Neuron
NeuroResource
The Local Transcriptome in the Synaptic
Neuropil Revealed by Deep Sequencing
and High-Resolution Imaging
Iván J. Cajigas,1,2,3 Georgi Tushev,1,2,3 Tristan J. Will,1,2 Susanne tom Dieck,1,2 Nicole Fuerst,1,2 and Erin M. Schuman1,2,*
1Max
Planck Institute for Brain Research, Max-von-Laue Strasse 3, Frankfurt am Main 60438, Germany
of Excellence for Macromolecular Complexes, Goethe University, Frankfurt am Main 60438, Germany
3These authors contributed equally to this work
*Correspondence: erin.schuman@brain.mpg.de
DOI 10.1016/j.neuron.2012.02.036
2Cluster
SUMMARY
In neurons, dendritic protein synthesis is required
for many forms of long-term synaptic plasticity.
The population of mRNAs that are localized to
dendrites, however, remains sparsely identified.
Here, we use deep sequencing to identify the mRNAs
resident in the synaptic neuropil in the hippocampus.
Analysis of a neuropil data set yielded a list of 8,379
transcripts of which 2,550 are localized in dendrites
and/or axons. Using a fluorescent barcode strategy
to label individual mRNAs, we show that their relative
abundance in the neuropil varies over 3 orders of
magnitude. High-resolution in situ hybridization
validated the presence of mRNAs in both cultured
neurons and hippocampal slices. Among the many
mRNAs identified, we observed a large fraction of
known synaptic proteins including signaling molecules, scaffolds and receptors. These results reveal
a previously unappreciated enormous potential for
the local protein synthesis machinery to supply,
maintain and modify the dendritic and synaptic
proteome.
INTRODUCTION
In eukaryotic cells, the localization of mRNA is an important
mechanism to establish or maintain cell polarity, regulate
gene expression, and sequester the activity of proteins.
Neurons, with their complex dendritic and axonal structure,
represent a special class of polarized cells with 103–104
synapses that can be modified independently. The establishment, maintenance, and regulation of this specificity are
mediated by differences in protein composition within synapses.
In neurons, mRNAs as well as polyribosomes have been
observed throughout the dendritic arbor, often hundreds of
microns from the cell body (Steward and Levy, 1982). In the
developing hippocampus, between 8% and 16% of dendritic
spines possess a polyribosome under control conditions (Ostroff
et al., 2002).
Although protein synthesis in neuronal cell bodies is undoubtedly important, emerging data indicate that local protein
translation can play an important role in synaptic development
and plasticity (Martin and Ephrussi, 2009; Richter and Klann,
2009; Sutton and Schuman, 2006). The synaptic potentiation
induced by BDNF requires local translation (Kang and Schuman,
1996) as do other forms of plasticity including long-term
facilitation in Aplysia (Martin et al., 1997), long-term depression
elicited by metabotropic glutamate receptor activation (Huber
et al., 2000), late-phase LTP (Bradshaw et al., 2003),
dopamine-induced plasticity (Smith et al., 2005), and homeostatic plasticity induced by a blockade of spontaneous
neurotransmitter release (Sutton et al., 2004, 2006, 2007).
In most cases above, the specific proteins that are locally
synthesized during plasticity have not been identified.
Several individual mRNAs have been visualized in
dendrites using in situ hybridization, including the mRNA
for the Ca2+-calmodulin-dependent protein kinase alpha
subunit, CaMKIIa (Burgin et al., 1990; Mayford et al., 1996),
MAP2 (Garner et al., 1988), Shank (Böckers et al., 2004), and
b-actin (Tiruchinapalli et al., 2003). The mRNAs localized
to growth cones of retinal ganglion cells have recently been
elucidated (Zivraj et al., 2010). Recent microarray approaches
using tissue enriched for dendrites expanded the local
transcriptome to !285 mRNAs (Poon et al., 2006; Zhong et al.,
2006) and the high-throughput in situ hybridization screen
performed by the Allen Brain Project identified 68 mRNAs
in the synaptic neuropil (Lein et al., 2007). Analysis of the
overlap between the various studies, however, yields a
surprisingly small number of mRNAs discovered by two or
more studies (Figure 1A), suggesting that the identification of
the local mRNA population is not near saturation. Here, we
used deep RNA sequencing to identify the full complement of
mRNAs present in synaptic regions (Figure 2). We focused our
attention on the CA1 area of the rat hippocampus because,
as indicated above, synapses in this region express several
forms of plasticity that require local translation. Following
sequencing and bioinformatic analysis with other data sets, we
identified 2,550 mRNAs that are associated with the dendrites
and/or axons in the hippocampal neuropil. High-resolution
imaging allowed us to validate, independently, a subset of these
mRNAs and to localize them specifically to the dendrites of
hippocampal neurons.
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Local Transcriptome in the Synaptic Neuropil
dendrites, axons, glia, and a sparse population of interneurons,
but lacks principal neuron cell bodies (Figures 1D and 1E).
Microdissection of CA1 synaptic neuropil from 120 individual
slices yielded sufficient RNA for a single deep sequencing run
(Figure 1F; 454 Technology, Roche). To maximize coverage of
the local mRNA population, poly(A) RNA was isolated and then
normalized cDNA libraries were prepared (Patanjali et al., 1991)
to enhance sensitivity to lower abundance transcripts. Two
different neuropil sequencing runs (using starting material from
two different dissections) yielded 550,442 and 571,554 reads
for a total of 1,121,196 reads with a mean read length of !400
nucleotides (Figure S1 available online). Reads were annotated
to identify the genes represented (see Experimental Procedures;
Figure S1). We chose 50% coverage of the coding sequence
(Table S1, Column F) as a threshold value for inclusion in our
subsequent analysis of the neuropil data sets yielding 8,379
unique mRNAs (Table S1). We compared this data set with the
three most recently published neuropil transcriptome data sets
obtained from microarrays (Poon et al., 2006; Zhong et al.,
2006) and high-throughput in situ hybridization analysis (Lein
et al., 2007). Using the above data set of 8,379 unique mRNAs
we found substantial overlap between our data and the
other three data sets (86%, 86%, and 91%, respectively, for
Zhong et al., 2006; Poon et al., 2006; and Lein et al., 2007)
(Figure S1; Table S4).
Figure 1. Isolation of Hippocampal RNA for Deep Sequencing
(A) Venn diagram showing overlap between mRNAs identified in three recently
published neuropil transcriptome data sets.
(B) Photograph of a slice before and after microdissection with somatic (red)
and neuropil (blue) segments outlined. Scale bar = 1 mm.
(C) Scheme of an individual microdissected slice, showing the orientation of CA1 neuron dendrites (for slice preparation, see Experimental
Procedures).
