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Porcine production is a primary market in the world economy. Controlling swine diseases in the farm is essential in order to achieve the sector necessities. Aujeszky's disease is a viral condition affecting pigs and is endemic in many countries of the world, causing important economic losses in the swine industry. microRNAs (miRNAs) are non-coding RNAs which modulates gene expression in animals, plants and viruses. With the aim of understanding miRNA roles during the Aujeszky's disease virus [ADV] (also known as suid herpesvirus type 1 [SuHV-1]) infection, the expression profiles of host and viral miRNAs were determined through deep sequencing in SuHV-1 infected porcine cell line (PK-15) and in an animal experimental SuHV-1 infection with virulent (NIA-3) and attenuated (Begonia) strains. In the in vivo approach miR-206, miR-133a, miR-133b and miR-378 presented differential expression between virus strains infection. In the in vitro approach, most miRNAs were down-regulated in infected groups. miR-92a and miR-92b-3p were up-regulated in Begonia infected samples. Functional analysis of all this over expressed miRNAs during the infection revealed their association in pathways related to viral infection processes and immune response. Furthermore, 8 viral miRNAs were detected by stem loop RT-qPCR in both in vitro and in vivo approaches, presenting a gene regulatory network affecting 59 viral genes. Most described viral miRNAs were related to Large Latency Transcript (LLT) and to viral transcription activators EP0 and IE180, and also to regulatory genes regarding their important roles in the host-pathogen interaction during viral infection.

microRNAs (miRNAs) are important post-transcriptional regulators in eukaryotes that target mRNAs repressing their expression. The uncertain process of pig domestication, with different origin focuses, and the selection process that commercial breeds suffered, have generated a wide spectrum of breeds with clear genetic and phenotypic variability. The aim of this work was to define the miRNAs expression profile in kidney of several porcine breeds. Small RNA libraries from kidney were elaborated and high-throughput sequenced with the 454 Genome Sequencer FLX (Roche). Pigs used were classified into three groups: the European origin group (Iberian breed and European Wild Boar ancestor), European commercial breeds (Landrace, Large White and Piétrain breeds) and breeds with Asian origin (Meishan and Vietnamese breeds). A total of 229 miRNAs were described in the pig kidney miRNA profile, including 110 miRNAs out of the 257 previously described pig miRNAs and 119 orthologous miRNAs. The most expressed miRNAs in pig kidney microRNAome were Hsa-miR-200b-3p, Ssc-miR-125b and Ssc-miR-23b. Moreover, 5 novel porcine miRNAs and 3 orthologous miRNAs could be validated through RT-qPCR. miRNA sequence variation was determined in 116 miRNAs, evidencing the presence of isomiRs. 125 miRNAs were differentially expressed between breed groups. The identification of breed-specific miRNAs, which could be potentially associated to certain phenotypes, is becoming a new tool for the study of the genetic variability underlying complex traits and furthermore, it adds a new layer of complexity to the interesting process of pig evolution.

Relative quantification is the strategy of choice for processing RT-qPCR data in microRNAs (miRNAs) expression studies. Normalisation of relative quantification data is performed by using reference genes. In livestock species, such as pigs, the determination of reference miRNAs and the optimal number of them has not been widely studied. In this study, the stability of ten miRNAs (Ssc-let-7a, Ssc-miR-103, Ssc-miR-17-3p, Hsa-miR-25, Hsa-miR-93, Ssc-miR-106a, Ssc-miR-191, Ssc-miR-16, Ssc-miR-26a and Ssc-miR-17-5p) was investigated by RT-qPCR in different tissues (skeletal muscle, kidney, liver, ovary and uterus) and in different pig breeds (Iberian, Landrace, Large White, Meishan and Vietnamese) as variation factors. Stability values were calculated with geNorm and NormFinder algorithms obtaining high correlation between them (r(2) = 0.99). The analyses showed that tissue is an important variability factor in miRNAs expression stability whereas breed is not a determinant factor. All ten miRNAs analysed had good stability values and, therefore, can be used as reference miRNAs. When all tissues were considered, miR-93 was the most stable miRNA. Dividing data set by tissues, let-7a was the most stable in skeletal muscle and ovary, miR-17-5p in kidney, miR-26a in liver and miR-103 in uterus. Moreover, the optimal number of reference miRNAs to be used for proper normalisation data was determined. It is suggested the use of five reference miRNAs (miR-93, miR-25, miR-106a, miR-17-5p and miR-26a) in multi-tissue experimental designs and the use of three reference miRNAs as the optimal number in single tissues studies (let-7a, miR-17-5p and miR-25 in skeletal muscle; miR-17-5p, miR-93 and miR-26a in kidney, miR-26a, miR-103 and let-7a in liver, let-7a, miR-25 and miR-106a in ovary and miR-103, let-7a and miR-93 in uterus). Overall, this study provides valuable information about the porcine reference miRNAs that can be used in order to perform a proper normalisation when relative quantification by RT-qPCR studies is undertaken.