Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins

Genome-wide association analyses reveals copy number variant regions associated with reproduction and disease traits in Canadian Holstein cattle

This study aimed to evaluate the impact of copy number variants (CNVs) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing Log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole genome sequence data from 126 animals, resulting in 870 high-confidence CNV regions (CNVRs) on 12,131 animals. Out of these, 54 CNVRs had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVRs were significantly (p-value < 3.7 × 10-5) associated with at least one of the traits analyzed in this study. Specifically, 2 CNVRs were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and non-return rate), and 2 CNVRs were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVRs harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVRs on the mentioned traits are warranted.

Genome-wide association study between copy number variation and feeding behavior, feed efficiency, and growth traits in Nellore cattle

BACKGROUND

Feeding costs represent the largest expenditures in beef production. Therefore, the animal efficiency in converting feed in high-quality protein for human consumption plays a major role in the environmental impact of the beef industry and in the beef producers' profitability. In this context, breeding animals for improved feed efficiency through genomic selection has been considered as a strategic practice in modern breeding programs around the world. Copy number variation (CNV) is a less-studied source of genetic variation that can contribute to phenotypic variability in complex traits. In this context, this study aimed to: (1) identify CNV and CNV regions (CNVRs) in the genome of Nellore cattle (Bos taurus indicus); (2) assess potential associations between the identified CNVR and weaning weight (W210), body weight measured at the time of selection (WSel), average daily gain (ADG), dry matter intake (DMI), residual feed intake (RFI), time spent at the feed bunk (TF), and frequency of visits to the feed bunk (FF); and, (3) perform functional enrichment analyses of the significant CNVR identified for each of the traits evaluated.

RESULTS

A total of 3,161 CNVs and 561 CNVRs ranging from 4,973 bp to 3,215,394 bp were identified. The CNVRs covered up to 99,221,894 bp (3.99%) of the Nellore autosomal genome. Seventeen CNVR were significantly associated with dry matter intake and feeding frequency (number of daily visits to the feed bunk). The functional annotation of the associated CNVRs revealed important candidate genes related to metabolism that may be associated with the phenotypic expression of the evaluated traits. Furthermore, Gene Ontology (GO) analyses revealed 19 enrichment processes associated with FF.

CONCLUSIONS

A total of 3,161 CNVs and 561 CNVRs were identified and characterized in a Nellore cattle population. Various CNVRs were significantly associated with DMI and FF, indicating that CNVs play an important role in key biological pathways and in the phenotypic expression of feeding behavior and growth traits in Nellore cattle.

Descriptive Statistics and Genome-Wide Copy Number Analysis of Milk Production Traits of Jiangsu Chinese Holstein Cows

Milk production traits are the most important quantitative economic traits in dairy cow production; improving the yield and quality of milk is an important way to ensure the production efficiency of the dairy industry. This study carried out a series of in-depth statistical genetics studies and molecular analyses on the Chinese Holstein cows in the Jiangsu Province, such as descriptive statistics and copy number variation analysis. A genetic correlation, phenotypic correlation, and descriptive statistical analysis of five milk production traits (milk yield, milk fat percentage, milk fat yield, milk protein percentage, and milk protein yield) of the dairy cows were analyzed using the SPSS and DMU software. Through quality control, 4173 cows and their genomes were used for genomic study. Then, SNPs were detected using DNA chips, and a copy number variation (CNV) analysis was carried out to locate the quantitative trait loci (QTL) of the milk production traits by Perl program software Penn CNV and hidden Markov model (HMM). The phenotypic means of the milk yield, milk fat percentage, milk fat mass, milk protein percentage, and milk protein mass at the first trimester were lower than those at the other trimesters by 8.821%, 1.031%, 0.930%, 0.003%, and 0.826%, respectively. The five milk production traits showed a significant phenotypic positive correlation (p < 0.01) and a high genetic positive correlation among the three parities. Based on the GGPBovine 100 K SNP data, QTL-detecting research on the fist-parity milk performance of dairy cows was carried out via the CNV. We identified 1731 CNVs and 236 CNVRs in the 29 autosomes of 984 Holstein dairy cows, and 19 CNVRs were significantly associated with the milk production traits (p < 0.05). These CNVRs were analyzed via a bioinformatics analysis; a total of 13 gene ontology (GO) terms and 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to lipid metabolism, amino acid metabolism, and cellular catabolic processes. This study provided a theoretical basis for the molecular-marker-assisted selection of dairy cows by developing descriptive statistics on the milk production traits of dairy cows and by locating the QTL and functional genes that affect the milk production traits of first-born dairy cows. The results describe the basic status of the milk production traits of the Chinese Holstein cows in Jiangsu and locate the QTL and functional genes that affect the milk production traits of the first-born cows, providing a theoretical basis for the molecular-marker-assisted selection of dairy cows.

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.

Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef Cattle

Meat quality is an economically important trait for global food production. Copy number variations (CNVs) have been previously implicated in elucidating the genetic basis of complex traits. In this article, we detected a total of 112,198 CNVs and 10,102 CNV regions (CNVRs) based on the Bovine HD SNP array. Next, we performed a CNV-based genome-wide association analysis (GWAS) of six meat quality traits and identified 12 significant CNV segments corresponding to eight candidate genes, including PCDH15, CSMD3, etc. Using region-based association analysis, we further identified six CNV segments relevant to meat quality in beef cattle. Among these, TRIM77 and TRIM64 within CNVR4 on BTA29 were detected as candidate genes for backfat thickness (BFT). Notably, we identified a 34 kb duplication for meat color (MC) which was supported by read-depth signals, and this duplication was embedded within the keratin gene family including KRT4, KRT78, and KRT79. Our findings will help to dissect the genetic architecture of meat quality traits from the aspects of CNVs, and subsequently improve the selection process in breeding programs.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Identification of copy number variations in the genome of Dairy Gir cattle

Studying structural variants that can control complex traits is relevant for dairy cattle production, especially for animals that are tolerant to breeding conditions in the tropics, such as the Dairy Gir cattle. This study identified and characterized high confidence copy number variation regions (CNVR) in the Gir breed genome. A total of 38 animals were whole-genome sequenced, and 566 individuals were genotyped with a high-density SNP panel, among which 36 animals had both sequencing and SNP genotyping data available. Two sets of high confidence CNVR were established: one based on common CNV identified in the studied population (CNVR_POP), and another with CNV identified in sires with both sequence and SNP genotyping data available (CNVR_ANI). We found 10 CNVR_POP and 45 CNVR_ANI, which covered 1.05 Mb and 4.4 Mb of the bovine genome, respectively. Merging these CNV sets for functional analysis resulted in 48 unique high confidence CNVR. The overlapping genes were previously related to embryonic mortality, environmental adaptation, evolutionary process, immune response, longevity, mammary gland, resistance to gastrointestinal parasites, and stimuli recognition, among others. Our results contribute to a better understanding of the Gir breed genome. Moreover, the CNV identified in this study can potentially affect genes related to complex traits, such as production, health, and reproduction.

