Collecting ribosome-bound mRNA from in vivo dendrites

We developed a strategy to collect in vivo dendritic mRNA from adult mouse brains using ribosome immunoprecipitation. Specifically, we created a transgenic mouse in which the Camk2a promoter drives expression of the epitope-tagged ribosomal protein (EGFP-L10a) through the tetracycline transactivator (tTA)–tetO system11 (Fig. 1a). Transgenic mice express EGFP-L10a at high levels in the striatum and in CA1 region of the hippocampus (Fig. 1b,c). The interneuron marker Gad1 did not overlap with the EGFP-L10a expression, confirming that within the CA1 region the transgene expression is specific to excitatory pyramidal neurons (Fig. 1d). EGFP-L10a expression was seen in the dendrites of CA1 pyramidal neurons (Fig. 1e), in agreement with previous reports of dendritic ribosome localization1,2,3. Since previous studies demonstrated the functional incorporation of EGFP-L10a into functional translating ribosomes12,13,14, the observed dendritic expression pattern of EGFP-L10a suggested the possibility of collecting dendritic mRNA by immunoprecipitating dendritically localized green fluorescent protein (GFP)-tagged ribosomes.

Figure 1: A novel method for collecting in vivo dendritic mRNA. (a) Camk2a-tTA, TetO-EGFP-L10a double transgenic mice were generated for cell-type-specific expression of EGFP-L10a. (b) EGFP-L10a expression is high in the striatum and dorsal CA1 (Green=EGFP-L10a, Blue=DAPI, Red=Gad1). Scale bar, 1 mm (c) Within the hippocampus the expression of EGFP-L10a is limited to the CA1 region. Scale bar, 0.5 mm (d) Within the CA1 region the expression of EGFP-L10a is restricted to excitatory pyramidal neurons (Green=EGFP-L10a, Blue=DAPI, Red=Gad1 and asterisk indicates Gad1-positive cell). Scale bars, 10 μm (e) EGFP-L10a is present in the dendrites of CA1 pyramidal neurons. Scale bar, 20 μm (f) Representative example of the location of somatic (S) and dendritic (D) punches in the CA1. Scale bar, 0.5 mm (g) Diagram showing the approach used for collecting ribosome-bound mRNA from in vivo dendrites. The immunoprecipitate (IP) will contain mRNA bound to ribosomes in CA1 pyramidal neuron dendrites while the supernatant (SN) will contain mRNA from other sources. (h) qPCR analysis of dendritic mRNA samples from home cage (n=6) and contextual fear conditioned (n=5) mice confirms the expected IP enrichment of Camk2a and SN enrichment of the astrocyte-specific gene Gfap. Error bars represent s.e.m. NS, not significant. Full size image

As previous in vitro studies found that ribosome association of dendritic mRNA changes after neuronal activation15,16,17,18,19,20,21, we sought to determine if this also occurs in vivo. To detect activity-induced changes, we collected ribosome-bound mRNA from mice in a resting state and from mice subjected to a novel experience. Specifically, we collected CA1 tissue punches from transgenic mice either resting in their home cage or immediately after a 500-s contextual fear conditioning trial. Expression of EGFP-L10a did not affect contextual fear conditioning behaviour (Supplementary Fig. 1a), and EGFP-L10a expression was similar between home cage and contextual fear conditioned mice (Supplementary Fig. 1b). Tissue punches were placed in either the CA1 layer containing the dendrites of pyramidal neurons (dendritic punches) or in the CA1 layer containing the soma of pyramidal neurons (somatic punches) (Fig. 1f). Accurately placed dendritic and somatic punches from individual mice were pooled and subjected to an immunoprecipitation protocol optimized for low background (Supplementary Fig. 1c–f). This enabled us to obtain immunoprecipitate (IP) fractions containing either dendritic or somatic mRNA bound to GFP-tagged ribosomes (Fig. 1g). The mRNA in both the IP and the supernatant (SN) fractions was isolated for further analysis. In agreement with the predicted presence of dendritic mRNA in the IP of dendritic punches, quantitative PCR (qPCR) analysis showed enrichment of the known dendritic mRNA Camk2a in the IP of home cage and contextual fear conditioned mice, while the glial gene Gfap was enriched in the SN of both groups, illustrating the specificity of the immunoprecipitation (Fig. 1h).

