SUMMARY
The mammalian imprinted Dlk1-Dio3 locus produces multiple long non-coding RNAs (lncRNAs) from the maternally inherited allele, including Meg3 (i.e. Gtl2) in the mammalian genome. Although this locus has well-characterized functions in stem cell and tumor contexts, its role during neural development is unknown. By transcriptome profiling cell types at each stage of spinal cord development, we uncovered that lncRNAs expressed from the Dlk1-Dio3 locus are predominantly and gradually enriched in rostral motor neurons (MNs). Mechanistically, Meg3 and other Dlk1-Dio3 locus-derived lncRNAs facilitate Jarid2-Ezh2 interactions. Loss of these lncRNAs compromises the H3K27me3 landscape, leading to aberrant expression of progenitor and caudal Hox genes in postmitotic MNs. Our data illustrate that these lncRNAs in the Dlk1-Dio3 locus play a critical role in maintaining postmitotic MN cell fate by repressing progenitor genes and they shape MN subtype identity by regulating Hox genes, providing strong evidence of how lncRNAs function during embryonic development.
INTRODUCTION
Investigations of the gene regulatory networks involved in cell type specification during embryonic development have been protein-centric for decades. However, given the prevalence of high-throughput sequencing analyses of mammalian genomes, it is now appreciated that non-coding RNAs (ncRNAs) account for at least 50~80 % of transcriptomes (Pauli et al, 2011; Rinn & Chang, 2012). Regulatory ncRNAs can be broadly classified based on their size (Mattick, 2009). Short RNA species (~20–30 nucleotides [nt]), such as microRNAs (miRNAs), have emerged as pivotal modulators of development and disease through mediation of translational repression or mRNA degradation (Esteller, 2011). Long non-coding RNAs (lncRNAs; > 200 nt) are gaining prominence for their roles in many cellular processes, from chromatin organization to gene expression regulation during embryonic development (Kung et al, 2013; Rinn & Chang, 2012; Rutenberg-Schoenberg et al, 2016). Thus, it is not surprising that lncRNAs were recently found to be associated with an array of diseases including cancers, as well as cardiovascular and neurological disorders (Briggs et al, 2015).
Accumulating evidence supports that lncRNAs can induce cis- and trans-acting gene silencing. For example, the lncRNA Airn directly represses the paternally-expressed Igf2r gene in cis for the maintenance of ESC differentiation (Pauler et al, 2005) and Xist lncRNA triggers in cis inactivation of the X chromosome (Lee, 2009). The human lncRNA HOTAIR, which is expressed from the caudal HOXC locus, acts in trans to target the HOXD cluster for gene silencing (Rinn et al, 2007). Approximately 20 % of lncRNAs are associated with polycomb repressive complex 2 (PRC2) (Jing et al, 2010; Khalil et al, 2009), which is comprised of many subunits and functions to deposit histone H3K27 trimethylation (H3K27me3) and to suppress gene expression (Di Croce & Helin, 2013; Margueron & Reinberg, 2011; Simon & Kingston, 2013). Although some evidence indicates that lncRNAs might serve as scaffolds for PRC2 assembly and guide PRC2 to specific genomic targets, whether the interaction is specific and necessary in development or disease contexts is still unclear (Cifuentes-Rojas et al, 2014; da Rocha et al, 2014; Davidovich & Cech, 2015; Davidovich et al, 2015; Davidovich et al, 2013; Kaneko et al, 2014a; Kaneko et al, 2014b). Therefore, it is imperative to demonstrate that the specific interactions of lncRNAs with the PRC2 complex are functionally important and have specific regulatory targets to direct development or induce disease in vivo.
We used spinal motor neuron (MN) differentiation as a paradigm to assess these interactions. Although spinal cord development is one of the best characterized processes in the central nervous system (CNS) (Alaynick et al, 2011; Catela et al, 2016; Chen et al, 2011; Mazzoni et al, 2013a; Mazzoni et al, 2013b; Narendra et al, 2015; Philippidou & Dasen, 2013), how lncRNAs are involved in its transcription factor-driven gene regulatory networks is unclear (Briscoe & Small, 2015). MN differentiation into subtypes is mediated by the mutually exclusive expression of Hox transcription factors, which is programmed according to the body segment along the rostrocaudal (RC) axis. For example, segmental identity of MNs is defined by the mutually exclusive expression of Hox6, Hox9 and Hox10 (Dasen et al, 2003; Lacombe et al, 2013). In each segment, MNs are grouped into different columns according to their innervating targets. For instance, within the brachial Hox6on segment, MNs are further grouped into axial muscle projecting MNs (Lhx3on, MMC) and forelimb-innervating MNs (Foxp1on, LMC). Finally, another set of mutually exclusive Hox proteins, such as Hox5 and Hox8 expression in the Foxp1on LMC, further controls the rostral and caudal motor pool identity, which directs motor pools to either innervate proximal or distal muscles in the forelimb (Catela et al, 2016; Dasen et al, 2005b).
In the spinal cord, polycomb proteins control the exclusion of certain Hox protein expression at specific rostro-caudal (RC) positions and maintain this repression in differentiated cells. Depletion of the polycomb repressive complex 1 (PRC1) component Bmi1 at brachial level causes ectopic expression of Hoxc9 and subjects LMC neurons to a thoracic preganglionic column (PGC) fate. Conversely, elevation of Bmi1 represses Hoxc9 at thoracic level and subjects PGC neurons to an LMC fate (Golden & Dasen, 2012). These observations suggest that specific Hox repression may be maintained in MNs by distinct PRC1 activity levels, programmed along the RC axis. Recently, it was shown that during MN differentiation, Hox chromatin is demarcated into discrete domains controlled by opposing RC patterning signals (i.e., retinoic acid (RA), Wnt, and fibroblast growth factors (FGFs)) that trigger rapid and domain-wide clearance of H3K27me3 modifications deposited by PRC2 (Mazzoni et al, 2013b). More specifically, RA activates retinoic acid receptors (RARs) and binds to the Hox1~5 chromatin domains, which is followed by synchronous domain-wide removal of H3K27me3 to acquire cervical spinal identity. At the tailbud, a gradient of Wnt and FGF signals induces expression of the Cdx2 transcription factor that binds and clears H3K27me3 from the Hox1-Hox9 chromatin domains, thereby establishing brachial or thoracic segmental identity (Mazzoni et al, 2013b). Together, these findings indicate that epigenetic regulation of Hox clusters is critical to initiate and maintain patterns of Hox expression and that cross-repressive interactions of combinations of Hox proteins later consolidate the diversification of postmitotic MNs. However, the underlying mechanism that demarcates the histone modifiers at a molecular level is still unclear. Although many lncRNAs are known to regulate these histone modifiers, whether lncRNAs are directly involved in MN fate determination remains to be established.
