piClust: a density based piRNA clustering algorithm

Databases and computational methods for the identification of piRNA-related molecules: A survey

Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNAs (ncRNAs) that plays important roles in many biological processes and major cancer diagnosis and treatment, thus becoming a hot research topic. This study aims to provide an in-depth review of computational piRNA-related research, including databases and computational models. Herein, we perform literature analysis and use comparative evaluation methods to summarize and analyze three aspects of computational piRNA-related research: (i) computational models for piRNA-related molecular identification tasks, (ii) computational models for piRNA-disease association prediction tasks, and (iii) computational resources and evaluation metrics for these tasks. This study shows that computational piRNA-related research has significantly progressed, exhibiting promising performance in recent years, whereas they also suffer from the emerging challenges of inconsistent naming systems and the lack of data. Different from other reviews on piRNA-related identification tasks that focus on the organization of datasets and computational methods, we pay more attention to the analysis of computational models, algorithms, and performances that aim to provide valuable references for computational piRNA-related identification tasks. This study will benefit the theoretical development and practical application of piRNAs by better understanding computational models and resources to investigate the biological functions and clinical implications of piRNA.

The curious case of the disappearing piRNAs

Small non-coding RNAs are key regulators of gene expression across eukaryotes. Piwi-interacting small RNAs (piRNAs) are a specific type of small non-coding RNAs, conserved across animals, which are best known as regulators of genome stability through their ability to target transposable elements for silencing. Despite the near ubiquitous presence of piRNAs in animal lineages, there are some examples where the piRNA pathway has been lost completely, most dramatically in nematodes where loss has occurred in at least four independent lineages. In this perspective I will provide an evaluation of the presence of piRNAs across animals, explaining how it is known that piRNAs are missing from certain organisms. I will then consider possible explanations for why the piRNA pathway might have been lost and evaluate the evidence in favor of each possible mechanism. While it is still impossible to provide definitive answers, these theories will prompt further investigations into why such a highly conserved pathway can nevertheless become dispensable in certain lineages. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.

LSTM4piRNA: Efficient piRNA Detection in Large-Scale Genome Databases Using a Deep Learning-Based LSTM Network

Piwi-interacting RNAs (piRNAs) are a new class of small, non-coding RNAs, crucial in the regulation of gene expression. Recent research has revealed links between piRNAs, viral defense mechanisms, and certain human cancers. Due to their clinical potential, there is a great interest in identifying piRNAs from large genome databases through efficient computational methods. However, piRNAs lack conserved structure and sequence homology across species, which makes piRNA detection challenging. Current detection algorithms heavily rely on manually crafted features, which may overlook or improperly use certain features. Furthermore, there is a lack of suitable computational tools for analyzing large-scale databases and accurately identifying piRNAs. To address these issues, we propose LSTM4piRNA, a highly efficient deep learning-based method for predicting piRNAs in large-scale genome databases. LSTM4piRNA utilizes a compact LSTM network that can effectively analyze RNA sequences from extensive datasets to detect piRNAs. It can automatically learn the dependencies among RNA sequences, and regularization is further integrated to reduce the generalization error. Comprehensive performance evaluations based on piRNAs from the piRBase database demonstrate that LSTM4piRNA outperforms current advanced methods and is well-suited for analysis with large-scale databases.

The non-redundant functions of PIWI family proteins in gametogenesis in golden hamsters

The piRNA pathway is essential for female fertility in golden hamsters and likely humans, but not in mice. However, the role of individual PIWIs in mammalian reproduction remains poorly understood outside of mice. Here, we describe the expression profiles, subcellular localization, and knockout-associated reproductive defects for all four PIWIs in golden hamsters. In female golden hamsters, PIWIL1 and PIWIL3 are highly expressed throughout oogenesis and early embryogenesis, while knockout of PIWIL1 leads to sterility, and PIWIL3 deficiency results in subfertility with lagging zygotic development. PIWIL1 can partially compensate for TE silencing in PIWIL3 knockout females, but not vice versa. PIWIL1 and PIWIL4 are the predominant PIWIs expressed in adult and postnatal testes, respectively, while PIWIL2 is present at both stages. Loss of any PIWI expressed in testes leads to sterility and severe but distinct spermatogenesis disorders. These findings illustrate the non-redundant regulatory functions of PIWI-piRNAs in gametogenesis and early embryogenesis in golden hamsters, facilitating study of their role in human fertility.

Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for the analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = Read length - 40% Adapter length; (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

PIWI-interacting RNAs in human diseases: databases and computational models

PIWI-interacting RNAs (piRNAs) are short 21-35 nucleotide molecules that comprise the largest class of non-coding RNAs and found in a large diversity of species including yeast, worms, flies, plants and mammals including humans. The most well-understood function of piRNAs is to monitor and protect the genome from transposons particularly in germline cells. Recent data suggest that piRNAs may have additional functions in somatic cells although they are expressed there in far lower abundance. Compared with microRNAs (miRNAs), piRNAs have more limited bioinformatics resources available. This review collates 39 piRNA specific and non-specific databases and bioinformatics resources, describes and compares their utility and attributes and provides an overview of their place in the field. In addition, we review 33 computational models based upon function: piRNA prediction, transposon element and mRNA-related piRNA prediction, cluster prediction, signature detection, target prediction and disease association. Based on the collection of databases and computational models, we identify trends and potential gaps in tool development. We further analyze the breadth and depth of piRNA data available in public sources, their contribution to specific human diseases, particularly in cancer and neurodegenerative conditions, and highlight a few specific piRNAs that appear to be associated with these diseases. This briefing presents the most recent and comprehensive mapping of piRNA bioinformatics resources including databases, models and tools for disease associations to date. Such a mapping should facilitate and stimulate further research on piRNAs.

Abundant small RNAs in the reproductive tissues and eggs of the honey bee, Apis mellifera

Background

Polyandrous social insects such as the honey bee are prime candidates for parental manipulation of gene expression in offspring. Although there is good evidence for parent-of-origin effects in honey bees the epigenetic mechanisms that underlie these effects remain a mystery. Small RNA molecules such as miRNAs, piRNAs and siRNAs play important roles in transgenerational epigenetic inheritance and in the regulation of gene expression during development.

Results

Here we present the first characterisation of small RNAs present in honey bee reproductive tissues: ovaries, spermatheca, semen, fertilised and unfertilised eggs, and testes. We show that semen contains fewer piRNAs relative to eggs and ovaries, and that piRNAs and miRNAs which map antisense to genes involved in DNA regulation and developmental processes are differentially expressed between tissues. tRNA fragments are highly abundant in semen and have a similar profile to those seen in the semen of other animals. Intriguingly we also find abundant piRNAs that target the sex determination locus, suggesting that piRNAs may play a role in honey bee sex determination.

Conclusions

We conclude that small RNAs may play a fundamental role in honey bee gametogenesis and reproduction and provide a plausible mechanism for parent-of-origin effects on gene expression and reproductive physiology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08478-9.

piRNAs and PIWI Proteins as Diagnostic and Prognostic Markers of Genitourinary Cancers

piRNAs (PIWI-interacting RNAs) are small non-coding RNAs capable of regulation of transposon and gene expression. piRNAs utilise multiple mechanisms to affect gene expression, which makes them potentially more powerful regulators than microRNAs. The mechanisms by which piRNAs regulate transposon and gene expression include DNA methylation, histone modifications, and mRNA degradation. Genitourinary cancers (GC) are a large group of neoplasms that differ by their incidence, clinical course, biology, and prognosis for patients. Regardless of the GC type, metastatic disease remains a key therapeutic challenge, largely affecting patients’ survival rates. Recent studies indicate that piRNAs could serve as potentially useful biomarkers allowing for early cancer detection and therapeutic interventions at the stage of non-advanced tumour, improving patient’s outcomes. Furthermore, studies in prostate cancer show that piRNAs contribute to cancer progression by affecting key oncogenic pathways such as PI3K/AKT. Here, we discuss recent findings on biogenesis, mechanisms of action and the role of piRNAs and the associated PIWI proteins in GC. We also present tools that may be useful for studies on the functioning of piRNAs in cancers.

piRNAQuest V.2: an updated resource for searching through the piRNAome of multiple species

