A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan

Abstract Background: Thyrotrophinoma (TSHoma) is rare and knowledge on the genomic landscape of this tumour type is very limited. Aim: To perform whole-exome sequencing (WES) in a population of TSHomas to identify recurrent somatic genetic events Method: WES was performed on paired tumour and germline DNA of 7 patients with TSHomas. Three tissue samples were formalin-fixed paraffin-embedded and 4 fresh frozen tumour samples. Fresh blood samples were also collected from each patient. The average of mean depth of coverage amongst all samples was 129X, and 97% of target bases were covered ≥20X. Results:Four (57%) of the seven patients were male and median age at diagnosis was 52 years. (IQR 46, 60) Six patients (86%) had macroadenomas. Four patients (57%) had central thyrotoxicosis at diagnosis and three patients’ tumour stained positive for TSH on histology examination. Two patients (29%) had growth hormone co-secreting tumours. In total, 69 somatic variants were identified to be of potential interest, averaging 1.4 variants per million base-pair of DNA read. No variants were observed in more than one individual. According to the GTEx database, 9 of 69 genes (DRC3, HDAC5, KDM1A, POLR21, TCF25, THAP7, TTC13, UNC5D, UNC13A) were highly expressed in the pituitary (top 10%). Four of these genes appear to contribute to tumour development via epigenetic pathway. Specifically, three of these genes (HDAC5, KDM1A, THAP7) either interact with or form part of histone deacetylases whilst POLR21 encodes a subunit of RNA polymerase II which is responsible for mRNA synthesis. On the other hand, TCF25 gene is thought to act as transcriptional repressor and UNC5D plays a role in cell-cell adhesion. Large scale copy number variations involving gain or loss of whole chromosome or chromosome (chr) arm were observed in six (86%) tumour samples. Chr 5, 9, 13 and 19 were most commonly affected by chromosomal gains. Deletion of chr 1p was seen in two cases and mutations in KDM1A (p.Glu161fs/c.482_491delAGGAAGAAAA) and ADGRB2 gene (p.Leu1565Gln/c.4694T>A) were found in each of the remaining single copy of chr 1p. ADGRB2 gene is thought to be involved in cell adhesion and angiogenesis inhibition. Copy neutral loss-of-heterozygosity were present in two (29%) of the tumour samples (chr 2 and 12q). However, no somatic mutation was found in these regions. Gene level copy number analysis identified a potential deletion in TTI2 gene which encodes for a regulator in DNA damaging response as well as telomere length regulation. ConclusionOverall, the rate of somatic variant mutations in TSHomas is low, consistent with the relative benign nature of this tumour type. No classical driver mutations were identified by this study however, chromosomal anomalies and epigenetics may play an important part in TSHoma development.

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GSA: An Independent Development Algorithm for Calling Copy Number and Detecting Homologous Recombination Deficiency (HRD) from Target Capture Sequencing

10.1101/2021.08.02.454110 ◽

2021 ◽

Author(s):

Dongju Chen ◽

Minghui Shao ◽

Pei Meng ◽

Chunli Wang ◽

Qi Li ◽

...

Keyword(s):

Homologous Recombination ◽

Copy Number ◽

Large Scale ◽

Parp Inhibitors ◽

Copy Number Variations ◽

Clinical Samples ◽

Real World Data ◽

Homologous Recombination Deficiency ◽

Tumor Purity ◽

Platinum Based Chemotherapy

The gain or loss of large chromosomal regions or even whole chromosomes is termed as genomic scarring and can be observed as copy number variations resulting from the failure of DNA damage repair. Aneuploidy is a common event in cancers, and it may lead to more copy number variation, but not caused by homologous recombination deficiency (HRD). In this study, a new algorithm called Genomic Scar Analysis (GSA) has developed and validated, calculating HRD score, combined with loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transition (LST) scores. The two critical submodules were tree recursion (TR) segmentation and filtering, and the estimation and correction of the tumor purity and ploidy. Then, this study evaluated the rationality of segmentation and genotype identification by the GSA algorithm and compared with other two algorithms, PureCN and ASCAT, found that the segmentation result of GSA algorithm was more logical. In addition, the results indicated that the GSA algorithm had an excellent predictive effect on tumor purity (correlation coefficient R2 were 0.9813 and 0.9812, respectively, in tumor and cell line diluted samples), and more stable ploidy predictors, if the tumor purity was more than 20%. Furtherly, this study evaluated the HRD scores and BRCA1/2 deficiency status of 195 clinical samples, and the results indicated that the accuracy was 0.98 (comparing with Affymetrix OncoScan assay) and the sensitivity was 91.9% (comparing with BRCA1/2 deficiency status), both were well-behaved. Finally, HRD scores and 16 genes mutations (TP53 and 15 HRR pathway genes) were analyzed in 17 cell lines, the results showed that there was higher frequency in HRR pathway genes in high HRD score samples, but it still need more data on the efficacy of PARP inhibitors or platinum-based chemotherapy to validate the accuracy of GSA algorithm in the real-world data.

