Copy number variants in a highly inbred Iberian porcine strain

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

BACKGROUND

Teat number is a vital reproductive trait in sows, crucial for providing immunity and nutrition to piglets during lactation. However, "missing heritability" in Single Nucleotide Polymorphism (SNP)-based Genome-Wide Association Studies (GWAS) has led to an increasing focus on structural variations in the genetic analysis of complex biological traits.

RESULTS

In this study, we generated a comprehensive CNV map in a population of French Yorkshire pigs (n = 644) and identified 429 CNVRs. Notably, 44% (189 CNVRs) of these were detected for the first time. Subsequently, we conducted GWAS for teat number in the French Yorkshire pig population using both 80K chip and its imputed data, as well as a GWAS analysis based on CNV regions (CNVR). Interestingly, 80K chip GWAS identified two SNPs located on Sus scrofa chromosome 5 (SSC5) that were simultaneously associated with Total Teat Number (TTN), Left Teat Number (LTN), and Right Teat Number (RTN). The leading SNP (WU_10.2_5_76130558) explained 3.33%, 2.69%, and 2.67% of the phenotypic variance for TTN, LTN, and RTN, respectively. Moreover, through imputed GWAS, we successfully identified 30 genetic variants associated with TTN located within the 73.22 -73.30 Mb region on SSC5. The two SNPs identified in the 80K chip GWAS were also located in this region. In addition, CNVR-based GWAS revealed three significant CNVRs associated with TTN. Finally, through gene annotation, we pinpointed two candidate genes, TRIM66 and PRICKLE1, which are related to diverse processes such as breast cancer and abnormal vertebral development.

CONCLUSIONS

Our research provides an in-depth analysis of the complex genetic structure underlying teat number, contributing to the genetic enhancement of sows with improved reproductive performance and, ultimately, bolstering the economic benefits of swine production enterprises.

Genome-wide identification of candidate copy number polymorphism genes associated with complex traits of Tibetan-sheep

Copy number variation (CNV) is a genetic structural polymorphism important for phenotypic diversity and important economic traits of livestock breeds, and it plays an important role in the desired genetic variation. This study used whole genome sequencing to detect the CNV variation in the genome of 6 local Tibetan sheep groups. We detected 69,166 CNV events and 7230 copy number variable regions (CNVRs) after merging the overlapping CNVs, accounting for 2.72% of the reference genome. The CNVR length detected ranged from 1.1 to 1693.5 Kb, with a total length of 118.69 Mb and an average length of 16.42 Kb per CNVR. Functional GO cluster analysis showed that the CNVR genes were mainly involved in sensory perception systems, response to stimulus, and signal transduction. Through CNVR-based Vst analysis, we found that the CACNA2D3 and CTBP1 genes related to hypoxia adaptation, the HTR1A gene related to coat color, and the TRNAS-GGA and PIK3C3 genes related to body weight were all strongly selected. The findings of our study will contribute novel insights into the genetic structural variation underlying hypoxia adaptation and economically important traits in Tibetan sheep.

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

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

Genome-Wide Detection of Copy Number Variations and Evaluation of Candidate Copy Number Polymorphism Genes Associated With Complex Traits of Pigs

