism is independent from the bias of DSBs to occur near transcribed regions. We also observed a stronger effect for sites with more than one protein bound.

CONCLUSIONS

Protein binding and open chromatin state are associated with nearby SM breakpoints in many cancer datasets. These observations suggest a consistent mechanism underlying SM locations across different cancers.

Systems consequences of amplicon formation in human breast cancer

Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. In a detailed reconstruction of events on chromosome 17, we found large unpaired inversions and deletions connect a tandemly duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. This series of events appeared to be unusually common when examined in larger genomic data sets of breast cancers albeit using approaches with lesser resolution. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently coamplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in ERBB2-transfected human normal mammary epithelial cells. Coamplification of other functionally tested oncogenic elements in other breast tumors examined, such as RIPK2 and MYC on chromosome 8, also parallel these findings. Our analyses suggest that structural variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.

A workflow to increase verification rate of chromosomal structural rearrangements using high-throughput next-generation sequencing

Somatic rearrangements, which are commonly found in human cancer genomes, contribute to the progression and maintenance of cancers. Conventionally, the verification of somatic rearrangements comprises many manual steps and Sanger sequencing. This is labor intensive when verifying a large number of rearrangements in a large cohort. To increase the verification throughput, we devised a high-throughput workflow that utilizes benchtop next-generation sequencing and in-house bioinformatics tools to link the laboratory processes. In the proposed workflow, primers are automatically designed. PCR and an optional gel electrophoresis step to confirm the somatic nature of the rearrangements are performed. PCR products of somatic events are pooled for Ion Torrent PGM and/or Illumina MiSeq sequencing, the resulting sequence reads are assembled into consensus contigs by a consensus assembler, and an automated BLAT is used to resolve the breakpoints to base level. We compared sequences and breakpoints of verified somatic rearrangements between the conventional and high-throughput workflow. The results showed that next-generation sequencing methods are comparable to conventional Sanger sequencing. The identified breakpoints obtained from next-generation sequencing methods were highly accurate and reproducible. Furthermore, the proposed workflow allows hundreds of events to be processed in a shorter time frame compared with the conventional workflow.

GAP-Seq: a method for identification of DNA palindromes

BACKGROUND

Closely spaced long inverted repeats, also known as DNA palindromes, can undergo intrastrand annealing to form DNA hairpins. The ability to form these hairpins results in genome instability, difficulties in maintaining clones in Escherichia coli and major problems for most DNA sequencing approaches. Because of their role in genomic instability and gene amplification in some human cancers, it is important to develop systematic approaches to detect and characterize DNA palindromes.

RESULTS

We developed a new protocol to identify palindromes that couples the S1 nuclease treated Cot0 DNA (GAPF) with high-throughput sequencing (GAP-Seq). Unlike earlier protocols, it does not involve restriction enzymatic digestion prior to DNA snap-back thereby preserving longer DNA sequences. It also indicates the location of the novel junction, which can then be recovered. Using MCF-7 breast cancer cell line as the proof-of-principle analysis, we have identified 35 palindrome candidates and physically characterized the top 5 candidates and their junctions. Because this protocol eliminates many of the false positives that plague earlier techniques, we have improved palindrome identification.

CONCLUSIONS

The GAP-Seq approach underscores the importance of developing new tools for identifying and characterizing palindromes, and provides a new strategy to systematically assess palindromes in genomes. It will be useful for studying human cancers and other diseases associated with palindromes.

Detection of chromosomal breakpoints in patients with developmental delay and speech disorders

Delineating candidate genes at the chromosomal breakpoint regions in the apparently balanced chromosome rearrangements (ABCR) has been shown to be more effective with the emergence of next-generation sequencing (NGS) technologies. We employed a large-insert (7-11 kb) paired-end tag sequencing technology (DNA-PET) to systematically analyze genome of four patients harbouring cytogenetically defined ABCR with neurodevelopmental symptoms, including developmental delay (DD) and speech disorders. We characterized structural variants (SVs) specific to each individual, including those matching the chromosomal breakpoints. Refinement of these regions by Sanger sequencing resulted in the identification of five disrupted genes in three individuals: guanine nucleotide binding protein, q polypeptide (GNAQ), RNA-binding protein, fox-1 homolog (RBFOX3), unc-5 homolog D (C.elegans) (UNC5D), transmembrane protein 47 (TMEM47), and X-linked inhibitor of apoptosis (XIAP). Among them, XIAP is the causative gene for the immunodeficiency phenotype seen in the patient. The remaining genes displayed specific expression in the fetal brain and have known biologically relevant functions in brain development, suggesting putative candidate genes for neurodevelopmental phenotypes. This study demonstrates the application of NGS technologies in mapping individual gene disruptions in ABCR as a resource for deciphering candidate genes in human neurodevelopmental disorders (NDDs).