PIWI interacting RNAs (piRNAs) have emerged as important gene regulators in recent times. Since the release of our first version of piRNAQuest in 2014, lots of novel piRNAs have been annotated in different species other than human, mouse and rat. Such new developments in piRNA research have led us to develop an updated database piRNAQuest V.2. It consists of 92,77,689 piRNA entries for 25 new species of different phylum along with human, mouse and rat. Besides providing primary piRNA features which include their genomic location, with further information on piRNAs overlapping with repeat elements, pseudogenes and syntenic regions, etc., the novel features of this version includes (i) density based cluster prediction, (ii) piRNA expression profile across various healthy and disease systems and (iii) piRNA target prediction. The concept of density-based piRNA cluster identification is robust as it does not consider parametric distribution in its model. The piRNA expression profile for 21 disease systems including cancer have been hosted in addition to 32 tissue specific piRNA expression profile for various species. Further, the piRNA target prediction section includes both predicted and curated piRNA targets within eight disease systems and developmental stages of mouse testis. Further, users can visualize the piRNA-target duplex structure and the ping-pong signature pattern for all the ping-pong piRNA partners in different species. Overall, piRNAQuest V.2 is an updated user-friendly database which will serve as a useful resource to survey, search and retrieve information on piRNAs for multiple species. This freely accessible database is available at http://dibresources.jcbose.ac.in/zhumur/pirnaquest2.

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

PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs (sncRNAs) that perform crucial biological functions in metazoans and defend against transposable elements (TEs) in germ lines. Recently, ubiquitously expressed piRNAs were discovered in soma and germ lines using small RNA sequencing (sRNA-seq) in humans and animals, providing new insights into the diverse functions of piRNAs. However, the role of piRNAs has not yet been fully elucidated, and sRNA-seq studies continue to reveal different piRNA activities in the genome. In this review, we summarize a set of simplified processes for piRNA analysis in order to provide a useful guide for researchers to perform piRNA research suitable for their study objectives. These processes can help expand the functional research on piRNAs from previously reported sRNA-seq results in metazoans. Ubiquitously expressed piRNAs have been discovered in the soma and germ lines in Annelida, Cnidaria, Echinodermata, Crustacea, Arthropoda, and Mollusca, but they are limited to germ lines in Chordata. The roles of piRNAs in TE silencing, gene expression regulation, epigenetic regulation, embryonic development, immune response, and associated diseases will continue to be discovered via sRNA-seq.

PiRNA pathway in the cardiovascular system: a novel regulator of cardiac differentiation, repair and regeneration

Piwi-interacting RNAs (piRNAs) are a novel group of small non-coding RNA molecules with lengths of 21-35 nucleotides, first identified from the germline. PiRNAs and their associated PIWI clade Argonaute proteins constitute a key part of the piRNA pathway, with the best-known biological function to silence transposable elements in germ cells. The piRNA pathway, in fact, is not exclusive to the germline. Somatic functions of piRNAs have been recorded since their first discovery. To date, involvement of the piRNA pathway has been identified within the biological functions of genome rearrangement, epigenetic regulation, protein regulation in the germline and/or the soma transcriptionally or post-transcriptionally. Emerging evidence has shown that the piRNA pathway is essential for the normal function of the cardiovascular system and that its abnormal expression is correlated with cardiovascular dysfunction, although comprehensive roles of the piRNA pathway in the cardiovascular system and underlying mechanisms remain unclear. In this review, we discuss current findings of piRNA pathway expression in cardiac cell types and their potential functions in cardiac differentiation, repair and regeneration, thus providing new insights into cardiovascular disease development associated with the piRNA pathway.

