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. Author manuscript; available in PMC: 2025 Oct 15.
Published in final edited form as: Neurobiol Dis. 2024 Sep 20;201:106673. doi: 10.1016/j.nbd.2024.106673

Expanded ATXN1 alters transcription and calcium signaling in SCA1 human motor neurons differentiated from induced pluripotent stem cells

Carrie Sheeler 1,2, Emmanuel Labrada 1, Lisa Duvick 4, Leslie M Thompson 3, Ying Zhang 1, Harry T Orr 4,5,6, Marija Cvetanovic 1,4,6
PMCID: PMC11514977  NIHMSID: NIHMS2026685  PMID: 39307401

Abstract

Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited and lethal neurodegenerative disease caused by the abnormal expansion of CAG repeats in the ATAXIN-1 (ATXN1) gene. Pathological studies identified dysfunction and loss of motor neurons (MNs) in the brain stem and spinal cord, which are thought to contribute to premature lethality by affecting the swallowing and breathing of SCA1 patients. However, the molecular and cellular mechanisms of MN pathogenesis remain unknown.

To study SCA1 pathogenesis in human MNs, we differentiated induced pluripotent stem cells (iPSCs) derived from SCA1 patients and their unaffected siblings into MNs. We examined proliferation of progenitor cells, neurite outgrowth, spontaneous and glutamate-induced calcium activity of SCA1 MNs to investigate cellular mechanisms of pathogenesis. RNA sequencing was then used to identify transcriptional alterations in iPSC-derived MN progenitors (pMNs) and MNs which could underlie functional changes in SCA1 MNs. We found significantly decreased spontaneous and evoked calcium activity and identified dysregulation of genes regulating calcium signaling in SCA1 MNs. These results indicate that expanded ATXN1 causes dysfunctional calcium signaling in human MNs.

Keywords: SCA1, Motor neurons, iPSCs, Transcription, calcium signaling

Introduction

Spinocerebellar ataxia type 1 (SCA1) is a relentlessly progressive neurodegenerative disorder caused by the expansion of CAG trinucleotide repeats in the ATXN1 gene. Over 39 uninterrupted CAG repeats in the coding region of ATXN1 result in disease, with longer number of repeats leading to earlier disease onset, more severe symptoms and faster disease progression (Orr et al. 1993; Orr and Zoghbi 2007). Thereby, while most patients with SCA1 have 40–60 CAG repeats, resulting in the onset of disease symptoms by 30 or 40 years of age, SCA1 patient with 82 CAG, the longest reported number of repeats, had a juvenile onset of disease at 4 years of age. SCA1 symptoms include progressively worsening motor discoordination, cognitive impairment, and difficulty breathing and swallowing, ultimately leading to death within 10–20 years of disease onset (Genis et al. 1995; Sasaki et al. 2009; Zoghbi and Orr 2009; Diallo et al. 2018; Matilla-Dueñas, Goold, and Giunti 2008).

Clinical symptoms of SCA1 are thought to result from the prominent degeneration of two key populations of neurons- the Purkinje cells of the cerebellum and the lower motor neurons of the brain stem and spinal cord. Postmortem neuropathological study documents marked reduction in the volume of the ventral horn of the spinal cord as well as in anterior roots and the gracile and cuneate fasciculi of the dorsal horn in patients with SCA1 (Robitaille, Schut, and Kish 1995). Magnetic resonance imaging (MRI)-based analysis reports spinal cord atrophy combined with anteroposterior flattening in SCA1 patients which correlates with severity of ataxia and length of CAG repeats (Martins et al. 2017). Given the importance of both brainstem motor nuclei and cervical lower motor neurons in driving respiratory strength (Marder and Bucher 2001; Mantilla and Sieck 2011) these findings have led to a predominant theory that the ongoing dysfunction and degeneration of lower motor neurons contributes to premature lethality in SCA1. Consistent with this, clinical signs of lower motor neuron dysfunction, specifically muscle weakening and fasciculations, have been correlated with time until death and have been found to be predictive of SCA1 lethality (Diallo et al. 2018).

