Identification Of Copy Number Variations Research Articles

Performance of bovine high density SNPs genotyping array in indigenous Pakistani cattle breeds

The bovine high density SNPs genotyping array has a wide range of applications including detection of selection signatures, identification of copy number variants (CNVs), genome wide association studies, and dendrogram relationships. This array can also be used to improve the accuracy of genomic predictions for low heritable traits viz. reproductive traits. The effectiveness of this array for genomic selection mainly depends on polymorphism level. In this study, we used 136 individuals from ten different Pakistani cattle breeds, include Achi (18), Bhagnari (14), Cholistani (13), Dajal (10), Dhanni (10), Kankraj (12), Lohani (19), Red Sindhi (13), Sahiwal (14), and Tharparkar (13) using high density SNPs genotyping and this array contained approximately 777, 962 SNPs. The results of this study revealed that approximately 500, 939 SNPs were found polymorphic in these breeds. The results indicate that high density SNPs bead chip would offer an informative genotyping platform for quantitative trait loci (QTL) mapping in indigenous Pakistani cattle breeds. Keywords: Copy number variants; Genotyping; Polymorphism; Quantitative trait loci; SNPs http://dx.doi.org/10.19045/bspab.2018.70026

Clinical Relevance of Gene Copy Number Variation in Metastatic Clear Cell Renal Cell Carcinoma.

Gene copy number variations (CNVs) have been reported to be frequent in renal cell carcinoma (RCC), with potential prognostic value for some. However, their clinical utility, especially to guide treatment of metastatic disease remains to be established. Our objectives were to assess CNVs on a panel of selected genes and determine their clinical relevance in patients who underwent treatment of metastatic RCC. The genetic assessment was performed on frozen tissue samples of clear cell metastatic RCC using quantitative multiplex polymerase chain reaction of short fluorescent fragment method to detect CNVs on a panel of 14 genes of interest. The comparison of the electropherogram obtained from both tumor and normal renal adjacent tissue allowed for CNV identification. The clinical, biologic, and survival characteristics were assessed for their associations with the most frequent CNVs. Fifty patients with clear cell metastatic RCC were included. The CNV rate was 21.4%. The loss of CDKN2A and PLG was associated with a higher tumor stage (P< .05). The loss of PLG and ALDOB was associated with a higher Fuhrman grade (P< .05). The loss of ALDOB was also associated with a worse Heng prognostic score (95% vs. 66%; P= .029) and lower 24-month survival rate (18% vs. 58%; P= .012). The loss of both ALDOB and PLG was frequent (32%) and was associated with a higher tumor stage and grade (P< .05). As expected, we showed that several CNVs were associated with clinical relevance, especially those located on CDKN2A, PLG, and ALDOB, in a homogeneous cohort of patients with clear cell metastatic RCC.

Application of Molecular Karyotyping in Acute Myeloid Leukemia: A Review

Acute myeloid leukemia (AML) is an aggressive disease characterized by the overproduction of immature myeloid cells that accumulate in blood and bone marrow. Integration of genetic findings and clinicopathological information is crucial in establishing the diagnosis, prognosis and determining the therapeutic approach in the management of AML patients. In recent years, the AML classification has evolved from morphology to cytogenetics/molecular genetics-based findings, which is essential in the detection of chromosomal abnormalities and has provided the framework for the diagnosis and risk-stratification in AML. Moreover, with advances in molecular karyotyping such as comparative genomic hybridization (CGH) and single nucleotide polymorphism (SNP) arrays, various limitations of conventional diagnostic approaches have been overcome. Hence, this review focuses on the insights into molecular karyotyping using CGH and SNP arrays which enable the identification of copy number variations (CNVs) at a higher resolution and facilitate the detection of copy neutral loss of heterozygosity (CN-LOH) otherwise undetectable by conventional cytogenetics. Technical hindrances of these methods (e.g. regions of losses, gains, or “undulating waves”) are also discussed in the context of AML.

Identification of Copy Number Variants from SNP Arrays Using PennCNV.

High-resolution single-nucleotide polymorphism (SNP) genotyping arrays offer a sensitive and affordable method for genome-wide detection of copy number variants (CNVs). PennCNV is a hidden Markov model (HMM)-based CNV caller for SNP arrays, first released 10 years ago. A typical CNV calling procedure using PennCNV includes preparation of input files, CNV calling, filtering CNV calls, CNV annotation, and CNV visualization. Here we describe several protocols for CNV calling using PennCNV, together with descriptions on several recent improvements to the software tool.

