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Abstract Plant microRNAs (miRNAs) are short, noncoding RNA molecules that restrict gene expression via posttranscriptional regulation and function in several essential pathways, including development, growth, and stress responses. Accurately identifying miRNAs in populations of small RNA sequencing libraries is a computationally intensive process that has resulted in the misidentification of inaccurately annotated miRNA sequences. In recent years, criteria for miRNA annotation have been refined with the aim to reduce these misannotations. Here, we describe miRador, a miRNA identification tool that utilizes the most up-to-date, community-established criteria for accurate identification of miRNAs in plants. We combined target prediction and Parallel Analysis of RNA Ends (PARE) data to assess the precision of the miRNAs identified by miRador. We compared miRador to other commonly used miRNA prediction tools and found that miRador is at least as precise as other prediction tools while being substantially faster than other tools. miRador should be broadly useful for the plant community to identify and annotate miRNAs in plant genomes. 

Abstract The Solanaceae or “nightshade” family is an economically important group with remarkable diversity. To gain a better understanding of how the unique biology of the Solanaceae relates to the family’s small RNA (sRNA) genomic landscape, we downloaded over 255 publicly available sRNA data sets that comprise over 2.6 billion reads of sequence data. We applied a suite of computational tools to predict and annotate two major sRNA classes: (1) microRNAs (miRNAs), typically 20- to 22-nucleotide (nt) RNAs generated from a hairpin precursor and functioning in gene silencing and (2) short interfering RNAs (siRNAs), including 24-nt heterochromatic siRNAs typically functioning to repress repetitive regions of the genome via RNA-directed DNA methylation, as well as secondary phased siRNAs and trans-acting siRNAs generated via miRNA-directed cleavage of a polymerase II-derived RNA precursor. Our analyses described thousands of sRNA loci, including poorly understood clusters of 22-nt siRNAs that accumulate during viral infection. The birth, death, expansion, and contraction of these sRNA loci are dynamic evolutionary processes that characterize the Solanaceae family. These analyses indicate that individuals within the same genus share similar sRNA landscapes, whereas comparisons between distinct genera within the Solanaceae reveal relatively few commonalities.