Dendritic mRNAs rapidly bind ribosomes upon novel experience

We used high throughput RNA sequencing (RNA-Seq) to perform genome-wide characterization of dendritic and somatic mRNA bound to GFP-tagged ribosomes (Supplementary Table 1). Analysis of sequencing read distribution revealed that a smaller number of sequencing reads aligned to the 3′ untranslated regions (3′UTR) in IP samples compared with SN samples (Fig. 2a). Further characterization of this 3′UTR depletion revealed a decrease in IP read coverage ~200 nucleotides after the stop codon with a concomitant increase in SN read coverage (Fig. 2b). This loss of 3′UTR reads in the IP can be explained by RNA fragmentation that occurred during the tissue processing steps and immunoprecipitation. Because ribosomes bind to the 5′UTR and coding sequence (CDS) of transcripts and fall off at the stop codon preceding the 3′ UTR, random RNA fragmentation would produce distal 3′UTR fragments that are not associated with GFP-tagged ribosomes and therefore end up in the SN (Fig. 2c). The depletion of 3′UTR reads observed in the IP samples therefore supports the predicted ribosome-bound state of the mRNAs in the IP samples.

Figure 2: RNA-Seq analysis confirms the ribosome-bound status of immunoprecipitated mRNA. (a) Dendritic immunoprecipitate (IP) samples had a smaller proportion of RNA-Seq reads mapping to the 3′UTR as compared with dendritic supernatant (SN) samples (CDS, coding sequence; FC, contextual fear conditioning; HC, home cage; UTR, untranslated region). (b) Depletion of 3′UTR reads in the dendritic IP started ~200 nucleotides after the stop codon as indicated by a decline in read coverage in the IP and a concomitant increase in read coverage in the SN. Read coverage was calculated for a set of genes that within the CA1 are only expressed in pyramidal neurons (+pyr genes, see Methods for details). (c) Diagram explaining how the depletion of 3′UTR reads in the IP confirms the expected ribosome-bound status of immunoprecipitated mRNA. As ribosomes bind to the 5′UTR and CDS of transcripts, random fragmenting of RNA would cause distal portions of the 3′UTR to remain in the SN. Full size image

The RNA-Seq data enabled us to further test the expected enrichment of dendritic mRNA in the IP samples by looking at a larger set of control genes than would be practical with qPCR analysis. For this, we used a positive-control set of 74 genes that within the CA1 are exclusively expressed in the pyramidal neurons (+pyr; for example, Camk2a and Ddn; Fig. 3a), and a negative-control set of 124 genes that within the CA1 are exclusively expressed outside of the pyramidal neurons (−pyr; for example Gad1 and Gfap; Fig. 3b). The +pyr and −pyr lists were created by manually curating the in situ images of 1,238 genes available through the Allen Mouse Brain Atlas (Supplementary Data 1). The levels of +pyr and −pyr mRNAs were quantified as Fragments Per Kilobase of gene length per Million mapped reads (FPKM) values (see Methods for details). Because of the decreased 3′UTR read coverage starting ~200 nucleotides after the stop codon in the IP samples (Fig. 2b), we calculated mRNA levels using a FPKM value based on the RNA-Seq reads that mapped upstream of 200 nucleotides after the stop codon (FPKMCDS(+); see Methods for details). By calculating the ratio of IP FPKMCDS(+) to SN FPKMCDS(+), we determined the level of IP or SN enrichment for each +pyr gene and each −pyr gene. In agreement with the Camk2a and Gfap qPCR results (Fig. 1h), +pyr genes were on an average enriched in the IP, while −pyr genes were on an average enriched in the SN (Fig. 3c). Because the +pyr and −pyr gene lists were obtained independently from our RNA-Seq expression data, the observed IP enrichment of +pyr genes provides a strong confirmation of the expected enrichment of dendritic mRNA in the IP samples.