Versatile Identification of Copy Number Variants with Canvas.

Versatile and efficient variant calling tools are needed to analyze large-scale sequencing datasets. In particular, identification of copy number changes remains a challenging task due to their complexity, susceptibility to sequencing biases, variation in coverage data and dependence on genome-wide sample properties, such as tumor polyploidy, polyclonality in cancer samples, or frequency of de novo variation in germline genomes of pedigrees. The frequent need of core sequencing facilities to process samples from both normal and tumor sources favors multipurpose variant calling tools with functionality to process these diverse sets within a single software framework. This not only simplifies the overall bioinformatics workflow but also streamlines maintenance by shortening the software update cycle and requiring only limited staff training. Here we introduce Canvas, a tool for identification of copy number changes from diverse sequencing experiments including whole-genome matched tumor-normal, small pedigree, and single-sample normal resequencing, as well as whole-exome matched and unmatched tumor-normal studies. In addition to variant calling, Canvas infers genome-wide parameters such as cancer ploidy, purity, and heterogeneity. It provides fast and easy-to-run workflows that can scale to thousands of samples and can be easily incorporated into variant calling pipelines.

Application of Chromosomal Microarray for Evaluation of Idiopathic Short Stature in Asian Indian Children: A Pilot Study.

Background:Human height is a classic polygenic trait and currently available data explains only 10% of the phenotypic variation in height. Almost 60%–80% of the children coming to pediatric and endocrinology outpatient department for the evaluation of short stature are still labeled as idiopathic.Objectives:The aim of this study is to identify various chromosomal alterations causing idiopathic short stature (ISS) and short stature with dysmorphic features not pertaining to known genetic syndromes.Materials and Methods:After exclusion of all nutritional, systemic, endocrine, and syndromic causes of short stature, 19 patients with height <2 standard deviation scores were subjected to chromosomal microarray (CMA) study using Affymetrix CytoScan 750K array and CMA Scanner 3000 platform.Results:We identified total 61 copy-number variant (CNV) and polymorphs (33 gains, 11 loss, and 17 gain-mosaics) not described as normal variants in database of genomic variations. We identified SHOX haploinsufficiency as a cause of short stature in two patients, whereas one patient was gain-mosaic for SHOX. All three had normal conventional karyotype. One of these patients also had deletion of PAX3, which could be the cause of both short stature and associated mild intellectual impairment in this patient. We also found a long noncoding RNA, namely, KIAA0125 and a pseudogene ADAM6 in 18 out of our 19 patients which might have a regulatory role.Conclusion:This study shows that CMA is a very promising tool for the identification of pathogenic CNVs in patients with ISS. It can also help to identify novel genes controlling height and can open up new insight into pathophysiologic mechanisms underlying ISS, and thus may help to unfold new therapeutic targets for treatment of this condition. The association of CNV having genes for long noncoding RNAs, such as KIAA0125 and pseudogene such as ADAM6 with ISS suggest that they may play a role in controlling the expression of height-related genes and it needs further investigations.

Identification of Isthmin 1 as a Novel Clefting and Craniofacial Patterning Gene in Humans.

Orofacial clefts are one of the most common birth defects, affecting 1-2 per 1000 births, and have a complex etiology. High-resolution array-based comparative genomic hybridization has increased the ability to detect copy number variants (CNVs) that can be causative for complex diseases such as cleft lip and/or palate. Utilizing this technique on 97 nonsyndromic cleft lip and palate cases and 43 cases with cleft palate only, we identified a heterozygous deletion of Isthmin 1 in one affected case, as well as a deletion in a second case that removes putative 3' regulatory information. Isthmin 1 is a strong candidate for clefting, as it is expressed in orofacial structures derived from the first branchial arch and is also in the same "synexpression group" as fibroblast growth factor 8 and sprouty RTK signaling antagonist 1a and 2, all of which have been associated with clefting. CNVs affecting Isthmin 1 are exceedingly rare in control populations, and Isthmin 1 scores as a likely haploinsufficiency locus. Confirming its role in craniofacial development, knockdown or clustered randomly interspaced short palindromic repeats/Cas9-generated mutation of isthmin 1 in Xenopus laevis resulted in mild to severe craniofacial dysmorphologies, with several individuals presenting with median clefts. Moreover, knockdown of isthmin 1 produced decreased expression of LIM homeobox 8, itself a gene associated with clefting, in regions of the face that pattern the maxilla. Our study demonstrates a successful pipeline from CNV identification of a candidate gene to functional validation in a vertebrate model system, and reveals Isthmin 1 as both a new human clefting locus as well as a key craniofacial patterning gene.

