4.5 Article

Comparative transcriptomic analysis to identify differentially expressed genes in fat tissue of adult Berkshire and Jeju Native Pig using RNA-seq

期刊

MOLECULAR BIOLOGY REPORTS
卷 41, 期 9, 页码 6305-6315

出版社

SPRINGER
DOI: 10.1007/s11033-014-3513-y

关键词

RNA-seq; Jeju Native Pig (JNP); Berkshire; Fat; Differentially expressed genes (DEGs)

资金

  1. Next-Generation BioGreen 21 Program, Rural Development Administration, Republic of Korea [PJ009032022012]
  2. Rural Development Administration (RDA), Republic of Korea [PJ009032022012] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Pork is a major source of animal protein for humans. The subcutaneous, intermuscular and the intramuscular fat are the factors responsible for meat quality. RNA-seq is rapidly adopted for the profiling of the transcriptomes in the studies related to gene regulation. The discovery of differentially expressed genes (DEGs) between adult animals of Jeju Native Pig (JNP) and Berkshire breeds are of particular interest for the current study. RNA-seq was used to investigate the transcriptome profiling in the fat tissue. Sequence reads were obtained from Ilumina HiSeq2000 and mapped to the pig genome using Tophat2. Total 153 DEGs were identified and 71 among the annotated genes, have BLAST matches in the non- redundant database. Metabolic, immune response and protein binding are enriched pathways in the fat tissue. In our study, biological adhesion, cellular, developmental and multicellular organismal processes in fat were up-regulated in JNP as compare to Berkshire. Multicellular organismal process, developmental process, embryonic morphogenesis and skeletal system development were the most significantly enriched terms in fat of JNP and Berkshire breeds (p = 1.17E-04, 0.044, 3.47E-04 and 4.48E-04 respectively). COL10A1, COL11A2, PDK4 and PNPLA3 genes responsible for skeletal system morphogenesis and body growth were down regulated in JNP. This study is the first statistical analysis for the detection of DEGs from RNA-seq data generated from fat tissue sample. This analysis can be used as stepping stone to understand the difference in the genetic mechanisms that might influence the identification of novel transcripts, sequence polymorphisms, isoforms and noncoding RNAs.

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