# Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain

Tom Bonnifet, Sandra Sinnassamy, Olivia Massiani-Beaudoin, Philippe Mailly, Héloïse Monnet, Damarys Loew, Berangère Lombard, Nicolas Servant, Rajiv Joshi, Julia Fuchs

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Tom Bonnifet, Sandra Sinnassamy, Olivia Massiani-Beaudoin, Philippe Mailly, Héloïse Monnet, et al. Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain. 2025. hal-04694146

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1 **Title:**

2

3 **Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA**

4 **increase with aging in the mouse and human brain**

5

6

7 **Authors:**

8

9 **Tom Bonnifet¹, Sandra Sinnassamy¹, Olivia Massiani-Beaudoin¹, Philippe Mailly², Héloïse**

10 **Monnet², Damarys Loew³, Berangère Lombard³, Nicolas Servant⁴, Rajiv L. Joshi¹* & Julia**

11 **Fuchs¹***

12

13 **Affiliations:**

14 ¹CIRB, Collège de France, Université PSL, INSERM, CNRS, 75005, Paris, France.

15 ² Orion Technological Core, CIRB, Collège de France, Université PSL, INSERM, CNRS,
16 75005, Paris, France.

17 ³ Institut Curie, Université PSL, Centre de Recherche, CurieCoreTech Spectrométrie de Masse
18 Protéomique, 26 rue d’Ulm, Paris 75248 Cedex 05, France

19 ⁴ Institut Curie, INSERM U900, Mines Paris Tech, Université PSL

20

21 **\*For correspondance:**

22 J.F. (Julia.fuchs@college-de-france.fr); R.L.J. (rajiv.joshi@college-de-france.fr)

23
**Key words:** Transposable elements, retrotransposons, LINE-1, ORF1p, aging, brain mapping, mass spectrometry, ORF1p protein interactors, human post-mortem brain, dopaminergic neurons, deep learning.

27

28 **Abstract**

29

30 Recent studies have established a reciprocal causal link between aging and the activation of transposable elements, characterized in particular by a de-repression of LINE-1 retrotransposons. These LINE-1 elements represent 21% of the human genome, but only a minority of these sequences retain the coding potential essential for their mobility. LINE-1 encoded proteins can induce cell toxicity implicated in aging and neurodegenerative diseases. However, our knowledge of the expression and localization of LINE-1-encoded proteins in the central nervous system is limited. Using a novel approach combining atlas-based brain mapping with deep-learning algorithms on large-scale pyramidal brain images, we unveil a heterogeneous, neuron-predominant and widespread ORF1p expression throughout the murine brain at steady-state. In aged mice, ORF1p expression increases significantly which is corroborated in human post-mortem dopaminergic neurons by an increase in young LINE-1 elements including those with open reading frames. Mass spectrometry analysis of endogenous mouse ORF1p revealed novel, neuron-specific protein interactors. These findings contribute to a comprehensive description of the dynamics of LINE-1 and ORF1p expression in the brain at steady-state and in aging and provide insights on ORF1p protein interactions in the brain.

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47

48
49 **Introduction**

50

51 Only about 2 % of the human genome are DNA sequences that will be translated into protein.

52 The remaining 98 % are comprised of introns, regulatory elements, non-coding RNA,

53 pseudogenes and repetitive elements including transposable elements. However, some

54 sequences in what is generally considered “non-coding genome” do in fact contain sequences

55 which encode proteins. This is true for specific lncRNAs which can encode peptides or

56 functional proteins ¹ but also for a few copies of two transposable element families, Long

57 INterspersed Element-1 (LINE-1) and Human Endogenous RetroViruses (HERV). Non-

58 functional copies of retrotransposons, to which LINE-1 and HERV belong, cover about 44% ²

59 of the human genome as remnants of an evolutionary ancient activity. Depending on the source,

60 about 100³ to 146⁴ full-length LINE-1 elements with two open reading frames encoding ORF1

61 and ORF2 are present in the Human reference genome (GRCh38 Genome Assembly) and

62 several incomplete HERV sequences encoding either or any combination of envelope (env),

63 gag, pro or pol ⁵. The LINE-1 encoded protein ORF1p, an RNA binding protein with “cis”

64 preference ⁶,⁷, and ORF2p, an endonuclease and reverse transcriptase ⁸,⁹ are required for the

65 mobility of LINE-1 elements. As many other transposable elements (TEs) including HERVs,

66 LINE-1 elements are repressed by multiple cellular pathways. It was thus generally thought that

67 TEs are repressed in somatic cells with no expression at steady-state ¹⁰⁻¹². However, the aging

68 process reduces the reliability of these repressive mechanisms ¹³. It is now, 31 years after the

69 initial proposition of the “transposon theory of aging” by Driver and McKechnie ¹⁴, still a matter

70 of debate whether TE activation can be both, a cause and a consequence of aging ¹⁵,¹⁶.

71 Sparse data has shown that the LINE-1 encoded protein ORF1p is expressed at steady-

72 state in the mouse ventral midbrain ¹⁷, the mouse hippocampus ¹⁸ and in some regions of the

73 human post-mortem brain ¹⁹ and recent data informed about the presence of full-length
transcripts in cancer cells, human epithelial cells and mouse hippocampal neurons <sup>20</sup>.
Repression of LINE-1 might thus be incomplete and if so, it remains unclear how cells then
prevent cell toxicity associated with LINE-1 encoded protein activity. Indeed, LINE-1 encoded
proteins have been demonstrated to induce genomic instability (ORF2p endonuclease-mediated
<sup>17,21-26</sup>) and inflammation (ORF2p reverse transcriptase-mediated <sup>27-29</sup>) and these cellular
activities might be causally related to organismal aging, cancer, autoimmune and neurological
diseases <sup>30</sup>. For instance, LINE-1 activation can drive neurodegeneration of mouse
dopaminergic neurons <sup>17</sup>, of drosophila neurons <sup>31,32</sup> and of mouse Purkinje neurons <sup>33</sup> which
can be at least partially rescued with nucleoside analogue reverse transcriptase inhibitors
(NRTIs) or other anti-LINE-1 strategies. NRTIs are currently being tested in several clinical
trials designed to target either the RT of HERVs or the RT encoded by the LINE-1 ORF2
protein. It is not known today, however, to which extend LINE-1 encoded proteins are
expressed at steady-state throughout the mouse and human brain, whether there is cell-type
specificity and whether activation of LINE-1 encoded proteins is associated with brain aging
or human neurodegeneration. Here, using a deep-learning assisted cellular detection
methodology applied to pyramidal large-scale images of the mouse brain mapped to the Allen
mouse brain atlas combined with post-mortem human brain imaging, co-IP mass spectrometry
and transcriptomic analysis of LINE-1 expression, we describe a brain-wide map of ORF1p
expression and interacting proteins at steady-state and in the context of aging. We find a
heterogenous but widespread expression of ORF1p in the mouse brain with predominant
expression in neurons. In aged mice, neuronal ORF1p expression increases brain-wide and in
some brain regions to up to 27%. In human dopaminergic neurons, young LINE-1 transcripts
and specific full-length and coding LINE-1 copies are increased in aged individuals. We further
describe endogenous mouse ORF1p interacting proteins revealing known interactors and
unexpected interacting proteins belonging to GO categories related to RNA metabolism, chromatin remodeling, cytoskeleton and the synapse.

100

101

## Results

102

103 **Widespread and heterogenous expression of the LINE-1 encoded ORF1p protein in the**
104 **wildtype mouse brain**

105 To investigate the expression pattern and intensities of endogenous LINE-1 encoded ORF1p
106 protein throughout the entire mouse brain, we devised a deep-learning assisted cellular
107 detection methodology applied to pyramidal large-scale images using a comprehensive
108 workflow complemented by an approach based on confocal imaging as schematized in Figure
109 1A. Briefly, starting from sagittal slide scanner images of the mouse brain, we defined
110 anatomical brain regions by mapping the Allen Brain Atlas onto the slide scanner images using
111 Aligning Big Brains & Atlases (ABBA) ³⁴. We then employed a deep-learning detection method
112 to identify all cell nuclei (Hoechst) and categorize all detected cells into neuronal cells (NeuN+)
113 or non-neuronal cells (NeuN-) and ORF1p-expressing cells (ORF1p+) or cells that do not
114 express ORF1p (ORF1p-). This workflow allowed us then to characterize the cell identity of
115 ORF1p+ cells and ORF1p intensity throughout the whole brain but also in specific anatomical
116 regions. In parallel, we completed the approach using confocal microscopy on selected
117 anatomical regions allowing for comparison with higher resolution. Importantly, the specificity
118 of the ORF1p antibody, a widely used, commercially available antibody ¹⁸,³⁵⁻³⁹, was confirmed
119 by blocking the ORF1p antibody with purified mouse ORF1p protein resulting in the complete
120 absence of immunofluorescence staining (Suppl Fig. 1A), by using an in-house antibody against
121 mouse ORF1p¹⁷ which colocalized with the anti-ORF1p antibody used (Suppl Fig. 1B,
122 quantified in Suppl Fig. 1C), by immunoprecipitation and mass spectrometry used in this study
(Fig 6A, Suppl Table 2) and by siRNA-mediated knock-down of ORF1 in a differentiated mouse dopaminergic cell line (MN9D; Suppl Fig. 1D). Unexpectedly, we found a generalized and widespread expression of ORF1p throughout the brain of wildtype mice (Fig. 1B; Swiss OF1 mice, three months-old; whole brain except regions with particularly high cellular density (cerebellum, hippocampus, olfactory bulb) which impedes nuclei detection by deep-learning. ORF1p is detectable in all regions and subregions analyzed with heterogenous expression patterns (density and intensity) per region/subregions. The ten regions shown in Figure 1B exemplify visible different densities of ORF1p+ cells with varying levels of expression. Notably, the expression pattern of ORF1p in the hippocampus is similar to what has recently been published<sup>18</sup> (Fig. 1B, panel 2). Throughout the entire brain, the mean density of ORF1p+ cells per mm<sup>2</sup> was ≈ 305 ±18 (mean ±SEM), representing up to 20% of all detected cells (Fig. 1C). ORF1p+ cells in each mouse brain analyzed showed up to eight-fold disparities in intensity between low- and high-expressed cells (Fig. 1C). We then quantified nine anatomical regions according to the Allen Brain Atlas on four brains of three-month old mice (Fig. 1D) using the automated workflow (Fig. 1A) with regard to cell density (Fig. 1D), cell proportions (Fig. 1E) and fluorescent intensity of ORF1p+ cells (Fig. 1F). This approach permitted the analysis of about 10 000 ORF1p+ cells per animal highlighting the power of our large-scale analysis. Densities of ORF1p+ cells ranged from the lowest density in the hindbrain with 154 ±19 cells per mm<sup>2</sup> (mean ±SEM) to the highest density of ORF1p+ cells in the isocortex with 451 ±44 cells per mm<sup>2</sup> (mean ±SEM) and the thalamus with 446 ±50 cells per mm<sup>2</sup> (mean ±SEM). The proportion of ORF1p+ cells per anatomical region fluctuated between 10% ±2.1 (ventral striatum, mean ±SEM) and 31% ±1.6 (thalamus, mean ±SEM). The dorsal striatum ("striatal dorsal" in the Allen Brain Atlas denomination) exhibited the lowest ORF1p expression intensity (658 ±3 mean ±SEM) of all regions tested, the hindbrain the highest mean intensity of ORF1p per cell (mean ±SD 1221 ±548) as illustrated in Figure 1B and quantified in Figure 1D and 1F.
Interestingly, cell density did not correlate with expression levels. Dorsal and ventral striatum for instance displayed similar ORF1p intensities per cell but exhibited significant differences in ORF1p cell density and proportion. The “midbrain motor” region as defined by the Allen Brain Atlas showed an intermediate cell density (mean ±SEM 265 ±16 cells per mm²) and a rather high ORF1p expression intensity (mean ±SEM 1006 ±533). Statistical analysis comparing mean density of ORF1p+cells per mm² or mean intensity per ORF1p+ cells among regions confirmed the heterogeneity concerning ORF1p expression throughout the mouse brain (Fig. 1D, 1F). Slide scanner and confocal images revealed an exceptionally high ORF1p expression intensity in the ventral region of the midbrain which we identified as the *Substantia nigra pars compacta (SNpc)*. This region displayed an important density of ORF1p+ cells and a comparatively high level of ORF1p expression as illustrated by confocal imaging (Fig. 1B, panel 8), but could not be quantified independently with our brain-wide approach due to the geometrically-complex anatomy of this region and its small size (subregion-level in the Allen Brain Atlas hierarchy). Another region which could not be included in our brain-wide analysis was the cerebellum due to its extremely high density of cell nuclei. However, slide scanner and confocal imaging (Fig. 1B, panel 10) revealed that ORF1p is expressed in Purkinje cells, while not detectable in the molecular or granular layers.

In order to confirm ORF1p expression by an independent method, we performed Western blot analysis on six micro-dissected regions from the mouse brain (Swiss/OF1 mouse, three-month old). As shown in Suppl Fig. 1E, ORF1p is expressed in all six regions with varying expression levels confirming the overall presence of ORF1p throughout the brain. We then chose two regions with significantly divergent ORF1p expression intensities as identified and quantified on pyramidal large-scale images: the frontal cortex (low) and the ventral midbrain (intermediate to high). We confirmed a significant higher expression of ORF1p in the ventral midbrain compared to the frontal cortex using an approach based on the unbiased,
automated quantification of multiple z-stacks using a confocal microscope (Fig. 1G) and by Western blotting on micro-dissected regions (Fig. 1H, 1I). In concordance with the findings stemming from the large-scale image quantification pipeline (Fig. 1F), the ventral midbrain showed ≈ 2-times higher expression of ORF1p than the frontal cortex as quantified in Figure 1G (1.8-fold) and Figure 1I (2.3-fold) validating our cellular detection methodology for pyramidal large-scale imaging and underscoring the heterogeneity of ORF1p expression levels in the mouse brain.

