CNV Regions Research Articles

Assessment of copy number variants in three Brazilian locally adapted cattle breeds using whole-genome re-sequencing data.

Further characterization of genetic structural variations should strongly focus on small and endangered local breeds given their role in unraveling genes and structural variants underlying selective pressures and phenotype variation. A comprehensive genome-wide assessment of copy number variations (CNVs) based on whole-genome re-sequencing data was performed on three Brazilian locally adapted cattle breeds (Caracu Caldeano, Crioulo Lageano, and Pantaneiro) using the ARS-UCD1.2 genome assembly. Data from 36 individuals with an average coverage depth of 14.07× per individual was used. A total of 24 945 CNVs were identified distributed among the breeds (Caracu Caldeano=7285, Crioulo Lageano=7297, and Pantaneiro=10363). Deletion events were 1.75-2.07-fold higher than duplications, and the total length of CNVs is composed mostly of a high number of segments between 10 and 30 kb. CNV regions (CNVRs) are not uniformly scattered throughout the genomes (n=463), and 105 CNVRs were found overlapping among the studied breeds. Functional annotation of the CNVRs revealed variants with high consequence on protein sequence harboring relevant genes, in which we highlighted the BOLA-DQB, BOLA-DQA5, CD1A, β-defensins, PRG3, and ULBP21 genes. Enrichment analysis based on the gene list retrieved from the CNVRs disclosed over-represented terms (p < 0.01) strongly associated with immunity and cattle resilience to harsh environments. Additionally, QTL associated with body conformation and dairy-related traits were also unveiled within the CNVRs. These results provide better understanding of the selective forces shaping the genome of such cattle breeds and identify traces of natural selection pressures by which these populations have been exposed to challenging environmental conditions.

The impact of 22q11.2 copy-number variants on human traits in the general population

While extensively studied in clinical cohorts, the phenotypic consequences of 22q11.2 copy-number variants (CNVs) in the general population remain understudied. To address this gap, we performed a phenome-wide association scan in 405,324 unrelated UK Biobank (UKBB) participants by using CNV calls from genotyping array. We mapped 236 Human Phenotype Ontology terms linked to any of the 90 genes encompassed by the region to 170UKBB traits and assessed the association between these traits and the copy-number state of 504 genotyping array probes in the region. We found significant associations for eight continuous and nine binary traits associated under different models (duplication-only, deletion-only, U-shape, and mirror models). The causal effect of the expression level of 22q11.2 genes on associated traits was assessed through transcriptome-wide Mendelian randomization (TWMR), revealing that increased expression of ARVCF increased BMI. Similarly, increased DGCR6 expression causally reduced mean platelet volume, in line with the corresponding CNV effect. Furthermore, cross-trait multivariable Mendelian randomization (MVMR) suggested a predominant role of genuine (horizontal) pleiotropy in the CNV region. Our findings show that within the general population, 22q11.2 CNVs are associated with traits previously linked to genes in the region, and duplications and deletions act upon traits in different fashions. We also showed that gain or loss of distinct segments within 22q11.2 may impact a trait under different association models. Our results have provided new insights to help further the understanding of the complex 22q11.2 region.

Lipolysis and gestational diabetes mellitus onset: a case-cohort genome-wide association study in Chinese

