Feng Li1,2, Karolina Elżbieta Kaczor-Urbanowicz2,3, Jie Sun4, Blanca Majem5, Hsien-Chun Lo6, Yong Kim2, Kikuye Koyano6, Shannon Liu Rao2, So Young Kang7, Su Mi Kim8, Kyoung-Mee Kim7, Sung Kim8, David Chia9, David Elashoff10, Tristan R Grogan10, Xinshu Xiao6, David T W Wong11,12,13,14. 1. Institute of Diagnostic in Chinese Medicine, Hunan University of Chinese Medicine, Hunan, China. 2. Center for Oral/Head & Neck Oncology Research, School of Dentistry, University of California at Los Angeles, Los Angeles, CA. 3. Department of Orthodontics, School of Dentistry, University of California at Los Angeles, Los Angeles, CA. 4. Medical School of Shenzhen University, Shenzhen, Guangdong, China. 5. Biomedical Research Unit in Gynecology, Vall d'Hebron Research Institute (VHIR) and University Hospital, University Autonoma of Barcelona (UAB), Barcelona, Spain. 6. Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA. 7. Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. 8. Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. 9. Department of Pathology & Laboratory Medicine, University of California at Los Angeles, Los Angeles, CA. 10. Department of Biostatistics, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA. 11. Center for Oral/Head & Neck Oncology Research, School of Dentistry, University of California at Los Angeles, Los Angeles, CA; dtww@ucla.edu. 12. Department of Biomedical Engineering, School of Engineering, University of California at Los Angeles, Los Angeles, CA. 13. Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA. 14. Department of Head and Neck Surgery/Otolaryngology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA.
Abstract
BACKGROUND: It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential. METHODS: We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated. RESULTS: The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%). CONCLUSIONS: Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.
BACKGROUND: It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential. METHODS: We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated. RESULTS: The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%). CONCLUSIONS: Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.
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