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LncRNA RUS shapes the gene expression program towards neurogenesis

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The evolution of brain complexity correlates with an increased expression of long, noncoding (lnc) RNAs in neural tissues. Although prominent examples illustrate the potential of lncRNAs to scaffold and target epigenetic regulators to chromatin loci, only few cases have been described to function during brain development. We present a first functional characterization of the lncRNA LINC01322, which we term RUS for "RNA upstream of Slitrk3." The RUS gene is well conserved in mammals by sequence and synteny next to the neurodevelopmental gene Slitrk3. RUS is exclusively expressed in neural cells and its expression increases during neuronal differentiation of mouse embryonic cortical neural stem cells. Depletion of RUS locks neuronal precursors in an intermediate state towards neuronal differentiation resulting in arrested cell cycle and increased apoptosis. RUS associates with chromatin in the vicinity of genes involved in neurogenesis, most of which change their expression upon RUS depletion. The identification of a range of epigenetic regulators as specific RUS interactors suggests that the lncRNA may mediate gene activation and repression in a highly context-dependent manner.
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Research Article
LncRNA RUS shapes the gene expression program towards
neurogenesis
Marius F Schneider
1,2
, Veronika Müller
2
, Stephan A Müller
3,4
, Stefan F Lichtenthaler
3,4,5
, Peter B Becker
1
,
Johanna C Scheuermann
2
The evolution of brain complexity correlates with an increased
expression of long, noncoding (lnc) RNAs in neural tissues. Al-
though prominent examples illustrate the potential of lncRNAs to
scaffold and target epigenetic regulators to chromatin loci, only
few cases have been described to function during brain devel-
opment. We present a rst functional characterization of the
lncRNA LINC01322, which we term RUS for RNA upstream of
Slitrk3.The RUS gene is well conserved in mammals by sequence
and synteny next to the neurodevelopmental gene Slitrk3. RUS is
exclusively expressed in neural cells and its expression increases
during neuronal differentiation of mouse embryonic cortical
neural stem cells. Depletion of RUS locks neuronal precursors in
an intermediate state towards neuronal differentiation resulting
in arrested cell cycle and increased apoptosis. RUS associates
with chromatin in the vicinity of genes involved in neurogenesis,
most of which change their expression upon RUS depletion. The
identication of a range of epigenetic regulators as specicRUS
interactors suggests that the lncRNA may mediate gene activation
and repression in a highly context-dependent manner.
DOI 10.26508/lsa.202201504 | Received 25 April 2022 | Revised 13 May
2022 | Accepted 13 May 2022 | Published online 10 June 2022
Introduction
Most parts of a higher eukaryotic genome are transcribed at times
and in certain cells, but only a minority of the resulting RNAs are
protein-coding. Whereas many of these noncoding transcripts are
immediately degraded, others are processed into small RNAs that
form an intricate network regulating gene expression in a co- and
post-transcriptional manner. In addition, mammalian genomes
encode thousands of stable RNAs longer than 200 nucleotides,
often capped and polyadenylated, but without any obvious coding
potential (long, noncoding [lnc] RNAs) (Engreitz et al, 2016;Quinn &
Chang, 2016;Rutenberg-Schoenberg et al, 2016;Kopp & Mendell,
2018). The functions of most lncRNAs discovered in large-scale
sequencing projects remain to be explored. Guilt-by-associa-
tionstrategies correlate their presence and expression levels with
certain cellular states, including disease conditions. Increasingly,
interference strategies reveal critical roles for lncRNAs in cellular
fates and states (Lin et al, 2014;Rinn & Chang, 2020;Statello et al,
2021).
Apparently, lncRNAs arise by pervasive transcription of the ge-
nome and evolve fast. Conceivably, their structural exibility makes
them an ideal substrate for constructive neural evolutionand
predisposes them for a function in chromatin regulation (Palazzo &
Koonin, 2020;Rinn & Chang, 2020). Indeed, more than 60% of an-
notated lncRNAs in human cells are chromatin-enriched (Rinn &
Chang, 2012). In the chromatin context, lncRNAs often combine two
functions: scaffolding and targeting. The intrinsic ability of lncRNAs
to mediate positional targeting in the genome qualies them to
impose allele-specic epigenetic regulation, such as genome im-
printing, X chromosome inactivation or rDNA regulation (Yao et al,
2019;Rinn & Chang, 2020;Statello et al, 2021). Their actions may be
locally restricted close to their site of transcription in cis,orintrans
via sequence-specic hybridization with DNA or RNA. Thus, they
may guide powerful epigeneticregulators (enzymes that modify
histones or DNA) to specic loci in chromatin, or participate in nuclear
condensates (Engreitz et al, 2016;Rutenberg-Schoenberg et al, 2016;
Kopp & Mendell, 2018;Statello et al, 2021). Prominent examples of
lncRNAs recruiting regulators that dene epigenetic chromatin states,
include XIST,HOTAIR,andANRIL that bind polycomb complexes (PRC)
to silence chromosomal regions, whereas others such as HOTTIP or
certain enhancer RNAs are known to recruit activating histone
acetyltransferase or methylase complexes (Werner & Ruthenburg,
2015;Quinn & Chang, 2016).
The fraction of lncRNAs that are expressed in a tissue-specic
manner exceeds that of cell type-specic protein-coding genes
(Djebali et al, 2012). A particular rich compendium of lncRNAs is
expressed in the mammalian brain (estimated 40% of known
lncRNAs) (Mercer et al, 2010;Briggs et al, 2015;Hezroni et al, 2019),
and a strong correlation between the number of expressed lncRNAs
and mammalian brain size was reported (Clark & Blackshaw, 2017).
1
Division of Molecular Biology, Biomedical Center Munich, Ludwig-Maximilians-University, Munich, Germany
2
Division of Metabolic Biochemistry, Faculty of Medicine,
Biomedical Center Munich (BMC), Ludwig-Maximilians-Universit ¨
at München, Munich, Germany
3
Neuroproteomics, School of Medicine, Klinikum rechts der Isar, Technical
University of Munich, Munich, Germany
4
German Center for Neurodegenerative Diseases (DZNE) Munich and Neuroproteomics Unit, Technical University, Munich,
Germany
5
Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
Correspondence: pbecker@bmc.med.lmu.de
©2022Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 1of19
Brain-specic lncRNAs tend to be more evolutionary conserved
between orthologues than lncRNAs expressed in other tissues and
their genes often reside next to protein-coding genes involved in
neuronal development or brain function processes (Ponjavic et al,
2009). Indeed, lncRNAs are drivers of key neurodevelopmental
processes such as neuroectodermal lineage commitment, prolif-
eration of neural precursor cells, specication of the precursor
cells, and the differentiation of precursor cells into neurons
(neurogenesis) or other neural cell types (gliogenesis) (Briggs et al,
2015;Zimmer-Bensch, 2019).
Diverse mechanisms have been documented. For example,
lncRNA TUNA (megamind) is involved in neural differentiation of
mouse embryonic stem cells (Lin et al, 2014). The nding that
depletion of TUNA also compromised ESC proliferation and
maintenance of pluripotency illustrates the power of lncRNA to
control gene networks in diverse ways, depending on the nature of
protein effectors and the timing and context of their lncRNA in-
teractions (Lin et al, 2014). The lncRNA RMST promotes neuronal
differentiation by recruiting the transcription factor Sox2 to pro-
moters of neurogenic genes (Ng et al, 2013). The lncRNA Pinky is
expressed in the neural lineage, where it helps to maintain the
proliferation of a transit-amplifying cell population, thereby
restraining neurogenesis. This regulation takes place at the level of
transcript splicing, illustrating the versatility of nuclear lncRNAs
(Ramos et al, 2015). Other mechanisms involve the control of miRNA
availability and function, as has been shown for the primate-
specic lncND during neurodevelopment (Rani et al, 2016).
Only a small fraction of lncRNAs involved in neurodevelopment
and brain function has been studied in detail. We here describe a
novel lncRNA involved in neurogenesis, which we term RUS (for
RNA upstream of Slitrk3). The RUS gene resides at a syntenic
position in mouse and human genomes upstream of the Slitrk3
gene, which encodes a transmembrane protein involved in sup-
pressing neurite outgrowth. RUS is expressed in neural tissues only
and its expression increases during the differentiation of neural
stem cells (NSCs) into neurons. RUS is a nuclear lncRNA that in-
teracts with chromatin in the vicinity of genes involved in neuro-
genesis. Depletion of RUS results in massive alterations in the gene
expression program of neuronal progenitor cells, trapping them in
an intermediate state during differentiation and eventually leading
to proliferation arrest. Proteomic identication of RUS-interacting
proteins suggests multiple mechanisms of RUS-mediated epige-
netic gene regulation.
Results
Identication of the neuronal-specic lncRNA RUS
To identify novel, functionally relevant lncRNAs in the context of
neurogenesis, we took advantage of prior work of Ziller et al, who
proled transcription during differentiation of human embryonic
stem cells along the neural lineage (Ziller et al, 2015). Their data
include transcriptome proles of hESC-derived neural progenitors:
neuroepithelial cells (NE), early, mid and late radial glia cells (ERG,
MRG, and LRG, respectively) and their in vitro differentiated
counterparts (Ziller et al, 2015). We evaluated 553 candidate lncRNA
transcripts according to the following criteria. They should (1) only
be expressed in neural tissues, (2) be dynamically regulated during
the differentiation of neural precursor cells, and (3) be conserved
between mouse and humans (Fig 1A). Of these, 10 transcripts de-
crease and 29 increase during the differentiation of the four cell
types (Fig 1B). Among them, we identied LINC01322 as an inter-
esting candidate, as it was absent in NE, ERG, and MRG but
expressed in all differentiated cell types. Intriguingly, LINC01322 was
also expressed in undifferentiated LRG.
