The vertebrate-conserved RNA-binding protein DND1 is required for the survival of primordial germ cells (PGCs), as well as the suppression of germ cell tumours in mice1,2,3,4,5. Here we show that in mice DND1 binds a UU(A/U) trinucleotide motif predominantly in the 3′ untranslated regions of mRNA, and destabilizes target mRNAs through direct recruitment of the CCR4–NOT deadenylase complex. Transcriptomic analysis reveals that the extent of suppression is dependent on the number of DND1-binding sites. This DND1-dependent mRNA destabilization is required for the survival of mouse PGCs and spermatogonial stem cells by suppressing apoptosis. The spectrum of target RNAs includes positive regulators of apoptosis and inflammation, and modulators of signalling pathways that regulate stem-cell pluripotency, including the TGFβ superfamily, all of which are aberrantly elevated in DND1-deficient PGCs. We propose that the induction of the post-transcriptional suppressor DND1 synergizes with concurrent transcriptional changes to ensure precise developmental transitions during cellular differentiation and maintenance of the germ line.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Sequence Read Archive
Youngren, K. K. et al. The Ter mutation in the dead end gene causes germ cell loss and testicular germ cell tumours. Nature 435, 360–364 (2005)
Northrup, E. et al. The ter mutation in the rat Dnd1 gene initiates gonadal teratomas and infertility in both genders. PLoS One 7, e38001 (2012)
Cook, M. S., Coveney, D., Batchvarov, I., Nadeau, J. H. & Capel, B. BAX-mediated cell death affects early germ cell loss and incidence of testicular teratomas in Dnd1Ter/Ter mice. Dev. Biol. 328, 377–383 (2009)
Noguchi, T. & Noguchi, M . A recessive mutation (ter) causing germ cell deficiency and a high incidence of congenital testicular teratomas in 129/Sv-ter mice. J. Natl. Cancer Inst. 75, 385–392 (1985)
Sakurai, T., Iguchi, T., Moriwaki, K. & Noguchi, M. The ter mutation first causes primordial germ cell deficiency in ter/ter mouse embryos at 8 days of gestation. Dev. Growth Differ. 37, 293–302 (1995)
Saitou, M. & Yamaji, M. Primordial germ cells in mice. Cold Spring Harb. Perspect. Biol. 4, a008375 (2012)
Yabuta, Y., Kurimoto, K., Ohinata, Y., Seki, Y. & Saitou, M. Gene expression dynamics during germline specification in mice identified by quantitative single-cell gene expression profiling. Biol. Reprod. 75, 705–716 (2006)
Kedde, M. et al. RNA-binding protein Dnd1 inhibits microRNA access to target mRNA. Cell 131, 1273–1286 (2007)
Suzuki, A. et al. Dead end1 is an essential partner of NANOS2 for selective binding of target RNAs in male germ cell development. EMBO Rep. 17, 37–46 (2016)
Kanatsu-Shinohara, M. et al. Long-term proliferation in culture and germline transmission of mouse male germline stem cells. Biol. Reprod. 69, 612–616 (2003)
Hafner, M. et al. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 141, 129–141 (2010)
Corcoran, D. L. et al. PARalyzer: definition of RNA binding sites from PAR-CLIP short-read sequence data. Genome Biol. 12, R79 (2011)
Barreau, C., Paillard, L. & Osborne, H. B. AU-rich elements and associated factors: are there unifying principles? Nucleic Acids Res. 33, 7138–7150 (2006)
Spiller, C. M. et al. Endogenous Nodal signaling regulates germ cell potency during mammalian testis development. Development 139, 4123–4132 (2012)
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015)
van der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008)
Kurimoto, K. et al. Quantitative dynamics of chromatin remodeling during germ cell specification from mouse embryonic stem cells. Cell Stem Cell 16, 517–532 (2015)
Hayashi, K., Ohta, H., Kurimoto, K., Aramaki, S. & Saitou, M. Reconstitution of the mouse germ cell specification pathway in culture by pluripotent stem cells. Cell 146, 519–532 (2011)
Kurimoto, K. et al. Complex genome-wide transcription dynamics orchestrated by Blimp1 for the specification of the germ cell lineage in mice. Genes Dev. 22, 1617–1635 (2008)
Ebert, M. S. & Sharp, P. A. Roles for microRNAs in conferring robustness to biological processes. Cell 149, 515–524 (2012)
Slanchev, K. et al. Control of dead end localization and activity–implications for the function of the protein in antagonizing miRNA function. Mech. Dev. 126, 270–277 (2009)
Roers, A., Hiller, B. & Hornung, V. Recognition of endogenous nucleic acids by the innate immune system. Immunity 44, 739–754 (2016)
