CNV Regions Research Articles

Whole-genome sequencing of copy number variation analysis in Ethiopian cattle reveals adaptations to diverse environments.

Genomic structural variations (GSVs), notably copy number variations (CNVs), significantly shape genetic diversity and facilitate adaptation in cattle populations. Despite their importance, the genome-wide characterization of CNVs in indigenous Ethiopian cattle breeds-Abigar, Fellata, and Gojjam-Highland remains largely unexplored. In this study, we applied a read-depth approach to whole genome sequencing (WGS) data to conduct the first comprehensive analysis of CNVs in these populations. We identified 3,893 CNV regions (CNVRs) covering 19.15Mb (0.71% of the cattle genome). These CNVRs ranged from 1.60kb to 488.0kb, with an average size of 4.92kb. These CNVRs included deletions (1713), duplications (1929), and mixed events (251) showing notable differences in distribution among the breeds. Four out of five randomly selected CNVRs were successfully validated using real time polymerase chain reaction (qPCR). Further analyses identified candidate genes associated with high-altitude adaptation (GBE1 and SOD1), heat stress adaptation (HSPA13, DNAJC18, and DNAJC8) and resistance to tick infestations (BoLA and KRT33A). In addition, variance stabilizing transformation (VST) statistics highlighted population-specific CNVRs, emphasizing the unique genetic signatures of high-altitude adaptation in the Gojjam-Highland cattle breed. Among the detected CNVRs, 4.93% (192 out of 3,893) overlapped with 520 quantitative traits loci (QTLs) associated with six economically important trait categories suggesting that these CNVRs may significantly contribute to the genetic variation underlying these traits. Our comprehensive analysis reveals significant CNVRs associated with key adaptive traits in Ethiopian cattle breeds highlighting their genetic diversity and resilience. These findings offer valuable insights into the genetic basis of adaptability and can inform sustainable breeding practices and conservation efforts. Future research should prioritize the functional validation of these CNVRs and their integration into breeding programs to enhance traits such as disease resistance and environmental adaptability.

Genome-wide copy number variation association study in anorexia nervosa.

This study represents the first large-scale investigation of rare (<1% population frequency) copy number variants (CNVs) in anorexia nervosa (AN). Large, rare CNVs are reported to be causally associated with anthropometric traits, neurodevelopmental disorders, and schizophrenia, yet their role in the genetic basis of AN is unclear. Using genome-wide association study (GWAS) array data from the Anorexia Nervosa Genetics Initiative (ANGI), which included 7414 AN case and 5044 controls, we investigated the association of 67 well-established syndromic CNVs and 178 pleiotropic disease-risk dosage-sensitive CNVs with AN. To identify novel CNV regions (CNVRs) that increase the risk of AN, we conducted genome-wide association studies with a focus on rare CNV-breakpoints (CNV-GWAS). We found no net enrichment of rare CNVs, either deletions or duplications, in AN, and none of the well-established syndromic or pleiotropic CNVs had a significant association with AN status. However, the CNV-GWAS found 21 nominally associated CNVRs that contribute to AN risk, covering protein-coding genes implicated in synaptic function, metabolic/mitochondrial factors, and lipid characteristics, like the CD36 (7q21.11) gene, which transports long-chain fatty acids into cells. CNVRs intersecting genes previously related to neurodevelopmental traits include deletions of NRXN1 intron 5 (2p16.3), IMMP2L (7q31.1), and PTPRD (9p23). Overall, given that our study is well powered to detect the CNV burden level reported for schizophrenia, we can conclude that rare CNVs have a limited role in the etiology of AN, as reported for bipolar disorder. Our nominal associations for the 21 discovered CNVRs are consistent with AN being a metabo-psychiatric trait, as demonstrated by the common genetic architecture of AN, and we provide association results to allow for replication in future research.