LncRNA genes relevant to neurogenesis are often located next to
neurodevelopmental protein-coding genes (Ponjavic et al, 2009). In
line with this observation, the gene for LINC01322 localizes up-
stream of the gene encoding the transmembrane protein Slitrk3,
which regulates neurite outgrowth (Aruga et al, 2003)(Fig 1C). In the
following, we refer to LINC01322 as RUS (RNA upstream to Slitrk3).
The location of the RUS gene is well conserved by synteny in mice
and humans between the Slitrk3 and Bche-201 genes (Fig 1C).
The murine RUS transcript, Gm20754, has two annotated iso-
forms. Two and ve exons are annotated for isoforms 1 and 2,
respectively. Both isoforms share the 232 bp exon 1, which is 75%
similar to the orthologous counterpart in humans (Fig 1C). The
sequence of mRUS exon 2 (114 bp) is conserved to 92%, but not part
of the predominant human transcript. In silico ORF predictions
revealed that the largest ORF encodes a theoretical polypeptide
of 80 amino acids (aa). Although the corresponding peptides are
not listed in the comprehensive peptide repository (http://www.
peptideatlas.org), we cannot exclude a functional role for a hy-
pothetical polypeptide encoded by this small ORF. Likewise, we
cannot exclude that RUS is processed to miRNAs (https://www.
mirbase.org/) contributing to its functionality.
Quantitative RT-PCR (RT-qPCR) analysis of the two isoforms in
different mouse adult and embryonic tissues revealed that RUS
annotated isoform 1 is the dominant form (Fig 1D). RUS expression is
restricted to neural tissues, with highest expression in the adult
hippocampus. We further explored the spatio-temporal expression
of RUS isoform 1 in the developing mouse brain. RT-qPCR analyses
of RUS-1 transcripts in cortex and hippocampus of different de-
velopmental stages (embryonic days E14 and E18, postnatal days P3
and P8, as well as adult animals) showed that RUS-1 expression
increased during cortical development and peaked on P3 when
nestin, a marker for neural precursor cells dropped. A reciprocal
expression pattern was observed in the hippocampus. Continuing
with isoform 1, we performed 39-RACE experiments to obtain the
annotated 39end (Fig S1A). However, amplication of RUS with
primers targeting the annotated 59and 39ends yielded two PCR
bands of 1.3 and 0.9 kbp. Sequencing the more abundant 0.9-kbp
PCR band revealed that it lacked exon 4 (Fig S1B).
RUS depletion leads to reduced neuronal differentiation,
proliferation arrest, and increased apoptosis
To monitor the expression of RUS during murine neurogenesis, we
differentiated embryonic cortical neural stem cells (NSCs) into
immature neurons in vitro (Kilpatrick & Bartlett, 1993;Azari et al,
2011;Mukhtar et al, 2020). Differentiating NSCs were maintained
proliferative by mitogen (bFGF) for the rst 4 d. On day 5, bFGF was
withdrawn to induce neurogenesis (Fig S2A). During a time course of
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 2of19
9 d, the expected changes in molecular marker expression were
detected via immunostaining and RT-qPCR analyses. The high
expression of the NSC marker Nestin decreased, with a concomitant
increase in RGC markers Gfap,Glast, and GluL (Figs 2A and S2A and
B), as observed elsewhere (Imura et al, 2003;Mamber et al, 2012).
Upon bFGF withdrawal, the culture acquired neuronal features with
Figure 1. RUS is a novel, conserved lncRNA involved in neurogenesis.
(A) Workow illustrating the criteria to identify candidate lncRNAs expressed in human ESC-derived NE, ERG, MRG, and LRG before and after differentiation in the data of
(Ziller et al, 2015). This led to the selection of the conserved lncRNA RUS as subject of this study performed in mouse cells. (B) Heat map of signicantly changed lncRNAs
expressed in human ESC-derived NE, ERG, MRG, and LRG before and after differentiation (two-sided ttest). Data of Ziller et al (2015) were analyzed. (C) Conservation of the
RUS gene between mouse and human genomes by synteny (top) and by sequence of exon 1 (bottom). Note that the RUS gene resides just upstream of the Slitrk3 gene in
either case. For mice, two RUS isoforms are indicated. (C, D) Expression of murine RUS-1 and RUS-2 isoforms (see panel C) in different embryonic (E-) and adult (A-) tissues:
cortex (Cor), cerebellum (Cer), hippocampus (Hip), gut, heart, kidney, liver, lung, muscle, skin, spleen, analyzed by RT-qPCR. (E) Expression of Nestin and RUS isoform 1 in
murine cortex and hippocampus at different developmental stages: embryonic day (E) 14 (n = 1 for Nestin, n = 2 for RUS), E18 (n = 5), postnatal day (P) 3 (n = 2), P8 (n = 4),
and in the adult mouse (n = 1 for Nestin, n = 2 for RUS). Error bars show the standard error of the mean. The values were normalized to expression constitutive TBP mRNA
(arbitrary units, in D and E).
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 3of19
Figure 2. RUS is involved in neuronal differentiation of murine embryonic cortical neural stem cells (NSCs).
(A) RT-qPCR analysis of expression of RUS,Map2,Gfap, and Nestin transcripts as indicated, during a 9-d time course of murine embryonic cortical NSC differentiation.
Values were normalized to the maximal expression of each RNA during the time course. Error bars show the standard error of the mean of three independent
experiments. bFGF: basic Fibroblast growth factor. (B) Experimental strategy to deplete RUS in differentiating NSC by expressing shRNAs upon lentiviral transduction.
(C) RUS levels determined by RT-qPCR in RUS knockdown cells (red, expressing shRNA
RUS
) compared with control cells (blue, expressing a scrambled shRNA
CON
). Error
bars show the SD of the mean of four individual experiments. (D) Immunouorescence visualization (left) of β-tubulin III (upper pane l)and Map2 (lower panel) in control
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 4of19
high expression of the neuronal markers Map2,Dcx, β-tubulin III, and
Mapt (Figs 2A and S2A and B). The expression level of RUS continually
increased along with the neuronal markers, reaching robust ex-
pression on day 5 of the differentiation process (Figs 2A and S2B).
To explore a potential involvement of RUS during neuronal
differentiation, we depleted RUS by RNA interference, expressing a
RUS-targeting shRNA (shRNA
RUS
) upon lentiviral transduction into
differentiating NSCs (Fig 2B and Table S2, [Moffat et al, 2006]). The
shRNA
RUS
was selected to have no predicted off-targets, whereas
signicantly reducing RUS levels. Upon expression of shRNA
RUS
,RUS
levels were typically reduced by ~50% compared with control cells
expressing a scrambled control shRNA
CON
(Fig 2C). Remarkably,
upon RUS depletion, the number of cells expressing the neuron-
specicβ-tubulin III or the dendritic marker Map2 were reduced to
37% and 8%, respectively (Fig 2D).
The specicity of the knockdown was assessed by a rescue
experiment. RUS-depleted and control cells were transduced with
lentiviruses expressing RUS isoform 1 driven by the strong CMV
promoter (Fig 2E). RT-qPCR revealed that RUS was increased roughly
20-fold compared with endogenous, wild-type levels (Fig 2F). Im-
munostaining of the cells for β-tubulin III served as a proxy for
neurogenesis (Fig 2G). RUS expression in cultures that had been
depleted of endogenous RUS largely restored the number of
β-tubulin III-positive cells but did not further increase this value in
the presence of endogenous RUS (Fig 2H).
RUS depletion led to reduced cell numbers in culture, which may
be a consequence of reduced cell proliferation or increased ap-
optosis. Our subsequent analysis suggested that both processes
contribute to cell loss. To explore proliferation effects, we sup-
plemented differentiating NSC cultures with BrdU and monitored
its incorporation by immunostaining as a measure of replication
(Fig S2C and D). RUS depletion reduced the number of BrdU-
positive, proliferating cells by 93.7% (Fig S2D). We also probed for
apoptosis. We replaced the puromycin resistance gene in the
shRNA vector by a GFP gene to visualize knockdown cells while
avoiding cell death because of puromycin selection (Fig S2C). Im-
munostaining for cleaved caspase 3 in GFP-positive cells revealed a
ninefold increase in apoptosis in shRNA
RUS
-expressing cells
compared with a very low level in control cultures (Fig S2E). We
conclude that the depletion of RUS in differentiating NSCs inhibits
cell proliferation and induces apoptosis.
Depletion of RUS locks neural progenitor cells in their
differentiation stage
For an in-depth characterization of the shRNA
RUS
knockdown
phenotype in differentiating NSC we monitored transcriptional
changes by RNA-seq analysis. We established the transcriptome at
days 5 and 7 after seeding, when endogenous RUS expression is
drastically increased, in cells either treated with shRNA
RUS
or
shRNA
CON
(Fig S3A and Table S3). RNA interference by shRNA
RUS
reduced RUS levels to roughly 50%, as before (Fig S3B). Despite this
incomplete depletion, the principal component analysis of four
replicates clearly separated shRNA
CON
and shRNA
RUS
transcriptome
proles at both time points (Fig S3C).
