A hallmark of neurodegenerative diseases is brain-region-specific cell death and dysfunction. Why specific brain regions are affected and others remain unscathed is a key question in the field. In order to answer this question, the innate differences and similarities in affected tissues must first be established. Studies in a diverse subset of neurodegenerative disorders have begun using large-scale transcriptomics and proteomics to assess brain region-dependent molecular alterations. For example, a large RNA-sequencing (RNA-seq) study conducted across brain regions and peripheral tissues in Huntington’s disease (HD) mouse models identified gene clusters related to transcription, chromatin factors, and mitochondria that appear to be specific to the striatum (Langfelder et al., 2016). The same study also found glia-related genes that were significantly enriched in the striatum and cortex, as well as other tissues thought to be less affected in HD, such as the cerebellum and brainstem (Langfelder et al., 2016). In Alzheimer’s Disease (AD), regional variability in transcriptional changes were observed early in disease progression, but the similarities between tissues increased as animals aged (Landel et al., 2014). Finally, a recent study in spinocerebellar ataxia type 3 (SCA3) identified brain region-dependent variability in gene expression changes prior to the onset of motor phenotypes despite modest transcriptional alterations in brain regions that remain largely unscathed (Toonen et al., 2018). Collectively, this suggests that a subset of gene clusters spans affected tissues regardless of the degree of tissue vulnerability, while other genes may be enriched in discrete affected tissues. Disease progression may also play a role in dictating the degree of overlap between two affected tissues, with a higher degree of variability between tissues early on in disease.

Mouse models for neurodegenerative disorders can be utilized to query the underlying differences and similarities in affected tissues, including the models generated for spinocerebellar ataxia type 1 (SCA1). SCA1 is a fatal late-onset neurodegenerative disorder that is characterized by impaired motor coordination and balance (Globas et al., 2008). Atrophy and loss of Purkinje cells (PCs) in the cerebellum and cell death in the inferior olive have been identified in postmortem human tissue (Koeppen, 2005; Koeppen et al., 2013). Many of these behavioral and pathological traits have been faithfully recaptured in both a transgenic, and a knockin, mouse model for SCA1 (Burright et al., 1995; Clark et al., 1997; Watase et al., 2002). Both SCA1 models demonstrate motor incoordination and PC pathology, and develop hallmark nuclear inclusions in PCs (Burright et al., 1995; Clark et al., 1997; Watase et al., 2002).

SCA1 is caused by a polyglutamine (polyQ) expansion in the ATAXIN-1 (ATXN1) protein, which is involved in gene regulation, including transcription (Orr et al., 1993). Transcriptional regulators, including Capicua, SMRT, and RORa/Tip-60, have been shown to interact with ATXN1 (Fryer et al., 2011; Gehrking et al., 2011; Kim et al., 2013b; Lam et al., 2006; Lim et al., 2008; Serra et al., 2006; Tsai et al., 2004). Since ATXN1 functions as a transcriptional regulator, several previous studies have investigated how polyQ-expanded ATXN1 can impact the normal transcriptional signature of the cerebellum (Crespo-Barreto et al., 2010; Cvetanovic et al., 2011; Gatchel et al., 2008; Ingram et al., 2016; Lin et al., 2000; Serra et al., 2004). These studies have identified that various biological pathways, including glutamate signaling, calcium signaling, and long-term depression, are enriched in this tissue at different time-points (Crespo-Barreto et al., 2010; Gatchel et al., 2008; Ingram et al., 2016; Serra et al., 2004). Despite the prevalence of transcriptomic data collected from the SCA1 cerebellum, other affected regions, such as the inferior olive, have remained largely unstudied.

The cerebellum and inferior olive are intricately connected. Neurons of the inferior olive, a collection of subnuclei in the rostral medulla, send climbing fibers to innervate PCs (Bengtsson and Hesslow, 2006). PC axons, in turn, synapse onto deep cerebellar nuclei, which send efferent fibers to various brain regions including the inferior olive. Previous studies have found inferior olive cell loss in postmortem SCA1 human tissue, as well as changes in climbing fiber synaptic density on PCs (Koeppen et al., 2013; Kuo et al., 2017). This coincides with data from the transgenic mouse model expressing polyQ-expanded human ATXN1 (ATXN1-82Q) in PCs under the control of the Pcp2 promoter (Burright et al., 1995). These mice exhibit aberrant climbing fiber pruning on PC soma and dendrites, a reduction in the responsiveness of PCs to climbing fibers, and alterations in climbing fiber arborization and extension (Barnes et al., 2011; Duvick et al., 2010; Ebner et al., 2013). Previous work has indicated that localization of ATXN1-82Q to the PC nucleus is associated with alterations in climbing fiber-PC synapses (Ebner et al., 2013). However, this does not exclude the possibility that affected inferior olive neurons may also influence the degree of climbing fiber synapses on PCs. Other neurodegenerative disorders, including SCA7, 14, and 23, as well as Essential Tremor, have aberrant climbing fiber innervation on PC soma and dendrites, indicating that this observation is not isolated to SCA1 (Smeets and Verbeek, 2016). Though the inferior olive is affected in SCA1, the precise role of the inferior olive in the manifestation of SCA1 clinical phenotypes is unclear (Barnes et al., 2011; Duvick et al., 2010; Ebner et al., 2013; Koeppen et al., 2013; Kuo et al., 2017). Furthermore, the molecular basis of inferior olive alterations in SCA1 is unknown.