We found that lncRNAs in the imprinted Dlk1-Dio3 locus are highly enriched in postmitotic MNs. The Dlk1-Dio3 locus contains three protein-coding genes (Dlk1, Rtl1, and Dio3) from the paternally inherited allele, and multiple lncRNAs and small ncRNAs are derived from the maternally inherited allele, including Meg3, Rian (containing 22 box C/D snoRNAs), as well as the largest miRNA mega-cluster in mammals (anti-Rtl1, which contains the miR-127/miR-136 cluster of 7 miRNAs, and Mirg that contains the miR-379/miR-410 cluster of 39 miRNAs). Interestingly, all of the ncRNAs are regulated by a common cis-element and epigenetic control, resulting in a presumable large polycistronic transcription unit (Das et al, 2015; Lin et al, 2003; Seitz et al, 2004). Although the Dlk1-Dio3 locus is well known to play crucial roles in stem cells (Lin et al, 2007; Lin et al, 2003; Qian et al, 2016), we unexpectedly found that expressions of Meg3 and other lncRNAs from the Dlk1-Dio3 locus are also all enriched in postmitotic MNs. However, whether this locus functions during neural development had not been explored previously. Here, we show that lncRNAs in the imprinted Dlk1-Dio3 locus shape postmitotic MNs by inhibiting progenitor and non-neural genes, and they also control MN subtype identity by regulating Hox expression. Our results provide strong evidence for the critical function of lncRNAs during MN development, emphasizing their physiological functions during embryonic development.
RESULTS
Identification of cell type-specific lncRNAs during MN differentiation
As epigenetic landscape remodelling and the cell fate transition during MN differentiation are well characterized (Chen et al, 2011; Li et al, 2017; Tung et al, 2015), we took advantage of an ESC differentiation approach that can recapitulate MN development to systematically identify cell type-specific lncRNAs during this differentiation process. Firstly, an ESC line harbouring the MN transgenic reporter Hb9::GFP was harnessed into MNs (Wichterle et al, 2002), and we then sequentially collected RA-induced nascent neural epithelia (Hoxa1on, NE at day 2), MN progenitors (Olig2on, pMN at day 4), and postmitotic MNs (Hb9::GFPon, postmitotic MNs at day 7) by fluorescence-activated cell sorting (FACS). Simultaneously, spinal interneurons (INs) derived from [smoothened agonist; SAG]low conditions were collected and Hb9::GFPoff cells were sorted at day 7 as controls (Figure 1A). Next, we performed strand-specific RNA-seq across a library preserving non-polyadenylated transcripts while removing ribosomal RNAs, since many lncRNAs are non-polyadenylated (Yin et al, 2012; Zhang et al, 2012), and carried out de novo transcriptome assembly (Qian et al, 2016) to discover novel lncRNAs that might be specifically enriched during motor neuron development (detailed in the Supplemental Experimental Procedures and summarized in Figure 1B and Table S1). Several known markers for each cell type during MN differentiation were accurately recovered, corroborating the high quality and specificity of our RNA-seq data (Figure 1C). Our approach yielded 10,177 lncRNAs, 752 of which (7.39 %) were previously unidentified from the Ensemble mm10 database. We also found that 4,295 (77.78 %) of our identified lncRNAs overlapped with recently reported spinal MN-related lncRNAs, which were discovered by poly A+-enriched RNA-seq approaches (Amin et al, 2015; Narendra et al, 2015) (Figure S1A). Finally, we removed minimally expressed transcripts (TMM normalized read count < 10 in all samples), which left 602 expressed lncRNAs (Table S2). Based on stage-specific scores (see Supplemental Experimental Procedures), we identified 70 stage-signature lncRNAs during the ESC~MNs differentiation process (ESC, NE, pMN, MN, and IN in Figure 1D). Compared to protein-coding genes, both annotated lncRNAs and novel lncRNAs (newly identified in our de novo transcriptome assembly) had higher cell-type specificity (Figure 1E, Kolmogorov-Smirnov test, P = 1.41 × 10−9 and P = 3.53 × 10−7, respectively; see Supplemental Experimental Procedures), implying that lncRNAs might play specific roles in each cell type during ESC~MNs differentiation.
Dlk1-Dio3 locus-derived lncRNAs are enriched in the nuclei of postmitotic MNs
To identify developmentally up-regulated lncRNAs, we compared day 4 pMNs vs. day 7 postmitotic MNs (Figure 2A). Furthermore, to differentiate cell type-specific lncRNAs, we performed a pairwise comparison of day 7 postmitotic MNs against day 7 INs (Figure 2B). We identified 117 lncRNA candidates from our analysis as being postmitotic MN-enriched. We further selected several MN-lncRNAs that manifested high normalized reads from RNA-seq data and verified their MN-specific expression by qPCR (Figure S1B). Interestingly, the lncRNAs Meg3, Rian, and Mirg, which are transcribed from the imprinted Dlk1-Dio3 locus on mouse chromosome 12qF, all manifested strong enrichment in postmitotic MNs (Figure S2A). Since these lncRNAs are conserved amongst placental mammals (Ogata & Kagami, 2016), we chose to characterize their functions in greater detail.
To investigate why Meg3-Rian-Mirg are highly enriched in postmitotic MNs, we examined the binding landscape of MN-specific transcription factors (i.e., Lhx3 and Isl1), chromatin accessibility (ATAC-seq), and histone modification (H3K4me3 and H3K27ac) across the Meg3-Rian-Mirg locus from previously published studies (Figure 2C) (Mazzoni et al, 2013a; Narendra et al, 2015; Rhee et al, 2016). Within this locus, we uncovered an MN-specific active chromatin region that possesses enhancer/promoter characteristics with direct MN-specific transcription factor binding (Figure 2C). Furthermore, overexpression of MN-TFs in a maternally-inherited intergenic differentially methylated region (IG-DMR) deletion (IG-DMRmatΔ) ESC line, which leads to simultaneous silencing of all maternally-expressed lncRNAs in the Meg3-Rian-Mirg locus but leaves the MN-TF binding site intact (Figure S2A) (Lin et al, 2007; Lin et al, 2003), can robustly induce Meg3 expression (Figure S2B). Therefore, we suggest that MN-TFs bind and directly activate Meg3-Rian-Mirg during differentiation.
We further performed Meg3 in situ hybridization and immunostaining of the adjacent sections along the RC axis from E10.5~12.5. We found that Meg3 expression: 1) is enriched in the mantle zone of the developing spinal cord during development and is gradually enriched in postmitotic MNs (Isl1/2on cells) after E12.5; 2) has no preference for columnar MN subtypes, as revealed by Foxp1 (LMC-MNs) and Lhx3 (MMC-MNs) immunostaining; and 3) exhibits rostral high (brachial and thoracic) and caudal low (lumbar) asymmetry after E12.5 (Figures 2D and 2E).