Next, we determined differentially expressed genes (Fig S3D and
Table S3) and analyzed enriched gene ontology (GO) classications
(Mi et al, 2013) among the up- and down-regulated genes, sepa-
rately for the two time points. Consistent with ndings that many
lncRNAs regulate the expression of genes in the vicinity of their
sites of transcription, the expression of the Slitrk3 was signi-
cantly reduced after RUS depletion (Table S3). In addition, the
depletion of RUS massively affected the transcriptome, arguing
that RUS also acts in trans. On day 5, 4,978 genes (24%) were
transcribed at elevated levels under reduced RUS levels and
4,586 genes (22%) were repressed (Fig S3D). The expression
changes were even more profound on day 7, when 6,623 genes
(30%) and 6,456 genes (29%) were up- or down-regulated,
respectively.
In agreement with the observed increase in apoptosis upon RUS
depletion, we found the GO annotations associated with cell
deathand apoptosis(represented by positive regulation of
apoptosisin Fig 3A) enriched among the induced genes on both
days 5 and 7, exemplied by genes encoding, Bak1, and Foxo3. Fig 3B
shows these genes among the 50 most deregulated genes enriching
for the GO annotations: cell-death,”“neurogenesis,”“cell-cycle
and microtubule-based process.Annotations represented by GO
classications cell cycleand microtubule-based process(Fig 3A)
were most signicantly enriched among the down-regulated genes
on both days, in support of the reduced BrdU incorporation (Fig S2E)
and indicative of proliferation arrest (Fig 3A and B). Interestingly,
genes with GO annotations relating to neurogenesisand neuron
differentiationwere mildly enriched among the down-regulated
on day 5, but strongly enriched among the induced genes on day 7
(Fig 3A and B). Of note, at this level of analysis direct and indirect
effects cannot be distinguished.
To explore the effects of RUS depletion in our RNA-seq data in
more detail, we determined the read counts of several prominent
genes that characterize the in vitro differentiation process (Fig 3C).
We assessed the proliferation state (Pcna and Ki67), the NSC/RGC
markers Sox2,Pax6, and Gfap as well as the neuronal markers
Neurog2,Neurod1,Map2,Camk2a,Grin3a, and Gabrb1. In addition,
we focused on the Notch1/2 and sonic hedgehog (Shh) signaling
pathways regulating the expansion of RGCs and transit-amplifying
intermediate progenitor cell populations. Notch1/2, its ligand Dll1
and their downstream effectors Hes1,Neurog2, and Ascl1 form an
oscillatory network that regulates RGC cell renewal (Hatakeyama &
Kageyama, 2006;Wang et al, 2016;Ivanov, 2019;Sueda & Kageyama,
(shRNA
CON
) and knockdown (shRNA
RUS
) cells using specic antibodies (magenta). Nuclei were stained with DAPI (49,6-diamidin-2-phenylindol, blue). Scale bar = 25 μm.
Quantication of percentage of immune-positive cells by ImageJ (right). The bar diagrams show the percentage of positive cells. Error bars show the SD of four
independent experiments. (E) Experimental strategy to rescue the RUS-depletion phenotype in differentiating NSC by lentiviral overexpression of RUS.(F) RUS levels were
determined by RT-qPCR in control (shRNA
CON
) and knockdown (shRNA
RUS
) cells. Where indicated (+), RUS was overexpressed from a CMV promoter. Error bars show the
SD of four independent experiments. The dashed line highlights the level of RUS in (shRNA
RUS
) cells. (G) β-tubulin III immunostaining in control (shRNA
CON
) and knockdown
(shRNA
RUS
) cells as a function of RUS overexpression. Nuclei are stained with DAPI. Scale bar = 50 μm. (G, H) Quantication of β-tubulin-III immunostaining of cultures as
in (G). Error bars show the SD of four independent experiments (*P< 0.05, **P< 0.01, ***P< 0.005).
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 5of19
Figure 3. Transcriptome changes upon depletion of RUS.
(A) Enriched gene ontology (GO) classications among genes down-regulated (blue) or up-regulated (orange) upon RUS depletion at days 5 and day 7 of culture, as
indicated. Circle size indicates the number of deregulated genes compared with the total number of genes enriched in the respective GO annotation (100% = 1). (B) Heat
map showing the top 50 deregulated genes enriching for the GO annotations cell-death,”“neurogenesis,”“cell-cycle,and microtubule-based processon day 5 (left)
and day 7 (right) of culture. Note that these are different genes. The genes were sorted by GO annotations and difference between shRNA
CON
and shRNA
RUS
.
(C) Expression levels of the indicated marker genes on day 5 and day 7 of culture in control (shRNA
CON
, blue) and knockdown (shRNA
RUS
, red) cells were determined by
RNA-seq (TPM values were normalized to those of the control cells on day 5. Error bars show the SD).
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 6of19
Figure 4. Localization of RUS to chromosomal sites.
(A) Browser view of two examples of RUS localization close to relevant neurogenic genes. The RUS ChIRP tag density of the three replicates is plotted in separate tracks
in the genomic regions of the Kcna1 (top) and Dclk2 (bottom) genes. For orientation, the respective chromosomal regions are displayed above and the gene models below
the traces. (B) Heat map showing the expression changes of 66 RUS putative target genes upon RUS depletion (shRNA
RUS
, red) or in control cells (shRNA
CON
, blue) on days 5
and 7. Replicate identiers are indicated below the columns. Genes were hierarchically clustered using Euclidean distance based on their combined expression on both
days. This yields two clusters depending on whether genes are activated or repressed upon RUS deplet ion. Thegene names are indicated to the right of the 7-d heat map.
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 7of19
2019). We also included Rest as a transcriptional repressor of
neuro-specic genes which helps to maintain the NSC state
(Schoenherr & Anderson, 1995;Mukherjee et al, 2016).
Our RNA-seq analysis conrmed that the proliferative markers
Pcna and Ki67 were robustly down-regulated on both day 5 and day
7(Fig 3C). The NSC/RGC markers Sox2,Pax6, and Gfap were less
affected. However, the substantially reduced expression of the
neuronal cell fate commitment markers Hes1,andShh as well as of
the neuronal markers: Neurog2,Neurod1,Camk2a,Grin3a,andGabrb1
conrmed our earlier notion that depletion of RUS compromises
neuronal differentiation. Of note, the expression of those genes that
are most strongly induced during neurogenesis between days 57
(i.e., Shh,Neurog2,andNeurod) was most strongly affected by RUS
depletion (Fig 3C). The increased expression of Notch2 is consistent
with the observed maintenance of NSC/RGC markers, the reduced
expression of cell cycle genes as well as genes involved in neuro-
genesis (Engler et al, 2018;Mase et al, 2021). The induction of Rest at
day 7 suggests a mechanism involving chromatin regulation.
We conclude that RUS is required for efcient proliferation and
for differentiation of neuronal precursor cells in this in vitro system.
The concomitant inhibition of cell proliferation (and hence cell
renewal) and neurogenic differentiation may leave neuronal pro-
genitor cells with conicting signals that trigger apoptosis. The
observation that at day 7 the most deregulated genes with an-
notated GO term neurogenesisare activated upon RUS depletion
(Fig 3B) prompts the speculation that RUS may be involved in the
repression of transcription. Again, direct and indirect effects cannot
be distinguished at this point.
RUS associates with chromatin of key neurodevelopmental genes
As a rst step towards dening the mechanism through which RUS
regulates gene expression, we determined the subcellular locali-
zation of RUS. After 2 d in culture, cells were fractionated into the
cytoplasm, nucleoplasm and chromatin. RT-qPCR analyses showed
that RUS is enriched in the chromatin fraction, similar to the
splicing-associated lncRNA MALAT (Fig S4A).
To explore whether RUS localizes to specic chromosomal re-
gions like other regulatory lncRNAs, we applied the ChIRP (Chro-
matin Isolation by RNA Purication) methodology (Chu et al, 2011).
Cells were harvested at day 7 of differentiation and RUS was iso-
lated by hybridization with two independent probe sets (oddand
even). The experiment was carried out in biological triplicate. All
three isolations effectively retrieved RUS (~30% of input) and
strongly enriched RUS over control RNAs TBP mRNA,MALAT, and
XIST (Fig S4B). Between 157 to 203 peaks were scored in individual
experiments, of which 129 (67%, Fig S4C) overlapped in all three
experiments (Table S4).
Although we considered only peaks enriched by both probe sets,
several enriched genomic sites contained sequences with similarity
to one of the used oligonucleotide probe sequences. After re-
moving them, 94 high-condence putative RUS binding sites
remained for further analysis (for simplicity called RUS binding
sitesbelow). Genomic annotation revealed that four of them (4.3%)
mapped to promoters, but the majority predominantly localized to
intergenic (35.1%) or intronic (28.7%) regions, compatible with long-
range regulatory elements. About a third of the locations mapped
close to degenerate repetitive elements of various types, such as
LINEs (4.2%), SINEs (12.8%), LTR (6.4%), and simple repeats (8.5%)
(Fig S4D). GO analysis of the active genes next to RUS binding sites
yielded an enrichment of the terms forebrain development,
neurogenesis,and generation of neurons.Among those are the
genes encoding the microtubule-stabilizing protein Dclk2 and the
potassium voltage-gated channel Kcna1 (Fig 4A, two further tracks:
Arid1b and Bin1 in Fig S4E). Both genes play a pivotal role in neuron
differentiation (Shin et al, 2013;Chou et al, 2021).
