scholarly journals Optical genome mapping as a next-generation cytogenomic tool for detection of structural and copy number variations for prenatal genomic analyses

2021 ◽  
Author(s):  
Nikhil Shri Sahajpal ◽  
Hayk Barseghyan ◽  
Ravindra Kolhe ◽  
Alex Hastie ◽  
Alka Chaubey
Keyword(s):  
Copy Number ◽  
Southern Blotting ◽  
Sex Chromosome ◽  
Genome Mapping ◽  
Genetic Disorders ◽  
Standard Of Care ◽  
Copy Number Variations ◽  
Repeat Expansion ◽  
Chromosomal Microarray ◽  
Next Generation

Global medical associations (ACOG, ISUOG, ACMG) recommend diagnostic prenatal testing for the detection and prevention of genetic disorders. Historically, cytogenetic methods such as karyotype analysis, fluorescent in situ hybridization (FISH), and chromosomal microarray (CMA) are utilized worldwide to diagnose common syndromes. However, the limitations of each of these methods, either performed in tandem or simultaneously, demonstrates the need of a revolutionary technology that can alleviate the need of multiple technologies. Optical genome mapping (OGM) is a novel technology that fills this void by being able to detect all classes of structural variations (SVs), including copy number variations (CNVs). OGM is being adopted by laboratories as a next-generation cytogenomic tool for both postnatal constitutional genetic disorders and hematological malignancies. This commentary highlights the potential of OGM to become a standard of care in prenatal genetic testing by its ability to identify large balanced and unbalanced SVs (currently the strength of karyotyping and metaphase FISH), CNVs (by CMA), repeat contraction disorders (by Southern blotting) and multiple repeat expansion disorders (by PCR based methods or Southern blotting). Also, next-generation sequencing (NGS) methods are excellent at detecting sequencing variants but are unable to accurately detect the repeat regions of the genome which limits the ability to detect all classes of SVs. Notably, multiple molecular methods are used to identify repeat expansion and contraction disorders in routine clinical laboratories around the world. With non-invasive prenatal screening test (NIPT) as the standard of care screening assay for all global pregnancies, we anticipate OGM as a high-resolution cytogenomic diagnostic tool employed following a positive NIPT screen or for high-risk pregnancies with an abnormal ultrasound. Accurate detection of all types of genetic disorders by OGM, such as liveborn aneuploidies, sex chromosome anomalies, microdeletion/microduplication syndromes, repeat expansion/contra5ction disorders is key to reducing the global burden of genetic disorders.

scholarly journals Optical Genome Mapping as a Next-Generation Cytogenomic Tool for Detection of Structural and Copy Number Variations for Prenatal Genomic Analyses

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 398
Author(s):  
Nikhil Shri Sahajpal ◽  
Hayk Barseghyan ◽  
Ravindra Kolhe ◽  
Alex Hastie ◽  
Alka Chaubey
Keyword(s):  
Copy Number ◽  
Southern Blotting ◽  
Genome Mapping ◽  
Genetic Disorders ◽  
Prenatal Testing ◽  
Standard Of Care ◽  
Copy Number Variations ◽  
Repeat Expansion ◽  
Chromosomal Microarray ◽  
Next Generation