To investigate intra-individual expression patterns of ORF1p in the post-mortem human brain, we analyzed three brain regions of a neurologically-healthy individual (Fig. 1J, entire Western blot membrane in Suppl Fig. 2A) by Western blotting using a commercial and well characterized antibody which we further validated by several means. While there is some discrepancy in the field, the double band pattern in Western blots has been observed in other studies for human ORF1p outside of the brain<sup>40,41</sup> as well as for mouse ORF1p<sup>42</sup>. The nature of this lower band is unknown, but it might be due to truncation<sup>43</sup>, specific proteolysis or degradation. Nevertheless, it appears that in cell culture models, a single ORF1p band is observed, whereas in murine and human samples, the ORF1p band is, to our knowledge, consistently associated with a lower molecular weight band<sup>35-37,40-42,44,45</sup>. We validated the antibody by immunoprecipitation and siRNA knock-down in human dopaminergic neurons in culture (differentiated LUHMES cells, Suppl Fig. 2B and 2C) where we detected in most cases the upper band only. ORF1p was expressed at different levels in the human post-mortem cingulate gyrus, the frontal cortex and the cerebellum underscoring a widespread expression of human ORF1p across the human brain. This was in accordance with ORF1p immunostainings of the human post mortem cingulate gyrus (Fig. 2H and Suppl Fig. 2E) and frontal cortex (Suppl Fig. 2E), with an absence of ORF1p staining when using the secondary antibody only (Suppl Fig. 2E).
In summary, our findings reveal the consistent presence of ORF1p expression throughout the mouse brain in all anatomical regions analyzed with high regional variability in terms of density of ORF1p+ cells and ORF1p+ cell intensity. ORF1p is also expressed in the human brain in at least three brain regions. This finding raises several questions concerning cell-type identity of ORF1p expressing cells and potential functions or consequences of ORF1p expression in the mouse and human brain at steady-state.

204

205 ORF1p is predominantly expressed in neurons

Following our observation of a wide-spread expression of endogenous ORF1p throughout the brain, we first addressed the question of the cellular identity of ORF1p+ cells. To this end, we used the neuron-specific marker NeuN, commonly used to identify post-mitotic neurons in the central nervous system ⁴⁶. This allowed us to determine the proportion of neuronal (NeuN+) or non-neuronal cells (NeuN-) expressing ORF1p (ORF1p+) or not (ORF1p-). Making use of our large-scale imaging approach (Fig. 1A), we observed drastic dissimilarities in detected cellular proportions between the white and grey brain matter. As expected, we observed only 1% of NeuN+ cells in the white matter (corpus callosum; Fig. 2A) validating both, the neuronal marker NeuN as such and the ABBA superposition of the Allen Brain Atlas onto the sagittal brain slices. In the grey matter, our approach detected 30.5% NeuN+ cells (dark red and yellow bars in Fig. 2A) which, according to the literature, should include all post-mitotic neurons with only minor exceptions ⁴⁶⁻⁴⁹ and corresponds to the reported proportion of neurons present in the mouse brain ⁵⁰. The nine identified grey matter regions in Fig. 2A display the proportions of the different cell types per region. The proportion of all cells in a given region which are positive for ORF1p (dark red bars) differed between regions (lowest proportion: hindbrain: 7%; highest proportion dorsal striatum: 26.6%). In the isocortex and the midbrain motor-related regions, the majority of neurons detected express ORF1p (54% and 59% by large-scale analysis, Suppl Fig. 206
3A; 68.7% and 68.8% by confocal imaging, Fig. 2B, quantified in C), while in the midbrain
sensory related regions the proportion dropped to 25% whereas it reached 82% in the thalamus
(Suppl Fig. 3A). Altogether, nearly half of all NeuN+ cells throughout the mouse brain
expressed ORF1p (mean of all regions: 48.2%; Suppl Fig. 3A). Regarding the cell identity of
ORF1p+ cells brain-wide, more than 70% were identified as neuronal by the large-scale
approach (Suppl Fig. 3B). This contrasted somewhat with results obtained by the second
approach using confocal imaging on multiple z-stacks which indicated that 91.3% (frontal
cortex) and 88.5% (ventral midbrain) of ORF1p+ cells were neuronal (Fig. 2D). This difference
in percentages of ORF1p+ expressing neurons among all neurons between the large-scale image
cell detection methodology and the confocal workflow is most probably due to technical
limitations inherent to the large-scale pipeline. Indeed, with the latter approach, region-
dependent differences in cell density and signal intensity might be the cause for an
underestimation of the proportion of ORF1p+ cells being neuronal due to difficulties in cell
detection by StarDist/Cellpose (high cell density) on a single focal plan, technical difficulties
which are widely reduced by the multiple z-stack based approach when using a confocal
microscope. Moreover, the large-scale pipeline involves background measurements in each
sub-region in order to apply stringent filtering. This, however, results in a loss of true positives
cells, but avoids cells which are out-of-focus, the presence of which is inherent to the slide
scanner microscope which lacks optical sectioning (see Materials & methods section for
evaluated model performance). Notably, frontal cortex and ventral midbrain present similar
proportion of neurons expressing ORF1p (Fig. 2C), although the percentage of NeuN+ cells
between these two regions is significantly different (Suppl Fig. 3C). As we could not rule out
that ORF1p might also be expressed in non-neuronal cells, we turned to non-neuronal markers
specific for different glial cell populations using two different astrocytic markers (GFAP,
Sox9), the astro- and oligodendrocytic marker S100β and the microglial marker Iba1<sup>50,51</sup> and
performed co-staining with ORF1p followed by confocal imaging as illustrated in Figure 2E.
We screened multiple images of frontal cortex, ventral midbrain, hippocampus and striatum
and did not find a single ORF1p+ cell which could unambiguously be defined as non-neuronal.
This indicated that ORF1p is not or only very rarely expressed in non-neuronal cells. To further
confirm the predominant presence of expression of ORF1p in neurons and the absence of
ORF1p expression in non-neuronal cells, we used fluorescence-activated cell sorting (FACS)
to isolate neurons (using a NeuN antibody) and non-neuronal cells (NeuN-) from the adult
mouse brain followed by Western blotting with an antibody against ORF1p (Fig. 2F, 2G). As
described above, this antibody is well characterized, extensively used and was validated further
in this study. After FACS-sorting of neurons from the adult mouse brain using an antibody
against NeuN (Fig. 2F, G), we detected ORF1p exclusively in the neuronal population (NeuN+,
internal control = heavy chain), confirming the results based on two different imaging
approaches. Finally, to assess whether predominant, if not exclusive ORF1p expression in
neurons is mouse brain specific or a pattern also applicable to the human brain, we investigated
the identity of ORF1p expressing cells in the post-mortem cingulate gyrus of a healthy human
brain. Similar to what we found in the mouse brain, we observed sparse NeuN expression in
the white and extensive NeuN staining in the grey matter corresponding to the cortical layers
(Suppl Fig. 2D, grey and white matter separated by a dashed line) with ORF1p+ cells
predominantly located in the grey matter (confocal images in Fig. 2H, Suppl Fig 2E are located
in the grey matter). All cells stained by ORF1p were co-stained with NeuN indicating that
ORF1p was expressed in neuronal cells in the human brain (Fig. 2H). However, due to the
lower signal quality inherent to human post-mortem sections compared to mouse sections, the
identity of ORF1p+ cells was estimated to be 80% neuronal by the automated image analysis
pipeline of confocal images (Fig. 2I), although no ORF1p+ / NeuN- cells could be clearly
272 identified. Of all neurons identified, 37.2% were ORF1p+ (Fig. 2J), indicating that, similar to
273 the mouse brain, only a fraction of neurons express ORF1p (Fig. 2H, right).

274 Next, we asked the question of a neuron-subtype specific expression of ORF1p. Our
275 previous study had revealed a higher expression of ORF1p in tyrosine-hydroxylase (TH)
276 positive neurons compared to TH-negative neurons in the mouse ventral midbrain <sup>17</sup>. A recent
277 study reported that endogenous LINE-1 RNA and ORF1p expression were higher in
278 parvalbumin (PV)-positive interneurons compared to PV-negative neurons in the mouse
279 hippocampus <sup>18</sup>. To address the question of a generalized co-expression of ORF1p and PV cells,
280 we co-stained sagittal brain sections of young mice with antibodies against ORF1p and PV and,
281 in some cases the lectin Wisteria floribunda agglutinin (WFA), which specifically stains
282 glycoproteins surrounding PV+ neurons. Confocal imaging on several brain regions including
283 the hippocampus, cortex, cerebellum, hindbrain, ventral midbrain and thalamus revealed
284 ORF1p+ neurons co-expressing PV, but also many examples of equally intense ORF1p+
285 neurons that do not express PV (Suppl Fig. 4).

286 In summary, ORF1p expression in the mouse and human brain is widely restricted to neurons
287 of which a proportion express ORF1p. This raises the question of the function and consequences
288 of ORF1p expression specifically in neurons but also on the dynamic regulation of this
289 expression upon exogenous (exposome) or endogenous (aging) challenges.
290

291 **ORF1p expression is increased in the aged mouse brain**

292 ORF1p is expressed at steady-state throughout the brain, but whether this expression is
293 dynamically regulated remains unknown. Aging has been linked to LINE-1 regulation in some
294 studies <sup>16,52</sup> potentially as both, a trigger and as a consequence of LINE-1 activation, but
295 whether this is true for the brain and if yes, whether this might be region-specific has not been
296 investigated brain-wide. We therefore addressed the question whether advanced age was
297 paralleled by a change of expression patterns or expression levels of ORF1p in the brain. We
298 first analyzed ORF1p expression levels comparing young (3-month) to aged (16-month) mouse
299 brains using the cell detection workflow applied to large-scale images described in Figure 1A.
300 Interestingly, the mean intensity of ORF1p expression increased moderately but significantly
301 with advanced age throughout the brain (13% increase brain-wide; n=4 young mice; n=4 aged
302 mice; p=0.03; Fig. 3A). This was in contrast to another protein, NeuN, which we used as a
303 control and whose intensity did not change between young and aged brains (n=4 young mice;
304 n=4 aged mice; p=0.27; Fig. 3B). Frequency distribution analysis unveiled a shift in ORF1p
305 mean expression per cell in aged mice (Fig. 3C). Importantly, the Hoechst mean intensity within
306 nuclei of ORF1p+ cells, serving as an internal control, showed no significant change (Fig. 3D).
307 Among nine analyzed regions, five demonstrated a general increase in ORF1p mean intensity
308 per cell in aged mice (p≤0.05), a change independent from inter-individual variations in both
309 young and aged mice (Fig. 3E). The increase of ORF1p expression (fold change intensity)
310 throughout the brain, reaching nearly a 30% increase in some regions, is represented on the
311 heatmap in Figure 1F. These results were confirmed by the confocal imaging approach; ORF1p
312 expression in the frontal cortex remained unchanged but increased significantly in the ventral
313 midbrain region in aged mice as shown in Figure 3G and quantified in Figure 3H.

314 We then asked whether the increase in ORF1p expression levels observed in several brain areas
315 in aged compared to young mice was also accompanied by a change in expression patterns. We
316 therefore analyzed cell proportions and densities comparing young and aged mouse
317 brains. Globally, we observed a reduction in the proportion of ORF1p+/NeuN+ cells in aged
318 mouse brains using the cell detection workflow applied to large-scale images described
319 in Figure 1A, a phenomenon mainly driven by the midbrain motor, the dorsal striatum, the
320 pallidum and the thalamus regions (Suppl Fig. 5A, dark red bars, Suppl_Table1). The confocal
321 approach applied to two regions, the frontal cortex and the ventral midbrain (Suppl Fig. 5B),
confirmed this reduction in ORF1p+/NeuN+ cell proportions in favor of the ORF1-/NeuN- cell population in the ventral midbrain with no change in cell proportions in the frontal cortex in accordance with the large-scale imaging approach (Suppl Fig. 5A). The predominantly neuronal identity of ORF1p+ cells, however, was unchanged in the ventral midbrain (Suppl Fig. 5C) just as the proportion of neurons expressing ORF1p (Suppl Fig. 5D). We observed a significant shift in NeuN+/- cell proportions (Suppl Fig. 5E) which could either suggest a decrease in NeuN+ cells or a gain of NeuN- cells in this region with age. While proportions are less sensitive to technical variability and can identify cell population shifts, cell densities allow for absolute comparisons. When quantifying global cellular densities throughout the brain, we did not observe a significant reduction of ORF1p expressing cells (Suppl Fig. 5F), neurons (Suppl Fig. 5G) or non-neuronal cells (Suppl Fig. 5H). When analyzing cell densities in the nine brain regions separately, there were no significant changes in ORF1p positive (Suppl Fig. 5I), NeuN positive (Suppl Fig. 5J) or NeuN negative (Suppl Fig. 5K) cell densities in eight out of nine brain regions. The only exception was the dorsal striatum, but technical limitations applying to this particular brain region might account for these changes. Indeed, the dorsal striatum is different from the other brain regions as it represents the only region consisting of a single ABBA sub-region resulting in only one overall background measurement. Taken together, while there were no major changes in cell proportions, densities nor in ORF1p+ cell identities, we observed an age-dependent increase in ORF1p expression per cell of up to 27%.