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Effects of copy number variations on brain structure and risk for psychiatric illness: Large‐scale studies from the ENIGMA working groups on CNVs

Human Brain Mapping ◽

10.1002/hbm.25354 ◽

2021 ◽

Author(s):

Ida E. Sønderby ◽

Christopher R. K. Ching ◽

Sophia I. Thomopoulos ◽

Dennis Meer ◽

Daqiang Sun ◽

...

Keyword(s):

Brain Structure ◽

Copy Number ◽

Psychiatric Illness ◽

Large Scale ◽

Copy Number Variations ◽

Working Groups

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Translational Study of Copy Number Variations in Schizophrenia

International Journal of Molecular Sciences ◽

10.3390/ijms23010457 ◽

2021 ◽

Vol 23 (1) ◽

pp. 457

Author(s):

Min-Chih Cheng ◽

Wei-Hsien Chien ◽

Yu-Shu Huang ◽

Ting-Hsuan Fang ◽

Chia-Hsiang Chen

Keyword(s):

Screening Test ◽

Copy Number ◽

Large Scale ◽

Cost Effective ◽

Copy Number Variations ◽

Chromosomal Microarray ◽

Chromosomal Microarray Analysis ◽

Two Stage ◽

Translational Study ◽

Analysis Group

Rare copy number variations (CNVs) are part of the genetics of schizophrenia; they are highly heterogeneous and personalized. The CNV Analysis Group of the Psychiatric Genomic Consortium (PGC) conducted a large-scale analysis and discovered that recurrent CNVs at eight genetic loci were pathogenic to schizophrenia, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.23, 15q13.3, distal 16p11.2, proximal 16p11.2, and 22q11.2. We adopted a two-stage strategy to translate this knowledge into clinical psychiatric practice. As a screening test, we first developed a real-time quantitative PCR (RT-qPCR) panel that simultaneously detected these pathogenic CNVs. Then, we tested the utility of this screening panel by investigating a sample of 557 patients with schizophrenia. Chromosomal microarray analysis (CMA) was used to confirm positive cases from the screening test. We detected and confirmed thirteen patients who carried CNVs at these hot loci, including two patients at 1q21.1, one patient at 7q11.2, three patients at 15q13.3, two patients at 16p11.2, and five patients at 22q11.2. The detection rate in this sample was 2.3%, and the concordance rate between the RT-qPCR test panel and CMA was 100%. Our results suggest that a two-stage approach is cost-effective and reliable in achieving etiological diagnosis for some patients with schizophrenia and improving the understanding of schizophrenia genetics.

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Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks

10.1101/023010 ◽

2015 ◽

Cited By ~ 3

Author(s):

Endre Sebestyén ◽

Babita Singh ◽

Belén Miñana ◽

Amadís Pagès ◽

Francesca Mateo ◽

...

Keyword(s):

Alternative Splicing ◽

Copy Number ◽

Large Scale ◽

Rna Binding ◽

Rna Binding Proteins ◽

Expression Patterns ◽

Copy Number Variations ◽

Eukaryotic Genes ◽

Cancer Drivers ◽

Tumor Types

AbstractAlternative splicing is regulated by multiple RNA-binding proteins and influences the expression of most eukaryotic genes. However, the role of this process in human disease, and particularly in cancer, is only starting to be unveiled. We systematically analyzed mutation, copy number and gene expression patterns of 1348 RNA-binding protein (RBP) genes in 11 solid tumor types, together with alternative splicing changes in these tumors and the enrichment of binding motifs in the alternatively spliced sequences. Our comprehensive study reveals widespread alterations in the expression of RBP genes, as well as novel mutations and copy number variations in association with multiple alternative splicing changes in cancer drivers and oncogenic pathways. Remarkably, the altered splicing patterns in several tumor types recapitulate those of undifferentiated cells. These patterns are predicted to be mainly controlled by MBNL1 and involve multiple cancer drivers, including the mitotic gene NUMA1. We show that NUMA1 alternative splicing induces enhanced cell proliferation and centrosome amplification in non-tumorigenic mammary epithelial cells. Our study uncovers novel splicing networks that potentially contribute to cancer development and progression.