(D) Microdissected regions containing the somatic layer of CA1 are enriched
with the neuron-specific transcription factor NeuN, whereas neuropil microdissected slices are de-enriched for NeuN. Protein lysates were prepared from
neuropil, somata, and whole CA1 (CA1) tissues and analyzed by western blot
using antibodies against NeuN and b-actin.
(E) Graph shows the enrichment of proteins in the different CA1 regions.
(F) Total RNA was isolated from the tissue corresponding to the microdissected neuropil and the microdissected somatic layer. The purity of
the sample was analyzed using an Agilent 2100 Bioanalyzer. mRNAs are
distributed throughout the lanes.
RESULTS
Next Generation Sequencing of Neuropil RNA Samples
Reveals a Large Number of Previously Undetected
Neuropil mRNAs
To discover the full local transcriptome, we first microdissected
individual synaptic neuropil (stratum radiatum and lacunosum
moleculare) segments from area CA1 of the adult rat hippocampus (Figures 1B and 1C). This synaptic neuropil comprises
454 Neuron 74, 453–466, May 10, 2012 ª2012 Elsevier Inc.
Gene Ontology Analysis of Neuropil Transcriptome and
Validation and Quantification of Target Transcripts
using nCounter Nanostring
We used Gene Ontology (GO) to identify the gene families
and protein functions significantly represented by our neuropil
data set. As shown in Figure 3A and Table S2, many transcripts
fall into categories associated with aspects of neuronal function
including genes associated with dendrites, spines, and axons.
To independently validate a subset of the above genes, we
used a new technique (Nanostring nCounter; (Geiss et al.,
2008) that permits high-resolution visualization of single mRNA
molecules and allows one to obtain quantitative estimates of
the abundance of a given mRNA species. For each mRNA of
interest, two specific nucleotide probes were designed, one
that contains a six molecule fluorescent barcode and the other
that contains a biotin group to enable binding of a hybridized
mRNA to a substrate. Following hybridization with both probes,
individual mRNAs were imaged (Figure 3B) and counted based
on their identifying barcode. We detected 290 of the 292 target
mRNAs in our sample (Figure 3C), as well as several positive
controls. None of the negative control probes were detected.
To quantify the abundance of our target mRNAs, we spiked
our sample with several control mRNAs at known quantities
(see Experimental Procedures). This allowed us to obtain
concentration estimates for our target mRNAs and to observe
their relative abundance (Figure 3C; Table S5). As shown in
Figure 3C, Camk2a (CAMKIIa) is the most abundant mRNA detected in the neuropil, consistent with its role as an organizer and
regulator of synaptic function, and its detection as a localized
mRNA in earlier studies (Miller et al., 2002; Ouyang et al.,
1999). Other relatively abundant mRNAs included Shank1,
Dlg4 (PSD-95), Ddn (Dendrin), and Map1a, all previously
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Local Transcriptome in the Synaptic Neuropil
Aim
Identify the full complement of mRNAs
present in synaptic regions
Strategy
a)
Experimental Setup
b)
Sequencing data
generation
c)
Gene annotation and
classification in functional
categories
d)
Validation of
gene expression
in the neuropil
Hippocampus microdissection
RNA isolation
Preparation of normalized cDNA libraries
454 Sequencing
Figure 1
Figure S1
Figure 3
Figure S1
Table S1
Table S2
Transcriptome annotation
Gene Ontology
Digital analysis (Nanostring) and real time PCR
293 mRNAs
Figure 3
Figure 4
Table S5
Table S6
Raw list
8379 mRNAs
Glia
e)
Neuropil set
filtering
Blood
vessels
f)
Validation of
mRNA localization
Nucleus
Interneurons
Mitochondria
Figure 5
Figure S3
Figure S7
Table S8
Filtered list
2550 mRNAs
High-resolution in situ hybridization (Panomics)
in primary neurons (74 mRNAs) and in
hippocampal slices (19 mRNAs)
Figure 6
Figure 7
Figure S4
Figure 2. Flowchart of Experiments and Analysis
Shown is a description of the experiments, beginning with sample preparation and concluding with the analysis and validation of the neuropil mRNA population.
identified in published studies (Böckers et al., 2004; Herb et al.,
1997; Muddashetty et al., 2007; Tucker et al., 1989). The power
of deep sequencing, however, is its ability to detect transcripts of lesser abundance. Indeed, we identified in the
neuropil many previously undetected mRNAs such as synGAP,
Snap25, Cyfip2, and Rptor. The abundance of different
mRNAs varied over 3 orders of magnitude. We also performed
additional validation of 15 synaptic targets by real-time PCR
(Table S6).
Relative Enrichment of Transcripts in the Neuropil, Glia,
and Somata
In addition to axons and dendrites, the synaptic neuropil also
contains glial cells. We initially determined the contribution of
putative glial transcripts to our data set by conducting
Nanostring analysis of a preparation of glial cells grown in culture
(see Experimental Procedures; Figure S2). In a series of ‘‘ramp’’
experiments, we tested whether the glial cells were a significant
source of the identified neuropil transcripts by varying the
relative amounts of glial-derived sample from 100% to 0%
and, in the opposite manner, varying the relative amount of
neuropil-derived sample (Figure 4A). If the glial cells were
a significant source of a given transcript, then we would expect
this transcript to exhibit high (red) levels in the 100% glial
sample, and progressively lower levels as the relative glial
contribution was reduced. For a majority (n = 167) of the neuropil transcripts we examined, we observed the opposite
pattern: most were relatively de-enriched in the 100% glial
sample (green in Figure 4A) and showed progressive enrichment
as the glial contribution was reduced, relative to the neuropil
sample (red in Figure 4A). For a relatively small group of targets,
we observed a significant enrichment in the glial sample, these
transcripts include some well-established glial genes such as
Gfap (Figure 4B; Table S7).
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Local Transcriptome in the Synaptic Neuropil
Figure 3. Gene Ontology Analysis of
Neuropil Transcriptome and Validation and
Quantification of Target Transcripts Using
Nanostring
(A) Bar graph illustrating some transcript families
from Gene Ontology (GO) that are significantly
overrepresented in our samples.
(B) Example of Nanostring image showing unique
fluorescent bar codes for individual mRNA transcripts. Bright red spots are fiducial markers used
to register high magnification images into
a montage. Scale bar = 2 mm.
(C) Plot of individual mRNA species and their
abundance from Nanostring experiments (n = 3
experiments). A selection of mRNAs representing
synaptically relevant transcripts is indicated by red
circles. For full data set with numbers, including
many more synaptically relevant transcripts see
Table S5.
See also Figure S1.
How does the neuropil transcriptome compare to that
found in the somatic compartment? As transcription occurs
in the nucleus followed by export of the mRNA to the cytoplasm, all neuronal transcripts, regardless of their ultimate
destination, reside in the cell body for some period of time.
