Deep sequencing and proteomic analysis of the microRNA-induced silencing complex in human red blood cells
2015; Elsevier BV; Volume: 43; Issue: 5 Linguagem: Inglês
10.1016/j.exphem.2015.01.007
ISSN1873-2399
AutoresImane Azzouzi, Hansjoerg Moest, Bernd Wollscheid, Markus Schmugge, Julia J.M. Eekels, Oliver Speer,
Tópico(s)Cancer-related molecular mechanisms research
Resumo•Deep sequencing of small RNA of circulating red blood cells revealed 197 different microRNAs (miRNAs).•MicroRNA-451a was the most abundant, representing over 60% of all reads.•Proteomic analysis of Argonaute2 miRNA-induced silencing complexes identified 26 protein cofactor candidates.•Circulating red blood cells contain a complex miRNA machinery, enabling the enucleated cells to control protein translation independent of de novo nucleic information. During maturation, erythropoietic cells extrude their nuclei but retain their ability to respond to oxidant stress by tightly regulating protein translation. Several studies have reported microRNA-mediated regulation of translation during terminal stages of erythropoiesis, even after enucleation. In the present study, we performed a detailed examination of the endogenous microRNA machinery in human red blood cells using a combination of deep sequencing analysis of microRNAs and proteomic analysis of the microRNA-induced silencing complex. Among the 197 different microRNAs detected, miR-451a was the most abundant, representing more than 60% of all read sequences. In addition, miR-451a and its known target, 14-3-3ζ mRNA, were bound to the microRNA-induced silencing complex, implying their direct interaction in red blood cells. The proteomic characterization of endogenous Argonaute 2–associated microRNA-induced silencing complex revealed 26 cofactor candidates. Among these cofactors, we identified several RNA-binding proteins, as well as motor proteins and vesicular trafficking proteins. Our results demonstrate that red blood cells contain complex microRNA machinery, which might enable immature red blood cells to control protein translation independent of de novo nuclei information. During maturation, erythropoietic cells extrude their nuclei but retain their ability to respond to oxidant stress by tightly regulating protein translation. Several studies have reported microRNA-mediated regulation of translation during terminal stages of erythropoiesis, even after enucleation. In the present study, we performed a detailed examination of the endogenous microRNA machinery in human red blood cells using a combination of deep sequencing analysis of microRNAs and proteomic analysis of the microRNA-induced silencing complex. Among the 197 different microRNAs detected, miR-451a was the most abundant, representing more than 60% of all read sequences. In addition, miR-451a and its known target, 14-3-3ζ mRNA, were bound to the microRNA-induced silencing complex, implying their direct interaction in red blood cells. The proteomic characterization of endogenous Argonaute 2–associated microRNA-induced silencing complex revealed 26 cofactor candidates. Among these cofactors, we identified several RNA-binding proteins, as well as motor proteins and vesicular trafficking proteins. Our results demonstrate that red blood cells contain complex microRNA machinery, which might enable immature red blood cells to control protein translation independent of de novo nuclei information. MicroRNAs (miRNAs) are small ∼22-nucleotide noncoding RNAs that regulate gene expression by targeting mRNAs in a sequence-specific manner [1Ambros V. The functions of animal microRNAs.Nature. 