A Comprehensive Workflow for Read Depth-Based Identification of Copy-Number Variation from Whole-Genome Sequence Data

A remaining hurdle to whole-genome sequencing (WGS) becoming a first-tier genetic test has been accurate detection of copy-number variations (CNVs). Here, we used several datasets to empirically develop a detailed workflow for identifying germline CNVs >1 kb fromshort-read WGS data using read depth-based algorithms. Our workflow is comprehensive in that it addresses all stages of the CNV-detection process, including DNA library preparation, sequencing, quality control, reference mapping, and computational CNV identification. We used our workflow to detect rare, genic CNVs in individuals with autism spectrum disorder (ASD), and 120/120 such CNVs tested using orthogonal methods were successfully confirmed. We also identified 71 putative genic de novo CNVs in this cohort, which had a confirmation rate of 70%; the remainder were incorrectly identified as de novo due to false positives in the proband (7%) or parental false negatives (23%). In individuals with an ASD diagnosis in which both microarray and WGS experiments were performed, our workflow detected all clinically relevant CNVs identified by microarrays, as well as additional potentially pathogenic CNVs < 20 kb. Thus, CNVs of clinical relevance can be discovered from WGS with a detection rate exceeding microarrays, positioning WGS as a single assay for genetic variation detection.

Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects

The effect of Copy Number Variants (CNVs) on Type 2 Diabetes (T2D) remains little explored. The present study characterized large rare CNVs in 686 T2D and 194 non-T2D subjects of Mexican ancestry genotyped using the Affymetrix Genome-Wide Human SNP array 5.0. Rare CNVs with ≥ 100 kb length were identified using a stringent strategy based on merging CNVs calls generated using Birdsuit, iPattern and PennCNV algorithms. We applied three different strategies to evaluate the distribution of CNVs in the T2D and non-T2D samples: 1) Burden analysis, 2) Identification of CNVs in loci previously associated to T2D, and 3) Identification of CNVs observed only in the T2D group. In the CNV burden analysis, the T2D group showed a higher proportion of CNVs, and also a higher proportion of CNVs overlapping at least one gene than the non T2D group. Five of the six loci previously associated with T2D had duplications or deletions in the T2D sample, but not the non-T2D sample. A gene-set analysis including genes with CNVs observed only in the T2D group highlighted gene-sets related with sensory perception (olfactory receptors, OR) and phenylpyruvate tautomerase/dopachrome isomerase activity (MIF and DDT genes).

Identification of copy number variation in French dairy and beef breeds using next-generation sequencing

BackgroundCopy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches.ResultsWe report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions.ConclusionsOur study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle.

Identification of copy number variations and translocations in cancer cells from Hi-C data.