Insights into Adaption and Growth Evolution: Genome–Wide Copy Number Variation Analysis in Chinese Hainan Yellow Cattle Using Whole–Genome Re–Sequencing Data

Copy number variation (CNV) serves as a crucial source of genomic variation and significantly aids in the mining of genomic information in cattle. This study aims to analyze re–sequencing data from Chinese Hainan yellow cattle, to uncover breed CNV information, and to elucidate the resources of population genetic variation. We conducted whole–genome sequencing on 30 Chinese Hainan yellow cattle, thus generating 814.50 Gb of raw data. CNVs were called using CNVnator software, and subsequent filtering with Plink and HandyCNV yielded 197,434 high–quality CNVs and 5852 CNV regions (CNVRs). Notably, the proportion of deleted sequences (81.98%) exceeded that of duplicated sequences (18.02%), with the lengths of CNVs predominantly ranging between 20 and 500 Kb This distribution demonstrated a decrease in CNVR count with increasing fragment length. Furthermore, an analysis of the population genetic structure using CNVR databases from Chinese, Indian, and European commercial cattle breeds revealed differences between Chinese Bos indicus and Indian Bos indicus. Significant differences were also observed between Hainan yellow cattle and European commercial breeds. We conducted gene annotation for both Hainan yellow cattle and European commercial cattle, as well as for Chinese Bos indicus and Indian Bos indicus, identifying 206 genes that are expressed in both Chinese and Indian Bos indicus. These findings may provide valuable references for future research on Bos indicus. Additionally, selection signatures analysis based on Hainan yellow cattle and three European commercial cattle breeds identified putative pathways related to heat tolerance, disease resistance, fat metabolism, environmental adaptation, candidate genes associated with reproduction and the development of sperm and oocytes (CABS1, DLD, FSHR, HSD17B2, KDM2A), environmental adaptation (CNGB3, FAM161A, DIAPH3, EYA4, AAK1, ERBB4, ERC2), oxidative stress anti–inflammatory response (COMMD1, OXR1), disease resistance (CNTN5, HRH4, NAALADL2), and meat quality (EHHADH, RHOD, GFPT1, SULT1B1). This study provides a comprehensive exploration of CNVs at the molecular level in Chinese Hainan yellow cattle, offering theoretical support for future breeding and selection programs aimed at enhancing qualities of this breed.

Genome-wide detection and analysis of copy number variations in Sal sheep using a high-density SNP array

Purpose: to identify CNV regions (CNVRs) and identify potentially specific CNVs in Sal sheep.Materials and methods. The research was carried out on 48 Salsk breed sheep. Genotyping was performed using high-density microarrays Ovine SNP 600 K BeadChip array (Illumina, USA). DNA copy number variation (CNV) searches were performed using PennCNV software based on the Oar_v3.1 reference genome.Results. We identified 4585 autosomal CNVs in 48 Sal breed sheep. The average CNV length was 92,3 Kb. 21,1 % of the total number of CNVs are less than 50 Kb in size. On average, from 65 to 138 CNVs were identified per animal. 527 autosomal CNVRs were obtained, representing 54,77 Mb of the entire sheep genome. The proportion of chromosomes covered by CNVR varies by chromosome, from 0,5 % on OAR25 to 9 % on OAR24. Analysis of CNVR in the ENCEMBL system revealed 42 genes in which CNVRs are localized; the remaining CNVRs are located in intergenic regions. Comparison of the identified CNVRs with sheep QTLs from the Animal QTL database showed that 39,24 % of the genes were responsible for reproductive traits, and 20,25 % were responsible for wool-related traits.Conclusions. Functional annotation of CNVRs localized in genes and intergenic spaces was carried out and the total number of detected CNVRs in the QTL database was analyzed. The results showed that CNVs are localized in genes associated with selection-significant traits in sheep.

Copy Number Variation and Selection Signal: Exploring the Domestication History and Phenotype Differences Between Duroc and the Chinese Native Ningxiang Pigs.