Studies in the SCA1 knock-in mouse model have found reactive gliosis, demyelination, ATXN1 inclusions and shrinkage of motor neurons in the spinal cord and brainstem in conjunction with peripheral muscle degeneration and disrupted breathing (Takechi et al. 2013; Orengo et al. 2018). While mouse models of SCA1 are very useful, there are important caveats to consider. First, repeat size in SCA1 knock-in mouse models (146–175 CAG repeats) is extreme in comparison to the repeat length present in the adult SCA1 patients (40–60 CAG repeats) (Watase et al. 2002). In addition, inherent species differences between humans and mice (Manuel et al. 2019; Rayon et al. 2020; Mansvelder, Verhoog, and Goriounova 2019) are likely to result in slight differences in SCA1 pathogenesis in mouse MNs compared to human MNs, which could hamper efforts to identify translatable therapeutics for human patients.

Human iPSCs are created by reprogramming adult somatic cells (Takahashi and Yamanaka 2006; Takahashi et al. 2007; Staerk et al. 2010; Okita et al. 2013) to return an embryonic-like state while maintaining the donor’s genome (Bahmad et al. 2017) and represent a renewable resource to model human disease in different cell types (Muratore et al. 2017; Joshi et al. 2019). Differentiation of hiPSCs into lower motor neurons (MNs) is well-established and was successfully used to model human MN pathology in many diseases including Amyotrophic Lateral Sclerosis (ALS), Spinomuscular Atrophy (SMA), and Spinobulbar Muscular Atrophy (SBMA) (Sareen et al. 2013; Bianchi et al. 2018; Ho et al. 2016; 2021; Fujimori et al. 2018; Li et al. 2021; Workman et al. 2023).

To investigate the SCA1 pathology in human MNs and identify underlying molecular mechanism, we differentiated iPSCs from three patients with SCA1 and three unaffected sibling controls into human motor neurons. We subsequently characterized the effects of mutant ATXN1 on proliferation, neurite outgrowth, and differentiation from iPSCs into MNs. Calcium imaging was used to assess functional alterations of human SCA1 MNs by quantifying spontaneous and glutamate-evoked calcium activity compared to control MNs. Finally, since transcriptional roles of ATXN1 are key for SCA1 pathogenesis we used RNAsequencing to investigate how mutant ATXN1 impacts gene expression in MNs.

Methods

Generation and characterization of iPS cells

Skin fibroblasts were collected from participants after obtaining written, informed content as approved by the Institutional Review Board of the Human Subjects Committee at the University of Minnesota. iPS cells were derived from fibroblasts (Tolar et al. 2011) using CytoTune-iPS Sendain reprogramming 2.0 kit (Invitrogen) according to the manufacturer’s instructions (Supplementary Figure 1A). The evaluation of iPS cells was performed as described previously (Tolar et al. 2010). Repeat lengths for the ATXN1 CAG sequence were assessed for each expanded allele to confirm pathogenic elongation (Supplementary Figure 1A).

Human iPSCs were cultured in E8 media (Thermo, cat # A1517001) on growth factor reduced Matrigel (Corning, cat # 354230). Full media changes were done daily with passages occurring every 5–7 days at an approximate dilution of 1:6. Passage numbers for iPS cells used in this experiment were kept within the range of 17–30 passages depending on previous maintenance history and speed of recovery post-thaw.