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Therapeutic Implication of Genomic Landscape of Adult Metastatic Sarcoma

JCO Precision Oncology ◽

10.1200/po.18.00325 ◽

2019 ◽

pp. 1-25 ◽

Cited By ~ 2

Author(s):

Xiaolan Feng ◽

Erin Pleasance ◽

Eric Y. Zhao ◽

Tony Ng ◽

Jasleen K. Grewal ◽

...

Keyword(s):

Copy Number ◽

Large Scale ◽

Therapeutic Potential ◽

Point Mutations ◽

Therapeutic Targets ◽

Genomic Analysis ◽

Copy Number Variations ◽

Cancer Genes ◽

Structural Variations ◽

Metastatic Sarcoma

PURPOSE This study investigated therapeutic potential of integrated genome and transcriptome profiling of metastatic sarcoma, a rare but extremely heterogeneous group of aggressive mesenchymal malignancies with few systemic therapeutic options. METHODS Forty-three adult patients with advanced or metastatic non-GI stromal tumor sarcomas of various histology subtypes who were enrolled in the Personalized OncoGenomics program at BC Cancer were included in this study. Fresh tumor tissues along with blood samples underwent whole-genome and transcriptome sequencing. RESULTS The most frequent genomic alterations in this cohort are large-scale structural variation and somatic copy number variation. Outlier RNA expression as well as somatic copy number variations, structural variations, and small mutations together suggest the presence of one or more potential therapeutic targets in the majority of patients in our cohort. Point mutations or deletions in known targetable cancer genes are rare; for example, tuberous sclerosis complex 2 provides a rationale for targeting the mammalian target of rapamycin pathway, resulting in a few patients with exceptional clinical benefit from everolimus. In addition, we observed recurrent 17p11-12 amplifications, which seem to be a sarcoma-specific event. This may suggest that this region harbors an oncogene(s) that is significant for sarcoma tumorigenesis. Furthermore, some sarcoma tumors carrying a distinct mutational signature suggestive of homologous recombination deficiency seem to demonstrate sensitivity to double-strand DNA–damaging agents. CONCLUSION Integrated large-scale genomic analysis may provide insights into potential therapeutic targets as well as novel biologic features of metastatic sarcomas that could fuel future experimental and clinical research and help design biomarker-driven basket clinical trials for novel therapeutic strategies.

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A genome-wide survey of copy number variations in Han Chinese residing in Taiwan

Genomics ◽

10.1016/j.ygeno.2009.06.004 ◽

2009 ◽

Vol 94 (4) ◽

pp. 241-246 ◽

Cited By ~ 18

Author(s):

Chien-Hsing Lin ◽

Ying-Chao Lin ◽

Jer-Yuarn Wu ◽

Wen-Harn Pan ◽

Yuan-Tsong Chen ◽

...

Keyword(s):

Copy Number ◽

Copy Number Variations ◽

Han Chinese ◽

Genome Wide ◽

A Genome ◽

Genome Wide Survey

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Detection of breed-specific copy number variations in domestic chicken genome

Genome ◽

10.1139/gen-2017-0016 ◽

2018 ◽

Vol 61 (1) ◽

pp. 7-14 ◽

Cited By ~ 7

Author(s):

Saeed S. Sohrabi ◽

Mohammadreza Mohammadabadi ◽

Dong-Dong Wu ◽

Ali Esmailizadeh

Keyword(s):

Copy Number ◽

Egg Production ◽

Large Scale ◽

Chicken Genome ◽

Genomic Structure ◽

Copy Number Variations ◽

Commercial Chicken ◽

Short Read Sequence ◽

Body Organ ◽

The Impact

Copy number variations (CNVs) are important large-scale variants. They are widespread in the genome and may contribute to phenotypic variation. Detection and characterization of CNVs can provide new insights into the genetic basis of important traits. Here, we perform whole-genome short read sequence analysis to identify CNVs in two indigenous and commercial chicken breeds to evaluate the impact of the identified CNVs on breed-specific traits. After filtration, a total of 12 955 CNVs spanning (on average) about 9.42% of the chicken genome were found that made up 5467 CNV regions (CNVRs). Chicken quantitative trait loci (QTL) datasets and Ensembl gene annotations were used as resources for the estimation of potential phenotypic effects of our CNVRs on breed-specific traits. In total, 34% of our detected CNVRs were also detected in earlier CNV studies. These CNVRs partly overlap several previously reported QTL and gene ontology terms associated with some important traits, including shank length QTL in Creeper-specific CNVRs and body weight and egg production characteristics, as well as muscle and body organ growth, in the Arian commercial breed. Our findings provide new insights into the genomic structure of the chicken genome for an improved understanding of the potential roles of CNVRs in differentiating between breeds or lines.