Following the hypothesis that RUS binding to chromatin is in-
volved in regulating near-by genes, we determined the expression
changes of genes residing next to RUS binding sites (referred to as
putative target geneshenceforth) using the RNA-seq data of RUS
knockdown samples. Of the 94 putative target genes, 66 were ro-
bustly expressed in differentiating NSC (Fig 4B). The number of
genes that changed their expression increased from day 5 to day 7
(54% and 77% of genes with altered expression, respectively), in line
with the increase of RUS expression between days 5 and 7 of
differentiation (Table S4).
Hierarchical clustering of expression separates putative target
genes into two distinct clusters (Fig 4B). Cluster I contains genes
signicantly down-regulated on both days, whereas cluster II
represents genes with enhanced expression, predominantly on day
7. The heat map shows several cluster II genes with reduced ex-
pression on day 5 after RUS depletion. Because RUS depletion was
less effective on day 5, we calculated the overall correlation of RUS
expression and its putative target genes (Fig 4B, purple-to-green
boxes to the right of heat maps). If we assume direct effects of RUS
binding on target gene expression, we expect a positive correlation
of genes with reduced expression with RUS depletion (essentially
genes in cluster I) and a negative correlation of genes with en-
hanced expression upon RUS depletion (predominantly cluster II
genes on day 7). This is indeed largely the case (Fig 4B). Quanti-
cation of the mRNA levels of Bin1,Kcna5,Arid1b,Dclk2,Dpp9, and
App by RT-qPCR conrmed the increase in these target genes after
RUS depletion on day 7 (Fig 4C). Remarkably, the expression of
genes that are repressed on day 5 and activated on day 7, for
example, Arid1b,App, and Kcna1 (Fig S4F), correlates positively on
day 5 and negatively on day 7 with RUS expression, in support of a
direct effect of RUS on close-by genes. Our results thus suggest that
RUS may mediate both, activating and repressive regulation.
RUS interactors suggest epigenetic regulatory mechanisms
LncRNAs usually elicit their gene regulatory effects through
interacting effector proteins. To explore how RUS may mediate
both, activating and repressive functions, we sought to identify
The purple-green code to the right of each individual heat map indicates the degree of correlation between RUS and putative target gene expression. (C) Expression
levels of the putative target genes: Bin1 (n = 3 or 7 [3/7] for days 5 or 7, respectively), Kcna5 (n = 7/7), Arid1b (n = 3/9), Dclk2 (n = 3/4), Dpp9 (n = 5/5), and App (n = 3/5) on day 5
and day 7 of culture in control (shRNA
CON
, blue) and knockdown (shRNA
RUS
, red) cells were determined by RT-qPCR (values were normalized to those of the control cells
on day 5, error bar show the standard error of the mean, *P< 0.05, **P< 0.01, ***P< 0.005).
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 8of19
RUS-binding proteins. When mouse and human RUS sequences are
compared, a remarkable degree of conservation of exon 1 stands
out (Fig 1C). Because such conservation may be indicative of
important functional interactions, we compared interactors of
complete RUS with a 59-deleted RNA (Δ59-RUS), lacking exon 1.
Both RNAs were tagged with 5 MS2 stem-loop structures at the 39
end, enabling afnity purication via binding to MS2-binding
protein (MS2BP) (Johansson et al, 1997;Zhou et al, 2002;Tsai et
al, 2011).
Because differentiating NSCs cannot be obtained in sufcient
amounts for RNA-afnity purication, we established an RNA-
afnity purication protocol using the well-established Neuro2A
cell line. RUS is normally not expressed in these cells and so our
experiment identies potential protein interactors that are not
relevant in these cells. To assure an equivalent expression of both
RNAs, we rst generated Neuro2A derivatives by inserting an FRT
recombinase site into the genome through lentiviral transduction.
These clonal cells were then transfected with FRT-anked RUS
expression constructs along with a ipase expression plasmid
(Andrews et al, 1985;Sauer, 1994;See et al, 2002). Clones containing
integrated RUS expression cassettes were expanded and analyzed.
These clones express comparable levels of either full-length RUS or
Δ59-RUS.
Lysates of RUS- and Δ59-RUS-expressing cells were incubated
with recombinant MS2-binding protein (MS2BP), which in turn was
tagged with a maltose-binding protein (MBP) (see scheme in Fig 5A).
MS2BP-bound RNA was retrieved by absorption of MBP to amylose
beads, captured proteins were eluted with RNAse A treatment and
Figure 5. RUS interacts with components of the nuclear pore, -lamina, and nucleolus.
(A) Schematic overview of the afnity purication of RUS-interacting proteins (colored spheres). RUS RNA (green), tagged with ve MS2 stem-loop structures (orange) is
stably expressed in Neuro2A cells. The RNA is afnity-puried by binding to MS2BP-maltose binding protein on an amylose resin. For details, see text. (B) Volcano plot
showing afnity-puried nuclear proteins that bind differentially to full-length RUS (left) or a RUS RNA from which exon 1 was deleted (Δ59-RUS). Proteins with a change
greater than 2 and a P-value smaller than 0.002 are considered robust interactors and annotated by their gene name. The dashed gray hyperbolic curves depict a
permutation-based false discovery rate estimation (P= 0.05; s0 = 1). Some proteins are color-coded: proteins of the nuclear lamina (red), nuclear porins (orange), and
nucleolar proteins (green). (C) RT-qPCR analysis of RUS co-immunoprecipitated with antibodies against Sox2, Brd2, Lbr, and control IgG from differentiating neural stem
cells. Error bars show the SD (***P< 0.01 compared with IgG purication).
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 9of19
Table 1. Table includes afnity-puried nuclear proteins that bind more than full length RUS (P-value < 0.002, log
2
(mut/RUS) < 21) and the localization
to nuclear compartments as nucleolus, nuclear lamin, and nuclear pore.
UniProt ID Gene name 2Log
10
(P-value) Log
2
(mut/) Only detected by full length RUS Nuclear compartment
Q7JJ13 Brd2 3.44 1.27 No
Q8R149 Bud13 3.20 1.61 No
O35658 C1qbp 3.66 2.06 No
Q9JJ89 Ccdc86 4.79 1.55 No
Q99LM2 Cdk5rap3 2.73 1.51 No
Q8K327 Champ1 4.35 1.52 No
Q921N6 Ddx27 5.15 2.14 No Nucleolus
O08749 Dld 6.00 2.13 No
Q9D2G2 Dlst 3.57 2.49 No
O08579 Emd 4.27 2.69 No Nuclear lamin
O35130 Emg1 5.19 1.08 No Nucleolus
P62806 Hist1h4a 3.63 1.98 No
Q9DC33 Hmg20a 4.31 2.16 No
P38647 Hspa9 6.57 1.99 No
Q3U9G9 Lbr 2.92 2.71 No Nuclear lamin
P48678 Lmna 5.43 1.18 No Nuclear lamin
P14733 Lmnb1 5.63 3.73 No Nuclear lamin
P21619 Lmnb2 4.90 3.00 No Nuclear lamin
Q6PB66 Lrpprc 3.00 2.05 No
Q810V0 Mphosph10 3.71 2.72 No Nucleolus
Q91VE6 Nifk 4.00 1.67 No Nucleolus
Q9WV70 Noc2l 2.99 1.26 No Nucleolus
Q8BH74 Nup107 3.23 1.14 No Nuclear pore
Q8R0G9 Nup133 3.34 1.70 No Nuclear pore
Q9CWU9 Nup37 4.06 2.31 No Nuclear pore
P59235 Nup43 6.28 2.93 No Nuclear pore
Q9JIH2 Nup50 5.74 1.13 No Nuclear pore
Q8BTS4 Nup54 4.34 3.37 No Nuclear pore
Q8R480 Nup85 3.47 1.98 No Nuclear pore
Q8BJ71 Nup93 4.32 3.14 No Nuclear pore
Q6PFD9 Nup98 5.50 2.68 No Nuclear pore
Q8R332 Nupl1 4.88 3.66 No Nuclear pore
P67778 Phb 4.68 2.54 Yes
O35129 Phb2 5.75 2.48 Yes
Q9WTU0 Phf2 3.19 1.48 No
Q8R3C6 Rbm19 4.06 1.51 No
Q9JJT0 Rcl1 3.08 1.63 No Nucleolus
Q91WM3 Rrp9 5.44 1.36 No Nucleolus
Q9CYH6 Rrs1 3.75 1.45 No Nucleolus
Q8R2U0 Seh1l 3.23 1.82 No Nuclear pore
Q91ZW3 Smarca5 3.74 1.30 No
Q8C4J7 Tbl3 3.78 1.41 No Nucleolus
(Continued on following page)
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 10 of 19
identied by LCMS, using label-free quantication (LFQ) (Cox &
Mann, 2009).
Full-length RUS enriched many more proteins in comparison to
Δ59-RUS (Fig 5B and Table S5). While we cannot exclude that this is
due to the increased size of the RUS RNA, this seems unlikely
given the size difference of 912 (RUS) versus 679 nucleotides (Δ59-
RUS). Proteins with a fold-change greater than 2 and a P-value
smaller than 0.002 were considered robust and specic binders.
