Genomic and Epigenetic Alterations Deregulate microRNA Expression in Human Epithelial Ovarian Cancer
Zhang L, Volinia S, Bonome T, Calin GA, Greshock J, Yang N, Liu CG, Giannakakis A, Alexiou P, Hasegawa K, Johnstone CN, Megraw MS, Adams S, Lassus H, Huang J, Kaur S, Liang S, Sethupathy P, Leminen A, Simossis VA, Sandaltzopoulos R, Naomoto Y, Katsaros D, Gimotty PA, DeMichele A, Huang Q, Bützow R, Rustgi AK, Weber BL, Birrer MJ, Hatzigeorgiou AG, Croce CM, Coukos G
MicroRNAs (miRNAs) are an abundant class of small noncoding RNAs that function as negative gene regulators. miRNA deregulation is involved in the initiation and progression of human cancer; however, the underlying mechanism and its contributions to genome-wide transcriptional changes in cancer are still largely unknown. We studied miRNA deregulation in human epithelial ovarian cancer by integrative genomic approach, including miRNA microarray (n = 106), array-based comparative genomic hybridization (n = 109), cDNA microarray (n = 76), and tissue array (n = 504). miRNA expression is markedly down-regulated in malignant transformation and tumor progression. Genomic copy number loss and epigenetic silencing, respectively, may account for the down-regulation of ≈15% and at least ≈36% of miRNAs in advanced ovarian tumors and miRNA down-regulation contributes to a genome-wide transcriptional deregulation. Last, eight miRNAs located in the chromosome 14 miRNA cluster (Dlk1-Gtl2 domain) were identified as potential tumor suppressor genes. Therefore, our results suggest that miRNAs may offer new biomarkers and therapeutic targets in epithelial ovarian cancer.
Proc Natl Acad Sci U S A ,105(19) ,7004-9.
DIANA-microT web server: elucidating microRNA functions through target prediction.
Maragkakis M, Reczko M, Simossis VA, Alexiou P, Papadopoulos GL, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Vergoulis T, Koziris N, Sellis T, Tsanakas P, Hatzigeorgiou AG
Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.
Nucleic Acids Res. ,37(Web Server issue):W273-6.
DIANA-mirPath: Integrating human and mouse microRNAs in pathways.
Papadopoulos GL, Alexiou P, Maragkakis M, Reczko M, Hatzigeorgiou AG.
DIANA-mirPath is a web-based computational tool developed to identify molecular pathways potentially altered by the expression of single or multiple microRNAs. The software performs an enrichment analysis of multiple microRNA target genes comparing each set of microRNA targets to all known KEGG pathways. The combinatorial effect of co-expressed microRNAs in the modulation of a given pathway is taken into account by the simultaneous analysis of multiple microRNAs. The graphical output of the program provides an overview of the parts of the pathway modulated by microRNAs, facilitating the interpretation and presentation of the analysis results.
Bioinformatics. ,2009 Aug 1;25(15):1991-3.
Accurate microRNA target prediction correlates with protein repression levels.
Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Simossis VA, Sethupathy P, Vergoulis T, Koziris N, Sellis T, Tsanakas P, Hatzigeorgiou AG.
DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT
BMC Bioinformatics ,2009 Sep 18;10:295.
Lost in translation: an assessment and perspective for computational microRNA target identification.
Alexiou P, Maragkakis M, Papadopoulos GL, Reczko M, Hatzigeorgiou AG
MicroRNAs (miRNAs) are a class of short endogenously expressed RNA molecules that regulate gene expression by binding directly to the messenger RNA of protein coding genes. They have been found to confer a novel layer of genetic regulation in a wide range of biological processes. Computational miRNA target prediction remains one of the key means used to decipher the role of miRNAs in development and disease. Here we introduce the basic idea behind the experimental identification of miRNA targets and present some of the most widely used computational miRNA target identification programs. The review includes an assessment of the prediction quality of these programs and their combinations.
