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

2017 ◽  
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.

Application of Copy Number Variation Sequencing in Genetic Analysis of Miscarriages in Early and Middle Pregnancy

2020 ◽  
Vol 160 (11-12) ◽  
pp. 634-642
Author(s):  
Shiqiang Luo ◽  
Xingyuan Chen ◽  
Tizhen Yan ◽  
Jiaolian Ya ◽  
Zehui Xu ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
High Throughput ◽  
Copy Number ◽  
High Throughput Sequencing ◽  
Chromosomal Abnormalities ◽  
Pregnancy Termination ◽  
Mendelian Inheritance ◽  
Copy Number Variations ◽  
Abnormal Chromosome ◽  
Number Variation

High-throughput sequencing based on copy number variation (CNV-seq) is commonly used to detect chromosomal abnormalities. This study identifies chromosomal abnormalities in aborted embryos/fetuses in early and middle pregnancy and explores the application value of CNV-seq in determining the causes of pregnancy termination. High-throughput sequencing was used to detect chromosome copy number variations (CNVs) in 116 aborted embryos in early and middle pregnancy. The detection data were compared with the Database of Genomic Variants (DGV), the Database of Chromosomal Imbalance and Phenotype in Humans using Ensemble Resources (DECIPHER), and the Online Mendelian Inheritance in Man (OMIM) database to determine the CNV type and the clinical significance. High-throughput sequencing results were successfully obtained in 109 out of 116 specimens, with a detection success rate of 93.97%. In brief, there were 64 cases with abnormal chromosome numbers and 23 cases with CNVs, in which 10 were pathogenic mutations and 13 were variants of uncertain significance. An abnormal chromosome number is the most important reason for embryo termination in early and middle pregnancy, followed by pathogenic chromosome CNVs. CNV-seq can quickly and accurately detect chromosome abnormalities and identify microdeletion and microduplication CNVs that cannot be detected by conventional chromosome analysis, which is convenient and efficient for genetic etiology diagnosis in miscarriage.

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

BMC Genetics ◽  
2008 ◽  
Vol 9 (1) ◽  
pp. 92 ◽  
Author(s):  
Chien-Hsing Lin ◽  
Ling-Hui Li ◽  
Sheng-Feng Ho ◽  
Tzu-Po Chuang ◽  
Jer-Yuarn Wu ◽  
...  
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
Copy Number Variations ◽  
Han Chinese ◽  
Large Scale Survey

Application of Restriction Site-Associated DNA Sequencing (RAD-Seq) for Copy Number Variation and Triploidy Detection in Human

2021 ◽  
pp. 1-8
Author(s):  
Jian-Chun He ◽  
Shao-Ying Li ◽  
Wen-Zhi He ◽  
Jia-Jia Xian ◽  
Xiao-Yan Ma ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Cell Lines ◽  
Genome Sequencing ◽  
Copy Number ◽  
Restriction Site ◽  
Chromosomal Abnormalities ◽  
Copy Number Variations ◽  
Str Analysis ◽  
Tissue Samples ◽  
Low Pass

At present, low-pass whole-genome sequencing (WGS) is frequently used in clinical research and in the screening of copy number variations (CNVs). However, there are still some challenges in the detection of triploids. Restriction site-associated DNA sequencing (RAD-Seq) technology is a reduced-representation genome sequencing technology developed based on next-generation sequencing. Here, we verified whether RAD-Seq could be employed to detect CNVs and triploids. In this study, genomic DNA of 11 samples was extracted employing a routine method and used to build libraries. Five cell lines of known karyotypes and 6 triploid abortion tissue samples were included for RAD-Seq testing. The triploid samples were confirmed by STR analysis and also tested by low-pass WGS. The accuracy and efficiency of detecting CNVs and triploids by RAD-Seq were then assessed, compared with low-pass WGS. In our results, RAD-Seq detected 11 out of 11 (100%) chromosomal abnormalities, including 4 deletions and 1 aneuploidy in the purchased cell lines and all triploid samples. By contrast, these triploids were missed by low-pass WGS. Furthermore, RAD-Seq showed a higher resolution and more accurate allele frequency in the detection of triploids than low-pass WGS. Our study shows that, compared with low-pass WGS, RAD-Seq has relatively higher accuracy in CNV detection at a similar cost and is capable of identifying triploids. Therefore, the application of this technique in medical genetics has a significant potential value.

scholarly journals Clinical Utility and the Yield of Single Nucleotide Polymorphism Array in Prenatal Diagnosis of Fetal Central Nervous System Abnormalities

2021 ◽  
Vol 8 ◽  
Author(s):  
Meiying Cai ◽  
Hailong Huang ◽  
Liangpu Xu ◽  
Na Lin
Keyword(s):  
Central Nervous System ◽  
Single Nucleotide Polymorphism ◽  
Copy Number ◽  
Chromosomal Abnormalities ◽  
Karyotype Analysis ◽  
Snp Array ◽  
Copy Number Variations ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Pathogenic Cnvs

