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Improved Detection and Characterization of Copy Number Variations Among Diverse Pig Breeds by Array CGH

文献类型: 外文期刊

作者: Wang, Jiying 1 ; Jiang, Jicai 1 ; Wang, Haifei 1 ; Kang, Huimin 1 ; Zhang, Qin 1 ; Liu, Jian-Feng 1 ;

作者机构: 1.China Agr Univ, Coll Anim Sci & Technol, Natl Engn Lab Anim Breeding, Key Lab Anim Genet Breeding & Reprod,Minist Agr, Beijing 100193, Peoples R China

2.Shandong Acad Agr Sci, Inst Anim Sci & Vet Med, Shandong Prov Key Lab Anim Dis Control & Breeding, Jinan 250100,

关键词: genomic variation;copy number variations;array CGH;pigs

期刊名称:G3-GENES GENOMES GENETICS ( 影响因子:3.154; 五年影响因子:3.369 )

ISSN: 2160-1836

年卷期: 2015 年 5 卷 6 期

页码:

收录情况: SCI

摘要: As a major component of genomic variation, copy number variations (CNVs) are considered as promising markers for some phenotypic and economically important traits in domestic animals. Using a custom-designed 1M array CGH (aCGH), we performed CNV discovery in 12 pig samples from one Asian wild boar population, six Chinese indigenous breeds, and two European commercial breeds. In total, we identified 758 CNV regions (CNVRs), covering 47.43 Mb of the pig genome sequence. Of the total porcine genes, 1295 genes were completely or partially overlapped with the identified CNVRs, which enriched in the terms related to sensory perception of the environment, neurodevelopmental processes, response to external stimuli, and immunity. Further probing the potential functions of these genes, we also found a suite of genes related important traits, which make them a promising resource for exploring the genetic basis of phenotype differences among diverse pig breeds. Compared with previous relevant studies, the current study highlights that different platforms can complement each other, and the combined implementation of different platforms is beneficial to achieve the most comprehensive CNV calls. CNVs detected in diverse populations herein are essentially complementary to the CNV map in the pig genome, which would be helpful for understanding the pig genome variants and investigating the associations between various phenotypes and CNVs.

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