2004; 431: 350-355Crossref PubMed Scopus (8739) Google Scholar, 2Bartel D.P. MicroRNAs: Genomics, biogenesis, mechanism, and function.Cell. 2004; 116: 281-297Abstract Full Text Full Text PDF PubMed Scopus (28319) Google Scholar]. MicroRNAs are processed from primary miRNAs (pri-miRNAs), which are either transcribed by polymerase II from miRNA-encoding genes or arise from spliced-out introns of mRNA-encoding genes, so-called mirtrons. Primary miRNAs are processed by the RNase III–type endonuclease Drosha to 70–120-nucleotide precursor miRNAs (pre-miRNAs). Drosha is active in complex with the dsRNA-binding protein DiGeorge syndrome critical region 8 (DGCR8). The pre-miRNAs are transported into cytoplasm by Exportin-5 and are further processed by Dicer, resulting in 19–25-nucleotide duplexes. One strand gives rise to a mature miRNA, and the other is released and degraded [3Bushati N. Cohen S.M. microRNA functions.Annu Rev Cell Dev Biol. 2007; 23: 175-205Crossref PubMed Scopus (2217) Google Scholar, 4Filipowicz W. Bhattacharyya S.N. Sonenberg N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?.Nat Rev Genet. 2008; 9: 102-114Crossref PubMed Scopus (4014) Google Scholar, 5Rana T.M. Illuminating the silence: Understanding the structure and function of small RNAs.Nat Rev Mol Cell Biol. 2007; 8: 23-36Crossref PubMed Scopus (823) Google Scholar]. The single-stranded miRNA assembles with proteins into ribonucleoprotein complexes called miRNA-induced silencing complexes (miRISCs). The key components of these complexes are Argonaute (AGO) proteins. Apart from AGO, miRISCs contain several other proteins, including helicases, mRNA-binding proteins, RNA metabolism proteins, and processing body (P-body) components, such as GW182 or RCK/p54 [6Behm-Ansmant I. Rehwinkel J. Doerks T. Stark A. Bork P. Izaurralde E. mRNA degradation by miRNAs and GW182 requires both CCR4:NOT deadenylase and DCP1:DCP2 decapping complexes.Genes Dev. 2006; 20: 1885-1898Crossref PubMed Scopus (710) Google Scholar, 7Chu C.Y. 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During erythropoiesis, multipotent hematopoietic stem cells become committed to the red cell lineage. During late erythropoiesis, the nucleus is extruded from the erythroblast, giving rise to young erythrocytes, called reticulocytes, which are released into the bloodstream. However, although lacking a nucleus, reticulocytes have been shown to be translationally active [12Skadberg O. Brun A. Sandberg S. Human reticulocytes isolated from peripheral blood: Maturation time and hemoglobin synthesis.Lab Hematol. 2003; 9: 198-206PubMed Google Scholar] and to contain around 600 transcripts, including globin transcripts [13Goh S.H. Josleyn M. Lee Y.T. et al.The human reticulocyte transcriptome.Physiol Genomics. 2007; 30: 172-178Crossref PubMed Scopus (71) Google Scholar], as well as a distinct set of miRNAs [14Azzouzi I. Moest H. Winkler J. et al.MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis.PLoS One. 2011; 6: e22838Crossref PubMed Scopus (56) Google Scholar, 15Bruchova H. Yoon D. Agarwal A.M. Mendell J. Prchal J.T. Regulated expression of microRNAs in normal and polycythemia vera erythropoiesis.Exp Hematol. 