Copy number variation (CNV) has been considered to be an important source of genetic variation for important phenotypic traits of livestock. In this study, we performed whole-genome CNV detection on Suhuai (SH) (n = 23), Chinese Min Zhu (MZ) (n = 11), and Large White (LW) (n = 12) pigs based on next-generation sequencing data. The copy number variation regions (CNVRs) were annotated and analyzed, and 10,885, 10,836, and 10,917 CNVRs were detected in LW, MZ, and SH pigs, respectively. Some CNVRs have been randomly selected for verification of the variation type by real-time PCR. We found that SH and LW pigs are closely related, while MZ pigs are distantly related to the SH and LW pigs by CNVR-based genetic structure, PCA, VST, and QTL analyses. A total of 14 known genes annotated in CNVRs were unique for LW pigs. Among them, the cyclin T2 (CCNT2) is involved in cell proliferation and the cell cycle. The FA Complementation Group M (FANCM) is involved in defective DNA repair and reproductive cell development. Ten known genes annotated in 47 CNVRs were unique for MZ pigs. The genes included glycerol-3-phosphate acyltransferase 3 (GPAT3) is involved in fat synthesis and is essential to forming the glycerol triphosphate. Glutathione S-transferase mu 4 (GSTM4) gene plays an important role in detoxification. Eleven known genes annotated in 23 CNVRs were unique for SH pigs. Neuroligin 4 X-linked (NLGN4X) and Neuroligin 4 Y-linked (NLGN4Y) are involved with nerve disorders and nerve signal transmission. IgLON family member 5 (IGLON5) is related to autoimmunity and neural activities. The unique characteristics of LW, MZ, and SH pigs are related to these genes with CNV polymorphisms. These findings provide important information for the identification of candidate genes in the molecular breeding of pigs.

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.

Genome-wide detection of copy number variants in European autochthonous and commercial pig breeds by whole-genome sequencing of DNA pools identified breed-characterising copy number states

In this study, we identified copy number variants (CNVs) in 19 European autochthonous pig breeds and in two commercial breeds (Italian Large White and Italian Duroc) that represent important genetic resources for this species. The genome of 725 pigs was sequenced using a breed-specific DNA pooling approach (30-35 animals per pool) obtaining an average depth per pool of 42×. This approach maximised CNV discovery as well as the related copy number states characterising, on average, the analysed breeds. By mining more than 17.5 billion reads, we identified a total of 9592 CNVs (~683 CNVs per breed) and 3710 CNV regions (CNVRs; 1.15% of the reference pig genome), with an average of 77 CNVRs per breed that were considered as private. A few CNVRs were analysed in more detail, together with other information derived from sequencing data. For example, the CNVR encompassing the KIT gene was associated with coat colour phenotypes in the analysed breeds, confirming the role of the multiple copies in determining breed-specific coat colours. The CNVR covering the MSRB3 gene was associated with ear size in most breeds. The CNVRs affecting the ELOVL6 and ZNF622 genes were private features observed in the Lithuanian Indigenous Wattle and in the Turopolje pig breeds respectively. Overall, the genome variability unravelled here can explain part of the genetic diversity among breeds and might contribute to explain their origin, history and adaptation to a variety of production systems.

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.

About the existence of common determinants of gene expression in the porcine liver and skeletal muscle

BACKGROUND

The comparison of expression QTL (eQTL) maps obtained in different tissues is an essential step to understand how gene expression is genetically regulated in a context-dependent manner. In the current work, we have compared the transcriptomic and eQTL profiles of two porcine tissues (skeletal muscle and liver) which typically show highly divergent expression profiles, in 103 Duroc pigs genotyped with the Porcine SNP60 BeadChip (Illumina) and with available microarray-based measurements of hepatic and muscle mRNA levels. Since structural variation could have effects on gene expression, we have also investigated the co-localization of cis-eQTLs with copy number variant regions (CNVR) segregating in this Duroc population.

RESULTS

The analysis of differential expresssion revealed the existence of 1204 and 1490 probes that were overexpressed and underexpressed in the gluteus medius muscle when compared to liver, respectively (|fold-change| > 1.5, q-value < 0.05). By performing genome scans in 103 Duroc pigs with available expression and genotypic data, we identified 76 and 28 genome-wide significant cis-eQTLs regulating gene expression in the gluteus medius muscle and liver, respectively. Twelve of these cis-eQTLs were shared by both tissues (i.e. 42.8% of the cis-eQTLs identified in the liver were replicated in the gluteus medius muscle). These results are consistent with previous studies performed in humans, where 50% of eQTLs were shared across tissues. Moreover, we have identified 41 CNVRs in a set of 350 pigs from the same Duroc population, which had been genotyped with the Porcine SNP60 BeadChip by using the PennCNV and GADA softwares, but only a small proportion of these CNVRs co-localized with the cis-eQTL signals.