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.

Genome-wide elucidation of CNV regions and their association with production and reproduction traits in composite Vrindavani cattle

The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.

Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations

BACKGROUND

Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens.

RESULTS

The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP - SNP and DUP - SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays.

CONCLUSIONS

The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.

The Contribution of Copy Number Variants and Single Nucleotide Polymorphisms to the Additive Genetic Variance of Carcass Traits in Cattle

The relative contributions of both copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) to the additive genetic variance of carcass traits in cattle is not well understood. A detailed understanding of the relative importance of CNVs in cattle may have implications for study design of both genomic predictions and genome-wide association studies. The first objective of the present study was to quantify the relative contributions of CNV data and SNP genotype data to the additive genetic variance of carcass weight, fat, and conformation for 945 Charolais, 923 Holstein-Friesian, and 974 Limousin sires. The second objective was to jointly consider SNP and CNV data in a least absolute selection and shrinkage operator (LASSO) regression model to identify genomic regions associated with carcass weight, fat, and conformation within each of the three breeds separately. A genomic relationship matrix (GRM) based on just CNV data did not capture any variance in the three carcass traits when jointly evaluated with a SNP-derived GRM. In the LASSO regression analysis, a total of 987 SNPs and 18 CNVs were associated with at least one of the three carcass traits in at least one of the three breeds. The quantitative trait loci (QTLs) corresponding to the associated SNPs and CNVs overlapped with several candidate genes including previously reported candidate genes such as MSTN and RSAD2, and several potential novel candidate genes such as ACTN2 and THOC1. The results of the LASSO regression analysis demonstrated that CNVs can be used to detect associations with carcass traits which were not detected using the set of SNPs available in the present study. Therefore, the CNVs and SNPs available in the present study were not redundant forms of genomic data.

Genome-wide association analyses of carcass traits using copy number variants and raw intensity values of single nucleotide polymorphisms in cattle

BACKGROUND

The carcass value of cattle is a function of carcass weight and quality. Given the economic importance of carcass merit to producers, it is routinely included in beef breeding objectives. A detailed understanding of the genetic variants that contribute to carcass merit is useful to maximize the efficiency of breeding for improved carcass merit. The objectives of the present study were two-fold: firstly, to perform genome-wide association analyses of carcass weight, carcass conformation, and carcass fat using copy number variant (CNV) data in a population of 923 Holstein-Friesian, 945 Charolais, and 974 Limousin bulls; and secondly to perform separate association analyses of carcass traits on the same population of cattle using the Log R ratio (LRR) values of 712,555 single nucleotide polymorphisms (SNPs). The LRR value of a SNP is a measure of the signal intensity of the SNP generated during the genotyping process.

RESULTS

A total of 13,969, 3,954, and 2,805 detected CNVs were tested for association with the three carcass traits for the Holstein-Friesian, Charolais, and Limousin, respectively. The copy number of 16 CNVs and the LRR of 34 SNPs were associated with at least one of the three carcass traits in at least one of the three cattle breeds. With the exception of three SNPs, none of the quantitative trait loci detected in the CNV association analyses or the SNP LRR association analyses were also detected using traditional association analyses based on SNP allele counts. Many of the CNVs and SNPs associated with the carcass traits were located near genes related to the structure and function of the spliceosome and the ribosome; in particular, U6 which encodes a spliceosomal subunit and 5S rRNA which encodes a ribosomal subunit.

CONCLUSIONS

The present study demonstrates that CNV data and SNP LRR data can be used to detect genomic regions associated with carcass traits in cattle providing information on quantitative trait loci over and above those detected using just SNP allele counts, as is the approach typically employed in genome-wide association analyses.

Genome Structural Variation Landscape and Its Selection Signatures in the Fast-growing Strains of the Pacific Oyster, Crassostrea gigas

The Pacific oyster (Crassostrea gigas) genome is highly polymorphic and affluent in structural variations (SVs), a significant source of genetic variation underlying inter-individual differences. Here, we used two genome assemblies and 535 individuals of genome re-sequencing data to construct a comprehensive landscape of structural variations in the Pacific oyster. Through whole-genome alignment, 11,087 short SVs and 11,561 copy number variations (CNVs) were identified. While analysis of re-sequencing data revealed 511,170 short SVs and 979,486 CNVs, a total of 63,100 short SVs and 58,182 CNVs were identified in at least 20 samples and regarded as common variations. Based on the common short SVs, both Fst and Pi ratio statistical methods were employed to detect the selective sweeps between 20 oyster individuals from the fast-growing strain and 20 individuals from their corresponding wild population. A total of 514 overlapped regions (8.76 Mb), containing 746 candidate genes, were identified by both approaches, in addition with 103 genes within 61 common CNVs only detected in the fast-growing strains. The GO enrichment and KEGG pathway analysis indicated that the identified candidate genes were mostly associated with apical part of cell and were significantly enriched in several metabolism-related pathways, including tryptophan metabolism and histidine metabolism. This work provided a comprehensive landscape of SVs and revealed their responses to selection, which will be valuable for further investigations on genome evolution under selection in the oysters.

Genome-wide association study between copy number variants and hoof health traits in Holstein dairy cattle

Genome-wide association studies based on SNP have been completed for multiple traits in dairy cattle; however, copy number variants (CNV) could add genomic information that has yet to be harnessed. The objectives of this study were to identify CNV in genotyped Holstein animals and assess their association with hoof health traits using deregressed estimated breeding values as pseudophenotypes. A total of 23,256 CNV comprising 1,645 genomic regions were identified in 5,845 animals. Fourteen genomic regions harboring structural variations, including 9 deletions and 5 duplications, were associated with at least 1 of the studied hoof health traits. This group of traits included digital dermatitis, interdigital dermatitis, heel horn erosion, sole ulcer, white line lesion, sole hemorrhage, and interdigital hyperplasia; no regions were associated with toe ulcer. Twenty candidate genes overlapped with the regions associated with these traits including SCART1, NRXN2, KIF26A, GPHN, and OR7A17. In this study, an effect on infectious hoof lesions could be attributed to the PRAME (Preferentially Expressed Antigen in Melanoma) gene. Almost all genes detected in association with noninfectious hoof lesions could be linked to known metabolic disorders. The knowledge obtained considering information of associated CNV to the traits of interest in this study could improve the accuracy of estimated breeding values. This may further increase the genetic gain for these traits in the Canadian Holstein population, thus reducing the involuntary animal losses due to lameness.