Dissecting the chromatin interactome of microRNA genes

Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes. RNA polymerase II-associated ChIA-PET data reveal that many groups of MIRs and protein-coding genes are organized into functionally compartmentalized chromatin communities and undergo coordinated expression when their genomic loci are spatially colocated. We observe that MIRs display widespread communication in those transcriptionally active communities. Moreover, miRNA-target interactions are significantly enriched among communities with functional homogeneity while depleted from the same community from which they originated, suggesting MIRs coordinating function-related pathways at posttranscriptional level. Further investigation demonstrates the existence of spatial MIR-MIR chromatin interacting networks. We show that groups of spatially coordinated MIRs are frequently from the same family and involved in the same disease category. The spatial interaction network possesses both common and cell-specific subnetwork modules that result from the spatial organization of chromatin within different cell types. Together, our study unveils an entirely unexplored layer of MIR regulation throughout the human genome that links the spatial coordination of MIRs to their co-expression and function.

Discovery of recurrent structural variants in nasopharyngeal carcinoma

We present the discovery of genes recurrently involved in structural variation in nasopharyngeal carcinoma (NPC) and the identification of a novel type of somatic structural variant. We identified the variants with high complexity mate-pair libraries and a novel computational algorithm specifically designed for tumor-normal comparisons, SMASH. SMASH combines signals from split reads and mate-pair discordance to detect somatic structural variants. We demonstrate a >90% validation rate and a breakpoint reconstruction accuracy of 3 bp by Sanger sequencing. Our approach identified three in-frame gene fusions (YAP1-MAML2, PTPLB-RSRC1, and SP3-PTK2) that had strong levels of expression in corresponding NPC tissues. We found two cases of a novel type of structural variant, which we call “coupled inversion,” one of which produced the YAP1-MAML2 fusion. To investigate whether the identified fusion genes are recurrent, we performed fluorescent in situ hybridization (FISH) to screen 196 independent NPC cases. We observed recurrent rearrangements of MAML2 (three cases), PTK2 (six cases), and SP3 (two cases), corresponding to a combined rate of structural variation recurrence of 6% among tested NPC tissues.

Genome-wide analysis of HPV integration in human cancers reveals recurrent, focal genomic instability

Genomic instability is a hallmark of human cancers, including the 5% caused by human papillomavirus (HPV). Here we report a striking association between HPV integration and adjacent host genomic structural variation in human cancer cell lines and primary tumors. Whole-genome sequencing revealed HPV integrants flanking and bridging extensive host genomic amplifications and rearrangements, including deletions, inversions, and chromosomal translocations. We present a model of “looping” by which HPV integrant-mediated DNA replication and recombination may result in viral–host DNA concatemers, frequently disrupting genes involved in oncogenesis and amplifying HPV oncogenes E6 and E7. Our high-resolution results shed new light on a catastrophic process, distinct from chromothripsis and other mutational processes, by which HPV directly promotes genomic instability.

Mate pair sequencing for the detection of chromosomal aberrations in patients with intellectual disability and congenital malformations

Recently, microarrays have replaced karyotyping as a first tier test in patients with idiopathic intellectual disability and/or multiple congenital abnormalities (ID/MCA) in many laboratories. Although in about 14-18% of such patients, DNA copy-number variants (CNVs) with clinical significance can be detected, microarrays have the disadvantage of missing balanced rearrangements, as well as providing no information about the genomic architecture of structural variants (SVs) like duplications and complex rearrangements. Such information could possibly lead to a better interpretation of the clinical significance of the SV. In this study, the clinical use of mate pair next-generation sequencing was evaluated for the detection and further characterization of structural variants within the genomes of 50 ID/MCA patients. Thirty of these patients carried a chromosomal aberration that was previously detected by array CGH or karyotyping and suspected to be pathogenic. In the remaining 20 patients no causal SVs were found and only benign aberrations were detected by conventional techniques. Combined cluster and coverage analysis of the mate pair data allowed precise breakpoint detection and further refinement of previously identified balanced and (complex) unbalanced aberrations, pinpointing the causal gene for some patients. We conclude that mate pair sequencing is a powerful technology that can provide rapid and unequivocal characterization of unbalanced and balanced SVs in patient genomes and can be essential for the clinical interpretation of some SVs.