2007; 35: 1657-1667Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar, 16Chen S.Y. Wang Y. Telen M.J. Chi J.T. The genomic analysis of erythrocyte microRNA expression in sickle cell diseases.PLoS One. 2008; 3: e2360Crossref PubMed Scopus (131) Google Scholar, 17Dore L.C. Amigo J.D. Dos Santos C.O. et al.A GATA-1-regulated microRNA locus essential for erythropoiesis.PNAS. 2008; 105: 3333-3338Crossref PubMed Scopus (271) Google Scholar]. Among these, miR-451a and miR-144 have been found to be essential for red blood cell (RBC) homeostasis and differentiation [17Dore L.C. Amigo J.D. Dos Santos C.O. et al.A GATA-1-regulated microRNA locus essential for erythropoiesis.PNAS. 2008; 105: 3333-3338Crossref PubMed Scopus (271) Google Scholar, 18Pase L. Layton J.E. Kloosterman W.P. Carradice D. Waterhouse P.M. Lieschke G.J. miR-451 regulates zebrafish erythroid maturation in vivo via its target gata2.Blood. 2009; 113: 1794-1804Crossref PubMed Scopus (161) Google Scholar, 19Patrick D.M. Zhang C.C. Tao Y. et al.Defective erythroid differentiation in miR-451 mutant mice mediated by 14-3-3ζ.Genes Dev. 2010; 24: 1614-1619Crossref PubMed Scopus (138) Google Scholar, 20Rasmussen K.D. Simmini S. Abreu-Goodger C. et al.The miR-144/451 locus is required for erythroid homeostasis.J Exp Med. 2010; 207: 1351-1358Crossref PubMed Scopus (231) Google Scholar, 21Yu D. dos Santos C.O. Zhao G. et al.miR-451 protects against erythroid oxidant stress by repressing 14-3-3ζ.Genes Dev. 2010; 24: 1620-1633Crossref PubMed Scopus (170) Google Scholar]. Furthermore, miR-451a has been reported to positively regulate terminal erythroid differentiation and to protect RBCs against oxidant stress by suppressing 14-3-3ζ expression [17Dore L.C. Amigo J.D. Dos Santos C.O. et al.A GATA-1-regulated microRNA locus essential for erythropoiesis.PNAS. 2008; 105: 3333-3338Crossref PubMed Scopus (271) Google Scholar, 18Pase L. Layton J.E. Kloosterman W.P. Carradice D. Waterhouse P.M. Lieschke G.J. miR-451 regulates zebrafish erythroid maturation in vivo via its target gata2.Blood. 2009; 113: 1794-1804Crossref PubMed Scopus (161) Google Scholar, 19Patrick D.M. Zhang C.C. Tao Y. et al.Defective erythroid differentiation in miR-451 mutant mice mediated by 14-3-3ζ.Genes Dev. 2010; 24: 1614-1619Crossref PubMed Scopus (138) Google Scholar, 20Rasmussen K.D. Simmini S. Abreu-Goodger C. et al.The miR-144/451 locus is required for erythroid homeostasis.J Exp Med. 2010; 207: 1351-1358Crossref PubMed Scopus (231) Google Scholar, 21Yu D. dos Santos C.O. Zhao G. et al.miR-451 protects against erythroid oxidant stress by repressing 14-3-3ζ.Genes Dev. 2010; 24: 1620-1633Crossref PubMed Scopus (170) Google Scholar]. It has been observed that miR-320 regulates the expression of the transferrin receptor CD71 [16Chen S.Y. Wang Y. Telen M.J. Chi J.T. The genomic analysis of erythrocyte microRNA expression in sickle cell diseases.PLoS One. 2008; 3: e2360Crossref PubMed Scopus (131) Google Scholar], whereas miR-144 has been demonstrated to play an important role in the tolerance of reticulocytes to oxidant stress in sickle cell disease patients [22Sangokoya C. Telen M.J. Chi J.T. MicroRNA miR-144 modulates oxidative stress tolerance and associates with anemia severity in sickle cell disease.Blood. 2010; 20: 4338-4348Crossref Scopus (244) Google Scholar]. Recently, miR-96 was shown to directly bind and inhibit the γ-globin mRNA and therefore to regulate the expression of fetal hemoglobin in postnatal erythropoiesis [14Azzouzi I. Moest H. Winkler J. et al.MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis.PLoS One. 2011; 6: e22838Crossref PubMed Scopus (56) Google Scholar]. Extensive miRNA profiling of erythroid cells in mice and humans revealed dynamic changes in miRNA expression during erythroid differentiation [15Bruchova H. Yoon D. Agarwal A.M. Mendell J. Prchal J.T. Regulated expression of microRNAs in normal and polycythemia vera erythropoiesis.Exp Hematol. 