Differentiation of hiPSC-derived Motor Neurons

The protocol used here has been previously described (Ho et al. 2021; Li et al. 2021) and was approved by Dr. Dhruv Sareen and Clive Svendsen (CSMNC-SOP-C-005). Briefly, in preparation for differentiation, iPSCs were passaged to reach approximately 30% density by the start of the experiment. On Day 0, Essential 8 Medium was removed from the cultured iPSCs and replaced with Neural Induction Medium comprised of 48% Iscove’s Modified Dulbecco’s Medium (IMDM), 48% Ham’s F-12 Nutrient Mixture (F12), 1% MEM Non-Essential Amino Acids Solution (NEAA), 2% B27, 1% N2, and the small molecules LDN193189 (0.2uM), SB431542 (10uM), and Chir99021(3uM) which serve to direct neuralization through dual Smad inhibition. Medium was replaced every other day until Day 6 of differentiation, when cells were considered to have reached a neural stem cell (NSC) state. At this point, cells were either directly passaged with Accutase at a density of 3.75e5 cells/mL or frozen down in Bambanker at a density of 5e6 cells/mL. Passaged cells were replated in an enriched version of Neural Induction Medium in which All-Trans Retinoic Acid (0.1 uM) and the Smoothened Agonist, SAG (1 uM), were added to further induce the relative caudal and ventral character of the developing cells in culture. Cells receive a full replacement of this medium every other day until Day 12 in culture, when they have reached an approximate motor neuron progenitor (or pre-Motor Neuron) stage of development. At this point, the medium was changed for a Maturation Medium comprised of 48% IMDM, 48% F12, 1% NEAA, 2% B27, 1%N2, and supplemented by the small molecules DAPT (2.5uM), Compound E (0.1uM), dibutryl-cAMP (0.1 uM), All-Trans Retinoic Acid (0.5 uM), SAG (0.1 uM), Ascorbic Acid (200ng/mL), Brain-Derived Neurotrophic Factor (BDNF, 10ng/mL), and Glial-Derived Neurotrophic Factor (GDNF, 10ng/mL). Starting on Day 18, 1mg/mL laminin was added as a supplement on a weekly basis. Maturation Medium was changed every other day until Day 35 in culture when samples were isolated for analysis. Based on Hox gene analysis in previous published work, this protocol yields motor neurons that approximate the upper cervical spinal cord and lowermost portion of the brain stem (Ho et al. 2021).

Because of the length of this process and the potential for introduced technical variability, the full differentiation was repeated four separate times with analyses repeated across experiments where possible.

RNA isolation and Reverse Transcriptase Quantitative Polymerase Chain Reaction (RT-qPCR)

Total RNA was extracted from 2 wells each of N = 3–4 SCA1 and N = 3 Unaffected cell cultures using the QIAshredder (Qiagen, Cat# 79654) and RNeasy Micro (Qiagen, Cat# 74004) Kits following manufacturer instructions.

cDNA was created in duplicates from isolated RNA using the Superscript First Strand Synthesis System (Thermo, Cat# 11904018) following manufacturer instructions. We used previously published oligomers for the following human genes: NANOG, SOX2, S16, GRIK1, HB9, CHAT, NGN2, and OLIG2. The specific forward and reverse sequences are provided on Table 1 below.

Table 1.

Primer list.

Gene Name Direction Sequence Reference
hATXN1 FWD AGAGATAAGCAACGACCTGAAGA
REV CCAAAACTTCAACGCTGACC
hNANOG FWD GCTTGCCTTGCTTTGAAGCA Bharathan et al 2017
REV TTCTTGACTGGGACCTTGTC
hSOX2 FWD CCCAGCAGACTTCACATGT
REV CCTCCCATTTCCCTCGTTTT
hsS16 FWD CGCGCACGCTACAGTACA Rousseaux et al 2018
REV CACGGATGTCTACACCAGCA
hsGRIK1 FWD GTCTCAAAGAGGAAGGAACTGAA
REV TCCCAATCTTCTTCCACACTTTA
hHB9 FWD GTCCACCGCGGGCATGATCC Shimojo et al 2015
REV TCTTCACCTGGGTCTCGGTGAGC
hChAT FWD GGAGGCGTGGAGCTCAGCGACACC
REV CGGGGAGCTCGCTGACGGAGTCTG
hNGN2 FWD AGACACGCACCACCACCACAACAC
REV TGACTTTGGCCTGTGCCGGGAATC
hOLIG2 FWD GTTCTCCCCTGAGGCTTTTC
REV AGAAAAAGGTCATCGGGCTC
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In addition, we used IDT Primetime primers for the following genes: GABRB2, GABRA2, ITPR2, CACNG3, FOXM1, GJA1, CACNA1G, NNAT, NUPR1, OR7D2, and DSCAM. Relative mRNA levels were calculated using either S16, ActB, or GAPDH as a loading control. Normalization was done using the average of the unaffected controls as a reference, with relative expression calculated using 2-ΔΔ-Ct as previously described (Rosa et al, 2023).

