PSXII-4 Impact of delayed processing time on total RNA quality and quantitation of transcript abundance

Abstract

Critical biological information related to economically important traits is present in the blood transcriptome in cattle. Following a sample collection, however, RNA molecules containing this valuable information are prone to degradation affecting transcript abundance. Thus, proper sample handling and storage is essential when working with RNA. Here, we hypothesized that delayed time between sample collection and processing would lead to RNA degradation and alter gene transcript quantification. We aimed to determine the effect of delayed processing of whole blood on transcriptomic profiles in peripheral white blood cells (PWBC). We collected blood samples (10ml) in tubes containing anticoagulant (K2EDTA) from estrus synchronized beef heifers (n = 5). The tubes remained chilled on ice until processing time. From each heifer, we collected five samples from the jugular vein. We processed one sample from each animal within one hour of collection, and we delayed the processing time of the remaining samples to three, six, eight, and 24 hours post collection. We extracted total RNA from PWBCs, measured yield and assessed quality. We also quantified transcript abundance of 12,724 genes by RNA-sequencing. Samples processed 24 hours post collection had lower RNA integrity number (RIN) compared to samples processed withing one hour of collection (RIN24h=8.00±0.37, RIN1h=8.52±0.37, P = 0.03). There were four and 504 genes with differential transcript abundance (FDR< 0.05) when comparing eight and 24 hours of delayed processing with samples processed within one hour of collection, respectively. Notably, several genes had >1.4-fold greater transcript abundance when samples were stored on ice for eight or 24 hours. Our results indicate that RNA degradation and cellular activity of PWBCs have critical impact on transcript abundance when blood samples are stored for 24 hours under refrigeration. As the development of RNA-based biomarkers gain importance in cattle production systems, timely handling of samples is critical for accurate results.