The Ningxiang pig, one of the well-known Chinese native pig breeds, has the advantages of tender meat, high intramuscular fat (IMF) content, and roughage tolerance, compared to the commercial lean pig breeds. The genetic basis for complex traits in Ningxiang pigs has been previously studied through other genetic markers, such as Single Nucleotide Polymorphism (SNP), while the characteristics of copy number variation (CNV) and the selection signal have not been investigated yet. In this study, GGP 50 k genotyping data of 2242 Ningxiang pigs (NX) and 1137 Duroc pigs (Duroc) were involved in CNV atlas construction and selection signals identification. Annotations of genes and quantitative trait locus (QTLs) were performed on the target candidate regions, as follows: (1) 162 CNVs were detected in Ningxiang pigs, while 326 CNVs were detected in Duroc pigs, and there are 21 copy number variation regions (CNVRs) shared between them; (2) The CNVRs of Duroc are more abundant, with 192 CNVRs, accounting for 1.61% of the entire genome, while those of Ningxiang pigs only have 98 CNVRs, accounting for 0.49%; (3) The QTLs annotated on CNVs and selected regions of Ningxiang pigs were mainly associated with meat quality and fertility. In contrast, the Duroc QTLs' notes relate primarily to the carcass and immunity, and explain why they have a higher slaughter rate and immunity; (4) There is a presence of high-frequency acquired CNVs, specifically in Ningxiang pigs, with 24 genes significantly enriched in the sensory receptor-related pathway in this region; (5) Based on the CNVs atlas, candidate genes such as 3 inositol 1,4,5-triphosphate receptor, type 3 (ITPR3), forkhead box protein K2 (FOXK2), G-protein coupled estrogen receptor 1 (GPER1), Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), triosephosphate isomerase 1 (TPI1), and other candidate genes related to fat deposition and differentiation were screened. In general, this study improved our knowledge about copy number variation and selection signal information of Ningxiang pigs, which can not only further explain the genetic differences between Chinese native and Western commercial pig breeds, but also provide new materials for the analysis of the genetic basis of complex traits.

A comprehensive map of copy number variations in dromedary camels based on whole genome sequence data

Copy number variants (CNVs) are structural variants within the eukaryotic genome that vary among individuals of a species. These variants have been associated with different phenotypic traits, making them a valuable consideration as markers for designing breeding programmes. In this study, whole genome sequence data of 60 dromedary camel samples originating from the Arabian Peninsula were analyzed to construct a comprehensive dromedary CNV map. Utilizing four CNV callers employing read-depth, split-read and paired-end mapping approaches, a total of 37,519 CNV events (17,847 deletions and 19,672 duplications) were called on the dromedary autosomes. These CNV events were merged into 2,557 regions, categorized as 1,322 losses, 122 gains, and 1,113 “mixed regions” comprising both types. The cumulative size of the CNV regions amounted to 22.5 Mb, covering roughly 1.16% of the dromedary autosomes. Approximately 32% of the defined CNV regions (comprising 60% losses, 18% gains, and 0.27% mixed regions) were found in ≥ 90% of the dromedary samples, classifying them as prevalent regions. Genes with biological functions related to the different adaptive physiologies of dromedary camels, such as fertility, heat stress, musculoskeletal development, and fat metabolism, were overlapping with or in close proximity to ~ 68% of the defined CNV regions, demonstrating their potential role in dromedaries’ physiology. This study presents the first comprehensive CNV map of dromedary camels and builds on the present knowledge in understanding the genetic structure of this species.