Thus, it is expected that, assuming perfect detection, all
dendritic transcripts should also be discovered in the cell
body. We compared our neuropil transcriptome to a somata
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data set, obtained from the microdissection of sister segments comprising
the stratum pyramidale (cell body layer)
of hippocampal area CA1. Deep sequencing (same protocol as above) of
two different somatic tissue samples resulted in 1,099,501 reads that correspond to 8,044 unique mRNAs (Table
S3). We used Nanostring to estimate
the relative enrichment of a subset of
mRNAs in somata versus neuropil. We
varied the relative amount of somatic
tissue to neuropil tissue and identified
a subset of mRNAs that is indeed enriched in the neuropil (Figures 4C and
4D). A unique cluster of mRNAs is also
apparently enriched in the cell body layer
(Figures 4C and 4D). We note here that
enrichment in somata is influenced by
many variables including transcript
abundance, decay rates, and transport
rates that have not yet been carefully
measured or quantified. Furthermore,
relative enrichment in somata does not
rule out a dendritic function. For
example, the most abundant dendritic
mRNA, Camk2a (Figure 3C), was not
detected as a dendritically enriched
transcript in two previous studies (Poon et al., 2006; Zhong
et al., 2006).
A Conservative Estimate of mRNAs Present in Synaptic
Regions
The neuropil is a composite tissue-comprising dendrites, axons,
glial cells, interneurons, and some blood vessels. To refine
our list of transcripts to those of dendritic and/or axonal origin
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Local Transcriptome in the Synaptic Neuropil
Figure 4. Relative Enrichment of Transcripts in the Neuropil, Glia, and Somata
(A) Heat map of a glia versus neuropil ramp experiment. Transcript enrichment is encoded in the heat map from low (green) to high (red). Transcripts that show
similar expression patterns are clustered together, as indicated by the colored groups to the left of the heat map.
(B) Summary graph indicating the significant enrichment of transcripts in either the neuropil (blue) or glial samples (red), (n = 3).
(C) Heat map of a somatic layer versus neuropil ramp experiment. Transcript enrichment is encoded in the heat map from low (green) to high (red). Transcripts that
show similar expression patterns are clustered together, as indicated by the colored groups to the left of the heat map. In the heat map it is evident that a clusters
of !105 and !150 transcripts are enriched in the neuropil and somata, respectively.
(D) Graph indicating those transcripts which exhibited a significant enrichment in either the neuropil (blue; n = 123) or somata (red; n = 14) (n = 3 experiments).
See also Figure S2.
we made use of recently published data sets to subtract transcripts enriched in other neuropilar cellular or subcellular
compartments (Figure 2; Figure S3). First, we expanded our
own list of glial-enriched transcripts with published data on
transcripts enriched in astrocytes and oligodendrocytes obtained via cell-type-specific expression of a fluorescent protein
(Cahoy et al., 2008; Okaty et al., 2011) and subtracted them
from the neuropil transcriptome (Figure 5A; Table S8). We
next developed a list of interneuron-enriched transcripts based
on published studies (Klausberger and Somogyi, 2008; Okaty
et al., 2011; Sugino et al., 2006) as well as in situ hybridization
data (http://mouse.brain-map.org/) and subtracted these
from our neuropil data set (Figure 5A; Table S8). We also subtracted mRNAs enriched in blood vessels (Daneman et al.,
2010) and mitochondrion (http://mitominer.mrc-mbu.cam.ac.
uk/release-1.1) as well as transcripts that code for nuclear
proteins (Figure 5A). Following subtraction of all potential
candidates, we obtained a list of 2,550 transcripts that are of
dendritic or axonal origin (Figure S3A; Table S10). These 2,550
mRNAs code for proteins that are involved in most of the cell
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Local Transcriptome in the Synaptic Neuropil
Figure 5. A Conservative Estimate of mRNAs Present in Synaptic Regions
(A) Venn diagram of the neuropil data set and its overlap with transcripts enriched in glia (astrocytes and oligodendroctyes) interneurons, mitochondria and
nucleus as well as the endothelium (blood vessels). The remaining transcripts number is 2,550.
(B) Analysis of the filtered neuropil list, showing a significant enrichment of transcripts in categories related to synaptic function and cell biological processes.
(C) Scheme of a postsynaptic compartment highlighting some of the transcript families for synaptically relevant proteins represented in the filtered neuropil list.
See also Figures S3 and S7.
biological functions known to occur in dendrites and axons
(Figure 5B); note that the subtraction of transcripts from other
compartments significantly enhanced the enrichment in these
458 Neuron 74, 453–466, May 10, 2012 ª2012 Elsevier Inc.
functions. The analysis of the individual mRNAs that are nested
in the above groups reveals a huge representation of previously
undetected synaptic proteins mRNAs (Figure 5C).
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Local Transcriptome in the Synaptic Neuropil
High-Resolution Fluorescent In Situ Hybridization
Detection of mRNA Transcripts in Hippocampal
Dendrites
To visualize neuropil transcripts in dendrites we used highresolution fluorescent in situ hybridization (Taylor et al., 2010).
Using 71 probe sets specific for individual synaptic mRNAs
we examined the subcellular localization in dissociated cultured
hippocampal neurons. As previously observed and predicted by
our Nanostring data, Camk2a and Shank1 mRNAs were
abundant in the dendrites (Figure 6A). Indeed, all of the mRNAs
for which we developed probes were detected in the dendrites
(Figure 6B; Figures S4, S5, and S6). Control experiments, either
lacking the initial probe or using a sense probe, showed no
significant detectable signal (Figures S7A–S7D). Some mRNAs
with high copy numbers within the dendrites included Cplx2,
Map1a, and Cyfip2 (Figures 6A and 6B). The mRNAs for obligate
subunits for ionotropic glutamate transmission (GluR1/a and 2/b,
gene names: Gria1 and Gria2, respectively) were detectable at
low copy number in the proximal dendrites, but not always
present in the distal dendrites (Figure 6B). In contrast, transcripts
predicted to reside in the cell body such as H3f3b, Kat7, and
Fads3 did not show any appreciable dendritic in situ signal that
extended beyond the proximal (approximately the first 25 mm)
dendrite (Figure 6B). The abundance of different mRNA types
varied both as a function of the initial concentration in the proximal dendrite and the rate of decline in the number of particles
along dendritic length (Figure 6B; Figure S6). We performed an
unbiased cluster analysis (see Experimental Procedures) to
group the dendritic mRNAs that exhibit similar distribution
patterns (Figures 6B and 6C); this clustering revealed three large
groups that differ in the way in which they distribute their mRNA
particles along the proximal-distal dendritic axis. Transcripts
that are associated with astrocytes (Cahoy et al., 2008; Doyle
et al., 2008), oligodendrocytes (Doyle et al., 2008), interneurons
(Doyle et al., 2008; Sugino et al., 2006), and endothelial cells
(Daneman et al., 2010) also did not exhibit any in situ signal in
neuronal dendrites (Figures S7E–S7I). Analysis of the different
mRNA distribution patterns indicates that the dendrite to soma
ratio for distinct mRNAs is not a constant value and is not solely
dependent on the apparent somatic concentration of an mRNA
(see Figure 6B). In addition, we quantified the ratio of the Dlg4
mRNA between the dendrites and the cell body in single neurons
and found a dendrite: soma ratio of !30:70 (Figure S5).