Only nine proteins were puried selectively along with Δ59-RUS.
By contrast, 49 proteins were enriched by co-purication with
the full-length construct and therefore considered exon 1-
specic interactors (Tables 1 andS5).Amongthem,Phb,Phb2,
Tor1aip1, and Utp3 were puried exclusively by the full-length
RUS RNA.
Phb and Phb2 correspond to the prohibitin complex, a mito-
chondrial regulator with neuroprotective functions and nuclear co-
repressor of cell cycle-regulated genes (Koushyar et al, 2015).
We also found nd numerous components of the nuclear pe-
riphery, most prominently subunits of the nuclear pore complex
(Nupl1, Nup37, Nup43, Nup50, Nup54, Nup85 Nup93, Nup98, Nup107,
Nup133, and Seh1l orange in Fig 5B) and several constituents of the
nuclear lamina: emerin (Emd), lamins A, B1, and B2 (Lmna, Lmnb1,
and Lmnb2), lamin B receptor (Lbr) as well as the lamin A/B binding
protein Tor1aip1 (red in Fig 5B).
Furthermore, RUS exon 1 retrieved many nucleolar proteins
(Ddx27, Emg1, Mphosph10, Noc2l, Nifk, Rcl1, Rrp9, Rrs1, Tbl3, Utp3,
Wdr3, Wdr12, and Wdr43 green in Fig 5B) and some interesting
chromatin regulators (e.g., the bromodomain protein Brd2, the
chromatin constituent Hmg20a, the nucleosome remodeling
ATPase Smarca5, the lysine demethylase subunit Phf2, and the RNA
helicase Ddx54).
The nding of robust interaction of RUS with nuclear pores
and the lamina suggest well-established epigenetic regulatory
mechanisms (to be discussed below). Binding of lncRNA Xist to
Lbr has been suggested to tether the inactive X chromosome to
the nuclear envelope, which forms a silent compartment (Chun-
Kan et al, 2016). To validate the binding between RUS and Lbr, we
returned to our NSC differentiation model. Nuclear extracts
were prepared from cells harvested at day 7 of differentiation.
Lbr was immunoprecipitated and co-precipitated RNA quanti-
ed by RT-qPCR. RUS was retrieved 3.7-fold more by comparison
to an anti-IgG purication (Fig 5C). Parallel reactions conrmed
the selective interaction of Brd2 with RUS, whereas Sox2 served
as a control.
In summary, our data support the idea of the long, noncoding
RNA RUS as a crucial regulator of the neurogenic gene expression
program through epigenetic mechanisms.
Discussion
The lncRNA RUS is required to execute the neurogenic program
Our study presents a rst functional characterization of the lncRNA
LINC01322, which we term RUS (for RNA upstream of Slitrk3). Like
other neurogenic lncRNAs, RUS is well conserved in mammals by
sequence and synteny next to the neurodevelopmental gene
Slitrk3. It is predominantly expressed in neural tissues. Although
the RNA bears some coding potential, we did not detect any of the
theoretically encoded peptides. RUS associates with chromatin at
specic sites in the vicinity of neurodevelopmental genes and
interacts with several proteins involved in epigenetic gene regu-
lation, suggesting that RUS acts as lncRNA. However, at this point we
cannot exclude the formal possibility that a fraction of RUS is
processed to functionally relevant miRNAs.
Transcriptome analyses revealed that sh-mediated depletion
of RUS results in massive gene expression changes. In fact, ap-
proximately half of all genes were affected to a certain degree.
The responses were equally divided between gene activation and
repression and were modulated during the 7 d of differentiation. This
nding is interesting because most lncRNAs studied so far either
mediate activation or repression (Rinn & Chang, 2020;Statello et al,
2021). Although indirect effects cannot be excluded yet, the fact that
we found epigenetic activators and repressors bound to RUS exon 1
in pull-down experiments, supports the idea that RUS may mediate
gene activation and repression in a highly context-dependent
manner. Conceivably, RUS may function through diverse mecha-
nisms, as emerges for the HOTAIR RNA (Price et al, 2021).
On day 5 of differentiation, reduced RUS levels correlate with
reduced expression of many genes involved in neurogenesis and
cell cycle, suggesting that the lncRNA promotes target gene ex-
pression to enable amplication of intermediate precursor cells
and NSC differentiation. This is in line with the observation that RUS
is expressed in hESC-derived LRGs (Ziller et al, 2015).
RUS is most highly expressed in the adult hippocampus, in which
neurogenesis still occurs (Eriksson et al, 1998). Adult neurogenesis
relies on expanding transit-amplifying IPs maintained by Shh ex-
pression (Antonelli et al, 2018) and differentiation by increased
Table 1. Continued
UniProt ID Gene name 2Log
10
(P-value) Log
2
(mut/) Only detected by full length RUS Nuclear compartment
Q9CR67 Tmem33 4.45 3.17 No
Q921T2 Tor1aip1 4.20 1.88 Yes Nuclear lamin
Q9JI13 Utp3 4.54 2.11 Yes Nucleolus
Q9JJA4 Wdr12 3.75 1.37 No Nucleolus
Q8BHB4 Wdr3 3.22 1.55 No Nucleolus
Q6ZQL4 Wdr43 2.95 1.40 No Nucleolus
Table highlights whether a protein was identied by full-length RUS only.
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 11 of 19
Neurog2 expression (Galichet et al, 2008). At day 7 of our differ-
entiation time course, Shh,Neurog2, and NeuroD1 are among the
most repressed genes upon RUS depletion. In addition, we found a
reduced expression of several subunits of glutamate and GABA
receptors, such as Grin3a and Gabrb1, which are predominantly
expressed in neurons.
Although the pattern of endogenous RUS expression and the
observation that neuron formation was impaired after RUS de-
pletion suggest a role of the lncRNA in promoting neuronal dif-
ferentiation, RNA-seq and GO analysis revealed a signicant
up-regulation of neuronal differentiation genes on day 7 after RUS
depletion. Such conicting results may be a consequence of induction
of proneuronal genes such as Notch2 and Rest after RUS depletion.
We speculate that RUS depletion locks neuronal precursors in an
intermediate state towards neuronal differentiation, with arrested
cell cycle. The activation of pro-apoptotic genes may result from
perturbed cell identity. However, it is also possible that increased
apoptosis after RUS depletion impaired neuron formation.
Potential mechanisms of RUS-mediated gene regulation
Given the diverse and presumably very site-specic effects of RUS
function, we can only speculate about potential mechanisms. Our
stringent ChIRP approach revealed a very consistent set of RUS
interactions with a limited number of high-condence chromatin
loci. The localization of binding sites predominantly in introns and
intergenic regions argue for long-range regulation. Considering that
the RNA is not highly expressed, we speculate that its range of
activity may be limited to the genes in the vicinity of tethering sites
(Engreitz et al, 2016).
Remarkably, most of the genes closest to a RUS binding site were
expressed in differentiating NSCs and changed their expression
state upon RUS depletion. For example, RUS binds in the genome
next to genes essential for cell cycle and neuronal differentiation,
such as Fgf9,Mapre3, and Ppp6c,Arid1b,Dclk2, and Kcna1. The
expression of these critical genes is affected by RUS depletion.
Furthermore, RUS binding sites can be observed in introns of the E3
ubiquitin ligase genes Itch and Fbxl17. Itch ubiquitinates Notch
proteins for degradation to turn off Notch signaling (Chen et al, 2021).
Fbxl17 plays a pivotal role in Shh signaling by degrading Sufu to
enable the translocation of Sufu-sequestered transcription factors to
the nucleus (Raducu et al, 2016). Consequently, reduction of both
factors after RUS depletion resulted in increased Notch signaling and
reduced Shh signaling, consistent with our RNA-Seq data. Notch
signaling is important for maintaining the active or quiescent NSC
state by preventing neuronal differentiation (Sueda & Kageyama,
2019). Shh signaling regulates proliferation of neural precursors (Yao
et al, 2016). By activating both genes RUS facilitates proliferation and
ensures proper differentiation of neural precursor cells.
LncRNA often work by recruiting epigenetic regulators to
locally concentrate them at target chromatin (Markaki et al, 2021).
Our RNA-afnity purication relies on protein-RUS interactions
formed under physiological conditions in intact cells and puri-
fying complexes under native conditions. Because we wished to
identify proteins interacting with the conserved exon 1 of RUS,we
monitored the differential binding to RNA containing or lacking
this sequence. This is a stringent approach because functionally
meaningful proteins may well (and are indeed likely to) bind to the
remainder of RUS as well, but they are not discussed here (but see
Table S5). In the following, we discuss hypothetical scenarios, in
which RUS recruits regulatory functions to chromosomal target loci.
It is also possible that RUS sequesters the factors in competition
with other interactors, which would have opposite effects on gene
regulation compared with recruitment scenarios (Xi et al, 2022).
