The effects of a globin blocker on the resolution of 3’mRNA sequencing data in porcine blood

Authors: LIM, KYU-SANG - Iowa State University; DONG, QIAN - Iowa State University; MOLL, PAMELA - Lexogen Gmbh; VITKOVSKA, JANA - Lexogen Gmbh; WIKTORIN, GREGOR - Lexogen Gmbh; BANNISTER, STEPHANIE - Lexogen Gmbh; DAUJOTYTE, DALIA - Lexogen Gmbh; TUGGLE, CHRISTOPHER - Iowa State University; Lunney, Joan; PLASTOW, G - University Of Alberta; DEKKERS, JCM - Iowa State University

Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/18/2019
Publication Date: 10/15/2019
Citation: Kyu-Sang, L., Dong, Q., Moll, P., Vitkovska, J., Wiktorin, G., Bannister, S., Daujotyte, D., Tuggle, C.K., Lunney, J.K., Plastow, G., Dekkers, J. 2019. BMC Genomics. 20:741. https://doi.org/10.1186/s12864-019-6122-2.
DOI: https://doi.org/10.1186/s12864-019-6122-2

Interpretive Summary: Our research uses gene expression profiling in blood to identify biomarkers that can predict phenotypic trait differences between pigs. QuantSeq 3'mRNA sequencing (QuantSeq) increases efficiency of gene expression analyses by sequencing only the 3' end of each mRNA. An additional issue is the high levels of hemoglobin (HB) mRNA in porcine blood; this was overcome by using novel, specific porcine globin blockers to block processing of HB mRNA prior to library construction. Overall, we are providing pig researchers 1) validation of the effectiveness of QuantSeq, and 2) globin blocker tools for improved quantification of whole gene expression profiles in porcine blood.

Technical Abstract: Background: Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of hemoglobin (HB) mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3'mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of HB mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq. Results: In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of HB reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-HB genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of HB reads (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12 %) as C1 but a better correlation of the expression of non-HB genes between NGB and GB (r = 0.98), allowed the expression of an additional 1,295 non-HB genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of HB reads for NGB (n=184) and GB (n=189) samples clearly showed the effects of the GB on reducing HB reads, in particular for HBB, similar to results from data set 1. Data set 3 (n=84) revealed that the proportion of HB reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001). Conclusions: The effect of the GB on reducing the proportion of HB reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-HB mRNA, the GB for QuantSeq has as advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.