The purpose of the present study was to investigate molecular and pathological signatures of the inferior olive in SCA1 mouse models, and further identify similarities and differences in the gene expression profile between the inferior olive and cerebellum, two highly affected tissues in SCA1. We used two SCA1 mouse models, knockin and PC-specific transgenic, which express polyQ-expanded ATXN1 in different cell types and tissues, but faithfully recapture many aspects of the behavioral and pathological phenotypes associated with SCA1 (Burright et al., 1995; Watase et al., 2002). Comparison of transcriptomics data from these two mouse models allowed for the dissection of how polyQ-expanded ATXN1 influences gene expression changes when it is preferentially expressed in specific cell-types and tissues. We found that differentially regulated genes in the inferior olive segregated into several unique biological pathways. Particularly, the defense response appears largely unique to the SCA1 inferior olive across SCA1 mouse models. We also found that there are common, and distinct, enriched biological pathways between the SCA1 cerebellum and inferior olive.

Neurodegeneration can affect multiple brain regions, however, many neurodegenerative studies have focused their research extensively on one classically defined affected tissue. Due to the increasing evidence that there are underlying differences in tissue-specific cell populations and responses to external stimuli, it is necessary to begin examining all affected and sparred tissues in neurodegenerative conditions to determine their underlying similarities and differences, which remain unknown. Identifying commonalities between tissues will provide insight into potential therapeutic targets, while elucidating discrepancies between tissues will provide a more thorough understanding of how disease uniquely affects each tissue. Further, previous work has highlighted that different mouse models created to study specific neurodegenerative diseases have somewhat different molecular alterations, sometimes making it difficult to discern a common mechanism driving pathological and clinical phenotypes (Hargis and Blalock, 2017). We addressed these questions for the first time in a SCA1 context by 1) identifying underlying molecular alterations that occur in the inferior olive, 2) assessing how these molecular alterations change during early SCA1 disease progression, 3) highlighting prevalent similar and unique biological pathways in two affected SCA1 tissues, and 4) conducting a cross-model comparison between two SCA1 mouse modes (Figure 8).

Figure 8

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Response to organic substance and hormone-related pathways were significantly enriched in both the Atxn1^154Q/2Q KI and ATXN1-82Q Tg inferior olive at 5 weeks of age, which coincides with the earliest reported onset of behavioral phenotypes (Figure 2—figure supplement 1; Figure 5—figure supplement 1; Figure 8). A subset of the Atxn1^154Q/2Q KI response to organic substance pathway contained ISGs, which are known to contribute to immune-related processes (Figure 2—figure supplement 1D). A small subset of immune-related genes were also identified in the 5 week ATXN1-82Q Tg inferior olive (Figure 5—figure supplement 1D). This suggests that some, but not a significant amount, of Defense Response-related genes are significantly different in the Atxn1^154Q/2Q KI and ATXN1-82Q Tg inferior olive at 5 weeks of age. However, by 12 weeks of age, both the Atxn1^154Q/2Q KI and ATXN1-82Q Tg inferior olive differentially regulated gene lists are made up of a substantial portion of defense response, or immune-related, genes (Figures 2D, 5E and 8; Figure 5—figure supplement 2C). The biological and pathological significance of the defense response in the SCA1 inferior olive will require further examination to determine whether this is a component of a pathological pathway or protective response. One interesting finding in this study is that although the defense response was a top significantly enriched pathway in the inferior olive of two distinct SCA1 models, the genes differentially regulated in these models do not strongly overlap (Figure 5F and G). For example, ISGs such as the retinoic acid-inducible genes (RIG-1) like receptors Ddx58 (RIG-1) and Ifih1 (MDA5) are significantly up-regulated in the Atxn1^154Q/2Q KI inferior olive, but do not change in the ATXN1-82Q Tg inferior olive. Due to the fundamental difference in the expression of polyQ-expanded mutant ATXN1 protein in the inferior olive between the two different SCA1 models (Figures 2A, 5A and B), the molecular and cellular mechanisms leading to the increased defense response will be different.