BackgroundGenetic knowledge of gestational diabetes mellitus (GDM) in Chinese women is quite limited. This study aimed to identify the risk factors and mechanism of GDM at the genetic level in a Chinese population.MethodsWe conducted a genome-wide association study (GWAS) based on single nucleotide polymorphism (SNP) array genotyping (ASA-CHIA Bead chip, Illumina) and a case-cohort study design. Variants including SNPs, copy number variants (CNVs), and insertions-deletions (InDels) were called from genotyping data. A total of 2232 pregnant women were enrolled in their first/second trimester between February 2018 and December 2020 from Anqing Municipal Hospital in Anhui Province, China. The GWAS included 193 GDM patients and 819 subjects without a diabetes diagnosis, and risk ratios (RRs) and their 95% confidence intervals (CIs) were estimated by a regression-based method conditional on the population structure. The calling and quality control of genotyping data were performed following published guidelines. CNVs were merged into CNV regions (CNVR) to simplify analyses. To interpret the GWAS results, gene mapping and overexpression analyses (ORAs) were further performed to prioritize the candidate genes and related biological mechanisms.ResultsWe identified 14 CNVRs (false discovery rate corrected P values < 0.05) and two suggestively significant SNPs (P value < 0.00001) associated with GDM, and a total of 19 candidate genes were mapped. Ten genes were significantly enriched in gene sets related to lipase (triglyceride lipase and lipoprotein lipase) activity (LIPF, LIPK, LIPN, and LIPJ genes), oxidoreductase activity (TPH1 and TPH2 genes), and cellular components beta-catenin destruction complex (APC and GSK3B genes), Wnt signalosome (APC and GSK3B genes), and lateral element in the Gene Ontology resource (BRCA1 and SYCP2 genes) by two ORA methods (adjusted P values < 0.05).ConclusionsGenes related to lipolysis, redox reaction, and proliferation of islet β-cells are associated with GDM in Chinese women. Energy metabolism, particularly lipolysis, may play an important role in GDM aetiology and pathology, which needs further molecular studies to verify.

Comparative analyses of copy number variations between swamp buffaloes and river buffaloes.

As an important source of genomic variation, copy number variation (CNV) contributes to environmental adaptation in worldwide buffaloes. Despite this importance, CNV divergence between swamp buffaloes and river buffaloes has not been studied previously. Here, we report 21 152 CNV regions (CNVRs) in 141 buffaloes of 20 breeds detected through multiple CNV calling strategies. Only 248 CNVRs were shared between river buffalo and swamp buffalo, reflecting great variation of CNVRs between the two subspecies. Population structure analysis based on CNVs successfully separated the two buffalo subspecies. We further assessed CNV divergence by calculating FST for genome-wide CNVs. Totally, we identified 110 significantly divergent CNV segments and 44 putatively selected genes between river buffaloes and swamp buffaloes. In particular, LALBA, a key gene controlling milk production in cattle, presented a highly differentiated CNV in the promoter region, which makes it a strong functional candidate gene for differences between swamp buffaloes and river buffaloes in traits related to milk production. Our study provides useful information of CNVs in buffaloes, which may help explain the genetic differences between the two subspecies.

Population differentiated copy number variation between Eurasian wild boar and domesticated pig populations

Sus scrofa is a globally distributed livestock species that still maintains two different ways of life: wild and domesticated. Herein, we detected copy number variation (CNV) of 328 animals using short read alignment on Sscrofa11.1. We compared CNV among five groups of porcine populations: Asian domesticated (AD), European domesticated (ED), Asian wild (AW), European wild (EW), and Near Eastern wild (NEW). In total, 21,673 genes were identified on 154,872 copy number variation region (CNVR). Differences in gene copy numbers between populations were measured by considering the variance-based value {V}_{ST} and the one-way ANOVA test followed by Scheffe test. As a result, 111 genes were suggested as copy number variable genes. Abnormally gained copy number on EEA1 in all populations was suggested the presence of minor CNV in the reference genome assembly, Sscrofa11.1. Copy number variable genes were related to meat quality, immune response, and reproduction traits. Hierarchical clustering of all individuals and mean pairwise {V}_{ST} in breed level were visualized genetic relationship of 328 individuals and 56 populations separately. Our findings have shown how the complex history of pig evolution appears in genome-wide CNV of various populations with different regions and lifestyles.

Genomewide Association Study Identifies Copy Number Variants Associated With Warfarin Dose Response and Risk of Venous Thromboembolism in African Americans.