Global medical associations (ACOG, ISUOG, ACMG) recommend diagnostic prenatal testing for the detection and prevention of genetic disorders. Historically, cytogenetic methods such as karyotype analysis, fluorescent in situ hybridization (FISH) and chromosomal microarray (CMA) are utilized worldwide to diagnose common syndromes. However, the limitations of each of these methods, either performed in tandem or simultaneously, demonstrates the need of a revolutionary technology that can alleviate the need for multiple technologies. Optical genome mapping (OGM) is a novel method that fills this void by being able to detect all classes of structural variations (SVs), including copy number variations (CNVs). OGM is being adopted by laboratories as a tool for both postnatal constitutional genetic disorders and hematological malignancies. This commentary highlights the potential for OGM to become a standard of care in prenatal genetic testing based on its capability to comprehensively identify large balanced and unbalanced SVs (currently the strength of karyotyping and metaphase FISH), CNVs (by CMA), repeat contraction disorders (by Southern blotting) and multiple repeat expansion disorders (by PCR-based methods or Southern blotting). Next-generation sequencing (NGS) methods are excellent at detecting sequence variants, but they are unable to accurately resolve repeat regions of the genome, which limits their ability to detect all classes of SVs. Notably, multiple molecular methods are used to identify repeat expansion and contraction disorders in routine clinical laboratories around the world. With non-invasive prenatal testing (NIPT) becoming the standard of care screening assay for all global pregnancies, we anticipate that OGM can provide a high-resolution, cytogenomic assay to be employed following a positive NIPT screen or for high-risk pregnancies with an abnormal ultrasound. Accurate detection of all types of genetic disorders by OGM, such as liveborn aneuploidies, sex chromosome anomalies, microdeletion/microduplication syndromes, repeat expansion/contraction disorders is key to reducing the global burden of genetic disorders.

scholarly journals A Rapid PCR-Free Next-Generation Sequencing Method for the Detection of Copy Number Variations in Prenatal Samples

Life ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 98
Author(s):  
Xiya Zhou ◽  
Xiangbin Chen ◽  
Yulin Jiang ◽  
Qingwei Qi ◽  
Na Hao ◽  
...  
Keyword(s):  
Prenatal Diagnosis ◽  
Next Generation Sequencing ◽  
Copy Number ◽  
Genomic Dna ◽  
Sex Chromosome ◽  
Copy Number Variations ◽  
Next Generation ◽  
Sequencing Data ◽  
Clinically Significant ◽  
Generation Sequencing

Next-generation sequencing (NGS) is emerging as a new method for the detection of clinically significant copy number variants (CNVs). In this study, we developed and validated rapid CNV-sequencing (rCNV-seq) for clinical application in prenatal diagnosis. Low-pass whole-genome sequencing was performed on PCR libraries prepared from amniocyte genomic DNA. From 10–40 ng of input DNA, PCR-free libraries consistently produced sequencing data with high unique read mapping ratios, low read redundancy, low coefficient of variation for all chromosomes and high genomic coverage. In validation studies, reliable and accurate CNV detection using PCR-free-based rCNV-seq was demonstrated for a range of common trisomies and sex chromosome aneuploidies as well as microdeletion and duplication syndromes. In reproducibility studies, CNV copy number and genomic intervals closely matched those defined by chromosome microarray analysis. Clinical testing of genomic DNA samples from 217 women referred for prenatal diagnosis identified eight samples (3.7%) with known chromosome disorders. We conclude that PCR-free-based rCNV-seq is a sensitive, specific, reproducible and efficient method that can be used in any NGS-based diagnostic laboratory for detection of clinically significant CNVs.

scholarly journals Application of Optical Genome Mapping For Comprehensive Assessment of Chromosomal Structural Variants for Clinical Evaluation of Myelodysplastic Syndromes

2021 ◽  
Author(s):  
Hui Yang ◽  
Guillermo Garcia-Manero ◽  
Diana Rush ◽  
Guillermo Montalban-Bravo ◽  
Saradhi Mallampati ◽  
...  
Keyword(s):  
High Throughput ◽  
Myelodysplastic Syndromes ◽  
Copy Number ◽  
Genome Mapping ◽  
Limit Of Detection ◽  
Standard Of Care ◽  
Chromosomal Microarray ◽  
Structural Variants ◽  
Accurate Identification ◽  
Chromosomal Variants