The above experiments validate the presence of mRNAs we
identified via deep sequencing in the dendrites of cultured
hippocampal neurons. To examine the localization of a subset
of mRNAs in a more realistic context, we adapted the high
resolution in situ hybridization technique for use in rat hippocampal slices and combined it with immunohistochemical
labeling of dendrites using an antibody to MAP2 (Figure 7A).
We focused our analysis on area CA1, the region from which
we microdissected tissue for deep sequencing and the site of
several forms of plasticity that require local translation. We
examined the localization of 19 (Dlg4, Map1a, Cacng2, Shank3,
Psd, Shank1, Cacna1i, Hpcal4, Nlgn3, Kcnd2, Camk4, Gria2, Cyfip2, Grin2a, Grik2, Kif5a, Kcna2, Actb, and Pclo; 11 are shown in
Figure 7) different transcripts and found positive evidence for
their presence within the synaptic neuropil (Figures 7A and 7B).
In some fortuitous cases, the MAP2-labeled dendrites were sufficiently well-resolved to allow us to visualize labeled mRNAs
associated with dendrites (Figure 7A). Taken together, these
data indicate that the mRNAs identified by deep sequencing
can be observed by high-resolution imaging to reside in the
synaptic neuropil of hippocampal area CA1.
DISCUSSION
A Dramatically Different Landscape for Local
Translation
The proteome of an individual synapse is the physical entity
that determines the response of a given synapse to an input,
and it is clear that, like other proteomes (e.g., Ingolia et al.,
2009), the synaptic proteome is subject to ongoing and dynamic
modification by regulated protein synthesis and degradation.
The prior identification of mRNAs resident in dendrites and
axons have yielded a largely heterogeneous mix of a small
number (100 or so) transcripts that did not suggest an ongoing
role for local protein synthesis in synaptic function, but rather
suggested that local synthesis might be used in special cases
during some forms of synaptic plasticity. Here, using next generation sequencing of hippocampal neuropil RNA samples we
reveal a surprisingly large number of previously undetected
neuropil mRNAs, suggesting that mRNA localization may be
more of a rule, than the exception. In addition, many of the
proteins that populate the synapse may originate from a local
source. Based on current reference databases (NCBI, Rattus
norvegicus transcriptome version rn4.2 2010), we estimate that
the number of unique transcripts associated with the various
cells and compartments (axons, dendrites, glia, and interneurons) of the entire hippocampal neuropil is about 8,379 mRNAs.
Using published data sets and experimental data to subtract
genes that are overrepresented in other cell types (glia, interneurons) or compartments (mitochondria and nucleus), we arrive at
a dendritic-axonal data set of !2,550 mRNAs (Table S10).
Considered together, these data sets suggest an enormous
potential for protein translation that is independent of the
principal cell somata, resident locally within the neuropil.
A Large Heterogeneity in mRNA Species Abundance and
Distribution
We used high-resolution imaging techniques to validate,
quantify, and localize a subset of the transcripts identified
through deep sequencing. Using Nanostring, we detected neuropil mRNAs that vary in their abundance over three orders of
magnitude, highlighting the sensitivity of our approaches.
Indeed, previous studies failed to identify most of the lesser
abundant mRNAs, presumably owing to the lower sensitivity of
microarray-based approaches (Figure S1). (The dynamic range
to quantify gene expression levels is up to a few hundred fold
for microarrays and >8,000-fold for RNA-Seq, Wang et al.,
2009). It is possible that some the of low-abundance transcripts
we identified are concentrated in subsets of pyramidal neurons,
rather than equally distributed across the population, as would
be expected if pyramidal cells are molecularly heterogeneous
(Doyle et al., 2008; Sugino et al., 2006). Our high-resolution
in situ hybridization data indicate that the distribution pattern of
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Local Transcriptome in the Synaptic Neuropil
A
Camk2a
Shank1
C
B
Dlg4
Cplx2
Map1a
Camk2a
Shank3
Shank1
Gabrb3
Eif4e
Camk4
Syn1
Grip1
Gria2
Gria1
Cyfip2
Grin2a
Nlgn1
Syt1
Rptor
Eif4a1
Pabpc1
Actb
H3f3b
Kat7
Fads3
Dlg4
Cplx2
Map1a
Pink1
Homer2
Camk2a
Ntrk2
Mtor
Eef2
Cacng2
Shank3
Psd
Shank1
Cacna1i
Hpcal4
Camkk2
Adcy5
Nlgn3
Cpeb4
Cpeb1
Spast
Nrxn1
Kcnc2
Kcnd2
Eif4ebp1
Sv2a
Ube3a
Hcn1
Grip2
Gabrb3
Eif4e
Fmr1
Camk4
Syp
Ngdn
Syn1
Grip1
Gria2
Gria1
Stxbp5
Fxr1
Eif2ak1
Snca
Cyfip2
Kcnd3
Grin2a
Eif4b
Hnrnpa1
App
Nlgn1
Grm5
Grin1
Als2cr4
Grik2
Syt1
Dnm1
Grik4
Rptor
Fxr2
Eif4a1
Stau2
Epha6
Cyfip1
Kif5a
Gap43
Snap25
Kcna2
Pabpc1
Calb1
Magi1
Actb
H3f3b
Kat7
Fads3
0
2
4
6
8
10
12
Dissimilarity
14
16
Figure 6. High-Resolution Fluorescent In Situ Hybridization Detection of mRNA Transcripts in the Dendrites of Cultured Hippocampal
Neurons
(A) Fluorescent in situ hybridization (FISH) signal in cultured hippocampal neurons (DIV 21) showing the presence of Camk2a and Shank1 mRNA molecules (red
particles) within the cell body and entire dendritic arbor. The neuron was immunostained with an antibody to MAP2 (green) to generate a mask that outlines the
dendrites. Scale bar = 20 mm.
(B) FISH signal in individual dendrites from cultured hippocampal neurons linearized for analysis. MAP2 immunostaining was used to generate a mask that
outlines the dendritic structure. The red particles show the transcripts for each indicated gene within the dendrites. The transcripts vary in their abundance as well
as their distribution along the length of the dendrite. Dendrites are shown in groups that display similar distribution patterns. Scale bar = 20 mm.