2007; 35: 1657-1667Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar, 23Noh S.J. Miller S.H. Lee Y.T. et al.Let-7 microRNAs are developmentally regulated in circulating human erythroid cells.J Transl Med. 2009; 7: 98Crossref PubMed Scopus (43) Google Scholar]. For instance, one of the first described miRNAs in erythropoiesis is the miR-221/222 cluster, which declines during differentiation and is shown to target the kit receptor, and decrease of miR-221/22 expression correlates with increased kit expression [24Felli N. Fontana L. Pelosi E. et al.MicroRNAs 221 and 222 inhibit normal erythropoiesis and erythroleukemic cell growth via kit receptor down-modulation.Proc Natl Acad Sci U S A. 2005; 102: 18081-18086Crossref PubMed Scopus (673) Google Scholar]. On the other hand, miR-451a expression increases gradually over the course of erythropoiesis [25Masaki S. Ohtsuka R. Abe Y. Muta K. Umemura T. Expression patterns of microRNAs 155 and 451 during normal human erythropoiesis.Biochem Biophys Res Commun. 2007; 364: 509-514Crossref PubMed Scopus (148) Google Scholar, 26Zhan M. Miller C.P. Papayannopoulou T. Stamatoyannopoulos G. Songs C.Z. MicroRNA expression dynamics during murine and human erythroid differentiation.Exp Hematol. 2007; 35: 1015-1025Abstract Full Text Full Text PDF PubMed Scopus (135) Google Scholar]. However, until now, no systematic characterization of miRNAs in RBCs has been carried out by deep sequencing, to our knowledge. Deep sequencing technology has the potential to determine the absolute abundance of the different miRNAs present in RBCs. Depending on their specific abundance in time and space, miRNAs are thought to have an important role during hematopoiesis, as well as in the homeostasis of RBCs. Therefore, a detailed molecular analysis of the endogenous miRNA-mediated silencing machinery of RBCs would be expected to provide mechanistic insights into miRNA-controlled cellular responses. Here, we report our findings from deep sequencing of the miRNAs in RBCs combined with proteomic analysis of endogenous AGO2-associated miRISC. Deep sequencing of human RBC small RNAs revealed the presence of 197 different miRNAs. Among all the detected miRNAs, miR-451a was the most abundant, representing more than 60% of all read sequences. In addition, the analysis of miR-451a sequence variation confirmed previous reports on miR-451a Dicer-independent processing. Subsequent proteomic characterization of endogenous AGO2 cofactors identified the protein composition of AGO2-associated miRISC in RBCs. Among the identified cofactors, we found Heat shock protein HSP 90-alpha (HSP90A), Y-box-binding protein 1 (YBX1) and Y-box binding protein 3 (YBX3), which have previously been shown to associate with AGO2 in human cells. Furthermore, we also identified transcriptional activator protein Pur-alpha (PURA), Ras GTPase-activating protein-binding protein 1 (G3BP1) and Zinc finger CCCH-type antiviral protein 1 (ZC3HAV1) as novel AGO2 cofactors, as well as motor proteins, including myosin chains and Dynamin-2 (DNM2), and the vesicular trafficking proteins sorting nexin-9 (SNX9), vacuolar protein sorting-associated protein 37C (VPS37C) and AP-2 complex (AP2). Materials and methods are described in detail in the Supplementary materials and methods (online only, available at www.exphem.org). The institutional ethics board of the University Children's Hospital, Zurich, and of the Canton of Zurich approved the study protocol, and all subjects provided written, informed consent to participate, in accordance with the Declaration of Helsinki. Venous blood samples were collected during routine blood tests. Five to ten mL of venous blood was collected into heparin, and RBCs