121 Copy number variation: From mapping to variance components in Holsteins

Abstract Copy number variations (CNVs) modify transcription levels mainly through changing genes and regulatory elements dosages. Hence, CNVs can contribute to the additive genetic variance of quantitative traits, which might not be fully captured by SNPs. Here, CNVs were mapped from 3,601 Holsteins and their contribution to complex traits was explored by i) quantitative trait loci (QTL) enrichment analysis, and ii) variance component analysis for metritis (1 = disease, 0 = no disease). The 4,113 CNVs derived from high-density (777k) genotypic information were compiled into 1,184 CNV regions (CNVRs) overlapping 7,832 QTLs reported in dairy cattle and available in the AnimalQTLdb. Fisher’s exact test was applied to perform the QTL enrichment analysis followed by False Discovery Rate (FDR) correction. Then, QTLs overlapping CNVRs were enriched for traits when the corrected P-value (PFDR) was lower than 0.05. For variance components estimation, genomic information from all CNVs loci was used to build the CNV-derived genomic relationship matrix (CNV_GRM). CNV loci showing double deletions, single deletions, and normal state in the population were coded as 0, 1, and 2, respectively, whereas CNV loci presenting normal state, single duplications, and double duplications were coded as 0, 1, and 2, respectively. Given that some CNVs presented both deletions and duplications at the same position in the population, these mixed-CNVs were treated as two distinct CNVs loci, one to represent deletions and the other to represent duplications. The variance components for metritis were estimated by fitting either only a SNP-derived GRM (SNP_GRM) or jointly SNP_GRM and CNV_GRM considering 3,272 cows in models that included the female category and farm-year-season as fixed effects. QTLs overlapped with CNVRs were enriched for milk (e.g., milk fat yield, milk yield, and milk protein percentage), reproduction (e.g., calving ease, non-return rate, and heat intensity), exterior (e.g., teat length, udder depth, and udder height), production (e.g., length of productive life, lifetime profit index, and net merit), and health traits (e.g., immune globulin G level, somatic cell, and bovine respiratory susceptibility). Regarding variance components, copy number variations were able to capture a fraction of the additive genetic variance not captured by SNPs alone, increasing the heritability estimate for metritis. In summary, our findings suggest that CNVs overlap QTLs associated with economically important traits more than only by chance and CNVs can capture additional additive genetic variance not fully captured by SNPs alone.

Genome-wide copy number variation regions in indigenous (Bos indicus) cattle breeds of Tamil Nadu, India.

Identification of large scale structural polymorphisms (Copy number variations) of more than 50 bp between the individuals of a species would help in knowing genetic diversity, phenotypic variability, adaptability to tropical environment and disease resistance. Read depth-based method implemented in CNVnator was used for calling copy number variant regions on sequenced data obtained from WGS from 15 pooled samples belonging to five draught cattle breeds of Tamil Nadu. A total of 11,605 CNV regions (CNVRs) were observed covering a genome size of 18.63 percent. Among these, 11,459 were restricted to autosomes, consisting of 11,013 deletions, 353 duplications and 93 complex events. These CNVRs were annotated to 4,989 candidate genes. A total of 8,291 numbers of CNVRs were shared among the five cattle breeds as also supported by PCA and STRUCTURE analyses and 1,172 CNVRs were breed-specific. Four out of five selected breed-specific CNVRs were validated using real-time PCR. Genes with CNVRs are related to milk production (BTN1A1, ABCA1 and LAP3), disease resistance (TLR4 and DNAH8), adaptability (SOD1, CAST and SMARCAL1), growth (EGFR, NKAIN3), reproduction (BRWD1 and PDE6D), meat and carcass traits (MAP3K5 and NCAM1) and exterior (ATRN and MITF) traits. Gene enrichment analysis based on the gene list retrieved from the CNVRs disclosed over-represented terms (p<0.01) associated with milk fat production. NETWORK analysis had identified 13 putative candidate genes involved in milk fat percentage, milk fat yield, lactation persistency, milk yield, heat tolerance, calving ease, growth and conformation traits. The genome-wide CNVRs identified in the present study produced genome-wide partial CNV map in indigenous cattle breeds of Tamil Nadu.