341

342 **Coding LINE-1 transcripts are increased in aged human dopaminergic neurons**

Following the observation of increased ORF1p expression in the aged mouse brain, among which the ventral midbrain, and given the age-related susceptibility of dopaminergic neurons in the *SNpc* to cell death and to degeneration in PD<sup>53</sup>, we turned to a previously published RNA-seq dataset of laser-captured micro-dissected post-mortem human dopaminergic neurons
of brain-healthy individuals<sup>54</sup>, in order to interrogate full-length LINE-1 mRNA expression profiles as a function of age. To avoid read-length bias to which TE analysis is particularly sensitive, we analyzed only the data derived from 50bp paired-end reads of linearly amplified total RNA as this dataset represented all age categories (n=41; with ages ranging from 38 to 97; mean age: 79.88 (SD ±12.07); n=6 ≤65y; n=35 >65y; mean PMI: 7.07 (SD ±7.84), mean RIN: 7.09 (±0.94), metadata available in Suppl_Table5). As age-related dysregulation of TEs might not be linear, we considered individuals with ages-at-death younger or equal to 65 years as “young” (n=6, 38-65 years, mean age 57.5 years (SD ±9.9)) and individuals older than 65 years as “aged” (n=35, 65-97 years, mean age 83 years (SD±7.8). The expression of the dopaminergic markers tyrosine hydroxylase (TH) and LMX1B were similar in both populations indicating no apparent change of dopaminergic identity of analyzed melanin-positive dopaminergic neurons (Suppl Fig. 6A, B). Next, we compared the expression of repeat elements at the class, family and name level based on the repeat masker annotation implemented in the UCSC genome browser using a commonly used mapping strategy for repeats consisting of randomly assigning multi-mapping reads<sup>55</sup>. No overt dysregulation of repeat elements at either level of repeat element hierarchy was observed (Suppl Fig. 6C-F). There was a modest but significant increase in several younger LINE-1 elements including L1HS and L1PA2 at the “name” level (Fig. 4A, B), an analysis which was however underpowered (post-hoc power calculation; L1HS: 28.4%; L1PA2: 32.8%) and thus awaits further confirmation in independent studies. No expression changes were observed for HERVK-int, a human endogenous retrovirus family with some copies having retained coding potential (Fig. 4B) or other potentially active TEs like HERVH-int, HERV-Fc1, SVA-F or AluYa5 transcripts in the >65y group (Suppl Fig. 6G). Interestingly, L1HS expression was highly correlated with L1PA2 expression and this correlation extended to almost all younger LINE-1 subfamilies weaning down with evolutionary distance (Fig. 4C). This was not true for other active TEs as L1HS was negatively correlated with HERVK-int
expression (Fig. 4C). Several regulators of LINE-1 activity have been identified<sup>17,56</sup> and
correlation of their expression with L1HS might allow to infer their relevance of interaction
(activation or repression) with L1HS in human dopaminergic neurons. Spearman correlation
analysis revealed three known repressors of LINE-1 activity whose expression was negatively
correlated with LINE-1 expression; EN1 (Engrailed 1<sup>17</sup>, Suppl Fig. 7A) with important
functions for dopaminergic neuron homeostasis<sup>57</sup>, CBX5/HP1a, a heterochromatin binding
protein binding to the histone mark H3K9me3, thereby mediating epigenetic repression<sup>58</sup>
(Suppl Fig. 7B) and XRCC5/6, also known as Ku86/Ku70, which are essential for DNA double-
stranded break repair through the nonhomologous end joining (NHEJ) pathway and limit LINE-
1 full-length insertions<sup>59</sup> (Suppl Fig. 7C). The transcripts of these genes showed, although not
statistically significant, a trend for decreased expression in the elderly (Suppl Fig. 7D-G). Based
on the increase of young LINE-1 families L1HS and L1PA2 in aged human dopaminergic
neurons and the finding that ORF1p was increased in the aged mouse brain, we focused our
attention on LINE-1 elements with coding potential for ORF1 and ORF2 according to the
L1Basev2 annotation which are specific elements comprised in the L1HS and L1PA2
annotation at the “name” level. Most of the 146 full-length and coding LINE-1 termed UIDs (=
Unique Identifier) in the L1Base are L1HS elements (76.03%), whereas the remaining 35 UIDs
belong to the evolutionary older L1PA2 family (Suppl Fig. 7A). The L1Base annotation is based
on the human reference genome (GRCh38) and annotates 146 human full-length (>6kB), intact
LINE-1 elements (ORF1 and ORF2 intact) with a unique identifier from 1 to 146<sup>4</sup>. Attribution
of sequencing reads to a specific, individual TE copy is problematic<sup>60</sup> and several approaches
have been proposed to circumvent this problem including the mapping of unique reads<sup>55</sup>. While
several tools using expectation maximization algorithms in assigning multi-mapping reads have
been developed and successfully tested in simulations<sup>55,61</sup>, we used a different approach in
mapping unique reads to the L1Base annotation of full-length LINE-1. Specific “hot” LINE-1
397 loci in a given cellular context have been identified ³, but usage of the L1Base annotation
398 enabled an unbiased approach albeit ignoring polymorphic LINE-1 sequences. Unique read
399 mapping strategies for repeat elements, especially young LINE-1 elements, will unavoidably
400 underestimate LINE-1 locus-specific expression levels ⁵⁵, but will be most accurate in assigning
401 reads to a specific genomic location while allowing the comparison of two different conditions
402 analyzed in parallel. Of the 146 full-length LINE-1 elements in the L1Base annotation, 111
403 were of the L1HS family and 35 belonged to the L1PA2 family (Suppl Fig. 8A). Assuming that
404 expression of UIDs was correlated with mappability, we plotted a mappability count of each
405 UID against its mean normalized read count expression of the six individuals ≤65y (Suppl Fig.
406 8B, C). Non-parametric Spearman correlation revealed no correlation between UID
407 mappability and expression (Suppl Fig. 8C) indicating no apparent bias between the two
408 parameters. However, individual UID dependency of mappability on expression cannot be
409 excluded, especially for high expressing UIDs like UID-16 for example (Suppl Fig. 8B, C).
410 Expression of LINE-1 at the locus-level has been attributed to artefacts not representing
411 autonomous transcription including differential high intronic read counts ⁶², pervasive
412 transcription or reads attributable to passive co-transcription with genes when the LINE-1
413 element is intronic ⁶³. To evaluate the latter, we determined the number of intronic (46.58%)
414 and intergenic UIDs (78/146; Suppl Fig. 8D) and identified the corresponding genes for intronic
415 UIDs (Suppl Fig. 8E). Of the 146 UIDs, 140 passed the threshold of >3 reads in at least 6
416 individuals. Differential expression of UID between “young” and “aged” dopaminergic neurons
417 revealed several significantly deregulated full-length LINE-1 loci (Fig. 5A). Paired analysis of
418 the expression of all UIDs indicated a general increase (Fig. 5B), especially of low expressed
419 UIDs. The comparative analysis of the sum expression of UIDs per individual comparing young
420 (≤65y) with elderly human dopaminergic neurons, however, did not reach statistical
421 significance (Fig. 5C). Several specific loci were dysregulated, in particular UID-68 (Fig. 5A
and 5D), a L1HS element located on chromosome 7 (chr7: 141920659-141926712) in between
two genes, OR9A4 (olfactory receptor family 9 subfamily A member 4) and CLEC5A (C-type
lectin domain containing 5A; Fig. 5E and Suppl Fig.7E). This specific full-length LINE-1
element had a high mappability count of 16 (range of all UIDs: 1-30, mean 9.0 (SD ±6.05),
Suppl Fig. 7C) and a post-hoc power analysis score of 96.6% (continuous endpoint, two
independent samples, alpha 0.05). To rule out any influence of “hosting” gene transcription
interference on measurable UID-68 expression differences, we performed Spearman correlation
which did not indicate any correlation between OR9A4 (Fig. 5F) or CLEC5A (Fig. 5G)
expression with UID-68. Together, this indicated that UID-68 might be a candidate for an age-
dependent gain of activity. Other dysregulated UIDs (i.e. UID-129, UID-37, UID-127 and UID-
137) had either a low mappability score, a low post-hoc power or did not pass the visualization
check in IGV, reinforcing the notion that a combination of quality control criteria is crucial to
retain a specific locus with confidence. In conclusion, TE expression analysis of this human
dataset covering an age-span of 59 years (mean age difference between both groups 25.5 years)
indicates an increase in the expression of young LINE-1 elements including those which have
coding potential in elderly dopaminergic neurons, particularly a specific full-length LINE-1
element on chromosome 7 (UID-68). A slight net sum increase of UID transcripts/cell might
be sufficient for the production of “above steady-state” levels of ORF1p and ORF2p. Other TEs
with coding potential, namely members of the HERV family, were not increased. Further,
correlation analyses suggest that L1HS expression might possibly be controlled by the
homeoprotein EN1, a protein specifically expressed in dopaminergic neurons in the ventral
midbrain<sup>57</sup>, the heterochromatin binding protein HP1 and the DNA repair proteins XRCC5/6.

Endogenous ORF1p interactors in the mouse brain
To go further in our understanding of steady-state neuronal ORF1p expression across the mouse brain, we immunoprecipitated ORF1p and performed quantitative label-free LC-MS/MS to identify potential protein partners of ORF1p in the adult mouse brain. We successfully immunoprecipitated endogenous ORF1p from whole brain lysates (Fig. 6A), where we detect ORF1p exclusively in the 5 independent ORF1p-IP samples (and not at all in 5 independent IgG-IP control samples; Suppl_Table2) and identified a total of 424 potential protein interactors associated with ORF1p (Suppl_Table2; n=5 mice). Using Gene Ontology (GO) analysis, we identified several interacting proteins belonging to GO terms related to known functions of the ORF1p protein in RNA binding, preferentially ⁶⁴ but not exclusively in cis ⁶⁵, for instance RNA decapping and mRNA catabolic process, or related to the known presence of ORF1p in ribonucleoprotein particles ⁶⁶,⁶⁷ (GO: cytoplasmic ribonucleotide granule) or the presence of ORF1p in p-bodies ⁶⁵ as shown in Figure 6B and listed in Suppl_Table3. Other GO terms that emerged, to our knowledge not previously associated with ORF1p, were related to cGMP-mediated signaling (GO: cGMP-mediated signaling and 3'-5'phosphodiesterase activity: i.e. PDE4A, PDE4B, PDE4DIP) and the cytoskeleton (GO: microtubule depolymerization, cytoskeleton organization, microtubule and tubulin binding, cytoskeletal motor activity and protein binding). cGMP signaling is regulated by 3'-5' phosphodiesterases (PDEs) which degrade 3',5'-cyclic guanosine monophosphate (cGMP) and 3',5'-cyclic adenosine monophosphate (cAMP), an activity essential for cell physiology for the integration of extra- and intracellular signals including neuronal excitability, synaptic transmission and neuroplasticity ⁶⁸,⁶⁹. Further, several ORF1p interacting proteins were constituents of the mating-type switching/sucrose nonfermenting complex (SWI/SNF complex), i.e. ARID1A, ARID1B, SMARCA2, SMARCB1, SMARCC2), an ATP-dependent chromatin remodeler complex disrupting nucleosome/DNA contacts to facilitate DNA/chromatin accessibility by shifting, removing or exchanging nucleosomes along DNA ⁷⁰,⁷¹. Finally, we also observed
proteins belonging to the GO term “neuronal cell body”, corroborating with the neuron-specific
presence of ORF1p in the brain. A comparative analysis with previous mass spectrometry
studies 35,67,72–76 aimed at identifying ORF1p interacting proteins unveiled significantly more
common proteins than randomly expected (overrepresentation test; representation factor 2.6,
p< 5.4e-08; Fig. 6C), including LARP1, STAU2, ATXN2, RALY, TARBP2 or DDX21 (for a
full list see Suppl_Table4). The presence of a significant number of overlapping ORF1p
interactors in different non-neuronal human cells (HEK 67,72,73, HeLa 74, human breast and
ovarian tumors 76 and hESCs 75) and mouse brain cells (our study), suggest conserved key
interactors between both species and between cell types, with a subset of these proteins
regulating RNA degradation and translation potentially relevant for the LINE-1 lifecycle itself.
However, differences in experimental conditions in between studies could also influence this
overlap. ORF1p interactors found in mouse spermatocytes 35 were also present in our analysis
including CNOT10, CNOT11, PRKRA and FXR2 among others (Suppl_Table4). To unravel
the physical interactions between the identified interactors of endogenous ORF1p within the
mouse brain, we used the STRING database (Search Tool for Recurring Instances of
Neighboring Genes, https://string-db.org/). This analysis generated a network representation,
where physical interactions are represented by edges (Fig. 6D). In analogy with the GO term
analysis, ORF1p displayed interactions with various clusters, including well-known RNA
decapping complexes directed against LINE-1 RNA, which also encompassed DCP2 and
DCP1A which had not previously been identified as interacting with ORF1p 77. Furthermore,
ORF1p exhibited interactions with the SWI/SNF complex (highlighted in red) as well as
subunits of the RNA polymerase II complex suggesting a direct or indirect association with
accessible chromatin, a hitherto unknown interaction of ORF1p with chromatin compartments
within the nucleus. Notably, a multitude of novel interactors belonged to the “neuronal cell
body” and “neuron projections” clusters, proposing potential neuron-specific partners of
ORF1p such as GRM2/5, BAI1, EPHA4, KCNN2, GRIK2 and DMD among others. A last cluster, formed by NCOA5 (Nuclear Receptor Coactivator 5), NXF1 (Nuclear RNA Export Factor 1), RANBP2 and NU133 (both nucleoporins), might imply a role for these interactions in L1-RNA nuclear export and/or a mechanism for the LINE-1 RNP to gain access to the nucleus in post-mitotic neurons. Altogether, the identification of known and novel interactors of ORF1p in the mouse brain suggests roles of ORF1p in the LINE-1 life cycle (RNA binding and metabolism, RNP formation, nuclear access) but also suggests potential novel physiological roles of ORF1p in the brain related to cytoskeleton organization, cGMP signaling, neuron-specific functions (i.e. synaptic signaling, Suppl_Table3) and chromatin organization and/or transcription regulation.

506

507

## Discussion

508

While LINE-1 derepression in aging has been extensively explored in peripheral tissues and various pathologies, including cancer, our understanding of LINE-1, particularly ORF1p, in the central nervous system remains limited<sup>20,41,78</sup>. A recent search of ORF1p peptides in mass spectrometry data spanning 29 different healthy tissues did not reveal the presence of ORF1p in the brain, suggesting that its presence might lie below detection limits<sup>20</sup>. Only a few studies explored and detected ORF1p expression in the brain, most focusing on a specific region (in mice<sup>17,33</sup> in rats<sup>79</sup> and in human post-mortem brain<sup>19</sup>), but it remained unclear if ORF1p is expressed throughout the entire brain, exhibits cell-type specificity, and most intriguingly, if its expression is influenced by the aging process. Here, using well characterized and validated antibodies, we demonstrate that ORF1p is expressed throughout the entire mouse brain and in at least three regions of the human post-mortem brain at steady-state. Leveraging a

520
comprehensive workflow that incorporates brain atlas registration and machine learning
algorithms, we quantified tens of thousands of brain cells, enabling a profound analysis of cell
proportions, cell identities, densities and ORF1p expression levels across the entire brain.
Surprisingly, more than one-fifth of detected cells expressed ORF1p. Regional variations in
ORF1p expression levels were observed, with each region exhibiting distinct proportions, cell
density, and signal intensity of ORF1p+ cells. In a non-neurologically diseased human brain,
ORF1p was expressed in all three regions examined, that is the cingulate gyrus, the frontal
cortex and the cerebellum. This is in accordance to an earlier study using histological staining,
which found ORF1p expression in the human frontal cortex, the hippocampus, in basal ganglia,
thalamus, midbrain and the spinal cord <sup>19</sup>. This suggests, similarly to the mouse brain, a
generalized expression across the human brain. On the transcriptomic level using long-read
sequencing of GTEx tissues, brain and liver were highlighted as the organs displaying the
highest expression of putatively active, full-length LINE-1 elements <sup>80</sup>. However, when the
authors looked at sub-regions, they found transcript expression in cerebellar hemispheres and
the putamen, but not in the caudate and the anterior cingulate gyrus and frontal cortex <sup>80</sup>. This
is in contrast to our data and the data from Sur et al, where ORF1p was found to be expressed
in the latter two regions using two different antibodies. We used the anti-human LINE-1 ORF1p
antibody clone 4H1, a well characterized antibody <sup>78,81</sup>. While the sample size for the staining
of human post-mortem tissues certainly needs to be increased in order to draw quantitative
conclusions, the presence of the protein in two independent studies does point to a steady-state
expression of ORF1p in the human brain.