Applying single nucleotide polymorphism (SNP) array to identify the etiology of fetal central nervous system (CNS) abnormality, and exploring its association with chromosomal abnormalities, copy number variations, and obstetrical outcome. 535 fetuses with CNS abnormalities were analyzed using karyotype analysis and SNP array. Among the 535 fetuses with CNS abnormalities, chromosomal abnormalities were detected in 36 (6.7%) of the fetuses, which were consistent with karyotype analysis. Further, additional 41 fetuses with abnormal copy number variations (CNVs) were detected using SNP array (the detection rate of additional abnormal CNVs was 7.7%). The rate of chromosomal abnormalities, but not that of pathogenic CNVs in CNS abnormalities with other ultrasound abnormalities was significantly higher than that in isolated CNS abnormalities. The rates of chromosomal abnormalities and pathogenic CNVs in fetuses with spine malformation (50%), encephalocele (50%), subependymal cyst (20%), and microcephaly (16.7%) were higher than those with other isolated CNS abnormalities. The pregnancies for 36 cases with chromosomal abnormalities, 18 cases with pathogenic CNVs, and three cases with VUS CNVs were terminated. SNP array should be used in the prenatal diagnosis of fetuses with CNS abnormalities, which can enable better prenatal assessment and genetic counseling, and affect obstetrical outcomes.

scholarly journals Chromosomal abnormalities and copy number variations in children with idiopathic mental illness

2019 ◽  
pp. 80-81
Author(s):  
O. S. Kurinnaia ◽  
I. Y. Iourov ◽  
S. G. Vorsanova
Keyword(s):  
Mental Illness ◽  
Mental Disorders ◽  
Copy Number ◽  
Genetic Factors ◽  
Chromosomal Abnormalities ◽  
Copy Number Variations ◽  
Molecular Karyotyping ◽  
Correct Data

Genetic factors of mental illness are generally recognized. Here, it is shown that molecular karyotyping in combination with original bioinformatics methods offers the opportunity for effective uncovering genomic pathology, which may provide correct data on genetic factors for mental disorders in children.

scholarly journals MON-LB48 The Genomic Landscape of Sporadic Thyrotrophinomas

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Angeline shen ◽  
Paul Wang ◽  
Sunita M C De Sousa ◽  
David J Torpy ◽  
Hamish Scott ◽  
...  
Keyword(s):  
Cell Adhesion ◽  
Rna Polymerase Ii ◽  
Copy Number ◽  
Large Scale ◽  
Neutral Loss ◽  
Copy Number Variations ◽  
Driver Mutations ◽  
Chromosomal Anomalies ◽  
Tumour Type ◽  
Genomic Landscape

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.

scholarly journals A Mechanism Leading to Changes in Copy Number Variations Affected by Transcriptional Level Might Be Involved in Evolution, Embryonic Development, Senescence, and Oncogenesis Mediated by Retrotransposons

2021 ◽  
Vol 9 ◽  
Author(s):  
Yunpeng Sui ◽  
Shuanghong Peng
Keyword(s):  
Embryonic Development ◽  
Copy Number ◽  
Three Dimensional ◽  
Induced Pluripotent Stem Cell ◽  
Copy Number Variations ◽  
Mrna Splicing ◽  
Transcriptional Level ◽  
Underlying Mechanisms ◽  
Induced Pluripotent ◽  
Hiv 1

In recent years, more and more evidence has emerged showing that changes in copy number variations (CNVs) correlated with the transcriptional level can be found during evolution, embryonic development, and oncogenesis. However, the underlying mechanisms remain largely unknown. The success of the induced pluripotent stem cell suggests that genome changes could bring about transformations in protein expression and cell status; conversely, genome alterations generated during embryonic development and senescence might also be the result of genome changes. With rapid developments in science and technology, evidence of changes in the genome affected by transcriptional level has gradually been revealed, and a rational and concrete explanation is needed. Given the preference of the HIV-1 genome to insert into transposons of genes with high transcriptional levels, we propose a mechanism based on retrotransposons facilitated by specific pre-mRNA splicing style and homologous recombination (HR) to explain changes in CNVs in the genome. This mechanism is similar to that of the group II intron that originated much earlier. Under this proposed mechanism, CNVs on genome are dynamically and spontaneously extended in a manner that is positively correlated with transcriptional level or contract as the cell divides during evolution, embryonic development, senescence, and oncogenesis, propelling alterations in them. Besides, this mechanism explains several critical puzzles in these processes. From evidence collected to date, it can be deduced that the message contained in genome is not just three-dimensional but will become four-dimensional, carrying more genetic information.

scholarly journals Evaluation of Chromosomal Abnormalities and Copy Number Variations in Fetuses with Ultrasonic Soft Markers