Eukaryotic chromosomes adapt a complex and highly dynamic three-dimensional (3D) structure, which profoundly affects different cellular functions and outcomes including changes in epigenetic landscape and in gene expression. Making the scenario even more complex, cancer cells harbor chromosomal abnormalities [e.g. copy number variations (CNVs) and translocations] altering their genomes both at the sequence level and at the level of 3D organization. High-throughput chromosome conformation capture techniques (e.g. Hi-C), which are originally developed for decoding the 3D structure of the chromatin, provide a great opportunity to simultaneously identify the locations of genomic rearrangements and to investigate the 3D genome organization in cancer cells. Even though Hi-C data has been used for validating known rearrangements, computational methods that can distinguish rearrangement signals from the inherent biases of Hi-C data and from the actual 3D conformation of chromatin, and can precisely detect rearrangement locations de novo have been missing. In this work, we characterize how intra and inter-chromosomal Hi-C contacts are distributed for normal and rearranged chromosomes to devise a new set of algorithms (i) to identify genomic segments that correspond to CNV regions such as amplifications and deletions (HiCnv), (ii) to call inter-chromosomal translocations and their boundaries (HiCtrans) from Hi-C experiments and (iii) to simulate Hi-C data from genomes with desired rearrangements and abnormalities (AveSim) in order to select optimal parameters for and to benchmark the accuracy of our methods. Our results on 10 different cancer cell lines with Hi-C data show that we identify a total number of 105 amplifications and 45 deletions together with 90 translocations, whereas we identify virtually no such events for two karyotypically normal cell lines. Our CNV predictions correlate very well with whole genome sequencing data among chromosomes with CNV events for a breast cancer cell line (r = 0.89) and capture most of the CNVs we simulate using Avesim. For HiCtrans predictions, we report evidence from the literature for 30 out of 90 translocations for eight of our cancer cell lines. Furthermore, we show that our tools identify and correctly classify relatively understudied rearrangements such as double minutes and homogeneously staining regions. Considering the inherent limitations of existing techniques for karyotyping (i.e. missing balanced rearrangements and those near repetitive regions), the accurate identification of CNVs and translocations in a cost-effective and high-throughput setting is still a challenge. Our results show that the set of tools we develop effectively utilize moderately sequenced Hi-C libraries (100-300 million reads) to identify known and de novo chromosomal rearrangements/abnormalities in well-established cancer cell lines. With the decrease in required number of cells and the increase in attainable resolution, we believe that our framework will pave the way towards comprehensive mapping of genomic rearrangements in primary cells from cancer patients using Hi-C. CNV calling: https://github.com/ay-lab/HiCnv, Translocation calling: https://github.com/ay-lab/HiCtrans and Hi-C simulation: https://github.com/ay-lab/AveSim. Supplementary data are available at Bioinformatics online.

The Identification of Copy Number Variation of Cnv Esv27061 among Young Adults with Hypertension: Preliminary Findings

Introduction: Hypertension related morbidities and mortalities around the world show a gradual increase and early detection and prevention are advocated. The Database of Genomic Variants (DGV) has associated variation in DNA sequences called copy number variation (CNV) with susceptibility to common diseases. However, little is known about CNV role in essential hypertension. Thus, this study aimed to characterize the CNV esv27061 among prehypertensive and hypertensive young adults in Malaysia. Materials and method: In this comparative cross-sectional study, 104 subjects living in Kuantan who gave voluntary consent to participate are recruited and divided into three groups; control (43 subjects), prehypertensive (38 subjects) and mild hypertensive (23 subjects). An optimized droplet digital polymerase chain reaction (ddPCR) was used in the determination of CNV esv27061 in this study. Results: All subjects in the control (n=38; 88.4% gain), prehypertensive (n=33; 86.8% gain) and mild hypertensive (n=21; 91.3% gain) groups had CNV gain (copy number &gt; 2) while 11.6% of control, 13.2% of prehypertensive and 8.7% of mild hypertensive subjects exhibited normal copies (copy number = 2). Conclusion: The present preliminary finding was consistent with the Database of Genomic Variants (DGV) which stated that CNV esv27061 showed more gain than loss.

Abstract 2905: Clinical and genomic resistance to second generation androgen blockade in paired biopsies of metastatic castration-resistant prostate cancer

Abstract Background Recent “next generation” androgen deprivation therapies (ADT), such as abiraterone and enzalutamide, have improved survival in patients with castrate-resistant prostate cancer (CRPC). Despite therapy, most patients develop resistance to these agents. We investigated the genetic basis of tumor evolution and clinical resistance to next generation ADT in CRPC by using whole exome sequencing (WES) on paired pretreatment and post-resistance biopsies from CRPC patients. Methods Matched “trios” of germline, pre-treatment and post-resistant tumor samples were obtained from 7 patients treated with abiraterone (n=4) and enzalutamide (n=3) and WES was performed. Clinical data, including PSA and radiographic measurements, was used to classify patients as intrinsically resistant or initially responsive to treatment. Quality control, mutation and indel calling, copy number variation identification were performed using analytical pipelines at the Broad Institute. Tumor purity and ploidy were inferred, and phylogenetic analysis was performed using ABSOLUTE and Phylogic, respectively to identify resistance associated alterations in the context of clinical phenotypes. Results We identified multiple putative mechanisms and genetic categories of resistance to next generation ADT in CRPC. One abiraterone patient acquired an AR mutation (L702H) in the post-treatment sample, previously reported to be associated with poor outcomes and to confer resistance to this therapy. Amplification of MYC was associated with resistance in two other abiraterone patients with pre-existing AR gain: one patient with initial response to therapy acquired a focal gain of MYC in the resistant sample, and the other harbored a pre-existing MYC amplification, but had no response to therapy. In three enzalutamide patients, all acquired alterations in cell cycle genes (CDKN2A mutation, focal amplifications in regions spanning CDK4/6, and CCND3 focal amplification) at the time of resistance that were absent in pre-treatment tumors. In parallel, we confirm CDK4/6 overexpression was sufficient to promote enzalutamide resistance in prostate cancer cell models. Additional candidate genomic events associated with CRPC were also implicated with this approach, such as RSPO3 amplification. Conclusion This study outlines an approach to identify clinical genetic resistance mechanisms of next generation ADT in CRPC through integration of genomic data from serial biopsies, clinical patient outcomes, and preclinical functional screening. These findings confirm previously known potential resistance mechanisms, such as AR and MYC activation, and suggest putative mechanisms linked to therapeutic agents, which may inform novel targets for treating CRPC patients. Citation Format: G. Celine Han, Justin Hwang, Stephanie A. Mullane, Carrie Cibulskis, Zhenwei Zhang, Rana R. McKay, PCF-SU2C Dream Team, Scott L. Carter, William C. Hahn, Mary-Ellen Taplin, Eliezer M. Van Allen. Clinical and genomic resistance to second generation androgen blockade in paired biopsies of metastatic castration-resistant prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2905. doi:10.1158/1538-7445.AM2017-2905