Among the proteins puried by full length RUS only, the pro-
hibitin complex (consisting of Phb and Phb2) stands out. Prohibitin
has functions in several cellular compartments, including mito-
chondria and nuclei (Wang et al, 2002;Fusaro et al, 2003;Rajalingam
& Rudel, 2005;Koushyar et al, 2015). Prohibitin has been termed an
oncogene, as it promotes proliferation and dedifferentiation in
neuroblast cells (MacArthur et al, 2019) and a tumour suppressor
gene beacuse it was shown to inhibit the cell cycle by repressing
E2F-regulated genes via recruitment of the retinoblastoma protein
and histone deacetylases (Wang et al, 2002). It is tempting to
speculate that tethering the Phb complex to chromatin contributes
to inhibition of proliferation and activation of apoptosis.
Strikingly, the RNA pull-down retrieved numerous proteins of the
nuclear envelope. We scored six constituents of the nuclear lamina,
including three types of lamins and lamin B receptor (Lbr). The
inner nuclear membrane assembles a well-known repressive
compartment to which inactive heterochromatin is tethered. These
lamina-associated domains may be constitutive or facultative (van
Steensel & Belmont, 2017). Conceivably, RUS mediates tethering of
genes destined to be silenced to the lamina, where they acquire
heterochromatic features. Such a scenario has precedent in the
nding that the lncRNA XIST promotes X chromosome inactivation
in female cells by tethering the target chromosome to the nuclear
envelope via Lbr (Chun-Kan et al, 2016).
Repressive heterochromatin is also found at the surface of
nucleoli (Kind et al, 2013;Vertii et al, 2019). Remarkably, we found 13
nucleolar proteins enriched specically by RUS exon 1, which
further supports the speculation that RUS partitions genes into
silencing compartments. However, some of the retrieved nucleolar
proteins also have nuclear functions. For example, NOC2L (NOC2
Like Nucleolar Associated Transcriptional Repressor, also known as
NIR) associates with p53 in the nucleus to repress a subset of p53-
target genes, including p21, by inhibition of histone acetylation
(Hublitz et al, 2005). Interestingly, the exon 1 interactor NIFK (also a
nucleolar protein with nuclear functions) also cooperates with p53
to silence the p21 promoter during checkpoint control (Takagi et al,
2001). Apparently, RUS also contributes to p21 silencing because the
gene gained activity upon depletion of the lncRNA. Similarly, the
exon-1 interactor Cdk5rap3 activates p53 activity by repressing its
degradation by Hdm2 (Wang et al, 2006). Such a scenario provides a
plausible and testable hypothesis for the observed cell cycle arrest
at reduced RUS levels.
In addition to constituents of the nuclear lamina, we found 11
nuclear pore components (Nup11, Nup37, Nup43, Nup50, Nup54,
Nup85, Nup93, Nup98, Nup107, Nup133, and Seh1l) among the exon 1
interactors. In addition to nuclear transport, the nuclear pore
complex plays an important role in transcriptional regulation and
cell identity, apparently by generating a microenvironment that
fosters epigenetic regulation of associated genes (Pascual-Garcia &
Capelson, 2021). In Drosophila, Nup93 is associated with genes
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 12 of 19
repressed by the polycomb complex and is required for efcient
repression (Gozalo et al, 2020).
By contrast, three nucleoporins bound RUS are predominantly
associated with transcriptional activation. Nup98 acts as anchor
point for enhancer (Pascual-Garcia et al, 2017) and activates
transcription by recruiting the Wdr82-Set1A/COMPASS complex to
regulate H3K4 trimethylation (Franks et al, 2017). Similarly, Nup107
and Seh1l activate transcription by assembling transcription factor
(TF) complexes at the nuclear pore (Liu et al, 2019). It is tempting to
speculate that RUS may mediate facultative association of gene loci
with the nuclear periphery, which would then be subject to reg-
ulation of the corresponding microenvironment. This may initially
involve an initial transcriptional activation to execute the differ-
entiation programme. The subsequent compartmentalization of
chromosomal loci into a repressive environment may serve to
terminally silence cell cycle genes in mature neurons.
The exon 1 interactor HMG20A (also known as iBraf) is known
to antagonize repressive LSD1REST complexes. Because LSD1
RESTdependent H3K4 demethylation represses neuronal genes,
HMG20A action promotes neuronal differentiation (Ceballos-
Ch´
avez et al, 2012;Garay et al, 2016). The interaction of RUS with
HMG20A, therefore, likely affects neuronal differentiation, but
whether the outcome is positive (through recruitment) or negative
(through squelching) remains to be explored. Of note, REST ex-
pression increases upon RUS depletion, consistent with the ob-
served inhibition of neurogenesis.
In summary, our mapping of putative target genes and RUS
interactors are compatible with a range of testable, hypothetical
and not mutually exclusive scenarios that may explain the ob-
served change in phenotype and gene expression upon RUS de-
pletion during differentiation of NSCs. We propose that RUS may be
involved in several aspects of the neurogenic program in a highly
context-dependent manner, including amplication of precursor
cells and terminal neuronal differentiation.
Materials and Methods
Used reagents, tools, and oligonucleotides are listed in Tables S1
and S2.
Cultivation and differentiation of primary NSCs
The isolation of cortical embryonic stem cells from E15-E16 murine
cortices was approved by the animal welfare committees of LMU
and the Bavarian state. Cortices were dissected from pooled mixed-
sex embryonic brains, washed ve times with Hanks Balanced Salt
Solution and incubated in 0.5% trypsinEDTA for 15 min. Cortices
were then washed ve times with MEM-HS supplemented with
L-glutamine, essential amino acids, nonessential amino acids, and
10% horse serum. The single cells in suspension were pelleted at
200gfor 5 min, and seeded at a density of 5 × 10
5
cells/ml. NSCs
were cultured in DMEM-F12 with 5% FCS, B27 supplement and 20 ng/
ml basic broblast growth factor (bFGF) on poly-D-lysine-coated
culture dishes at 37°C in 5% CO
2
(Kilpatrick & Bartlett, 1993;Johe
et al, 1996;Azari et al, 2011;Mukhtar et al, 2020). Every second day,
the culture medium was supplemented with 20 ng/ml bFGF. Cells
were passaged up to six times by trypsin digestion at 95% con-
uency by 1:2 dilution. Differentiation was induced 5 d after seeding
in neurobasal medium with B27 supplement/0.25× GlutaMAX.
For RT-qPCR analysis or RNA-seq experiments, 3 × 10
5
NSCs were
seeded in 2 ml medium on 35-mm dishes. For microscopy exper-
iments, 1.6 × 10
5
NSCs were seeded in 1 ml medium on 12.8-mm
dishes equipped with 12-mm coverslips.
Sh-mediated knockdown experiments were started 1 d after
seeding by addition of 5 μl virus per 35-mm dish or 3 μl KD virus per
12.8-mm dish. To restore RUS expression, 10 or 6 μlRUS
overexpression-virus per 35 or 12.8 mm dish, respectively, was
added to KD cells 4 d after seeding.
Cultivation of Neuro2A cells
Neuro2A cells were cultured in DMEM-GlutaMAX and 10% FCS at
37°C in 5% CO
2
.
Immunohistochemistry
Cells were plated on poly-L-lysine-coated glass plates in a 24-well
plate. All cell washes were carried out in PBS, all incubations were
at RT. Cells were xed in 4% PFA for 20 min at RT, washed once for 10
min, and blocked with blocking solution (0.3% Triton X-100, 2%
donkey serum in PBS) for 30 min. The primary antibody (1:1,000) was
diluted in 200 μl blocking solution and added for 1 h 30 min while
shaking. The antibody solution was removed, and the cells were
washed three times for 10 min. Cells were incubated with the
secondary antibody (1:2,000) in 200 μl blocking solution for 1 h
30 min as before. After three 10-min washes, nuclei were stained for
15 min using DAPI (2-[4-amidinophenyl]-6-indolecarbamidine
dihydrochloride) 1:1,000 in PBS. The cells were mounted in the
presence of diazabicyclo-octane (DABCO). Stained cells were an-
alyzed with a Leica DM8000 uorescent microscope, and images
were quantitatively processed with ImageJ. Images from DAPI and
antibody staining were thresholded, colocalized, and watershed-
transformed. The particles in the resulting overlay image were counted
using the particle analyzer. Per experiment, 35microscopeelds on
34 plates each were recorded and analyzed.
BrdU labeling
Cull culture medium was supplemented with 1 μg/ml bromode-
soxyuridine. After 24 h, cells were immunostained with an anti-BrdU
antibody.
Quantitative reverse transcription-PCR (RT-qPCR)
RNA from cells, tissues or biochemical experiments was extracted
with Trizol and chloroform and precipitated using 50% isopropanol
and 15 μg linear acrylamide. RNA was washed twice with 75% EtOH,
dissolved in nuclease-free water, and reverse-transcribed using
MMuLV RT (Thermo Fisher Scientic) and oligodT(18-20). ChIRP and
RIP-puried RNA was amplied with random hexamers. RT-qPCR
analysis was performed with 1 μM of each primer in Fast SYBR Green
Master Mix (Thermo Fisher Scientic). The ΔCt values were
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 13 of 19
normalized with amplicons detecting against TATA-binding protein
(TBP) mRNA.
39RACE
The RUS 39-end was cloned from a hippocampal RNA using the
FirstChoice RLM-RACE Kit (Thermo Fisher Scientic). One microgram
of RNA was reverse-transcribed using an anchored 39RACE oli-
go(dT) primer. This was followed by two rounds of nested PCR using
RUS-39-RACE as forward and 39-outer primers and 39-inner as re-
verse primer. The PCR product was gel-puried and sequenced.