The piRNA pathway is essential for generating functional oocytes in golden hamsters

Piwi-interacting RNAs (piRNAs) are predominantly expressed in germ cells and function in gametogenesis in various species. However, Piwi-deficient female mice are fertile and mouse oocytes express a panel of small RNAs that do not appear to be widely representative of mammals. Thus, the function of piRNAs in mammalian oogenesis remains largely unclear. Here, we generated Piwil1- and Mov10l1-deficient golden hamsters and found that all female and male mutants were sterile, with severe defects in embryogenesis and spermatogenesis, respectively. In Piwil1-deficient female hamsters, the oocytes and embryos displayed aberrant transposon accumulation and extensive transcriptomic dysregulation, and the embryos were arrested at the two-cell stage with impaired zygotic genome activation. Moreover, PIWIL1-piRNAs exert a non-redundant function in silencing endogenous retroviruses in the oocytes and embryos. Together, our findings demonstrate that piRNAs are indispensable for generating functional germ cells in golden hamsters and show the value of this model species for piRNA studies in gametogenesis, especially those related to female infertility.

The biogenesis and biological function of PIWI-interacting RNA in cancer

Small non-coding RNAs (ncRNAs) are vital regulators of biological activities, and aberrant levels of small ncRNAs are commonly found in precancerous lesions and cancer. PIWI-interacting RNAs (piRNAs) are a novel type of small ncRNA initially discovered in germ cells that have a specific length (24-31 nucleotides), bind to PIWI proteins, and show 2'-O-methyl modification at the 3'-end. Numerous studies have revealed that piRNAs can play important roles in tumorigenesis via multiple biological regulatory mechanisms, including silencing transcriptional and posttranscriptional gene processes and accelerating multiprotein interactions. piRNAs are emerging players in the malignant transformation of normal cells and participate in the regulation of cancer hallmarks. Most of the specific cancer hallmarks regulated by piRNAs are involved in sustaining proliferative signaling, resistance to cell death or apoptosis, and activation of invasion and metastasis. Additionally, piRNAs have been used as biomarkers for cancer diagnosis and prognosis and have great potential for clinical utility. However, research on the underlying mechanisms of piRNAs in cancer is limited. Here, we systematically reviewed recent advances in the biogenesis and biological functions of piRNAs and relevant bioinformatics databases with the aim of providing insights into cancer diagnosis and clinical applications. We also focused on some cancer hallmarks rarely reported to be related to piRNAs, which can promote in-depth research of piRNAs in molecular biology and facilitate their clinical translation into cancer treatment.

Computational Methods and Online Resources for Identification of piRNA-Related Molecules

piRNAs are a class of small non-coding RNA molecules, which interact with the PIWI family and have many important and diverse biological functions. The present review is aimed to provide guidelines and contribute to piRNA research. We focused on the four types of identification models on piRNA-related molecules, including piRNA, piRNA cluster, piRNA target, and disease-related piRNA. We evaluated the types of tools for the identification of piRNAs based on five aspects: datasets, features, classifiers, performance, and usability. We found the precision of 2lpiRNApred was the highest in datasets of model organisms, piRNN had a better performance of datasets of non-model organisms, and 2L-piRNA had the fastest recognition speed of all tools. In addition, we presented an overview of piRNA databases. The databases were divided into six categories: basic annotation, comprehensive annotation, isoform, cluster, target, and disease. We found that piRNA data of non-model organisms, piRNA target data, and piRNA-disease-associated data should be strengthened. Our review might assist researchers in selecting appropriate tools or datasets for their studies, reveal potential problems and shed light on future bioinformatics studies.

Identifying Cleaved and Noncleaved Targets of Small Interfering RNAs and MicroRNAs in Mammalian Cells by SpyCLIP

Recently, the US Food and Drug Administration (FDA) approved the first small interfering RNA (siRNA) drug, marking a significant milestone in the therapeutic use of RNA interference (RNAi) technology. However, off-target gene silencing by siRNA remains one of the major obstacles in siRNA therapy. Although siRNA off-target effects caused by a mechanism known for microRNA (miRNA)-mediated gene repression have been extensively discussed, whether RNAi can cause unintended cleavage through the effector protein AGO2 at sites harboring partially complementary sequences to the siRNA remains unknown. Here, we report a strategy to establish a comprehensive picture of siRNA cleaved and noncleaved off-targets by performing SpyCLIP using wild-type and catalytically inactive AGO2 mutants in parallel. Additionally, we investigated naturally occurring cleavage events mediated by endogenous miRNAs using the same strategy. Our results demonstrated that AGO2 SpyCLIP is a powerful method to identify both the cleaved and noncleaved targets of siRNAs, providing valuable information for improving siRNA design rules.