Figure 3: Fear conditioning increases ribosome binding to dendritic mRNA. (a) Examples of +pyr control genes with exclusive expression only in CA1 pyramidal cells. Scale bar, 0.4 mm (b) Examples of –pyr control genes with expression only outside of CA1 pyramidal cells (a and b: images from Allen Mouse Brain Atlas25). Scale bar, 0.4 mm (c) In agreement with the enrichment of dendritic mRNA in the IP of dendritic punches, +pyr genes were on an average enriched in the IP (IP/SN ratio>1), while –pyr genes were on an average enriched in the SN (IP/SN ratio<1; CDS(+) FPKM values calculated from RNA-Seq data were used to calculate IP/SN ratios; red dashed line indicates IP/SN=1; error bars represent s.e.m; Wilcoxon signed rank tests versus IP/SN=1 were performed for each group: NS=not significant, *=P<0.05, ***=P<0.0001). (d) Limited enrichment of dendritic mRNA in the home cage IP as indicated by a partial overlap between +pyr and –pyr genes in a scatterplot of IP and SN expression values (CDS(+) log2(FPKM+1) values calculated from the home cage dendritic RNA-Seq data were used to obtain expression values). (e) Fear conditioning increased enrichment of dendritic mRNA as indicated by increased separation between +pyr and –pyr genes (scatterplot generated similar to (d) except contextual fear conditioning dendritic RNA-Seq data were used). The increased enrichment of dendritic mRNA indicates increased ribosome binding of dendritic mRNA as a result of fear conditioning. Full size image

Though the qPCR and RNA-Seq data of both the home cage and contextual fear conditioned samples were in agreement with an enrichment of dendritic mRNA in the IP (Figs 1h and 3c), this enrichment appeared to be stronger after contextual fear conditioning (see +pyr genes in Fig. 3c). To confirm that the IP samples from contextual fear conditioned mice differed from the IP samples of home cage mice, we performed clustering analysis of all the RNA-Seq data obtained from home cage and contextual fear conditioned IP samples. This revealed that the contextual fear conditioned IP samples clustered separately from the home cage IP samples (Supplementary Fig. 2). Furthermore, scatterplots of all the individual +pyr and –pyr genes showed a better separation between +pyr and −pyr genes after contextual fear conditioning compared with home cage (Fig. 3d,e), in agreement with a higher IP enrichment of dendritic mRNA after contextual fear conditioning. The higher IP enrichment of dendritic mRNA after contextual fear conditioning could not have been caused by increased gene transcription, as the 500 s duration of the contextual fear conditioning trial did not provide sufficient time for mRNA to be transcribed, processed and transported to dendrites22,23. The increased enrichment of dendritic mRNA in the IP after contextual fear conditioning therefore reflects changes in the ribosome binding of mRNAs that were already present in the dendrites, revealing that dendritic mRNAs rapidly associate with ribosomes following a novel experience.

Machine learning classification predicts new dendritic mRNAs

Given the broad enrichment of +pyr genes in the dendrite IP after fear conditioning (Fig. 3c,e), we anticipated that the underlying RNA-Seq data could be used for the genome-wide discovery of dendritic mRNAs. We applied a supervised machine learning algorithm to our contextual fear conditioning dendrite RNA-Seq data, thereby enabling discovery of novel dendritic mRNAs. Specifically, we employed a linear support vector machine (SVM) algorithm using the +pyr and −pyr genes as training sets with four FPKM values per gene (FPKMCDS(+) for IP and SN, and FPKM3′UTR(−) for IP and SN; see Methods for details). The FPKMCDS(+) was calculated as described earlier, while the FPKM3′UTR(−) was calculated using the RNA-Seq reads that mapped to the 3′UTR region downstream of 200 nucleotides after the stop codon. The location of the CDS(+)/3′UTR(−) split at 200 nucleotides after the stop codon was based on the observed switch in 3′UTR coverage at this location (Fig. 2b), and was further validated by performing separate rounds of machine learning classification using alternative CDS(+)/3′UTR(−) splits (Supplementary Fig. 3a,c).

Our machine learning classification generated a list of 1,890 unique mRNAs predicted to be bound to ribosomes in CA1 pyramidal neuron dendrites after fear conditioning (false positive rate: 0.056; false negative rate: 0.094; Supplementary Data 2). For genes with a high FPKMCDS(+) (>1), the classification was largely based on the FPKMCDS(+) (Fig. 4a). In contrast, we found that for genes with a low FPKMCDS(+) (<1) the classification was less based on the FPKMCDS(+) (Fig. 4b), but instead was more based on the FPKM3′UTR(−) (Fig. 4c). This indicated that including the FPKM3′UTR(−) in our machine learning algorithm enabled a more accurate classification for a subset of genes with lower expression values (Supplementary Fig. 3e–i). Machine learning produced poor classification results for the RNA-Seq data generated from home cage dendritic punches, in accordance with the incomplete separation between +pyr and −pyr genes (Fig. 3d; Supplementary Fig. 3b,d).