SLMSuite: a suite of algorithms for segmenting genomic profiles

BackgroundThe identification of copy number variants (CNVs) is essential to study human genetic variation and to understand the genetic basis of mendelian disorders and cancers. At present, genome-wide detection of CNVs can be achieved using microarray or second generation sequencing (SGS) data. Although these technologies are very different, the genomic profiles that they generate are mathematically very similar and consist of noisy signals in which a decrease or increase of consecutive data represent deletions or duplication of DNA. In this framework, the most important step of the analysis consists of segmenting genomic profiles for the identification of the boundaries of genomic regions with increased or decreased signal.ResultsHere we introduce SLMSuite, a collection of algorithms, based on shifting level models (SLM), to segment genomic profiles from array and SGS experiments. The SLM algorithms take as input the log-transformed genomic profiles from SGS or microarray experiments and output segmentation results. We apply our method to the analysis of synthetic genomic profiles and real whole genome sequencing data and we demonstrate that it outperforms the state of the art circular binary segmentation algorithm in terms of sensitivity, specificity and computational speed.ConclusionThe SLMSuite contains an R library with the segmentation methods and three wrappers that allow to use them in Python, Ruby and C++. SLMSuite is freely available at https://sourceforge.net/projects/slmsuite.

Potential Value of Genomic Copy Number Variations in Schizophrenia.

Schizophrenia is a devastating neuropsychiatric disorder affecting approximately 1% of the global population, and the disease has imposed a considerable burden on families and society. Although, the exact cause of schizophrenia remains unknown, several lines of scientific evidence have revealed that genetic variants are strongly correlated with the development and early onset of the disease. In fact, the heritability among patients suffering from schizophrenia is as high as 80%. Genomic copy number variations (CNVs) are one of the main forms of genomic variations, ubiquitously occurring in the human genome. An increasing number of studies have shown that CNVs account for population diversity and genetically related diseases, including schizophrenia. The last decade has witnessed rapid advances in the development of novel genomic technologies, which have led to the identification of schizophrenia-associated CNVs, insight into the roles of the affected genes in their intervals in schizophrenia, and successful manipulation of the target CNVs. In this review, we focus on the recent discoveries of important CNVs that are associated with schizophrenia and outline the potential values that the study of CNVs will bring to the areas of schizophrenia research, diagnosis, and therapy. Furthermore, with the help of the novel genetic tool known as the Clustered Regularly Interspaced Short Palindromic Repeats-associated nuclease 9 (CRISPR/Cas9) system, the pathogenic CNVs as genomic defects could be corrected. In conclusion, the recent novel findings of schizophrenia-associated CNVs offer an exciting opportunity for schizophrenia research to decipher the pathological mechanisms underlying the onset and development of schizophrenia as well as to provide potential clinical applications in genetic counseling, diagnosis, and therapy for this complex mental disease.