The anticoagulant warfarin is commonly used to control and prevent thrombotic disorders, such as venous thromboembolism (VTE), which disproportionately afflicts African Americans. Despite the importance of copy number variants (CNVs), few studies have focused on characterizing and understanding their role in drug response and disease risk among African Americans. In this study, we conduct the first genome-wide analysis of CNVs to more comprehensively account for the contribution of genetic variation in warfarin dose requirement and VTE risk among African Americans. We used hidden Markov models to detect CNVs from high-throughput single-nucleotide polymorphism arrays for 340 African American participants in the International Warfarin Pharmacogenetics Consortium. We identified 11,570 CNVs resulting in 2,038 copy number variable regions (CNVRs) and found 3 CNVRs associated with warfarin dose requirement and 3 CNVRs associated with VTE risk in African Americans. CNVRs 1q31.2del and 6q14.1del were associated with increased warfarin dose requirement (β=11.18 and 4.94, respectively; Pemp =< 0.002); CNVR 19p13.31del was associated with decreased warfarin dose requirement (β=-1.41, Pemp =0.0004); CNVRs (2p22.1del and 5q35.1-q35.2del) were found to be associated with increased risk of VTE (odds ratios (ORs)=1.88 and 14.9, respectively; Pemp ≤0.02); and CNVR 10q26.12del was associated with a decreased risk of VTE (OR=0.6; Pemp =0.05). Modeling of the 10q26.12del in HepG2 cells revealed that this deletion results in decreased fibrinogen gene expression, decreased fibrinogen and WDR11 protein levels, and decreased secretion of fibrinogen into the extracellular matrix. We found robust evidence that CNVRs could contribute to warfarin dose requirement and risk of VTE in African Americans and for 10q26.3del describe a possible pathogenic mechanism.

Comparative genomic diversity analysis of copy number variations (CNV) in indicine and taurine cattle thriving in Europe and Indian subcontinent

Copy number variations (CNVs) include deletions, duplications, and insertions that are larger than 50 bp in size causing structural variation responsible for diversity, adaptation, and breed development. Indian cattle breeds are highly diverse from the taurine breeds. The pattern of CNVRs in 191 animals belonging to 39 cattle breeds (four Indicine and 35 Taurine) was studied based on Illumina 777K BovineHD chip data. The Indicine breeds revealed 2590 CNVs and 335 copy number variation regions (CNVRs) in autosomes. Out of the identified CNVs, 50 were found to be novel. Structure analysis revealed admixed nature of Siri. Neighbor joining tree from CNVR data showed that hot (Kankrej and Hallikar) and cold (Ladakhi and Siri) adapted cattle breeds clustered separately. CNVR of Indian and European breeds revealed that Balkan and Italian breeds of Podolian group are admixed with Indian cattle breeds corroborating indicine introgression (6.1–13.5%). CNVRs spanning the regions of olfactory receptors and immune system genes were identified. AMOVA revealed 9% variation among populations which is 2% greater than SNP based studies showing higher inclusion of variation by CNVR. Detailed analysis of CNVs/CNVRs in Indian cattle adapted to hot and cold climate, and their diversity among worldwide cattle is presented in this study.

A novel scatterplot-based method to detect copy number variation (CNV).

Objective: Most methods to detect copy number variation (CNV) have high false positive rates, especially for small CNVs and in real-life samples from clinical studies. In this study, we explored a novel scatterplot-based method to detect CNVs in microarray samples. Methods: Illumina SNP microarray data from 13,254 individuals were analyzed with scatterplots and by PennCNV. The data were analyzed without the prior exclusion of low-quality samples. For CNV scatterplot visualization, the median signal intensity of all SNPs located within a CNV region was plotted against the median signal intensity of the flanking genomic region. Since CNV causes loss or gain of signal intensities, carriers of different CNV alleles pop up in clusters. Moreover, SNPs within a deletion are not heterozygous, whereas heterozygous SNPs within a duplication show typical 1:2 signal distribution between the alleles. Scatterplot-based CNV calls were compared with standard results of PennCNV analysis. All discordant calls as well as a random selection of 100 concordant calls were individually analyzed by visual inspection after noise-reduction. Results: An algorithm for the automated scatterplot visualization of CNVs was developed and used to analyze six known CNV regions. Use of scatterplots and PennCNV yielded 1019 concordant and 108 discordant CNV calls. All concordant calls were evaluated as true CNV-findings. Among the 108 discordant calls, 7 were false positive findings by the scatterplot method, 80 were PennCNV false positives, and 21 were true CNVs detected by the scatterplot method, but missed by PennCNV (i.e., false negative findings). Conclusion: CNV visualization by scatterplots allows for a reliable and rapid detection of CNVs in large studies. This novel method may thus be used both to confirm the results of genome-wide CNV detection software and to identify known CNVs in hitherto untyped samples.