Why does Meg3 exhibit strong enrichment in the brachial spinal cord? Given that previous reports indicate that rostral Hox genes enriched in the brachial spinal cord are mediated by an RA gradient (Mazzoni et al, 2013b; Novitch et al, 2003), we hypothesized that Meg3 might also be induced by RA. To examine this possibility, we checked if there is any RA-driven binding to RAR sites near the Meg3 promoter (Figure 2F) (Mahony et al, 2011). Interestingly, we found that RA treatment results in novel binding of RAR directly to the Meg3 promoter, as well as subsequent recruitment of the basal transcription complex (Pol2 S5P in Figure 2G). Moreover, we observed that Meg3 is induced after the addition of RA in IG-DMRmatΔ ESCs after 8 hours (Figure S2C), indicating that RA/RAR activation triggers the strong Meg3 expression in rostral brachial MNs.
Finally, to characterize the abundance and subcellular localization patterns of Meg3 at a cellular level, we designed a set of single molecule RNA FISH probes specific to Meg3 and examined their expression in ESC~MNs. We observed a speckled pattern of Meg3 expression enriched in the nucleus, suggesting it has a potential function in gene regulation (Figure S2D). Furthermore, qPCR of subcellular-fractionated RNAs from ESC~MNs validated that Meg3 is not only enriched in the nucleus, but that it is also chromatin-associated (Figure S2E; Gapdh as cytoplasmic marker, U1 as nuclear marker, and Kcnq1ot1 as a chromatin-associated RNA control). Together, these findings suggest that lncRNAs in the Dlk1-Dio3 locus are postmitotic MN-enriched, and that they are directly activated by MN-TFs and RA/RAR. At a cellular level, Meg3 is highly enriched in MN nuclei and is chromatin-associated, indicating a potential function in chromatin regulation.
Meg3 facilitates interaction of the PRC2 complex with Jarid2 in MNs
Several previous reports have revealed that interactions between Jarid2 and ncRNAs regulate PRC2 recruitment to chromatin, including lncRNAs in the Dlk1-Dio3 locus of ESCs (da Rocha et al, 2014; Kaneko et al, 2014a; Kaneko et al, 2014b). The roles of PRC2/Jarid2 in postmitotic cells are less clear. Unlike the PRC2 complex, Jarid2 is known to have diverse cell type-specific functions (Landeira & Fisher, 2011). Surprisingly, we found that expression of Jarid2 was reactivated in postmitotic MNs, pointing to specific regulation in this cell type (Figure S3A) (Takeuchi et al, 1995). This prompted us to examine if lncRNAs in the Dlk1-Dio3 locus bind to the PRC2 complex and maintain postmitotic MN fate by controlling the H3K27me3 landscape. To test this hypothesis, we first demonstrated that immunoprecipitation (IP) of endogenous PRC2 complex components (i.e., Ezh2 and Suz12), as well as the PRC2 cofactor Jarid2, from ESC~MNs specifically retrieves Meg3, Rian and Mirg RNA, whereas the nuclear ncRNA U1 and the lncRNA Malat1 were not captured by Ezh2, Jarid2, or Suz12 (Figure 3A). Given that Rian and Mirg are further processed to snoRNAs and miRNAs (Lin et al, 2003) and that Meg3 is known to regulate pluripotency (Stadtfeld et al, 2010), imprinting (Das et al, 2015), and PRC2 function (Zhao et al, 2010), we focused on biochemical characterization of Meg3. Several Meg3 isoforms have previously been documented, so we scrutinized across the entire Meg3 locus (~31 kb) and found that two isoforms, Meg3v1 and Meg3v5 (Ensemble mm10 database), are predominantly expressed in Hb9::GFPon MNs (Figures S3B and S3C). This result was confirmed by qPCR, which indicated that expression of Meg3v5 is more significantly enriched in Hb9::GFPon MNs compared to the other common variants that have previously been studied in ESC~MNs (Figure S3D) (Kaneko et al, 2014a; Zhou et al, 2007). Interestingly, Meg3v1 and Meg3v5 have mutually exclusive exon sequences (Figure S3E), raising the possibility that the two isoforms might exert different functions. However, both purified biotinylated Meg3v1 and Meg3v5 RNA retrieved Ezh2 from cell nuclear extracts of ESC~MNs (Figure 3B; GFP RNA was used as a negative control). These results suggest that these Meg3 isoforms directly interact with PRC2/Jarid2 complexes and might facilitate association of the PRC2 complex with Jarid2.
As the PRC2 complex and Jarid2 are known to interact in a non-stoichiometric manner (Pasini et al, 2010; Peng et al, 2009), we further examined if Meg3 facilitates the interaction between PRC2 complex and Jarid2. To test this possibility, we performed IP with Ezh2 (a core component of PRC2) to retrieve Jarid2 from ESCs (Figure 3C). We first verified that Meg3 knockdown (KD) did not affect the protein abundance of Ezh2/Jarid2, but we did observe that it undermined the interaction between Ezh2 and Jarid2, suggesting that Meg3 facilitates this interaction (Figure 3C and Figure S3F). We then investigated if the two Meg3 isoforms have differing abilities to facilitate Ezh2/Jarid2 binding by generating two locus-defined Tet-ON-inducible Meg3 ESCs (Figure 3D, iMeg3v1 and iMeg3v5). Upon doxycycline induction, both Meg3 isoforms were induced ~20–50 fold, yet the abundance of Ezh2/Jarid2 remained unaffected (Figures 3E and 3F). Meg3v5 overexpression in ESCs significantly increased the binding of Ezh2 and Jarid2, whereas Meg3v1 overexpression had a minimal effect (Figure 3G), indicating that Meg3v5 is a strong facilitator of the binding of the PRC2 complex and Jarid2. Accordingly, we suggest that Meg3, and particularly the Meg3v5 isoform, facilitates the binding of the PRC2 complex and Jarid2 in postmitotic MNs.
Dlk1-Dio3 locus-derived lncRNAs maintain the epigenetic landscape in postmitotic MNs
To test if the binding of Ezh2/Jarid2 by the lncRNAs in the Dlk1-Dio3 locus is important to maintain the epigenetic landscape in postmitotic MNs, we systematically analyzed genome-wide H3K27me3 profiles of control and IG-DMRmatΔ ESC~MNs by ChIP-seq (chromatin immunoprecipitation-sequencing) (Figure 4A). To overcome the complication of concomitant up-regulation of paternal coding genes in IG-DMRmatΔ ESCs (Lin et al, 2007; Lin et al, 2003), we further established two retrovirus-based short hairpin RNAs (shRNAs) targeting Meg3 and used a knockdown approach to prevent impairment of DMR sites. Both shRNAs reduced the expression of Meg3 by an average of ~90 % compared to endogenous levels in ESC~MNs (Figure S4A). As negative controls, we performed independent infections with retroviruses containing scrambled shRNA with no obvious cellular target RNA. We selected two stable Meg3 knockdown (KD) ESCs (referred to as H6 and K4 hereafter) that had the best ESC morphology for further experiments. Verification by qPCR indicated that the expressions of two other lncRNAs, Rian and Mirg, from the maternal allele of the Dlk1-Dio3 imprinted locus were all significantly down-regulated in Meg3 KD MNs, whereas paternal genes were unaffected (Figure S4A). This finding is consistent with a previous report indicating that Meg3-Rian-Mirg probably represents a single continuous transcriptional unit (Das et al, 2015).