Evolution of an X-Linked miRNA Family Predominantly Expressed in Mammalian Male Germ Cells

MicroRNAs (miRNAs) are important posttranscriptional regulators of gene expression. However, comprehensive expression profiles of miRNAs during mammalian spermatogenesis are lacking. Herein, we sequenced small RNAs in highly purified mouse spermatogenic cells at different stages. We found that a family of X-linked miRNAs named spermatogenesis-related miRNAs (spermiRs) is predominantly expressed in the early meiotic phases and has a conserved testis-specific high expression pattern in different mammals. We identified one spermiR homolog in opossum; this homolog might originate from THER1, a retrotransposon that is active in marsupials but extinct in current placental mammals. SpermiRs have expanded rapidly with mammalian evolution and are diverged into two clades, spermiR-L and spermiR-R, which are likely to have been generated at least in part by tandem duplication mediated by flanking retrotransposable elements. Notably, despite having undergone highly frequent lineage-specific duplication events, the sequences encoding all spermiR family members are strictly located between two protein-coding genes, Slitrk2 and Fmr1. Moreover, spermiR-Ls and spermiR-Rs have evolved different expression patterns during spermatogenesis in different mammals. Intriguingly, the seed sequences of spermiRs, which are critical for the recognition of target genes, are highly divergent within and among mammals, whereas spermiR target genes largely overlap. When miR-741, the most highly expressed spermiR, is knocked out in cultured mouse spermatogonial stem cells (SSCs), another spermiR, miR-465a-5p, is dramatically upregulated and becomes the most abundant miRNA. Notably, miR-741^−/− SSCs grow normally, and the genome-wide expression levels of mRNAs remain unchanged. All these observations indicate functional compensation between spermiR family members and strong coevolution between spermiRs and their targets.

Elucidating the Small Regulatory RNA Repertoire of the Sea Anemone Anemonia viridis Based on Whole Genome and Small RNA Sequencing

Cnidarians harbor a variety of small regulatory RNAs that include microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs), but detailed information is limited. Here, we report the identification and expression of novel miRNAs and putative piRNAs, as well as their genomic loci, in the symbiotic sea anemone Anemonia viridis. We generated a draft assembly of the A. viridis genome with putative size of 313 Mb that appeared to be composed of about 36% repeats, including known transposable elements. We detected approximately equal fractions of DNA transposons and retrotransposons. Deep sequencing of small RNA libraries constructed from A. viridis adults sampled at a natural CO₂ gradient off Vulcano Island, Italy, identified 70 distinct miRNAs. Eight were homologous to previously reported miRNAs in cnidarians, whereas 62 appeared novel. Nine miRNAs were recognized as differentially expressed along the natural seawater pH gradient. We found a highly abundant and diverse population of piRNAs, with a substantial fraction showing ping–pong signatures. We identified nearly 22% putative piRNAs potentially targeting transposable elements within the A. viridis genome. The A. viridis genome appeared similar in size to that of other hexacorals with a very high divergence of transposable elements resembling that of the sea anemone genus Exaiptasia. The genome encodes and expresses a high number of small regulatory RNAs, which include novel miRNAs and piRNAs. Differentially expressed small RNAs along the seawater pH gradient indicated regulatory gene responses to environmental stressors.

Identification of substrates of the small RNA methyltransferase Hen1 in mouse spermatogonial stem cells and analysis of its methyl-transfer domain

