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EN
Post-transcriptional gene regulation guided by microRNAs has emerged as one of the major gene regulatory mechanisms in higher eukaryotes. microRNAs regulate gene translation through the recognition of complementary sequences between microRNAs and their target genes. Recent studies in livestock have revealed that many microRNAs are species- and tissue-specic, indicating that microRNAs play important roles in essential physiological processes in livestock, such as metabolism, and muscle and organ development. It is anticipated that many microRNAs will be linked to phenotypic differences or quantitative trait variations of livestock. The role of microRNA in developmental decisions that affect animal biology is of significant interest, yet the current literature on livestock models is limited. In this review, we summarize the current microRNA studies undertaken in livestock.
EN
Expression patterns of candidate genes with important functions in animal metabolism can help to identify potential molecular markers for cattle production traits. Reverse transcription followed by polymerase chain reaction is a method for rapid and accurate mRNA quantification. However, for exact comparison of mRNA quantity in various samples or tissues, it is important to choose appropriate reference genes. In cattle, little information is available on the expression stability of housekeeping genes (HKGs). The aim of the present study is to develop a set of reference genes that can be used for normalization of concentrations of mRNAs of genes expressed in the bovine liver, kidney, pituitary and thyroid. The study was performed on 6-, 9-, and 12-month-old bulls of dairy and meat cattle breeds. Six HKGs were investigated: ACTB, GAPDH, HPRTI, SDHA, TBP, and YWHAZ. The most stably expressed potential reference HKGs differed among tissues/organs examined: ACTB, TBP, YWHAZ, GAPDH, HPRTI, and SDHA in the liver; GAPDH and YWHAZ in the kidney; GAPDH and SDHA in the pituitary; and TBP and HPRTI in the thyroid. The results showed that the use of a single gene for normalization may lead to relatively large errors, so it is important to use multiple control genes based on a survey of potential reference genes applied to representative samples from specific experimental conditions.
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