RESUMEN
Transcriptomics analysis of various small RNA (sRNA) biotypes is a new and rapidly developing field. Annotations for microRNAs, tRNAs, piRNAs and rRNAs contain information on transcript sequences and loci that is vital for downstream analyses. Several databases have been established to provide this type of data for specific RNA biotypes. However, these sources often contain data in different formats, which makes the bulk analysis of several sRNA biotypes in a single pipeline challenging. Information on some transcripts may be incomplete or conflicting with other entries. To overcome these challenges, we introduce ITAS, or Integrated Transcript Annotation for Small RNA, a filtered, corrected and integrated transcript annotation containing information on several types of small RNAs, including tRNA-derived small RNA, for several species (Homo sapiens, Rattus norvegicus, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans). ITAS is presented in a format applicable for the vast majority of bioinformatic transcriptomics analysis, and it was tested in several case studies for human-derived data against existing alternative databases.
RESUMEN
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.