We then performed H3K27me3 ChIP-seq of control and Meg3 KD MNs. We observed a trend of global down-regulation of H3K27me3 in both independent experiments of Meg3 KD MNs, most likely a reflection of compromised Ezh2/Jarid2 interaction (Figure 4B and Figure S4B). Since the response to PRC2 activity change in a given cell type might be context-dependent (Davidovich et al, 2013), we sought to identify the most prominent genes in MNs regulated by Dlk1-Dio3 locus-derived lncRNAs based on the loss of H3K27me3. To achieve this, we profiled gene transcriptomes of control, IG-DMRmatΔ, and Meg3 KD MNs. Next, we compared the co-upregulated genes between IG-DMRmatΔ and Meg3 KD MNs, together with H3K27me3 landscape upon the loss of ncRNAs in the Dlk1-Dio3 locus (Figure 4C and FigureS4C). This approach revealed 497 genes in MNs that displayed down-regulation of the H3K27me3 epigenetic landscape and concomitant up-regulation of gene expression upon loss of the Meg3 imprinted lncRNAs (Figure 4C). Gene ontology (GO) analysis of these genes revealed significant enrichment for rostrocaudal patterning and progenitor genes, and strikingly so for homeodomain Hox genes (Figures 4D and Figure S4D; false discovery rate (FDR) q-value ≤ 0.05). We observed that a majority of caudal Hox genes (Hox8~13) were up-regulated with a concomitant down-regulation of the H3K27me3 epigenetic landscape (Figure 4E). We corroborated this finding by generating a third Meg3 KD ESC line (I6) and confirming that all Meg3 KD ESC~MNs exhibited imbalanced expression of 3’ and 5’ Hox genes across entire Hox clusters (Figure S4E). Thus, for both Meg3 KD and IG-DMRmatΔ MNs, dysregulation of progenitor and Hox gene expression is the most prominent phenotype, likely due to loss of the robustness of the epigenetic landscape of postmitotic MNs.
IG-DMRmatΔ embryos manifest dysregulation of progenitor and Hox genes in postmitotic MNs
To corroborate the observed phenotype of IG-DMRmatΔ ESC~MNs, we further scrutinized the MN phenotype in IG-DMRmatΔ embryos. Consistent with previous studies, IG-DMRmatΔ embryos died soon after E16 (Lin et al, 2007), so we analyzed MN phenotypes from E10.5~E13.5 in this study. Since we had observed that the progenitor gene Dbx1 is one of the most up-regulated progenitor genes in IG-DMRmatΔ ESC~MNs (Figure S4C), we first checked if Dbx1 is affected by crossing IG-DMRmatΔ to the Dbx1LacZ/+ reporter mice (Bielle et al, 2005). Compared to the control Dbx1LacZ/+ littermates, we observed a significant increase in the number of Dbx1on cells along the entire rostrocaudal axis of the ventral spinal cord in IG-DMRmatΔ; Dbx1LacZ/+ embryos (Figures 5A and 5C, only the cervical segment is shown). However, Hb9on and Isl1(2)on MNs were comparable between control and IG-DMRmatΔ embryos at E10.5 (Figures 5B and 5C). This finding indicates that although progenitor genes are aberrantly up-regulated in the ventral spinal cord, production of MNs remains relatively unaffected.
Next, we checked if the expression of Hox proteins is affected in IG-DMRmatΔ embryos. We first assessed how loss of Dlk1-Dio3 locus-derived lncRNAs affected the specification of segmental MNs, marked by brachial (Hoxc6), thoracic (Hoxc9), and lumbar (Hoxd10) Hox levels. We observed comparable numbers of cells expressing respective Hox proteins at each segmental level between control and mutant embryos (Figures S5A and S5B). Columnar identities of axial (Lhx3on) and limb-innervating MNs (Foxp1on) were also largely unaffected in the IG-DMRmatΔ embryos (Figures S5C and S5D).
To further examine MN subtype diversification within the limb-innervating MNs, we checked the Hox proteins involved in pool specification (Catela et al, 2016; Dasen et al, 2005a). Whereas reciprocal expression of Hoxa5 and Hoxc8 was maintained along the rostrocaudal axis in the Hox6on LMC MNs of control embryos, Hoxc8 was expanded rostrally into Hoxa5on territory in IG-DMRmatΔ embryos, along with a significant increase of the Hoxc8-mediated downstream motor pool genes, Pea3 and Scip (n=5 embryos in Figures 6A and 6C for rostral brachial segments and Figures 6B and 6D for caudal brachial segments; quantification in Figures 6E and 6F). The reduction of Hoxa5 was not attributable to apoptosis, as cCasp3on cells were comparable in both control and IG-DMRmatΔ mutant embryos (data not shown).
Peripheral innervation defects in IG-DMRmatΔ mutants
To further examine the impact of switching the MN pool subtype identity of LMC-MNs, we assessed the potential trajectory and target selectivity of motor axons in wild type control and IG-DMRmatΔ embryos. We bred IG-DMRmatΔ mutants to a transgenic line of Hb9::GFP mice in which all motor axons are labeled with GFP and then analyzed the overall pattern of limb innervation. First, the images of motor nerves from light sheet microscopy were converted into panoramic 3D images (Figure 7A upper panel; Supplementary Movies 1 and 2). The overall trajectory of each motor nerve was reconstructed by Imaris (lower panel in Figure 7A) and this conversion enabled semi-automatic calculation of the number of motor nerve terminals in each skeletal muscle, as well as comparison of the extent of motor axon arborization between skeletal muscles (see Supplementary Experimental Procedures for details). Under higher magnification with better resolution, we observed the terminal arbors of suprascapular (Ss) nerves of scapulohumeralis posterior muscles were significantly eroded and reduced (Figure 7B), consistent with the caudalized switch from Hoxa5 to Hoxc8 expression within LMC neurons. Concomitantly, increased arborization complexity of distal muscle-innervating nerves, including axillary (Ax) and posterior brachial cutaneous (PBC) nerves were manifested in the IG-DMRmatΔ embryos (Figures 7C and 7D, quantification in 7E, n = 6, P <0.01, Mann-Whitney U test). Thus, the IG-DMRmatΔ mutants displayed deficiencies in peripheral innervation of MNs, which might be a consequence of dysregulation of Hox proteins and/or other axon arborization genes in the absence of lncRNAs from the Dlk1-Dio3 locus.
DISCUSSION
Although mammalian genomes encode tens of thousands of lncRNAs, only less than a hundred have been shown to play critical roles in gene regulation in vitro. Consequently, the in vivo functions of the vast majority of lncRNAs remain to be vigorously tested. Strikingly, 40 s of lncRNAs are expressed specifically in the central nervous system (CNS), which makes it one of the best systems for uncovering the physiological functions of lncRNAs (Briggs et al, 2015; Ng et al, 2013). In this study, we identified a series of novel and/or uncharacterized lncRNAs that exhibit precisely regulated temporal and spatial expression patterns during MN development. Here, we focused on characterizing lncRNAs located in the imprinted Dlk1-Dio3 locus for three reasons: 1) this locus is conserved between human and mouse (Lin et al, 2007; Lin et al, 2003); 2) several studies have highlighted that Meg3 might function as a tumor suppressor (Zhang et al, 2010; Zhou et al, 2007); and 3) a previous report indicates that the paternally-expressed coding gene Dlk1 has an unexpected function in determining MN subtype diversification (Muller et al, 2014), which prompted us to examine whether the MN-enriched lncRNAs in the same locus also participate in MN cell fate determination.