IRLnc: a novel functional noncoding RNA contributes to intramuscular fat deposition

Background

Intramuscular fat (IMF) is associated with meat quality and insulin resistance in animals. Research on genetic mechanism of IMF decomposition has positive meaning to pork quality and diseases such as obesity and type 2 diabetes treatment. In this study, an IMF trait segregation population was used to perform RNA sequencing and to analyze the joint or independent effects of genes and long intergenic non-coding RNAs (lincRNAs) on IMF.

Results

A total of 26 genes including six lincRNA genes show significantly different expression between high- and low-IMF pigs. Interesting, one lincRNA gene, named IMF related lincRNA (IRLnc) not only has a 292-bp conserved region in 100 vertebrates but also has conserved up and down stream genes (< 10 kb) in pig and humans. Real-time quantitative polymerase chain reaction (RT-qPCR) validation study indicated that nuclear receptor subfamily 4 group A member 3 (NR4A3) which located at the downstream of IRLnc has similar expression pattern with IRLnc. RNAi-mediated loss of function screens identified that IRLnc silencing could inhibit both of the RNA and protein expression of NR4A3. And the in-situ hybridization co-expression experiment indicates that IRLnc may directly binding to NR4A3. As the NR4A3 could regulate the catecholamine catabolism, which could affect insulin sensitivity, we inferred that IRLnc influence IMF decomposition by regulating the expression of NR4A3.

Conclusions

In conclusion, a novel functional noncoding variation named IRLnc has been found contribute to IMF by regulating the expression of NR4A3. These findings suggest novel mechanistic approach for treatment of insulin resistance in human beings and meat quality improvement in animal.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07349-5.

Copy number variation analysis reveals variants associated with milk production traits in dairy goats

Copy number variation (CNV) is a major type of genomic structural variation. We investigated their impacts on goat dairy traits using the CaprineSNP50 array. From 120 samples of five dairy goat breeds, we totally identified 42 CNVs ranging from 56,044 bp to 4,337,625 bp. We found significant associations between two CNVs (CNV5 and CNV25) and two milk production traits (mean of milk fat yield and mean of milk protein yield) after false discovery rate (FDR) correction (P < 0.05). CNV5 overlaps the ADAMTS20 gene, which is involved in the differentiation of mammary cell and plays a crucial role in lactogenic activity of bovine mammary epithelial cells. CNV25 overlaps with PAPPA2, which has been found to be associated with bovine reproduction and milk production traits. Our results revealed that CNVs overlapped with ADAMTS20 and PAPPA2 could be involved in goat dairy traits and function as candidate markers for further genetic selection.

Distribution and association study of PLAG1 gene between copy number variation and Chinese cattle populations

Copy number variation mainly refers to the copy number change of DNA fragments from 1 to 5 Mb. The deletion, duplication, inversion and ectopic of these fragments are collectively referred to as CNV. Numerous studies have shown that transfer factors play a vital role in regulating the growth and development of the body, for example the pleomorphic adenoma gene (PLAG). However, there is no study of CNV in PLAG1 gene. We qualified copy numbers within PLAG1 gene in 8 cattle breeds (Qinchuan, Qaidamu, Jinjiang, Guangfeng, Ji'an, Jiaxian, Pinan and Xianan cattle) by quantitative PCR, and explored their impacts on CNV of PLAG1 gene and phenotypic traits in Xianan cattle. We defined Deletion into CN = 0, Normal into CN = 1 and Duplication into CN = 2. The results showed that the individual with type of CN = 1 has a significant better effect on heart girth in JA cattle population (p < 0.01); the individual with type of CN = 1 and CN = 0 has a better effect on Rump length in JX cattle population (p < 0.05); the individual with type of CN = 0 has a better effect on cannon bone circumference in XN cattle population (p < 0.05). Association analysis showed that in JA cattle, the number of CN = 2 is great in JA cattle population, and the performance of CN = 2 in heart girth is better than CN = 1; in JX cattle, the rump length of CN = 2 is less than individual with CN = 0 and CN = 1; in XN cattle, individuals with CN = 0 have a better performance on cannon bone circumference than others. The results can provide a theoretical basis for molecular breeding of Chinese cattle, molecular mark-assist selection (MAS) of growth traits of Chinese cattle, and rapidly establish a Chinese cattle population with excellent genetic resources. Simple summaryWith the living standards rising, people's demand for beef is getting higher and higher, and there is a great significance to improve the growth performance of cattle. We measured body size data and detected copy number type of different cattle breeds (Xianan cattle, Ji'an cattle and Jiaxian cattle), and analyzed the correlation between the two object. We found that copy number variation of PLAG1 gene significantly affected some growth traits of XN cattle, JA cattle, and JX cattle. This may provide the basic material for molecular marker-assisted selection breeding of Chinese cattle breeds.

Copy number variation of the USP16 gene and its association with milk traits in Chinese Holstein cattle

Copy number variations (CNVs) were similar to single nucleotide polymorphisms (SNPs) and insertion-deletion (InDel), regarded as genetic variations in many species. CNV is defined as the variable change of DNA segment length compared with the reference genome, including gains or losses from 50 bp to several mega bases. The functions of USP16 gene are diverse, such as regulating the cell cycle, DNA damage, histone H2A deubiquitination or mitotic nuclear division. To analyze the relationship between CNV of USP16 gene and milk traits in Chinese Holstein, we used qPCR to detect the individuals of Chinese Holstein (n = 180). The results showed that the effect of USP16 gene CNV on daily milk yield and fat percentage had significant difference (p < 0.05). The gain was the advantage type in daily milk yield and the loss was the advantage type in fat percentage. Therefore, CNV of USP16 gene is an important factor of milk traits in Chinese Holstein. Meanwhile, it may be used as a molecular marker for assisted selection of milk traits in Chinese Holstein, which provides a theoretical basis for the genetic improvement of cow breeds in China.

Integrating Genome-Wide CNVs Into QTLs and High Confidence GWAScore Regions Identified Positional Candidates for Sheep Economic Traits

Copy number variations (CNVs) are important source of genetic variation, which can affect diverse economic traits through a variety of mechanisms. In addition, genome scan can identify many quantitative trait loci (QTLs) for the economic traits, while genome-wide association studies (GWAS) can localize genetic variants associated with the phenotypic variations. Here, we developed a method called GWAScore which collected GWAS summary data to identify potential candidates, and integrated CNVs into QTLs and high confidence GWAScore regions to detect crucial CNV markers for sheep growth traits. We got 197 candidate genes which were overlapping with the candidate CNVs. Some crucial genes (MYLK3, TTC29, HERC6, ABCG2, RUNX1, etc.) showed significantly elevated GWAScore peaks than other candidate genes. In this study, we developed the GWAScore method to excavate the potential value of candidate genes as markers for the sheep molecular breeding.

