Diversity and signature of small RNA in different bodily fluids using next generation sequencing

• Main Authors: Mohamed El-Mogy, Bernard Lam, Taha A. Haj-Ahmad, Shannon McGowan, Darrick Yu, Lucas Nosal, Nezar Rghei, Pam Roberts, Yousef Haj-Ahmad
• Format: Article
• Language: English
• Published: BMC 2018-05-01
• Series: BMC Genomics
• Subjects: miRNA; tRNA; piRNA; Next generation sequencing; Blood; Plasma
• Online Access: http://link.springer.com/article/10.1186/s12864-018-4785-8

Abstract Background Small RNAs are critical components in regulating various cellular pathways. These molecules may be tissue-associated or circulating in bodily fluids and have been shown to associate with different tumors. Next generation sequencing (NGS) on small RNAs is a powerful tool for profiling and discovery of microRNAs (miRNAs). Results In this study, we isolated total RNA from various bodily fluids: blood, leukocytes, serum, plasma, saliva, cell-free saliva, urine and cell-free urine. Next, we used Illumina’s NGS platform and intensive bioinformatics analysis to investigate the distribution and signature of small RNAs in the various fluids. Successful NGS was accomplished despite the variations in RNA concentrations among the different fluids. Among the fluids studied, blood and plasma were found to be the most promising fluids for small RNA profiling as well as novel miRNA prediction. Saliva and urine yielded lower numbers of identifiable molecules and therefore were less reliable in small RNA profiling and less useful in predicting novel molecules. In addition, all fluids shared many molecules, including 139 miRNAs, the most abundant tRNAs, and the most abundant piwi-interacting RNAs (piRNAs). Fluids of similar origin (blood, urine or saliva) displayed closer clustering, while each fluid still retains its own characteristic signature based on its unique molecules and its levels of the common molecules. Donor urine samples showed sex-dependent differential clustering, which may prove useful for future studies. Conclusions This study shows the successful clustering and unique signatures of bodily fluids based on their miRNA, tRNA and piRNA content. With this information, cohorts may be differentiated based on multiple molecules from each small RNA class by a multidimensional assessment of the overall molecular signature.