Abstract
MicroRNAs (miRNAs) are small 21–22 nt RNAs that act to regulate the expression of mRNA target genes through direct binding to mRNA targets. While miRNAs typically dominate small RNA (sRNA) transcriptomes, many other classes are present including tRNAs, snoRNAs, snRNAs, Y-RNAs, piRNAs, and siRNAs. Interactions between processing machinery and targeting networks of these various sRNA classes remains unclear, largely because these sRNAs are typically analyzed separately. Here, we present TEsmall, a tool that allows for the simultaneous processing and analysis of sRNAs from each annotated class in a single integrated workflow. The pipeline begins with raw fastq reads and proceeds all the way to producing count tables formatted for differential expression analysis. Several interactive charts are also produced to look at overall distributions in length and annotation classes. We next applied the TEsmall pipeline to sRNA libraries generated from melanoma cells responding to targeted inhibitors of the MAPK pathway. Targeted oncogene inhibitors have emerged as way to tailor cancer therapies to the particular mutations present in a given tumor. While these targeted strategies are typically effective for short intervals, the emergence of resistance is extremely common, limiting the effectiveness of single-agent therapeutics and driving the need for a better understanding of resistance mechanisms. Using TEsmall, we identified several microRNAs and other sRNA classes that are enriched in inhibitor resistant melanoma cells in multiple melanoma cell lines and may be able to serve as markers of resistant populations more generally.
Highlights
MicroRNAs are small 21–22 nucleotide RNA molecules which have been shown to play a critical role in metazoan development and gene regulation
The small RNA (sRNA) sequencing libraries were prepared with the Illumina TruSeq Small RNA Library Preparation Kits using an input of 1.2 μg total RNA and following the manufacturer’s protocols as described, using 15 PCR cycles to reduce the likelihood of PCR amplification artifacts
TEsmall is a package designed to identify sRNAs derived from a variety of genomic features simultaneously, such that users can evaluate the relative abundances and profiles of many source of sRNAs on a common scale in a single pipeline. This serves as a novel improvement to currently available software such as mirDeep2 (Friedländer et al, 2012) and piPipes (Han et al, 2015), which are optimized for the analysis of miRNAs and piRNAs, respectively, but are not equipped to evaluate both types of sRNAs together
Summary
MicroRNAs (miRNAs) are small 21–22 nucleotide RNA molecules which have been shown to play a critical role in metazoan development and gene regulation. In addition to governing development, small RNAs (sRNAs) play a critical role in repressing transcripts derived from repetitive regions of the genome. Identification of miRNAs and siRNAs which originate from non-canonical regions of the genome is more challenging with few programs designed to detect sRNAs from all classes in both unique and repetitive genomic loci. It is for this reason we present TEsmall, a package designed for the simultaneous analysis of sRNAs derived from a variety of genomic features. This package facilitates the discovery of intriguing biological phenomena otherwise masked by insufficient annotation of repetitive genomic elements, such as siRNAs, and allows these elements to be incorporated into downstream differential analysis through packages like DESeq (Love et al, 2014)
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