Homology-mediated end-capping as a primary step of sister chromatid fusion in the breakage-fusion-bridge cycles

Breakage-fusion-bridge (BFB) cycle is a series of chromosome breaks and duplications that could lead to the increased copy number of a genomic segment (gene amplification). A critical step of BFB cycles leading to gene amplification is a palindromic fusion of sister chromatids following the rupture of a dicentric chromosome during mitosis. It is currently unknown how sister chromatid fusion is produced from a mitotic break. To delineate the process, we took an integrated genomic, cytogenetic and molecular approach for the recurrent MCL1 amplicon at chromosome 1 in human tumor cells. A newly developed next-generation sequencing-based approach identified a cluster of palindromic fusions within the amplicon at ∼50-kb intervals, indicating a series of breaks and fusions by BFB cycles. The physical location of the amplicon (at the end of a broken chromosome) further indicated BFB cycles as underlying processes. Three palindromic fusions were mediated by the homologies between two nearby inverted Alu repeats, whereas the other two fusions exhibited microhomology-mediated events. Such breakpoint sequences indicate that homology-mediated fold-back capping of broken ends followed by DNA replication is an underlying mechanism of sister chromatid fusion. Our results elucidate nucleotide-level events during BFB cycles and end processing for naturally occurring mitotic breaks.

Diverse mechanisms of somatic structural variations in human cancer genomes

Identification of somatic rearrangements in cancer genomes has accelerated through analysis of high-throughput sequencing data. However, characterization of complex structural alterations and their underlying mechanisms remains inadequate. Here, applying an algorithm to predict structural variations from short reads, we report a comprehensive catalog of somatic structural variations and the mechanisms generating them, using high-coverage whole-genome sequencing data from 140 patients across ten tumor types. We characterize the relative contributions of different types of rearrangements and their mutational mechanisms, find that ~20% of the somatic deletions are complex deletions formed by replication errors, and describe the differences between the mutational mechanisms in somatic and germline alterations. Importantly, we provide detailed reconstructions of the events responsible for loss of CDKN2A/B and gain of EGFR in glioblastoma, revealing that these alterations can result from multiple mechanisms even in a single genome and that both DNA double-strand breaks and replication errors drive somatic rearrangements.

TPD52 represents a survival factor in ERBB2-amplified breast cancer cells

TPD52 and ERBB2 co-expression has been persistently reported in human breast cancer and animal models of this disease, but the significance of this is unknown. We identified significant positive associations between relative TPD52 and ERBB2 transcript levels in human diagnostic breast cancer samples, and maximal TPD52 expression in the hormone receptor (HR)- and ERBB2-positive sub-group. High-level TPD52 expression was associated with significantly reduced metastasis-free survival, within the overall cohort (log rank test, P = 8.6 × 10(-4), n = 375) where this was an independent predictor of metastasis-free survival (hazard ratio, 2.69, 95% confidence interval 1.59-4.54, P = 2.2 × 10(-4), n = 359), and the HR- and ERBB2-positive sub-group (log rank test, P = 0.035, n = 47). Transient TPD52 knock-down in the ERBB2-amplified breast cancer cell lines SK-BR-3 and BT-474 produced significant apoptosis, both singly and in combination with transient ERBB2 knock-down. Unlike ERBB2 knock-down, transient TPD52 knock-down produced no reduction in pAKT levels in SK-BR-3 or BT-474 cells. We then derived multiple SK-BR-3 cell lines in which TPD52 levels were stably reduced, and measured significant inverse correlations between pERBB2 and TPD52 levels in viable TPD52-depleted and control cell lines, all of which showed similar proliferative capacities. Our results therefore identify TPD52 as a survival factor in ERBB2-amplified breast cancer cells, and suggest complementary cellular functions for TPD52 and ERBB2.