Genome wide detection of CNV and their association with body size in Danzhou chickens

Copy number variation (CNV) is a crucial component of genetic diversity in the genome, serving as the foundation for the genetic architecture and phenotypic variability of complex traits. In this study, we examined CNVs in the Danzhou (DZ) chicken, an indigenous breed exclusive to Hainan Province, China. By employing whole-genome resequencing data from 200 DZ chickens, we conducted a comprehensive genome-wide analysis of CNVs using CNVpytor and performed CNV-based genome-wide association studies (GWAS) on six body size traits, including body slope length (BSL), keel length (KeL), tibial length (TiL), tibial circumference (TiC), chest width (ChW), and chest depth (ChD) utilizing linear mixed model methods considering a genomic relationship matrix. We identified a total of 144,265 autosomal CNVs among the 200 individuals, comprising 67,818 deletions and 76,447 duplications. After merging these variants together, we obtained 4,824 distinct copy number variant regions, which accounted for approximately 20% of the chicken autosomal genome. Furthermore, we discovered several significantly associated CNV segments with body size traits located proximal to genes such as IHH, WNT6, WNT10A, LPR4, FZD2, WNT7B, and GNAS that have been extensively implicated in skeletal development and growth processes. These findings enhance our understanding of CNVs in chickens and their potential impact on body size traits by revealing candidate genes involved in the regulation of these traits. This establishes a solid framework for future studies and may prove particularly beneficial for exploring genetic structural variation in chickens.

Genome-wide identification of copy number variations in wrinkled skin cases of Xiang pigs

Copy number variation (CNV) tends to occur in genetically enriched regions and is likely associated with a number of complex diseases such as skin aging. In this study, we investigated the genome-wide CNVs in 20 wrinkled skin cases (WSC) of Xiang pigs and 63 controls, and identified 7893 copy number variable regions (CNVRs). We estimated the F-statistic (Fst) at each locus and identified that 93 case-controls stratified CNVRs (Fst > = 0.15) overlapped with 87 known genes. Functional enrichment analysis showed that most of these genes were predominantly enriched in pathways and terms related to the extracellular matrix. Finally, we found that some CNVs were predicted to have high effects on genes such as VCAN, TIMP1 and FOXO1 through transcriptional amplification, transcript ablation and so on. Most of the genes overlapped with those CNVRs have been reported to be related to aging in human or animals. The copy numbers presented the positive correlations with the transcript level of the genes in skins between the cases and controls. Our results suggested that those 22 CNVRs, including 19 CNV losses and 3 CNV gains, were putatively associated with the skin wrinkle of Xiang pigs.

Genome-wide association study of copy number variations in Parkinson's disease.

Our study investigates the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data, aiming to uncover novel genetic mechanisms and improve the understanding of the role of CNVs in sporadic PD. We applied a sliding window approach to perform CNV-GWAS and conducted genome-wide burden analyses on CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium. We identified 14 genome-wide significant CNV loci associated with PD, including one deletion and 13 duplications. Among these, duplications in 7q22.1, 11q12.3 and 7q33 displayed the highest effect. Two significant duplications overlapped with PD-related genes SNCA and VPS13C, but none overlapped with recent significant SNP-based GWAS findings. Five duplications included genes associated with neurological disease, and four overlapping genes were dosage-sensitive and intolerant to loss-of-function variants. Enriched pathways included neurodegeneration, steroid hormone biosynthesis, and lipid metabolism. In early-onset cases, four loci were significantly associated with EOPD, including three known duplications and one novel deletion in PRKN. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results. This is the largest CNV-based GWAS in PD identifying novel CNV regions and confirming the significant CNV burden in EOPD, primarily driven by the PRKN gene, warranting further investigation.

Identification of copy-number variants in patients with overgrowth disorders.

Overgrowth syndromes (OGS) comprise a heterogeneous group of disorders whose main characteristic is that the weight, height or the head circumference are above the 97th centile or 2-3 standard deviations above the mean for age, gender, and ethnic group. Several copy-number variants (CNVs) have been associated with the development of OGS, such as the 5q35 microdeletion or the duplication of the 15q26.1-qter, among many others. In this study, we have applied 850K SNP-arrays to 112 patients and relatives with OGS from the Spanish OverGrowth Registry Initiative. We have identified CNVs associated with the disorder in nine individuals (8%). Subsequently, whole genome sequencing (WGS) analysis was performed in these nine samples in order to better understand these genomic imbalances. All the CNVs were detected by both techniques, settling that WGS is a useful tool for CNV detection. We have found six patients with genomic abnormalities associated with previously well-established disorders and three patients with CNVs of unknown significance, which may be related to OGS, based on scientific literature. In this report, we describe these findings and comment on genes associated with OGS that are located within the CNV regions.

