piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER

Abstract

With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction.

A low-bias and sensitive small RNA library preparation method using randomized splint ligation

“…As we demonstrated in this study, we were able to identify a higher diversity of piRNA than any other method. The piRNA we identified showed the characteristic clustering patterns and 5′ uridine bias related to their biogenesis and feed-forward amplification mechanism ( 31 , 44 ).…”

“…Reads were then subsampled to a total of 16.5 million reads per method using BBtools ( https://sourceforge.net/projects/bbmap/ ). These datasets were further analyzed using the PILFER pipeline to characterize the piRNA ( 31 ). Briefly, reads were mapped to the human genome (build hg19) and piRNAbank ( 32 ) using bowtie.…”

RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

“…Relevant examples include: ArrayExpressHTS ( https://www.bioconductor.org/packages/release/bioc/html/ArrayExpressHTS.html ), BioJupies [ 5 ], BioWardrobe [ 6 ], DEWE [ 7 ], easyRNASeq [ 8 ], ExpressionPlot [ 9 ], FX [ 10 ], GENE-counter [ 11 ], GeneProf [ 12 ], Grape RNA-Seq [ 13 ], MAP-RSeq [ 14 ], NGScloud [ 15 , 16 ], RAP [ 17 ], RobiNA [ 18 ], RSEQREP [ 19 ], RSEQtools [ 20 ], RseqFlow [ 21 ], S-MART [ 22 ], TCW [ 23 ], TRAPLINE [ 24 ] and wapRNA [ 25 ]. In addition, other pipelines have been developed for the analysis of different ncRNA classes: DSAP [ 26 ], miRanalyzer [ 27 ], miRExpress [ 28 ], miRNAkey [ 29 ], iMir [ 30 ], CAP-miRSeq [ 31 ], mirTools 2.0 [ 32 ], sRNAtoolbox [ 33 ], miRDeep 2 [ 34 ], and MapMi [ 35 ] for microRNAs (miRNAs); piPipes [ 36 ], PILFER [ 37 ], piRNAPredictor [ 38 ] and PIANO [ 39 ] for piwi-associated RNAs (piRNAs); and UClncR [ 40 ] for long non-coding RNAs (lncRNAs).…”

A Review of Discovery Profiling of PIWI-Interacting RNAs and Their Diverse Functions in Metazoans

“…For example, Pinao [ 56 ], a genetic algorithm-based weighted ensemble (GA-WE) [ 57 ], and accurate piRNA prediction [ 58 ] have been used for transposon-related piRNA prediction, and two-layer integrated programs for identifying piRNAs (2L-piRNA) [ 59 ], such as 2L-piRNAPred [ 60 ], 2lpiRNApred [ 61 ], and 2L-piRNADNN [ 62 ], have been developed for mRNA-related piRNA prediction, while piRNAPredictor [ 2 ], PiRPred [ 3 ], piRNAdetect [ 63 ], IpiRId [ 64 ], piRNN [ 65 ], and piRNApred [ 66 ] have been employed for total piRNA prediction. miRanda [ 17 ], pirnaPre [ 67 ], and pirScan [ 18 ] have been used for piRNA target prediction, and three algorithms have been proposed for predicting piRNA clusters from sRNA-seq data: proTRAC [ 54 ], piClust [ 68 ], and PILFER [ 69 ]. In addition, multiple integrated platforms, such as sRNAtools [ 70 ] and Workflow for piRNAs and Beyond (WIND) [ 71 ], have been recently developed for piRNA annotation and downstream analysis from raw data to plots and statistics by sRNA-seq.…”