Enrichment for defense response-related genes in the 12 week old ATXN1-82Q Tg inferior olive is particularly striking given that ATXN1-82Q is not detectable at the mRNA and protein level in this tissue compared to the cerebellum (Figure 5A and B). Further, polyQ-expanded ATXN1 would only be expressed in neurons if it is expressed below detectable levels since the expression of ATXN1-82Q is driven by the Pcp2 promoter (Burright et al., 1995). Therefore, the large number of defense response-related genes, especially those expressed at higher levels in glia cells, suggest that some non-cell autonomous effects on transcription are occurring in ATXN1-82Q Tg inferior olive. Interestingly, potential upstream regulators identified with IPA did not indicate that Irf7 was a significant regulatory factor in the ATXN1-82Q Tg mice (Supplementary File 5). This further enhances our prediction that polyQ-expanded mutant Atxn1 may directly influence the Irf7 activity in a cell-autonomous manner in glia cells in the Atxn1^154Q/2Q KI inferior olive (Figure 2I). While alterations in glia-expressed genes appear to be a major component of the inferior olive transcriptome, we cannot rule out the possibility that some of these gene expression alterations are occurring in other cell-types in the inferior olive. One alternative explanation for the gene expression changes in the ATXN1-82Q Tg inferior olive is dysfunction and pathology of cerebellar PCs having a retrograde effect on the inferior olive.

Our results suggest that gene expression changes are dynamic between 5 and 12 weeks of age in the inferior olive of both mouse models (Figure 8). Comparison of the differentially regulated gene lists over time found a large proportion of genes altered at both time-points with dysregulated expression (Figure 2—figure supplement 4B and C; Figure 5—figure supplement 3B and C). These genes were typically up-regulated at 5 weeks of age, but were down-regulated at 12 weeks of age, and this was consistent across both SCA1 mouse models (Figure 2—figure supplement 4B and C; Figure 5—figure supplement 3B and C; Figure 8). This is in comparison to the cerebellar time-point comparison, which found that the majority of overlapping genes remained consistently either down-regulated or up-regulated over time (Figure 3—figure supplements 2B, C, 4B and C; Figure 6—figure supplement 3B and C; Figure 8). Whether this switch in gene expression regulation is tied to disease onset and progression, pathological cerebellar input, or other mechanisms is unknown.

One caveat of the present study is the few number of differentially regulated genes identified in the 5 week old Atxn1^154Q/2Q KI cerebellum (Figure 3—figure supplement 1B). Previous reports from a 4 week and 7 week time-point microarray study identified more genes significantly altered in this brain region (Crespo-Barreto et al., 2010; Gatchel et al., 2008). After extending our p-value to include nominally significant genes p < 0.01, we found significant overlap between our dataset with the previously published datasets (Figure 3—figure supplement 3A). This suggests that animal variability, differences in animal housing, and potentially our stringent FDR p-value < 0.05 cut-off ultimately led to a small number of genes differentially regulated at 5 weeks of age. Despite this, our current findings in the Atxn1^154Q/2Q KI and ATXN1-82Q Tg cerebellum are consistent with previously published reports (Gatchel et al., 2008; Ingram et al., 2016). In the Ingram et al. study (Ingram et al., 2016) investigating cerebellar molecular alterations in ATXN1-82Q Tg mice that correlate with disease progression, the 10 hub genes that correlate with disease progression in PCs were also significantly down-regulated in our 5 and 12 week datasets (Figure 3D; GEO accession 122099). In addition, Cck and Col18a1 were down-regulated in our 5 and 12 week datasets (Figures 4E and 7D; Figure 2—figure supplement 4E), which match the previous report (Ingram et al., 2016).

There was a marked difference in the biological functions associated with the differentially expressed genes in both the 12 week old Atxn1^154Q/2Q KI and ATXN1-82Q Tg inferior olive and cerebellum comparisons (Figures 4B, 6D and 8). The defense response was consistently enriched in the inferior olive relative to the cerebellum across SCA1 mouse models (Figures 4B, 6D and 8). The lack of significantly enriched defense response-related pathways in the Atxn1^154Q/2Q KI and ATXN1-82Q Tg cerebellum is particularly striking given that a previous study found increased gliosis in the cerebellum around this time-point (Cvetanovic et al., 2015). Further, our transcriptomics data found a significant decrease in Gfap expression in the Atxn1^154Q/2Q KI cerebellum (Figure 7D), which is consistent with a recently published report (Edamakanti et al., 2018). This may indicate that protein levels and mRNA expression do not coincide in some instances. It is also possible that defense response-related genes are enriched among activated glia in the SCA1 cerebellum, however, those differentially regulated genes may be lost due to sequencing in bulk cerebellar lysates. There is significant up-regulation for some components of the defense response, including ISGs in the Atxn1^154Q/2Q KI cerebellum (Figure 4D), and compliment cascade factors in the ATXN1-82Q Tg cerebellum (Figure 6C), however, the relatively small number of genes associated with the defense response that are differentially regulated within the cerebella suggests that it is not a major feature of the SCA1 cerebellar transcriptome.