Association Analysis to Copy Number Variation (CNV) of Opn4 Gene with Growth Traits of Goats

Simple Summary

Copy number variation is a common genetic polymorphism and is mainly represented by submicroscopic levels of deletion and duplication which are caused by rearrangement of the genome. It is well known that copy number variations of genes are associated with growth traits of livestock. In this study, we detected the correlation between the copy number variation of the Opn4 gene and growth traits of Guizhou goats. We found that the copy number variation of the Opn4 gene had a significant influence on the body length and body weight of Guizhou goats. The results may provide preliminary suggestions into Guizhou goat breeding and new insights into the future of CNV as a new promising molecular marker in animal breeding.

Abstract

Extensive research has been carried out regarding the correlation between the growth traits of livestock and genetic polymorphisms, including single nucleotide polymorphisms and copy number variations (CNV). The purpose of this study was to analyze the CNV and its genetic effects of the Opn4 gene in 284 Guizhou goats (Guizhou black goat: n = 186, Guizhou white goat: n = 98). We used qPCR to detect the CNV of the Opn4 gene in Guizhou goats, and the classification results were correlated with the corresponding individual growth traits by SPSS software. The results showed that the Opn4 gene had a superior effect on growth traits with multiple copy variants in Guizhou black goats, and there was a significant correlation between copy number variation sites and body length traits. Contrary to the former conclusion, in Guizhou white goats, individuals with the Normal copy number type showed superior growth traits and copy number variant sites were significantly associated with body weight traits. Therefore, the CNV of the Opn4 gene can be used as a candidate molecular genetic marker to improve goat growth traits, speeding up the breeding process of goat elite varieties.

Concordance rate between copy number variants detected using either high- or medium-density single nucleotide polymorphism genotype panels and the potential of imputing copy number variants from flanking high density single nucleotide polymorphism haplotypes in cattle

Background

The trading of individual animal genotype information often involves only the exchange of the called genotypes and not necessarily the additional information required to effectively call structural variants. The main aim here was to determine if it is possible to impute copy number variants (CNVs) using the flanking single nucleotide polymorphism (SNP) haplotype structure in cattle. While this objective was achieved using high-density genotype panels (i.e., 713,162 SNPs), a secondary objective investigated the concordance of CNVs called with this high-density genotype panel compared to CNVs called from a medium-density panel (i.e., 45,677 SNPs in the present study). This is the first study to compare CNVs called from high-density and medium-density SNP genotypes from the same animals. High (and medium-density) genotypes were available on 991 Holstein-Friesian, 1015 Charolais, and 1394 Limousin bulls. The concordance between CNVs called from the medium-density and high-density genotypes were calculated separately for each animal. A subset of CNVs which were called from the high-density genotypes was selected for imputation. Imputation was carried out separately for each breed using a set of high-density SNPs flanking the midpoint of each CNV. A CNV was deemed to be imputed correctly when the called copy number matched the imputed copy number.

Results

For 97.0% of CNVs called from the high-density genotypes, the corresponding genomic position on the medium-density of the animal did not contain a called CNV. The average accuracy of imputation for CNV deletions was 0.281, with a standard deviation of 0.286. The average accuracy of imputation of the CNV normal state, i.e. the absence of a CNV, was 0.982 with a standard deviation of 0.022. Two CNV duplications were imputed in the Charolais, a single CNV duplication in the Limousins, and a single CNV duplication in the Holstein-Friesians; in all cases the CNV duplications were incorrectly imputed.

Conclusion

The vast majority of CNVs called from the high-density genotypes were not detected using the medium-density genotypes. Furthermore, CNVs cannot be accurately predicted from flanking SNP haplotypes, at least based on the imputation algorithms routinely used in cattle, and using the SNPs currently available on the high-density genotype panel.

Population Structure, and Selection Signatures Underlying High-Altitude Adaptation Inferred From Genome-Wide Copy Number Variations in Chinese Indigenous Cattle

Copy number variations (CNVs) have been demonstrated as crucial substrates for evolution, adaptation and breed formation. Chinese indigenous cattle breeds exhibit a broad geographical distribution and diverse environmental adaptability. Here, we analyzed the population structure and adaptation to high altitude of Chinese indigenous cattle based on genome-wide CNVs derived from the high-density BovineHD SNP array. We successfully detected the genome-wide CNVs of 318 individuals from 24 Chinese indigenous cattle breeds and 37 yaks as outgroups. A total of 5,818 autosomal CNV regions (683 bp-4,477,860 bp in size), covering ~14.34% of the bovine genome (UMD3.1), were identified, showing abundant CNV resources. Neighbor-joining clustering, principal component analysis (PCA), and population admixture analysis based on these CNVs support that most Chinese cattle breeds are hybrids of Bos taurus taurus (hereinafter to be referred as Bos taurus) and Bos taurus indicus (Bos indicus). The distribution patterns of the CNVs could to some extent be related to the geographical backgrounds of the habitat of the breeds, and admixture among cattle breeds from different districts. We analyzed the selective signatures of CNVs positively involved in high-altitude adaptation using pairwise Fst analysis within breeds with a strong Bos taurus background (taurine-type breeds) and within Bos taurus×Bos indicus hybrids, respectively. CNV-overlapping genes with strong selection signatures (at top 0.5% of Fst value), including LETM1 (Fst = 0.490), TXNRD2 (Fst = 0.440), and STUB1 (Fst = 0.420) within taurine-type breeds, and NOXA1 (Fst = 0.233), RUVBL1 (Fst = 0.222), and SLC4A3 (Fst=0.154) within hybrids, were potentially involved in the adaptation to hypoxia. Thus, we provide a new profile of population structure from the CNV aspects of Chinese indigenous cattle and new insights into high-altitude adaptation in cattle.

Functional and population genetic features of copy number variations in two dairy cattle populations

BACKGROUND

Copy Number Variations (CNVs) are gain or loss of DNA segments that are known to play a role in shaping a wide range of phenotypes. In this study, we used two dairy cattle populations, Holstein Friesian and Jersey, to discover CNVs using the Illumina BovineHD Genotyping BeadChip aligned to the ARS-UCD1.2 assembly. The discovered CNVs were investigated for their functional impact and their population genetics features.

