Genome-wide copy number variations inferred from SNP genotyping arrays using a Large White and Minzhu intercross population

Genome-Wide Assessment Characteristics of Genes Overlapping Copy Number Variation Regions in Duroc Purebred Population

Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.

A Survey of Copy Number Variation in the Porcine Genome Detected From Whole-Genome Sequence

Copy number variations (CNVs) are gains and losses of large regions of genomic sequence between individuals of a species. Although CNVs have been associated with various phenotypic traits in humans and other species, the extent to which CNVs impact phenotypic variation remains unclear. In swine, as well as many other species, relatively little is understood about the frequency of CNV in the genome, sizes, locations, and other chromosomal properties. In this work, we identified and characterized CNV by utilizing whole-genome sequence from 240 members of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the purebred founding boars (12 Duroc and 12 Landrace), 48 of the founding Yorkshire-Landrace composite sows, 109 composite animals from generations 4 through 9, 29 composite animals from generation 15, and 30 purebred industry boars (15 Landrace and 15 Yorkshire) used as sires in generations 10 through 15. Using a combination of split reads, paired-end mapping, and read depth approaches, we identified a total of 3,538 copy number variable regions (CNVRs), including 1,820 novel CNVRs not reported in previous studies. The CNVRs covered 0.94% of the porcine genome and overlapped 1,401 genes. Gene ontology analysis identified that CNV-overlapped genes were enriched for functions related to organism development. Additionally, CNVRs overlapped with many known quantitative trait loci (QTL). In particular, analysis of QTL previously identified in the USMARC herd showed that CNVRs were most overlapped with reproductive traits, such as age of puberty and ovulation rate, and CNVRs were significantly enriched for reproductive QTL.

A genome-wide single nucleotide polymorphism and copy number variation analysis for number of piglets born alive

Background

In this study we integrated the CNV (copy number variation) and WssGWAS (weighted single-step approach for genome-wide association) analyses to increase the knowledge about number of piglets born alive, an economically important reproductive trait with significant impact on production efficiency of pigs.

Results

A total of 3892 samples were genotyped with the Porcine SNP80 BeadChip. After quality control, a total of 57,962 high-quality SNPs from 3520 Duroc pigs were retained. The PennCNV algorithm identified 46,118 CNVs, which were aggregated by overlapping in 425 CNV regions (CNVRs) ranging from 2.5 Kb to 9718.4 Kb and covering 197 Mb (~ 7.01%) of the pig autosomal genome. The WssGWAS identified 16 genomic regions explaining more than 1% of the additive genetic variance for number of piglets born alive. The overlap between CNVR and WssGWAS analyses identified common regions on SSC2 (4.2–5.2 Mb), SSC3 (3.9–4.9 Mb), SSC12 (56.6–57.6 Mb), and SSC17 (17.3–18.3 Mb). Those regions are known for harboring important causative variants for pig reproductive traits based on their crucial functions in fertilization, development of gametes and embryos. Functional analysis by the Panther software identified 13 gene ontology biological processes significantly represented in this study such as reproduction, developmental process, cellular component organization or biogenesis, and immune system process, which plays relevant roles in swine reproductive traits.

Conclusion

Our research helps to improve the understanding of the genetic architecture of number of piglets born alive, given that the combination of GWAS and CNV analyses allows for a more efficient identification of the genomic regions and biological processes associated with this trait in Duroc pigs. Pig breeding programs could potentially benefit from a more accurate discovery of important genomic regions.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5687-0) contains supplementary material, which is available to authorized users.

Copy number variations of MTHFSD gene across pig breeds and its association with litter size traits in Chinese indigenous Xiang pig

Copy number variation (CNV) is a major proportion of genetic variation, which changes the gene structure and dosage and affects gene expression and function. To validate the presence and the function of CNV in pig, we used real-time quantitative polymerase chain reaction (qPCR) method to validate a 496 kb CNV region comprising MTHFSD gene on chromosome 6 of Xiang pig detected by single nucleotide polymorphism (SNP) array. Then we investigated the distribution of the MTHFSD CNV in a total of 545 pigs in four breeds. About 46.2% and 32.7% individuals in the four pig breeds were detected to be types of loss and gain of MTHFSD locus. The relative copy numbers of MTHFSD gene showed the largest variation range (0-55 copies) in the Xiang pig population. The copy numbers of MTHFSD gene presented the positive correlations with the transcript level of MTHFSD gene in adult ovaries. Statistical analysis indicated that CNVs of MTHFSD gene was significantly changed the litter size traits of Xiang pigs, and the individuals with CNV gain showed more litter size than the CNV loss pigs. We have reasons to believe that the MTHFSD as RNA-binding protein play an important role in pig reproduction as a result of regulating MTHFS mRNA metabolism.