CONCLUSION

Despite the fact that there are considerable differences in the gene expression patterns of the porcine liver and skeletal muscle, we have identified a substantial proportion of common cis-eQTLs regulating gene expression in both tissues. Several of these cis-eQTLs influence the mRNA levels of genes with important roles in meat (CTSF) and carcass quality (TAPT1), lipid metabolism (TMEM97) and obesity (MARC2), thus evidencing the practical importance of dissecting the genetic mechanisms involved in their expression.

Genomic Analysis Reveals Specific Patterns of Homozygosity and Heterozygosity in Inbred Pigs

The inbred strain of miniature pig is an ideal model for biomedical research due to its high level of homozygosity. In this study, we investigated genetic diversity, relatedness, homozygosity, and heterozygosity using the Porcine SNP60K BeadChip in both inbred and non-inbred Wuzhishan pigs (WZSPs). Our results from multidimensional scaling, admixture, and phylogenetic analyses indicated that the inbred WZSP, with its unique genetic properties, can be utilized as a novel genetic resource for pig genome studies. Inbreeding depression and run of homozygosity (ROH) analyses revealed an average of 61 and 12 ROH regions in the inbred and non-inbred genomes of WZSPs, respectively. By investigating ROH number, length, and distribution across generations, we further briefly studied the impacts of recombination and demography on ROH in these WZSPs. Finally, we explored the SNPs with higher heterozygosity across generations and their potential functional implications in the inbred WZSP. We detected 56 SNPs showing constant heterozygosity with He = 1 across six generations in inbred pigs, while only one was found in the non-inbred population. Among these SNPs, we observed nine SNPs located in swine RefSeq genes, which were found to be involved in signaling and immune processes. Together, our findings indicate that the inbred-specific pattern of homozygosity and heterozygosity in inbred pigs can offer valuable insights for elucidating the mechanisms of inbreeding in farm animals.

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.

Identification of copy number variations using high density whole-genome SNP markers in Chinese Dongxiang spotted pigs

Objective

Copy number variations (CNVs) are a major source of genetic diversity complementary to single nucleotide polymorphism (SNP) in animals. The aim of the study was to perform a comprehensive genomic analysis of CNVs based on high density whole-genome SNP markers in Chinese Dongxiang spotted pigs.

Methods

We used customized Affymetrix Axiom Pig1.4M array plates containing 1.4 million SNPs and the PennCNV algorithm to identify porcine CNVs on autosomes in Chinese Dongxiang spotted pigs. Then, the next generation sequence data was used to confirm the detected CNVs. Next, functional analysis was performed for gene contents in copy number variation regions (CNVRs). In addition, we compared the identified CNVRs with those reported ones and quantitative trait loci (QTL) in the pig QTL database.

Results

We identified 871 putative CNVs belonging to 2,221 CNVRs on 17 autosomes. We further discarded CNVRs that were detected only in one individual, leaving us 166 CNVRs in total. The 166 CNVRs ranged from 2.89 kb to 617.53 kb with a mean value of 93.65 kb and a genome coverage of 15.55 Mb, corresponding to 0.58% of the pig genome. A total of 119 (71.69%) of the identified CNVRs were confirmed by next generation sequence data. Moreover, functional annotation showed that these CNVRs are involved in a variety of molecular functions. More than half (56.63%) of the CNVRs (n = 94) have been reported in previous studies, while 72 CNVRs are reported for the first time. In addition, 162 (97.59%) CNVRs were found to overlap with 2,765 previously reported QTLs affecting 378 phenotypic traits.

Conclusion

The findings improve the catalog of pig CNVs and provide insights and novel molecular markers for further genetic analyses of Chinese indigenous pigs.