Genome-wide detection of multiple variants associated with teat number in French Yorkshire pigs

BackgroundTeat number is a vital reproductive trait in sows, crucial for providing immunity and nutrition to piglets during lactation. However, “missing heritability” in Single Nucleotide Polymorphism (SNP)-based Genome-Wide Association Studies (GWAS) has led to an increasing focus on structural variations in the genetic analysis of complex biological traits.ResultsIn this study, we generated a comprehensive CNV map in a population of French Yorkshire pigs (n = 644) and identified 429 CNVRs. Notably, 44% (189 CNVRs) of these were detected for the first time. Subsequently, we conducted GWAS for teat number in the French Yorkshire pig population using both 80K chip and its imputed data, as well as a GWAS analysis based on CNV regions (CNVR). Interestingly, 80K chip GWAS identified two SNPs located on Sus scrofa chromosome 5 (SSC5) that were simultaneously associated with Total Teat Number (TTN), Left Teat Number (LTN), and Right Teat Number (RTN). The leading SNP (WU_10.2_5_76130558) explained 3.33%, 2.69%, and 2.67% of the phenotypic variance for TTN, LTN, and RTN, respectively. Moreover, through imputed GWAS, we successfully identified 30 genetic variants associated with TTN located within the 73.22 -73.30 Mb region on SSC5. The two SNPs identified in the 80K chip GWAS were also located in this region. In addition, CNVR-based GWAS revealed three significant CNVRs associated with TTN. Finally, through gene annotation, we pinpointed two candidate genes, TRIM66 and PRICKLE1, which are related to diverse processes such as breast cancer and abnormal vertebral development.ConclusionsOur research provides an in-depth analysis of the complex genetic structure underlying teat number, contributing to the genetic enhancement of sows with improved reproductive performance and, ultimately, bolstering the economic benefits of swine production enterprises.

Analysis of genomic copy number variations through whole-genome scan in Yunling cattle.

Yunling cattle is a new breed of beef cattle bred in Yunnan Province, China, which has the advantages of fast growth, excellent meat quality, improved tolerance ability, and important landscape value. Copy number variation (CNV) is a significant source of gene structural variation and plays a crucial role in evolution and phenotypic diversity. Based on the latest reference genome ARS-UCD2.0, this study analyzed the genome-wide distribution of CNVs in Yunling cattle using short-read whole-genome sequencing data (n = 129) and single-molecule long-read sequencing data (n = 1), and a total of 16,507 CNVs were detected. After merging CNVs with overlapping genomic positions, 3,728 CNV regions (CNVRs) were obtained, accounting for 0.61% of the reference genome. The functional analysis indicated significant enrichment of CNVRs in 96 GO terms and 57 KEGG pathways, primarily related to cell adhesion, signal transduction, neuromodulation, and nutritional metabolism. Additionally, 111 CNVRs overlapped with 76 quantitative trait loci (QTLs), including Subcutaneous fat thickness QTL, Longissimus muscle area QTL, and Marbling score QTL. Several CNVR-overlapping genes, including BZW1, AOX1, and LOC100138449, overlap with regions associated with meat color and quality QTLs. Furthermore, Vst analysis showed that PSMB4, ERICH1, SMC2, and PPP4R3A were highly divergent between Yunling and Brahman cattle. In summary, we have constructed the genomic CNV map of Yunling cattle for the first time using whole-genome resequencing. This provides valuable genetic variation resources for the study of the Yunling cattle genome and contributes to the study of economic traits in Yunling cattle.

A novel method addressing NGS-based mappability bias for sensitive detection of DNA alterations.