ABSTRACTStructural chromosomal variants [copy number variants (CNVs): losses/ gains and structural variants (SVs): inversions, balanced and unbalanced fusions/translocations] are important for diagnosis and risk-stratification of myelodysplastic syndromes (MDS). Optical genome mapping (OGM) is a novel single-platform cytogenomic technique that enables high-throughput, accurate and genome-wide detection of all types of clinically important chromosomal variants (CNVs and SVs) at a high resolution, hence superior to current standard-of-care cytogenetic techniques that include conventional karyotyping, FISH and chromosomal microarrays. In this proof-of-principle study, we evaluated the performance of OGM in a series of 12 previously well-characterized MDS cases using clinical BM samples. OGM successfully facilitated detection and detailed characterization of twenty-six of the 28 clonal chromosomal variants (concordance rate: 93% with conventional karyotyping; 100% with chromosomal microarray). These included copy number gains/losses, inversions, inter and intra-chromosomal translocations, dicentric and complex derivative chromosomes; the degree of complexity in latter aberrations was not apparent using standard technologies. The 2 missed aberrations were from a single patient within a composite karyotype, below the limit of detection. Further, OGM uncovered 6 additional clinically relevant sub-microscopic aberrations in 4 (33%) patients that were cryptic by standard-of-care technologies, all of which were subsequently confirmed by alternate platforms. OGM permitted precise gene-level mapping of clinically informative genes such as TP53, TET2 and KMT2A, voiding the need for multiple confirmatory assays. OGM is a potent single-platform assay for high-throughput and accurate identification of clinically important chromosomal variants.

scholarly journals Prenatal Diagnosis and Molecular Cytogenetic Characterization of Copy Number Variations on 4p15.2p16.3, Xp22.31, and 12p11.1q11 in a Fetus with Ultrasound Anomalies: A Case Report and Literature Review

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Han Zhang ◽  
Qi Xi ◽  
Xiangyin Liu ◽  
Fagui Yue ◽  
Hongguo Zhang ◽  
...  
Keyword(s):  
Copy Number ◽  
De Novo ◽  
Genetic Disorders ◽  
Chromosomal Rearrangements ◽  
Copy Number Variations ◽  
Chromosomal Microarray ◽  
Chromosomal Microarray Analysis ◽  
Chromosome 2 ◽  
Cytogenetic Characterization

Chromosomal rearrangements, such as duplications/deletions, can lead to a variety of genetic disorders. Herein, we reported a prenatal case with right aortic arch and aberrant left subclavian artery, consisting of a complex chromosomal copy number variations. Routine cytogenetic analysis described the chromosomal karyotype as 46,XY, add (2)(q37) for the fetus. However, the chromosomal microarray analysis (CMA) identified a 22.4 Mb duplication in chromosome 4p16.3p15.2, a 3.96 Mb microduplication in 12p11.1q11, and a 1.68 Mb microdeletion in Xp22.31. Fluorescence in situ hybridization (FISH) using a chromosome 4 painting probe was found to hybridize to the terminal of chromosome 2q on the fetus, thus confirming that the extra genetic materials of chromosome 2 was actually trisomy 4p detected through CMA. Meanwhile, the parental karyotypes were normal, which proved that the add (2) was de novo for fetus. The duplication of Wolf-Hirschhorn syndrome critical region (WHSCR) and X-linked recessive ichthyosis associated with Xp22.31 deletion separately were considered potentially pathogenic causes although other abnormalities involving these syndromes were not observed. For prenatal cases, the combined utilization of ultrasonography, traditional cytogenetic, and molecular diagnosis technology will enhance better diagnostic benefits, offer more detailed genetic counselling, and assess the prognosis of the fetuses.

scholarly journals Multiplex ligation-dependent probe amplification – a short overview

2020 ◽  
Vol 28 (2) ◽  
pp. 123-131
Author(s):  
Valeriu Moldovan ◽  
Elena Moldovan
Keyword(s):  
Copy Number ◽  
Genetic Disorders ◽  
Cost Effective ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Gene Deletions ◽  
Conventional Cytogenetic Analysis ◽  
Main Technique ◽  
Cost Effective Technique ◽  
Dependent Probe