were purified as described previously [14Azzouzi I. Moest H. Winkler J. et al.MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis.PLoS One. 2011; 6: e22838Crossref PubMed Scopus (56) Google Scholar]. Total RNA samples were prepared from RBCs using the mirVana microRNA isolation kit (Ambion, Rotkreuz, Switzerland) following the manufacturer's protocol. A small RNA cDNA library was constructed using a protocol adapted from Hafner et al. [27Hafner M. Landgraf P. Ludwig J. et al.Identification of microRNAs and other small regulatory RNAs using cDNA library sequencing.Methods. 2008; 44: 3-12Crossref PubMed Scopus (370) Google Scholar], (for details, see Supplementary materials and methods, online only, available at www.exphem.org) Amplicons were sequenced using a 454 Genome Sequencer FLX system (Roche, Rotkreuz, Switzerland) according to the manufacturer's instructions [28Margulies M. Egholm M. Altman W.E. et al.Genome sequencing in microfabricated high-density picolitre reactors.Nature. 2005; 437: 376-380Crossref PubMed Scopus (5828) Google Scholar]. The sequence data have been deposited in Gene Expression Omnibus (GEO; GSE27250; www.ncbi.nlm.nih.gov/geo). Analysis of reads is described in detail in the Supplementary materials and methods (online only, available at www.exphem.org). We performed AGO2 immunoprecipitation (IP) according to Galgano et al. and Rüdel et al. [29Galgano A. Forrer M. Jaskiewicz L. Kanitz A. Zavolan M. Gerber A.P. Comparative analysis of mRNA targets for human PUF-family proteins suggests extensive interaction with the miRNA regulatory system.PLoS One. 2008; 3: e3164Crossref PubMed Scopus (199) Google Scholar, 30Rüdel S. Flatley A. Weinmann L. Kremmer E. Meister G. A multifunctional human Argonaute2-specific monoclonal antibody.RNA. 2008; 14: 1244-1253Crossref PubMed Scopus (112) Google Scholar] as described previously [14Azzouzi I. Moest H. Winkler J. et al.MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis.PLoS One. 2011; 6: e22838Crossref PubMed Scopus (56) Google Scholar], with further adaptations as described in the Supplementary materials and methods (online only, available at www.exphem.org). For the miRNA analysis, 25 ng of RNA isolated from IP samples was reverse transcribed and quantified by real-time polymerase chain reaction (qPCR) using the TaqMan MicroRNA Cells-to-CT Kit and specific primers (Applied Biosystems, Rotkreuz, Switzerland) according to the manufacturer's instructions. Sample preparation for liquid chromatography–mass spectrometry/mass spectrometry (LC-MS/MS) and the methods used for reversed-phase high-performance liquid chromatography and mass spectrometry are described in detail in the supplementary material. Heparinized blood samples were obtained from eight children and one adult during routine follow-up controls (median age 12 years; six females, three males). Blood samples were depleted of platelets by low-speed centrifugation and were leukodepleted by density gradient centrifugation followed by filtration, as previously described [14Azzouzi I. Moest H. Winkler J. et al.MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis.PLoS One. 2011; 6: e22838Crossref PubMed Scopus (56) Google Scholar]. Depletion of platelets and leukocytes was confirmed by flow cytometry; all samples contained less than 0.001% leukocytes and less than 0.1% platelets [14Azzouzi I. Moest H. Winkler J. et al.MicroRNA-96 directly inhibits gamma-globin expression in human erythropoiesis.PLoS One. 2011; 6: e22838Crossref PubMed Scopus (56) Google Scholar]. Purified RBCs were analyzed and sorted by flow cytometry for the expression of CD71 to compare the content of reticulocytes (CD71+) and mature erythrocytes (CD71-); both cell types were present in the samples (Supplementary Figure E1 (online only, available at www.exphem.org) [10Landthaler M. Gaidatzis D. Rothballer A. et al.Molecular characterization of human Argonaute-containing ribonucleoprotein complexes and their bound target mRNAs.RNA. 2008; 14: 2580-2596Crossref PubMed Scopus (266) Google Scholar, 13Goh S.H. Josleyn M. Lee Y.T. et al.The human reticulocyte transcriptome.Physiol Genomics. 