A turning point in cancer research is the introduction of massively parallel sequencing technology which greatly reduced the cost and time for genome sequencing. This enhanced the scope for detecting and analyzing the role of structural alterations in cancer. However, certain bias exists in NGS-based approaches, which badly affects the CNV identification process. Moreover, DNA repeats existing in CNV regions need special attention as they will degrade the performance of majority of the existing CNV detection tools, even after applying generalized bias correction method. This motivated this work, where a novel method has been designed to address the issue of DNA repeats and thereby mappability bias existing in regions of CNV.The method consists of three phases, where the first phase computes the alignment information of uniquely mapped DNA reads, considering the base quality and base mismatch parameters at nucleotide level precision. The second and the third phase use a novel approach to allocate the non-uniquely mapped reads to an optimal region of the DNA repeats based on a probabilistic membership model. The proposed method is capable of identifying CNVs present in coding, as well as non-coding region of the DNA, and is also capable of detecting CNVs existing in DNA repeat regions. The methodology achieves a sensitivity greater than [Formula: see text] during the performed simulations, and on real data, the detected variants are validated with the database of genomic variants, where the percentage overlap is also greater than 95%, and has achieved much better breakpoint prediction, as compared with other popular bias correction CNV detection methods.

Genome-wide association study reveals 2 copy number variations associated with the variation of plumage color in the white duck hybrid population

Plumage color is an intuitive external poultry characteristic with rich manifestations and complex genetic mechanisms. In our previous study, we observed that there were more dark variations in plumage color in the F2 population derived from the hybridization of 2 white duck varieties. Therefore, based on the statistics of plumage color of 308 F2 populations, we further used the resequencing data of these individuals to detect copy number variations (CNVs) in the whole genome and conducted genome-wide association studies (GWAS) to determine the genetic basis related to plumage color traits. The CNV detection revealed 9,337 CNVs, with an average length of 15,950 bp and a total length of 142.02 MB, accounting for approximately 12.91% of the reference genome. The CNV distribution on the chromosomes was relatively uniform, and the number of CNVs on each chromosome positively correlated with the length of the chromosome. In the pure black plumage group, 2,101 CNVs were only identified, and 1,714 were specifically identified in the pure white plumage group. Ten CNVs were randomly selected for validation using quantitative real-time PCR, and 9 CNVs had the same CNV types as predicted, with an accuracy of 90%. Based on GWAS, we identified 2 CNVs potentially associated with plumage color variations, with the associated CNV regions covering 9 genes. Enrichment analysis of these 9 candidate genes showed significant enrichment of 3 pathways (ribosome biogenesis in eukaryotes, RNA transport, and protein export) and 17 gene ontology terms. Among these, VWA5A can downregulate MITF by binding to the regulatory factors SOX10. The occurrence of CNV may indirectly contribute to duck plumage color variation by affecting the regulatory factors of the switch gene MITF in the melanogenesis pathway. These findings have improved the understanding of the genetic basis of duck plumage color variation and have been beneficial for developing and using plumage color traits in subsequent poultry breeding.

Association of copy number variation in X chromosome-linked PNPLA4 with heterotaxy and congenital heart disease.

Heterotaxy (HTX) is a thoracoabdominal organ anomaly syndrome and commonly accompanied by congenital heart disease (CHD). The aim of this study was to analyze rare copy number variations (CNVs) in a HTX/CHD cohort and to examine the potential mechanisms contributing to HTX/CHD. Chromosome microarray analysis was used to identify rare CNVs in a cohort of 120 unrelated HTX/CHD patients, and available samples from parents were used to confirm the inheritance pattern. Potential candidate genes in CNVs region were prioritized via the DECIPHER database, and PNPLA4 was identified as the leading candidate gene. To validate, we generated PNPLA4 -overexpressing human induced pluripotent stem cell lines as well as pnpla4 -overexpressing zebrafish model, followed by a series of transcriptomic, biochemical and cellular analyses. Seventeen rare CNVs were identified in 15 of the 120 HTX/CHD patients (12.5%). Xp22.31 duplication was one of the inherited CNVs identified in this HTX/CHD cohort, and PNPLA4 in the Xp22.31 was a candidate gene associated with HTX/CHD. PNPLA4 is expressed in the lateral plate mesoderm, which is known to be critical for left/right embryonic patterning as well as cardiomyocyte differentiation, and in the neural crest cell lineage. Through a series of in vivo and in vitro analyses at the molecular and cellular levels, we revealed that the biological function of PNPLA4 is importantly involved in the primary cilia formation and function via its regulation of energy metabolism and mitochondria-mediated ATP production. Our findings demonstrated a significant association between CNVs and HTX/CHD. Our data strongly suggested that an increased genetic dose of PNPLA4 due to Xp22.31 duplication is a disease-causing risk factor for HTX/CHD.