Enrichment for Cic binding sites within the Atxn1^154Q/2Q KI and ATXN1-82Q Tg cerebellum down-regulated genes (Tables 2 and 3) is consistent with a previous report (Fryer et al., 2011), indicating that the presence of polyQ-expanded ATXN1 acts synergistically with Cic to further repress transcriptional activity. While there was a degree of enrichment for Cic binding sites among the up-regulated Atxn1^154Q/2Q KI and down-regulated ATXN1-82Q Tg inferior olive genes, it was not the most significantly over-represented potential transcriptional regulator at the 12 week time-point (Tables 1–3; Figure 2—source data 3; Supplementary File 5). While we cannot rule out the role of Cic-Atxn1 interactions on regulating molecular alterations in the inferior olive, other transcriptional regulators, such as Irf7 and Esr1, may be regulating a proportion of the differentially regulated genes in the inferior olive in the Atxn1^154Q/2Q KI and ATXN1-82Q Tg mouse models.

The two SCA1 mouse cerebellar datasets had significant enrichment for similar biological functions, which initially suggested to us that similar genes may be altered in these two mouse models despite the mouse model differences in polyQ-expansion, cell-type expression, expression level of polyQ-expanded ATXN1, human vs. mouse protein, or genetic backgrounds (Burright et al., 1995; Watase et al., 2002). While a proportion of genes did overlap between these two mouse models, we observed a difference in the directionality of gene expression changes across the models (Figure 7B and C). A similar observation can be found in SCA2 transgenic and KI mouse models (Halbach et al., 2017; Pflieger et al., 2017). The majority of the commonly dysregulated genes were up-regulated in the ATXN1-82Q Tg mouse cerebellum and down-regulated in the Atxn1^154Q/2Q KI cerebellum (Figure 7C), and contained genes associated with nervous system development (Figure 7D). The disparity in significant gene expression directionality in these two models may be due to the cell-type-specific expression of polyQ-expanded ATXN1. The PC-specific expression of ATXN1-82Q, and its effect on PC function, may lead to up-regulation of a subset of non-neuronal genes. However, cell-type appropriate expression of polyQ-expanded Atxn1 in Atxn1^154Q/2Q KI cerebellum may lead to alterations in similar genes via cell-type specific intrinsic mechanisms. Despite the discrepancy in the directionality of the differentially expressed genes, previous studies show that the two mouse models exhibit similar behavioral and pathological phenotypes. Both models manifest motor coordination deficits at approximately 5 weeks of age (Clark et al., 1997; Watase et al., 2002). Molecular layer thinning is obvious at 12 weeks in the ATXN1-82Q Tg mouse model, but occurs at a later time-point in the Atxn1^154Q/2Q KI mouse (Barnes et al., 2011; Clark et al., 1997; Duvick et al., 2010; Watase et al., 2002).

Variability in gene expression in the brain across multiple inbred mouse strains has previously been demonstrated (Nadler et al., 2006). The two SCA1 mouse models analyzed in the present study were maintained on different mouse genetic backgrounds. The Atxn1^154Q/2Q KI mice are maintained on a C57BL/6J background, while the ATXN1-82Q Tg are kept on a pure FVB/NJ background. Therefore, the genetic interaction between polyQ-expanded ATXN1 and the mouse genetic background should be considered. In addition, the two SCA1 mouse models utilize either the mouse or human homologue of polyQ-expanded ATXN1. The amino acid sequence similarity between the mouse and human ATXN1 is 89% when excluding the polyQ-tract. While this indicates a high degree of sequence similarity, how the sequence differences influence subsequent gene expression changes is unknown.

In summary, our work shows for the first time that there are specific biological pathways enriched in a less studied SCA1 affected tissue, the inferior olive. Further, there are intrinsic molecular differences between two affected tissues in SCA1, and biological pathways that are largely brain-region-specific are conserved across SCA1 mouse models, regardless of the expression of polyQ-expanded ATXN1. The commonalities between affected tissues indicate that a subset of molecular changes may be useful as disease biomarkers in SCA1.

RNA sequencing data have been deposited in GEO under accession (number: 122099).

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Author details

1. Terri M Driessen

   Department of Genetics, Yale School of Medicine, New Haven, Unites States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Methodology, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9116-5497

2. Paul J Lee

   Department of Genetics, Yale School of Medicine, New Haven, Unites States

   Contribution

   Formal analysis, Validation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4009-8220

3. Janghoo Lim

   1. Department of Genetics, Yale School of Medicine, New Haven, Unites States
   2. Department of Neuroscience, Yale School of Medicine, New Haven, Unites States
   3. Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale School of Medicine, New Haven, Unites States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing—review and editing

   For correspondence

   janghoo.lim@yale.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5331-210X

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