RNAsequencing and Analysis

Total RNA was isolated from two wells each of N = 3 SCA1 and N = 3 unaffected Day 12 pMN cultures and Day 35 MN enriched cultures using the QIAshredder (Qiagen, Cat# 79654) and RNeasy Micro (Qiagen, Cat# 74004) Kits following manufacturer instructions. RNA was sent to the University of Minnesota Genomics Center for quality control, which included fluorimetry quantification using the RiboGreen assay kit (Thermo Fisher Scientific) and assessment of RNA integrity via capillary electrophoresis using an Agilent BioAnalyzer 2100 to generate an RNA integrity number (RIN). Only samples with RIN values above 8.0 were submitted for sequencing. Library creation was completed using oligo-dT purification of polyadenylated RNA, which was reverse transcribed to create cDNA. cDNA was fragmented, blunt ended, and ligated to barcode adaptors. Libraries were size selected to 320 bp ± 5% to produce average inserts of approximately 200 bp, and size distribution was validated using capillary electrophoresis and quantified using fluorimetry (PicoGreen, Thermo Fisher Scientific) and qPCR. Libraries were then normalized, pooled, and sequenced on an S4 flow cell by an Illumina NovaSeq 6000 using a 150-nucleotide, paired-end read strategy. The resulting FASTQ files were trimmed, aligned to the human reference genome (GRCm38), sorted, and counted using the Bulk RNAseq Analysis Pipeline from the Minnesota Supercomputing Institute’s Collection of Hierarchical UMII/RIS Pipelines (v0.2.0) (Rosa et al. 2023).

Differential gene expression analysis was performed using the EdgeR package(Robinson, McCarthy, and Smyth 2010; McCarthy, Chen, and Smyth 2012) (v3.30.3) in R (R Foundation for Statistical Computing v3.6.1 “Lost Library Book”). Genes shorter than 300 bp are too small to be accurately captured in standard RNAseq library preparations, so they were discarded from all analyses. Genes with fewer than 10 read counts across all samples were excluded. Genes with resulting p values less than or equal to 0.05 with a corresponding absolute value of Log Fold Change (LogFC) of greater than or equal to 0.6 were considered significant. Pathway analysis and dot plot creation was performed using the gProfiler2 server at (https://biit.cs.ut.ee/gprofiler/gost) (PMID: 37144459) and clusterProfiler package (Yu et al. 2012) (v3.16.1) in R (v4.0.3). Heatmaps were created using the pheatmap package (https://cran.r-project.org/web/packages/pheatmap/index.html) (v1.0.12) in R (v4.0.3).

To identify which pMN and MN genes are regulated by CIC, we initially aimed to survey CIC motifs in the human genome as described in the 2023 Neuron paper. This approach required a position-specific weight matrix for the CIC binding motif. However, since we could not obtain this information from the 2023 paper, we used a reference CIC motif (TSAATGR) from the 2018 Cancer Research paper by Weissmann et al., which Coffin et al. identified as significantly similar. Scanning this 7-mer across the genome yielded over 2 million potential binding sites, leading us to hesitate in continuing with the motif enrichment analysis. We then reviewed the 131 CIC-regulated genes from the 2023 Neuron paper and identified 129 human homologous genes. Of these, 110 genes were evaluated in both the pMN and MN3 datasets

We have deposited the files in the public database, GEO accession GSE267449:

Western Blot

Cells were collected from culture plates using brief incubation with Accutase and pelleted by centrifugation at 1000g for 5 minutes. The resulting cell pellet was briefly washed with PBS and samples were lysed and homogenized in 100–200uL of Tris-Triton Lysis Buffer (50mM Tris, pH 7.5, 100mM NaCl, 2.5mM MgCl2, 0.5% Triton X-100) with protease and phosphatase inhibitors (Thermo, cat # 1862495 and 1862209) and a Roche COmplete Mini Protease inhibitor tablet (cat# 11836170001). Homogenized samples were shaken at 1500rpm at 4°C for 30 minutes, frozen and thawed in liquid nitrogen and 37°C water bath 3 times, and centrifuged at 21,000xg for 10 min at 4°C. Samples containing 30–60g total protein were boiled in Laemmli loading buffer and run on a 4%–20% Bio-Rad precast gel. Proteins were transferred to a nitrocellulose membrane using the BioRad Trans-Blot Turbo system (High molecular weight setting). Blots were blocked overnight at 4°C in 5% milk PBST (phosphate-buffered saline, 0.1% Tween 20), then incubated in 5% milk PBST with the ATXN1 antibody 11750 or 12NQ (1:2000) and a housekeeping control (either 1:10,000 α-Tubulin antibody (Millipore Sigma) or 1:5000 anti-GAPDH antibody (Millipore, MAB374)) overnight at 4°C. Blots were washed 3 times with PBST and then developed with Super Signal West Dura (Thermo Fisher Scientific) detection reagents. Blots were imaged and band intensity quantified on ImageQuant LAS 4000.

Immunocytochemistry (ICC)

Cells for fluorescent immunolabeling were grown on glass coverslips. Plated cells were fixed using freshly prepared 4% formaldehyde in PBS for 20 minutes at RT. Following fixation, cells were washed 1X with RT PBS before permeabilization with 0.25% PBS-Triton for 7 minutes. Blocking was performed in 10% NGS for 1hr at RT. Primary antibodies in 4% NGS were applied overnight at 4C followed by 3X wash in PBS at RT. Finally, secondary antibodies were applied for 1 hr at RT in a light-free environment before a final 3X wash in PBS and rinse in diH2O. Coverslips were airdried in a light-free environment and plated on glass slides using Vectashield with DAPI (Cat# H-1500) Primary and secondary antibodies used described in Table 2.

Table 2.

Antibody list.

Target Catalog Number
Nestin (Rb) N5413
Nestin (Ms) MA1–110
hSox2 (Ms) MAB2018
hNanog (Gt) AF1997
βIII Tubulin (Rb) T2200
ChAT (Ms) MA5–31387
Islet1 (Ms) Ab86501
Olig2 (Ms) MA5–15810
MNX1/HB9 (Rb) ABN174
NfH/SMI32 (Ms) 801701
VGLUT2 (Gp) Ab2251-i
PSD95 (Rb) 516800
BrdU (Rt) Ab6326
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Imaging and image analysis

For synaptic quantification image acquisition, confocal images (Z-stacks consisting of 20 non-overlapping 0.5-μm-thick slices) were acquired using a confocal microscope (Leica Stellaris 8) using a 40X oil objective. To quantify excitatory synaptic content, we analyzed synaptic quantification images using the ImageJ Puncta Analyzer plugin. Presynaptic (VGLUT2 and VGAT) signals were quantified individually, and colocalized puncta are then counted based on the Puncta Analyzer parameters.

Calcium Imaging

Motor Neuron enriched cultures were plated and maintained in 35mm dishes with full media changes of Maturation Media occurring every other day until cells reached Day 35. On the day of imaging, cells were treated with 3μM of freshly prepared Fluo4-AM in BrainPhys Medium (StemCell, Cat# 05790) following the manufacturer’s specifications. In brief, after a 20-minute incubation (37°C, 5% CO2), cells were washed 2x with RT PBS. Following this, cells were given 2mL of BrainPhys Medium per dish and returned to the incubator for 20 minutes to recover (37°C, 5% CO2).

Spontaneous calcium responses were recorded over a period of 4 minutes at RT at a rate of 1 frame per second (1Hz) on an epifluorescence microscope, using ProgRes Imaging Software. Image sequences were uploaded to ImageJ.

