Yuhua Fu1, Jingxuan Li1, Qianzi Tang2, Cheng Zou1, Linyuan Shen2, Long Jin2, Cencen Li1, Chengchi Fang1, Rui Liu2, Mingzhou Li2, Shuhong Zhao1, Changchun Li1. 1. Key Lab of Agriculture Animal Genetics, Breeding, & Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, PR China. 2. Institute of Animal Genetics & Breeding, College of Animal Science & Technology, Sichuan Agricultural University, Chengdu, 611130, PR China.
Abstract
AIM: Integrated analysis of methylome and transcriptome may help understand the molecular basis of the different breeds with different traits of commercial interest. MATERIALS & METHODS: We obtained the first genome-wide methylome with single-base resolution, miRNAome and transcriptome from three swine breeds. RESULTS: We displayed the landscape of the three omics in the whole-genome level. Integrated outcomes of methylome with genetic selection, miRNAome and transcriptome are also provided. Finally, we identified 11 candidate differentially methylated genes associated with phenotype variance in pigs. CONCLUSION: DNA methylation not only suppresses transcriptome but also miRNAome. The different -omics data have complicated interaction in directly or indirectly and exhibited close relations with the distinct phenotypic traits of growth, disease resistance and energy metabolism.
AIM: Integrated analysis of methylome and transcriptome may help understand the molecular basis of the different breeds with different traits of commercial interest. MATERIALS & METHODS: We obtained the first genome-wide methylome with single-base resolution, miRNAome and transcriptome from three swine breeds. RESULTS: We displayed the landscape of the three omics in the whole-genome level. Integrated outcomes of methylome with genetic selection, miRNAome and transcriptome are also provided. Finally, we identified 11 candidate differentially methylated genes associated with phenotype variance in pigs. CONCLUSION: DNA methylation not only suppresses transcriptome but also miRNAome. The different -omics data have complicated interaction in directly or indirectly and exhibited close relations with the distinct phenotypic traits of growth, disease resistance and energy metabolism.
Entities:
Keywords:
important economic trait; methylome; transcriptome