Segregation patterns and inheritance rate of copy number variations regions assessed in a Gochu Asturcelta pig pedigree

Copy Number Variation Regions (CNVR) were subjected to pedigree analysis to contribute to the understanding of their segregation patterns. Up to 492 Gochu Asturcelta pig individuals forming 478 different parents-offspring trios (61 different families) were genotyped using the Axiom_PigHDv1 Array (658,692 SNPs). CNVR calling, performed using two different platforms (PennCNV and QuantiSNP), allowed to identify a total of 344 candidate CNVR on the 18 porcine autosomes covering about 106.8 Mb of the pig genome. Sixty-nine CNVR were identified, to some extent, in both the parents and the offspring and were classified as segregating CNVR. The other candidate CNVR were called in one or more progeny but in neither parent and classified either as singleton or recurrent de novo CNVR. Segregating CNVR were, on average, larger and more frequent than the recurrent de novo CNVR (444.8 kb vs 287.9 kb long and 34 vs 5 individuals, respectively). In any case, segregating CNVR did not conform to strict Mendelian inheritance patterns: estimates of average paternal and maternal transmission rates ranged from 11.0 % to 13.4 % and mean inheritance rate was below 21 %. This issue should be carefully considered when interpreting the results of CNV studies. Segregating CNVR, present across generations, are unlikely to be artifacts or false positives and can be hypothesized to be important at the population level.

CNV-PCC: An efficient method for detecting copy number variations from next-generation sequencing data.

Copy number variations (CNVs) significantly influence the diversity of the human genome and the occurrence of many complex diseases. The next-generation sequencing (NGS) technology provides rich data for detecting CNVs, and the read depth (RD)-based approach is widely used. However, low CN (copy number of 3-4) duplication events are challenging to identify with existing methods, especially when the size of CNVs is small. In addition, the RD-based approach can only obtain rough breakpoints. We propose a new method, CNV-PCC (detection of CNVs based on Principal Component Classifier), to identify CNVs in whole genome sequencing data. CNV-PPC first uses the split read signal to search for potential breakpoints. A two-stage segmentation strategy is then implemented to enhance the identification capabilities of low CN duplications and small CNVs. Next, the outlier scores are calculated for each segment by PCC (Principal Component Classifier). Finally, the OTSU algorithm calculates the threshold to determine the CNVs regions. The analysis of simulated data results indicates that CNV-PCC outperforms the other methods for sensitivity and F1-score and improves breakpoint accuracy. Furthermore, CNV-PCC shows high consistency on real sequencing samples with other methods. This study demonstrates that CNV-PCC is an effective method for detecting CNVs, even for low CN duplications and small CNVs.

Genome-wide association analysis reveals 6 copy number variations associated with the number of cervical vertebrae in Pekin ducks.

As a critical developmental stage in vertebrates, the vertebral column formation process is under strict control; however, we observed variations in the number of cervical vertebrae in duck populations in our previous study. Here, we further explored the variations in the number of vertebrae in two duck populations: 421 Pekin duck × mallard F2 ducks and 850 Pekin ducks. Using resequencing data of 125 Pekin ducks with different numbers of cervical vertebrae and 352 Pekin duck × mallard F2 ducks with different numbers of thoracic vertebrae, we detected whole-genome copy number variations (CNVs) and implemented a genome-wide association study (GWAS) to identify the genetic variants related to the traits. The findings verified the existence of variations in the number of cervical vertebrae in duck populations. The number of cervical vertebrae in most ducks was 15, while that in a small number of the ducks was 14 or 16. The number of cervical vertebrae had a positive influence on the neck production, and one cervical vertebra addition could increase 11g or 2cm of duck neck. Genome-wide CNV association analysis identified six CNVs associated with the number of cervical vertebrae, and the associated CNV regions covered 15 genes which included WNT10A and WNT6. These findings improve our understanding of the variations in the number of vertebrae in ducks and lay a foundation for future duck breeding.