RESULTS

We discovered 14,272 autosomal CNVs, which were aggregated into 1755 CNV regions (CNVR) from 451 animals. These CNVRs together cover 2.8% of the bovine autosomes. The assessment of the functional impact of CNVRs showed that rare CNVRs (MAF < 0.01) are more likely to overlap with genes, than common CNVRs (MAF ≥ 0.05). The Population differentiation index (Fst) based on CNVRs revealed multiple highly diverged CNVRs between the two breeds. Some of these CNVRs overlapped with candidate genes such as MGAM and ADAMTS17 genes, which are related to starch digestion and body size, respectively. Lastly, linkage disequilibrium (LD) between CNVRs and BovineHD BeadChip SNPs was generally low, close to 0, although common deletions (MAF ≥ 0.05) showed slightly higher LD (r2 = ~ 0.1 at 10 kb distance) than the rest. Nevertheless, this LD is still lower than SNP-SNP LD (r2 = ~ 0.5 at 10 kb distance).

CONCLUSIONS

Our analyses showed that CNVRs detected using BovineHD BeadChip arrays are likely to be functional. This finding indicates that CNVs can potentially disrupt the function of genes and thus might alter phenotypes. Also, the population differentiation index revealed two candidate genes, MGAM and ADAMTS17, which hint at adaptive evolution between the two populations. Lastly, low CNVR-SNP LD implies that genetic variation from CNVs might not be fully captured in routine animal genetic evaluation, which relies solely on SNP markers.

Detection and analysis of genome-wide copy number variation in the pig genome using an 80 K SNP Beadchip

Copy number variation (CNV) is an important source of genetic variability in human or animal genomes and play key roles in phenotypic diversity and disease susceptibility. In the present study, we performed a genome-wide analysis for CNV detection using SNP genotyping data of 857 Large White pigs. A total of 312 CNV regions (CNVRs) were detected with the PennCNV algorithm, which covered 57.76 Mb of the pig genome and correspond to 2.36% of the genome sequence. The length of the CNVRs on autosomes ranged from 1.77 Kb to 1.76 Mb with an average of 185.11 Kb. Of these, 220 completely or partially overlapped with 1,092 annotated genes, which enriched a wide variety of biological processes. Comparisons with previously reported pig CNVR revealed 92 (29.49%) novel CNVRs. Experimentally, 80% of CNVRs selected randomly were validated by quantitative PCR (qPCR). We also performed an association analysis between some of the CNVRs and reproductive traits, with results demonstrating the potential importance of CNVR61 and CNVR283 associated with litter sizes. Notably, the GPER1 gene located in CNVR61 plays a key role in reproduction. Our study is an important complement to the CNV map in the pig genome and provides valuable information for investigating the association between genomic variation and economic traits.

Integrative analysis of APOL3 gene CNV for adult cattle stature

Copy number variations (CNVs) have been identified as another important structural variation of genome. In recent years, a large amount of CNVRs have been identified in humans and animals. However, association and dosage effects studies of CNVs are very limited. Apolipoprotein L3 (APOL3) gene plays a central role in modulating gene transcription and is located within a CNVR that encompasses quantitative trait locis (QTLs) for economic traits like meat quality. Herein, we analyzed the CNV polymorphism of APOL3 in 421 individuals from five distinct cattle breeds, and then correlated their genotypes with growth traits. Association analysis revealed that the APOL3 CNV was significantly associated with hip height and cannon circumference of Xianan (XN) cattle (P < .01), and visibly associated with body slanting length and hucklebone width of Pinan (PN) cattle (P < .05). Overall, the data provide evidence for the functional role of APOL3 CNV and a basis for future applications in cattle breeding.

Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep

Copy number variation (CNV) is a major source of genomic structural variation. The aim of this study was to detect genomic CNV regions (CNVR) in Valle del Belice dairy sheep population and to identify those affecting milk production traits. The GO analysis identified possible candidate genes and pathways related to the selected traits. We identified CNVs in 416 individuals genotyped using the Illumina OvineSNP50 BeadChip array. The CNV association using a correlation-trend test model was examined with the Golden Helix SVS 8.7.0 tool. Significant CNVs were detected when their adjusted p-value was <0.01 after false discovery rate (FDR) correction. We identified 7,208 CNVs, which gave 365 CNVRs after aggregating overlapping CNVs. Thirty-one CNVRs were significantly associated with one or more traits included in the analysis. All CNVRs, except those on OAR19, overlapped with quantitative trait loci (QTL), even if they were not directly related to the traits of interest. A total of 222 genes were annotated within the significantly associated CNVRs, most of which played important roles in biological processes related to milk production and health-related traits. Identification of the genes in the CNVRs associated with the studied traits will provide the basis for further investigation of their role in the metabolic pathways related to milk production and health traits.

Array CGH-based detection of CNV regions and their potential association with reproduction and other economic traits in Holsteins

BACKGROUND

Copy number variations (CNVs) are structural variants consisting of large-scale insertions and deletions of genomic fragments. Exploring CNVs and estimating their effects on phenotypes are useful for genome selection but remain challenging in the livestock.

RESULTS

We identified 1043 CNV regions (CNVRs) from array comparative genomic hybridization (CGH) data of 47 Holstein bulls. Using a probe-based CNV association approach, we detected 87 CNVRs significantly (Bonferroni-corrected P value < 0.05) associated with at least one out of 41 complex traits. Within them, 39 CNVRs were simultaneously associated with at least 2 complex traits. Notably, 24 CNVRs were markedly related to daughter pregnancy rate (DPR). For example, CNVR661 containing CYP4A11 and CNVR213 containing CTR9, respectively, were associated with DPR and other traits related to reproduction, production, and body conformation. CNVR758 was also significantly related to DPR, with a nearby gene CAPZA3, encoding one of F-actin-capping proteins which play a role in determining sperm architecture and male fertility. We corroborated these CNVRs by examining their overlapped quantitative trait loci and comparing with previously published CNV results.

CONCLUSION

To our knowledge, this is one of the first genome-wide association studies based on CNVs called by array CGH in Holstein cattle. Our results contribute substantial information about the potential CNV impacts on reproduction, health, production, and body conformation traits, which lay the foundation for incorporating CNV into the future dairy cattle breeding program.

Variational Inference for Coupled Hidden Markov Models Applied to the Joint Detection of Copy Number Variations

Hidden Markov models provide a natural statistical framework for the detection of the copy number variations (CNV) in genomics. In this context, we define a hidden Markov process that underlies all individuals jointly in order to detect and to classify genomics regions in different states (typically, deletion, normal or amplification). Structural variations from different individuals may be dependent. It is the case in agronomy where varietal selection program exists and species share a common phylogenetic past. We propose to take into account these dependencies inthe HMM model. When dealing with a large number of series, maximum likelihood inference (performed classically using the EM algorithm) becomes intractable. We thus propose an approximate inference algorithm based on a variational approach (VEM), implemented in the CHMM R package. A simulation study is performed to assess the performance of the proposed method and an application to the detection of structural variations in plant genomes is presented.