A global analysis of CNVs in swine using whole genome sequence data and association analysis with fatty acid composition and growth traits

Copy number variations (CNVs) are important genetic variants complementary to SNPs, and can be considered as biomarkers for some economically important traits in domestic animals. In the present study, a genomic analysis of porcine CNVs based on next-generation sequencing data was carried out to identify CNVs segregating in an Iberian x Landrace backcross population and study their association with fatty acid composition and growth-related traits. A total of 1,279 CNVs, including duplications and deletions, were detected, ranging from 106 to 235 CNVs across samples, with an average of 183 CNVs per sample. Moreover, we detected 540 CNV regions (CNVRs) containing 245 genes. Functional annotation suggested that these genes possess a great variety of molecular functions and may play a role in production traits in commercial breeds. Some of the identified CNVRs contained relevant functional genes (e.g., CLCA4, CYP4X1, GPAT2, MOGAT2, PLA2G2A and PRKG1, among others). The variation in copy number of four of them (CLCA4, GPAT2, MOGAT2 and PRKG1) was validated in 150 BC1_LD (25% Iberian and 75% Landrace) animals by qPCR. Additionally, their contribution regarding backfat and intramuscular fatty acid composition and growth–related traits was analyzed. Statistically significant associations were obtained for CNVR112 (GPAT2) for the C18:2(n-6)/C18:3(n-3) ratio in backfat and carcass length, among others. Notably, GPATs are enzymes that catalyze the first step in the biosynthesis of both triglycerides and glycerophospholipids, suggesting that this CNVR may contribute to genetic variation in fatty acid composition and growth traits. These findings provide useful genomic information to facilitate the further identification of trait-related CNVRs affecting economically important traits in pigs.

Identification of copy number variations in three Chinese horse breeds using 70K single nucleotide polymorphism BeadChip array

Copy number variation (CNV), an essential form of genetic variation, has been increasingly recognized as one promising genetic marker in the analysis of animal genomes. Here, we used the Equine 70K single nucleotide polymorphism genotyping array for the genome-wide detection of CNVs in 96 horses from three diverse Chinese breeds: Debao pony (DB), Mongolian horse (MG) and Yili horse (YL). A total of 287 CNVs were determined and merged into 122 CNV regions (CNVRs) ranging from 199 bp to 2344 kb in size and distributed in a heterogeneous manner on chromosomes. These CNVRs were integrated with seven existing reports to generate a composite genome-wide dataset of 1558 equine CNVRs, revealing 69 (56.6%) novel CNVRs. The majority (69.7%) of the 122 CNVRs overlapped with 438 genes, whereas 30.3% were located in intergenic regions. Most of these genes were associated with common CNVRs, which were shared by divergent horse breeds. As many as 60, 42 and 91 genes overlapping with the breed-specific ss were identified in DB, MG and YL respectively. Among these genes, FGF11, SPEM1, PPARG, CIDEB, HIVEP1 and GALR may have potential relevance to breed-specific traits. These findings provide valuable information for understanding the equine genome and facilitating association studies of economically important traits with equine CNVRs in the future.