Bioinformatics , 25(23):3049-55
miRGen 2.0: a database of microRNA genomic information and regulation
Alexiou P, T. Vergoulis, M. Gleditzsch, G. Prekas, T. Dalamagas, M. Megraw, I. Grosse, T. Sellis, A.G. Hatzigeorgiou
MicroRNAs are small, non-protein coding RNA molecules known to regulate the expression of genes by binding to the 3’UTR region of mRNAs. MicroRNAs are produced from longer transcripts which can code for more than one mature miRNAs. miRGen 2.0 is a database that aims to provide comprehensive information about the position of human and mouse microRNA coding transcripts and their regulation by transcription factors, including a unique compilation of both predicted and experimentally supported data. Expression profiles of microRNAs in several tissues and cell lines, single nucleotide polymorphism locations, microRNA target prediction on protein coding genes and mapping of miRNA targets of co-regulated miRNAs on biological pathways are also integrated into the database and user interface. The miRGen database will be continuously maintained and freely available at http://www.microrna.gr/mirgen/.
Nucleic Acids Research , 38(Database issue): D137–D141.
The DIANA-mirExTra web server: from gene expression data to microRNA function.
Alexiou P, Maragkakis M, Papadopoulos GL, Simmosis VA, Zhang L, Hatzigeorgiou AG
High-throughput gene expression experiments are widely used to identify the role of genes involved in biological conditions of interest. MicroRNAs (miRNA) are regulatory molecules that have been functionally associated with several developmental programs and their deregulation with diverse diseases including cancer. Although miRNA expression levels may not be routinely measured in high-throughput experiments, a possible involvement of miRNAs in the deregulation of gene expression can be computationally predicted and quantified through analysis of overrepresented motifs in the deregulated genes 3′ untranslated region (3’UTR) sequences. Here, we introduce a user-friendly web-server, DIANA-mirExTra (www.microrna.gr/mirextra) that allows the comparison of frequencies of miRNA associated motifs between sets of genes that can lead to the identification of miRNAs responsible for the deregulation of large numbers of genes. To this end, we have investigated different approaches and measures, and have practically implemented them on experimental data. On several datasets of miRNA overexpression and repression experiments, our proposed approaches have successfully identified the deregulated miRNA. Beyond the prediction of miRNAs responsible for the deregulation of transcripts, the web-server provides extensive links to DIANA-mirPath, a functional analysis tool incorporating miRNA targets in biological pathways. Additionally, in case information about miRNA expression changes is provided, the results can be filtered to display the analysis for miRNAs of interest only.
PLoS ONE ,5(2):e9171
In vivo profiling of hypoxic gene expression in gliomas using the hypoxia marker EF5 and laser-capture microdissection.
Marotta D, Karar J, Jenkins WT, Kumanova M, Jenkins KW, Tobias JW, Baldwin D, Hatzigeorgiou A, Alexiou P, Evans SM, Alarcon R, Maity A, Koch C, Koumenis C.
Hypoxia is a key determinant of tumor aggressiveness, yet little is known regarding hypoxic global gene regulation in vivo. We used the hypoxia marker EF5 coupled with laser-capture microdissection to isolate RNA from viable hypoxic and normoxic regions of 9L experimental gliomas. Through microarray analysis, we identified several mRNAs (including the HIF targets Vegf, Glut-1, and Hsp27) with increased levels under hypoxia compared with normoxia both in vitro and in vivo. However, we also found striking differences between the global in vitro and in vivo hypoxic mRNA profiles. Intriguingly, the mRNA levels of a substantial number of immunomodulatory and DNA repair proteins including CXCL9, CD3D, and RAD51 were found to be downregulated in hypoxic areas in vivo, consistent with a protumorigenic role of hypoxia in solid tumors. Immunohistochemical staining verified increased HSP27 and decreased RAD51 protein levels in hypoxic versus normoxic tumor regions. Moreover, CD8(+) T cells, which are recruited to tumors upon stimulation by CXCL9 and CXCL10, were largely excluded from viable hypoxic areas in vivo. This is the first study to analyze the influence of hypoxia on mRNA levels in vivo and can be readily adapted to obtain a comprehensive picture of hypoxic regulation of gene expression and its influence on biological functions in solid tumors.
Cancer Res ,71(3):779-89
Online resources for microRNA analysis.
Alexiou P, Maragkakis M, Hatzigeorgiou AG
The use of online tools for bioinformatics analyses is becoming increasingly widespread. Resources specific to the field of microRNAs are available, varying in scope and usability. Online tools are the most useful for casual as well as power users since they need no installation, are hardware independent and are used mostly through graphic user interfaces and links to external sources. Here, we present an overview of useful online resources that have to do with microRNA genomics, gene finding, target prediction and functional analysis.