We performed event-based analysis with AQuA software (https://github.com/yu-lab-vt/AQuA), an open-source toolbox for fluorescence imaging data based on MATLAB (R2023b). The Fluo4-AM fluorescence dynamics were analyzed following the AQuA manual user guide, modifying parameters to optimize event detection for our recordings. An event was defined as follows: Minimum area of 16 square micrometers, minimum dF/F value of 0.15, minimum duration, 1 second. Edges were excluded. For spontaneous events, we analyzed the whole 4-minute recording except for the first 20 seconds to prevent false positives caused by photoactivation. The detected events were grouped by condition (unaffected and SCA1). For the glutamate application recordings, we considered baseline events that occur from the second 20 to the second 110 for both conditions. The stimulus events were considered from the glutamate application at 115 seconds up to 135 seconds.

Statistical Analysis

The RNAseq analyses were performed in R as described above. All other statistical tests were performed using GraphPad Prism software (v9.0). Data was assessed for normal distribution using Kolmogrov-Smirnov and Shapiro-Wilk tests. Parametric tests were performed if normal distribution of the data was established, otherwise non-parametric tests were chosen. Data was analyzed using two-way ANOVA, one-way ANOVA followed by either Tukey’s or Bonferroni post-hoc tests, or Student’s t-test. All data presented are shown as mean ± SD unless otherwise specified. Statistical analysis results are either indicated directly on graphs or denoted within the graph as “ns” (p≥0.05), * (p<0.05), ** (p<0.01), *** (p<0.001), and **** (p<0.0001).

Results

Creation of SCA1 Motor Neurons

Six iPSC lines were previously derived from the fibroblasts of three SCA1 patients (41, 43 and 46 CAG repeats) and three unaffected sibling controls. Karyotyping and quality control were performed as previously described (Tolar et al. 2011; Rousseaux et al. 2018) (Supplementary Figure 1A). Differentiation of hiPSCs into motor neurons was done following a well-established protocol (NeuroLINCs) (Supplementary Figure 1B) (Ho et al. 2016; 2021; Fuller et al. 2016; Li et al. 2021). In brief, this system uses a chemical environment reminiscent of the developing embryo to drive neuralization with dual-Smad inhibitors. During these initial six days of neuralization, cells go from a densely growing colony of iPSCs that highly express early proliferative markers such as Sox2 and Nanog to neural stem cells (NSCs) enriched for the early neural marker Nestin (Figure 1A). We then induced ventral spinal cord character through the application of All-trans Retinoic Acid, Sonic Hedgehog Agonist, and Wnt activation, resulting in an enriched population of motor neuron progenitors (pMNs), marked by high expression of transcription factors Olig2 and Nkx6.1 as well as the early outgrowth of neurites into the surrounding dish (Figure 1A). Finally, we applied Notch inhibitors and other maturation factors to induce maturation of motor neurons. We detected expression of motor neuron markers including neurofilament heavy chain component SMI32 at day 18 in culture, here referred to as the immature motor neuron (iMN) stage. Notably, in previously published work this is often the stage at which motor neurons are isolated for transcriptional assessment such as RNA sequencing (Ho et al. 2021). However, to examine a physiologically more mature motor neuron population, our cultures were maintained until day 35 when previous studies showed MNs become spontaneous active (NeuroLINCs). Mature motor neurons differentiated from both SCA1 and control iPSCs exhibited robust expression of MN markers including choline acetyl transferase (ChAT), Islet1 (ISL1), Homeobox HB9 (HB9 or MNX1), and neurofilament heavy chain component SMI32 (Figure 1A).

Figure 1. Creation of SCA1 MNs from patient and sibling control donated iPSCs.

Figure 1.