It is interesting to note that ORF1p is expressed at steady-state in both, the mouse and
human brain, despite the fact that evolutionary young and thus potentially ORF1-encoding
LINE-1 elements in mice <sup>82</sup> (L1A, Tf/Gf) and in humans <sup>4</sup> (L1HS, L1PA2) differ significantly
in number, sequence and regulation <sup>83</sup>. Most differences lie in the 5'promoter region, but also
546 ORF1 and ORF2 sequences are strikingly divergent between mouse and humans. For example,
547 mouse LINE-1 promoters are composed of a varying number of monomers, a structure not
548 found in human-specific LINE-1 promoters 84. This has obvious implications for LINE-1
549 expression regulation which can be very different, but examples of co-evolution of regulatory
550 networks have been described 85 and might operate in the brain to regulate LINE-1 and thereby
551 ORF1p expression.

552 In the mouse brain, we find ORF1p to be expressed predominantly if not exclusively in
553 neurons using immunofluorescence and fluorescence-activated cell sorting (FACS) followed
554 by Western blotting. This result is consistent with previous studies, such as the identification of
555 ORF1p in excitatory neurons within the mouse frontal cortex 86, in parvalbumin neurons in the
556 hippocampus 18, its presence in neurons in the ventral midbrain including in dopaminergic
557 neurons 17 and the recognition of morphological similarities between stained neurons and
558 ORF1p+ cells in a post-mortem hippocampus sample of a healthy individual 19. We also
559 detected ORF1p in Purkinje cells in the mouse and human cerebellum. Neuronal specificity or
560 preference of LINE-1 expression was also shown on the transcriptomic level in recent studies
561 investigating LINE-1 expression in the mouse hippocampus, where neuronal LINE-1
562 expression exceeded that of astrocytes and microglia by approximately twofold 20, is abundant
563 in parvalbumin interneurons 18 and single-nuclei RNA-seq data from the mouse hippocampus
564 and frontal cortex which confirmed globally that repetitive elements including LINE-1 are more
565 active in neurons than in glial cells 86. In the human brain, LINE-1 transcripts were found in
566 greater quantities in neurons compared to non-neuronal cells by single-nucleus sequencing87.
567 Furthermore, retrotransposition-competent LINE-1 elements were found expressed exclusively
568 in neurons 88. While ORF1p expression is suggested to be expressed in microglia under
569 experimental autoimmune encephalomyelitis conditions in the spinal cord 89, no evidence of
570 such expression was observed in non-neuronal cells under non-pathological condition.
On average, throughout the mouse brain, the majority of neurons were positive for ORF1p and in some regions (i.e. the thalamus) around 80% of neurons expressed ORF1p. Comparing the results of both imaging approaches, the percentages of neurons expressing ORF1p in the ventral midbrain and frontal cortex were roughly similar (around 70% of neurons expressed ORF1p as quantified by confocal imaging and about 60% of neurons were identified as ORF1p+ using the slide scanner approach). In the human cingulate gyrus, we found that 37.2% of neurons express ORF1p and that 80% of cells expressing ORF1p were neurons, which are proportions similar to some regions of the mouse brain. It is however possible that these percentages are underestimated due to technical issues inherent to the machine-learning based algorithm for cell detection as our observations often indicated a positive signal in neurons which were classified as negative due to a particular shape or our stringent intensity threshold. A question which arises based on these findings is whether specific features distinguish ORF1p+ and ORF1p- neurons. One hint comes from a recent study suggesting that in the mouse hippocampus, it is the parvalbumin positive neurons that predominantly express ORF1p <sup>18</sup>. However, as we show here, while PV-positive neurons often co-stain with ORF1p, not all ORF1p positive cells are PV-positive. In the mouse ventral midbrain, TH-positive dopaminergic neurons express higher levels of ORF1p compared to surrounding, non-dopaminergic neurons <sup>17</sup> (and this study Fig. 1B, panel 8). In the mouse cerebellum, ORF1p staining was detected in Purkinje cells and in the human post-mortem brain in Purkinje and possibly in Basket cells. Parvalbumin positive neurons are inhibitory neurons, so are Purkinje and Basket cells. However, dopaminergic neurons are modulatory neurons exerting excitatory and inhibitory effects depending on the brain region they act on. Specific neurons in the granular layer (i.e. Golgi and unipolar brush cells) of the cerebellum are inhibitory, but ORF1p negative, indicating that the decisive feature might not be the excitatory or inhibitory nature of a neuron. Further, ORF1p is expressed in excitatory (CamKIIa-positive) and CamKIIa-negative neurons
596 in the mouse frontal cortex<sup>86</sup> and there is evidence of full-length L1 RNA expression in both
597 excitatory and inhibitory neurons<sup>87</sup>. While further studies are necessary to define the neuronal
598 subtypes expressing ORF1p and their epigenetic make-up allowing this expression, it seems
599 reasonable to conclude on the above-mentioned data that there is no neuronal sub-type
600 specificity characterizing ORF1p expressing neurons. Another possibility is a cell-type specific
601 chromatin organization permissive for the expression of LINE-1 and future single-cell studies
602 in the mouse and human brain might reveal those differences.

603 Because transposable elements are known to become active in somatic tissues during
604 aging<sup>15,16,28,90,91</sup>, we aimed to investigate whether there was a corresponding increase at the
605 protein level. In aged mice, ORF1p expression significantly increased throughout the mouse
606 brain consistent with a previously documented increase in ORF1p outside the central nervous
607 system in aged rats<sup>79,92</sup> and aged mice<sup>90</sup> and in neurons of layer 2/3 of the mouse frontal cortex
608<sup>86</sup>. By quantifying the mean intensity of ORF1p in over 70 000 cells identified as ORF1p+, we
609 were able to characterize the extent of this increase in each anatomical sub-region. Remarkably,
610 apart from the isocortex which did not show any change, ORF1p expression increased in all
611 other brain regions by 7% to 27%, indicating a generalized increase of ORF1p expression in
612 neurons throughout the brain (13%). We did not detect any change in cell identity of ORF1p
613 expressing cells, that is, ORF1p expression remained predominantly if not exclusively
614 neuronal. Globally, there was also no change in ORF1p-positive, neuronal or non-neuronal cell
615 densities in the aged mouse brain. Further investigations are necessary to investigate the
616 underlying mechanism of the loss of ORF1p+ cells in the dorsal striatum in the aged mouse
617 brain and to examine a possible relationship to the change of proportions of cells in the ventral
618 midbrain, a structure which contains the SNpc which projects to the dorsal striatum and which
619 is prone to LINE-1 driven neuronal degeneration<sup>17</sup>. Thus, while ORF1p intensities per cell
increase significantly in older mice in several brain regions, here is no global change in ORF1p+ cell numbers.

An increase of ORF1p might have several direct or indirect consequences on a cell or here, on a neuron. As ORF1p is translated from a polycistronic LINE-1 RNA together with ORF2p, albeit in much higher amounts (the estimated ratio ORF1p to ORF2p is 240:1 in non-native conditions)⁹³, it can be expected that a LINE-1 ribonucleotide particles are formed and ORF2-dependent cell toxicity in form of genomic instability¹⁷,²¹ and single-stranded cytoplasmic DNA triggered inflammation²⁷,²⁸,⁹⁰ might result. This has been shown in mouse dopaminergic neurons where oxidative stress induced LINE-1 causally contributed to neurodegeneration¹⁷.

Neurodegeneration was partially prevented by anti-LINE-1 strategies among which NRTIs¹⁷ and similar LINE-1 protein-dependent neuronal toxicity has been shown in drosophila³¹,³² and the mouse cerebellum³³.

In order to test whether an increase in LINE-1 is a feature of human brain aging, we turned to a unique RNA-seq dataset of human laser-captured dopaminergic neurons of 41 individuals ranging from 38 to 99 years⁵⁴. In accordance with our focus on LINE-1 sequences which are full-length and coding, we developed a rationale to interrogate LINE-1 families with representatives that are coding (L1HS, L1PA2, multimappers; RepeatMasker) and to specifically investigate full-length LINE-1 elements that have intact open reading frames for ORF1p and ORF2p (unique reads; L1Basev2⁴). Indeed, we find an increase in L1HS and L1PA2 elements in individuals ≥65y as well as an increase in specific full-length LINE-1 elements but only a trend for increase of all full-length LINE-1 in sum in the elderly. This analysis has technical limitations inherent to transcriptomic analysis of repeat elements especially as it is based on short-read sequences and on a limited and disequilibrated number of individuals in both groups. Nevertheless, we tried to rule out several biases by demonstrating
that mappability did not correlate with expression overall and used a combination of visualization, post-hoc power analysis and analysis of the mappability profile of each differentially expressed full-length LINE-1 locus. Interestingly, dysregulated full-length LINE-1 elements in aged dopaminergic neurons did not correspond to those identified in bladder cancer <sup>94</sup> indicating the intricate nature of this expression across tissues and pathological conditions. Overall, a slight net sum increase of UID transcripts/cell might be sufficient for the production of “above steady-state” levels ORF1p and ORF2p. Further, a dissociation of LINE-1 transcript and protein levels in aging has been observed recently in excitatory neurons of the mouse cortex. In the absence of transcriptional changes of LINE-1, protein levels of ORF1p were increased <sup>86</sup>.

We can only speculate about the reason for an increase in ORF1p in the aged brain. A recent single-cell epigenome analysis of the mouse brain suggested a specific decay of heterochromatin in excitatory neurons of the mouse brain with age which was paralleled by an increase in ORF1p, albeit equally in excitatory and inhibitory neurons, again not indicating any dependency of ORF1p regulation on the excitatory or inhibitory nature of neurons <sup>86</sup>. Chromatin and particularly heterochromatin disorganization are a primary hallmark of aging <sup>91</sup> but other repressive cellular pathways which control the LINE-1 life cycle might also fail with aging <sup>13</sup>. Another possibility is a loss of accessibility of repressive factors to the LINE-1 promoter or an age-dependent decrease in their expression. Matrix correlation analysis of several known LINE-1 regulators, both positive and negative, revealed possible regulators of young LINE-1 sequences in human dopaminergic neurons. Despite known and most probable cell-type unspecific regulatory factors like the heterochromatin binding protein CBX5/HP1 <sup>58</sup> or the DNA repair proteins XRCC5 and XRCC6 <sup>56</sup>, we identified the homeoprotein EN1 as negatively correlated with young LINE-1 elements including L1HS and L1PA2. EN1 is an essential protein for mouse dopaminergic neuronal survival <sup>57</sup> and binds, in its properties as a
transcription factor, to the promoter of LINE-1 in mouse dopaminergic neurons <sup>17</sup>. As EN1 is specifically expressed in dopaminergic neurons in the ventral midbrain, our findings suggest that EN1 controls LINE-1 expression in human dopaminergic neurons as well and serves as an example for a neuronal sub-type specific regulation of LINE-1. Although these proteins are known regulators of LINE-1, this correlative relationship awaits experimental validation.

The heterogenous, brain-wide presence of ORF1p expression at steady-state is intriguing. In cancer cell lines or mouse spermatocytes, ORF1p interacts with several “host” proteins, some if not most of which are related to the LINE-1 life cycle. However, a profile of endogenous ORF1p interactors in the mouse brain might inform on possible other and organ-specific functions besides its binding to the LINE-1 RNA in “cis”<sup>35</sup>. Among the total 424 potential interactors of endogenous ORF1p in the mouse brain, 38 partners had been previously identified by mass spectrometry in human cancers, cancerous cell lines and mouse spermatocytes <sup>35,67,72-76</sup> (Suppl_Table4). This supports the validity of the list of ORF1p partners identified, although we cannot rule out the possibility that unspecific protein partners might be pulled down due to colocalization in the same subcellular compartment. GO term analysis contained expected categories like “P-body”, mRNA metabolism related categories and “ribonucleoprotein granule”. We also identified NXF1 as a protein partner of ORF1p, a protein found to interact with LINE-1 RNA related to its nuclear export <sup>95</sup>. This suggests the conservation of key interactors probably essential for completing or repressing the LINE-1 life cycle in both species, despite the divergence of mouse and human ORF1p protein sequences <sup>96</sup>. Along these lines, several ORF1p protein partners we identified might complete the list of post-transcriptional regulators implicated in LINE-1 silencing. Recent work conducted on human cancerous cell lines has demonstrated that MOV10 orchestrates the recruitment of DCP2 for LINE-1 RNA decapping <sup>77</sup>. In our analysis, we identified DCP2 along with DCP1A, known to enhance the decapping activity of DCP2 <sup>97</sup>, and DCP1b, a pivotal component of the mRNA decapping
complex ⁹⁸. Intriguingly, MOV10 was not detected in our mass spectrometry analysis, despite its established role in recruiting DCP2 and forming a complex with L1-RNP to mediate LINE-1 RNA decapping, as reported by Liu et al ⁷⁷. However, we found two enhancers of mRNA decapping, EDC3 and EDC4, both core components of P-bodies, a membrane-less organelle known to contain L1-RNP ⁶⁵. Multiple ubiquitin-ligase proteins were found although not appearing as a significantly enriched GO term. These results add to the picture of the post-transcriptional and translational control of ORF1p and suggest that these mechanisms, despite a steady-state expression, are operational in neurons. Further, several neuron-specific interactors were identified belonging to GO term categories “neuron projection” (75 proteins) and “neuronal cell body” (5 proteins), again pointing to the neuron-predominant expression of ORF1p in the mouse brain. Other interesting aspects were raised from this analysis. Among significantly enriched GO terms, several were related to the cytoskeleton, the functional consequences of which need to be determined in future studies. Our screen also identified PDE10A as an interactor of ORF1p in the mouse brain, a PDE almost exclusively expressed in medium spiny neurons of the striatum and a target for treatment of neurological diseases related to basal ganglia function like Huntington’s disease, schizophrenia and Tourette syndrome ⁹⁹. Interestingly, PDE10A inhibition is related to beta-catenin signaling, another GO term which emerged from our screen ¹⁰⁰. Finally, we found components of RNA polymerase II and the SWI/SNF complex as partners of ORF1p. This might further indicate that ORF1p has access to the nucleus in mouse brain neurons as described for other cells ¹⁰¹,¹⁰², however a bias due to a post-lysis effect cannot be excluded. These findings give rise to intriguing questions regarding the potential function of ORF1p in neuron in health and disease as (i) ORF1p is widely distributed throughout the brain under normal physiological conditions, (ii) ORF1p shows a wide range expression levels within and in between regions, (iii) ORF1p is expressed predominantly if not exclusively in neurons, (iv) but not in all neurons and (v) interacts with
720 proteins that might not directly relate to the LINE-1 life cycle, some of which are neuron-
721 specific. In addition, physicochemical properties of ORF1p to form compacted nucleic acid -
722 bound complexes with sequestration potential were shown <sup>96,103</sup>. Future loss-of-function studies
723 should help to shed light on the necessity of ORF1p for neuronal functions if they exist. This
724 data spurs the idea of a possible “physiological” function of ORF1p as an integrative protein
725 with exapted function in neuronal homeostasis and a loss of restriction in the aged brain limiting
726 LINE-1 expression to steady-state levels.