Mapping of chromosomal balanced rearrangements by whole-genome sequencing identifies genes involved in epilepsy

Objective: Epilepsy is a frequent neurologic condition, with a frequency of 1% in the population. Identification of genes involved in epilepsy has been challenged by the genetic heterogeneity, phenotypic variability and phenocopies. During the last years, new whole-genome technologies such as array-comparative genomic hybridization (aCGH) and next-generation sequencing (NGS) allowed the identification of copy-number variations (CNVs) and single nucleotide variations (SNVs) involved in this condition. An alternative strategy to uncover new genes in epilepsy is the molecular characterization of apparently-balanced chromosomal rearrangements (ABCRs). This approach relies on the fact that a disease-causing gene may be disrupted by the breakpoints or its expression may be affected by a position effect. Methods: We report the study of 3 patients carrying respectively a paracentric inversion inv(2)(q22;q32.3) (P1), a pericentric inversion inv(2)(p12q22) (P2), and a balanced translocation t(11;15)(p14;q14) (P3) associated with epilepsy, intellectual disability and malformations for P3. Whole-genome paired-end sequencing, coupled with Sanger sequencing, allowed the characterization of ABCRs at base-pair level in all three patients. These results were also confirmed by FISH. Results: We demonstrated the disruption of three genes: MBD5 (2q23.1) in P1 and P2, M1AP (2p13.1) in P1 and MEIS2 (15q14) in P3. Expression studies by RT-qPCR showed a reduced expression of MBD5 in both patients P1 and P2. MBD5 is associated with intellectual disability, severe language impairment, epilepsy, and autistic spectrum disorders. Disruption of MBD5 appears to be responsible for the phenotype of patients P1 and P2. Disruption of MEIS2 in patient P3 contributes to her malformations and intellectual disability but has never been described in epilepsy to our knowledge. Conclusion: MEIS2 may be a new candidate gene in epilepsy, but a position effect on neighboring genes may not be excluded. Ongoing expression studies may help to confirm these hypotheses.

Association study and expression analysis of CYP4A11 gene copy number variation in Chinese cattle

The identification of copy number variations (CNVs) allow us to explore genomic polymorphisms. In recent years, significant progress in understanding CNVs has been made in studies of human and animals, however, association and expression studies of CNVs are still in the early stage. It was previously reported that the Cytochrome P-450 4A11 (CYP4A11) gene is located within a copy number variable region (CNVR) that encompasses quantitative trait loci (QTLs) for economic traits like meat quality and milk production. So, this study was performed to determine the presence of CYP4A11 CNV in six distinct cattle breeds, identify its relationship with growth, and explore the biological effects of gene expression. For three CYP4A11 CNV types, Normal was more frequent than Gain or Loss. Association analysis revealed a positive effect of CYP4A11 copy number on growth traits (P < 0.05). One-way analysis of variance (ANOVA) analysis revealed that more CYP4A11 copies increased the gene expression level. Moreover, overexpression of CYP4A11 in vitro revealed its effect on lipid deposit. The data provide evidence for the functional role of CYP4A11 CNV and provide the basis for future applications in cattle breeding.

The clinical impact of copy number variants in inherited bone marrow failure syndromes

Inherited bone marrow failure syndromes comprise a genetically heterogeneous group of diseases with hematopoietic failure and a wide array of physical malformations. Copy number variants were reported in some inherited bone marrow failure syndromes. It is unclear what impact copy number variants play in patients evaluated for a suspected diagnosis of inherited bone marrow failure syndromes. Clinical and genetic data of 323 patients from the Canadian Inherited Marrow Failure Registry from 2001 to 2014, who had a documented genetic work-up, were analyzed. Cases with pathogenic copy number variants (at least 1 kilobasepairs) were compared to cases with other mutations. Genotype-phenotype correlations were performed to assess the impact of copy number variants. Pathogenic nucleotide-level mutations were found in 157 of 303 tested patients (51.8%). Genome-wide copy number variant analysis by single-nucleotide polymorphism arrays or comparative genomic hybridization arrays revealed pathogenic copy number variants in 11 of 67 patients tested (16.4%). In four of these patients, identification of copy number variant was crucial for establishing the correct diagnosis as their clinical presentation was ambiguous. Eight additional patients were identified to harbor pathogenic copy number variants by other methods. Of the 19 patients with pathogenic copy number variants, four had compound-heterozygosity of a copy number variant with a nucleotide-level mutation. Pathogenic copy number variants were associated with more extensive non-hematological organ system involvement (p = 0.0006), developmental delay (p = 0.006) and short stature (p = 0.04) compared to nucleotide-level mutations. In conclusion, a significant proportion of patients with inherited bone marrow failure syndromes harbor pathogenic copy number variants which were associated with a more extensive non-hematological phenotype in this cohort. Patients with a phenotype suggestive of inherited bone marrow failure syndromes but without identification of pathogenic nucleotide-level mutations should undergo specific testing for copy number variants.

