NEXTFLEX® Small RNA-Seq Kit v3 

A small RNA library prep kit for Illumina® sequencing which provides randomized adapters for bias reduction along with gel-free or low-input protocols.

Maximize Reads Mapped to miRNAs

The efficiency of the reduced ligation bias technology of the NEXTFLEX® Small RNA-Seq Kit v3 can be accentuated with the adoption of the NEXTFLEX® tRNA/YRNA blockers, which seamlessly integrate into the library prep to block the formation of tRNA and YRNA products in your small RNA libraries, thus increasing the relative proportion of reads mapped to miRNAs. This is particularly helpful for miRNA discovery from complex samples such as biofluids, which can have a high abundance of tRNA/YRNA fragments.

Small RNA-Seq Automation Compatibility

The NEXTFLEX® Small RNA-Seq Kit V3 is 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.

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.

Features

• Completely gel-free protocol with normal input amounts

• Greater discovery/detection rates reduce sequencing cost

• Randomized adapters reduce ligation bias, resulting in more accurate data

• Low input (1 ng) gel-based protocol included

• Offers greater sequencing depth

• Use more of your RNA sample – 10.5 µL input volume

• Barcoded primers are included in the kit allowing multiplexing of up to 48 samples

• An automation protocol is available for the PerkinElmer® Sciclone® G3 NGS/NGSx and the Zephyr® G3 NGS workstation

• Functionally validated with Illumina® sequencing platforms

Kit Specs

KIT CONTENTS

• NEXTFLEX® 3’ 4N Adenylated Adapter

• NEXTFLEX® 3’ Ligation Buffer

• NEXTFLEX® 3’ Ligation Enzyme Mix

• NEXTFLEX® Adapter Depletion Solution

• NEXTFLEX® Adapter Inactivation Buffer

• NEXTFLEX® Adapter Inactivation Enzyme

• NEXTFLEX® 5’ 4N Adapter

• NEXTFLEX® 5’ Ligation Buffer

• NEXTFLEX® 5’ Ligation Enzyme Mix

• M-MuLV Reverse Transcriptase

• NEXTFLEX® RT Buffer

• NEXTFLEX® Universal Primer

• NEXTFLEX® Barcode Primer

• NEXTFLEX® Small RNA PCR Master Mix

• 6X Loading Dye

• Ready to Load Low MW Ladder

• Resuspension Buffer

• Nuclease-free Water

• microRNA Control

• NEXTFLEX® Cleanup Beads

• NEXTFLEX® Elution Buffer

REQUIRED MATERIALS NOT PROVIDED

• 1 ng – 2 μg total RNA or purified small RNA from 1-10 μg total RNA in up to 10.5 μL Nuclease-free Water

• Isopropanol

• 80% Ethanol

• 2, 10, 20, 200 and 1000 μL pipettes

• RNase-free pipette tips

• Microcentrifuge

• 96 well PCR Plate Non-skirted (Phenix Research®, Cat # MPS-499) or similar

• Thin-wall nuclease-free PCR tubes

• Thermocycler

• Heat block

• Vortex

• Magnetic Stand -96 (Thermo Fisher Scientific®, Cat # AM10027) or similar

Selected Citations that Reference the Use of the NEXTFLEX Small RNA-Seq Kit V3:

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.

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.

Chu, C. P., & Nabity, M. B. (2019). Comparison of RNA isolation and library preparation methods for small RNA sequencing of canine biofluids. Veterinary Clinical Pathology. doi:10.1111/vcp.12743.

Coenen-Stass, A.M.L., et al. (2018) Evaluation of methodologies for microRNA biomarker detection by next generation sequencing. RNA Biology. 15: 8. 15:8, 1133-1145. doi: 10.1080/15476286.2018.1514236.

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.

Fu, F. et al. (2018) Loss of mCHH islands in maize chromomethylase and DDM1-type nucleosome remodeler mutants. dx.doi.org/10.1101/253567.

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.

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.

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

Han, S. A., Jhun, B. W., Kim, S.-Y., Moon, S. M., Yang, B., Kwon, O. J., … Koh, W.-J. (2020). miRNA Expression Profiles and Potential as Biomarkers in Nontuberculous Mycobacterial Pulmonary Disease. Scientific Reports, 10(1). doi: 10.1038/s41598-020-60132-0

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.

Kim, K., Yoo, D., Lee, H. S., Lee, K. J., Park, S. B., Kim, C., . . . Song, S. Y. (2019). Identification of potential biomarkers for diagnosis of pancreatic and biliary tract cancers by sequencing of serum microRNAs. BMC Medical Genomics,12(1). doi:10.1186/s12920-019-0521-8.

Ku, A., Ravi, N., Yang, M., Evander, M., Laurell, T., Lilja, H., & Ceder, Y. (2019). A urinary extracellular vesicle microRNA biomarker discovery pipeline; from automated extracellular vesicle enrichment by acoustic trapping to microRNA sequencing. Plos One, 14(10). doi: 10.1371/journal.pone.0224604.

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.

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.

Ong, J., Woldhuis, R. R., Boudewijn, I. M., Berg, A. V., Kluiver, J., Kok, K., . . . Brandsma, C. A. (2019). Age-related gene and miRNA expression changes in airways of healthy individuals. Scientific Reports,9(1). doi:10.1038/s41598-019-39873-0.

Oxnard, G. et al. (2020) Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial (ALCHEMIST).

Pinti, M. V., Hathaway, Q. A., Kunovac, A., Durr, A. J., Cook, C. C., Roberts, H. G., Salman, M., and Hollander, J. M. (2019) microRNA Changes in Diabetic Cardiac Mitochondria: What are they doing there? FASEB J. doi:10.1096/fasebj.2019.33.1_supplement.713.3.

Prieto-Fernández E, Aransay AM, Royo F, et al. (2019) A Comprehensive Study of Vesicular and Non-Vesicular miRNAs from a Volume of Cerebrospinal Fluid Compatible with Clinical Practice. Theranostics. 9(16):4567–4579. doi:10.7150/thno.31502

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.

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.

Russell, S. J., Menezes, K., Balakier, H., & Librach, C. (2020). Comprehensive profiling of Small RNAs in human embryo-conditioned culture media by improved sequencing and quantitative PCR methods. Systems Biology in Reproductive Medicine, 1–11. doi: 10.1080/19396368.2020.1716108.

Wei J, Blenkiron C, Tsai P, James JL, Chen QI, Stone PR, Chamley LW. (2017) Placental trophoblast debris mediated feto-maternal signaling via small RNA delivery: implications for preeclampsia. Scientific Reports. 7:14681. doi.org/10.1038/s41598-017-14180-8

Wright, C., Rajpurohit, A., Burke, E. E., Williams, C., Collado-Torres, L., Kimos, M., . . . Shin, J. H. (2018). Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods. bioRxiv 445437. doi:10.1101/445437.

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.

Zaragoza C, Saura M, Hernández I, et al. (2019) Differential expression of circulating miRNAs as a novel tool to assess BAG3-associated familial dilated cardiomyopathy. Biosci Rep. 39(3):BSR20180934. doi:10.1042/BSR20180934.

Zhang J, Zhang Y, Shen W, Fu R, Ding Z, Zhen Y, Wan Y. (2019) Cytological effects of honokiol treatment and its potential mechanism of action in non-small cell lung cancer. Biomedicine & Pharmacotherapy. 9(117): 109058. doi.org/10.1016/j.biopha.2019.109058