727

728 **Materials & Methods**

729

730 **Animals**

731 Swiss OF1 wild-type mice (Janvier) were housed on a 12h light/dark cycle with free access to
732 water and food. Mice were sacrificed at 3-month or 16-month. Animal experiments were
733 performed according to the EU directive 2010/63/EU.

734

735 **Mouse tissue dissection and protein extraction**

736 Tissues were extracted from 3-month-old and 16-month-old Swiss/OF1 mice. Briefly, the two
737 hemispheres were separated in ice cold PBS -/-. For each mouse, one hemisphere was rinsed
738 and fixed in 4% PFA for 1h followed by 24h of incubation in 30% sucrose. Hemispheres were
739 kept at -20°C until being sliced on a freezing microtome (Epredia, HM 450) with a 20µm
740 thickness. The other hemisphere was dissected in ice cold PBS -/ 1X and 6 brain regions were
741 rinsed, cut in small pieces and dissociated separately using a large (21G) to small gauge (27G)
742 needle in RIPA lysis buffer for 5 min. Lysates were kept on ice for 25 min, were sonicated for
743 15 min and supernatants were collected after a 30 min centrifugation at 4°C at 14 000 rpm.
744 Proteins were quantified and Laemmli buffer was added before boiling for 10min at 95°C to be
745 used for Western Blot.

746

747 **Human Samples:**
748 Cerebellum, frontal cortex and cingulate gyrus human samples were provided by Neuro-CEB
749 biobank from a 78-year-old brain-healthy male and conserved at -80°C.

750

751 **Human Samples pulverization and protein extraction**
752 We used the dry pulverizer Cryoprep (Covaris) for pulverization of tissue blocs. Each sample
753 was disposed in a liquid-nitrogen precooled Tissue-tube bag and dry cryo-pulverized with one
754 impact at the maximum level. The pulverized brain sample was then weighed and resuspended
755 in lysis buffer (mg/v) (0.32M sucrose, 5mM CaCl₂, 3mM Mg(CH3COOH)₂, 0.1mM EDTA,
756 10mM Tris-HCL pH8, 1mM DTT, 0.1% TritonX-100 and Protease Inhibitors), kept on ice for
757 30 min with gentle up-and-down pipetting until homogenization. We added 2X RIPA buffer
758 (v/v) to totals fractions for 30 min on ice. We then sonicated samples 2 times for 15 min.
759 AtlasSupernatants were collected after a 30 min centrifugation at 14 000 rpm at 4°C, proteins
760 were quantified and Laemmli buffer was added to be used for Western Blot. All samples were
761 boiled 10 min at 95°C to be used for Western Blot.

762

763 **Cell culture and siRNA delivery**
764 LUHMES were purchased from ATCC (CRL2927). Cells were cultured on 50 µg/mL Poly-L-
765 ornithine (Merck) and 1 µg/mL human plasma fibronectin (Sigma) coated flasks and cultured
766 in Advanced DMEM/F12 (Gibco) added with 1% N-2 supplement (Gibco), GlutaMax (Gibco)
767 and 40 ng/mL human recombinant FGF (Peprotech) at in 5 % CO2, 37C° incubator.
768 Differentiation was initiated by adding to the media 1 µg/ml doxycycline (Sigma), 2 ng/ml
769 recombinant human GDNF (Peprotech) and 1 mM cAMP (Sigma). Media was changed every
770 two days. Experiences were performed on day 7 of differentiation. Cells were passaged less
771 than 12 times.

772
773 MN9D were purchased from Merck (SCC281). Cells were cultured on 1 mg/mL poly-lysine
774 (Merck) coated flasks and cultured in DMEM High Glucose (Sigma, D5796) with 10% FBS
775 (Gibco) in 5% CO2, 37C° incubator. Over a period of 10 days, cells were differentiated by
776 adding to the media 1 mM n-butyrate (Sigma) and 1 mM dibutyryl cAMP (Sigma). Media was
777 changed every two days. Experiences were performed on day 10 of differentiation. Cells were
778 passaged less than 15 times.

779
780 LUHMES were lipofected using RNAiMAX (Invitrogen) at day 3 of differentiation with 100
781 nM of siRNA. MN9D were lipofected using RNAiMAX (Invitrogen) at day 7 of differentiation
782 with 100 nM of siRNA. The siRNA sequences used were as follows:

783
784 siRNA control: TAATGTATTGGAACGCATA

785 siRNA ORF1 (LUHMES): AAGAAGGCTTCAGACGATCAA

786 siRNA ORF1 (MN9D): CTATTACTCTGATACCTAAAC

787
788 LUHMES were scrapped at day 7 of differentiation and MN9D at 10 days of differentiation, in
789 RIPA buffer (10mM Tris-HCl, pH 8.0; 150mM NaCl; 1mM EDTA; 1% Triton X-100; 0.1%
790 Sodium Deoxycholate; 0.1% SDS). Laemmli buffer was added and samples were boiled 10 min
791 at 95C° before being loaded on a gel.

792
793 Western Blot
We used 1.5mm NuPAGE 4-12% Bis-Tris-Gel (Invitrogen™). Proteins samples (sorted mouse brain cells: 10000 cells/ µl -> 5 µl loaded; human brain lysates: 10µg; mouse brain lysates: 20µg) were loaded and gel migration was performed with NuPAGE™ MES SDS Running Buffer (Invitrogen™) for 45 minutes at 200mV. Gels were transferred onto a methanol activated PVDF membrane (Immobilon) in a buffer containing: Tris 25 mM, pH=8,3 and Glycine 192 mM, during 1h30 at 400 mA. Membranes were blocked 30 min with 5% milk in TBST (0,2% Tween 20, 150 mM NaCl, 10 mM Tris pH:8). The primary antibodies (mouse ORF1p antibody: abcam ab216324; human ORF1p antibody: abcam ab245249) were diluted in 5% milk in TBST, and membranes were incubated o/n at 4 C°. After 3 x 10 min washing in TBST, membranes were incubated for 1h30 with the respective secondary antibodies diluted at a concentration of 1/2000 in 5% milk TBST. Membranes were washed 3 x 10 min in TBST and were revealed by the LAS-4000 Fujifilm system using Clarity Western ECL Substrate (Bio Rad) or Maxi Clarity Western ECL Substrate (Bio Rad).

## Immunostaining

Sagittal mouse brains slices were fixed for 10min in PFA 4% and rinsed 3 times for 10min in PBS -/-. Slices were then incubated 20 min in glycine 100mM, washed 3 times for 5min in PBS and immersed in 10mM citrate pH 6 at 62°C during 45min for antigen retrieval. Slices were then immersed 3 times in PBS with Triton X-100 0.2% and incubated in blocking buffer for 1,5 h (PBS with Triton X-100 0.2% and FBS (10%) previously inactivated 20min at 56°C (Gibco, 16141061). Primary antibodies (ORF1p antibody: abcam ab216324; NeuN antibody: GeneTex GTX00837) were diluted (1/200 and 1/500 respectively) in blocking buffer and incubated with slices overnight at 4°C and then washed 3 times for 10 min with PBS. For validation, an in-house ORF1p antibody was used (09) (guinea pig, 1/200). For non-neuronal marker (GFAP antibody: Millipore AB5541; Iba1 antibody: GeneTex GTX101495; Sox9 antibody:
819 RnDsystems AF3075; S100β antibody: Sigma S2532), antibodies were diluted at 1/500.
820 Additionally, WFA (Sigma L1516) and PV antibodies (Swant PV235) were used, diluted at
821 1/500 and 1/1000 respectively. Suitable secondary antibodies (Invitrogen) and Hoechst
822 (Invitrogen, 15586276) were incubated for 1,5h at 1/2000 in PBS with inactivated FBS (10%)
823 and washed 3 times 10 min in PBS. To quench tissue autofluorescence, especially lipofuscin,
824 TrueBlack Plus (Biotium) in PBS was used during 10min. Slices were rinsed 3 times in PBS
825 and mounted with Fluoromount (Invitrogen™).

826 For human cingulate gyrus stainings, the same protocol was performed, with the difference that
827 a human ORF1p antibody (Abcam 245249) was used. Mouse and human brain slices were
828 imaged by the Axioscan 7 Digital Slide Scanner (Zeiss) or a Spinning Disk W1 confocal
829 microscope (Yogogawa).

830

831 Blocking peptide

832 The ORF1p antibody (abcam ab216324) was incubated 2h on a turning wheel with excess (4:1)
833 of mouse ORF1p recombinant protein as in ¹⁷ before the blocked antibody was used in the
834 above-described immunofluorescence protocol.

835

836 Quantification of confocal acquisitions

837 Analysis was conducted using a custom-written plugin developed for the Fiji software,
838 incorporating Bio-Formats ¹⁰⁴ and 3D ImageJ Suite ¹⁰⁵ libraries. Code is freely available online
839 at https://github.com/orion-cirb/DAPI_NEUN_ORF1P. Nuclei were detected in the Hoechst
840 channel downscaled by a factor of 2 with the 2D-stitched version of Cellpose ¹⁰⁶ (percentile
841 normalization = [1-99], model = ‘cyto’, diameter = 30, flow threshold = 0.4, cell probability
842 threshold = 0.0, stitching threshold = 0.75). The segmented image was then rescaled to its
843 original size, and the obtained 3D nuclei were filtered by volume to reduce false positive
detections. NeuN+ and ORF1p+ cells were detected in their respective channel using the same approach as for nuclei detection, but with adjusted Cellpose settings (model = 'cyto2', diameter = 40, flow threshold = 0.4, cell probability threshold = 0.0, stitching threshold = 0.75). Finally, each cell was associated with a nucleus having at least half of its volume in contact with. Cells without any associated nucleus were discarded. Each nucleus was thus labeled according to NeuN and/or ORF1p positivity.

Nuclei and cell detection using the respective Cellpose models and hyperparameters were evaluated on eight images per channel, capturing intensity variability across different mouse ages and brain regions. A total of approximately 2,000 nuclei and 1,000 NeuN and ORF1p cells were manually annotated. We evaluated model performance with the average precision (AP) metric, computed from the number of true positives (TP), false positives (FP), and false negatives (FN) as $AP = \frac{TP}{TP+FP+FN}$ at the commonly used Intersection over Union (IoU) threshold of 0.5. The AP at an IoU threshold of 0.5 was 0.995 for nuclei, 0.960 for NeuN, and 0.974 for ORF1p cells. These results confirmed that the selected models and hyperparameters were well-suited for processing the entire dataset.

## ABBA Registration and Qupath analysis

Each sagittal brain section was registered with the Allen Mouse Brain Atlas (CCFv3 ¹⁰⁷) using the Aligning Big Brains & Atlases plugin ³⁴,¹⁰⁸ in Fiji. Slices were first manually positioned and oriented along the Z-axis. Automated affine registration was then applied in the XY plane, followed by manual refinement. The final registration results were imported into QuPath software ¹⁰⁹ for downstream processing. Cell analysis in each brain subregion was performed with custom Groovy scripts developed for QuPath. Code is freely available online at https://github.com/orion-cirb/QuPath_ORF1P. Hoechst nuclei were detected with StarDist 2D ¹¹⁰, applying the DSB 2018 pretrained model with the following parameters: percentile
normalization = [1-99], probability threshold = 0.82, overlap threshold = 0.25. Cells in NeuN and ORF1p channels were detected with Cellpose 2D (percentile normalization = [1-99], model = 'cyto2', diameter = 30, flow threshold = 0.4, cell probability threshold = 0.0). Nuclei and cells were then filtered by area and intensity to minimize false positive detections. Minimum intensity threshold was based on the channel background noise, which was estimated for each subregion as the mean intensity of pixels not belonging to any detected nucleus or cell in the respective channel. Finally, each cell was associated with a nucleus having its centroid located inside the cell mask. Cells without an assigned nucleus were discarded, cells with associated nuclei were classified as NeuN+ or NeuN- and ORF1p+ or ORF1p-. Intensity values were normalized by subtracting the background noise computed in the corresponding channel and subregion. As a last step, subregional results were merged into regional ones and data were analyzed using the Pandas Python library <sup>111</sup>.

Nuclei and cell detection were evaluated on 14 images per channel, corresponding to approximately 800 nuclei and 400 NeuN and ORF1p cells manually annotated. The average precision (AP) at an IoU threshold of 0.5 was lower than for confocal images: 0.806 for nuclei, 0.675 for NeuN, and 0.695 for ORF1p cells. This decline in performance was primarily due to a lower signal-to-noise ratio in slide scanner images, leading to an increased number of false positives and false negatives. While fine-tuning the models could enhance detection robustness, the selected models and hyperparameters were considered suitable for processing the entire dataset.

