Experimental and computational analysis of Caenorhabditis elegans small RNAs

2019 Summer.Includes bibliographical references.Caenorhabditis elegans contains twenty-five Argonautes, of which, only ALG-1 and ALG-2 are known to interact with microRNAs (miRNAs). ALG-5 belongs to the AGO subfamily of Argonautes that includes ALG-1 and ALG-2, but its role in small RNA pathways is unknown. We analyzed by high-throughput sequencing the small RNAs associated with ALG-5, ALG-1, and ALG-2, as well as changes in mRNA expression in alg-5, alg-1, and alg-2 mutants. We show that ALG-5 defines a distinct branch of the miRNA pathway affecting the expression of genes involved in immunity, defense, and development. In contrast to ALG-1 and ALG-2, which associate with the majority of miRNAs and have general roles throughout development, ALG-5 interacts with only a small subset of miRNAs and is specifically expressed in the germline. alg-5 is required for optimal fertility and mutations in alg-5 lead to a precocious transition from spermatogenesis to oogenesis. Our results provide a near-comprehensive analysis of miRNA-Argonaute interactions in C. elegans and reveal a new role for miRNAs in the germline. The small RNA field has grown rapidly since miRNAs were discovered to be conserved regulators of developmental timing. This growth occurred during a time when high-throughput transcriptomic data from microarrays and next-generation sequencing became widely accessible. As a result, research projects dissecting small RNA pathways often produce sequencing data that can be complex and difficult to perform appropriate data analysis for without specialized or advanced computational knowledge. Many researchers end up only study a subset of small RNAs, outsourcing their analysis, or piecing together a pipeline using tools developed for mRNA sequencing. We aim to reduce this barrier to entry in the field and improve reproducibility by creating an open-source, user-friendly data processing pipeline for small RNA sequencing. To create a simple, reproducible pipeline, we utilized the Common Workflow Language (CWL) and Python, while otherwise minimizing dependencies. The pipeline reads a configuration file and sample sheets that can be easily modified by a user to run the complete analysis from raw fastq file to summary statistics and publication-ready plots. We present AQuATx (automated quantitative analysis of transcript expression) for small RNAs and the analysis of C. elegans germline tissue as an example data set. Our software will allow bench scientists with little to no computational knowledge to easily analyze their small RNA sequencing data. Overall, the final software will be a valuable tool for anyone interested in studying small RNAs