AbstractMultiplex Ligation-dependent Probe Amplification is a technique proposed for the detection of deletions or duplications that may lead to copy number variations in genomic DNA, mainly due to its higher resolution, and shorter overall diagnosis time, when compared with techniques traditionally used, namely karyotyping, fluorescence in situ hybridization, and array comparative genomic hybridization. Multiplex Ligation-dependent Probe Amplification is a fast (about 2 days), useful and cost-effective technique, being suitable for the diagnosis of hereditary conditions caused by complete or partial gene deletions or duplications, as these conditions are either more difficult or impossible to be diagnosed by other techniques, such as PCR, Real-Time PCR, or sequencing (Sanger or Next Generation). Due to its numerous advantages over conventional cytogenetic analysis techniques, Multiplex Ligation-dependent Probe Amplification could be used in the near future as the main technique for the molecular investigation of genetic conditions caused by copy number variations, in both rare and complex genetic disorders.

scholarly journals Copy number variant detection with low-coverage whole-genome sequencing is a viable replacement for the traditional array-CGH

2020 ◽  
Author(s):  
Marcel Kucharik ◽  
Jaroslav Budis ◽  
Michaela Hyblova ◽  
Gabriel Minarik ◽  
Tomas Szemes
Keyword(s):  
In Silico ◽  
Copy Number ◽  
Normal Population ◽  
Genetic Disorders ◽  
Prenatal Testing ◽  
In Silico Analysis ◽  
Copy Number Variant ◽  
Detection Algorithm ◽  
Copy Number Variations ◽  
Cnv Detection

Copy number variations (CNVs) are a type of structural variant involving alterations in the number of copies of specific regions of DNA, which can either be deleted or duplicated. CNVs contribute substantially to normal population variability; however, abnormal CNVs cause numerous genetic disorders. Nowadays, several methods for CNV detection are used, from the conventional cytogenetic analysis through microarray-based methods (aCGH) to next-generation sequencing (NGS). We present GenomeScreen - NGS based CNV detection method based on a previously described CNV detection algorithm used for non-invasive prenatal testing (NIPT). We determined theoretical limits of its accuracy and confirmed it with extensive in-silico study and already genotyped samples. Theoretically, at least 6M uniquely mapped reads are required to detect CNV with a length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in-silico analysis showed the requirement at least 8M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has a 200 kb mean resolution. GenomeScreen and aCGH both detected 59 deviations, GenomeScreen furthermore detected 134 other (usually) smaller variations. Furthermore, the overall cost per sample is about 2-3x lower in the case of GenomeScreen.

scholarly journals CNV-P: a machine-learning framework for predicting high confident copy number variations

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12564
Author(s):  
Taifu Wang ◽  
Jinghua Sun ◽  
Xiuqing Zhang ◽  
Wen-Jing Wang ◽  
Qing Zhou
Keyword(s):  
Machine Learning ◽  
False Positive ◽  
Copy Number ◽  
Genetic Disorders ◽  
Genetic Diseases ◽  
Basic Research ◽  
Read Depth ◽  
Copy Number Variations ◽  
Sequencing Data ◽  
Learning Framework

Background Copy-number variants (CNVs) have been recognized as one of the major causes of genetic disorders. Reliable detection of CNVs from genome sequencing data has been a strong demand for disease research. However, current software for detecting CNVs has high false-positive rates, which needs further improvement. Methods Here, we proposed a novel and post-processing approach for CNVs prediction (CNV-P), a machine-learning framework that could efficiently remove false-positive fragments from results of CNVs detecting tools. A series of CNVs signals such as read depth (RD), split reads (SR) and read pair (RP) around the putative CNV fragments were defined as features to train a classifier. Results The prediction results on several real biological datasets showed that our models could accurately classify the CNVs at over 90% precision rate and 85% recall rate, which greatly improves the performance of state-of-the-art algorithms. Furthermore, our results indicate that CNV-P is robust to different sizes of CNVs and the platforms of sequencing. Conclusions Our framework for classifying high-confident CNVs could improve both basic research and clinical diagnosis of genetic diseases.

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