## FACS

Mouse brains were dissociated with Adult Brain Dissociation kit (Miltenyi Biotec, 130-107-677) and incubated with the coupled antibody NeuN Alexa 647 (Abcam, ab190565) or the control isotype IgG Alexa 647 (Abcam, ab199093). Stained cells were filtered a last time with
894 a 40µm filter before FACS sorting (FACS ARIA II). Neuronal and non-neuronal cells were
895 separately collected in PBS -/- 2m EDTA and then centrifugate (5min at 700rpm). Pellets
896 were resuspended in RIPA for protein extraction in an appropriate volume in order to achieve
897 equal cell concentrations (10 000 cells/µl).

898

899 RNA-seq analysis

900 The RNA-seq dataset from Dong et al⁵⁴ was downloaded from dbGAP (phs001556.v1.p1) and
901 contains unstranded paired-end 50bp and 75bp reads from pooled laser-capture micro-dissected
902 dopaminergic neurons from human post-mortem brain (107 samples) from 93 individuals w/o
903 brain disease. RNA-seq had been done on total and linearly amplified RNA. We focused our
904 analysis on data obtained with 50bp reads, in order to avoid mappability bias, while still
905 regrouping all age categories (n=41; with ages ranging from 38 to 97 (mean age: 79.88 (SD
906 ±12.07); n=6 ≤65y; n=35 >65y; mean PMI: 7.07 (SD ±7.84), mean RIN: 7.09 (±0.94)).
907 Sequencing reads were aligned on the Human reference genome (hg38) using the STAR mapper
908 (v2.7.0a) 3 and two different sets of parameters. Genome-wide individual repeat quantification
909 was performed using uniquely mapped reads and the following STAR parameters: --outFilter
910 mapNmax 1--alignEndsType EndToEnd--outFilterMismatchNmax 999--
911 outFilterMismatchNoverLmax 0.06. Repeats class, family and name quantification was
912 performed using a random mapping procedure and the following parameters : --
913 outFilterMultimapNmax 5000--outSAMmultNmax 1--alignEndsType EndToEnd--
914 outFilterMismatchNmax 999--outFilterMismatchNoverLmax 0.06--outSAMprimaryFlag
915 OneBestScore--outMultimapperOrder Random.
916 Repeats annotations were downloaded from the UCSC Table Browser (repeatMasker database:
917 https://genome.ucsc.edu/cgi-bin/hgTables) and coordinates of LINE-1 full length and coding
918 elements were downloaded from the L1base database 2 (http://l1base.charite.de/l1base.php; ⁴)
selecting LINE-1 full length elements containing two predicted complete open reading frames for ORF1 and ORF2 (UID= Unique IDentifier) from the LINE-1 database (http://l1base.charite.de/l1base.php) and corrected genomic intervals with the repeat masker annotation of the corresponding genomic locus. Repeat quantification from the aligned data was done using a gtf file composed of all genes (Gencode v29) and all individual repeat elements. This strategy was used to avoid overestimation of repeat elements due to overlaps with expressed genes. For individual repeat quantification of the full length L1 elements (L1base), we therefore used a gtf of all genes and all L1base entries, and ran the FeatureCounts tool ¹¹² with the following parameters: -g gene_id -s 0 -p. In the context of the family-based analysis, we used a gtf with all genes and all annotated repeats elements and ran FeatureCounts with -g gene_family -s 0 -p -M. Before DeSeq2 analysis, we remove all genes and repeat elements with less than 10 reads in a minimum of n individuals, n being the number of individuals in the condition containing the fewest individuals (“young” condition: n=6, 38-65y, mean 57.5 years). We use the same conditions with genes and UIDs with less than 3 reads in a minimum of n individuals. Finally, we calculated the scaling factors using DeSeq2 on all genes + all repeat elements or all gene + UID according to the quantification method and then applied these scaling factors to the corresponding counts tables.

In order to test for the mappability of each UID (= full-length and coding LINE-1), we extracted the bed track « main on human:umap50 (genome hg38) from the UCSC genome browser (≈ 7Mio regions) directly into Galaxy (usegalaxy.org) and joined genomic intervals with a minimum overlap of 45bp of this dataset with a dataset containing the annotation of UIDs extracted from L1Basev2 ⁴ corrected in length with repeat masker and completed with information on whether the UID is intra- or intergenic and, if intragenic, in which gene (NM_ID, chr, strand, start, end, gene length, number of exons, gene symbol) the fl-LINE-1 is located, which resulted in 1266 regions. We then used the “group on data and group by”
function in Galaxy and counted the number of overlapping 50kmers with all 146 UIDs (=mappability score). Correlation analysis (non-parametric Spearman) was then done between the mappability score and the normalized read counts.

For visualization of expression, bigwig files were generated for each age group, that is </=65y and >65y, respectively. We used bamcoverage to obtain bigwig files (normalized by cpm). Then for each age group an average bigwig was generated using bigwigAverage from deeptools (galaxy version 3.5.4); Bigwigs were loaded into IGV alongside tracks showing mappability (Umap50) and selected tracks from repeat masker (LINE, SINE and LTR).

Post-hoc power analysis was performed using the “Post-hoc Power Calculator” (https://clincalc.com/stats/Power.aspx).

## 955 Immpunoprecipitation of ORF1p from the mouse brain

For immunoprecipitation, we used ORF1p (abcam, ab245122) and IgG rabbit (abcam, ab172730) antibodies. The antibodies were coupled to magnetic beads using the Dynabeads® Antibody Coupling Kit (Invitogen, 14311D) according to the manufacture's recommendations. We used 5µg of antibody for 1 mg of beads and used 1.5mg of beads for IP. Individual mouse brain lysates (n=5), homogenized using dounce and sonicated, were incubated with ORF1p or IgG-control coupled beads and a small fraction was kept as input. Each of these two tubes containing coupled beads and brain lysates were diluted in 5 ml buffer (10 mM Tris HCl, 150 mM NaCl, protease inhibitor). The samples were then incubated overnight on a wheel at 4°C. Samples were then washed 3 times with 1 ml buffer (10 mM Tris HCl pH 8, 200 mM NaCl) using a magnet and then resuspended in the same buffer. The samples were boiled in Laemmli buffer (95°C, 10 min) and 20 µl of each sample were loaded on a 4-12% Nupage gel (Invitrogen, NP0336) to be revealed by WB. For samples used in Mass Spectrometry study, beads were washed with buffer (10 mM Tris HCl pH 8, 200 mM NaCl) using a magnet. After 3 washes
969 with 1ml buffer the beads were washed twice with 100 µL of 25 mM NH4HCO3 (ABC buffer).

970 Finally, beads were resuspended in 100 µl of 25mM ABC buffer and digested by adding 0.20
971 µg of trypsine/LysC (Promega) for 1 hour at 37 °C. A second round of digestion was applied
972 simultaneously on the beads by adding 100 µL of 25 mM ABC buffer and to the previous digest
973 by adding 0.20 µg of trypsin/LysC for 1 hour at 37 °C. Samples were then loaded into
974 homemade C18 StageTips packed by stacking three AttractSPE® disk (#SPE-Disks-Bio-C18-
975 100.47.20 Affinisep) into a 200 µL micropipette tip for desalting. Peptides were eluted using a
976 ratio of 40:60 CH3CN:H2O + 0.1% formic acid and vacuum concentrated to dryness with a
977 SpeedVac device. Peptides were reconstituted in 10 µL of injection buffer in 0.3%
978 trifluoroacetic acid (TFA) before liquid chromatography-tandem mass spectrometry (LC-
979 MS/MS) analysis.

980

981 Immunoprecipitation of ORF1p from LUHMES cells (human) differentiated into mature
dopaminergic neurons

982 For immunoprecipitation, we used ORF1p (Millipore, MABC 1152) and IgG mouse
983 (Thermofisher, #31903) antibodies. The antibodies were coupled to magnetic beads using the
984 Dynabeads® Antibody Coupling Kit (Invitogen, 14311D) according to the manufacturer's
985 recommendations. We used 8 µg of antibody for 1 mg of beads. The appropriate volume of
986 buffer was added to the coupled beads to achieve a final concentration of 10 mg/ml. Cells were
987 washed with 1X PBS and harvested using 1 ml of lysis buffer (10 mM Tris HCl pH 8, 150 mM
988 NaCl, NP40 0.5% v/v, protease inhibitor 10 µl/ml). Samples were sonicated for 15 min at 4°C,
989 then centrifuged at 1200 rpm for 15 min at 4°C. The supernatants obtained were transferred to
990 a new microcentrifuge tube and then separated into 3 tubes. One tube was used as the input and
991 the two other tubes were used for the control and ORF1p IP, respectively. Each of these
992 two tubes were then diluted to 1.5 ml with buffer (10 mM Tris HCl pH8, 150 mM NaCl, 10
993
994 µl/ml protease inhibitor) to dilute the NP40. The samples were then incubated overnight on a
995 wheel at 4°C, then washed 3 times (first wash corresponds to post-bead samples) with 1 ml
996 buffer (10 mM Tris HCl pH 8, 150 mM NaCl, 10 µl/ml protease inhibitor) using a magnet and
997 then resuspended in the same buffer. The samples were boiled in Laemmli buffer (95°C, 10
998 min) and 20 µl of each sample were deposited on a 4-12% Nupage gel (Invitrogen, NP0336).

999

1000 Mass Spectrometry

1001 Online chromatography was performed with an RSLCnano system (Ultimate 3000, Thermo
1002 Scientific) coupled to a Q Exactive HF-X with a Nanospay Flex ion source (Thermo Scientific).

1003 Peptides were first trapped on a C18 column (75 µm inner diameter × 2 cm; nanoViper Acclaim
1004 PepMapTM 100, Thermo Scientific) with buffer A (2/98 MeCN/H2O in 0.1% formic acid) at a
1005 flow rate of 2.5 µL/min over 4 min. Separation was then performed on a 50 cm x 75 µm C18
1006 column (nanoViper Acclaim PepMapTM RSLC, 2 µm, 100Å, Thermo Scientific) regulated to a
1007 temperature of 50°C with a linear gradient of 2% to 30% buffer B (100% MeCN in 0.1% formic
1008 acid) at a flow rate of 300 nL/min over 91 min. MS full scans were performed in the ultrahigh-
1009 field Orbitrap mass analyzer in ranges m/z 375–1500 with a resolution of 120 000 at m/z 200.

1010 The top 20 intense ions were subjected to Orbitrap for further fragmentation via high energy
1011 collision dissociation (HCD) activation and a resolution of 15 000 with the intensity threshold
1012 kept at 1.3 x 105. We selected ions with charge state from 2+ to 6+ for screening. Normalized
1013 collision energy (NCE) was set at 27 and the dynamic exclusion of 40s. For identification, the
1014 data were searched against the Mus Musculus (UP000000589_10090 012019) Uniprot database
1015 using Sequest HT through proteome discoverer (version 2.4). Enzyme specificity was set to
1016 trypsin and a maximum of two-missed cleavage sites were allowed. Oxidized methionine, Met-
1017 loss, Met-loss-Acetyl and N-terminal acetylation were set as variable modifications. Maximum
1018 allowed mass deviation was set to 10 ppm for monoisotopic precursor ions and 0.02 Da for
1019 MS/MS peaks. The resulting files were further processed using myProMS <sup>113</sup> v3.10.0. FDR calculation used Percolator and was set to 1% at the peptide level for the whole study. The label 1020 free quantification was performed by peptide Extracted Ion Chromatograms (XICs), reextracted 1021 by conditions and computed with MassChroQ version 2.2.21 <sup>114</sup>. For protein quantification, 1022 XICs from proteotypic peptides shared between compared conditions (TopN matching) with 1023 missed cleavages were used. Median and scale normalization at peptide level was applied on 1024 the total signal to correct the XICs for each biological replicate (n=5). To estimate the 1025 significance of the change in protein abundance, a linear model (adjusted on peptides and 1026 biological replicates) was performed, and p-values were adjusted using the Benjamini-Hochberg FDR procedure. Proteins with at least three peptides, identified in each biological 1028 replicates of ORF1p condition, a 10-fold enrichment and an adjusted p-value ≤ 0.05 were 1029 considered significantly enriched in sample comparisons. Unique proteins were considered with 1030 at least three peptides in all replicates. Protein selected with these criteria were used for Gene 1031 Ontology enrichment analysis and string network analysis. 1032

1033 The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository <sup>115</sup> with the dataset identifier PXD047160. 1034 1035

1036

1037 GO term and STRING network analysis

1038 Gene Ontology analysis was performed using GO PANTHER <sup>116</sup> and String network physical 1039 interactions were retrieved using the STRING database v11.5 (https://string-db.org/) and then 1040 implemented in Cytoscape software <sup>117</sup>. 1041

1041

1042 Statistical analyses
1043 In column comparisons, data in each column were tested for normality using two normality and
1044 lognormality tests (Shapiro-Wilk test and Kolmogorov-Smirnov test). Data which passed the
1045 normality tests were analyzed subsequently by a parametric test, data which did not pass the
1046 normality tests were analyzed by a non-parametric statistical test as indicated in the figure
1047 legends. The significance threshold was defined as p<0.05 except stated otherwise. Statistical
1048 analyses were done with PRISM software (v10).
1049
1050

1051 Acknowledgments

1052 This work was supported by the Fondation de France (00086320, to J.F.), the Fondation du
1053 Collège de France (to J.F. and T.B.), the Fondation NRJ/Institut de France (to J.F.), the
1054 Fondation Alzheimer and the National French Agency for Research (ANR-20-CE16-0022
1055 NEURAGE). We gratefully acknowledge the Orion Technological Core (IMACHEM-IBiSA)
1056 of CIRB for their support, member of the France-BioImaging research infrastructure, especially
1057 Estelle Anceaume and Julien Dumont for assistance with slide scanner and spinning disk
1058 acquisition and Magali Fradet for assistance with FACS analysis. We also thank the Fondation
1059 Bettencourt Schueller for their support.
1060

1061 Contributions

1062 T.B. carried out most of the experimental work and analyzed the data. T.B., S.S. and J.F.
1063 analyzed the transcriptomic data. S.S participated in the experimental work and established and
1064 performed the loss of function experiments. O.M.B. performed the FACS analysis. T.B. and
1065 J.F. wrote the manuscript. T.B., P.M. and H.M. developed the image analysis pipeline. B.L.
1066 carried out the MS experimental work and D.L. supervised MS and performed data analysis
1067 with T.B.. Read alignment, quality control and mapping were done by N.S.. J.F. and R.L.J.

