Identification of Copy Number Variations in Xiang and Kele Pigs

Xie, Jian Ming; Li, Rongrong; Li, Sheng; Ran, Xueqin; Wang, Jiafu; Jiang, Jicai; Zhao, Pengju

doi:10.1371/journal.pone.0148565

Cited by 26 publications

(18 citation statements)

References 74 publications

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“…We also compared our results with previous studies on CNVRs, which showed a low overlap rate [17,35,44,46,54,[57][58][59][60]. In brief, a total of 404 CNVRs entirely or partially overlapped with the previously reported CNVRs.…”

Section: Discussionsupporting

confidence: 52%

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Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

Qiu

Ding²,

Zhuang

et al. 2020

Preprint

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Background: In the process of pig breeding, the average daily gain (ADG), days to 100 kg (AGE), and backfat thickness (BFT) are directly related to growth rate and fatness. However, the genetic mechanisms involved are not well understood. As an essential source of genetic diversity, copy number variation (CNV) that can affect a variety of complex traits and diseases, has gradually been thrust into the limelight. In this study, we reported the genome-wide CNVs of Duroc pigs by SNP genotyping data of 6,627 Duroc pigs. Moreover, we also performed CNV region (CNVR) based association analysis for growth and fatness traits in two Duroc populations.Results: Our study identified a total of 835 nonredundant CNVRs in American and Canadian Duroc pigs, which covered 226.73 Mb (~ 10.00%) of the pig autosomal genome. Among them, we identified 682 CNVRs in the American Duroc pigs and 424 CNVRs in the Canadian Duroc pigs, and 271 CNVRs were detected in both populations. Experimentally, 77.8% of randomly selected CNVRs were validated by quantitative PCR (qPCR). We also identified 24 significant CNVRs for growth and fatness traits though CNVR-based association analysis. Among these, six and three CNVRs in American and Canadian Duroc pigs were found to be associated with both ADG and AGE traits, respectively. Notably, four CNVRs showed both significant in ADG, AGE, and BFT, indicating that these CNVRs may play a pleiotropic role in regulating pig growth and fat deposition. Besides, further bioinformatics analysis determined a subset of potential candidate genes, such as PDGFRB, INSIG1, GPER1, PDGFA, and LPCAT1.Conclusions: The present study provides a necessary supplement to the CNV map of the Duroc genome through a large-scale population genotyping. Also, the CNVR-based association results provide a meaningful way to elucidate the genetic mechanisms of complex traits. The identified CNVRs can be used as molecular markers for genetic improvement in molecular-guided breeding of modern commercial pigs

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Section: Discussionsupporting

confidence: 52%

“…In brief, a total of 404 CNVRs entirely or partially overlapped with the previously reported CNVRs. A considerable overlap rate was observed in the results of Zheng et al [17], while that of Xie et al [60] was the lowest. These discrepant observations may be due to the difference in the breed and population size between our study and others.…”

Section: Discussionmentioning

confidence: 78%

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

Qiu

Ding²,

Zhuang

et al. 2020

Preprint

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“…Although several methodologies have been applied to detect CNVs in the pig genome, SNP arrays have better properties, such as lower cost compared to next generation sequencing (NGS) methodology and can be used for both GWAS and CNV detections. Employing SNP for CNV detection, previous studies have identified thousands of porcine CNVs [12, 16–28]. Because most of these studies comprised relatively small numbers of animals, the impacts of CNVs on phenotypes are still relatively poorly understood.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.

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“…[ 11 ] also identified 368 unique CNV regions from 265 Korean Hanwoo cattle based on 50K SNP array covering 15.8Mb of the genome using PennCNV algorithm without considering the pedigree information and genomic waves. Recent studies on CNV detection using different approaches are given in the Table-1 [ 11 - 14 , 23 , 30 , 34 - 37 , 42 - 46 ] for cattle and Table-2 [ 14 , 16 , 47 - 52 ] for other species.…”

Section: Cnv Identification Studies In Domestic Speciesmentioning

confidence: 99%

Copy number variation in livestock: A mini review

Bhanuprakash¹,

Chhotaray²,

Dr³

et al. 2018

Vet World

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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.

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Identification of Copy Number Variations in Xiang and Kele Pigs

Cited by 26 publications

References 74 publications

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

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

Copy number variation in livestock: A mini review

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