Identification of Copy Number Variations in Xiang and Kele Pigs

Xiang and Kele pigs are two well-known local Chinese pig breeds that possess rich genetic resources and have enormous economic and scientific value. We performed a comprehensive genomic analysis of the copy number variations (CNVs) in these breeds. CNVs are one of the most important forms of genomic variation and have profound effects on phenotypic variation. In this study, PorcineSNP60 genotyping data from 98 Xiang pigs and 22 Kele pigs were used to identify CNVs. In total, 172 candidate CNV regions (CNVRs) were identified, ranging from 3.19 kb to 8175.26 kb and covering 80.41 Mb of the pig genome. Approximately 56.40% (97/172) of the CNVRs overlapped with those identified in seven previous studies, and 43.60% (75/172) of the identified CNVRs were novel. Of the identified CNVRs, 82 (47 gain, 33 loss, and two gain-loss events that covered 4.58 Mb of the pig genome) were found only in a Xiang population with a large litter size. In contrast, 13 CNVRs (8 gain and 5 loss events) were unique to a Xiang population with small litter sizes, and 30 CNVRs (14 loss and 16 gain events) were unique to Kele pigs. The CNVRs span approximately 660 annotated Sus scrofa genes that are significantly enriched for specific biological functions, such as sensory perception, cognition, reproduction, ATP biosynthetic processes, and neurological processes. Many CNVR-associated genes, particularly the genes involved in reproductive traits, differed between the Xiang populations with large and small litter sizes, and these genes warrant further investigation due to their importance in determining the reproductive performance of Xiang pigs. Our results provide meaningful information about genomic variation, which may be useful in future assessments of the associations between CNVs and important phenotypes in Xiang and Kele pigs to ultimately help protect these rare breeds.

Evaluation of the linkage-disequilibrium method for the estimation of effective population size when generations overlap: an empirical case

BACKGROUND

Within the genetic methods for estimating effective population size (N e ), the method based on linkage disequilibrium (LD) has advantages over other methods, although its accuracy when applied to populations with overlapping generations is a matter of controversy. It is also unclear the best way to account for mutation and sample size when this method is implemented. Here we have addressed the applicability of this method using genome-wide information when generations overlap by profiting from having available a complete and accurate pedigree from an experimental population of Iberian pigs. Precise pedigree-based estimates of N e were considered as a baseline against which to compare LD-based estimates.

METHODS

We assumed six different statistical models that varied in the adjustments made for mutation and sample size. The approach allowed us to determine the most suitable statistical model of adjustment when the LD method is used for species with overlapping generations. A novel approach used here was to treat different generations as replicates of the same population in order to assess the error of the LD-based N e estimates.

RESULTS

LD-based N e estimates obtained by estimating the mutation parameter from the data and by correcting sample size using the 1/2n term were the closest to pedigree-based estimates. The N e at the time of the foundation of the herd (26 generations ago) was 20.8 ± 3.7 (average and SD across replicates), while the pedigree-based estimate was 21. From that time on, this trend was in good agreement with that followed by pedigree-based N e.

CONCLUSIONS

Our results showed that when using genome-wide information, the LD method is accurate and broadly applicable to small populations even when generations overlap. This supports the use of the method for estimating N e when pedigree information is unavailable in order to effectively monitor and manage populations and to early detect population declines. To our knowledge this is the first study using replicates of empirical data to evaluate the applicability of the LD method by comparing results with accurate pedigree-based estimates.

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.

Global copy number analyses by next generation sequencing provide insight into pig genome variation

Background

Copy number variations (CNVs) confer significant effects on genetic innovation and phenotypic variation. Previous CNV studies in swine seldom focused on in-depth characterization of global CNVs.

Results

Using whole-genome assembly comparison (WGAC) and whole-genome shotgun sequence detection (WSSD) approaches by next generation sequencing (NGS), we probed formation signatures of both segmental duplications (SDs) and individualized CNVs in an integrated fashion, building the finest resolution CNV and SD maps of pigs so far. We obtained copy number estimates of all protein-coding genes with copy number variation carried by individuals, and further confirmed two genes with high copy numbers in Meishan pigs through an enlarged population. We determined genome-wide CNV hotspots, which were significantly enriched in SD regions, suggesting evolution of CNV hotspots may be affected by ancestral SDs. Through systematically enrichment analyses based on simulations and bioinformatics analyses, we revealed CNV-related genes undergo a different selective constraint from those CNV-unrelated regions, and CNVs may be associated with or affect pig health and production performance under recent selection.

Conclusions

Our studies lay out one way for characterization of CNVs in the pig genome, provide insight into the pig genome variation and prompt CNV mechanisms studies when using pigs as biomedical models for human diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-593) contains supplementary material, which is available to authorized users.