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Local Transcriptome in the Synaptic Neuropil
transcripts within dendrites is also heterogeneous. We identified
three main groups that differ in their spatial allocation of mRNA
particles along the proximal to distal dendrite axis. Gradients
of localized mRNAs might be used to establish or maintain gradients of protein distribution or to create local computationally
relevant subdomains within dendritic branches (Govindarajan
et al., 2011).
Our data, combined with previously published data sets
(Table S14) validates with in situ hybridization 140 mRNAs
(Table S14) within the dendrites of hippocampal slices or dissociated hippocampal neurons that were also identified by our
deep sequencing. Taking into account our data set and internal
(in situ hybridization) and external (previously published studies)
sources for validation, we assign a 95% confidence level of
dendritic localization for 90% (2,295/2,550) of our transcripts.
mRNAs for Most Protein Families Are Present in the
Local Transcriptome
The transcriptome identified here includes mRNAs that belong
to diverse classes of synaptically relevant proteins, including
ionotropic and metabotropic neurotransmitter receptors, adhesion molecules, synaptic scaffolding molecules, signaling
molecules as well as components and regulators of the protein
synthesis and degradation machinery (Figure 5C; Table S11).
This expanded list indicates that many of the proteins that
populate the synapse could arise from a local, rather than
somatic, source.
We also detected many mRNAs for proteins associated with
the presynaptic terminal, including mRNAs encoding synapsins,
synaptotagmins, synaptophysins, and active-zone molecules
(Table S10). Although axonal protein synthesis has been clearly
documented during development and regeneration (Andreassi
et al., 2010; Lin and Holt, 2008) and a large number of mRNAs
have been detected in growth cones (Zivraj et al., 2010), it
remains unclear whether mature axons of the CNS are capable
of local protein synthesis. Here, we demonstrate mRNAs coding
for proteins associated with presynaptic function are present in
the mature rat neuropil, suggesting the possibility that healthy
adult axons are the sites of protein synthesis.
We also detected the mRNAs for many membrane proteins,
including a large number of voltage-gated ion channels: 5
distinct Na+, 15 Ca2+, and 33 K+ channel subunits (Table S10).
It is known that many of these channels are expressed in
gradients from the soma to the dendrites, resulting in local
control of signaling as well as the excitability of the dendrites
(Johnston and Narayanan, 2008; Makara et al., 2009). For
example, synaptic excitation has been shown to suppress
translation of Kv1.1 (Raab-Graham et al., 2006), resulting in
enhanced excitability of pyramidal neurons. The presence of
multiple K+, Ca2+, and Na+ channel subunits mRNAs in our
dendritic/axonal data set suggests that local translation could
establish, maintain, and regulate these protein gradients,
resulting in local control of the dendritic integrative properties.
If membrane protein mRNAs are translated locally then the
machinery required for co- and posttranslational processing of
these proteins should also be localized. While it is clear that
there are some components of ER and Golgi present (Gardiol
et al., 1999; Horton and Ehlers, 2003; Horton et al., 2005; Torre
and Steward, 1996), it remains a matter of debate as to the
nature and location of membrane protein processing. It is thus
interesting that we identified mRNAs for components of the
secretory pathway as well as many enzymes associated with
the N-glycosylation pathway including key enzymes that influence ER export and complex type N-glycan biosynthesis. The
glycosylation status of a membrane protein influences its folding,
trafficking, as well as membrane residence time and function.
The detection of mRNAs for membrane proteins as well as
secretory pathway components and enzymes strengthen the
view that membrane protein synthesis and processing might
occur locally (Gardiol et al., 1999; Torre and Steward, 1996)
(Table S11).
Local translation has been implicated in neurodevelopmental,
psychiatric or degenerative diseases (Swanger and Bassell,
2011). In the local transcriptome, we discovered many mRNAs
relevant for these and other diseases including, but not limited
to, multiple Bbs transcripts (Bardet Biedl syndrome), Dgcr8
(diGeorge syndrome) Cyfip1, Fmr1 and Fxr1 and 2 (Fragile X
syndrome), Nlgn1,3, and Shank3 (Autism-spectrum disorders),
Snca (Alzheimer’s disease), and Ube3a (Angelman’s syndrome).
The localization of these mRNAs within the processes suggests
the possibility that dysregulation of mRNA localization or
translation may give rise to some of the phenotypes associated
with these diseases.
What fraction of a single cell’s transcriptome exhibits localization within the dendrites and/or axons? One previous study
provided an estimate of the CA1 neuron transcriptome number
to be !4,500 genes (Kamme et al., 2003). Our own analysis,
combining the unique mRNAs expressed in the somata (Tables
S9 and S12) and axodendritic compartments provides an
estimate of 3,508 genes (Table S13). We thus estimate that
greater than one-half of the CA1 neuron transcriptome can be
detected in the axons and dendrites. Once established within
a network, most of a neuron’s important moment-to-moment
function occurs in dendrites and axons. In addition, in an
individual CA1 pyramidal neuron the volume of axons and
dendrites is about 30–60 times greater than that of the soma,
indicating that a huge majority of the total cellular proteome
function in the neuropil, rather than the somata. Thus, viewed
from either a functional or morphological perspective, it is
perhaps not surprising that most transcripts are found in the
dendrites and/or axons. A previous study demonstrated that
deletion of Camk2a mRNA from the dendrites resulted in an
85% loss of the synaptic CaMKIIa protein (Miller et al.,
2002). This observation, together with the expanded local
(C) The transcripts are represented in groups identified by cluster analysis (see Experimental Procedures) based the distribution of mRNA particles along
the dendritic axis. The cophenetic correlation coefficient for the dendrogram is 0.8058 and the generation of each of the four labeled clusters is significant:
p < 0.001.
See also Figures S4, S5, S6, and S7.
Neuron 74, 453–466, May 10, 2012 ª2012 Elsevier Inc. 461
Neuron
Local Transcriptome in the Synaptic Neuropil
Figure 7. High-Resolution Fluorescent In Situ Hybridization Detection of mRNA Transcripts in the Synaptic Neuropil of Area CA1 of the Rat
Hippocampus
(A) Raw image from an in situ hybridization experiment using antisense probes against the Psd (pleckstrin and Sec7 domain protein) mRNA (green) in area CA1 of
rat hippocampal slices (left). Dendrites were immunostained using an anti-Map2 antibody (red). The nuclei were stained with DAPI (blue). There are several
examples where mRNA puncta are clearly present within the dendrites (arrows). In order to increase visibility when displaying larger areas of area CA1 we
processed the images by dilating the mRNA puncta in ImageJ after setting a threshold (middle). For printing purposes, images were converted for display on white
background (right). The DAPI channel was converted to a binary image, inverted, and displayed in gray to provide orientation in the CA1 region, the mRNA signal
was converted to red, and the two channels were merged using Adobe Photoshop. Scale bar = 4 mm.