Korkola, J. E. et al. Down-regulation of stem cell genes, including those in a 200-kb gene cluster at 12p13.31, is associated with in vivo differentiation of human male germ cell tumors. Cancer Res. 66, 820–827 (2006)
Gerstberger, S., Hafner, M. & Tuschl, T. A census of human RNA-binding proteins. Nat. Rev. Genet. 15, 829–845 (2014)
Zhang, P. et al. MIWI and piRNA-mediated cleavage of messenger RNAs in mouse testes. Cell Res. 25, 193–207 (2015)
Reuter, M. et al. Miwi catalysis is required for piRNA amplification-independent LINE1 transposon silencing. Nature 480, 264–267 (2011)
Collier, B., Gorgoni, B., Loveridge, C., Cooke, H. J. & Gray, N. K. The DAZL family proteins are PABP-binding proteins that regulate translation in germ cells. EMBO J. 24, 2656–2666 (2005)
Suzuki, A ., Igarashi, K ., Aisaki, K ., Kanno, J & Saga, Y. NANOS2 interacts with the CCR4-NOT deadenylation complex and leads to suppression of specific RNAs. Proc. Natl Acad. Sci. USA 107, 3594–3599 (2010)
Bhandari, D., Raisch, T., Weichenrieder, O., Jonas, S. & Izaurralde, E. Structural basis for the Nanos-mediated recruitment of the CCR4-NOT complex and translational repression. Genes Dev. 28, 888–901 (2014)
Li, C. & Hung Wong, W. Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol. 2 RESEARCH0032 (2001)
Spitzer, J., Landthaler, M. & Tuschl, T. Rapid creation of stable mammalian cell lines for regulated expression of proteins using the Gateway® recombination cloning technology and Flp-In T-REx® lines. Methods Enzymol. 529, 99–124 (2013)
Al-Zoghaibi, F. et al. Bioinformatics and experimental derivation of an efficient hybrid 3′ untranslated region and use in expression active linear DNA with minimum poly(A) region. Gene 391, 130–139 (2007)
Wiznerowicz, M. & Trono, D. Conditional suppression of cellular genes: lentivirus vector-mediated drug-inducible RNA interference. J. Virol. 77, 8957–8961 (2003)
Moffat, J. et al. A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell 124, 1283–1298 (2006)
Sarbassov, D. D., Guertin, D. A., Ali, S. M. & Sabatini, D. M. Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex. Science 307, 1098–1101 (2005)
Fabian, M. R. et al. Structural basis for the recruitment of the human CCR4-NOT deadenylase complex by tristetraprolin. Nat. Struct. Mol. Biol. 20, 735–739 (2013)
Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protocols 4, 44–57 (2009)
Huang, W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1–13 (2009)
Bailey, T. L. DREME: motif discovery in transcription factor ChIP-seq data. Bioinformatics 27, 1653–1659 (2011)
Yamaji, M. et al. PRDM14 ensures naive pluripotency through dual regulation of signaling and epigenetic pathways in mouse embryonic stem cells. Cell Stem Cell 12, 368–382 (2013)
Ran, F. A. et al. Genome engineering using the CRISPR-Cas9 system. Nat. Protocols 8, 2281–2308 (2013)
Chen, X. et al. Dual sgRNA-directed gene knockout using CRISPR/Cas9 technology in Caenorhabditis elegans. Sci. Rep. 4, 7581 (2014)
Bastos, H. et al. Flow cytometric characterization of viable meiotic and postmeiotic cells by Hoechst 33342 in mouse spermatogenesis. Cytometry A 65, 40–49 (2005)
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015)
Rouya, C. et al. Human DDX6 effects miRNA-mediated gene silencing via direct binding to CNOT1. RNA 20, 1398–1409 (2014)
Jishage, M. et al. Transcriptional regulation by Pol II(G) involving mediator and competitive interactions of Gdown1 and TFIIF with Pol II. Mol. Cell 45, 51–63 (2012)
Goujon, M. et al. A new bioinformatics analysis tools framework at EMBL-EBI. Nucleic Acids Res. 38, W695–W699 (2010)
McWilliam, H. et al. Analysis tool web services from the EMBL-EBI. Nucleic Acids Res. 41, W597–W600 (2013)
Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011)
Letunic, I., Doerks, T. & Bork, P. SMART: recent updates, new developments and status in 2015. Nucleic Acids Res. 43, D257–D260 (2015)
Petersen, B., Petersen, T. N., Andersen, P., Nielsen, M. & Lundegaard, C. A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Struct. Biol. 9, 51 (2009)
Handa, N. et al. Structural basis for recognition of the tra mRNA precursor by the Sex-lethal protein. Nature 398, 579–585 (1999)
Wang, X. & Tanaka Hall, T. M. Structural basis for recognition of AU-rich element RNA by the HuD protein. Nat. Struct. Biol. 8, 141–145 (2001)
Kuwasako, K. et al. Solution structure of the second RNA recognition motif (RRM) domain of murine T cell intracellular antigen-1 (TIA-1) and its RNA recognition mode. Biochemistry 47, 6437–6450 (2008)
