Department of Exact Science, School of Agricultural and Veterinarian Sciences (FCAV), Sao Paulo State University (UNESP), Jaboticabal, SP, 14884-900, Brazil.
Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA.
BMC Genomics. 2019 Apr 27;20(1):321. doi: 10.1186/s12864-019-5687-0.
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.
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.
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.
本研究整合了 CNV（拷贝数变异）和 WssGWAS（全基因组关联的加权单步方法）分析，以增加关于产仔数的知识，产仔数是一个具有重要经济意义的繁殖性状，对猪的生产效率有重大影响。
共有 3892 个样本使用 Porcine SNP80 BeadChip 进行了基因分型。经过质量控制后，从 3520 头杜洛克猪中共保留了 57962 个高质量 SNP。PennCNV 算法鉴定出 46118 个 CNV，通过重叠形成 425 个 CNV 区域（CNVR），这些 CNV 区域的大小范围为 2.5 Kb 至 9718.4 Kb，覆盖了猪常染色体基因组的 197 Mb（~7.01%）。WssGWAS 鉴定出 16 个基因组区域，这些区域解释了产仔数的加性遗传方差的 1%以上。CNVR 和 WssGWAS 分析的重叠在 SSC2（4.2-5.2 Mb）、SSC3（3.9-4.9 Mb）、SSC12（56.6-57.6 Mb）和 SSC17（17.3-18.3 Mb）上鉴定出了共同区域。这些区域已知含有对猪繁殖性状有重要因果变异的基因，因为它们在受精、配子和胚胎发育过程中起着至关重要的作用。Panther 软件的功能分析确定了本研究中显著代表的 13 个基因本体论生物过程，如生殖、发育过程、细胞成分组织或生物发生和免疫系统过程，这些过程在猪的繁殖性状中起着重要作用。
本研究有助于提高对产仔数遗传结构的理解，因为 GWAS 和 CNV 分析的结合可以更有效地鉴定与杜洛克猪产仔数相关的基因组区域和生物学过程。猪的育种计划可能会从更准确地发现重要基因组区域中受益。