Journal of Nucleic Acid Investigation, 2(1)
DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association.
Maragkakis M, Vergoulis T, Alexiou P, Reczko M, Plomaritou K, Gousis M, Kourtis K, Koziris N, Dalamagas T, Hatzigeorgiou AG.
microRNAs (miRNAs) are small endogenous RNA molecules that are implicated in many biological processes through post-transcriptional regulation of gene expression. The DIANA-microT Web server provides a user-friendly interface for comprehensive computational analysis of miRNA targets in human and mouse. The server has now been extended to support predictions for two widely studied species: Drosophila melanogaster and Caenorhabditis elegans. In the updated version, the Web server enables the association of miRNAs to diseases through bibliographic analysis and provides insights for the potential involvement of miRNAs in biological processes. The nomenclature used to describe mature miRNAs along different miRBase versions has been extensively analyzed, and the naming history of each miRNA has been extracted. This enables the identification of miRNA publications regardless of possible nomenclature changes. User interaction has been further refined allowing users to save results that they wish to analyze further. A connection to the UCSC genome browser is now provided, enabling users to easily preview predicted binding sites in comparison to a wide array of genomic tracks, such as single nucleotide polymorphisms. The Web server is publicly accessible in www.microrna.gr/microT-v4.
Nucleic Acids Res. 39(Web Server issue):W145-8
TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support.
Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G, Maragkakis M, Reczko M, Gerangelos S, Koziris N, Dalamagas T, Hatzigeorgiou AG.
As the relevant literature and the number of experiments increase at a super linear rate, databases that curate and collect experimentally verified microRNA (miRNA) targets have gradually emerged. These databases attempt to provide efficient access to this wealth of experimental data, which is scattered in thousands of manuscripts. Aim of TarBase 6.0 (http://www.microrna.gr/tarbase) is to face this challenge by providing a significant increase of available miRNA targets derived from all contemporary experimental techniques (gene specific and high-throughput), while incorporating a powerful set of tools in a user-friendly interface. TarBase 6.0 hosts detailed information for each miRNA–gene interaction, ranging from miRNA- and gene-related facts to information specific to their interaction, the experimental validation methodologies and their outcomes. All database entries are enriched with function-related data, as well as general information derived from external databases such as UniProt, Ensembl and RefSeq. DIANA microT miRNA target prediction scores and the relevant prediction details are available for each interaction. TarBase 6.0 hosts the largest collection of manually curated experimentally validated miRNA–gene interactions (more than 65 000 targets), presenting a 16.5–175-fold increase over other available manually curated databases.
Nucleic Acids Res. 40(Database issue):D222-9
Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data.
Reczko M, Maragkakis M, Alexiou P, Papadopoulos GL, Hatzigeorgiou AG.
MicroRNAs (miRNAs) are a class of small regulatory genes regulating gene expression by targeting messenger RNA. Though computational methods for miRNA target prediction are the prevailing means to analyze their function, they still miss a large fraction of the targeted genes and additionally predict a large number of false positives. Here we introduce a novel algorithm called DIANA-microT-ANN which combines multiple novel target site features through an artificial neural network (ANN) and is trained using recently published high-throughput data measuring the change of protein levels after miRNA overexpression, providing positive and negative targeting examples. The features characterizing each miRNA recognition element include binding structure, conservation level, and a specific profile of structural accessibility. The ANN is trained to integrate the features of each recognition element along the 3’untranslated region into a targeting score, reproducing the relative repression fold change of the protein. Tested on two different sets the algorithm outperforms other widely used algorithms and also predicts a significant number of unique and reliable targets not predicted by the other methods. For 542 human miRNAs DIANA-microT-ANN predicts 120000 targets not provided by TargetScan 5.0. The algorithm is freely available at http://microrna.gr/microT-ANN.
Front Genet. 2:103
Mili and Miwi target RNA repertoire reveals piRNA biogenesis and function of Miwi in spermiogenesis.
Vourekas A, Zheng Q, Alexiou P, Maragkakis M, Kirino Y, Gregory BD, Mourelatos Z.