Mukherjee, N. et al. Integrative regulatory mapping indicates that the RNA-binding protein HuR couples pre-mRNA processing and mRNA stability. Mol. Cell 43, 327–339 (2011)
Nakaki, F. et al. Induction of mouse germ-cell fate by transcription factors in vitro. Nature 501, 222–226 (2013)
The authors acknowledge expert support by the members of the Rockefeller University resource centers (C. Zhao, genomics; H. Molina, proteomics; S. Mazel, flow cytometry; A. North, bio-imaging; R. Norinsky, chimaera assay) and of the NIAMS Genomics Core (G. Gutierrez-Cruz and S. Dell'Orso). We also thank M. Morita (McGill University, Montréal, Canada) for critical discussions on biochemical analysis, K. Hayashi (Kyusyu University, Japan) and Y. Saito (Rockefeller University) for technical guidance regarding PGCLC induction, and N. Mukherjee (Max-Delbrück Centrum for Molecular Medicine, Berlin, Germany) for bioinformatic tools, E. Macosko, M. Goldman, and S. McCarroll for advice to establish DropSeq, and S. Yamada and S. Keeney (Memorial Sloan Kettering Cancer Center, New York) for technical guidance regarding spermatogenic cell sorting. The GST-CNOT constructs were provided by N. Sonenberg (McGill University, Montréal, Canada). pCMV-PP7 and β-globin-4×PP7-hairpin reporter plasmid were provided by D. R. Larson and M. Palangat (National Cancer Institute/NIH) and J. R. Hogg (National Heart, Lung, and Blood Institute/NIH), respectively. T.T. is an HHMI investigator. The study was supported, in part, by the Starr Cancer Foundation (T.T.), the Starr Foundation (T.T., Ma.Y.: TRI-SCI 2014-036; R.G.R.: TRI-SCI), NCI (R.G.R.), NCATS/NIH/CTSA, the Vilcek Foundation (Ma.Y.; UL1 TR000043), DAAD (C.M.), and NIH TRA (T.T.; R01CA159227). The Intramural Research Program of NIAMS/NIH supports S.M., H.L.M., and M.H. Ma.Y. was a recipient of a JSPS Research Fellowship.
CFI statement: T.T. is co-founder of and scientific advisor to Alnylam Pharmaceuticals and Regulus Therapeutics.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a–c, Dnd1 mRNA abundance determined by RNA-seq during embryogenesis from oocytes to birth (Postnatal day 0, P0) at embryonic day (E) 19.5 (a), in embryonic stem cells (ES cells), developing PGCs isolated from E9.5 to E13.5 embryos, and in vitro culture of spermatogonial stem cells (germline stem cells, GSCs) (b) and in adult tissues (c). Error bars indicate s.e.m. (3–5 replicates). GV, germinal vesicle oocytes; MII, mature metaphase II oocytes; -M, male; -F, female. d, Domain organization of DND1 proteins from representative vertebrates determined by SMART (Normal mode, http://smart.embl.de/)50. The peptide length in amino acids is indicated. RNA recognition motif (RRM) (P < 10−8) and RRM-like (P > 0.05) domains are represented as blue and light blue boxes, respectively. e, f, Structure and amino acid sequence comparison of DND1 RRM (e) and RRM-like (f) domains between human and other vertebrates. The top panel indicates the probability for α-helix (yellow) and β-sheet (green) formation of human DND1 predicted by NetSurfP51 (http://www.cbs.dtu.dk/services/NetSurfP/), as well as information on secondary structure elements required to form the RRM fold52,53,54. The arrowheads indicate the residues forming the hydrophobic interactions for the β3′–β3′′ β-hairpin. Similarity in the amino acid composition was assessed based on the classification of the amino acid residues as shown in the legend; aliphatic (A and V), aromatic (F, Y and W), basic (K and R), acidic (D and E), neutral (S, T, C, N, Q and H), or small (G and P). The highly conserved ribonucleoprotein motifs, RNP2 and RNP1, involved in protein–RNA interaction, are indicated in black boxes, together with their consensus sequences, (L/I)(Y/F)(V/I)XXL and (R/K)G(F/Y)(G/A)(F/Y)(I/V)X(F/Y), respectively52,53. Note that aromatic residues in RNP1 and RNP2 and basic residues in RNP1 are not conserved in the RRM-like domain (f). Additionally, compared with the RRM domain, the probability to form β3′ and β3′′ sheets in the RRM-like domain is low and the aliphatic residues (V200 and L206 in human) constraining the β3′–β3′′ β-hairpin (arrowheads) are less conserved. g, Screen for stable HEK293 cell clones expressing FH–DND1. Clone 4 was selected for PAR-CLIP experiments and clones 1 and 4 were used for apoptosis assays. h, The indicated amounts of purified Flag-tagged protein (Flag–BAP) were spiked into lysates from parental Flp-In HEK293-TRex cells. Expression of FH–DND1 in stable HEK293 cell lines was induced by doxycycline for the indicated amount of time. The equivalent of 104 cells was loaded into each well of the SDS–PAGE for immunoblotting. Flag–BAP and FH–DND1 were detected using anti-Flag M2 antibodies. i, Calibration curve from the signal intensity of Flag–BAP (h) quantified by ImageJ software and plotted against the amount of Flag–BAP (pg per 104 cells). The regression line and coefficient of determination (R2) are shown. j, Protein expression of human or mouse FH–DND1 in HEK293 cells with or without Dox treatment for the indicated time or in mouse SNL cells, respectively. 