Abstract
Post-transcriptional trimming and tailing of RNA 3' ends play key roles in the processing and quality control of noncoding RNAs (ncRNAs). However, bioinformatic tools to examine changes in the RNA 3' "tailome" are sparse and not standardized. Here we present Tailer, a bioinformatic pipeline in two parts that allows for robust quantification and analysis of tail information from next-generation sequencing experiments that preserve RNA 3' end information. The first part of Tailer, Tailer-processing, uses genome annotation or reference FASTA gene sequences to quantify RNA 3' ends from SAM-formatted alignment files or FASTQ sequence read files produced from sequencing experiments. The second part, Tailer-analysis, uses the output of Tailer-processing to identify statistically significant RNA targets of trimming and tailing and create graphs for data exploration. We apply Tailer to RNA 3' end sequencing experiments from three published studies and find that it accurately and reproducibly recapitulates key findings. Thus, Tailer should be a useful and easily accessible tool to globally investigate tailing dynamics of nonpolyadenylated RNAs and conditions that perturb them.