Small noncoding RNAs (sncRNAs) regulate many genes in eukaryotic cells. Hua enhancer 1 (Hen1) is a 2'-O-methyltransferase that adds a methyl group to the 2'-OH of the 3'-terminal nucleotide of sncRNAs. The types and properties of sncRNAs may vary among different species, and the domain composition, structure, and function of Hen1 proteins differ accordingly. In mammals, Hen1 specifically methylates sncRNAs called P-element-induced wimpy testis-interacting RNAs (piRNAs). However, other types of sncRNAs that are methylated by Hen1 have not yet been reported, and the structures and the substrates of mammalian Hen1 remain unknown. Here, we report that mouse Hen1 (mHen1) performs 3'-end methylation of classical piRNAs, as well as those of most noncanonical piRNAs derived from rRNAs, small nuclear RNAs and tRNAs in murine spermatogonial stem cells. Moreover, we found that a distinct class of tRNA-derived sncRNAs are mHen1 substrates. We further determined the crystal structure of the putative methyltransferase domain of human Hen1 (HsHen1) in complex with its cofactor AdoMet at 2.0 Å resolution. We observed that HsHen1 has an active site similar to that of plant Hen1. We further found that the putative catalytic domain of HsHen1 alone exhibits no activity. However, an FXPP motif at its N terminus conferred full activity to this domain, and additional binding assays suggested that the FXPP motif is important for substrate binding. Our findings shed light on its methylation substrates in mouse spermatogonial stem cells and the substrate-recognition mechanism of mammalian Hen1.

Contrasting Sex-and Caste-Dependent piRNA Profiles in the Transposon Depleted Haplodiploid Honeybee Apis mellifera

Protecting genome integrity against transposable elements is achieved by intricate molecular mechanisms involving PIWI proteins, their associated small RNAs (piRNAs), and epigenetic modifiers such as DNA methylation. Eusocial bees, in particular the Western honeybee, Apis mellifera, have one of the lowest contents of transposable elements in the animal kingdom, and, unlike other animals with a functional DNA methylation system, appear not to methylate their transposons. This raises the question of whether the PIWI machinery has been retained in this species. Using comparative genomics, mass spectrometry, and expressional profiling, we present seminal evidence that the piRNA system is conserved in honeybees. We show that honey bee piRNAs contain a 2'-O-methyl modification at the 3' end, and have a bias towards a 5' terminal U, which are signature features of their biogenesis. Both piRNA repertoire and expression levels are greater in reproductive individuals than in sterile workers. Haploid males, where the detrimental effects of transposons are dominant, have the greatest piRNA levels, but surprisingly, the highest expression of transposons. These results show that even in a transposon-depleted species, the piRNA system is required to guard the vulnerable haploid genome and reproductive castes against transposon-associated genomic instability. This also suggests that dosage plays an important role in the regulation of transposons and piRNAs expression in haplo-diploid systems.

IsopiRBank: a research resource for tracking piRNA isoforms

PIWI-interacting RNAs (piRNAs) are essential for transcriptional and post-transcriptional regulation of transposons and coding genes in germline. With the development of sequencing technologies, length variations of piRNAs have been identified in several species. However, the extent to which, piRNA isoforms exist, and whether these isoforms are functionally distinct from canonical piRNAs remain uncharacterized. Through data mining from 2154 datasets of small RNA sequencing data from four species (Homo sapiens, Mus musculus, Danio rerio and Drosophila melanogaster), we have identified 8 749 139 piRNA isoforms from 175 454 canonical piRNAs, and classified them on the basis of variations on 5' or 3' end via the alignment of isoforms with canonical sequence. We thus established a database named IsopiRBank. Each isoforms has detailed annotation as follows: normalized expression data, classification, spatiotemporal expression data and genome origin. Users can also select interested isoforms for further analysis, including target prediction and Enrichment analysis. Taken together, IsopiRBank is an interactive database that aims to present the first integrated resource of piRNA isoforms, and broaden the research of piRNA biology. IsopiRBank can be accessed at http://mcg.ustc.edu.cn/bsc/isopir/index.html without any registration or log in requirement. Database URL: http://mcg.ustc.edu.cn/bsc/isopir/index.html.

Effective computational detection of piRNAs using n-gram models and support vector machine

Background

Piwi-interacting RNAs (piRNAs) are a new class of small non-coding RNAs that are known to be associated with RNA silencing. The piRNAs play an important role in protecting the genome from invasive transposons in the germline. Recent studies have shown that piRNAs are linked to the genome stability and a variety of human cancers. Due to their clinical importance, there is a pressing need for effective computational methods that can be used for computational identification of piRNAs. However, piRNAs lack conserved structural motifs and show relatively low sequence similarity across different species, which makes accurate computational prediction of piRNAs challenging.