4 × 104 cells were loaded in each lane of the SDS-polyacrylamide gel. Immunoblot was probed with anti-HA antibodies (upper panel). The same membrane was re-probed for α-tubulin (TUBA) as loading control. k, Protein expression of mouse FH–DND1 (black arrowhead) in SNL cells or endogenous mouse DND1 (red arrowhead) in GSCs, respectively. SNL cells transformed with empty vector (EV) was used as negative control. Immunoblot was probed with anti-DND1-antibody9. TUBA served as loading control. Lysate from the indicated amount of cells was loaded onto each lane of the SDS-polyacrylamide gel. l, Copy numbers per cell of FH–DND1 in HEK293 cells after induction of transgene expression for the indicated amount of time. Values were determined by quantification (h, j). m, Copy numbers per cell of FH–DND1 and endogenous DND1 in mouse cells, determined by quantification of the DND1 band from k.
a, Left, scatter plot of the T-to-C transition per gene for the two DND1 4SU-PAR-CLIP replicates from FH–DND1-expressing HEK293 cells. Spearman correlation is indicated. Middle, scatter plot relating mRNA expression levels in FH–DND1 HEK293 cells with T-to-C transitions per mRNA for the intersected DND1 4SU-PAR-CLIP experiments. Right, scatter plot relating transcript length with T-to-C transitions per mRNA for the intersected DND1 4SU-PAR-CLIP experiments. b, Left, genomic overlap of 3′ UTR clusters derived from the two DND1 PAR-CLIP replicates in a. Right, overlap of bound transcripts of the two DND1 PAR-CLIP replicates in a. c, Immunofluorescence staining of the Flag epitope in HEK293 cells expressing FH–DND1. d, Count of the DND1-binding motif in the intersected DND1 4SU-PAR-CLIP. Note that multiple motifs can be found in a cluster. e, Overlap of DND1-binding sites with those of other AU-rich element binding, ELAVL1/HuR55 (top) and ZFP36/TTP (bottom). f, Scatter plot of T-to-C transitions per gene for DND1 PAR-CLIP and ELAVL1 PAR-CLIP (left) or ZFP36 PAR-CLIP (right). Spearman correlation coefficient is indicated. g, mRNA expression changes upon transgene induction in FH–DND1 HEK293 cells were determined by RNA-seq. The empirical cumulative distribution function (CDF) of DND1 PAR-CLIP targets binned according to presence of DND1-binding sites exclusively in the 3′ UTR (red line) or exclusively in the coding sequence (CDS; orange line), as well as mRNA targets with binding sites in both coding sequence and 3′ UTR (purple line), and compared to expressed non-targets (FPKM ≥ 5, black line). h, Normalized density of DND1 PAR-CLIP binding sites over the 3′ UTR, coding sequence, 5′ UTR and introns (red lines) compared to a randomized background (grey lines). DND1-binding sites were enriched within 100 nucleotides of the cleavage and polyadenylation site. i, mRNAs bound within 100 nucleotides of the mRNA poly(A) tail were only slightly more destabilized than those bound elsewhere in the 3′ UTR. mRNA expression changes upon transgene induction in FH–DND1 HEK293 cells were determined by RNA-seq. The empirical cumulative distribution function of DND1 PAR-CLIP targets binned according to presence of DND1-binding sites within this window (red line) or >100 nucleotide distance of the mRNA poly(A) tail (orange line) and compared to expressed non-targets (FPKM ≥ 5, black line). Coordinates of the poly(A) tails found in five out of seven 3′-end sequencing experiments in HEK293 cells obtained from http://polyasite.unibas.ch were used. The median transcript abundance change is indicated by a dot on the x axis. P values were determined by the Mann–Whitney U-test. j, Transcriptional inhibition by actinomycin D did not change the DND1-mediated reduction of target mRNA levels. mRNA expression changes in FH–DND1 HEK293 cells (with or without Dox) were compared to expression changes in FH–DND1 HEK293 cells (with or without Dox) after inhibition of transcription with actinomycin D for 2 h. DND1 targets and non-targets were binned as in Fig. 1e.
