Gel-Free Small RNA Library Prep with Randomized Adapters for Reduced Bias
The NEXTflex® Small RNA-Seq Kit v3 uses patented and patent-pending technology to provide a reduced-bias small RNA library preparation solution for Illumina® sequencing platforms with gel-free or low-input options. Bioo Scientific’s approach to reducing ligation-associated bias involves the use of adapters with randomized bases at the ligation junctions, resulting in greatly decreased bias in comparison to standard protocols. This reduction in bias results in data that more accurately represents abundances of small RNAs in the starting material. In addition, reduction of bias allows more miRNAs to be detected with fewer total reads, increasing efficiency and reducing cost for small RNA sequencing.
PAGE purification, required for traditional small RNA library prep, is tedious, time consuming, limits throughput, and prevents start-to-finish automation. The NEXTflex Small RNA-Seq Kit v3 allows for gel-free small RNA library preparation. This is possible thanks to the dual approach used for adapter-dimer reduction. Unprecedented reduction of adapter-dimer formation allows completely gel-free small RNA library prep when starting with ≥200 ng of total RNA. Libraries prepared with the NEXTflex Small RNA-Seq kit v3 have a higher proportion of reads mapping to miRNAs (Fig. 1).
Figure 1. Small RNA libraries were created in duplicate from the human brain total RNA and sequenced on an Illumina MiSeq. The indicated number of reads were sampled from each library and the average number of miRNA groups with ≥20 reads determined. The inset shows the number of reads required to detect 100 miRNA groups at a threshold of ≥20 reads.
Low Input Small RNA Library Prep for Illumina® Sequencing
The adapter-dimer reduction technology incorporated into this kit also allows low input library preparation. Library preparation with as little as 1 ng of total RNA is possible as additional PCR cycles can be performed without adapter-dimer products dominating the final library. Fig. 2 illustrated that expression values are reproducible across different sample inputs.
Figure 2. Correlation of miRNA expression between samples created with 100 ng and 10 ng total RNA from human brain with the NEXTflex Small RNA-Seq kit v3. The Pearson correlation coefficient is shown.
Illumina Small RNA-Seq Multiplexing
Eight barcoded primers are included in the eight reaction NEXTflex Small RNA-Seq Kit v3 and forty-eight barcoded primers are included in the forty-eight reaction NEXTflex Small RNA-Seq Kit v3.
Small RNA-Seq Automation Compatibility
The NEXTflex Small RNA-Seq Kit V3 was designed for easy migration onto automated liquid handling platforms. Currently methods are available for the PerkinElmer® Sciclone® NGS/NGSx and the Zephyr® G3 NGS workstation.
Download the Sciclone® NGS and NGSx Workstation Automation Guide for the NEXTflex Small RNA-Seq Kit V3.
Download the Zephyr® G3 NGS Workstation Automation Guide for the NEXTflex® Small RNA-Seq Kit v3.
For more information contact Bioo.NGS@PerkinElmer.com.
Selected Citations that Reference the Use of the NEXTflex Small RNA-Seq Kit V3
Garcia-Elias, A. et al. (2017) Defining quantification methods and optimizing protocols for microarray hybridization of circulating microRNAs. Scientific Reports. 7: 7725. doi:10.1038/s41598-017-08134-3.
Giraldez, M. D., Spengler, R. M., Etheridge, A., Godoy, P. M., Barczak, A. J., Srinivasan, S., . . . Tewari, M. (2018). Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling. Nature Biotechnology. doi:10.1038/nbt.4183.
Fu, F. et al. (2018) Loss of mCHH islands in maize chromomethylase and DDM1-type nucleosome remodeler mutants. dx.doi.org/10.1101/253567.
Lee, E. K., Jeong, H. O., Bang, E. J., Kim, C. H., Mun, J. Y., Noh, S., & Chung, H. Y. (2018). The involvement of serum exosomal miR-500-3p and miR-770-3p in aging: modulation by calorie restriction. Oncotarget, 9(5), 5578–5587. http://doi.org/10.18632/oncotarget.23651.