Figure 4: Machine learning prediction of dendritically localized mRNAs. (a) Classification of dendritic mRNAs by machine learning analysis of contextual fear conditioning dendritic RNA-Seq data (blue=dendritic, brown=background). One-dimensional density (rug) plots on the x and y axes show that mRNAs classified as dendritic have in general higher IP FPKMCDS(+) values and lower SN FPKMCDS(+) values when compared with mRNAs classified as background. One of the exceptions, Pafah1b1, is highlighted in green. Pafah1b1 is classified as dendritic despite having IP and SN FPKMCDS(+) values more similar to mRNAs classified as background. The light blue box indicates the area magnified in Fig. 4b. (b) Dendritic classification of mRNAs with low FPKMCDS(+) values (both IP and SN<1) is not based on FPKMCDS(+) values as indicated by the intermixing of mRNAs classified as dendritic and background. (c) The same mRNAs as shown in Fig. 4b, this time plotted using the FPKM3′UTR(−) values. Pafah1b1 (green) is an example of an mRNA classified as dendritic mainly based on the FPKM3′UTR(−) values. Also see Supplementary Fig. 3e–i. (d) Pafah1b1 in situ using a FISH probe shows Pafah1b1 expression in the soma of pyramidal neurons (rectangular box) and an interneuron (square box with arrow) in the CA1 region. Scale bar, 50 μm. (e) In situ hybridization of Pafah1b1 mRNA in Thy1–YFP transgenic tissue shows punctate labelling within dendrites, which is absent when using a sense probe (green=Pafah1b1 probe, red=Thy1–YFP and blue=DAPI). Scale bar, 10 μm. On the right is a magnified view of the area indicated by the white box showing a Pafah1b1 mRNA puncta located within a YFP-labelled dendrite (crosshair in z view marks same puncta shown in x and y views). Full size image

As a first validation of our machine learning results, we tested the predicted dendritic presence of Pafah1b1 mRNA using fluorescent in situ hybridization (FISH). We chose Pafah1b1 for several reasons. First, Pafah1b1 is an example of a gene classified primarily through its FPKM3′UTR(−) (Fig. 4a,c), and confirming its dendritic presence would therefore further validate the use of separate FPKMCDS(+) and FPKM3′UTR(−) values in our machine learning algorithm. Second, Pafah1b1 was previously detected in a RNA-Seq analysis of dendrite-containing CA1 neuropil, but it was not classified as a dendritic mRNA because of its known presence in interneurons that surround the dendrites of CA1 pyramidal neurons8. Confirming the dendritic presence of Pafah1b1 mRNA would therefore exemplify the benefit of our strategy for unbiased discovery of dendritic mRNAs. Third, mutations in the Pafah1b1 gene, also known as Lis1 (lissencephaly-1), are associated with autism and intellectual disability, and accordingly the Pafah1b1 protein is required for normal dendritic spine plasticity24. Demonstrating the dendritic presence of Pafah1b1 mRNA would contribute to the mechanistic understanding of Pafah1b1’s role in synaptic plasticity and neurodevelopment. FISH analysis confirmed the expression of Pafah1b1 in both excitatory neurons and interneurons within the CA1 dendritic layer, consistent with in situ images from the Allen Mouse Brain Atlas25(Fig. 4d). FISH performed on a Thy1–yellow fluorescent protein (YFP) mouse brain was used for the detection of Pafah1b1 mRNA within sparsely labelled CA1 pyramidal neurons26. This revealed punctate Pafah1b1 mRNA labelling within dendrites of CA1 excitatory neurons, thereby confirming the dendritic presence of Pafah1b1 mRNA as predicted by our machine learning analysis (Fig. 4e).