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.

A genome-wide association study of copy number variations with umbilical hernia in swine

Umbilical hernia (UH) is one of the most common congenital defects in pigs, leading to considerable economic loss and serious animal welfare problems. To test whether copy number variations (CNVs) contribute to pig UH, we performed a case-control genome-wide CNV association study on 905 pigs from the Duroc, Landrace and Yorkshire breeds using the Porcine SNP60 BeadChip and penncnv algorithm. We first constructed a genomic map comprising 6193 CNVs that pertain to 737 CNV regions. Then, we identified eight CNVs significantly associated with the risk for UH in the three pig breeds. Six of seven significantly associated CNVs were validated using quantitative real-time PCR. Notably, a rare CNV (CNV14:13030843-13059455) encompassing the NUGGC gene was strongly associated with UH (permutation-corrected P = 0.0015) in Duroc pigs. This CNV occurred exclusively in seven Duroc UH-affected individuals. SNPs surrounding the CNV did not show association signals, indicating that rare CNVs may play an important role in complex pig diseases such as UH. The NUGGC gene has been implicated in human omphalocele and inguinal hernia. Our finding supports that CNVs, including the NUGGC CNV, contribute to the pathogenesis of pig UH.

Copy number variation-based genome wide association study reveals additional variants contributing to meat quality in Swine

Pork quality is important both to the meat processing industry and consumers' purchasing attitude. Copy number variation (CNV) is a burgeoning kind of variants that may influence meat quality. In this study, a genome-wide association study (GWAS) was performed between CNVs and meat quality traits in swine. After false discovery rate (FDR) correction, a total of 8 CNVs on 6 chromosomes were identified to be significantly associated with at least one meat quality trait. All of the 8 CNVs were verified by next generation sequencing and six of them were verified by qPCR. Only the haplotype block containing CNV12 is adjacent to significant SNPs associated with meat quality, suggesting the effects of those CNVs were not likely captured by tag SNPs. The DNA dosage and EST expression of CNV12, which overlap with an obesity related gene Netrin-1 (Ntn1), were consistent with Ntn1 RNA expression, suggesting the CNV12 might be involved in the expression regulation of Ntn1 and finally influence meat quality. We concluded that CNVs may contribute to the genetic variations of meat quality beyond SNPs, and several candidate CNVs were worth further exploration.

A genome-wide scan for copy number variations using high-density single nucleotide polymorphism array in Simmental cattle

Copy number variations (CNVs) have recently been identified as promising sources of genetic variation, complementary to single nucleotide polymorphisms (SNPs). As a result, detection of CNVs has attracted a great deal of attention. In this study, we performed genome-wide CNV detection using Illumina Bovine HD BeadChip (770k) data on 792 Simmental cattle. A total of 263 CNV regions (CNVRs) were identified, which included 137 losses, 102 gains and 24 regions classified as both loss and gain, covering 35.48 Mb (1.41%) of the bovine genome. The length of these CNVRs ranged from 10.18 kb to 1.76 Mb, with an average length of 134.78 kb and a median length of 61.95 kb. In 136 of these regions, a total of 313 genes were identified related to biological functions such as transmembrane activity and olfactory transduction activity. To validate the results, we performed quantitative PCR to detect nine randomly selected CNVRs and successfully confirmed seven (77.6%) of them. Our results present a map of cattle CNVs derived from high-density SNP data, which expands the current CNV map of the cattle genome and provides useful information for investigation of genomic structural variation in cattle.

Genome-Wide Copy Number Variations Using SNP Genotyping in a Mixed Breed Swine Population

Copy number variations (CNVs) are increasingly understood to affect phenotypic variation. This study uses SNP genotyping of trios of mixed breed swine to add to the catalog of known genotypic variation in an important agricultural animal. PorcineSNP60 BeadChip genotypes were collected from 1802 pigs that combined to form 1621 trios. These trios were from the crosses of 50 boars with 525 sows producing 1621 piglets. The pigs were part of a population that was a mix of ¼ Duroc, ½ Landrace and ¼ Yorkshire breeds. Merging the overlapping CNVs that were observed in two or more individuals to form CNV regions (CNVRs) yielded 502 CNVRs across the autosomes. The CNVRs intersected genes, as defined by RefSeq, 84% of the time – 420 out of 502. The results of this study are compared and contrasted to other swine studies using similar and different methods of detecting CNVR. While progress is being made in this field, more work needs to be done to improve consistency and confidence in CNVR results.