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Minimum Error Calibration and Normalization for Genomic Copy Number Analysis

10.1101/720854 ◽

2019 ◽

Author(s):

Bo Gao ◽

Michael Baudis

Keyword(s):

Copy Number ◽

Large Scale ◽

Tumor Cell Line ◽

Copy Number Variations ◽

The Cancer Genome Atlas ◽

Generation Process ◽

Minimum Error ◽

Genomic Copy Number ◽

Genomic Copy ◽

Error Calibration

AbstractCopy number variations (CNV) are regional deviations from the normal autosomal bi-allelic DNA content. While germline CNVs are a major contributor to genomic syndromes and inherited diseases, the majority of cancers accumulate extensive “somatic” CNV (sCNV or CNA) during the process of oncogenetic transformation and progression. While specific sCNV have closely been associated with tumorigenesis, intriguingly many neoplasias exhibit recurrent sCNV patterns beyond the involvement of a few cancer driver genes.Currently, CNV profiles of tumor samples are generated using genomic micro-arrays or high-throughput DNA sequencing. Regardless of the underlying technology, genomic copy number data is derived from the relative assessment and integration of multiple signals, with the data generation process being prone to contamination from several sources. Estimated copy number values have no absolute and linear correlation to their corresponding DNA levels, and the extent of deviation differs between sample profiles which poses a great challenge for data integration and comparison in large scale genome analysis.In this study, we present a novel method named Minimum Error Calibration and Normalization of Copy Numbers Analysis (Mecan4CNA). For each sCNV profile,Mecan4CNAreduces the noise level, calculates values representing the normal DNA copies (baseline) and the change of one copy (level distance), and finally normalizes all values. Experiments ofMecan4CNAon simulated data showed an overall accuracy of 93% and 91% in determining the baseline and level distance, respectively. Comparison of baseline and level distance estimation with existing methods and karyotyping data on the NCI-60 tumor cell line produced coherent results. To estimate the method’s impact on downstream analyses we performed GISTIC analyses on original andMecan4CNAdata from the Cancer Genome Atlas (TCGA) where the normalized data showed prominent improvements of both sensitivity and specificity in detecting focal regions.In general,Mecan4CNAprovides an advanced method for CNA data normalization especially in research involving data of high volume and heterogeneous quality. but with its informative output and visualization can also facilitate analysis of individual CNA profiles.Mecan4CNAis freely available as a Python package and through Github.

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OneD: increasing reproducibility of Hi-C Samples with abnormal karyotypes

10.1101/148254 ◽

2017 ◽

Cited By ~ 2

Author(s):

Enrique Vidal ◽

François le Dily ◽

Javier Quilez ◽

Ralph Stadhouders ◽

Yasmina Cuartero ◽

...

Keyword(s):

Copy Number ◽

Large Scale ◽

Chromosomal Abnormalities ◽

Three Dimensional ◽

R Package ◽

Copy Number Variations ◽

Normalization Methods ◽

Alternative Approach ◽

Systematic Biases ◽

Biological Differences

AbstractThe three-dimensional conformation of genomes is an essential component of their biological activity. The advent of the Hi-C technology enabled an unprecedented progress in our understanding of genome structures. However, Hi-C is subject to systematic biases that can compromise downstream analyses. Several strategies have been proposed to remove those biases, but the issue of abnormal karyotypes received little attention. Many experiments are performed in cancer cell lines, which typically harbor large-scale copy number variations that create visible defects on the raw Hi-C maps. The consequences of these widespread artifacts on the normalized maps are mostly unexplored. We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities. The method, called OneD, increases reproducibility among replicates of Hi-C samples with abnormal karyotype, outperforming previous methods significantly. On normal karyotypes, OneD fared equally well as state-of-the-art methods, making it a safe choice for Hi-C normalization. OneD is fast and scales well in terms of computing resources for resolutions up to 1 kbp. OneD is implemented as an R package available at http://www.github.com/qenvio/dryhic.

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