4.6 Article

Identifying suitable reference genes for gene expression analysis in developing skeletal muscle in pigs

Journal

PEERJ
Volume 4, Issue -, Pages -

Publisher

PEERJ INC
DOI: 10.7717/peerj.2428

Keywords

Expression analysis; Reference gene; Skeletal muscle; Development

Funding

  1. National Key Project [2016ZX08009003-006-003]
  2. National Natural Science Foundation of China [31372295, 31330074]
  3. Agricultural Science and Technology Innovation Program [ASTIP-IAS16]

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The selection of suitable reference genes is crucial to accurately evaluate and normalize the relative expression level of target genes for gene function analysis. However, commonly used reference genes have variable expression levels in developing skeletal muscle. There are few reports that systematically evaluate the expression stability of reference genes across prenatal and postnatal developing skeletal muscle in mammals. Here, we used quantitative PCR to examine the expression levels of 15 candidate reference genes (ACTB, GAPDH, RNF7, RHOA, RPS18, RPL32, PPIA, H3F3, AP15, B2M, AP1S1, DRAP1, TBP, WSB, and VAPB) in porcine skeletal muscle at 26 different developmental stages (15 prenatal and 11 postnatal periods). We evaluated gene expression stability using the computer algorithms geNorm, NorrmFinder, and BestKeeper. Our results indicated that GAPDH and ACTB had the greatest variability among the candidate genes across prenatal and postnatal stages of skeletal muscle development. RPS18, API5, and VAPB had stable expression levels in prenatal stages, whereas API5, RPS18, RPL32, and H3F3 had stable expression levels in postnatal stages. API5 and H3F3 expression levels had the greatest stability in all tested prenatal and postnatal stages, and were the most appropriate reference genes for gene expression normalization in developing skeletal muscle. Our data provide valuable information for gene expression analysis during different stages of skeletal muscle development in mammals. This information can provide a valuable guide for the analysis of human diseases.

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