Single-nucleotide polymorphisms and copy number variations drive adaptive evolution to freezing stress in a subtropical evergreen broad-leaved tree: Hexaploid wild Camellia oleifera

Subtropical evergreen broad-leaved trees are usually vulnerable to freezing stress, while hexaploid wild Camellia oleifera shows strong freezing tolerance. As a valuable genetic resource of woody oil crop C. oleifera, wild C. oleifera can serve as a case for studying the molecular bases of adaptive evolution to freezing stress. Here, 47 wild C. oleifera from 11 natural distribution sites in China and 4 relative species of C. oleifera were selected for genome sequencing. “Min Temperature of Coldest Month” (BIO6) had the highest comprehensive contribution to wild C. oleifera distribution. The population genetic structure of wild C. oleifera could be divided into two groups: in cold winter (BIO6 ≤ 0 °C) and warm winter (BIO6 > 0 °C) areas. Wild C. oleifera in cold winter areas might have experienced stronger selection pressures and population bottlenecks with lower Ne than those in warm winter areas. 155 single-nucleotide polymorphisms (SNPs) were significantly correlated with the key bioclimatic variables (106 SNPs significantly correlated with BIO6). Twenty key SNPs and 15 key copy number variation regions (CNVRs) were found with genotype differentiation > 50% between the two groups of wild C. oleifera. Key SNPs in cis-regulatory elements might affect the expression of key genes associated with freezing tolerance, and they were also found within a CNVR suggesting interactions between them. Some key CNVRs in the exon regions were closely related to the differentially expressed genes under freezing stress. The findings suggest that rich SNPs and CNVRs in polyploid trees may contribute to the adaptive evolution to freezing stress.

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

Copy number variations in autistic children.

Autism spectrum disorder (ASD) manifests as a neurodevelopmental condition marked by challenges in social communication, interaction and the performing of repetitive behaviors. The prevalence of autism increases markedly on an annual basis; however, the etiology remains incompletely understood. Cytogenetically visible chromosomal abnormalities, including copy number variations (CNVs), have been shown to contribute to the pathogenesis of ASD. More than 1% of ASD conditions can be explained based on a known genetic locus, whereas CNVs account for 5-10% of cases. However, there are no studies on the Saudi Arabian population for the detection of CNVs linked to ASD, to the best of our knowledge. Therefore, the aim of the present study was to explore the prevalence of CNVs in autistic Saudi Arabian children. Genomic DNA was extracted from the peripheral blood of 14 autistic children along with four healthy control children and then array-based comparative genomic hybridization (aCGH) was used to detect CNVs. Bioinformatics analysis of the aCGH results showed the presence of recurrent and non-recurrent deletion/duplication CNVs in several regions of the genome of autistic children. The most frequent CNVs were 1q21.2, 3p26.3, 4q13.2, 6p25.3, 6q24.2, 7p21.1, 7q34, 7q11.1, 8p23.2, 13q32.3, 14q11.1-q11.2 and 15q11.1-q11.2. In the present study, CNVs in autistic Saudi Arabian children were identified to improve the understanding of the etiology of autism and facilitate its diagnosis. Additionally, the present study identified certain possible pathogenic genes in the CNV region associated with several developmental and neurogenetic diseases.