a, Colloidal Blue staining of SDS–PAGE fractionating an RNase-treated anti-Flag immunoprecipitate from lysates of HEK293 cells not induced (−) or induced (+) to express FH–DND1. A selection of the enriched protein components of the CCR4–NOT complex co-immunoprecipitated identified by mass spectrometry and their mass are shown. b, Scatter plot of per cent coverage and enrichment of signal intensity for FH–DND1 immunoprecipitate calculated against Flag immunoprecipitate from non-induced HEK293 cells for proteins identified by mass spectrometry. For a complete list of identified proteins, see Supplementary Table 2. c, Immunoblot probed for the indicated proteins after Flag immunoprecipitation from lysates of FH–DND1-expressing HEK293 cells with and without FH–DND1 induction by doxycycline or RNase A/T1 treatment. d, Scheme of known interactions of CNOT129,36. e, Immunoblot probed for the indicated proteins after GST pull-down of recombinant GST–CNOT1 proteins (Fig. 2c) from lysates of FH–DND1-expressing HEK293 cells with RNase A treatment. f, mRNA expression levels determined by RNA-seq in HEK293 cells not induced (−) or induced (+) to express FH–DND1 after transfection of shRNA-expressing plasmids. Three independent shRNA sequences were used as replicates. The relative expression levels of CNOT1 and CNOT7 are shown, as well as the mean value (black line) and standard error (s.e.m., error bars). g, The indicated amounts of plasmids encoding DND1–PP7 fusion protein and β-globin mRNA containing 4× PP7 hairpin loops in its 3′ UTR were co-transfected into HEK293 cells. β-globin reporter expression was quantified by qRT–PCR. Mean of relative expression levels of reporter mRNA (four replicates) were shown. Error bars, s.d.; P values calculated with Student’s t-test. h, β-Globin reporter expression was quantified after knockdown of Cnot1 and Cnot7. The indicated shRNA plasmids were transfected 72 h before co-transfection of indicated reporter and shRNA plasmids to ensure depletion of CNOT proteins upon reporter expression. Mean of relative expression levels of reporter mRNA (four replicates) are shown. Error bars, s.d.; P values calculated with Student’s t-test. i, Top, gene structure of the Cdkn1b gene and phyloP conservation score. Middle, alignment of DND1 (red), AGO1–4 (green), ZFP36 (blue), and ELAVL1 (purple) PAR-CLIP sequence reads to the 3− UTR of the CDKN1B mRNA. The RNA-seq coverage is shown in black and the PhyloP conservation score is shown in dark blue. Note that the conservation of RNA sequences in the area mutated by Kedde et al. (yellow highlight)8 is significantly higher than the mean conservation of the open reading frame (top panel). miR-221/AGO and DND1 target sites in the 3′ UTR are indicated by green and red arrowheads, respectively. Bottom, RNA sequence of the region studied by Kedde et al.8 aligned with miR-221 sequences. DND1 PAR-CLIP binding motifs are shown in red. The nucleotides with frequent crosslinking ( ≥ 20%) are underlined in black or red. A G-rich sequence and the poly(A) signal (AAUAAA), presumably causing insufficient RNA-seq coverage, are indicated with an asterisk and black arrow, respectively.
a, b, KEGG pathway (a) and GO (b) analyses of the top 300 DND1 targets according to the number of clusters in the 3′ UTR. Top 12 KEGG pathways and GO terms ranked by P value are shown (Supplementary Table 3). c–h, Genome browser tracks showing 3′-end portions of representative targets genes involving the KEGG pathway ‘Signalling pathways regulating pluripotency of stem cells’. The coverage track from HEK293 and the mapped sequence read from the intersection of the replicates of the FH–DND1 PAR-CLIP experiments are shown. The selected genes were categorized according to the known functions: c, TGFβ receptors; d, NODAL receptors; e, BMP receptors; f, SMAD signal transducers; g, RAS signalling; h, WNT receptor.