2020 ◽  
Author(s):  
Meiying Cai ◽  
Na Lin ◽  
Liangpu Xu ◽  
hailong huang
Keyword(s):  
Copy Number ◽  
Chromosomal Abnormalities ◽  
Snp Array ◽  
Copy Number Variations ◽  
Clinical Value ◽  
Obstetrical Outcomes ◽  
Genetic Abnormalities ◽  
Significant Difference ◽  
Snp Array Analysis ◽  
Soft Marker

Abstract Background: Some ultrasonic soft markers can be found during ultrasound examination. However, the etiology of the fetuses with ultrasonic soft markers is still unknown. This study aimed to evaluate the genetic etiology and clinical value of chromosomal abnormalities and copy number variations (CNVs) in fetuses with ultrasonic soft markers.Methods: Among 1131 fetuses, 729 had single ultrasonic soft marker, 322 had two ultrasonic soft markers, and 80 had three or more ultrasonic soft markers. All fetuses underwent conventional karyotyping, followed by single nucleotide polymorphism (SNP) array analysis. Results: Among 1131 fetuses with ultrasonic soft markers, 46 had chromosomal abnormalities. In addition to the 46 fetuses with chromosomal abnormalities consistent with the results of the karyotyping analysis, the SNP array identified additional 6.1% (69/1131) abnormal CNVs. The rate of abnormal CNVs in fetuses with ultrasonic soft marker, two ultrasonic soft markers, three or more ultrasonic soft markers were 6.2%, 6.2%, and 5.0%, respectively. No significant difference was found in the rate of abnormal CNVs among the groups.Conclusions: Genetic abnormalities affect obstetrical outcomes. The SNP array can fully complement conventional karyotyping in fetuses with ultrasonic soft markers, improve detection rate of chromosomal abnormalities, and affect obstetrical outcomes.

scholarly journals Blind estimation and correction of microarray batch effect

2017 ◽  
Author(s):  
Sudhir Varma
Keyword(s):  
Large Scale ◽  
Reference Sample ◽  
R Package ◽  
Batch Effect ◽  
Data Repository ◽  
Blind Estimation ◽  
Reference Set ◽  
Shared Information ◽  
Scale Integration ◽  
Biological Differences

AbstractMicroarray batch effect (BE) has been the primary bottleneck for large-scale integration of data from multiple experiments. Current BE correction methods either need known batch identities (ComBat)or have the potential to overcorrect, by removing true but unknown biological differences (SVA).Even though the effects of technical differences on measured expression have been published, there are no BE correction algorithms that take the approach of predicting technical effects from parameters computed from a fixed reference sample set. We show that a set of signatures, each of which is a vector the length of the number of probes, calculated on a Reference set of microarray samples can predict much of the batch effect in other Validation sets. We present a rationale of selecting a Reference set of samples designed to estimate technical differences without removing biological differences. Putting both together, we introduce the Batch Effect Signature Correction (BESC) algorithm that uses the BES calculated on the Reference set to efficiently predict and remove BE. Using two independent Validation sets, we show that BESC is capable of removing batch effect without removing unknown but true biological differences. Much of the variations due to batch effect is shared between different microarray datasets. That shared information can be used to predict signatures (i.e. directions of perturbation) due to batch effect in new datasets. The correction is blind (without needing to re-compute the parameters on new samples to be corrected), single sample, (each sample is corrected independently of each other) and conservative (only those perturbations known to be likely to be due to technical differences are removed ensuring that unknown but important biological differences are maintained). Those three characteristics make it ideal for high-throughput correction of samples for a microarray data repository. An R Package besc implementing the algorithm is available from http://explainbio.com.

scholarly journals Probabilistic method corrects previously uncharacterized Hi-C artifact

2020 ◽  
Author(s):  
Yihang Shen ◽  
Carl Kingsford
Keyword(s):  
Copy Number ◽  
Computational Models ◽  
High Throughput Sequencing ◽  
Probabilistic Method ◽  
Three Dimensional ◽  
Copy Number Variations ◽  
Chromosome Conformation ◽  
Chromosomal Structure ◽  
Processing Pipeline ◽  
Capture Techniques

AbstractThree-dimensional chromosomal structure plays an important role in gene regulation. Chromosome conformation capture techniques, especially the high-throughput, sequencing-based technique Hi-C, provide new insights on spatial architectures of chromosomes. However, Hi-C data contains artifacts and systemic biases that substantially influence subsequent analysis. Computational models have been developed to address these biases explicitly, however, it is difficult to enumerate and eliminate all the biases in models. Other models are designed to correct biases implicitly, but they will also be invalid in some situations such as copy number variations. We characterize a new kind of artifact in Hi-C data. We find that this artifact is caused by incorrect alignment of Hi-C reads against approximate repeat regions and can lead to erroneous chromatin contact signals. The artifact cannot be corrected by current Hi-C correction methods. We design a probabilistic method and develop a new Hi-C processing pipeline by integrating our probabilistic method with the HiC-Pro pipeline. We find that the new pipeline can remove this new artifact effectively, while preserving important features of the original Hi-C matrices.

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