Germ cells implement elaborate mechanisms to protect their genetic material and to regulate gene expression during differentiation. Piwi proteins bind Piwi-interacting RNAs (piRNAs), small germline RNAs whose biogenesis and functions are still largely elusive. We used high-throughput sequencing after cross-linking and immunoprecipitation (HITS-CLIP) coupled with RNA-sequencing (RNA-seq) to characterize the genome-wide target RNA repertoire of Mili (Piwil2) and Miwi (Piwil1), two Piwi proteins expressed in mouse postnatal testis. We report the in vivo pathway of primary piRNA biogenesis and implicate distinct nucleolytic activities that process Piwi-bound precursor transcripts. Our studies indicate that pachytene piRNAs are the end products of RNA processing. HITS-CLIP demonstrated that Miwi binds spermiogenic mRNAs directly, without using piRNAs as guides, and independent biochemical analyses of testis mRNA ribonucleoproteins (mRNPs) established that Miwi functions in the formation of mRNP complexes that stabilize mRNAs essential for spermiogenesis.
Nat Struct Mol Biol. 19(8):773-81
Mitochondrial protein BmPAPI modulates the length of mature piRNAs.
Honda S, Kirino Y, Maragkakis M, Alexiou P, Ohtaki A, Murali R, Mourelatos Z, Kirino Y.
PIWI proteins and their associated PIWI-interacting RNAs (piRNAs) protect genome integrity by silencing transposons in animal germlines. The molecular mechanisms and components responsible for piRNA biogenesis remain elusive. PIWI proteins contain conserved symmetrical dimethylarginines (sDMAs) that are specifically targeted by TUDOR domain-containing proteins. Here we report that the sDMAs of PIWI proteins play crucial roles in PIWI localization and piRNA biogenesis in Bombyx mori-derived BmN4 cells, which harbor fully functional piRNA biogenesis machinery. Moreover, RNAi screenings for Bombyx genes encoding TUDOR domain-containing proteins identified BmPAPI, a Bombyx homolog of Drosophila PAPI, as a factor modulating the length of mature piRNAs. BmPAPI specifically recognized sDMAs and interacted with PIWI proteins at the surface of the mitochondrial outer membrane. BmPAPI depletion resulted in 3′-terminal extensions of mature piRNAs without affecting the piRNA quantity. These results reveal the BmPAPI-involved piRNA precursor processing mechanism on mitochondrial outer membrane scaffolds.
Identification of in vivo, conserved, TAF15 RNA binding sites reveals the impact of TAF15 on the neuronal transcriptome.
Ibrahim F, Maragkakis M, Alexiou P, Maronski MA, Dichter MA, Mourelatos Z.
RNA binding proteins (RBPs) have emerged as major causative agents of amyotrophic lateral sclerosis (ALS). To investigate the function of TAF15, an RBP recently implicated in ALS, we explored its target RNA repertoire in normal human brain and mouse neurons. Coupling high-throughput sequencing of immunoprecipitated and crosslinked RNA with RNA sequencing and TAF15 knockdowns, we identified conserved TAF15 RNA targets and assessed the impact of TAF15 on the neuronal transcriptome. We describe a role of TAF15 in the regulation of splicing for a set of neuronal RNAs encoding proteins with essential roles in synaptic activities. We find that TAF15 is required for a critical alternative splicing event of the zeta-1 subunit of the glutamate N-methyl-D-aspartate receptor (Grin1) that controls the activity and trafficking of NR1. Our study uncovers neuronal RNA networks impacted by TAF15 and sets the stage for investigating the role of TAF15 in ALS pathogenesis.
Cell Rep. 3(2):301-8
FUS regulates genes coding for RNA-binding proteins in neurons by binding to their highly conserved introns.
Nakaya T, Alexiou P, Maragkakis M, Chang A, Mourelatos Z.
Dominant mutations and mislocalization or aggregation of Fused in Sarcoma (FUS), an RNA-binding protein (RBP), cause neuronal degeneration in Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Lobar Degeneration (FTLD), two incurable neurological diseases. However, the function of FUS in neurons is not well understood. To uncover the impact of FUS in the neuronal transcriptome, we used high-throughput sequencing of immunoprecipitated and cross-linked RNA (HITS-CLIP) of FUS in human brains and mouse neurons differentiated from embryonic stem cells, coupled with RNA-seq and FUS knockdowns. We report conserved neuronal RNA targets and networks that are regulated by FUS. We find that FUS regulates splicing of genes coding for RBPs by binding to their highly conserved introns. Our findings have important implications for understanding the impact of FUS in neurodegenerative diseases and suggest that perturbations of FUS can impact the neuronal transcriptome via perturbations of RBP transcripts.