The correlation between copy number variation in Chromosome 14 and DNA methylation in Saudi autistic children.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that represents a range of aberrant behaviour symptoms such as repetitive behaviours and defects in social communication. The prevalence of ASD has been increasing worldwide and many studies have reported that both genetic and epigenetic factors play an important role in the etiology of this disorder. The aim of this study was to investigate the implementation of DNA methylation and Copy number variation (CNV) in the diagnosis of ASD. This study was carried out on 14 Saudi autistic children and four of their healthy siblings. Comparative genomic hybridization array was used to identify CNV in chromosome 14 and MethyLight qPCR was used to estimate levels of DNA methylation. The results identified CNVs in six cytobands in chromosome 14 for 13 out of 14 autistic samples: 14q11.1-q11.2, 14q11.2, 14q12, 14q21.1, 14q32.2, and 14q32.33. However, some of these cytobands were also found in normal samples with different sizes. Interestingly, chromosomal abnormalities in 14q11.1-q11.2 was only found in ASD samples. The result also showed an increase in methylation ratio of ASD samples in those CNV regions compared with their siblings. The findings suggest that CNV in 14q11.1-q11.2 might be a potential target in ASD diagnosis and further work is required to detect which biological pathways are affected.

CmirC: an integrated database of clustered miRNAs co-localized with copy number variations in cancer

Genomic rearrangements and copy number variations (CNVs) are the major regulators of clustered microRNAs (miRNAs) expression. Several clustered miRNAs are harbored in and around chromosome fragile sites (CFSs) and cancer-associated genomic hotspots. Aberrant expression of such clusters can lead to oncogenic or tumor suppressor activities. Here, we developed CmirC (Clustered miRNAs co-localized with CNVs), a comprehensive database of clustered miRNAs co-localized with CNV regions. The database consists of 481 clustered miRNAs co-localized with CNVs and their expression patterns in 35 cancer types of the TCGA. The portal also provides information on CFSs, miRNA cluster candidates, genomic coordinates, target gene networks, and gene functionality. The web portal is integrated with advanced tools such as JBrowse, NCBI-BLAST, GeneSCF, visNetwork, and NetworkD3 to help the researchers in data analysis, visualization, and browsing. This portal provides a promising avenue for integrated data analytics and offers additional evidence for the complex regulation of clustered miRNAs in cancer. The web portal is freely accessible at http://slsdb.manipal.edu/cmirclust to explore clinically significant miRNAs.

Identification and functional interpretation of miRNAs affected by rare CNVs in CAKUT