On the power and the systematic biases of the detection of chromosomal inversions by paired-end genome sequencing

One of the most used techniques to study structural variation at a genome level is paired-end mapping (PEM). PEM has the advantage of being able to detect balanced events, such as inversions and translocations. However, inversions are still quite difficult to predict reliably, especially from high-throughput sequencing data. We simulated realistic PEM experiments with different combinations of read and library fragment lengths, including sequencing errors and meaningful base-qualities, to quantify and track down the origin of false positives and negatives along sequencing, mapping, and downstream analysis. We show that PEM is very appropriate to detect a wide range of inversions, even with low coverage data. However, ≥% of inversions located between segmental duplications are expected to go undetected by the most common sequencing strategies. In general, longer DNA libraries improve the detectability of inversions far better than increments of the coverage depth or the read length. Finally, we review the performance of three algorithms to detect inversions--SVDetect, GRIAL, and VariationHunter--, identify common pitfalls, and reveal important differences in their breakpoint precisions. These results stress the importance of the sequencing strategy for the detection of structural variants, especially inversions, and offer guidelines for the design of future genome sequencing projects.

Improving mammalian genome scaffolding using large insert mate-pair next-generation sequencing

Background

Paired-tag sequencing approaches are commonly used for the analysis of genome structure. However, mammalian genomes have a complex organization with a variety of repetitive elements that complicate comprehensive genome-wide analyses.

Results

Here, we systematically assessed the utility of paired-end and mate-pair (MP) next-generation sequencing libraries with insert sizes ranging from 170 bp to 25 kb, for genome coverage and for improving scaffolding of a mammalian genome (Rattus norvegicus). Despite a lower library complexity, large insert MP libraries (20 or 25 kb) provided very high physical genome coverage and were found to efficiently span repeat elements in the genome. Medium-sized (5, 8 or 15 kb) MP libraries were much more efficient for genome structure analysis than the more commonly used shorter insert paired-end and 3 kb MP libraries. Furthermore, the combination of medium- and large insert libraries resulted in a 3-fold increase in N50 in scaffolding processes. Finally, we show that our data can be used to evaluate and improve contig order and orientation in the current rat reference genome assembly.

Conclusions

We conclude that applying combinations of mate-pair libraries with insert sizes that match the distributions of repetitive elements improves contig scaffolding and can contribute to the finishing of draft genomes.

An algorithmic approach for breakage-fusion-bridge detection in tumor genomes

Breakage-fusion-bridge (BFB) is a mechanism of genomic instability characterized by the joining and subsequent tearing apart of sister chromatids. When this process is repeated during multiple rounds of cell division, it leads to patterns of copy number increases of chromosomal segments as well as fold-back inversions where duplicated segments are arranged head-to-head. These structural variations can then drive tumorigenesis. BFB can be observed in progress using cytogenetic techniques, but generally BFB must be inferred from data such as microarrays or sequencing collected after BFB has ceased. Making correct inferences from this data is not straightforward, particularly given the complexity of some cancer genomes and BFB's ability to generate a wide range of rearrangement patterns. Here we present algorithms to aid the interpretation of evidence for BFB. We first pose the BFB count-vector problem: given a chromosome segmentation and segment copy numbers, decide whether BFB can yield a chromosome with the given segment counts. We present a linear time algorithm for the problem, in contrast to a previous exponential time algorithm. We then combine this algorithm with fold-back inversions to develop tests for BFB. We show that, contingent on assumptions about cancer genome evolution, count vectors and fold-back inversions are sufficient evidence for detecting BFB. We apply the presented techniques to paired-end sequencing data from pancreatic tumors and confirm a previous finding of BFB as well as identify a chromosomal region likely rearranged by BFB cycles, demonstrating the practicality of our approach.