A MicroRNA precursor surveillance system in quality control of MicroRNA synthesis.
Liu X, Zheng Q, Vrettos N, Maragkakis M, Alexiou P, Gregory BD, Mourelatos Z.
MicroRNAs (miRNAs) are essential for regulation of gene expression. Though numerous miRNAs have been identified by high-throughput sequencing, few precursor miRNAs (pre-miRNAs) are experimentally validated. Here we report a strategy for constructing high-throughput sequencing libraries enriched for full-length pre-miRNAs. We find widespread and extensive uridylation of Argonaute (Ago)-bound pre-miRNAs, which is primarily catalyzed by two terminal uridylyltransferases: TUT7 and TUT4. Uridylation by TUT7/4 not only polishes pre-miRNA 3′ ends, but also facilitates their degradation by the exosome, preventing clogging of Ago with defective species. We show that the exosome exploits distinct substrate preferences of DIS3 and RRP6, its two catalytic subunits, to distinguish productive from defective pre-miRNAs. Furthermore, we identify a positive feedback loop formed by the exosome and TUT7/4 in triggering uridylation and degradation of Ago-bound pre-miRNAs. Our study reveals a pre-miRNA surveillance system that comprises TUT7, TUT4, and the exosome in quality control of miRNA synthesis.
Mol Cell. 55(6):868-79.
The RNA helicase MOV10L1 binds piRNA precursors to initiate piRNA processing
Vourekas A, Zheng K, Fu Q, Maragkakis M, Alexiou P, Ma J, Pillai RS, Mourelatos Z, Wang PJ.
Piwi-piRNA (Piwi-interacting RNA) ribonucleoproteins (piRNPs) enforce retrotransposon silencing, a function critical for preserving the genome integrity of germ cells. The molecular functions of most of the factors that have been genetically implicated in primary piRNA biogenesis are still elusive. Here we show that MOV10L1 exhibits 5′-to-3′ directional RNA-unwinding activity in vitro and that a point mutation that abolishes this activity causes a failure in primary piRNA biogenesis in vivo. We demonstrate that MOV10L1 selectively binds piRNA precursor transcripts and is essential for the generation of intermediate piRNA processing fragments that are subsequently loaded to Piwi proteins. Multiple analyses suggest an intimate coupling of piRNA precursor processing with elements of local secondary structures such as G quadruplexes. Our results support a model in which MOV10L1 RNA helicase activity promotes unwinding and funneling of the single-stranded piRNA precursor transcripts to the endonuclease that catalyzes the first cleavage step of piRNA processing.
Genes Dev. 2015 Mar 15;29(6):617-29.
GenOO: A Modern Perl Framework for High Throughput Sequencing analysis
Maragkakis M*, Alexiou P*, Mourelatos M.
Background: High throughput sequencing (HTS) has become one of the primary experimental tools used to extract genomic information from biological samples. Bioinformatics tools are continuously being developed for the analysis of HTS data. Beyond some well-defined core analyses, such as quality control or genomic alignment, the consistent development of custom tools and the representation of sequencing data in organized computational structures and entities remains a challenging effort for bioinformaticians.
Results: In this work, we present GenOO [jee-noo], an open-source; object-oriented (OO) Perl framework specifically developed for the design and implementation of HTS analysis tools. GenOO models biological entities such as genes and transcripts as Perl objects, and includes relevant modules, attributes and methods that allow for the manipulation of high throughput sequencing data. GenOO integrates these elements in a simple and transparent way which allows for the creation of complex analysis pipelines minimizing the overhead for the researcher. GenOO has been designed with flexibility in mind, and has an easily extendable modular structure with minimal requirements for external tools and libraries. As an example of the framework’s capabilities and usability, we present a short and simple walkthrough of a custom use case in HTS analysis.
Conclusions: GenOO is a tool of high software quality which can be efficiently used for advanced HTS analyses. It has been used to develop several custom analysis tools, leading to a number of published works. Using GenOO as a core development module can greatly benefit users, by reducing the overhead and complexity of managing HTS data and biological entities at hand.
Maragkakis M*, Alexiou P*, Nakaya T, Mourelatos Z.