Generation of the RUS knockdown vector
ShRNAs were designed according to standard procedures (Yuan et
al, 2004). In brief, 100 pmol RUS-sh-FW and 100 pmol RUS-sh-RV
were annealed in 50 μl NEB2.1. The annealed fragment was cloned
into pLKO.1-TRC-Puro vector, linearized with AgeI and EcoRI (Moffat
et al, 2006), and amplied in Dh5α. For pLKO.1 vectors containing
GFP as a selection marker, the puromycin resistance gene was
replaced with the GFP gene via BamHI and KpnI restriction sites.
Towards this end, the GFP cDNA was amplied from pLenti-CMV-
GFP-Hygro (Campeau et al, 2009) by PCR using the primers: BamH-
GFP-fw and Kpn-GFP-rv.
Construction of pcDNA-5FRT-5xMS2
pcDNA.5-FRT vectors used to generate stable FlpIN Neuro2A cells
were equipped with 5xMS2 stem-loops. The 3xMS2 stem-loop se-
quence was PCR-amplied with the primers MS2_fw and MS2_rv
from pAdMl3-(MS2)
3
, digested with BamHI and XbaI, and ligated to
BamHI/ XbaI-linearized pcDNA5-FRT. Upon amplication in Dh5α,
one clone fortuitously expanded 3xMS2 stem-loops to 5xMS2 stem-
loops. This clone was used.
Generation of RUS overexpression vector
RUS and Δ59RUS sequences of isoform 1 missing exon 4 were
isolated from a hippocampal cDNA library by PCR with the primers:
RUS-LIC-fw or Δ59RUS-LIC-fw, respectively, and RUS-LIC-rv and
cloned into pcDNA-5-FRT or pcDNA.5-FRT-5xMS2 (Thermo Fisher
Scientic) via LIC cloning (Wang et al, 2012) and amplied in Dh5α.
For rescue experiments, the RUS cDNA targeted by shRNA
RUS
was
shufed into pLenti-CMV-GFP-Hygro (Campeau et al, 2009) via ClaI
and ApaI restriction sites to replace GFP and the hygromycin re-
sistance gene. All constructs were veried by sequencing.
Construction of pLenti-FRT
pLenti-GFP-Puro (Campeau et al, 2009) was digested with XbaI and
BamHI to remove GFP downstream of the CMV promoter. FRT site
was generated by annealing the oligonucleotides FRT_fw and
FRT_rv. For annealing, 100 pmol of each oligonucleotide was heated
in 50 μl NEB 2.195°C for 5 min and slowly cooled down. 2 μl
annealing scale was ligated into 20 ng digested vector and
transformed in Dh5α.
Production of lentiviral particles
All lentiviral experiments were conducted according to standard
protocols (Moffat et al, 2006) and approved by the Bavarian state.
3×10
6
HEK293T cells were seeded in 8 ml DMEM-GlutMax sup-
plemented with 8% FCS on a 10 cm culture dish. Per virus production,
four 10-cm dishes were seeded. Next day, 53 μg DNA in a molar ratio
of 2:1:1 of lentiviral-vector: psPAX2: pMD2.G transfected into 5070%
conuent cells. The medium was changed next day. 2 d after
transfection, viral particles were puried by sedimentation (87,000g,2h)
from the medium and dissolved in 200 μlTBS5(50mMTrisHCl, pH 7.8,
130 mM NaCl, 10 mM KCl, 5 mM MgCl
2
,and10%BSA).
Subcellular fractionation
Subcellular fractionation was adapted from Gagnon et al (2014).
Briey, cells were lysed in ice-cold hypotonic lysis buffer (HLB;
10 mM TrisHCl, pH 7.5, 10 mM NaCl, 3 mM MgCl
2
, 0.3% NP-40, and 10%
glycerol) for 10 min on ice. The cytoplasm was harvested by cen-
trifugation (1,000g, 5 min) and the nuclear pellet was washed thrice
in HLB. Nuclei were incubated in ice-cold modied WuarinSchibler
buffer (MWS; 10 mM TrisHCl, pH 7.5, 4 mM EDTA, 0.3 M NaCl, 1 M urea,
and 1% NP-40) for 15 min on ice. The nucleoplasm was separated
from the chromatin by centrifugation (1,000g, 5 min). The RNA in the
cytoplasmic and nucleoplasmic fractions was ethanol-precipitated
and subjected along with the chromatin pellet for RNA purication.
RNA-seq analysis
Total RNA was isolated and polyA-enriched. After reverse tran-
scription, the cDNA was fragmented, end-repaired, and polyA-tailed.
Solexa sequencing adaptors were ligated, and adaptor-modied
fragments were enriched by 1018 cycles of PCR amplication.
Quantity and the size of the sequencing library were accessed on
a Bioanalyzer before sequencing on an Illumina NextSeq 500
platform. Sequencing reads from FASTAQ les were aligned the
STAR Aligner version (Dobin et al, 2013) and quantied using
rsem (Li & Dewey, 2011). The reference genome used for alignment
was constructed using the mm10 fasta le and GRCm38.99 tran-
script table. Quantied values were further statistically evaluated
using Bioconductors DeSeq2 package (Love et al, 2014). Expression
changes with an FDR < 0.05 were considered signicant. Among
them, genes with a stat < 2 or >2 were extracted as down- or up-
regulated genes, respectively (Table S3).
GO term enrichment analysis
GO enrichment used the Web-based PANTHER software (Mi et al,
2013). The deregulated genes enriching for GO terms of interest
were extracted from the provided xml le and matched to their
expression values using R.
ChIRP-seq analysis
NSCs from 8 × 15-cm dishes were harvested 7 d after seeding and
washed twice with PBS. Cells were cross-linked in 100 ml 1% glu-
taraldehyde for 10 min at RT. Cross-linking was quenched 125 mM
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 14 of 19
glycine for 5 min. Cells were pelleted at 1,000gfor 5 min. ChIRP was
performed according to Chu et al (2011). Cross-linked cells were
washed twice in PBS and lysed in 2 ml ChIRP-lysis buffer (50 mM
TrisHCl pH 7.0, 10 mM EDTA, 1% SDS, 1 mM PMSF, protease in-
hibitor, SuperaseIn 100 U/ml). Chromatin shearing by Bioruptor
typically yielded fragments of 150600 bp. Sheared chromatin was
diluted with 4 ml ChIRP-hybridization buffer (50 mM TrisHCl pH 7.0,
750 mM NaCl, 15% [m/v] formamide, 1 mM EDTA, 1% SDS, with
protease and RNase inhibitors) and divided into two aliquots, which
were hybridized with 100 pmol biotinylated oddand evenprobe
sets, respectively, at 37°C for 4 h with continuous rotation. Then
1 mg of magnetic streptavidin bead suspension (Thermo Fisher
Scientic) in ChIRP-Lysis buffer were added and incubated for
30 min at 37°C with continuous rotation. Beads were washed ve
times with 1 ml ChIRP Wash buffer (300 mM NaCl, 30 mM Na
3
-citrate,
0.1% SDS, and 1 mM PMSF) for 5 min at 37°C. 90% of bead material was
used for DNA isolation and 10% for RNA isolation. The enrichment of
RUS,TBP mRNA, MALAT,andXIST was analyzed by RT-qPCR.
Isolated DNA was processed alongside an input chromatin
sample. Ends were blunted with T4 DNA polymerase and poly-
nucleotide kinase and an AMP was added. Solexa sequencing
adaptors were ligated and adaptor-modied fragments were
enriched by 1018 cycles of PCR amplication. Sequencing libraries
were size-selected on AMPure Beads (Beckman Coulter), quality-
controlled on a Bioanalyzer (Agilent) and sequenced on an Illumina
NextSeq-500 platform.
Sequencing reads from FASTQ les were aligned with bowtie2
(Langmead & Salzberg, 2012) to mm10. Multimapping reads were
removed using samtools (Li et al, 2009). ChIRP peaks were called
with MACS1.4 for both probe sets independently (Feng et al, 2012).
The deeptools package was used to generate the bedgaph les
(Ram´
ırez et al, 2016). Bedtools (Quinlan & Hall, 2010) and python 2.7
matched even and odd bedgraph les into a single bedgraph le via
the take-lowermethod. The experiment was performed in trip-
licates. Only peaks occurring in each even and odd sample and in
all three data sets called with Bioconductors GenomicRanges
package (Lawrence et al, 2013) were considered valid RUS binding
sites. The overlap demanded a minimal distance of 200 bp be-
tween the evenand oddsummit. Probe sequences within
overlapping peaks were detected using Fimo (Grant et al, 2011)of
the MEME software (Bailey et al, 2015) and removed using a cutoff
of p < 1 × 10
8
before further analysis using GenomicRanges
(Lawrence et al, 2013).
Filtered peaks were annotated with Homer (Heinz et al, 2010)
using mm10 as reference genome (Table S4). The obtained anno-
tation statistic was used to calculate the distribution of RUS peaks
within promoter, intergenic, intron, and close to repetitive sites. The
annotated neighboring genes of RUS peaks were considered pu-
tative RUS target genes. GO term enrichment of putative target
genes used the Web-based PANTHER software (Mi et al, 2013). Next,
putative target gene expression and changes upon in shRNA
CON
and
shRNA
RUS
treatment on day 5 and 7 were extracted from the RNA-
seq data using the R-package SummarizedExperiments and DeSeq2
(Table S4). Expression changes with an FDR < 0.05 were considered
signicant. Among them, genes with a stat < 2 or >2 were con-
sidered as down- or up-regulated genes. Expression values of
both time points were merged, log
2
-transformed, and ranked by
hierarchically clustering using the Euclidean distance method in R.