a, Autoradiograph of crosslinked, 32P-labelled, FH–DND1 RNA immunoprecipitate separated by SDS–PAGE after 4SU-PAR-CLIP in mouse embryonic fibroblasts. b, Distribution of crosslinked sequence reads across annotation categories. We detected a total of 108,705 sites, of which 78% were mapped to 9,697 mRNAs, predominantly in exonic sequences. c, Occurrence of the TT(T/A) RNA recognition element in the 108,705 binding sites (Supplementary Table 4). d, Scatter plot comparing number of T-to-C transitions in the 3′ UTR of target mRNAs from DND1 PAR-CLIP in HEK293 cells and their mouse homologues from PAR-CLIP in mouse FH–DND1-expressing SNL cells. e, Genome browser tracks showing portions of the human E2F3 (top) and its mouse homologue E2f3 (bottom). The conservation tracks (PhyloP), the coverage track from HEK293 and mouse ES cell RNA-seq, and the mapped sequence read from each replicate of the FH–DND1 PAR-CLIP experiments are shown. f, g, KEGG pathway (f) and GO (g) analyses of the top 300 DND1 targets from mouse PAR-CLIP according to the number of clusters in the 3′ UTR. Top 12 KEGG pathways and GO terms ranked by P value are shown (Supplementary Table 3).
a, Hoechst profile of seminiferous tubular cells visualized in a Hoechst blue/Hoechst red contour plot. Numbers in parentheses indicate percentage of each population. Spermatogenic cells show heterogeneous morphologies, intracellular complexities, and DNA contents reflecting meiotic cell cycle. Spg, spermatogonia; PreL, preleptotene spermatocytes; L-Z, leptotene–zygotene spermatocytes; P-D, pachytene–diplotene spermatocytes; MII, meiosis II spermatocytes; RS, round spermatids. Further analysis of the spermatogonia fraction is presented in Fig. 3. b, DNA content of the gated spermatogenic cells in a reveals successful separation of developing spermatogenic cells. c, Histogram of EPCAM+ spermatogonia in the total population is shown in lower panel. The top panel represents an unstained control from the same cell suspension. d, t-SNE analysis of single-cell RNA-seq experiments from sorted spermatogonia (from a) reveals specific clusters representing the indicated cell types. PMCs, peritubular myoid cells; MAPs, macrophages. e, Heat map representation of the expression of indicated genes on the t-SNE plot. Cell types from c were identified according to the expression levels of marker genes. In total, 187 cells were analysed, and 115 cells of these cells (61%) were determined as actual spermatogonia according to expressions of lineage marker genes including Dazl. Numbers of other cell populations were: RS, 16 cells; PMCs, 29 cells; MAP, 5 cells. f, Knockdown efficiency of four different DND1-targetting shRNA constructs (red) and three different CNOT1- and CNOT7-targeting shRNA constructs (blue and purple, respectively) compared to five control shRNAs (grey) assessed by RNA-seq. g, Appearance of GSCs four days after transduction with the indicated shRNA (scale bar, 50 μm). h, Appearance of GSCs transduced with the indicated shRNA, as well as with an empty (top) and FH–DND1 cDNA construct (bottom; scale bar, 50 μm). i, Representative FACS contour plots for shRNA-transduced GSCs with the signal intensity of annexin V on the x axis (log10 scale) and the forward scatter (FSC) on the y axis. Annexin V-positive cells represent early apoptotic cells and are gated as P8 population (green). j, The mean per cent of the population classified as P8 in three replicates of shDND1-transduced cells and controls are shown with s.e.m. P < 0.03 (Student’s t-test). k, Scatter plot comparing the average FPKM value of GSCs treated with shDND1 and control shRNAs. The numbers of twofold up- or downregulated genes with P < 0.05 are indicated in red or blue, respectively. l, Scatter plots comparing the mean FPKM value of shCNOT1 (three replicates; left panel) and shCNOT7 (three replicates; right panel) with control (five replicates). Transcripts are coloured according to q value of transcript abundance change. m, Cumulative distribution function of transcript abundance changes between GSCs treated with shDND1 and control shRNAs. Black line represents transcripts not targeted by DND1 and the red line represents targets classified as positive regulators of apoptosis according to GO (GO:0043065). The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. n, Proliferation of shRNA-transduced GSCs. The cumulative numbers of shControl-, shDND1-, or shCNOT1-transduced GSCs were shown in black, red, or blue coloured dots, respectively. shRNAs were transduced by using lentiviral vectors at day 0. Puromycin (25 ng ml−1) was added at day 2 to the culture medium to select stable transformants. o, Scatter plot similar to Fig. 3g–h of the log2 value of transcript abundance changes of shCNOT1- and shCNOT7-treated cells versus controls. Pearson’s correlation coefficient is indicated. Transcripts are coloured according to the log2 value of transcript abundance change of shDND1-treated cells versus control.