Functional perspectives of lncRNAs in MNs
Although lncRNAs derived from the Dlk1-Dio3 locus are highly expressed in the CNS, their functions during neural development are largely unknown (Wang et al, 2012; Zhang et al, 2003; Zhou et al, 2012). Upon knockdown of Meg3 (a Dlk1-Dio3 locus-derived lncRNA), we uncovered that: 1) many adjacent progenitor genes were significantly up-regulated; and 2) the rostral Hox genes were significantly down-regulated, with a concomitant increased expression of caudal Hox genes in ESC~MNs. This phenotype was recapitulated in IG-DMRmatΔ embryos, in which Hoxc8 expression is expanded in Hoxa5on MNs. Several reports have identified that certain lncRNAs can shape the Hox epigenetic landscape by cis and trans modulation (Dasen, 2013; Rinn et al, 2007; Wang et al, 2011). In addition, we recently uncovered that a novel trans Hox-miRNA circuit can filter Hox transcription noise and control the timing of protein expression to confer robust individual MN identity (Li et al, 2017). Here, we have now added the Meg3 imprinted lncRNA to that list as a novel trans-acting lncRNA that maintains the Hox epigenetic landscape, most likely by recruiting Jarid2 to the PRC2 complex.
PRC1/2 with lncRNA: a fail-safe mechanism to guard MN epigenetic landscape
Why do MNs deploy an lncRNA-mediated strategy to maintain postmitotic cell fate by inhibiting progenitor genes and regulating Hox boundaries? The dynamic role of lncRNAs in modulating PRC2 function is well documented; ranging from recruitment, complex loading and activity control to gene targeting (Davidovich & Cech, 2015; Kretz & Meister, 2014). A recent study of Drosophila Hox genes revealed that epigenetic H3K27me3 chromatin modification functions as a legitimate carrier of epigenetic memory (Coleman & Struhl, 2017), providing compelling evidence for a physiologically significant role of chromatin modification in epigenetic inheritance. Nonetheless, the epigenetic memory carried by H3K27me3 in a postmitotic cell may still be overridden by H3K27me3-opposing demethylases (Coleman & Struhl, 2017). Our RNA-seq data revealed that two prominent H3K27me3 demethylases, Kdm6a (Utx) and Kdm6b (Jmjd3), are reactivated in postmitotic MNs (data not shown). Although the function of H3K27me3 demethylase reactivation in postmitotic MNs remains unknown, these findings raise the possibility that the epigenetic memory of the H3K27me3 landscape in postmitotic MNs might still need to be “actively” maintained to counterbalance H3K27me3 demethylase activity. Enrichment of postmitotic MN lncRNAs might therefore bridge and scaffold the PRC2/Jarid2 interaction and activity to maintain MN epigenetic memory by repressing progenitor genes and also carve MN subtype identity by repressing caudal Hox genes (Figure S6).
It is probably not surprising that some caudal Hox genes (i.e., Hoxc6, Hoxc9, and Hoxd10) that we observed to be up-regulated in vitro upon Meg3 KD were not entirely phenocopied in the IG-DMRmatΔ embryos, since this outcome is consistent with the finding that removal of Ezh2 from MN progenitors has no detectable impact on segmental Hox expression in the spinal cord (Hoxc6 and Hoxc9) (Golden & Dasen, 2012). This result also suggests that a compensatory PRC1-mediated function in vivo might make up for the loss of Meg3-mediated epigenetic maintenance in segmental MNs. However, the significant Hoxa5-to-Hoxc8 homeotic transformation in MN subtypes supports the function of lncRNAs in mediating motor pool identity. Together with previous studies on stem cell-derived MNs and embryonic MNs, our results indicate that PRC2 plays dual roles at distinct phases in developing MNs. First, it establishes the chromatin landscape in the early pMNs. Then, together with the PRC1 complex, it consolidates segmental MN identity and maintains MN pool specification by decorating caudal Hox loci, particularly at the Hox8 region (Golden & Dasen, 2012; Mazzoni et al, 2013b).
PRC2-lncRNA regulation in MNs
A previous study reported that hypomorphic Suz12−/− ESCs maintained with a low amount of H3K27me3 can differentiate into MNs, albeit with a significant increase in the expression of caudal Hoxc6 and Hoxa7 compared to wild-type cells (Mazzoni et al, 2013b). Interestingly, another study found that several PRC2 mutant ESC lines that maintain varying levels of H3K27me3 allowed for proper temporal activation of lineage genes during directed differentiation of ESCs to MNs, but only a subset of the genes that function to specify other lineages were not repressed in these cells (Thornton et al, 2014). This outcome might not be entirely surprising since other epigenetic marks, such as DNA methylation, might safeguard gene expression throughout differentiation (Manzo et al, 2017). In this study, up-regulated genes in spinal MNs upon loss of Meg3-Rian-Mirg exhibited 40% concordance (962/1598) with the up-regulated genes in Suz12−/− spinal MNs (data not shown). Altogether, these results strongly endorse the critical function of PRC2/lncRNA in perpetuating the postmitotic cell fate of cervical MNs.
Given that lncRNAs are also proposed to exert targeting of the PRC2 complex to specific genome loci (Rinn & Chang, 2012), it is tantalizing to hypothesize that Meg3 might manifest dual functions of scaffolding the PRC2/Jarid2 complex and guiding it to specific loci in different cell contexts. This scenario could partially explain why only subsets of genes in an MN context are particularly sensitive to the loss of ncRNAs from the Dlk1-Dio3 locus. Inspired by the salient Hox phenotype exhibited in the IG-DMRmatΔ mutants, we envisage using Meg3 as a paradigm to decipher the Meg3-protein-DNA interactome by ChIRP-seq/ChIRP-MS, thereby allowing us to decipher the detailed targeting mechanism of PRC2/Jarid2 involved in maintaining the epigenetic landscape during embryonic development (Chu et al, 2015).