Rare copy number variants (CNVs) are among the most common genomic disorders underlying CAKUT. miRNAs located in rare CNVs represent well-founded functional variants for human CAKUT research. The study aimed to identify and functionally interpret miRNAs most frequently affected by rare CNVs in CAKUT and to estimate the overall burden of rare CNVs on miRNA genes in CAKUT. The additional aim of this study was to experimentally confirm the effect of a rare CNV in CAKUT on candidate miRNA’s expression and the subsequent change in mRNA levels of selected target genes. A database of CAKUT-associated rare CNV regions, created by literature mining, was used for mapping of the miRNA precursors. miRNAs and miRNA families, most frequently affected by rare CAKUT-associated CNVs, have been subjected to bioinformatic analysis. CNV burden analysis was performed to identify chromosomes with over/underrepresentation of miRNA genes in rare CNVs associated with CAKUT. A functional study was performed on HEK293 MIR484+/- KO and HEK293 WT cell lines, followed by the analysis of relative miRNA and mRNA target gene levels. 80% of CAKUT patients with underlying rare CNV had at least one miRNA gene overlapping the identified CNV. Network analysis of the most frequently affected miRNAs has revealed the dominant regulation of the two miRNAs, hsa-miR-484 and hsa-miR-185-5p. Additionally, miR-548 family members have shown substantial enrichment in rare CNVs in CAKUT. An over/underrepresentation of miRNA genes in rare CNVs associated with CAKUT was observed in multiple chromosomes, such as chr16, chr20, and chr21. A significant 0.37 fold downregulation of hsa-miR-484, followed by a notable upregulation of MDM2 and APAF1 and downregulation of NOTCH3 was detected in HEK293 MIR484+/- KO compared to HEK293 WT cell lines, supporting the study hypothesis. miRNA genes are frequently affected by rare CNVs in CAKUT patients. Understanding the potential of CNV-affected miRNAs to participate in CAKUT as genetic drivers represent a crucial implication for the development of novel therapeutic approaches.

Copy number variations: A novel molecular marker for papillary thyroid cancer

BackgroundWe aimed to screen tumor-associated functional genes on a large scale through copy number variation (CNV) analysis of papillary thyroid cancer (PTC). MethodsWe analyzed 74 tissue samples from 41 patients with thyroid nodules. The samples were subjected to whole-genome resequencing and then analyzed by the ‘WISECONDOR’ method. Potential chromosome CNV regions were identified between the different sample groups. ResultsOf the 74 samples from 41 patients, 28 were PTC tissue samples, 29 were para-carcinoma tissue samples, 13 were benign tumor tissue samples and 4 were para-benign tumor tissue samples. According to our findings, PTC can be identified by CNVs at the corresponding positions on chromosomes 5, 7, 8, 10, and 17. For carcinoma tissue, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and area under the curve (AUC) of the test method were 100%, 66.7%, 87.5%, 100.0%, 90.0% and 0.83 (95% confidence interval [CI], 0.67–1.00) and for para-carcinoma tissue, these values were 96.6%, 75.0%, 96.6%, 75.0%, 93.9% and 0.86 (95% CI, 0.60–1.00). ConclusionCNV analysis assays involving high-volume sequencing analysis can increase the identification of PTC, potentially avoiding errors caused by position deflection in sampling.

Identification of copy number variations and candidate genes for reproduction traits in Finnish pig populations

Animal breeding programs can be improved by genetic markers associated with production and reproduction traits.Reproduction traits are important for economic success of pig production and therefore development of genetictools for selection is of high interest to pig breeding. In this study our objective was to identify genomic regions associatedwith fertility traits in two Finnish pig breeds using large scale SNP genotyping and genome wide associationanalysis and characterization of copy number variations (CNV). Since CNVs are structural variations of the genomethey potentially have a large effect on gene expression and protein function. We analyzed 1265 genotyped boarsfor nine different reproduction traits and identified 46 CNV regions encompassing 13 genes. 11 of the CNV regionswere shared between the breeds, 20 were unique to the Finnish Yorkshire and 15 to the Finnish Landrace. The genomewide association (GWAS) analysis identified zero to five reproduction associated genomic regions per trait.Furthermore, we identified 23 genomic regions with 20 candidate genes associated with fertility traits using GWASanalysis. The identified CNV regions were compared against GWAS regions to detect candidate regions with an effecton reproduction traits. This study reports candidate genes and genomic regions within two Finnish pig breedsfor reproduction traits, which can be utilized in breeding programs.

BMI-CNV: a Bayesian framework for multiple genotyping platforms detection of copy number variants.