Results

In this paper, we propose a novel method, piRNAdetect, for reliable computational prediction of piRNAs in genome sequences. In the proposed method, we first classify piRNA sequences in the training dataset that share similar sequence motifs and extract effective predictive features through the use of n-gram models (NGMs). The extracted NGM-based features are then used to construct a support vector machine that can be used for accurate prediction of novel piRNAs.

Conclusions

We demonstrate the effectiveness of the proposed piRNAdetect algorithm through extensive performance evaluation based on piRNAs in three different species – H. sapiens, R. norvegicus, and M. musculus – obtained from the piRBase and show that piRNAdetect outperforms the current state-of-the-art methods in terms of efficiency and accuracy.

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

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.

Clustering and evolutionary analysis of small RNAs identify regulatory siRNA clusters induced under drought stress in rice

Motivation

Drought tolerance is an important trait related to growth and yield in crop. Until now, drought related research has focused on coding genes. However, non-coding RNAs also respond significantly to environmental stimuli such as drought stress. Unfortunately, characterizing the role of siRNAs under drought stress is difficult since a large number of heterogenous siRNA species are expressed under drought stress and non-coding RNAs have very weak evolutionary conservation. Thus, to characterize the role of siRNAs, we need a well designed biological and bioinformatics strategy. In this paper, to characterize the function of siRNAs we developed and used a bioinformatics pipeline that includes a genomic-location based clustering technique and an evolutionary conservation tool.

Results

By comparing the wild type Nipponbare and two drought resistant rice varities, we found that 21 nt and 24 nt siRNAs are significantly expressed in the three rice plants but at different time points under a short-term (0, 1, and 6 hrs) drought treatment. siRNAs were up-regulated in the wild type at an early stage while the up-regulation was delayed in the two drought tolerant plants. Genes targeted by up-regulated siRNAs were related to oxidation reduction and proteolysis, which are well known to be associated with water deficit phenotypes. More interestingly, we found that siRNAs were located in intronic regions as clusters and were of high evolutionary conservation among monocot grass plants. In summary, we show that siRNAs are important respondents to drought stress and regulate genes related to the drought tolerance in water deficit conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0355-3) contains supplementary material, which is available to authorized users.

Germ cell and tumor associated piRNAs in the medaka and Xiphophorus melanoma models

Background

A growing number of studies report an abnormal expression of Piwi-interacting RNAs (piRNAs) and the piRNA processing enzyme Piwi in many cancers. Whether this finding is an epiphenomenon of the chaotic molecular biology of the fast dividing, neoplastically transformed cells or is functionally relevant to tumorigenesisis is difficult to discern at present. To better understand the role of piRNAs in cancer development small laboratory fish models can make a valuable contribution. However, little is known about piRNAs in somatic and neoplastic tissues of fish.

Results

To identify piRNA clusters that might be involved in melanoma pathogenesis, we use several transgenic lines of medaka, and platyfish/swordtail hybrids, which develop various types of melanoma. In these tumors Piwi, is expressed at different levels, depending on tumor type. To quantify piRNA levels, whole piRNA populations of testes and melanomas of different histotypes were sequenced. Because no reference piRNA cluster set for medaka or Xiphophorus was yet available we developed a software pipeline to detect piRNA clusters in our samples and clusters were selected that were enriched in one or more samples. We found several loci to be overexpressed or down-regulated in different melanoma subtypes as compared to hyperpigmented skin. Furthermore, cluster analysis revealed a clear distinction between testes, low-grade and high-grade malignant melanoma in medaka.

Conclusions

Our data imply that dysregulation of piRNA expression may be associated with development of melanoma. Our results also reinforce the importance of fish as a suitable model system to study the role of piRNAs in tumorigenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2697-z) contains supplementary material, which is available to authorized users.

Towards a piRNA prediction using multiple kernel fusion and support vector machine

Motivation: Piwi-interacting RNA (piRNA) is the most recently discovered and the least investigated class of Argonaute/Piwi protein-interacting small non-coding RNAs. The piRNAs are mostly known to be involved in protecting the genome from invasive transposable elements. But recent discoveries suggest their involvement in the pathophysiology of diseases, such as cancer. Their identification is therefore an important task, and computational methods are needed. However, the lack of conserved piRNA sequences and structural elements makes this identification challenging and difficult.