A global analysis of CNVs in diverse yak populations using whole-genome resequencing

Background

Genomic structural variation represents a source for genetic and phenotypic variation, which may be subject to selection during the environmental adaptation and population differentiation. Here, we described a genome-wide analysis of copy number variations (CNVs) in 16 populations of yak based on genome resequencing data and CNV-based cluster analyses of these populations.

Results

In total, we identified 51,461 CNV events and defined 3174 copy number variation regions (CNVRs) that covered 163.8 Mb (6.2%) of yak genome with more “loss” events than both “gain” and “both” events, and we confirmed 31 CNVRs in 36 selected yaks using quantitative PCR. Of the total 163.8 Mb CNVR coverage, a 10.8 Mb region of high-confidence CNVRs directly overlapped with the 52.9 Mb of segmental duplications, and we confirmed their uneven distributions across chromosomes. Furthermore, functional annotation indicated that the CNVR-harbored genes have a considerable variety of molecular functions, including immune response, glucose metabolism, and sensory perception. Notably, some of the identified CNVR-harbored genes associated with adaptation to hypoxia (e.g., DCC, MRPS28, GSTCD, MOGAT2, DEXI, CIITA, and SMYD1). Additionally, cluster analysis, based on either individuals or populations, showed that the CNV clustering was divided into two origins, indicating that some yak CNVs are likely to arisen independently in different populations and contribute to population difference.

Conclusions

Collectively, the results of the present study advanced our understanding of CNV as an important type of genomic structural variation in yak, and provide a useful genomic resource to facilitate further research on yak evolution and breeding.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5451-5) contains supplementary material, which is available to authorized users.

Probe-based association analysis identifies several deletions associated with average daily gain in beef cattle

BACKGROUND

Average daily gain (ADG) is an important trait that contributes to the production efficiency and economic benefits in the beef cattle industry. The molecular mechanisms of ADG have not yet been fully explored because most recent association studies for ADG are based on SNPs or haplotypes. We reported a systematic CNV discovery and association analysis for ADG in Chinese Simmental beef cattle.

RESULTS

Our study identified 4912 nonredundant CNVRs with a total length of ~ 248.7 Mb, corresponding to ~ 8.9% of the cattle genome. Using probe-based CNV association, we identified 24 and 12 significant SNP probes within five deletions and two duplications for ADG, respectively. Among them, we found one common deletion with 89 kb imbedded in LHFPL Tetraspan Subfamily Member 6 (LHFPL6) at 22.9 Mb on BTA12, which has high frequency (12.9%) dispersing across population. CNV selection test using V_ST statistic suggested this common deletion may be under positive selection in Chinese Simmental cattle. Moreover, this deletion was not overlapped with any candidate SNP for ADG compared with previous SNPs-based association studies, suggesting its important role for ADG. In addition, we identified one rare deletion near gene Growth Factor Receptor-bound Protein 10 (GRB10) at 5.1 Mb on BTA4 for ADG using both probe-based association and region-based approaches.

CONCLUSIONS

Our results provided some valuable insights to elucidate the genetic basis of ADG in beef cattle, and these findings offer an alternative perspective to understand the genetic mechanism of complex traits in terms of copy number variations in farm animals.

Modeling copy number variation in the genomic prediction of maize hybrids

Our study indicates that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids. Moreover, predicting hybrid phenotypes by combining additive-dominance effects with copy variants has the potential to be a viable predictive model. Non-additive effects resulting from the actions of multiple loci may influence trait variation in single-cross hybrids. In addition, complementation of allelic variation could be a valuable contributor to hybrid genetic variation, especially when crossing inbred lines with higher contents of copy gains. With this in mind, we aimed (1) to study the association between copy number variation (CNV) and hybrid phenotype, and (2) to compare the predictive ability (PA) of additive and additive-dominance genomic best linear unbiased prediction model when combined with the effects of CNV in two datasets of maize hybrids (USP and HELIX). In the USP dataset, we observed a significant negative phenotypic correlation of low magnitude between copy number loss and plant height, revealing a tendency that more copy losses lead to lower plants. In the same set, when CNV was combined with the additive plus dominance effects, the PA significantly increased only for plant height under low nitrogen. In this case, CNV effects explicitly capture relatedness between individuals and add extra information to the model. In the HELIX dataset, we observed a pronounced difference in PA between additive (0.50) and additive-dominance (0.71) models for predicting grain yield, suggesting a significant contribution of dominance. We conclude that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids, although the inclusion of CNVs into datasets does not return significant gains concerning PA.

Genome-wide detection of copy-number variations in local cattle breeds

The aim of the present study was to identify copy-number variations (CNVs) in Cinisara (CIN) and Modicana (MOD) cattle breeds on the basis of signal intensity (logR ratio) and B allele frequency of each marker, using Illumina’s BovineSNP50K Genotyping BeadChip. The CNVs were detected with the PennCNV and SVS 8.7.0 software and were aggregated into CNV regions (CNVRs). PennCNV identified 487 CNVs in CIN that aggregated into 86 CNVRs, and 424 CNVs in MOD that aggregated into 81 CNVRs. SVS identified a total of 207 CNVs in CIN that aggregated into 39 CNVRs, and 181 CNVs in MOD that aggregated into 41 CNVRs. The CNVRs identified with the two softwares contained 29 common CNVRs in CIN and 17 common CNVRs in MOD. Only a small number of CNVRs identified in the present study have been identified elsewhere, probably because of the limitations of the array used. In total, 178 and 208 genes were found within the CNVRs of CIN and MOD respectively. Gene Ontology and KEGG pathway analyses showed that several of these genes are involved in milk production, reproduction and behaviour, the immune response, and resistance/susceptibility to infectious diseases. Our results have provided significant information for the construction of more-complete CNV maps of the bovine genome and offer an important resource for the investigation of genomic changes and traits of interest in the CIN and MOD cattle breeds. Our results will also be valuable for future studies and constitute a preliminary report of the CNV distribution resources in local cattle genomes.