Extended Data Figure 7 DND1 target mRNAs are silenced in developing PGC and Cas9-mediated gene knockout of Dnd1 in murine ES cells.
a, b, mRNA expression change between day 0 and day 2 PGCLCs (a) and day 2 and day 4 PGCLCs (b) induced from EpiLCs was determined by RNA-seq (Supplementary Table 6). Expressed mouse DND1 PAR-CLIP target mRNAs (FPKM >5) were binned according to the number of binding sites (coloured lines) and compared to expressed non-targets (FPKM >5, black line). The empirical cumulative distribution function was plotted. The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. c, mRNA abundance change between DND1high and DND1low PGC precursors at E6.5–6.75 (n = 6 each) was determined in a previous study8 by single-cell microarray analysis (Supplementary Tables 7 and 9). Expressed mouse DND1 PAR-CLIP target mRNAs (log2 array signal intensity >8) were binned and compared to expressed non-targets (log2 array signal intensity >8, black line) and the cumulative distribution function plotted as described in a. d, Same as c, except mRNA abundance change in specified PGCs at E7.25 (n = 8) compared to DND1low PGC precursor cells (n = 6) was shown. e, Genome browser track showing the gene structure of Dnd1 on mouse chromosome 18. The bottom track indicates the regions encoding the RNA binding domain of DND1. RNP1 and RNP2 motifs contacting RNA (Extended Data Fig. 2). f, RNA-seq tracks for the same region as a showing the deletions induced by the sgRNAs for three different clones. g, Sanger DNA sequencing of the indicated region confirms successful deletions by the sgRNAs predicted to cut at the indicated positions. Allele pairs 13-8 and 13-10 showed targeted deletion of RNP2 associated with a frame shift, resulting in the generation of null mutations in both alleles (Dnd1tm/tm). Allele pair 12-1 has in-frame deletions for loss of RNP2 (Dnd1tmRNP2/tmRNP2). There was no distinguishable phenotype differences between these mutant mice in germline development (Extended Data Fig. 8 and data not shown) and we therefore combined data from these three lines referred to as Dnd1–/–.
a, Scheme of blastocyst injection protocol to generate chimeric mouse embryos for the analysis of the developmental potential of Dnd1−/− ES cells. b, Injected ES cells successfully form chimeric mouse embryos. Arrowheads indicate white (recipient-derived) and black (donor ESC-derived) eyes. c, Analysis of the PGCs from chimeric E12.5 embryos. DDX4 served as marker for germ cells and mCherry marked cells derived from injected ES cells. Only Dnd1+/+ ES cells were able to give rise to DDX4-positive PGCs. d, Representative FACS plots comparing the ITGB3-positive PGCLC fraction after four days of induction from Dnd1+/+ (left) or Dnd1−/− EpiLCs (right). e, Quantification of relative induction efficiency of PGCLCs from Dnd1+/+ or Dnd1−/− EpiLCs, (5 or 7 replicates, respectively). Error bars, s.e.m.; P values calculated with Student’s t-test. f, Scatter plot of gene expression levels comparing Dnd1−/− and Dnd1+/+ cells at day 0 (left), day 2 (middle), and day 4 (right) of the PGCLC induction time course. Transcripts are coloured by the q value of transcript abundance change.
Extended Data Figure 9 Analysis of transcript abundance changes of specific transcript categories in Dnd1−/− PGCLCs.
a, CDF of transcript abundance changes between Dnd1+/+ and Dnd1–/– PGCLCs at between day 2 (left) and day 4 (right). The green lines represent DND1 targets classified as GO category ‘germ cell development’ (GO:0007281), and the black line represents all the other genes. The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. b, Cumulative distribution function of transcript abundance change between day 4 Dnd1+/+ and Dnd1–/– PGCLCs. The green line represents the genes defined as Core PGC genes in a previous study56, and the black line represents all the other genes. The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. c, Cumulative distribution function of transcript abundance changes between day 2 Dnd+/+ and Dnd−/− PGCLCs. Black line represents transcripts not targeted by DND1 and the coloured lines represent DND1 targets classified according to the indicated GO categories (innate immune response, GO:0045087; positive regulation of apoptotic process, GO:0043065; inflammatory response, GO:0006954; positive regulation of IKKβ/NFκB signalling GO0043123). The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. d, Cumulative distribution function of transcript abundance changes between day 2 Dnd+/+ and Dnd−/− PGCLCs. The purple line represents transcripts classified as ‘mediators of inflammatory apoptosis’ (GO:0006925), regardless of DND1 binding. The black line represents all the other genes. The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. e, Transcript abundance change of representative genes involved in TGFβ superfamily signalling pathways (Extended Data Figs 8, 9). f, Cumulative distribution funciton of transcript abundance changes between day 2 Dnd+/+ and Dnd−/− PGCLCs. Black line represents transcripts not targeted by DND1 and the blue line represents DND1 targets classified as genes involved in stem cell population maintenance by GO (GO:0019827). The median transcript abundance change is indicated by a dot on the x axis. P values were determined with a Mann–Whitney U-test. g, Transcript abundance change of representative pluripotency genes.