1068 conceived and supervised the project.

1069

## Competing interests

1071 The authors declare no competing interests.

1072

1073

## Figure Legends

1075

## Fig. 1: Widespread and heterogenous expression of ORF1p protein in the mouse brain

1077 (A) Schematic representation of the unbiased cell detection pipeline on large-scale and confocal

1078 images. Immunofluorescent images on sagittal mouse brain slices were acquired on a digital

1079 pathology slide scanner or on a confocal microscope (DNA stain: Hoechst, neuronal marker;

1080 NeuN, protein of interest: ORF1p). Pyramidal images acquired with the slide scanner were then

1081 aligned with the hierarchical anatomical annotation of the Allen Brain Atlas using ABBA. Once

1082 the regions defined, a deep-learning based detection of cell nuclei (Hoechst staining, Stardist)

1083 and cell cytoplasm (NeuN staining, Cellpose) was performed on each sub-region of the atlas.

1084 Objects were filtered according to the background intensity measured in each sub-region for

1085 each channel (NeuN and ORF1p). The identity and intensity measures were analyzed at the

1086 regional and whole brain level. In parallel, confocal images (multiple z-stacks) of two selected

1087 regions (frontal cortex and ventral midbrain) were also acquired and identity and intensity were

1088 quantified using Cellpose.

1089 (B) Widespread and heterogenous expression of the LINE-1 encoded protein ORF1p in the

1090 mouse brain. Representative image of ORF1p immunostaining (orange) of a sagittal section of

1091 the brain of a young (three months-old) mouse acquired on a slide scanner. Scale bar = 1mm.
1092 (1-10) Representative images of confocal images of immunostainings showing ORF1p expression (orange) in 10 different regions of the mouse brain. Nuclei are represented in blue (Hoechst), scale bar = 50µm. (1) Isocortex, (2) Hippocampus, (3) Striatum dorsal, (4) Thalamus, (5) Midbrain motor, (6) Pallidum, (7) Hypothalamus, (8) Substantia nigra pars compacta, (9) Hindbrain, (10) Cerebellum. ORF1p expression profile in the mouse brain. The entire mouse brain with the exception of the olfactory bulb and the cerebellum were analyzed according to the pipeline on large-scale images described in (A).

1099 (C) Bar plot showing the total number of ORF1p+ cells per mm² in the mouse brain. Data is represented as mean ±SEM, n=4 mice (top). Bar plot indicating the proportion of ORF1p+ cells compared to all cells detected. Data is represented as mean ±SEM, n=4 mice (labeled M1 to M4), 202001 total cells analyzed (middle). Scatter plot showing the mean intensity of ORF1p per ORF1p+ cell. Data is represented as mean ±SD, n=4 mice, 40999 ORF1p+ cells analyzed (bottom).

1105 (D-F) ORF1p expression profile (density, proportion and expression) in defined anatomical regions of the mouse brain. Nine anatomical regions as defined by the Allen Brain Atlas and mapped onto sagittal brain slices (four three-month-old Swiss/OF1) with ABBA were analyzed using the pipeline on large-scale images described in (A). (D) ORF1p+ cell density in 9 different regions. Bar plot showing the number of ORF1p+ cells per mm². Data is represented as mean ±SEM; \*p<0.05; \*\*p<0.01; adjusted p-value, one-way ANOVA followed by a Benjamin-Hochberg test (E) Proportion of ORF1p positive cells in 9 different regions. Bar plot showing the proportion of ORF1p+ cells among all cells detected per region. Data is represented as mean ±SEM. (F) Mean ORF1p expression per cell in 9 different regions. Dot plot showing the mean intensity of ORF1p signal per ORF1p+ cell in 9 different regions. Data is represented as mean ±SD. The number of analyzed cells per region is indicated in the figure. \*p<0.05; \*\*p<0.01;
1116 ***p<0.001; ****p<0.0001; adjusted p-value, nested one-way ANOVA followed by Sidak'
1117 multiple comparison test.

1118 (G) ORF1p expression in the mouse frontal cortex and ventral midbrain. Confocal images with
1119 multiple z-stacks. Dot plot representing the mean intensity levels of ORF1p per ORF1p+ cells.

1120 Four three-month-old Swiss/ OF1 mice (labeled as M1 to M4) are represented each by a
1121 different color, the scattered line represents the median. ****p<0.0001, nested one-way
1122 ANOVA. Total cells analyzed = 4645.

1123 (H-I) ORF1p expression in the mouse frontal cortex and the ventral midbrain. (H) Western blots
1124 showing ORF1p (top) and actin expression (bottom) in four individual mice per region which
1125 were quantified in (I) using actin as a reference control. The signal intensity is plotted as the
1126 fold change of ORF1p expression in the ventral midbrain to ORF1p expression in the frontal
cortex. *p<0.05; two-sided, unpaired student's-test.

1128 (J) ORF1p expression in three regions of the human brain. Western blot showing human ORF1p
1129 expression in the cingulate gyrus (CG), frontal cortex (FC) and cerebellum (CB) of post-mortem
1130 tissues from a healthy individual. ORF1p (Top), Actin (bottom). For the full Western blot image
1131 please see Suppl Fig. 2A.

1132

1133 **Fig. 2: ORF1p is predominantly expressed in neurons in the mouse brain**

1134 (A) ORF1p expression is absent in the white matter (corpus callosum) and predominantly
1135 expressed in neurons. Proportion of ORF1p+/NeuN+, ORF1p+/NeuN-, ORF1p-/NeuN+ and
1136 ORF1p-/NeuN- cells in the white matter (corpus callosum) and the grey matter (left) and in
1137 nine different regions (right) analyzed by the cell detection pipeline on large-scale images
1138 presented in Figure1A. Exact values can be found in Suppl_Table1.

1139 (B) Representative confocal microscopy images showing ORF1p (red) and NeuN expression
1140 (green) in two different regions of the mouse brain. The bottom images show the merge of the
1141 two stainings, an overlap of both markers is represented in orange. z-projections; scalebar =
1142 25µm.

1143 (C) Proportion of neurons expressing ORF1p in the frontal cortex and ventral midbrain
1144 quantified on confocal images. ns: non-significant; chi-square test on the cell number of the
1145 different cell-types analyzed; n=4 mice, data is represented as mean ± SEM.

1146 (D) Proportion of ORF1p+ cells identified as NeuN+ or NeuN- in two different regions,
1147 analyzed by confocal microscopy on multiple z-stacks. ns: non-significant; chi-square test, n=4
1148 mice.

1149 (E) ORF1p does not colocalize with glial or microglial cell markers. Representative confocal
1150 microscopy images showing ORF1p staining (red) and three different glial cell (GFAP, Sox9,
1151 S100β) or microglial (Iba1) markers (white). Note that Iba1 antibody (rabbit) was used with
1152 the ORF1p 09 antibody (guinea pig, in house) z-projections, scalebar = 50µm.

1153 (F-G) Separation of neuronal and non-neuronal - cells by FACS confirms predominant
1154 neuronal expression of ORF1p. (F) Neuronal (NeuN+) and non-neuronal (NeuN-) cells isolated
1155 by fluorescent activated cell sorting (FACS). Dot plots showing autofluorescence versus an
1156 appropriate control antibody (IgG rabbit 647; left) and an antibody against NeuN (AB 657,
1157 right). The P4 window represents isolated NeuN+ cells (pink) and the P5 fraction NeuN- cells
1158 (orange) containing the same number of cells as sorted in P4 for comparison, others NeuN- are
1159 represented in blue. (G) Western blot showing ORF1p expression in NeuN- and NeuN+ FACS-
1160 sorted cells stemming from Figure F (A and B representing two different FACS experiments).

1161 (H) Representative confocal microscopy images showing ORF1p (red), NeuN (green) and
1162 Hoechst (blue) in the cingulate gyrus of the human brain. z-projection; scalebar = 25µm (left).
1163 Examples of individuals neurons expressing ORF1p or not are shown on the right panel. z-
1164 projection; scalebar = 5 µm (right).
1165 (I) Proportion of ORF1p+ cells identified as NeuN+ or NeuN- in the human cingulate gyrus,  
1166 analyzed by confocal microscopy on multiple z-stacks.

1167 (J) Proportion of neurons expressing ORF1p in the human cingulate gyrus, analyzed by  
1168 confocal microscopy on multiple z-stacks.

1169

1170 **Fig. 3: ORF1p expression is increased in some regions of the aged mouse brain**

1171 (A) ORF1p mean intensity per ORF1p+ cell in the brain, analyzed on large-scale images. Dot  
1172 plot showing the ORF1p mean expression per ORF1p+ cell in young (Y1-4) and aged (O1-4)  
1173 mice in the whole brain (except cerebellum and olfactory bulb). 74985 total cells were analyzed;  
1174 * p<0.05, nested two-way ANOVA; n=4 mice per condition, data is represented as mean ±  
1175 SEM.

1176 (B) NeuN mean intensity per NeuN+ cell in the brain, analyzed on large-scale images. Dot plot
1177 showing the NeuN mean expression per NeuN+ cell in young (Y1-4) and aged (O1-4) mice in
1178 the whole brain (except cerebellum and olfactory bulb). Nested two-way ANOVA; n=4 mice
1179 per condition, data is represented as mean ± SEM.

1180 (C) Frequency distribution of ORF1p mean intensity in ORF1p+ cells of young (blue) and aged  
1181 (orange) mice. ***p<0.001, Kolmogorov-Smirnov test.

1182 (D) Frequency distribution of Hoechst mean intensity in the nuclei of OrF1p+ cells of young
1183 (blue) and aged (orange) mice. ns: non- significant, Kolmogorov-Smirnov test.

1184 (E) Mean ORF1p expression per ORF1p+ cell in nine different anatomical regions. Dot plot
1185 showing the ORF1p mean expression per ORF1p positive cell (n=74985). Adjusted p-value are
1186 represented, two-tailed nested t-test followed by a Benjamin, Krieger and Yukutieli test; n=4
1187 mice per region, data is represented as mean ± SEM.

1188 (F) Color-coded representation of fold-changes of ORF1p expression comparing young and
1189 aged brains. Represented is the fold-change in percent (aged vs young) of the “mean of the
1190 mean" ORF1p expression per ORF1p+ cell quantified and mapped onto the nine different
1191 regions analyzed as shown in (J).

1192 (G) Representative confocal microscopy images showing increased ORF1p expression (red) in
1193 the ventral midbrain region of aged mice (one z plan is shown). Cell nuclei are shown in blue
1194 (Hoechst staining). Scalebar = 50µm.

1195 (H) ORF1p expression is increased in the ventral midbrain of aged mice. Dot plot representing
1196 ORF1p expression in two different regions of young and aged mice analyzed on confocal
1197 images with multiple z-stacks; total cells analyzed = 8381 ns: non-significant *p<0.05, two-
1198 tailed one-way ANOVA; dashed lines represent the medians.

1199

1200 **Fig. 4: Young LINE-1 elements are increased in aged human dopaminergic neurons**

1201 TE transcript expression in RNA-seq data of laser-captured micro-dissected post-mortem
1202 human dopaminergic neurons of brain-healthy individuals was analyzed using RepeatMasker
1203 (multimappers) or the L1Base (unique reads).

1204 (A) Volcano plot of differential analysis of LINE-1 expression using DESeq2 comparing young
1205 (≤65y, n=6) or aged (>65y, n=35) human dopaminergic neurons at the "name" level of
1206 RepeatMasker. Young LINE-1 elements, including the two families L1HS and L1PA2 that have
1207 coding copies, are highlighted in red.

1208 (B) Scatter plots of normalized read counts ("name" level) of the young L1HS and L1PA2
1209 families as well as the human endogenous virus family HERVK-int, another TE family with
1210 coding potential comparing young (≤65y, n=6) or aged (>65y, n=35) human dopaminergic
1211 neurons. Mann-Whitney test, p<0.05.

1212 (C) Correlation of the RNA expression levels of LINE-1 elements with known transposable
1213 element regulators in human dopaminergic neurons (all ages included). Spearman correlation
1214 of evolutionary close (L1HS, L1PA2-17) and distant LINE-1 (L1PB and L1MA5) as well as
1215 HERV elements with coding potential (HERV-Kint, HERV-Fc1, HERV-Fc2 and HERV-H-int)  
1216 with known regulators of transposable elements for each individual sample, all ages included.  
1217 HERV-W and TREX1 did not pass the normalized read count threshold of >3 reads in >6  
1218 individuals.

1219

1220 **Fig. 5: Dysregulation of locus-specific full-length LINE-1 elements in aged human**
1221 **dopaminergic neurons**

1222 (A) Volcano plot of differential expression analysis of TE expression using DEseq2 comparing
1223 young (≤65y, n=6) and aged (>65y, n=35) human dopaminergic neurons at the locus-level of
1224 specific full-length LINE-1 elements (140 of 146 “UID’s” as annotated in L1Base; threshold
1225 >3 reads in at least 6 individuals).

1226 (B) Pairwise comparison of the expression of 140 out of 146 full-length LINE-1 elements
1227 comparing young (≤65y, n=6) and aged (>65y, n=35) human dopaminergic neurons. Wilcoxon
1228 matched signed rank test, p<0.0001(left panel).

1229 (C) The sum of read counts of all UIDs per individual were plotted comparing young (≤65y,  
1230 n=6) and aged (>65y, n=35) human dopaminergic neurons.

1231 (D) UID-68 is dysregulated in aged human dopaminergic neurons. Normalized read counts of
1232 uniquely mapping reads mapping to the full-length LINE-1 element “UID-68” per individual
1233 were plotted comparing human post-mortem dopaminergic neurons from young (≤65y, n=6)
1234 and aged (>65y, n=35) individuals; two-tailed Mann-Whitney test (* p=0.046).

