Expression analysis of porcine miR-33a/b in liver, adipose tissue and muscle and its potential role in fatty acid metabolism

mir-33a and mir-33b are co-transcribed with the SREBF2 and SREBF1 transcription factors, respectively. The main role of SREBF1 is the regulation of genes involved in fatty acid metabolism, while SREBF2 regulates genes participating in cholesterol biosynthesis and uptake. Our objective was to study the expression of both miR-33a and miR-33b, together with their host SREBF genes, in liver, adipose tissue and muscle to better understand the role of miR-33a/b in the lipid metabolism of pigs. In our study, the expression of miR-33a, miR-33b and SREBF2 in liver, adipose tissue, and muscle was studied in 42 BC1_LD (25% Iberian x 75% Landrace backcross) pigs by RT-qPCR. In addition, the expression of in-silico predicted target genes and fatty acid composition traits were correlated with the miR-33a/b expression. We observed different tissue expression patterns for both miRNAs. In adipose tissue and muscle a high correlation between miR-33a and miR-33b expression was found, whereas a lower correlation was observed in liver. The expression analysis of in-silico predicted target-lipid related genes showed negative correlations between miR-33b and CPT1A expression in liver. Conversely, positive correlations between miR-33a and PPARGC1A and USF1 gene expression in liver were observed. Lastly, positive and negative correlations between miR-33a/b expression and saturated fatty acid (SFA) and polyunsaturated fatty acid (PUFA) content, respectively, were identified. Overall, our results suggested that both miRNAs are differentially regulated and have distinct functions in liver, in contrast to muscle and adipose tissue. Furthermore, the correlations between miR-33a/b expression both with the expression of in-silico predicted target-lipid related genes and with fatty acid composition, opens new avenues to explore the role of miR33a/b in the regulation of lipid metabolism.
This work was supported by the Spanish Ministerio de Economía y Competitividad (MINECO) with project AGL2017-82641-R (https://portal.mineco.gob.es/es-es/Paginas/default.aspx) and the Fondo Europeo de Desarrollo Regional (FEDER, http://ec.europa.eu/regional_policy/es/funding/erdf/). LCM was financially supported by an FPI grant from the AGL2014-56369-C2 project. MB was funded with a “Ramón y Cajal” contract (RYC-2013-12573) from the Spanish Ministerio de Economía y Competitividad. DCP was funded by a “Formació i Contractació de Personal Investigador Novell” (FI-DGR) Ph.D grant from the Generalitat de Catalunya (ECO/1788/2014). MP was funded by an FPI grant from the AGL2017-82641-R project. We acknowledge the support of the Spanish Ministerio de Economía y Competitividad for the “Severo Ochoa Programme for Centres of Excellence in R&D” 2016-2019 (SEV-2015-0533) to the Centre for Research in Agricultural Genomics and the CERCA Programme / Generalitat de Catalunya.