Combinatorial and individual roles of the Meg3-Rian-Mirg lncRNA cluster
There have been multiple efforts to dissect the functions of the maternally-expressed lncRNAs in the Meg3-Rian-Mirg locus over the past decade (McMurray & Schmidt, 2012; Steshina et al, 2006; Takahashi et al, 2009; Zhou et al, 2010), but definitive results remain elusive. The difficulty is mainly attributable to two major hurdles; namely that 1) there are many DMRs that control imprinting status in upstream, promoter, and exon regions of Meg3, and 2) Meg3 might function in cis to regulate its imprinting status (Matsubara et al, 2015; Ogata & Kagami, 2016). Specifically, two Meg3 knockout mouse lines have previously been generated either by deletion of the first five exons plus approximately 300 bp of the adjacent upstream promoter region of Meg3 (~5.9 kb) (Yildirim et al, 2011) or by deletion of ~10 kb that includes the Meg3-DMR region plus the first five exons of Meg3 (Takahashi et al, 2009). Both of these Meg3 KO lines also manifested loss of maternal Rian and Mirg lncRNA expression. However, whereas the ~5.9 kb Meg3 KO line (Yildirim et al, 2011) exhibited perinatal lethality, the ~10 kb Meg3 KO line (Takahashi et al, 2009) presented a much milder phenotype in that the mice were born alive and lived up to 4 weeks after birth. It is important to point out that it is not possible to discern whether the effect of the Meg3 deletion in either animal model is due to a lack of transcription from the Meg3 promoter (leading to silencing of all lncRNAs), or due to a lack of Meg3 expression that in turn causes silencing of downstream lncRNAs. We also found that expression of most, if not all, lncRNAs in the Meg3-Rian-Mirg locus are reduced upon Meg3 KD and in IG-DMRmatΔ mutants. Therefore, it remains technically challenging to obtain a specific Meg3 KO without abrogating the expression levels of downstream lncRNAs.
Although we have further shown here that Meg3 acts as a scaffold for the PRC2/Jarid2 complex, it is still possible that Rian and Mirg could independently and/or synergistically function with Meg3 to contribute to the Hox-mediated MN subtype switching we observed in the IG-DMRmatΔ mutants. Interestingly, Rian and Mirg KO ESCs/embryos seem to have a less severe phenotype and lack homeotic transformation (Han et al, 2014; Labialle et al, 2014). Thus, it is likely that Meg3 is the major contributor to MN subtype specification in IG-DMRmatΔ embryos. Since lncRNAs are emerging as important modulators of gene regulatory networks and as epigenetic regulators of gene expression, we are endeavoring to systematically knockout individual lncRNAs by a CRISPR-Cas9-mediated approach and we anticipate that a detailed map of lncRNA functions during neural development will be uncovered in the near future.
Versatile functions of Meg3 in development and disease
Consistent with the imprinting status of the DLK1-DIO3 locus in humans, epimutations (hypermethylations) and microdeletions affecting IG-DMR and/or MEG3-DMR of maternal origin result in a unique human phenotype manifested as a small bell-shaped thorax, coat-hanger-like appearance of the ribs, abdominal wall defects, placentomegaly and polyhydramnios. One hallmark of patients with this disease, termed ‘Kagami-Ogata syndrome’ (KOS) (Kagami et al, 2015; Ogata & Kagami, 2016), is that nearly all of them display delayed gross motor development. It is currently unknown why epimutations and microdeletions of maternal IG-DMR give rise to this phenotype.
In our IG-DMRmatΔ embryos, we previously observed extra ossification at the sites where the 6th to 8th ribs attach to the sternum, similar to the malformed thorax in KOS patients (Lin et al, 2007). Interestingly, this phenotype was also observed in Hox5 mutant mouse embryos (McIntyre et al, 2007). Here, we uncovered that two isoforms of the Meg3 imprinted lncRNA are enriched in embryonic MNs and confer the fidelity of the epigenetic landscape for the Hoxa5-Hoxc8 boundary of MN subtypes. Loss of Meg3 in vitro and in vivo abrogates the Hoxa5on MNs in the brachial region, with a concomitant increase of ectopic Hoxc8on subtypes. This switch leads to erosion of Hoxa5on motor axon arborization in the proximal muscles, as well as eroded axon terminals along the tibialis anterior nerve. As Meg3 expression is also highly enriched in somites, we suggest that impairment of the Hox boundary mediated by Meg3 in the spinal cord and ribs might account for the bell-shaped thorax and motor deficit in KOS patients, potentially identifying a new therapeutic target for KOS patients.
In addition to the roles of the Meg3 imprinted lncRNA uncovered by our study, other reports have also emphasized Meg3 as being important for proper growth and development and to be a putative tumor suppressor that activates p53 and inhibits cell proliferation (Takahashi et al, 2009; Zhang et al, 2010; Zhou et al, 2007). Moreover, aberrant repression of Meg3 and other maternally-expressed lncRNAs from the DLK1-DIO3 imprinting cluster is present in several induced pluripotent stem cell (iPSC) lines. This scenario might lead to failure of these iPSCs to form viable mice (Stadtfeld et al, 2010) or to efficiently differentiate into neural lineage cells (Mo et al, 2015), raising the possibility that Meg3 might be involved in a broad spectrum of developmental processes and disease contexts. Thus, our exploration of Meg3 may also suggest new avenues for treating other diseases, such as cancers, as well as in elucidating the reprogramming mechanism of iPSCs.
EXPERIMENTAL PROCEDURES
Mouse ESC culture and MN differentiation
ESCs were cultured and differentiated into spinal MNs as previously described (Wichterle et al, 2002; Wichterle et al, 2009). Cells were trypsinized and collected for FACS at day 7 to purify GFPon neurons for qPCR analysis and strand-specific RNA-seq when required.
Mouse crosses and in vivo studies
The IG-DMRmatΔ mouse strain is described in Lin et al. (2003). Female mice carrying the deletion were mated with wild type C57BL6/J male mice to generate embryos with the maternally-inherited deletion. Mice were mated at the age of 8~12 weeks and the embryo stage was estimated as E0.5 when a copulation plug was observed. Embryos were analyzed between E9.5~E13.5. All of the live animals were kept in an SPF animal facility, approved and overseen by IACUC Academia Sinica.
Knockdown of Meg3 in mouse ES cells by shRNA
The Meg3 HuSH-29 shRNA plasmids (Origene®, cat. No. TG501330) and non-effective scrambled sequence (TR20003) were used to create stable knockdown lines of Meg3 within the Hb9::GFP ESCs. We used two different shRNA sequences to knockdown Meg3. Additionally, stable infected ESCs were selected by puromycin. Single ESC clones with good morphology and only presenting knockdown efficiencies > 90 % were picked for further expansion and characterization.
Expression analysis
ESCs or embryoid bodies were harvested for total RNA isolation by Trizol (Thermo Scientific). For qPCR analysis, total RNA from each sample was reverse transcribed with Superscript III (Thermo Scientific). One-tenth of the reverse transcription reaction was used for subsequent qPCR reactions, which were performed in triplicate with three independent experimental samples on a LightCycler480 Real Time PCR instrument (Roche) using SYBR Green PCR mix (Roche) for each gene of interest. Gapdh was used as a control for normalization. For GeneChip expression analysis, RNA was purified and amplified using the Qiagen RNAeasy kit and a one-color Low Input Quick Amp Labeling Kit (Agilent Genomics) and hybridized to a SurePrint G3 Mouse GE 8x60K Microarray. Differentially-expressed genes were defined by ranking all probes according to Moderated t-test and a fold-change threshold ≥ 2 (P < 0.001).
