GO enrichment analysis of clusters
Once targets were detected we ran a gene set enrichment analysis (GSEA) on the targets of the miRNA in each cluster using the parent-child algorithm in topGO [v2.46.0 (Alexa & Rahnenfuhrer, 2020; Grossmann, Bauer, Robinson, & Vingron, 2007)] and a functional annotation for the longest isoforms of each gene in our P. napi annotation produced with eggNOG (Rodríguez del Río et al., 2022).. We checked for enrichment for Biological Processes using the functional annotations of their identified miRNA targets (Wheat et al., in review ). An FDR of 0.001 was used as a cutoff, as well as a minimum of 2 members present. Due to the number of targets in each cluster the results were dominated by large GO terms that are difficult to interpret. To focus the GSEA analysis, gene sets within cluster were filtered to only include those containing a minimal number of miRNA target sites per gene. An increased number of predicted targets per gene reduces false-positive detection of miRNA targets (Ritchie, Flamant, & Rasko, 2009), and also indicates coordination of targets within a larger set of targeted genes. Each cluster had varying numbers of miRNAs targeting genes, so the minimum number of targeting miRNAs needed per locus to be included per cluster GSEA was determined to be the number that produced a majority of the top ten GO terms containing more than one significant gene.