A summary of PAR-CLIP and gene expression data in FH-DND1 expressing HEK293 cells. Sheet 1 provides the detailed table legends. Sheet 2 show statistics of annotation and mapping of DND1 PAR-CLIP in HEK293. Sheet 3 show the intersected binding sites from FH-DND1 PAR-CLIP replicate 1 and 2. In sheet4, summary of PAR-CLIP binding sites and RNAseq experiments in HEK293 cells using ENSEMBL mRNA annotation are shown. (XLSX 22977 kb)
Mass spectrometric analysis of FH-DND1 immunoprecipitates in HEK293 cells. Mass spectrometric analysis of proteins co-immunoprecipitated with doxycycline-induced FLAG/HA tagged DND1 from HEK293 cells. Enrichment of signal intensity for FLAG/HA-DND1 IP was calculated against FLAG immunoprecipitate from uninduced HEK293 cells. (XLSX 736 kb)
Pathway analysis of the top 300 targets of DND1 in HEK293 cells and SNL cells. Complete results of Gene ontology (GO) (first tab) and KEGG pathway (second tab) analyses in Extended Data Fig. 8. The list of the top 300 DND1 targets according to the number of clusters in the 3’UTR was used in the analyses. KEGG pathways and GO terms are listed according to p values. (XLSX 83 kb)
PARalyzer defined clusters and summary of DND1-PAR-CLIP binding profile on the transcriptome in mouse SNL cells. Sheet 1 provides the detailed table legends. Sheet 2 shows complete results of clusters defined by PARalyzer from PAR-CLIP in mouse SNL cells. In sheet3, the summary of DND1 PAR-CLIP binding profiles on the transcriptome in mouse SNL cells is shown. (XLSX 26287 kb)
Gene expression analysis from spermatogonia using DropSeq. Sheet 1 provides the detailed table legends. Sheet 2 shows datasets used in the gene expression analyses for Fig. 3 and Extended Data Fig. 6. (XLSX 7144 kb)
Gene expression analysis from GSCs, ESCs, EpiLCs and PGCLCs. Sheet 1 provides the detailed table legends. Sheet 2 shows datasets used in the gene expression analyses of ESCs, GSCs, and PGCLCs are shown for Figs. 3, 4 and Extended Data Figs. 6-9. (XLSX 25232 kb)
Gene expression analysis from reanalysed microarray data from PGCs. Sheet 1 provides the detailed table legends. Sheet 2 shows gene expression in PGC precursors and PGCs from E6.25 to E7.25 determined by single-cell microarrays in previous report. (XLSX 3573 kb)
Pathway analysis of the significantly upregulated genes in Dnd1–/– d2 PGCLCs. Gene ontology (GO) (first tab) and KEGG pathway (second tab) analyses of significantly upregulated genes (FPKM >2, log2 fold change > 0.8, q<0.05) in Dnd1-/- d2PGCLCs. (XLSX 23 kb)
This table contains information regarding microarray datasets and shRNA sequences used in this study. Sheet 1 provides the detailed table legends. Lists of microarray datasets (sheet2) and shRNA sequences (sheet3) are shown. (XLSX 45 kb)
This file contains the uncropped images of the immunoblots shown in this study. (PDF 826 kb)
About this article
Cite this article
Yamaji, M., Jishage, M., Meyer, C. et al. DND1 maintains germline stem cells via recruitment of the CCR4–NOT complex to target mRNAs. Nature 543, 568–572 (2017) doi:10.1038/nature21690
Trends in Cell Biology (2019)
A programmed wave of uridylation-primed mRNA degradation is essential for meiotic progression and mammalian spermatogenesis
Cell Research (2019)
Stage-specific combinations of opposing poly(A) modifying enzymes guide gene expression during early oogenesis
Nucleic Acids Research (2019)
PLOS ONE (2019)
RNA-binding proteins distinguish between similar sequence motifs to promote targeted deadenylation by Ccr4-Not