Chromatin immunoprecipitation (ChIP)
We followed a previously published protocol to perform ChIP-seq for ESC~MNs (Mazzoni et al, 2011; Narendra et al, 2015). Four million cells were freshly dissociated from day 7 ESC~MNs by trypsin and fixed in 10 mM HEPES pH 7.6, 1 % formaldehyde, 15 mM NaCl, 0.15 mM EDTA and 0.075 mM EGTA for 15 minutes at room temperature. After fixation, cells were quenched with 1.25 M glycine. After an ice-cold PBS wash and low-speed centrifugation, nuclear extracts were suspended with ice-cold shearing buffer (SDS included) containing protease inhibitor and sheared using a Covaris M220 system to an average chromatin size of 200 bp. Chromatin was diluted with 2X IP buffer (2 % NP-40, 200 mM NaCl in 10 mM Tris-HCl pH 8, 1 mM EDTA). Anti-H3K27me3 antibody was added to each ChIP (antibodies are listed in the resource table). Each ChIP reaction was performed in a rotator at 4 °C overnight, followed by washing in wash buffer (25 mM HEPES pH 7.6, 1 mM EDTA, 0.1 % N-Lauryl sarcosine, 1 % NP-40, and 0.5 M LiCl) at room temperature. Cross-linking was reversed at 65 °C for 16 hours with 5 M NaCl. Proteinase K was added to digest for another 2 hours at 56 °C and DNA was extracted using the ChIP DNA Clean & Concentrator™ system (Zymo Research). We treated 1 % of the input in parallel. Libraries were prepared according to the Illumina protocol and sequenced using an Illumina NextSeq™ Sequencing System.
Whole-mount staining, immunohistochemistry, and in situ hybridization
Immunohistochemistry was performed on 20-µm cryostat sections as described (Chen et al, 2011). Primary antibodies used in this study are detailed in the resource table. Whole-mount antibody staining was performed as described (Dasen et al, 2008), and GFP-labeled motor axons were visualized in projections of a Zeiss Lightsheet Z.1 microscope (400–600 µm). Unless indicated otherwise, immunohistological data shown in figures are representative of n > 3 analyzed mutants. Images for control animals are from age-matched littermates. In situ hybridizations were performed as described previously (Chen et al, 2007; Chen et al, 2011) and in the Supplementary Experimental Procedures.
EXTENDED EXPERIMENTAL PROCEDURES
KEY RESOURCES TABLE
Further information and requests for reagents may be directed to, and will be fulfilled by, the Lead Contact, Jun-An Chen (jachen{at}imb.sinica.edu.tw).
METHOD DETAILS
Immunocytochemistry
Embryos and/or embryoid bodies were fixed with 4 % paraformaldehyde (vol/vol) in phosphate-buffered saline, embedded in OCT (Tissue-Tek) and sectioned for staining; 24 hours at 4 °C for primary antibodies and 1~2 hours at 20~25 °C for secondary antibodies. Alexa488-, Cy3- and Cy5-conjugated secondary antibodies were obtained from either Invitrogen or Jackson Immunoresearch. After staining, samples were mounted with Fluoroshield with DAPI (Roche). Images were acquired with a Zeiss LSM 710/780 or LightSheet Z. 1 confocal microscope.
Subcellular RNA fractionation
We followed a previously published protocol to extract subcellular fractions of RNA (Gagnon et al. 2014). We used TRIzol (Thermo Fisher Scientific) to extract RNA and perform reverse transcription (RT) with hexamer primers. Gapdh (mRNA in cytoplasm), U1 (snRNA in nucleus), and Kcnq1ot1 (a known chromatin-associated lncRNA) were used as quality controls to verify fractionation.
RNA pull-down assay
In vitro-transcribed biotin-labelled RNAs were generated by the Biotin RNA Labeling Mix (Roche) and T7 RNA polymerase (Promega). Templates were treated with RNase-free DNase I (Promega) and the reaction mix was purified with Oligo Clean & Concentrator™ (D4060, Zymo Research). Biotinylated RNA (3 µg) was heated to 65 °C for 10 minutes and then slowly cooled down to 4 °C. After that, RNA structure buffer (10 mM Tris pH 7, 0.1 M KCl, 10 mM MgCl2) was added and the mix was shifted to room temperature for 20 minutes to allow proper secondary structure formation. Folded RNA was then mixed with 1 mg of ESC protein nuclear extract in RIP buffer (500 mM NaCl, 10 mM HEPES pH 7.5, 25 % glycerol, 1 mM EDTA, and protease inhibitor) and incubated at 4 °C for one hour. Twenty µL Dynabeads® M-280 Streptavidin (Invitrogen) were added to each binding reaction and further incubated at room temperature for one hour. Beads were washed briefly five times and boiled in SDS buffer, and the retrieved protein was detected by standard Western blot analysis.
Co-immunoprecipitation (Co-IP) and Western blot
For each IP, cells were harvested from a 10-cm dish and washed twice with ice cold PBS. Cell pellets were allowed to swell in twice the volume of cytoplasmic lysis buffer (50 mM NaCl, 10 mM HEPES-pH 7.5, 500 mM sucrose, 1 mM EDTA and protease inhibitors). Samples were incubated on ice for 10 minutes, followed by centrifugation at 2,000 rpm for 10 minutes. The cloudy supernatant cytoplasmic fraction was removed. After washing twice (50 mM NaCl, 10 mM HEPES-pH 7.5, 25 % glycerol, 1 mM EDTA and protease inhibitors), the cell pellets were resuspended in the same volume of high salt buffer (500 mM NaCl, 10 mM HEPES-pH 7.5, 25 % glycerol, 1 mM EDTA and protease inhibitors), and rotated for 30~60 minutes at 4 °C. Then cell pellets were centrifuged at 14,000 rpm for 10 minutes at 4 °C. The supernatant was incubated overnight at 4 °C with antibody and pre-cleared Protein-G beads (depending upon the antibody) to immunoprecipitate endogenous protein against the specific antibody used. We collected 10 % of cleared supernatant as input. Subsequently, IP-protein beads were washed three times with PBS and 0.01 % Tween-20, each for 5 minutes at 4 °C. IP-proteins and their interacting partners were eluted from beads in 6X reducing loading buffer at 70 °C for 15 minutes. Finally, samples were cooled down to room temperature and spun briefly to collect condensation. Standard Western blot procedures were applied using anti-Jarid2 (Novus Biologicals, NB100–2214) or anti-Ezh2 (Millipore, 17–662) antibodies. Blots were developed using HRP-conjugated anti-rabbit or -mouse antibodies, depending on the species of the primary antibody. Signals were developed and filmed by enhanced SuperSignal™ West Femto Maximum Sensitivity Substrate (Thermo, 34096). All exposures were done using hyper film.
