Computational identification of PIWI associated RNA sources using novel small RNA and evolutionary analyses

Abstract

PIWI-interacting RNAs (piRNAs) form an essential component in the defense mechanismsagainst transposable elements (TEs), ensuring genomic stability in germ cells across animal species. PiRNAs are small non-coding RNAs that function by guiding PIWI proteins towards target transcripts using sequence complementarity. PiRNA pathways are essential for fertility. Understanding these diverse small RNAs and identifying their longer precursors requires the development of specific computational tools. My thesis work introduces ”piRNA Cluster Builder” (PICB), an R package developed to identify piRNA generating genomic intervals. PICB address the challenges of short read mapping and integrate multimapping reads effectively. PICB employs a nuanced approach to handle unique and multi-mapping alignments differently, ensuring the detection of piRNA clusters and the accurate identification of cluster boundaries. This method consists of three-layer analysis unique mapping alignments to generate seeds, primary multimapping alignments to define cores, and secondary multimapping alignments to finalize clusters. Using PICB, this study examines the piRNA populations in various model organisms including Drosophila melanogaster, Schmidtea mediterranea, and mammals Mus musculus and Mesocricetus auratus. In Drosophila, PICB reveals distinct characteristics of piRNA clusters in ovarian somatic sheath cells compared to germ cells, highlighting the complexity and specialization of piRNA pathways. Analysis of S.mediterranea demonstrates the presence of an active ”ping-pong” mechanism and a high level of strand purification in piRNA clusters, which contrasts sharply with the relatively homogeneous strand productivity observed in Drosophila ovaries. In mammals, the piRNA populations in mouse and hamster testes during different developmental stages show different regulatory mechanisms as revealed by PICB. Notably, pachytene piRNA clusters in mice exhibit a varying degree of transposon content and distinct patterns of piRNA biogenesis compared to prepachytene clusters. The comparative analysis provides insights into the evolutionary dynamics of piRNA clusters, shedding light on conserved regulatory themes and lineage-specific adaptations. Predicted evolutionary feature has been independently verified using RNA sequencing data confirming the analysis. Through supporting cross-species comparisons, PICB paves the way for a deeper understanding of the piRNA pathway evolutionary and functional diversity. The insights gained from these comparative studies hold potential implications for improving RNA therapy and understanding the broader impact of non-coding RNAs in gene expression regulation. This dissertation includes the following supplementary materials: spreadsheet of piRNA cluster genomic coordinates; two large scale phylogenetic trees.