A copy number variation generated by complicated organization of PCDHA gene cluster is associated with egg performance traits in Xinhua E-strain

In recent years, a mass of duplicated and deleted DNA sequences have been found in human and animal genomes following the prevalence of employing high-throughput sequencing and SNP array. However, few copy number variation (CNV) studies have been performed on egg performance traits of chicken. In this study, 17 loci reported in previous studies were selected for CNV detection in the Xinhua E-strain by using the CNVplex kit, and the detection results showed that locus14 exhibited CNV. Further association analysis indicated the copies of locus14 could be significantly associated with age at first egg (AFE; P < 0.0086) and egg number at 250 d (250EN; P < 0.036). DNA sequence amplification showed the loss of a 260-bp-long fragment in the upstream of locus14, which mainly occurred in normal or copy-gain individuals. The qPCR results showed that subjects with gain of copies could promote the total expression level of the PCDHA gene cluster in the pituitary gland of adult individuals. Additionally, PCR amplification with randomly combined primers revealed a larger number of chicken variable exons than that previously reported, indicating the complexity of the organization of the PCDHA gene cluster. Those variable exons are divergent in their distribution among the populations of Xinhua E-strain, Chahua, Tibetan, and Tulufan Game Chicken, and most individuals only possess part of variable exons. Overall, the copies of locus14 reflect the variable exon dosage effects on the total expression level of the PCDHA gene cluster, which may regulate the layer egg production by affecting the development of the neural system.

Characterization of copy number variants in a large multibreed population of beef and dairy cattle using high-density single nucleotide polymorphism genotype data

Copy number variants (CNVs) are a form of genomic variation that changes the structure of the genome through deletion or duplication of stretches of DNA. The objective of the present study was to characterize CNVs in a large multibreed population of beef and dairy bulls. The CNVs were called on the autosomes of 5,551 cattle from 22 different beef and dairy breeds, using 2 freely available software suites, QuantiSNP and PennCNV. All CNVs were classified into either deletions or duplications. The median concordance between PennCNV and QuantiSNP, per animal, was 18.5% for deletions and 0% for duplications. The low concordance rate between PennCNV and QuantiSNP indicated that neither algorithm, by itself, could identify all CNVs in the population. In total, PennCNV and QuantiSNP collectively identified 747,129 deletions and 432,523 duplications; 80.2% of all duplications and 69.1% of all deletions were present only once in the population. Only 0.154% of all CNVs identified were present in more than 50 animals in the population. The distribution of the percentage of the autosomes that were composed of deletions, per animal, was positively skewed, as was the distribution for the percentage of the autosomes that were composed of duplications, per animal. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of deletions were 0.019%, 0.037%, and 0.201%, respectively. The first quartile, median, and third quartile of the distribution of the percentage of the autosomes that were composed of duplications were 0.013%, 0.028%, and 0.076%, respectively. The distributions of the number of deletions and duplications per animal were both positively skewed. The interquartile range for the number of deletions per animal in the population was between 16 and 117, whereas for duplications it was between 8 and 23. Per animal, there tended to be twice as many deletions as duplications. The distribution of the length of deletions was positively skewed, as was the distribution of the length of duplications. The interquartile range for the length of deletions in the population was between 25 and 101 kb, and for duplications the interquartile range was between 46 and 235 kb. Per animal, duplications tended to be twice as long as deletions. This study provides a description of the characteristics and distribution of CNVs in a large multibreed population of beef and dairy cattle.

Copy Number Variations of KLF6 Modulate Gene Transcription and Growth Traits in Chinese Datong Yak (Bos Grunniens)

Copy number variation (CNV) is a significant marker of the genetic and phenotypic diversity among individuals that accounts for complex quantitative traits of phenotype and diseases via modulating gene dosage and disrupting coding regions in the genome. Biochemically, Kruppel-like factor 6 (KLF6) genes plays a significant role in the regulation of cell differentiation and proliferation and muscle development. The aim of this study was to detect the distributions of KLF6 copy number variations (CNVs) in five breeds of domestic yak and to explore their effect on growth traits and gene expression. The data were analyzed by real-time quantitative PCR (qPCR). Our results elucidated that a decreased CNV in the KLF6 gene is more highly associated (p < 0.05) with various growth traits than increased or normal CNVs in six-month-old and five-year-old Datong yak. Nevertheless, negative correlations between the DNA copy number and KLF6 gene expression were observed in the skeletal muscle of adult Datong yak. These results suggest that CNVs of the KLF6 gene could be crucial genomic markers for growth phenotypes of Chinese Datong yak breeds and this finding constitutes the first evidence of the biological role of KLF6 CNVs in Chinese Datong yak breeds.

Genomic predictions combining SNP markers and copy number variations in Nellore cattle

Background

Due to the advancement in high throughput technology, single nucleotide polymorphism (SNP) is routinely being incorporated along with phenotypic information into genetic evaluation. However, this approach often cannot achieve high accuracy for some complex traits. It is possible that SNP markers are not sufficient to predict these traits due to the missing heritability caused by other genetic variations such as microsatellite and copy number variation (CNV), which have been shown to affect disease and complex traits in humans and other species.

Results

In this study, CNVs were included in a SNP based genomic selection framework. A Nellore cattle dataset consisting of 2230 animals genotyped on BovineHD SNP array was used, and 9 weight and carcass traits were analyzed. A total of six models were implemented and compared based on their prediction accuracy. For comparison, three models including only SNPs were implemented: 1) BayesA model, 2) Bayesian mixture model (BayesB), and 3) a GBLUP model without polygenic effects. The other three models incorporating both SNP and CNV included 4) a Bayesian model similar to BayesA (BayesA+CNV), 5) a Bayesian mixture model (BayesB+CNV), and 6) GBLUP with CNVs modeled as a covariable (GBLUP+CNV). Prediction accuracies were assessed based on Pearson’s correlation between de-regressed EBVs (dEBVs) and direct genomic values (DGVs) in the validation dataset. For BayesA, BayesB and GBLUP, accuracy ranged from 0.12 to 0.62 across the nine traits. A minimal increase in prediction accuracy for some traits was noticed when including CNVs in the model (BayesA+CNV, BayesB+CNV, GBLUP+CNV).

Conclusions

This study presents the first genomic prediction study integrating CNVs and SNPs in livestock. Combining CNV and SNP marker information proved to be beneficial for genomic prediction of some traits in Nellore cattle.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4787-6) contains supplementary material, which is available to authorized users.

Genome-wide copy number variant analysis reveals variants associated with 10 diverse production traits in Holstein cattle

BACKGROUND

Copy number variation (CNV) is an important type of genetic variation contributing to phenotypic differences among mammals and may serve as an alternative molecular marker to single nucleotide polymorphism (SNP) for genome-wide association study (GWAS). Recently, GWAS analysis using CNV has been applied in livestock, although few studies have focused on Holstein cattle.

