Optimization of small RNA extraction and comparative study of NGS library preparation from low count sperm samples
Year: 2021
Type: article
Abstract: Recent studies demonstrate that sperm epigenome is a vehicle that conveys paternal experiences to offspring phenotype. That evidence triggers interest of both experimental and epidemiological studies of epigenetic markers in sperm. Since samples are often unique in epidemiological studies, a careful and efficient use of the material is a critical requirement. The goal of this study was to provide optimization of methods for the isolation of small RNAs from spermatozoa and library preparation for sequencing. A total 67 fractionated sperm samples from the Russian Children's Study biobank prospectively collected at 18-20 years of age were used to isolate small RNAs with median (IQR) input total sperm count 17.0 (7.4-35.9) million. Twenty-four pairs of libraries were prepared using the NEBNext and NEXTFlex kits, 19 libraries using NEBNext and 6 using NEXTFlex. All libraries were sequenced on NextSeq 500, and the results were evaluated as a function of the number of small non-coding RNA (sncRNA) detected, quality parameters of sequencing libraries, as well as technical features of sample preparation. Although the same amount of miRNA input was used for NEBNext and NEXTFlex libraries, the concentration of DNA in NEBNext libraries was significantly higher in comparison with NEXTFlex libraries. In high input (sperm count >28 million and more than 25 ng miRNA in library) NEXTFlex Small RNA-Seq kit detected more microRNAs. In low input, the NEBNext proved more effective. The tricks and traps to protocol optimization are presented, including an efficient and effector gel-based system for the removal of sequencing library adaptors.
Institutions: Lomonosov Moscow State University, Ministry of Health of the Russian Federation, National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I.Kulakov of the Ministry of Healthcare of the Russian Federation, University of Massachusetts Amherst, Harvard University, Wayne State University
Language: English
Subfield: Reproductive Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Russian Science Foundation
Award: G4702077908
OpenAlex ID: W3165036471