Single molecular RNA FISH
ESC~MNs were cultured and harvested on slides. Cells were fixed in 4 % paraformaldehyde for 10 minutes at room temperature, permeabilized for 5 minutes on ice in PBS with 0.5 % Triton X-100, and then rinsed in 70 % EtOH for subsequent RNA FISH. Slides and coverslips were kept in 70 % EtOH at 4 °C until staining. Slides were then washed in wash buffer (10 % deionized formamide in 2X SSC) for 5 minutes and incubated in a dark room at 37 °C for at least 4 hours with 1 µL of probe stock solution and 100 µL of hybridization buffer (1 g dextran sulfate, 1 mL 20X SSC, 1 mL deionized formamide). Meg3 smFISH probes were purchased from Stellaris. Images were captured with a Delta Vision microscopy system.
RNA immunoprecipitation (RIP)
RIP was performed with the RNA-Binding Protein Immunoprecipitation Kit (17–700, Millipore) according to the manufacturer’s protocol with some modifications. ESC~MNs were dissociated at a concentration of 2 million cells/mL and treated with 0.3 % formaldehyde in ice-cold PBS for 10 minutes at 37 °C. Glycine/PBS was added to a final concentration of 0.125 M and each sample was incubated for 5 minutes at room temperature. After crosslinking, ten million cells were washed twice with cold PBS and then suspended in 100 µL RIP lysis buffer (with the addition of protease inhibitor and RNase inhibitor). The lysate was incubated on ice for 5 minutes and centrifuged at 14,000 rpm for 10 minutes at 4 °C. Ezh2, Jarid2, and Suz12 antibodies were added for respective IP reactions and then incubated in RIP buffer (0.5 M EDTA/RNase inhibitor) for 3 hours to overnight at 4 °C. Samples were washed at least five times with RIP washing buffer. RIP beads were resuspended in RIPA buffer (RIP washing buffer + 10 % SDS + protease K) to reverse crosslinking at 56 °C for 30 minutes. RNA samples were extracted and qPCR was performed as described above. Isolated proteins before proteinase K treatment were collected from the beads and verified by Western blot analysis. Data on retrieved RNAs was calculated from the RT/input ratio for each experiment.
Statistical analyses and graphical representations
All statistical analyses were generated with GraphPad Prism 6 (GraphPad Software). The values are shown as mean ± SD, as indicated. Student’s t-tests were used for comparisons between experimental samples and controls. Statistical significance was defined as *p < 0.05 and **p < 0.01 by Student’s t-test.
Bioinformatics procedures
RNA-seq analysis
Adapter contamination in the paired-end reads was removed using PEAT (Li et al. 2015), and the trimmed reads were aligned to the mm10 genome with STAR (Dobin et al. 2013). The standard GTF-formatted transcript annotation was defined by GENCODE (version M9) (Harrow et al. 2012), which includes many evidence-based lncRNAs. We used this annotation to aid the junction read alignment in STAR, the output of which was submitted to Cufflinks (Trapnell et al. 2010) for de novo transcript assembly with the option ‘library type; first-strand’ to allow strand-specific alignments. We followed a strategy for novel lncRNA identification similar to that suggested by a previous report (Qian et al. 2016), by which only transcripts that were longer than 200 bp, had no overlap with any known genes, and consisted of more than one exon were regarded as novel lncRNAs. We pooled these novel lncRNAs along with all known genes annotated in GENCODE and used HTseq (Anders et al. 2015) to calculate the read count aligned onto each transcript. This procedure was repeated for all RNA-seq samples in this study. The read counts of all transcripts among different samples were normalized using a TMM algorithm with the trimming option M=30 % and A=5 % (Robinson and Oshlack 2010). A general comparison of different normalization algorithms can be found in Lin et al (Lin et al. 2016). We calculated the specificity score of each transcript among the samples at different stages according to the Jensen–Shannon definition for tissue specificity scores (Trapnell et al. 2010; Cabili et al. 2011). The transcripts were split into three groups—namely protein coding genes, annotated lncRNAs, and novel lncRNAs—for which specificity score distributions were plotted and compared.
ChIP-seq analysis
Reads were trimmed by PEAT and aligned to the mm10 genome using Bowtie2 (Langmead and Salzberg 2012). Following a similar flow analysis described in our previous work (Yildirim et al. 2011; Chen et al. 2013), all alignments were extended downstream to span an exact 150 bp-long region. Extensions that exceeded the ends of chromosomes were clipped. The extended alignments were input into the genomecov functionality supported in the BEDTools suite (Quinlan and Hall 2010) to generate read coverage profiles at a base-pair resolution. The coverage for each chromosomal position was normalized according to the mappable read count. Each sample was averaged and binned to reveal major trends. To identify possible differentially-enriched histone marks among stages or treatments, we used MACS 1.4 (Feng et al. 2011) to call peaks (P-value <10−5) in each ChIP-seq sample with the corresponding input library and then overlapping peaks were merged using MAnorm (Shao et al. 2012) to reveal loci with a significant change between two samples.
Axon arborization quantification with Imaris
The 3D images acquired with a Zeiss Lightsheet Z.1 microscope were subjected to analyses in Imaris 8.4.0 (Bitplane, Zurich, Switzerland) for quantification of axon arborization. Regions of interest were segmented for detection of individual neurons. Motor nerve terminals were semi-automatically traced using the filament tracer wizard from a defined starting point. The AutoPath (no loops) algorithm was selected. Seed points detected from background signals were manually removed. Disconnected segments were removed by indicating the maximum gap length, and background subtraction was applied for noise removal. The “Filament No. Dendrite Terminal Points” tool automatically calculated the number of motor nerve terminals.
ACKNOWLEDGMENTS
We thank people in the Chen lab, particularly to Hung Lo, for reading and giving critical comments to this manuscript. Dr. Mei-Yeh Lu from the NGS Core in Academia Sinica for invaluable technical advice and help in performing RNA-seq. Experiments and data analysis were performed in part through the use of the advanced optical microscopes at the Division of Instrument Services of Academia Sinica and with the assistance of Shu-Chen Shen. We appreciate the Genomic, FACS and Imaging core facilities in IMB for considerable technical assistance. The IG-DMRmatΔ line was a kind gift from Prof. Ann Fergusson Smith of the University of Cambridge, UK, while the Dbx1Laz/+ strain was from Prof. Alessandra Pierani from Institut Jacques Monod, CNRS UMR 7592, Université Paris Diderot, Sorbonne Paris Cité, France. The NIL plasmid was a gift from Prof. Hynek Wichterle from Columbia University, USA. We also acknowledge Bernhard Payer (CRG, Spain) and Wee-Wei Tee (A*STAR, Singapore) for their insightful and critical comments and for discussing the experimental results. The IMB’s Scientific English Editing Core reviewed the manuscript. This work is funded by Academia Sinica (AS-104-TP-B09), MoST (104–2311-B-001–030-MY3), and NHRI (NHRI-EX106–10315NC). SPL was supported by MoST (104–2321-B-002–043) and JHH was supported by MoST (104–2311-B-009–002-MY3 and 105–2221-E-009–126-MY3).
Footnotes
↵# Lead contact