1235 (E) IGV window of the locus around the full-length LINE-1 UID-68 (chr7:141.918.055-  
1236 141.932.948). UID-68 is located adjacent to the genes CLEC5A (right) and OR9A4 (left).  
1237 Coverage and mappability of the locus including UID-68 is shown in tracks. Coverage is  
1238 represented by average bigwig profiles (same scale, black: <=/65y, red >65y); mappability of
1239 the genomic locus is depicted by Umap 50 tracks showing peaks overlapping with the peaks of
1240 reads (bigwig averages).

1241 (F) Spearman correlation analysis of the expression of UID-68 and OR9A4 in young (≤65y,
1242 n=6, black dots; Spearman r= 0.66, p=0.17)) or aged (>65y, n=35, red squares, Spearman r=
1243 0.15, p=0.40) human dopaminergic neurons.

1244 (G) Spearman correlation analysis of the expression of UID-68 and CLEC5A in young (≤65y,
1245 n=6, black dots, Spearman r= 0.75, p=0.11) or aged (>65y, n=35, red squares; Spearman r= -
1246 0.03, p=0.87) human dopaminergic neurons.

1247

1248 **Fig. 6: Endogenous ORF1p interactors in the mouse brain**

1249 Immunoprecipitation (IP) of endogenous ORF1p from the mouse brain. WB against ORF1p
1250 showing ORF1p enrichment after IP but no signal in the IgG control. Five independent samples
1251 were then prepared for proteomic analysis by mass spectrometry (LC-MS/MS).

1252 (B) GO slim enrichment analysis of proteins selected as endogenous ORF1p protein partners in
1253 the mouse brain after quantitative LC-MS/MS. ORF1p-immunoprecipitated proteins were
1254 categorized into GO slim terms. The nine GO slim term with the highest fold-change are
1255 plotted. Fold enrichment is depicted on the upper axis and displayed as bars, the FDR value
1256 appears on the lower axis and is represented by the black points. BP: Biological Process, CC:

1257 Cellular Component, MF: Molecular Function.

1258 (C) Venn diagram showing common interactors (purple) between interactors of endogenous
1259 ORF1p in the mouse brain identified in this study (red) and known (published) interactors of
1260 ORF1p (blue). Statistical significance of the overlap between the two groups of proteins was
1261 tested by an overrepresentation test (http://nemates.org/MA/progs/overlap_stats.html).

1262 (D) ORF1p associates with the SWI/SNF complex (red), RNA pol II complex (orange) and
1263 interactors belonging to GO terms related to neuronal cell body & neuron projection (green).
1264 Known interactors previously published 35,67,72-76 are indicated with a purple ring. STRING
1265 network of physical interactions where nodes represent proteins partners identified in (A) and
1266 edges thickness represents the strength of shared physical complexes. Only proteins sharing
1267 physical interactions were represented.

1268

1269

1270 **Supplementary Figures**

1271

1272 Suppl Fig. 1

1273 (A) Specific antigen recognition by the ORF1p antibody. IHC showing ORF1p positives cells
1274 in sagittal mouse brain slice (left) and abolition of the signal when blocking the antibody with
1275 purified ORF1p (right).

1276 (B) Representative acquisition showing ORF1p stainings obtained with a commercially
1277 available ORF1p antibody (abcam ab216324) used in this study (red) and with an in-house
1278 ORF1p gp antibody (guinea pig, green) in the mouse brain. Scalebar = 20µm (top) and 100µm
1279 (bottom).

1280 (C) Quantification of double positive cells (gp+/ab+) using the commercial ORF1p ab
1281 antibody (abcam ab216324) and in-house ORF1p gp antibody (guinea pig) versus single-
1282 positive cells (gp+/ab- and gp-/ab+) in mouse frontal cortex (left) and ventral midbrain (right).

1283 (D) Validation of the ORF1p antibody (abcam ab216324) by knock-down of ORF1p in mouse
1284 dopaminergic neurons in cluture. MN9D cells differentiated into mature mouse dopaminergic
1285 neurons were transfected with either control siRNA or ORF1p siRNA and ORF1p was revealed
1286 by Western blot. Actin was used as a loading control.

1287 (E) ORF1p is expressed in six different brain regions in the mouse.
1288 Brain regions were micro-dissected from a three-month old mouse brain. Western blot showing

1289 ORF1p expression in 6 brain regions. ORF1p (Top), Actin (bottom).

1290

1291

1292 Suppl Fig. 2

1293 (A) ORF1p is expressed in the human post-mortem brain.

1294 Complete membrane of the ORF1p Western blot on human post-mortem cingulate gyrus (CG),

1295 frontal cortex (FC) and cerebellum (CB) shown in Fig. 1J.

1296 (B) Immunoprecipitation of ORF1p from LUHMES cells which were differentiated into mature

1297 human dopaminergic neurons. First lane: Input; second lane: Control IP; third lane: ORF1p IP;

1298 forth lane: post-beads from control IP; fifth lane: post-beads from ORF1p IP.

1299 (C) Validation of the human ORF1p antibody by knock-down.

1300 LUHMES cells differentiated into mature human dopaminergic neurons were transfected with

1301 either control siRNA or ORF1p siRNA and ORF1p was revealed by Western blot using the

1302 ORF1p abcam ab245249. Actin was used as a loading control.

1303 (D) Representative slide-scanner acquisition of a human cingulate gyrus section showing NeuN

1304 positives cells (green) mostly located in the grey matter (right) compared to the white matter

1305 from a brain-healthy individual; scale bar = 400µm. A zoom into the grey matter region

1306 showing ORF1p stainings is shown in Figure 2H.

1307 (E) Control experiment using a 2nd antibody-only control on human cingulate gyrus and frontal

1308 cortex alongside ORF1p stainings. Representative confocal microscopy images showing

1309 ORF1p or only secondary antibody. z-projection; scalebar = 25µm.

1310

1311 Suppl Fig. 3
1312 (A) Proportion of neurons (NeuN+) expressing ORF1p in the whole brain (left, red) and in different regions of the mouse brain (black bars) or not (grey) as quantified using the cell detection pipeline on large-scale images.

1313
1314
1315 (B) ORF1p cell identity. Proportion of ORF1p+ cells identified as NeuN+ (black) or NeuN-(grey), in the whole brain (left, red)) and in 9 different regions analyzed (right) using the cell detection pipeline on large-scale images presented in Figure 1A; data is represented as mean ± SEM, n=4 mice.

1316
1317
1318
1319 (C) Proportion of neurons in the frontal cortex and ventral midbrain quantified using the confocal approach. \*p\<0.05, chi-square test on the cell number of the different cell-types analyzed; n=4 mice, data is represented as mean ± SEM.

1320
1321
1322
1323 Suppl Fig. 4
1324
1325 Representative confocal microscopy images showing ORF1p (red), PV (green), WFA (grey), Hoechst (blue) and merged images in six regions of the mouse brain, scalebar = 50µm.

1326
1327
1328 (A) Proportion of ORF1p+/NeuN+, ORF1p+/NeuN+, ORF1p+/NeuN-, ORF1p-/NeuN+ and ORF1p-/NeuN-cell-type in the whole brain (left) and the different analyzed regions (right) of young (three-month aged, n=4) and aged (16-month-old, n=4) mice using the cell detection pipeline on large scale images presented in Figure 1A, data is represented as mean ± SEM. Exact values can be found in Suppl Table1.

1330
1331
1332
1333 (B) Proportion of ORF1p+/NeuN+, ORF1p+/NeuN+, ORF1p+/NeuN-, ORF1p-/NeuN+ and ORF1p-/NeuN-cell-type in two different regions of young and aged mice, analyzed on multiple z-stack confocal images. ns: non-significant; \*p\<0.05 calculated using two-way ANOVA with

1334
1335
sidak's multiple comparisons test on the cell number of the different cell-types analyzed; data
is represented as mean ± SEM.

(C) Proportion of ORF1p+ cells being neuronal in the ventral midbrain comparing young and
aged mice as quantified using the confocal approach. Kolmogorov-Smirnov test; data is
represented as mean ± SEM.

(D) Proportion of neurons expressing ORF1p in the ventral midbrain comparing young and
aged mice as quantified using the confocal approach. Kolmogorov-Smirnov test; data is
represented as mean ± SEM.

(E) Proportion of neurons in the ventral midbrain comparing young and aged mice as quantified
using the confocal approach. Kolmogorov-Smirnov test; data is represented as mean ± SEM.

(F) ORF1p+ cell density in the brain comparing young and aged mice, analyzed on large-scale
images. ORF1p+ cell number per mm2 in young and aged mice (n=4 per condition); Shapiro
Wilk normality test followed by an unpaired, two-tailed t-test.

(G) Neuronal cell density in the brain comparing young and aged mice, analyzed on large-scale
images. NeuN+ cells per mm2 in young and aged mice (n=4 per condition); Shapiro Wilk
normality test followed by an unpaired, two-tailed t-test.

(H) Non-neuronal cell density in the brain comparing young and aged mice, analyzed on large-scale images. NeuN- cells per mm2 in young and aged mice (n=4 per condition); Shapiro Wilk normality test followed by an unpaired, two-tailed t-test.

(I) ORF1p+ cell density in young and aged mice in nine brain regions, analyzed on large-scale
images. Data is represented as mean ± SEM, n=4 mice per condition. Two-way ANOVA
followed by a Sidak's multiple comparisons test, alpha = 0.05. Adjusted p-values <0.05 are
shown.

(J) NeuN+ cell density in young and aged mice in nine brain regions, analyzed on large-scale
images. Data is represented as mean ± SEM, n=4 mice per condition. Two-way ANOVA
1361 followed by a Sidak's multiple comparisons test, alpha = 0.05. Adjusted p-values <0.05 are
1362 shown.

1363 (K) Non-neuronal cell density in young and aged mice in nine brain regions, analyzed on large-scale images. Data is represented as mean ± SEM, n=4 mice per condition. Two-way ANOVA
1364 followed by a Sidak's multiple comparisons test, alpha = 0.05. Adjusted p-values <0.05 are
1365 shown.
1366

1367

1368 Suppl Fig. 6

1369 (A-B) Scatter plots comparing of the expression of dopaminergic markers tyrosine hydroxylase
1370 (TH, A) and LMX1B (B) between young (≤65y, n=6)) and aged (>65y, n=35) human
1371 dopaminergic neurons; Mann Whitney test.

1372 (C, E) Volcano plot of differential expression analysis of TE expression using DEseq2
1373 comparing young (≤65y, n=6) and aged (>65y, n=35) human dopaminergic neurons at the
1374 "class" (C) and "family" (E) level of RepeatMasker.

1375 (D) Scatter plot comparing the expression of LINE at the "class" level between young (≤65y, n=6)) and aged (>65y, n=35) human dopaminergic neurons; Mann Whitney test.
1376

1377 (F) Scatter plot comparing the expression of LINE and Alu at the "family" level between young (≤65y, n=6)) and aged (>65y, n=35) human dopaminergic neurons; Mann Whitney test.
1378

1379 (G) Scatter plot comparing the expression of HERVH-int, HERV-Fc1 and two non-coding, non-autonomous but active TEs in the human genome, AluYa5 and SVA-F at the "name" level
1380 between young (≤65y, n=6)) and aged (>65y, n=35) human dopaminergic neurons; Mann Whitney test.
1381

1382

1383

1385 Suppl Fig. 7
1386 (A-C) Correlation analyses of L1HS expression with Engrailed 1 (EN1, A, Spearman r=-0.43, p=0.002), CBX5/HP1 (B, Spearman r=-0.35, p=0.01) and XRCC6 expression (C, Spearman r=-0.394, p=0.005). Normalized read counts are plotted. Black dots correspond to young individuals (≤65y), red dots correspond to aged individuals (>65y).

1390 (D-G) Scatter plots comparing the expression of EN1, CBX5/HP1, XRCC5 and XRCC6 between young (≤65y, n=6)) and aged (>65y, n=35) human dopaminergic neurons. Student's t-test (EN1) or Mann Whitney test (HP1, XRCC5/6).

1393

1394 Suppl Fig. 8

1395 (A) *In silico* analysis of annotated full-length LINE-1 elements as in L1Basev2 (human reference genome hg38). Percentage of L1HS and L1PA2 elements among the 146 full-length elements (UID1-146).

1398 (B) Mean expression of all 146 full-length LINE-1 elements in dopaminergic neurons of all individuals ≤65y.

1400 (C) Correlation of mappability (UMAP hit counts over UID, see methods) and UID expression (normalized read counts). Spearman correlation.

1402 (D) *In silico* analysis of annotated full-length LINE-1 elements as in L1Basev2 (human reference genome hg38). Percentage of full-length LINE-1 elements located inside or outside a gene.

1405 (E) *In silico* analysis of annotated full-length LINE-1 elements as in L1Basev2 (human reference genome hg38). Presence (blue, with gene symbol) or absence (white) of a "hosting" gene among the 146 annotated full-length LINE-1 in the human reference genome.

1408

1409

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1683
<figure><img src="image_2.png" /><figcaption>Fig. 1</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>Fig. 2</figcaption></figure>
<caption>Fig. 3</caption>

bioRxiv preprint doi: https://doi.org/10.1101/2023.12.12.571308; this version posted July 24, 2025. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

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<figure><img src="image_12.png" /><figcaption>Fig. 4</figcaption></figure>
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<figure><img src="image_14.png" /><figcaption>Fig. 6</figcaption></figure>
<caption>Suppl Fig. 1</caption>

<figure><img src="image_15.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>C</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>D</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>E</figcaption></figure>

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<caption>**Suppl Fig. 2** (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.</caption>

<figure><img src="image_20.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_21.png" /><figcaption>C</figcaption></figure>

<figure><img src="image_22.png" /><figcaption>D</figcaption></figure>

<figure><img src="image_23.png" /><figcaption>E</figcaption></figure>

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<figure><img src="image_29.png" /><figcaption>Suppl Fig. 6</figcaption></figure>
Suppl Fig. 7

A

EN1 vs L1HS

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CBX5/ HP1 vs L1HS

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C

XRCC6 vs L1HS

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D

EN1

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E

HP1

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F

XRCC5

<figure><img src="image_35.png" /></figure>

G

XRCC6

<figure><img src="image_36.png" /></figure>
bioRxiv preprint doi: https://doi.org/10.1101/2023.12.12.571308; this version posted July 24, 2025. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Suppl Fig. 8

A

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B

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C

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