(B) Distribution of mRNA puncta in CA1 from in situ hybridization experiments in hippocampal slices displayed as indicated in (A) (right panel). In some control
experiments, slices were not exposed to the probe (no probe) but to all subsequent amplification steps; in other controls, a sense probe followed by all
subsequent amplification steps was used. Experiments were performed with the indicated probes. Scale bar = 25 mm.
462 Neuron 74, 453–466, May 10, 2012 ª2012 Elsevier Inc.
Neuron
Local Transcriptome in the Synaptic Neuropil
transcriptome identified here, suggests that a substantial fraction of the dendritic and synaptic proteins may be translated at
a local, rather than somatic, source.
EXPERIMENTAL PROCEDURES
Tissue Microdissection and RNA Isolation
Hippocampal slices were prepared as previously described (Aakalu et al.,
2001). The CA1 neuropil and cell body layers were carefully microdissected
by hand from each slice. One cut was made at the stratum pyramidale-stratum
radiatum border. Another cut was made at the stratum lacunosum molecularehippocampal fissure border. Lateral cuts were made at the CA2-CA1 border
and near the end of region inferior in area CA1. To prepare sufficient tissue
for a single deep sequencing run, we dissected both hippocampi from 6 male
rats, yielding 12 hippocampi, and 120 microdissected slices. From 120 microdissected slices, we obtained !25 mg of RNA from which we estimate we obtained 3 3 109 to 8 3 109 molecules of mRNA (Sambrook and Russell, 2001).
After microdissection, the tissue was transferred to a tube containing
RNAlater (Ambion) in order to stabilize and prevent degradation of RNA.
Total RNA was extracted using Trizol (Invitrogen) following the manufacturer’s
recommendations. Briefly, the microdissected slices were homogenized
in 1 ml of Trizol using a Teflon homogenizer. The homogenate was incubated
on ice for 5 min. Two hundred microliters of chloroform was added to the
samples and mixed for 15 s. Then the samples were centrifuged for 15 min
(13,000 rpm; 4" C). The aqueous (upper) phase was collected and transferred
to a new microtube. Five hundred microliters of isopropanol was added and
the RNA was precipitated at #20" C for 30 min. The samples were centrifuged
at 10,000 rpm for 10 min. After centrifugation, the isopropanol was removed,
the pellet was washed with 1 ml of 70% ethanol and samples were centrifuged
for 5 min at 5,000 rpm. Finally, the ethanol was discarded and the RNA
pellet was air-dried.
Preparation of Glial Cell-Enriched Cultures
The cortex and hippocampus from P2 rat pups were removed and
collected in DMEM (+ Glucose, + Glutamine) containing 13 PenStrep on
ice. They were subsequently transferred to a Petri dish containing cold
DMEM (+ Glucose). The medium was aspirated and the tissue was cut into
small pieces. The chopped tissue was strained (BD Falcon Cell Strainer
40 mm; Catalog #352340) into a Falcon tube containing cold DMEM. The
solution was centrifuged for 10 min at 600 rpm. The pellet was resuspended
in 20 ml ice-cold DMEM (+ glucose, + glutamine), 10% fetal calf serum, 1%
pyruvate per brain and 20 ml were plated per 10 cm tissue culture dish. The
media was exchanged every 2 days. The relatively late stage of the rat pups,
the mechanical disruption of cells and the lack of neuronal growth factors
in the media promotes glial, but not neuronal, growth. It is also possible that
the above process may alter glial transcription resulting in differences with glial
transcriptome observed in vivo.
Preparation of Normalized cDNA Libraries
Twenty-five micrograms of total RNA (per sequencing run) was used as starting
material. For cDNA synthesis the RNA was treated with DNase and poly(A)
mRNA was isolated. (Note that the isolation of poly(A) mRNA dramatically
reduces the presence of noncoding RNAs in our sample, and, as such, we focus
on the mRNA population in this study). First-strand cDNA synthesis was conducted with a N6 randomized primer. Normalization of the sample was carried
out by one cycle of denaturation and reassociation of the cDNAs. Reassociated
double stranded-cDNAs were separated from the single-stranded cDNAs
(normalized cDNA) by passing the mixture over a hydroxylapatite column. The
cDNAs in the size range of 600–800 bp were eluted from preparative agarose
gels. Then 454 adapters were ligated to the 50 and 30 ends of the cDNAs and
they were finally amplified with 16 PCR cycles using a proofreading enzyme.
454 Next-Generation Sequencing and Annotation
cDNAs were sequenced by GATC Biotech (Konstanz, Germany). The resulting
reads were mapped to the Rattus norvegicus Transcriptome (version rn4.2
September 2010, ftp://ftp.ncbi.nih.gov/genomes/R_norvegicus/RNA).
Two sets of reference files were used. The fasta file (rna.fa) contains the
sequences used in the alignment process, while the GenBank file (rna.gbk)
provides information about start and stop positions of the coding regions in
each transcript. Reads were aligned and genes were annotated using GMAP
(Wu and Watanabe, 2005). Due to the unpredictable nature of predicted and
hypothetical records, we intentionally excluded them from the analysis.
In order to include a gene in our subsequent analysis, we selected for coding
sequences in which reads spanned 50% or more. To give readers access to
the full data set, we provide in Table S1 the identity of all genes identified
with one or more reads in coding or untranslated regions.
Data Mining of Filter Lists
As the filtering process is designed to remove transcripts that are contributed
from sources other than dendrites and axons in the neuropil region of area CA1
of the hippocampus, the first step was to identify these sources and data mine
studies that correspond to the sources of contamination. We screened results
from microarray studies performed on the same microarray chip in a different
rodent species (Mus musculus) for glia, interneurons, and endothelilal cellenriched candidates. The annotation of the chip probes was downloaded
from the NCBI GEO DataSets Repository (http://www.ncbi.nlm.nih.gov/gds).
In order to convert mouse gene ids to rat gene ids, we referred to homologous
genes described by three different sources, namely, NCBI Homolog Genes,
http://www.ncbi.nlm.nih.gov/homologene; MGI (mouse genome informatics
database), ftp://ftp.informatics.jax.org/pub/reports/index.html#nomen; and
RGD (rat genome database): ftp://rgd.mcw.edu/pub/data_release/.
The up-to-date homolog records between the three databases were
unified and a reference local database was built, associating mouse gene
records with rat gene records. This procedure was used to convert the lists
of overenriched genes from the above studies into usable measures for our
analysis. On average the lists showed more than 95% conversion rate. The
remaining genes can be explained by gene family member isoforms not
present in rat.