Results: In the present study, we propose a new modular and extensible machine learning method based on multiple kernels and a support vector machine (SVM) classifier for piRNA identification. Very few piRNA features are known to date. The use of a multiple kernels approach allows editing, adding or removing piRNA features that can be heterogeneous in a modular manner according to their relevance in a given species. Our algorithm is based on a combination of the previously identified features [sequence features (k-mer motifs and a uridine at the first position) and piRNAs cluster feature] and a new telomere/centromere vicinity feature. These features are heterogeneous, and the kernels allow to unify their representation. The proposed algorithm, named piRPred, gives promising results on Drosophila and Human data and outscores previously published piRNA identification algorithms.

Availability and implementation: piRPred is freely available to non-commercial users on our Web server EvryRNA http://EvryRNA.ibisc.univ-evry.fr

Contact:tahi@ibisc.univ-evry.fr

Prediction of piRNAs using transposon interaction and a support vector machine

Background

Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNA primarily expressed in germ cells that can silence transposons at the post-transcriptional level. Accurate prediction of piRNAs remains a significant challenge.

Results

We developed a program for piRNA annotation (Piano) using piRNA-transposon interaction information. We downloaded 13,848 Drosophila piRNAs and 261,500 Drosophila transposons. The piRNAs were aligned to transposons with a maximum of three mismatches. Then, piRNA-transposon interactions were predicted by RNAplex. Triplet elements combining structure and sequence information were extracted from piRNA-transposon matching/pairing duplexes. A support vector machine (SVM) was used on these triplet elements to classify real and pseudo piRNAs, achieving 95.3 ± 0.33% accuracy and 96.0 ± 0.5% sensitivity. The SVM classifier can be used to correctly predict human, mouse and rat piRNAs, with overall accuracy of 90.6%. We used Piano to predict piRNAs for the rice stem borer, Chilo suppressalis, an important rice insect pest that causes huge yield loss. As a result, 82,639 piRNAs were predicted in C. suppressalis.

Conclusions

Piano demonstrates excellent piRNA prediction performance by using both structure and sequence features of transposon-piRNAs interactions. Piano is freely available to the academic community at http://ento.njau.edu.cn/Piano.html.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0419-6) contains supplementary material, which is available to authorized users.

piRNAQuest: searching the piRNAome for silencers

Background

PIWI-interacting RNA (piRNA) is a novel and emerging class of small non-coding RNA (sncRNA). Ranging in length from 26-32 nucleotides, this sncRNA is a potent player in guiding the vital regulatory processes within a cellular system. Inspite of having such a wide role within cellular systems, piRNAs are not well organized and classified, so that a researcher can pool out the biologically relevant information concerning this class.

Description

Here we present piRNAQuest- a unified and comprehensive database of 41749 human, 890078 mouse and 66758 rat piRNAs obtained from NCBI and different small RNA sequence experiments. This database provides piRNA annotation based on their localization in gene, intron, intergenic, CDS, 5^/UTR, 3^/UTR and repetitive regions which has not been done so far. We have also annotated piRNA clusters and have elucidated characteristic motifs within them. We have looked for the presence of piRNAs and piRNA clusters in pseudogenes, which are known to regulate the expression of protein coding transcripts by generating small RNAs. All these will help researchers progress towards solving the unanswered queries on piRNA biogenesis and their mode of action. Further, expression profile for piRNA in different tissues and from different developmental stages has been provided. In addition, we have provided several tools like 'homology search’, 'dynamic cluster search’ and 'pattern search’. Overall, piRNAQuest will serve as a useful resource for exploring human, mouse and rat piRNAome. The database is freely accessible and available at http://bicresources.jcbose.ac.in/zhumur/pirnaquest/.

Conclusion

piRNAs play a remarkable role in stem cell self-renewal and various vital processes of developmental biology. Although researchers are mining different features on piRNAs, the exact regulatory mechanism is still fuzzy. Thus, understanding the true potential of these small regulatory molecules with respect to their origin, localization and mode of biogenesis is crucial. piRNAQuest will provide us with a better insight on piRNA origin and function which will help to explore the true potential of these sncRNAs.