Rafael G Miranda, James J McDermott, Alice Barkan; RNA-binding specificity landscapes of designer pentatricopeptide repeat proteins elucidate principles of PPR–RNA interactions, Nucleic Acids Research, Volume 46, Issue 5, 16 March 2018, Pages 2613–2623, https://doi.org/10.1093/nar/gkx1288.
Chen, Y., Wang, J., Yang, S., Utturkar, S., Crodian, J., Cummings, S., & Plaut, K. (2017). Effect of high-fat diet on secreted milk transcriptome in midlactation mice. Physiological genomics, 49(12), 747-762.
Chotewutmontri, P., Stiffler, N., Watkins, K. P., & Barkan, A. (2018). Ribosome Profiling in Maize. In Maize (pp. 165-183). Humana Press, New York, NY.
Carney, M. C., Tarasiuk, A., DiAngelo, S. L., Silveyra, P., Podany, A., Birch, L. L., ... & Hicks, S. D. (2017). Metabolism-related microRNAs in maternal breast milk are influenced by premature delivery. Pediatric research, 82(2), 226.
Dard-Dascot, C., et al. (2018) Systematic comparison of small RNA library preparation protocols for next-generation sequencing. BMC Genomics 19(118), doi:10.1186/s12864-018-4491-6.
Ghasemzadeh, A., ter Haar, M. M., Shams-bakhsh, M., Pirovano, W., & Pantaleo, V. (2018). Shannon entropy to evaluate substitution rate variation among viral nucleotide positions in datasets of viral siRNAs. In Viral Metagenomics (pp. 187-195). Humana Press, New York, NY.
He, R., Xie, X., Lv, L., Huang, Y., Xia, X., Chen, X., & Zhang, L. (2017). Comprehensive investigation of aberrant microRNAs expression in cells culture model of MnCl2-induced neurodegenerative disease. Biochemical and biophysical research communications, 486(2), 342-348.
Hicks, S. D., Carney, M. C., Tarasiuk, A., DiAngelo, S. L., Birch, L. L., & Paul, I. M. (2017). Breastmilk microRNAs are stable throughout feeding and correlate with maternal weight.
Hicks, S. D., Johnson, J., Carney, M. C., Bramley, H., Olympia, R. P., Loeffert, A. C., & Thomas, N. J. (2018). Overlapping microRNA expression in saliva and cerebrospinal fluid accurately identifies pediatric traumatic brain injury. Journal of neurotrauma, 35(1), 64-72.
Mateescu, B., Kowal, E. J., van Balkom, B. W., Bartel, S., Bhattacharyya, S. N., Buzás, E. I., ... & Driedonks, T. A. (2017). Obstacles and opportunities in the functional analysis of extracellular vesicle RNA–an ISEV position paper. Journal of extracellular vesicles, 6(1), 1286095.
Miranda, R. G., McDermott, J. J., & Barkan, A. (2017). RNA-binding specificity landscapes of designer pentatricopeptide repeat proteins elucidate principles of PPR–RNA interactions. Nucleic acids research.
Nguyen, Q., Iritani, A., Ohkita, S., Vu, B. V., Yokoya, K., Matsubara, A., & Nakayashiki, H. (2018). A fungal Argonaute interferes with RNA interference. Nucleic acids research.
Rosenberg, A. Z., Wright, C., Fox-Talbot, K., Rajpurohit, A., Williams, C., Porter, C., . . . Halushka, M. K. (2018). XMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells. doi:10.1101/333658.
Yeri, A., et al. (2018) Evaluation of commercially available small RNASeq library preparation kits using low input RNA. BMC Genomics 201819:331. doi: 10.1186/s12864-018-4726-6.
The NEXTflex Small RNA Sequencing Kit v3 contains the reagents, including barcoded primers, to prepare 8 or 48 small RNA samples for Illumina® next-generation sequencing. The shelf life of all reagents is 6 months when stored properly at -20°C. Ships on dry ice.