2007; 30: 172-178Crossref PubMed Scopus (71) Google Scholar]. Reticulocytes, but not erythrocytes, contained ribosomal RNA, as was described before [10Landthaler M. Gaidatzis D. Rothballer A. et al.Molecular characterization of human Argonaute-containing ribonucleoprotein complexes and their bound target mRNAs.RNA. 2008; 14: 2580-2596Crossref PubMed Scopus (266) Google Scholar]. Moreover, reticulocytes expressed 55 times more α-globin, 39 times more β-globin, 77 times more δ-globin, and 96 times more γ-globin mRNA compared with erythrocytes, confirming other reports that mainly reticulocytes have the capacity to synthesize hemoglobin [12Skadberg O. Brun A. Sandberg S. Human reticulocytes isolated from peripheral blood: Maturation time and hemoglobin synthesis.Lab Hematol. 2003; 9: 198-206PubMed Google Scholar, 31Bard H. The postnatal decline of hemoglobin F synthesis in normal full-term infants.J Clin Invest. 1975; 55: 395-398Crossref PubMed Scopus (73) Google Scholar]. Finally, after comparing 95 miRNAs, we found that the number of different miRNA species was nearly double in reticulocytes, and the commonly expressed miRNAs were on average 8.1 ± 2.6 times (mean relative quantification ± SEM) more abundant in reticulocytes than in erythrocytes (Supplementary Figure E2 (online only, available at www.exphem.org), confirming a previous report [10Landthaler M. Gaidatzis D. Rothballer A. et al.Molecular characterization of human Argonaute-containing ribonucleoprotein complexes and their bound target mRNAs.RNA. 2008; 14: 2580-2596Crossref PubMed Scopus (266) Google Scholar]. These results suggest that mainly reticulocytes possess the essential components for active translation and posttranscriptional regulation by miRNAs. Therefore, we decided to perform all subsequent experiments in circulating RBCs containing both reticulocytes and mature erythrocytes. The experiments performed in our study are represented graphically in Figure 1. The alignment of the reads of all six libraries to miRBase 20 [32Kozomara A. Griffiths-Jones S. miRBase: Annotating high confidence microRNAs using deep sequencing data.Nucleic Acids Res. 2014; 42: D68-D73Crossref PubMed Scopus (3632) Google Scholar] identified 197 annotated miRNAs (Supplementary Table E1, online only, available at www.exphem.org). Analysis of the average number of reads for each miRNA showed that miR-451a was represented, on average, by more than 50,000 reads per library (Fig. 2A) and was identified to be the most abundant miRNA in circulating RBCs, with 60% of the total number of reads (Fig. 2B). The 20 most abundant miRNAs detected in the circulating RBC miRNAome are listed in Table 1, and all detected miRNAs are indexed in Supplementary Table E1 (online only, available at www.exphem.org). We observed that miR-451a and miR-16-5p were among the five most abundant miRNAs in circulating RBCs, based on the results of deep sequencing and qPCR. Since the identification of putative targets may provide insights into the biological role of the most abundant miRNAs in circulating RBCs, we used TargetScan 6.2 (www.targetscan.org) [33Grimson A. Farh K.K. Johnston W.K. Garrett-Engele P. Lim L.P. Bartel D.P. MicroRNA Targeting specificity in mammals: Determinants beyond seed pairing genome research.Mol Cell. 2009; 19: 92-105Google Scholar, 34Lewis B.P. Burge C.B. Bartel D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (9572) Google Scholar] to perform a target prediction. Putative targets of the 20 most abundant RBC miRNAs are shown in Table 1. A gene ontology clustering of miRNA targets showed a significant overrepresentation in protein modification processes (GO:0006464) and posttranscriptional regulation of gene expression (GO:0010608). In addition, we did not detect reads corresponding to unknown miRNA sequences.Table 1The 20 most abundant miRNAs detected in the circulating RBC miRNAomemiRNARank seqAverage readsRank qPCRPredicted targetshsa-miR-451a1517134OSR1 MEX3C SAMD4B CUX2 ZNF644 TB1D9B ST8SIA4 CAV1 LETM2 DCAF5hsa-miR-16-5p2136841ZFHX4 SYNJ1 SLC9A6 IPO7 CDCA4 NUP50 PAPPA LUZP1 SLC13A3 UNC80hsa-miR-15a-5p3191230ZFHX4 SYNJ1 CDCA4 NUP50 PAPPA LUZP1 SLC13A3 UNC80 MTMR3 PTPN4hsa-miR-20a-5p414295KATNAL1 ARID4B PKD2 SLC40A1 PDCD1LG2 ZNF800 PTPN4 ZNFX1 FBXL5 EPHA4hsa-miR-15b-5p5129712ZFHX4 SYNJ1 CDCA4 NUP50 PAPPA LU2P1 SLC13A3 UNC80 MTMR3 PTPN4hsa-miR-486-5p612153BTA1 ABHD17B SNRPD1 ARID4B DCC LMTK2 ADAMTSL1 PYCR2 TOB1 CADM1hsa-let-7a-5p7118041SMARAD1 FAM178A LIN28B GATM LRIG3 GNPTAB BZW1 ZNF322 ADAMTS8 C8ORF58hsa-let-7f-5p890051SMARCAD1 FAM178 LIN28B GATM GNPTAB GATM LRIG3 ADRB2 BZW1 ADAMTS8hsa-let-7i-5p9835152SMARCAD1 LIN28B FAM178 GATM GNPTAB LRIG3 BZW1 ADRB2 ADAMTS8 PDP2hsa-miR-92a-3p1061916SYNJ1 DNAJB9 EFR3A SLC12A5 USP28 FBXW7 CD69 APPL1 MOAP1 MAP2K4hsa-miR-93-5p1161517PDCD1LG2 ZNFX1 FBXL5 EPHA4 ZNF800 PKD2 SLC40A1 MAP3K2 EZH1 SACShsa-miR-26a-5p1259628SLC2A13 SLC7A11 FAM98A ZNF608 NAP1L5 PITPNC1 EPB41L3 RNF6 CILP NAB1hsa-miR-185-5p1359237SIX2 SLC16A2 SMG7 TSPAN18 KIAA1467 SF1 PCDHAC2 SGMS1 SOX13 PM20D1hsa-miR-191-5p1450615TAF5 NEURL4 B4GALT6 MAP3K12 CBFA2T3 TJP1 TMOD2 CEBPB YBX3 CASKhsa-miR-25-3p1540127DNAJB9 CD69 SYNJ1 FBXW7 SLC12A5 EFR3A MAP2K4 USP28 KIAA1109 KIAA1432hsa-miR-374a-5p1637438SLIT3 NHLRC2 RSF1 CEBPB PARP8 HIBADH ZSWIM6 UBE3A EN1 CSGALNACT2hsa-miR-22-3p1735131PDSS1 NET1 YARS IKZF4 CPEB1 COA7 CCDC47 TRUB1 FAM49B EMILIN3hsa-miR-363-3p1832066DNAJB9 SLC12A5 FBXW7 CD69 USP28 EFR3A SYNJ1 FNIP1 WASL MAP2K4hsa-let-7b-5p193129SMARCAD1 LIN28B FAM178A LRIG3 GNPTAB TMPRSS2 GATM DNA2 C8ORF58 BZW1hsa-miR-106b-5p2030222PTPN4 ARID4B EPHA4 PKD2 PDCD1LG2 SLC40A1 FBXL5 ZNF800 ADARB1 ZNFX1DS = deep sequencing. Open table in a new tab DS = deep sequencing. Among the 197 miRNAs identified by deep sequencing, only 19 coexpressed both -3p and 5p strands, with a relative ratio of 5p/3p sequence reads ranging from 0.03 to 707.36 (Table 2). For all the remaining miRNAs, only one strand was detected. None of the miRNAs were found to have equivalent read counts generated from each arm of the pre-miRNA.Table 2miRNAs identified by deep sequencing to coexpress both -3p and 5p strandsmiRNA3p (reads)5p (reads)Ratio 5p/3phsa-miR-29c24970.03hsa-miR-142401140.03hsa-miR-1261682660.04hsa-miR-1441104880.08hsa-miR-140243430.18hsa-miR-34229110.38hsa-miR-4231412601.84hsa-miR-151a1192582.17hsa-miR-424651432.20hsa-miR-500a11302.73hsa-miR-5057213.00hsa-miR-5328526.50hsa-miR-30e3233210.38hsa-miR-324714220.29hsa-miR-106b55181132.93hsa-miR-18a43177841.35hsa-let-7d23115950.39hsa-miR-374a112242203.82hsa-miR-15b117781707.36 Open table in a new tab Although miRNA genes are distributed throughout the genome, several are organized into clusters [1Ambros V. The functions of animal microRNAs.Nature. 