Mitochondria related genes were downloaded from MitoMiner Database
(http://mitominer.mrc-mbu.cam.ac.uk/release-2.0/begin.do). The nucleus
related genes were extracted from Gene Ontology annotation files (http://
www.geneontology.org/GO.downloads.annotations.shtml). Candidate genes
were selected from the Gene Ontology database based on a search for
gene products within the GO term ‘‘nuclear.’’ Since it has been shown that
transcription factors can have functions in neuronal processes, we included
in the filter only proteins that are part of the core RNA Polymerase and the
DNA replication machinery. The above lists were specific for Rattus
norvegicus. Two further data sets were provided by personal communication
from their authors including a microglia list from Ben Barres (personal
communication) and a hippocampal interneuron list from Ed Lein (Allen Mouse
Brain Atlas, 2011 and personal communication).
All incorporated references are as follows
Blood Brain Barier Enriched (Daneman et al., 2010)
Developmentally CNS Up Regulated Vascular (Daneman et al., 2010)
Endothelial Specific (Daneman et al., 2010)
Pericyte (Daneman et al., 2010)
Cortical Astrocytes (Doyle et al., 2008)
Cortical Oligodendrocytes Cmtm5 (Doyle et al., 2008)
Cortical Oligodendrocytes Olig2 (Doyle et al., 2008)
Glia Culture Enriched (Nanostring Ramp Experiment)
Forbrain Astrocytes (Cahoy et al., 2008)
Forebrain Microglia (B. Barres, personal communication)
Forebrain Oligodendrocytes (Cahoy et al., 2008)
Hippocampus Interneurons (E. Lein, personal communication)
CA1 Underrepresented (Allen Mouse Brain Atlas, 2011)
Hippocampus Interneurons (Sugino et al., 2006)
Cortical Interneurons (Doyle et al., 2008)
Mitochondrion Related (mitoMiner Database 2011)
Nucleus Related (Gene Ontology Annotation 2011)
In order to incorporate these lists in our filter data set, we first selected only
those genes that were present in the initial rat transcriptome set for alignment.
Neuron 74, 453–466, May 10, 2012 ª2012 Elsevier Inc. 463
Neuron
Local Transcriptome in the Synaptic Neuropil
In that step we equalized all lists to the initial gene pool, thus allowing us to
conduct statistics for list comparison by treating the data sets as random
samples with common source. For calculating overlapping probabilities we
used a cumulative hypergeometric distribution as described by (Fury et al.,
2006). To ensure that we compared the same labels by genes, we compiled
a table where each record contains the following fields:
Official Gene Symbol by Nomenclature
Entrez Gene ID from Entrez Reference Sequence Database (NCBI)
Offical Gene Name by Nomenclature
Reference Source
The Entrez Gene ID was used as a key field for comparison. The gene
information was extracted from weekly updated gene information files on
NCBI repository (ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/Mammalia/).
Filter Process
The filter process is conducted in two main steps. First, comparison is done
between our query data set and the filter data. We split the query list in two:
potential filtered transcripts and potential dendritic/axonal transcripts. The
second step is the assessment of false candidate after filtering.
False-negative candidates arise in the filtered list due coexpression of
those candidates in different cell types. Such records are identified and rescued
by comparing the filtered list to transcripts that are present in hippocampus
pyramidal neurons (Sugino et al., 2006) or are identified by in situ methods either
conducted by us (71 in situ probes) or by previous studies (Table S14).
False-positive candidates arise in the cleaned list due to genes that were
detected by 454 but were not present on the microarray chip from the reference studies. Those genes were checked in the Allen Brain Atlas for pyramidal
neuron expression in area CAI of the hippocampus. The genes that were
de-enriched in the investigated area were pulled out of the result list and
a false-positive rate was determined.
Gene Ontology
The Gene Ontology analysis was conducted using the Bingo Plug-In (v 2.44) for
Cytoscape (Maere et al., 2005). The Cytoscape output is a text file with the
following parameters: term id, term name, p value, x (number of genes from
the query list annotated to a certain term), X (number of genes from the query
list that are annotated to a specific ontology), n (total number of genes annotated to a certain term by the rat genome database), N (total number of genes
annotated to an ontology by the rat genome database). One file was generated
per ontology (biological process, molecular function, and cellular component).
We calculated cluster frequency, total frequency, fold change, for each term
graph level, where:
Cluster Frequency = 100 $
Total Frequency = 100 $
Fold Change =
x
X
n
N
Cluster Frequency
:
Total Frequency
Three biographs with the ancestors of all overrepresented terms in the
corresponding ontology were built. An application was developed in order to
search for the shortest path from each overrepresented term to the root of
its graph and assign the distance as the depth level for the term (Dijkstra,
1959). We used an additional custom application to combine the results
from the three ontologies in one file. The file was imported to Microsoft Excel
in order to obtain one table per query list. The table was sorted by depth
level and fold change. All terms in the table are overrepresented with p value
less than 0.05, after correction with the Benjamini & Hochberg false discovery
rate method.
Digital Analysis of Gene Expression Using Nanostring
Custom codesets were manufactured based on the accession numbers
(NCBI) of the transcripts. Each mRNA was detected by two probes of 50
464 Neuron 74, 453–466, May 10, 2012 ª2012 Elsevier Inc.
nucleotide length: a target-specific capture and a reporter probe. The reporter
probe was linked to a six-color fluorescent barcode and the capture probe had
biotin attached in order to bind the surface of the Nanostring cartridge. All
probes were designed against coding sequences (Geiss et al., 2008). One
hundred nanograms of total RNA treated with DNaseI and cleaned with the
RNeasy MinElute cleanup kit (QIAGEN) was hybridized to capture and reporter
probes for at least 16 hr at 65" C. Samples were prepared for data collection
using an automated fluidic handling system (nCounter Prep Station). After
posthybridization processing, the nCounter Digital Analyzer collected the
data by taking images of the immobilized fluorescent reporters with a CCD
camera through a microscope objective lens. All cartridges were imaged using
a 603 objective with 1,150 fields of view.
Each reaction contained positive and negative controls for hybridization.
The positive controls were from the External RNA Control Consortium
(ERCC) sequences with a synthetic template spiked in at different concentrations. The ERCC sequences were developed by a consortium looking for
nonbiological sequences to be used as controls for gene expression
experiments. The negative controls were also obtained from the ERCC set,
but are spiked without any RNA, to provide an estimate of the background
signal. Genes with stable mRNA levels throughout the different conditions
were identified by the geNorm method in order to normalize the data for
concentration variation; these mRNAs included Map1lc3b, Htt, Clcn3, Pten,
Gsk3b, Cript, and Mtor. Hierarchical clustering was applied to the normalized
counts to identify clusters in the ramp experiments. To address overrepresentation in the different compartments, a t test was conducted. Cutoff parameters for biological significance were *p < 0.05 and fold change >2. To correct
for false p values each test was bootstrapped 1,000 times.