Immunoprecipitation of RNA binding proteins (RBPs) after in vivo crosslinking coupled with sequencing of associated RNA footprints (HITS-CLIP, CLIP-seq), is a method of choice for the identification of RNA targets and binding sites for RBPs. Compared with RNA-seq, CLIP-seq analysis is widely diverse and depending on the RBPs that are analyzed, the approaches vary significantly necessitating the development of flexible and efficient informatics tools. In this study, we present CLIPSeqTools, a novel, highly flexible computational suite that can perform analysis from raw sequencing data with minimal user input. It contains a wide array of tools to provide an in-depth view of CLIP-seq data sets. It supports extensive customization and promotes improvization, a critical virtue, since CLIP-seq analysis is rarely well defined a priori. To highlight CLIPSeqTools capabilities, we used the suite to analyze Ago-miRNA HITS-CLIP data sets that we prepared from human brains.
RNA (2016) 22 (1), 1-9
Vourekas A*, Alexiou P*, Vrettos N, Maragkakis M, Mourelatos M
The conserved Piwi family of proteins and piwi-interacting RNAs (piRNAs) have a central role in genomic stability, which is inextricably linked to germ-cell formation, by forming Piwi ribonucleoproteins (piRNPs) that silence transposable elements . In Drosophila melanogaster and other animals, primordial germcell specification in the developing embryo is driven by maternal messenger RNAs and proteins that assemble into specialized messenger ribonucleoproteins (mRNPs) localized in the germ (pole) plasm at the posterior of the oocyte . Maternal piRNPs, especially those loaded on the Piwi protein Aubergine (Aub), are transmitted to the germ plasm to initiate transposon silencing in the offspring germ line. The transport of mRNAs to the oocyte by midoogenesis is an active, microtubule-dependent process8 ; mRNAs necessary for primordial germ-cell formation are enriched in the germ plasm at late oogenesis via a diffusion and entrapment mechanism, the molecular identity of which remains unknown. Aub is a central component of germ granule RNPs, which house mRNAs in the germ plasm, and interactions between Aub and Tudor are essential for the formation of germ granules. Here we show that Aubloaded piRNAs use partial base-pairing characteristics of Argonaute RNPs to bind mRNAs randomly in Drosophila, acting as an adhesive trap that captures mRNAs in the germ plasm, in a Tudor-dependent manner. Notably, germ plasm mRNAs in drosophilids are generally longer and more abundant than other mRNAs, suggesting that they provide more target sites for piRNAs to promote their preferential tethering in germ granules. Thus, complexes containing Tudor, Aub piRNPs and mRNAs couple piRNA inheritance with germline specification. Our findings reveal an unexpected function for piRNP complexes in mRNA trapping that may be generally relevant to the function of animal germ granules.
Vrettos N, Maragkakis M, Alexiou P, Mourelatos Z
PIWI family proteins bind to small RNAs known as PIWI-interacting RNAs (piRNAs) and play essential roles in the germline by silencing transposons and by promoting germ cell specification and function. Cell lines that endogenously express piRNAs and PIWI proteins are an invaluable complement to whole-organism studies as they facilitate molecular and biochemical investigations of piRNAs. Here we report that the widely used Kc167 cell line, derived from Drosophila melanogaster embryos, expresses piRNAs that are loaded to Aub and Piwi. Kc167 piRNAs are produced by a canonical, primary piRNA biogenesis pathway, from phased processing of precursor transcripts by the Zuc endonuclease, Armi helicase and dGasz mitochondrial scaffold protein. Kc167 piRNAs derive from cytoplasmic transcripts, notably tRNAs and mRNAs, and their abundance correlates with that of parent transcripts. The expression of Aub is robust in Kc167, that of Piwi is modest, while Ago3 is undetectable, explaining the lack of transposon-related piRNA amplification by the Aub-Ago3, ping-pong mechanism. We propose that the default state of the primary piRNA biogenesis machinery is random transcript sampling to allow generation of piRNAs from any transcript, including newly acquired retrotransposons. This state is unmasked in Kc167, likely because they do not express piRNA cluster transcripts in sufficient amounts and do not amplify transposon piRNAs. We use Kc167 to characterize an inactive isoform of Aub protein. Since most Kc167 piRNAs are genic, they can be mapped uniquely to the genome, facilitating computational analyses. Furthermore, because Kc167 is a widely used and well-characterized cell line that is easily amenable to experimental manipulations, we expect that it will serve as an excellent system to study piRNA biogenesis and piRNA-related factors.
RNA (2017) 23 (1), 108-118.