2004; 431: 350-355Crossref PubMed Scopus (8739) Google Scholar]. Clustered miRNAs are thought to be transcribed into a single primary transcript and cleaved into individual pre-miRNAs by the Drosha enzyme [2Bartel D.P. MicroRNAs: Genomics, biogenesis, mechanism, and function.Cell. 2004; 116: 281-297Abstract Full Text Full Text PDF PubMed Scopus (28319) Google Scholar]. However, we observed inconsistent expression of miR-451a and miR-144-3p (Fig. 3). On average, miR-451a was 456 ± 114 times more abundant than miR-144-3p. In addition, no sequence was detected from the opposite strand from miR-451a, whereas a total of 88 miR-144-5p sequence reads was detected in all six libraries. Analysis of the miR-451a sequence revealed variations in length and in sequence. Specifically, 11 different length variations were detected, revealing two major forms: the 22-nucleotide sequence as annotated in miRBase 20 [32Kozomara A. Griffiths-Jones S. miRBase: Annotating high confidence microRNAs using deep sequencing data.Nucleic Acids Res. 2014; 42: D68-D73Crossref PubMed Scopus (3632) Google Scholar] and an additional 21-nucleotide sequence (Fig. 4). Additional variability at the 5′ and 3′ ends was observed, as were six different nucleotide exchanges throughout the sequence (Table 3). These variations could be classified into two groups: C-to-U nucleotide exchange and 3′ A addition. No C-to-U nucleotide exchange was observed in miR-16-5p, the second most abundant miRNA in reticulocytes. However, statistical analysis of the substitution rates in miR-451a reads revealed no significant difference from the rate of experimental error for all 6 detected errors (p = 1) [35de Hoon M.J. Taft R.J. Hashimoto T. et al.Cross-mapping and the identification of editing sites in mature microRNAs in high-throughput sequencing libraries.Genome Res. 2010; 20: 257-264Crossref PubMed Scopus (105) Google Scholar].Table 3Sequence variation detected in miR-451a reads in all six librariesLibrary 1Library 2Library 3Library 4Library 5Library 6MFE (kcal/mol)AAACCGTTACCATTACTGAGTT75,82765,02932,88169,18031,08436,275−18.2AAACCGTTACCATTATTGAGTT426366156398191200−21.2AAACCGTTACCATTACTGAGTTA262198137384167338−19.8AAACCGTTACTATTACTGAGTT182139561275357−18.1AAACCGTTATCATTACTGAGTT158142591263160−22.1AAACTGTTACCATTACTGAGTT125106721435160−20.0AAATCGTTACCATTACTGAGTT645123752834−17.5Nucleotide variations are indicated as bold letters.MFE = Hybridization minimum free energy between miR-451a and 14-3-3ζ 3′ untranslated region calculated with RNA hybrid 52Rehmsmeier M. Steffen P. Höchsmann M. Giegerich R. Fast and effective prediction of microRNA/target duplexes.RNA. 2004; 10: 1507-1517Crossref PubMed Scopus (1751) Google Scholar. Open table in a new tab Nucleotide variations are indicated as bold letters. MFE = Hybridization minimum free energy between miR-451a and 14-3-3ζ 3′ untranslated region calculated with RNA hybrid 52Rehmsmeier M. Steffen P. Höchsmann M. Giegerich R. Fast and effective prediction of microRNA/target duplexes.RNA. 2004; 10: 1507-1517Crossref PubMed Scopus (1751) Google Scholar. To determine whether miR-451a has a function in reticulocytes, we immunoprecipitated miRISC from reticulocytes and investigated miRNA enrichment by qPCR. Overall, 83% of miRNAs identified by deep sequencing, including miR-451a, were enriched more than one hundredfold within the AGO2-containing miRISC, with the highly abundant miRNA miR-16-5p exhibiting a fold enrichment of 180 (Fig. 5A). MicroRNAs that were not detected by deep sequencing (miR-518, miR-136, and miR-1) were also not enriched in
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