Copy number variations in high and low fertility breeding boars

Background

In this study we applied the extreme groups/selective genotyping approach for identifying copy number variations in high and low fertility breeding boars. The fertility indicator was the calculated Direct Boar Effect on litter size (DBE) that was obtained as a by-product of the national genetic evaluation for litter size (BLUP). The two groups of animals had DBE values at the upper (high fertility) and lower (low fertility) end of the distribution from a population of more than 38,000 boars. Animals from these two diverse phenotypes were genotyped with the Porcine SNP60K chip and compared by several approaches in order to prove the feasibility of our CNV analysis and to identify putative markers of fertility.

Results

We have identified 35 CNVRs covering 36.5 Mb or ~1.3% of the porcine genome. Among these 35 CNVRs, 14 were specific to the high fertility group, while 19 CNVRs were specific to the low fertility group which overlap with 137 QTLs of various reproductive traits. The identified 35 CNVRs encompassed 50 genes, among them 40 were specific to the low fertility group, seven to the high fertility group, while three were found in regions that were present in both groups but with opposite gain/loss status. A functional analysis of several databases revealed that the genes found in CNVRs from the low fertility group have been significantly enriched in members of the innate immune system, Toll-like receptor and RIG-I-like receptor signaling and fatty acid oxidation pathways.

Conclusions

We have demonstrated that our analysis pipeline could identify putative CNV markers of fertility, especially in case of low fertility boars.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1473-9) contains supplementary material, which is available to authorized users.

Copy number variation detection using SNP genotyping arrays in three Chinese pig breeds

We performed genome-wide CNV detection based on SNP genotyping data of 96 Chinese-native Tibetan, Dahe and Wuzhishan pigs. These pigs are particularly interesting because of their excellent adaptation to hypoxia or small body size, which facilitates the use of them as models of different human diseases in addition to valuable agricultural animals. A total of 105 CNV regions (CNVRs) were identified, encompassing 16.71 Mb of the pig genome. Seven of 10 (70%) CNVRs selected randomly were validated by quantitative real-time PCR. Comparison with previous studies revealed 25 (23.81%) novel CNVRs, indicating that CNV coverage of the pig genome is still incomplete and there exists large diversity between pig breeds. Functional analysis of genes located in these CNVRs confirmed the high representation of genes involved in sensory perception, neurological system processes and other basic metabolic processes. In addition, the majority of these CNVRs were detected to span reported pig QTL that affect various traits, which highlighted three biologically interesting genes with copy number changes (i.e., ANKRD34B, FAM110B and ABCG1). These genes may have economic importance in pig breeding and are worth being further investigated. We also obtained some CNVRs harboring genes that had human orthologs involved in human diseases such as cardiovascular disease and Alzheimer's disease. The findings of this study are a significant extension of the coverage of CNVRs in the pig genome and provide valuable resources for follow-up-associated studies of CNVs in pig complex traits as well as important implications of human diseases.

Single-nucleotide polymorphism analysis of GH, GHR, and IGF-1 genes in minipigs

Tibetan (TB) and Bama (BM) miniature pigs are two popular pig breeds that are used as experimental animals in China due to their small body size. Here, we analyzed single-nucleotide polymorphisms (SNPs) in gene fragments that are closely related to growth traits [growth hormone (GH), growth hormone receptor (GHR), and insulin-like growth factor (IGF)-1)] in these pig breeds and a large white (LW) control pig breed. On the basis of the analysis of 100 BMs, 108 TBs, and 50 LWs, the polymorphic distribution levels of GH, GHR, and IGF-1 were significantly different among these three pig breeds. According to correlation analyses between SNPs and five growth traits--body weight (BW), body length (BL), withers height (WH), chest circumference (CC), and abdomen circumference (AC)--three SNP loci in BMs and four SNP loci in TBs significantly affected growth traits. Three SNP sites in BMs and four SNP sites in TBs significantly affected growth traits. SNPs located in the GH gene fragment significantly affected BL and CC at locus 12 and BL at locus 45 in BMs, and also BW, WH, CC, and AC at locus 45 and WH and CC at locus 93 in TBs. One SNP at locus 85 in the BM GHR gene fragment significantly affected all growth traits. All indices were significantly reduced with a mixture of alleles at locus 85. These results provide more information regarding the genetic background of these minipig species and indicate useful selection markers for pig breeding programs.