Furthermore, the correlation between RUS and putative target gene
expression was calculated using the Pearson correlation coefcient
on both time points separately (Table S4).
MS2 afnity purication of RUS interactors
Stable pools of Neuro2A cells expressing 5xMS2-tagged RUS were
generated as follows. 5 × 10
4
Neuro2A cells were transfected with
5μl pLenti-FRT virus and 2 d later selected in GlutMax, 8% FCS
supplemented with 2 μg/ml puromycin and expanded. 10
6
Neu-
ro2A-FRT cells were seeded on a 10-cm culture dish. On the next
day, cells were transfected with 15 μg plasmid DNA, consisting of a
molar ratio of 1:6 (up to 1:9) of pcDNA5-lncRNA-5xMS2: pCSFLPe
(encoding the ipase). Plasmids were diluted appropriately in 300
μl 150 mM NaCl and 15 μl JetPEI (2.6 μg/μl) and mixed. After 30 min
equilibration at RT, the solution was added dropwise to Neuro2-FRT
cells. 2 d later, cells were transferred to a new 10-cm dish and
selected in GlutaMax 8% FCS, 2 μg/ml puromycin, and 600 μg/ml
hygromycin. The medium was replaced every second day to remove
cell debris. Colonies formed 710 d after transfection. They were
harvested and further cultivated.
Nuclear extract from MS2-tagged RUS-expressing Neuro2A cells
was prepared typically from 8 × 10
7
cells without dialysis, according
to Dignam et al (1983). Extract preparation and MS2-afnity puri-
cation were carried out at 4°C. Cell pellets were suspended in 5 vol
buffer A (10 mM Hepes, pH 7.9 at 4°C, 1.5 mM MgCl
2
, 10 mM KCl, 0.5 mM
DTT, and 200 U/ml RNAsin) and incubated for 10 min. Cells were
homogenized with a Dounce tissue grinder. Nuclei were pelleted at
500gfor 10 min, washed with ve nuclear volumes (vol) buffer A,
dissolved in one vol buffer C (20 mM Hepes, pH 7.9, 25% [vol/vol]
glycerol, 0.42 M KCl, 1.5 mM MgCl
2
, 0.2 mM EDTA, 0.5 mM PMSF, 0.5 mM
DTT, and 200 U/ml RNAsin) and homogenized again with a Dounce
tissue grinder. After gentle rotation for 30 min, chromatin was
pelleted at 17,000gfor 30 min. The supernatant was diluted with 1
vol buffer G (20 mM Hepes, pH 7.9, 20% [vol/vol] glycerol, 0.2 mM
EDTA, 0.5 mM PMSF, 0.5 mM DTT, and 200 U/ml RNAsin) and used for
afnity purication.
Standard MS2-afnity purication was carried out on superna-
tant containing 1 mg protein. To this, 760 pmol yeast t-RNA com-
petitor and 120 pmol recombinant MS2BP-MBP (Jurica et al, 2002;
Zhou & Reed, 2003) was added. After 2 h of gentle rotation, 50 μl
equilibrated amylose resin (New England Biolabs) was added and
incubation continued for 2 h. The resin was pelleted at 1,900gfor 1
min and washed thrice with 900 μl buffer D (buffer G containing 0.1
M KCl and lacking RNasin) and thrice 900 μl buffer F (buffer D
containing 1.5 mM MgCl
2
).
RNA-interacting proteins were identied by mass spectrometry.
Interacting proteins were eluted with 50 μg RNAse A in 80 μl buffer D
at 37°C for 10 min. The resin was pelleted at 1,900gfor 1 min at 4°C
and the supernatant subjected to lter-aided sample preparation
(Wi´
sniewski et al, 2009), and peptides were desalted using C18
StageTips, dried by vacuum centrifugation, and dissolved in 20 μl
0.1% formic acid. Samples were analyzed on a Easy nLC 1,000
coupled online to a Q-Exactive mass spectrometer (Thermo Fisher
Scientic). 8 μl peptide solution per sample were separated on a
self-packed C18 column (30 cm × 75 μm; ReproSil-Pur 120 C18-AQ,
LncRNA RUS shapes neurogenic program Schneider et al. https://doi.org/10.26508/lsa.202201504 vol 5 | no 10 | e202201504 15 of 19
1.9 μm, Dr. Maisch GmbH) using a 180-min binary gradient of water
and acetonitrile supplemented with 0.1% formic acid (0 min, 2% B; 3:
30 min, 5% B; 137:30 min, 25% B; 168:30 min, 35% B; 182:30 min, 60% B)
at 50°C column temperature. A top 10 DDA method was used. Full
scan MS spectra were acquired with a resolution of 70,000. Frag-
ment ion spectra were recorded using a 2 m/z isolation window, 75
ms maximum trapping time with an AGC target of 10
5
ions.
The raw data were analyzed with the MaxQuant (version 2.0.1.0)
software (Cox & Mann, 2008) using a one protein per gene canonical
database of Mus musculus from UniProt (download : 2021-04-09;
21,998 entries). Trypsin was dened as protease. Two missed
cleavages were allowed for the database search. The option rst
search was used to recalibrate the peptide masses within a window
of 20 ppm. For the main search, peptide and peptide fragment mass
tolerances were set to 4.5 and 20 ppm, respectively. Carbamido-
methylation of cysteine was dened as a static modication.
Acetylation of the protein N terminus as well as oxidation of me-
thionine set as variable modications. Match between runs was
enabled with a retention time window of 1 min. Two ratio counts of
unique peptides were required for LFQ.
Output les were further analyzed using the software Perseus
(Tyanova et al, 2016). Proteins identied by site, reverse matching
peptides and contaminants were removed and LFQ intensities were
log
2
-transformed. Next, only protein groups with ve out of ve
quantications in one condition were considered for relative
protein quantication. To account for proteins that were only
consistently quantied in one condition, data imputation was used
with a down-shift of 2 and a width of 0.2. A permutation-based FDR
correction (Tusher et al, 2001) for multiple hypotheses was applied
(P= 0.05; s0 = 0.1). Proteins were considered enriched if the fold
change was greater than two and the P-value less than 0.002 (Table
S5).
RNA immunoprecipitation
Protein A/G-Agarose beads (35 μl; Thermo Fisher Scientic) were
blocked overnight with 1% BSA in buffer D. To nuclear extract from 5
×10
6
NSC 760 pmol yeast tRNA, 300 μg salmon sperm DNA and 4 μg
Lbr antibody were added and incubated for 2 h at 4°C under gentle
rotation. Anti-rabbit IgG was used as a negative control. The binding
reaction was added to blocked Protein A/GAgarose and incubated
for 2 h at 4°C with gentle rotation. Protein A/G beads were sedi-
mented, washed with 900 μl buffer D, suspended in 800 μl Trizol,
and subject to RNA extraction. RUS levels were analyzed by RT-qPCR
analysis and compared against the IgG purication. The experiment
was performed in triplicates and statistically evaluated by a one-
tailored ttest using Bonferroni P-value adjustment.
Data Availability
The RNA-Seq and ChIRP Seq data from this publication were de-
posited to the Gene Expression Omnibus repository (https://
www.ncbi.nlm.nih.gov/geo) with accessions GSE196487,GSE196527,
respectively. The protein interaction AP-MS data can be found at
the PRIDE repository (Perez-Riverol et al, 2022)(http://www.ebi.ac.
uk/pride/archive) with the accession PXD031664. Computer scripts
are deposited on GitHub (https://github.com/MariusFSchneider/
Schneider22).
Supplementary Information
Supplementary Information is available at https://doi.org/10.26508/lsa.
202201504.
Acknowledgements
We thank Aline Campos, Silke Krause, and Anna Berghofer for technical
assistance, Tobias Straub for advice on bioinformatic analysis, Bianka
Baying, Vladimir Benes (EMBL GeneCore), and Stefan Krebs (LAFUGA) for
library preparation and sequencing, Magdalena G ¨
otz, Daniela Cimino, and
Maroussia Hennes for providing mouse brain tissues and Christian Haass for
his continued support. We are grateful to Sandra Schick, Marie Kube, and
Rodrigo Villaseñor for critical reading of the manuscript. This work was
funded by the Deutsche Forschungsgemeinschaft (DFG) within the frame-
work of the Munich Cluster for Systems Neurology (EXC 2145 SyNergyID
390857198), grant BE1140/8-1 (to PB Becker), and the Adele Hartmann
Programm of the LMU (to JC Scheuermann).
Author Contributions
MF Schneider: conceptualization, data curation, visualization,
methodology, and writingoriginal draft, review, and editing.
V Müller: investigation and methodology.
SA Müller: data curation, formal analysis, investigation, method-
ology, and writingreview and editing.
SF Lichtenthaler: funding acqisition, validation and writingreview
and editing.
PB Becker: conceptualization, supervision, funding acquisition,
writingoriginal draft, and project administration.
JC Scheuermann: funding acqisition, conceptualization, and project
administration.
Conict of Interest Statement
The authors declare that they have no conict of interest.
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