W916A Preliminary Analysis of Longissimus Muscle microRNA Expression Profiles in the Michigan State University F2 Duroc X Pietrain Pig Resource Population
A Preliminary Analysis of Longissimus Muscle microRNA Expression Profiles in the Michigan State University F2 Duroc X Pietrain Pig Resource Population
Date: Saturday, January 9, 2016
Time: 5:55 PM
Time: 5:55 PM
Room: Royal Palm Salon 1-2
MicroRNAs (miRNAs) are a class of small, single-stranded RNAs shown to post-transcriptionally regulate gene expression through complementary binding with target mRNAs. While miRNAs have been shown to regulate gene expression during fetal and early postnatal pig skeletal muscle development, miRNA regulation in market-age pigs has been less explored. The overall objectives of this study are to profile miRNAs in Longissimus dorsi (LD) muscle of F2 pigs from the MSU Duroc x Pietrain resource population for integration into a genome-wide eQTL analysis, and to elucidate gene networks controlling economically important phenotypes. Total RNA extracted from 147 LD samples was sequenced on the Illumina HiSeq 2500 platform. Raw sequence reads were trimmed, quality-filtered and PCR duplicates were removed. After filtering for low read counts, 241 normalized annotated mature miRNA expression profiles were included in a preliminary GBLUP analysis to identify miRNA exhibiting heritable expression utilizing the gwaR package. These miRNA with heritable expression are strong candidates for exhibiting association with genome-wide SNP markers. Average heritability of the 241 miRNAs was 0.16, whereas heritability of the 69 significant miRNAs was 0.34 (q < 0.05). Additionally, miRDeep2 was utilized to predict potentially pig-novel miRNA precursors revealing 235 putative precursors at an estimated false positive rate of 11%. Of these precursors, 89 have a homologous approximately 6-nt seed sequence with annotated human mature miRNA, suggesting their potential as putative pig-novel miRNAs. Further investigation is required to characterize these miRNAs, in order to identify candidates for inclusion in future analyses. Supported by USDA-NIFA-AFRI Grant 2014-67015-21619.