Copy number variants in Italian Large White pigs detected using high-density single nucleotide polymorphisms and their association with back fat thickness

The aim of this study was to identify copy number variants (CNVs) in Italian Large White pigs and test them for association with back fat thickness (BFT). Within a population of 12 000 performance-tested pigs, two groups of animals with extreme and divergent BFT estimated breeding values (EBVs; 147 with negative and 150 with positive EBVs) were genotyped with the Illumina Porcine SNP60 BeadChip. CNVs were detected with PENNCNV software. We identified a total of 4146 CNV events in 170 copy number variation regions (CNVRs) located on 15 porcine autosomes. Validation of detected CNVRs was carried out (i) by comparing CNVRs already detected by other studies and (ii) by semiquantitative fluorescent multiplex (SQFM) PCR of a few CNVRs. Most of CNVRs detected in Italian Large White pigs (71.2%) were already reported in other pig breeds/populations, and 82.1% of the CNV events detected by PENNCNV were confirmed by SQFM PCR. For each CNVR, we compared the occurrence of CNV events between the pigs of the high and low BFT EBV tails. Sixteen regions showed significance at P < 0.10, and seven were significant at P < 0.05 but were not significant after Bonferroni correction (Fisher's exact test). These results indicated that CNVs could explain a limited fraction of the genetic variability of fat deposition in Italian Large White pigs. However, it was interesting to note that one of these CNVRs encompassed the ZPLD1 gene. In humans, a rare CNV event including this gene is associated with obesity. Studies identifying CNVs in pigs could assist in elucidating the genetic mechanisms underlying human obesity.

Detection of genome-wide copy number variations in two chicken lines divergently selected for abdominal fat content

Background

The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. Copy number variations (CNVs) are a form of genomic structural variation widely distributed in the genome. CNV analysis has recently gained greater attention and momentum, as the identification of CNVs can contribute to a better understanding of traits important to both humans and other animals. To detect chicken CNVs, we genotyped 475 animals derived from two broiler chicken lines divergently selected for abdominal fat content using chicken 60 K SNP array, which is a high-throughput method widely used in chicken genomics studies.

Results

Using PennCNV algorithm, we detected 438 and 291 CNVs in the lean and fat lines, respectively, corresponding to 271 and 188 CNV regions (CNVRs), which were obtained by merging overlapping CNVs. Out of these CNVRs, 99% were confirmed also by the CNVPartition program. These CNVRs covered 40.26 and 30.60 Mb of the chicken genome in the lean and fat lines, respectively. Moreover, CNVRs included 176 loss, 68 gain and 27 both (i.e. loss and gain within the same region) events in the lean line, and 143 loss, 25 gain and 20 both events in the fat line. Ten CNVRs were chosen for the validation experiment using qPCR method, and all of them were confirmed in at least one qPCR assay. We found a total of 886 genes located within these CNVRs, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed they could play various roles in a number of biological processes. Integrating the results of CNVRs, known quantitative trait loci (QTL) and selective sweeps for abdominal fat content suggested that some genes (including SLC9A3, GNAL, SPOCK3, ANXA10, HELIOS, MYLK, CCDC14, SPAG9, SOX5, VSNL1, SMC6, GEN1, MSGN1 and ZPAX) may be important for abdominal fat deposition in the chicken.

Conclusions

Our study provided a genome-wide CNVR map of the chicken genome, thereby contributing to our understanding of genomic structural variations and their potential roles in abdominal fat content in the chicken.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-517) contains supplementary material, which is available to authorized users.

Copy Number Variation in Chickens: A Review and Future Prospects

DNA sequence variations include nucleotide substitution, deletion, insertion, translocation and inversion. Deletion or insertion of a large DNA segment in the genome, referred to as copy number variation (CNV), has caught the attention of many researchers recently. It is believed that CNVs contribute significantly to genome variability, and thus contribute to phenotypic variability. In chickens, genome-wide surveys with array comparative genome hybridization (aCGH), SNP chip detection or whole genome sequencing have revealed a large number of CNVs. A large portion of chicken CNVs involves protein coding or regulatory sequences. A few CNVs have been demonstrated to be the determinant factors for single gene traits, such as late-feathering, pea-comb and dermal hyperpigmentation. The phenotypic effects of the majority of chicken CNVs are to be delineated.