Whole-exome sequencing (WES) enables the detection of copy number variants (CNVs) with high resolution in protein-coding regions. However, variants in the intergenic or intragenic regions are excluded from studies. Fortunately, many of these samples have been previously sequenced by other genotyping platforms which are sparse but cover a wide range of genomic regions, such as SNP array. Moreover, conventional single sample-based methods suffer from a high false discovery rate due to prominent data noise. Therefore, methods for integrating multiple genotyping platforms and multiple samples are highly demanded for improved copy number variant detection. We developed BMI-CNV, a Bayesian Multisample and Integrative CNV (BMI-CNV) profiling method with data sequenced by both whole-exome sequencing and microarray. For the multisample integration, we identify the shared copy number variants regions across samples using a Bayesian probit stick-breaking process model coupled with a Gaussian Mixture model estimation. With extensive simulations, BMI-copy number variant outperformed existing methods with improved accuracy. In the matched data from the 1000 Genomes Project and HapMap project data, BMI-CNV also accurately detected common variants and significantly enlarged the detection spectrum of whole-exome sequencing. Further application to the data from The Research of International Cancer of Lung consortium (TRICL) identified lung cancer risk variant candidates in 17q11.2, 1p36.12, 8q23.1, and 5q22.2 regions.

Copy number variations of LRRFIP1 gene and the relationship with growth traits in four Chinese sheep

CNVs (copy number variations) are the novel and common structural variants that could cover entire genes found in plenty of species. CNV may influence economically important traits or disease susceptibility in livestock species. Based on the whole genome resequencing results, we found that there was a CNV region on the LRRFIP1 gene. Then we used qPCR to detect the copy number type distribution in 553 individuals of four sheep breeds and used them for association analysis. The results showed that: (1) In the CKS, the sheep with gain type had a larger heart girth (p = 0.049). (2) For the HS, the CNV could significantly affect rump breadth (p = 0.037) and circumference of the cannon (p = 0.035). And the sheep with median type showed better performance in rump breadth and circumference of cannon. (3) At the STHS, the CNV was significantly correlated with chest width (p = 0.000) with loss type as the most favorable CNV type. Meanwhile, the best was the loss type, and the lowest was the median. (4) This CNV had no significant effect on the LTHS. So, the CNV of LRRFIP1 was related to the growth traits of these three sheep breeds and it may be used as a molecular marker for sheep.

PSXII-1 CNV and Cnvr Detection from High-Density SNP Genotyping in Holstein Cattle

Abstract Copy number variation (CNV) represents an important source of genetic variation complementary to single nucleotide polymorphism (SNP) and provides valuable insights into the genetic architecture of complex traits in humans and livestock animals. However, many factors affect CNV detection, including sample size. Previous studies in Holstein cattle have only used hundreds of individuals. Therefore, in the present study, CNVs were identified from high-density genotype array data in 3,529 Holstein cows from 16 herds located in 7 U.S. states. CNVs were derived from 546,802 autosomal SNP markers with MAF &amp;gt; 0.05 and call rate &amp;gt; 0.90 using the intensity signals at each SNP position in a hidden Markov model implemented in PennCNV software. The log R ratio (LRR) values were corrected based on the guanine-cytosine content in the genomic regions located 500 kb upstream and downstream of each marker. After detection, CNVs presenting LRR ≤ 0.30, B allele frequency drift &amp;lt; 0.01, waviness factor ≤ 0.05, number of SNPs &amp;gt; 10 and length &amp;gt; 1 kb were merged into CNV regions (CNVR) using CNVRanger. A total of 1,881 non-redundant CNV events spanning the entire genome were identified in 1,771 cows, with a mean of 10 CNVs per individual and ranging from 1 to 27. The highest percentage of CNV calls was located on BTA7 (16%), while only 9 CNVs were identified on BTA9. The CNV calls were grouped into 685 CNVRs covering 3.07% of the bovine autosomal genome. The number of CNVRs with copy loss and gain were 356 and 310, and both types were observed in 19 regions. The chromosomal distribution of CNVR revealed that BTA7 harbors 38 CNVRs, while only 2 were detected on BTA28. These results will support further research on the contribution of CNVs and CNVRs to the genetic architecture of complex traits in Holstein cattle.

Rare copy number variation in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24–71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10−8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further.