Breakpoint profiling of 64 cancer genomes reveals numerous complex rearrangements spawned by homology-independent mechanisms

Tumor genomes are generally thought to evolve through a gradual accumulation of mutations, but the observation that extraordinarily complex rearrangements can arise through single mutational events suggests that evolution may be accelerated by punctuated changes in genome architecture. To assess the prevalence and origins of complex genomic rearrangements (CGRs), we mapped 6179 somatic structural variation breakpoints in 64 cancer genomes from seven tumor types and screened for clusters of three or more interconnected breakpoints. We find that complex breakpoint clusters are extremely common: 154 clusters comprise 25% of all somatic breakpoints, and 75% of tumors exhibit at least one complex cluster. Based on copy number state profiling, 63% of breakpoint clusters are consistent with being CGRs that arose through a single mutational event. CGRs have diverse architectures including focal breakpoint clusters, large-scale rearrangements joining clusters from one or more chromosomes, and staggeringly complex chromothripsis events. Notably, chromothripsis has a significantly higher incidence in glioblastoma samples (39%) relative to other tumor types (9%). Chromothripsis breakpoints also show significantly elevated intra-tumor allele frequencies relative to simple SVs, which indicates that they arise early during tumorigenesis or confer selective advantage. Finally, assembly and analysis of 4002 somatic and 6982 germline breakpoint sequences reveal that somatic breakpoints show significantly less microhomology and fewer templated insertions than germline breakpoints, and this effect is stronger at CGRs than at simple variants. These results are inconsistent with replication-based models of CGR genesis and strongly argue that nonhomologous repair of concurrently arising DNA double-strand breaks is the predominant mechanism underlying complex cancer genome rearrangements.

High-throughput sequencing for biology and medicine

Advances in genome sequencing have progressed at a rapid pace, with increased throughput accompanied by plunging costs. But these advances go far beyond faster and cheaper. High-throughput sequencing technologies are now routinely being applied to a wide range of important topics in biology and medicine, often allowing researchers to address important biological questions that were not possible before. In this review, we discuss these innovative new approaches-including ever finer analyses of transcriptome dynamics, genome structure and genomic variation-and provide an overview of the new insights into complex biological systems catalyzed by these technologies. We also assess the impact of genotyping, genome sequencing and personal omics profiling on medical applications, including diagnosis and disease monitoring. Finally, we review recent developments in single-cell sequencing, and conclude with a discussion of possible future advances and obstacles for sequencing in biology and health.

Whole-genome reconstruction and mutational signatures in gastric cancer

Background

Gastric cancer is the second highest cause of global cancer mortality. To explore the complete repertoire of somatic alterations in gastric cancer, we combined massively parallel short read and DNA paired-end tag sequencing to present the first whole-genome analysis of two gastric adenocarcinomas, one with chromosomal instability and the other with microsatellite instability.

Results

Integrative analysis and de novo assemblies revealed the architecture of a wild-type KRAS amplification, a common driver event in gastric cancer. We discovered three distinct mutational signatures in gastric cancer - against a genome-wide backdrop of oxidative and microsatellite instability-related mutational signatures, we identified the first exome-specific mutational signature. Further characterization of the impact of these signatures by combining sequencing data from 40 complete gastric cancer exomes and targeted screening of an additional 94 independent gastric tumors uncovered ACVR2A, RPL22 and LMAN1 as recurrently mutated genes in microsatellite instability-positive gastric cancer and PAPPA as a recurrently mutated gene in TP53 wild-type gastric cancer.

Conclusions

These results highlight how whole-genome cancer sequencing can uncover information relevant to tissue-specific carcinogenesis that would otherwise be missed from exome-sequencing data.

Large-scale functional organization of long-range chromatin interaction networks

Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic through evolution. Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the least-evolving key genomic domains against random genetic or transcriptional errors in the genome. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions.

Capturing native long-range contiguity by in situ library construction and optical sequencing

The relatively short read lengths associated with the most cost-effective DNA sequencing technologies have limited their use in de novo genome assembly, structural variation detection, and haplotype-resolved genome sequencing. Consequently, there is a strong need for methods that capture various scales of contiguity information at a throughput commensurate with the current scale of massively parallel sequencing. We propose in situ library construction and optical sequencing on the flow cells of currently available massively parallel sequencing platforms as an efficient means of capturing both contiguity information and primary sequence with a single technology. In this proof-of-concept study, we demonstrate basic feasibility by generating >30,000 Escherichia coli paired-end reads separated by 1, 2, or 3 kb using in situ library construction on standard Illumina flow cells. We also show that it is possible to stretch single molecules ranging from 3 to 8 kb on the surface of a flow cell before in situ library construction, thereby enabling the production of clusters whose physical relationship to one another on the flow cell is related to genomic distance.