Real-Time PCR
One microgram of RNA was treated with DNase I and subsequently reversetranscribed using the QuantiTect Reverse Transcription Kit (QIAGEN).
Dilutions (1:100) were used as template in the PCR. Each reaction contained
5 ml of template, 13 primers (QuantiTect primer assays from QIAGEN),
and 13 SYBR Green PCR master mix (Applied Biosystems). The cycling
parameters used were those recommended by the QuantiTect primer assays.
High-Resolution RNA In Situ Hybridization and Immunostaining
We prepared and maintained dissociated hippocampal neurons as previously
described (Aakalu et al., 2001). In situ hybridization was performed using
the QuantiGene (QG) ViewRNA kit from Panomics as previously described
(Taylor et al., 2010) with the following modifications. Cells (DIV 18-24) were
fixed for 30 min at room temperature using a 4% paraformaldehyde solution
(4% paraformaldehyde, 5.4% Glucose, 0.01 M sodium metaperiodate, in
lysine-phosphate buffer). The Proteinase K treatment was omitted in
order to preserve the integrity of the dendrites. After completion of in situ
hybridizations, cells were washed with PBS 13 and incubated in blocking
buffer (4% goat serum in PBS 13) for 1 hr. Neurons were subsequently
processed for immunofluorescence using standard methods (Aakalu et al.,
2001). Images were obtained from 10 micron z-stacks (!20 images) that
were acquired with 2,048 3 2,048 pixel resolution. They were analyzed using
custom applications created in MATLAB. Briefly, dendrites were straightened
and maximum intensity projections were generated. Areas of local maxima
were detected and binary masks were created. The areas were distancetransformed and a watershed algorithm was applied in order to detect single
puncta. For representation purposes, the channels corresponding to the
detected mRNA and the MAP2 staining were converted to binary images.
The mRNA puncta were dilated two times. An outline of the dendrite or
soma was generated using the MAP2 immunostaining as a mask (see
Figure S5). Both processed channels were merged using Adobe Photoshop.
In order to quantify the number of puncta for the Dlg4 (PSD-95) mRNA in the
neuronal compartments (Figures S5D and S5E), we acquired two sets of
images from each cell. Puncta in the entire dendritic field were obtained
from maximum intensity projections of 10-micron z-stacks (!20 images)
acquired using a 403 oil objective (0.73 digital zoom) with 2,048 3 2,048 pixel
resolution. Puncta in the cell body were counted from maximum intensity
projections of images taken using the same parameters described above
but using a 23 digital zoom in order to increase the resolution of the particles.
Neuron
Local Transcriptome in the Synaptic Neuropil
Individual punctae were counted manually from both sets of images. Great
care was taken to resolve and differentiate individual punctae.
For in situ hybridization in tissue, 500 mm hippocampal slices were cut with
a tissue chopper (Stölting), collected in ACSF, immersion fixed for 30 min at
room temperature using a 4% paraformaldehyde solution (4% paraformaldehyde, 5.4% glucose, 0.01 M sodium metaperiodate, in lysine-phosphate
buffer) and cryoprotected by sequential incubation in 10% (1 hr, 4" C), 20%
(1 hr, 4" C), and 30% sucrose (over night, 4" C) in PBS. Hippocampal slices
were embedded in tissue-tek (Sakura) and cryostat sectioned at a thickness
of 4 mm. Sections were collected on superfrost+ slides and stored at #80" C.
On the day of the experiment, the slices were air-dried for 10 min at room
temperature before they were covered by secure seal gaskets (Invitrogen).
To remove embedding medium, sections were washed three times in PBS
and postfixed for 10 min at room temperature in the above-mentioned fixative.
Permeabilization and in situ hybridization were carried out essentially as
described for hippocampal neurons but with additional washing steps. After
in situ hybridization, sections were washed in PBS, blocked for 1 hr with
blocking buffer (4% goat serum in PBS) and incubated for 3 hr at room
temperature with rabbit anti-MAP2 (Millipore, 1:1000) and mouse Smi312
(Covance, 1:4000) in blocking buffer. Secondary antibodies were applied
in blocking buffer for 30 min at room temperature, nuclei were stained
for 3 min with DAPI and samples were mounted in Aqua Polymount
(Polysciences). The CA1 region of hippocampal slices was imaged using
a Zeiss LSM780 confocal microscope and a 403 oil objective (plan achromate,
NA 1.4). Z-stacks spanning the entire thickness of the slice were obtained
and channels were separated and collapsed to a maximum intensity projection
in ImageJ. For representation purposes, the channels corresponding to
the detected mRNA and the DAPI staining were converted to binary images
with fixed thresholds within an experiment for control and experimental
sections. The mRNA puncta were dilated three times for better visualization.
Both processed channels were merged using Adobe Photoshop.
Clustering of mRNA Localization Patterns
Using the in situ hybridization data, each investigated dendrite was divided in
bins of 25 mm and signal puncta were counted per bin. A master dendrite was
made for every transcript with the average number of puncta per bin assigned
to the bin. We used sum norm to normalize the row expression vector for each
candidate to make transcripts comparable, normalizing for differences in total
expression levels. A hierarchical clustering algorithm was used to group the
normalized expression vectors of all transcripts. As a dissimilarity measure, we
used 1 minus the standardized covariance of the signal and the linkage option
was the average of the dissimilarities. We visualized the resulting dendrogram
in MATLAB. Four main clusters were identified by the above procedure. In order
to measure how faithfully the dendrogram preserves the pairwise distances
between the original unmodeled data points, we calculated the cophenetic
correlation coefficient. We also addressed the significance of the generation of
the four main clusters as previously described (Varshavsky et al., 2008).
SUPPLEMENTAL INFORMATION
Supplemental Information includes seven figures and fourteen tables and can
be found with this article online at doi:10.1016/j.neuron.2012.02.036.
ACKNOWLEDGMENTS
Financial support was provided in part by the DFG-funded Collaborative
Research Center 902: ‘‘Molecular Principles of RNA-based Regulation.’’ We
are extremely grateful to Mona Khan, Christian Lozanoski, and Peter Mombaerts for assistance with the Nanostring technology. We thank Ben Barres
for discussions on glial transcriptomes. We thank Ed Lein for assistance in
compiling interneuron-enriched transcripts. We thank Ina Bartnik for the
preparation of cultured hippocampal neurons. We thank Gilles Laurent,
Mona Khan, and Schuman lab members for comments on the manuscript.
Accepted: February 22, 2012
Published: May 9, 2012
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