RESULTS

We describe 191 CNV detected using intensity data from over 700,000 SNP genotypes generated with the BovineHD Genotyping BeadChip (Illumina, San Diego, CA) in 528 Holstein cows. The CNV were used for GWAS analysis of 10 important production traits of 473 cattle related to feed intake, milk quality, and female fertility, as well as 2 composite traits of net merit and productive life. In total, we detected 57 CNV associated (P < 0.05 after false discovery rate correction) with at least one of the 10 phenotypes. Focusing on feed efficiency and intake-related phenotypes of residual feed intake and dry matter intake, we detected a single CNV associated with both traits which overlaps a predicted olfactory receptor gene OR2A2 (LOC787786). Additionally, 2 CNV within the RXFP4 (relaxin/insulin like family peptide receptor 4) and 2 additional olfactory receptor gene regions, respectively, were associated with residual feed intake. The RXFP4 gene encodes a receptor for an orexigenic peptide, insulin-like peptide 5 produced by intestinal L cells, which is expressed by enteric neurons. Olfactory receptors are critical for transmitting the effects of odorants, contributing to the sense of smell, and have been implicated in participating in appetite regulation.

CONCLUSIONS

Our results identify CNV for genomic evaluation in Holstein cattle, and provide candidate genes, such as RXFP4, contributing to variation in feed efficiency and feed intake-related traits. These results indicate potential novel targets for manipulating feed intake-related traits of livestock.

Copy number variation in livestock: A mini review

Copy number variation (CNV) is a phenomenon in which sections of the genome, ranging from one kilo base pair (Kb) to several million base pairs (Mb), are repeated and the number of repeats vary between the individuals in a population. It is an important source of genetic variation in an individual which is now being utilized rather than single nucleotide polymorphisms (SNPs), as it covers the more genomic region. CNVs alter the gene expression and change the phenotype of an individual due to deletion and duplication of genes in the copy number variation regions (CNVRs). Earlier, researchers extensively utilized SNPs as the main source of genetic variation. But now, the focus is on identification of CNVs associated with complex traits. With the recent advances and reduction in the cost of sequencing, arrays are developed for genotyping which cover the maximum number of SNPs at a time that can be used for detection of CNVRs and underlying quantitative trait loci (QTL) for the complex traits to accelerate genetic improvement. CNV studies are also being carried out to understand the evolutionary mechanism in the domestication of livestock and their adaptation to the different environmental conditions. The main aim of the study is to review the available data on CNV and its role in genetic variation among the livestock.

Genome-wide mapping of large deletions and their population-genetic properties in dairy cattle

Large genomic deletions are potential candidate for loss-of-function, which could be lethal as homozygote. Analysing whole genome data of 175 cattle, we report 8,480 large deletions (199 bp–773 KB) with an overall false discovery rate of 8.8%; 82% of which are novel compared with deletions in the dbVar database. Breakpoint sequence analyses revealed that majority (24 of 29 tested) of the deletions contain microhomology/homology at breakpoint, and therefore, most likely generated by microhomology-mediated end joining. We observed higher differentiation among breeds for deletions in some genic-regions, such as ABCA12, TTC1, VWA3B, TSHR, DST/BPAG1, and CD1D. The genes overlapping deletions are on average evolutionarily less conserved compared with known mouse lethal genes (P-value = 2.3 × 10⁻⁶). We report 167 natural gene knockouts in cattle that are apparently nonessential as live homozygote individuals are observed. These genes are functionally enriched for immunoglobulin domains, olfactory receptors, and MHC classes (FDR = 2.06 × 10⁻²², 2.06 × 10⁻²², 7.01 × 10⁻⁶, respectively). We also demonstrate that deletions are enriched for health and fertility related quantitative trait loci (2-and 1.5-fold enrichment, Fisher’s P-value = 8.91 × 10⁻¹⁰ and 7.4 × 10⁻¹¹, respectively). Finally, we identified and confirmed the breakpoint of a ∼525 KB deletion on Chr23:12,291,761-12,817,087 (overlapping BTBD9, GLO1 and DNAH8), causing stillbirth in Nordic Red Cattle.

Distribution and Functionality of Copy Number Variation across European Cattle Populations

Copy number variation (CNV), which is characterized by large-scale losses or gains of DNA fragments, contributes significantly to genetic and phenotypic variation. Assessing CNV across different European cattle populations might reveal genetic changes responsible for phenotypic differences, which have accumulated throughout the domestication history of cattle as consequences of evolutionary forces that act upon them. To explore pattern of CNVs across European cattle, we genotyped 149 individuals, that represent different European regions, using the Illumina Bovine HD Genotyping array. A total of 9,944 autosomal CNVs were identified in 149 samples using a Hidden Markov Model (HMM) as employed in PennCNV. Animals originating from several breeds of British Isles, and Balkan and Italian regions, on average, displayed higher abundance of CNV counts than Dutch or Alpine animals. A total of 923 CNV regions (CNVRs) were identified by aggregating CNVs overlapping in at least two animals. The hierarchical clustering of CNVRs indicated low differentiation and sharing of high-frequency CNVRs between European cattle populations. Various CNVRs identified in the present study overlapped with olfactory receptor genes and genes related to immune system. In addition, we also detected a CNV overlapping the Kit gene in English longhorn cattle which has previously been associated with color-sidedness. To conclude, we provide a comprehensive overview of CNV distribution in genome of European cattle. Our results indicate an important role of purifying selection and genomic drift in shaping CNV diversity that exists between different European cattle populations.

CNV Analysis of Host Responses to Porcine Reproductive and Respiratory Syndrome Virus Infection

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease with a significant impact on the swine industry causing major economic losses. The objective of this study is to examine copy number variations (CNVs) associated with the group-specific host responses to PRRS virus infection. We performed a genome-wide CNV analysis using 660 animals genotyped with on the porcine SNP60 BeadChip and discovered 7097 CNVs and 271 CNV regions (CNVRs). For this study, we used two established traits related to host response to the virus, i.e. viral load (VL, area under the curve of log-transformed serum viremia from 0 to 21 days post infection) and weight gain (WG42 from 0 to 42 days post infection). To investigate the effects of CNVs on differential host responses to PRRS, we compared groups of animals with extreme high and low estimated breeding values (EBVs) for both traits using a case-control study design. For VL, we identified 163 CNVRs (84 Mb) from the high group and 159 CNVRs (76 Mb) from the low group. For WG42, we detected 126 (68 Mb) and 156 (79 Mb) CNVRs for high and low groups, respectively. Based on gene annotation within group-specific CNVRs, we performed network analyses and observed some potential candidate genes. Our results revealed these group-specific genes are involved in regulating innate and acquired immune response pathways. Specifically, molecules like interferons and interleukins are closely related to host responses to PRRS virus infection.