Abstract 174: The Use of Next-Generation Sequencing to Detect Copy Number Variation in the Molecular Diagnosis of Familial Hypercholesterolemia

Background: Familial hypercholesterolemia (FH) is a common monogenic disorder of lipoprotein metabolism, characterized by elevated LDL cholesterol and increased risk for premature cardiovascular disease. Efforts to provide a molecular diagnosis of FH are trending towards the use of targeted next-generation sequencing (NGS) panels to interrogate canonical FH-associated genes— LDLR , APOB , and PCSK9 —for clinically relevant small-scale variants. However, large-scale copy number variants (CNVs) or deldup variants constitute 10-15% of LDLR variants in many cohorts. Because these are not routinely accessible by NGS, a second assay, namely multiplex-ligation dependent probe amplification (MLPA), is currently required to screen for them. To increase efficiency and decrease costs associated with identifying the genetic causes for FH, use of a single platform to detect both small and large-scale variants would be extremely beneficial in a clinical setting. Objective: Here we determine the accuracy of NGS bioinformatic tools in identifying CNVs. Methods: In 313 clinically ascertained, unrelated patients with at least possible FH per the Dutch Lipid Clinic Network (DLCN) criteria, we sequenced canonical FH-associated genes using our targeted NGS panel (LipidSeq TM ). These patients were also assayed using MLPA. The CNV analysis tool (VarSeq® Golden Helix, Inc.) was run using the NGS data generated for each patient. Concordance between the NGS tool and standard MLPA was subsequently determined. Results: We evaluated a subset of 99 FH individuals: 19 were positive while 80 were negative for a LDLR mutation using MLPA. Our CNV analysis using bioinformatically processed NGS data compared to MLPA yielded 2 out of 19 false negatives and 0 out of 80 false positives. This translates to a sensitivity of 89% and a specificity of 100% for our NGS approach, considering MLPA as the current ’gold standard’. Conclusions: Analysis of deeply resequenced targeted NGS data for the identification of CNVs in FH shows excellent potential to become a standard diagnostic test for those with suspected FH, potentially eliminating the need for secondary MLPA analysis. Future applications of this NGS tool may also allow for novel CNV screening in additional FH-associated genes.

Detection and assessment of copy number variation using PacBio long-read and Illumina sequencing in New Zealand dairy cattle

Single nucleotide polymorphisms have been the DNA variant of choice for genomic prediction, largely because of the ease of single nucleotide polymorphism genotype collection. In contrast, structural variants (SV), which include copy number variants (CNV), translocations, insertions, and inversions, have eluded easy detection and characterization, particularly in nonhuman species. However, evidence increasingly shows that SV not only contribute a substantial proportion of genetic variation but also have significant influence on phenotypes. Here we present the discovery of CNV in a prominent New Zealand dairy bull using long-read PacBio (Pacific Biosciences, Menlo Park, CA) sequencing technology and the Sniffles SV discovery tool (version 0.0.1; https://github.com/fritzsedlazeck/Sniffles). The CNV identified from long reads were compared with CNV discovered in the same bull from Illumina sequencing using CNVnator (read depth-based tool; Illumina Inc., San Diego, CA) as a means of validation. Subsequently, further validation was undertaken using whole-genome Illumina sequencing of 556 cattle representing the wider New Zealand dairy cattle population. Very limited overlap was observed in CNV discovered from the 2 sequencing platforms, in part because of the differences in size of CNV detected. Only a few CNV were therefore able to be validated using this approach. However, the ability to use CNVnator to genotype the 557 cattle for copy number across all regions identified as putative CNV allowed a genome-wide assessment of transmission level of copy number based on pedigree. The more highly transmissible a putative CNV region was observed to be, the more likely the distribution of copy number was multimodal across the 557 sequenced animals. Furthermore, visual assessment of highly transmissible CNV regions provided evidence supporting the presence of CNV across the sequenced animals. This transmission-based approach was able to confirm a subset of CNV that segregates in the New Zealand dairy cattle population. Genome-wide identification and validation of CNV is an important step toward their inclusion in genomic selection strategies.