Expected soma-restricted mRNAs can localize in dendrites

We used Gene Ontology (GO) analysis to gain a more comprehensive understanding of the types of mRNAs that can localize in dendrites. To enable a comparison between predicted dendritic and somatic mRNAs, we employed machine learning classification to obtain a list of 2,903 unique mRNAs predicted to be bound to ribosomes in CA1 pyramidal neuron soma after contextual fear conditioning (false positive rate: 0.216; false negative rate: 0.133; Fig. 5a and Supplementary Fig. 4a–c; Supplementary Data 3). For the GO analysis we used the top 75th percentile in the contextual fear conditioning dendritic and somatic mRNA lists to focus on the more highly enriched genes. As expected, the dendritic and somatic lists showed different enrichment profiles (selected categories in Fig. 5b, top 20 categories in Supplementary Fig. 4d). Genes involved in translation and the cytoskeleton were the most enriched in the contextual fear conditioning dendritic list, in agreement with previous reports and suggesting the importance of increased local translation and cytoskeleton remodelling in dendrites shortly after neuronal activation27,28. Unexpectedly, the dendritic list also showed enrichment in mRNAs encoding proteins known for their functions inside the nucleus, such as those involved in chromosome organization and transcriptional regulation (Fig. 5b). While in vitro studies have observed the dendritic localization of transcription factor mRNA29, a previous in vivo study had to exclude mRNAs encoding proteins with nuclear functions from the analysis due to potential interneuron or glia origins8. The list of dendritic mRNA predicted by our unbiased classification included several gene families with well-known nuclear functions. These included H4 histones, which are part of the core histone complex30, and members of the mediator complex, which is an important regulator of gene transcription31. Out of the seven H4 histone mRNAs detected in our RNA-Seq data, three were predicted to be localized in dendrites, and out of the 21 detected mediator mRNAs, seven were predicted to be localized in dendrites (Fig. 5b).

Figure 5: Gene ontology enrichment analysis reveals unexpected classes of ribosome-bound dendritic transcripts. (a) Classification of somatic mRNAs by machine learning analysis of contextual fear conditioning somatic RNA-Seq data (green=somatic and brown=background). (b) Gene ontology (GO) enrichment analysis of dendritic and somatic mRNAs. In agreement with previous studies27,28, dendritic mRNAs were highly enriched in translation and cytoskeleton GO categories. Unexpected GO categories with dendritic mRNA enrichment included chromosome organization and transcription factor binding. GO categories that include the Pafah1b1 gene, mediator genes and H4 histone genes are indicated. Venn diagram insets show the number of unique histone H4 and mediator mRNAs that were detected in the RNA-Seq data as well as their classifications. Also see Supplementary Fig. 4. Full size image

To test the predicted dendritic presence of mRNAs encoding H4 histones and mediator proteins, we used FISH and immunohistochemisty (IHC) to image the subcellular localization of one member of the H4 histone gene family (Hist1h4j) and one member of the mediator gene family (Med8). FISH using an antisense probe specific for Hist1h4j confirmed the presence of Hist1h4j mRNA within the dendrites of Thy1–YFP-labelled CA1 pyramidal neurons (Fig. 6a). IHC using a histone H4-specific antibody resulted in the expected punctate labelling within the nuclei of CA1 pyramidal neurons, but in addition also resulted in punctate labelling within dendrites (Fig. 6b). The histone H4 antibody produced a similar punctate staining pattern in the nuclei and dendrites of Thy1–YFP-labelled pyramidal neurons in the cortex (Supplementary Fig. 5a). FISH and IHC analysis of Med8 generated results similar to the Hist1h4j results. As predicted by our machine learning results, Med8 mRNA was detected within the dendrites of CA1 pyramidal neurons (Fig. 7a). IHC with a Med8-specific antibody resulted in the expected punctate labelling within nuclei, as well as punctate labelling within CA1 and cortical dendrites (Fig. 7b; Supplementary Fig. 5b). The FISH and IHC data confirm that our list of 1,890 putative ribosome-bound dendritic transcripts can be used to predict the dendritic localization of specific mRNAs and their protein products, even when these proteins were previously assumed to be exclusively localized within the nucleus.

Figure 6: Dendritic localization of mRNA and protein encoded by the chromatin-associated gene Hist1h4j. (a) In situ hybridization for Hist1h4j shows puncta within YFP-labelled dendrites with the antisense probe, but not with the sense probe (green=Hist1h4j probe, red=YFP and blue=DAPI). The bottom panels show magnified views of the area indicated by the white box. Views from all three planes show colocalization between Hist1h4j mRNA and the YFP-labelled dendrite. (b) Histone H4 IHC results in dendritically localized puncta (green=Thy1–YFP, red=histone H4 and blue=DAPI). Magnified dendritic and somatic areas are indicated with white boxes. Dashed white lines in the magnified dendritic image outline a single dendrite. Views from all three planes show colocalization between histone H4 protein and the dendrite. A dashed white circle in the magnified somatic image outlines a nucleus with the expected presence of histone H4 protein. Scale bars, 10 μm. Full size image