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A-A. hiPSCs, expressing Sox2 grow in tightly packed colonies with rounded edges. A-B Once neuralization began, budding of NSCs of stem cell colonies was evident and cells exhibited increased expression of early neural marker Nestin. A-C. Neurite outgrowth in pMNs revealed by SMI32 and expression of Nkx6.1 in pMNs. A-D. By D35, a large proportion of the cells were MNs expressing motor neuron markers HB9 and SMI32+. Scale bar = 30uM. B. RT-qPCR of marker genes demonstrates characteristic profiles expected across MN development. SOX2, a transcription factor highly expressed in iPSC (Day 0) and NSC (Day 6) cultures, OLIG2 is expressed in motor neuron progenitors (pMN), and the motor neuron marker ChAT is most highly expressed in MNs. C. Yield of motor neurons measured as a percentage of ISL1 or ChAT+ cells compared to total DAPI+ cells in MNs from SCA1 and unaffected controls. Unpaired students t-test, Welch’s correction did not reveal any difference between unaffected and SCA1 lines.

In addition to immunocytochemistry to confirm the expression of these markers in cultured cells, we quantified the expression of key marker genes over time using RT-qPCR. Comparison across stages demonstrated that the early proliferation gene SOX2 is most highly expressed in hiPSCs and NSCs with a subsequent decrease in expression as cultures mature into pMNs and finally MNs (Figure 1B). Previous work has shown that high expression of the bHLH transcription factor OLIG2 is temporally locked to pMNs in the early spinal cord (Lee et al. 2005; Dessaud et al. 2007). In agreement with this, we see an approximately 500-fold increase in OLIG2 expression that is restricted to cells around day 12 in culture (Figure 1B). Finally, ChAT expression is robustly associated with day 35 MNs (Figure 1B), indicative of MN differentiation. Importantly, comparison between SCA1 cultures and those of unaffected sibling controls demonstrated no significant differences in differentiation at any time point assessed. For both SCA1 and unaffected controls we achieved a 40% yield of motor neurons by the final time point (Figure 1C), consistent with previously established yields for hiPSC to MN differentiation (Sances et al. 2016) and indicating that expanded ATXN1 does not disrupt the differentiation of hiPSCs to motor neurons.

In situ hybridization has shown that Atxn1 is detectable from E14.5 in mice (Banfi et al. 1996). In humans, expression of ATXN1 is detectable from post conception week eight, the earliest time point sampled (Supplementary Figure 2, derived from BrainSpan: Atlas of the Developing Human Brain). While these results indicate that ATXN1 is expressed early in mouse and human neural development, it is important to determine how ATXN1 expression is altered during iPSC to MN differentiation. We found a robust induction of ATXN1 mRNA expression: approximately a 50-fold increase in MN (Day 35) compared to iPSCs (Day 0) (Figure 2A). Importantly, we have found that ATXN1 expression is not significantly different between SCA1 and unaffected controls at any of the stages of differentiation, including iPSC, and MNs (Figure 2B, Supplementary Figure 3).

Figure 2. ATXN1 is expressed in human iPSCs derived MNs.

Figure 2.

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A. RT-qPCR was used to assess the relative expression of ATXN1 over differentiation. Data is mean ± SD with dots representing individual cell lines. N = 3 SCA1 and N = 3 Unaffected sibling controls. Two-Way ANOVA Genotype x Cell Stage, genotype p = 0.8959, time p = 0.0002. B. Quantification of ATXN1 protein between SCA1 and control lines. Data is mean ± SD with dots representing individual cell lines. N = 3 SCA1 and N = 3 Unaffected sibling controls. Unpaired student’s t-test, NSC p = 0.1803, iMN p = 0.3460, Day 35 MN p = 0.7635.

Expanded polyQ increases stability of proteins and this can lead to formation of inclusions and aggregates. We performed ICC for ATXN1 in MN cultures to assess the presence of inclusions or aggregates and did not detect ATXN1 aggregates in SCA1 MNs cultures (Supplementary Figure 4). These results indicate that expanded ATXN1 is present in MN enriched cultures, providing the opportunity to investigate how ATXN1 with 41 to 46Q impacts human motor neurons.

Mutant ATXN1 does not affect proliferation human iPSCs and NSCs

Previous studies indicated that expanded ATXN1 affects proliferation of adult hippocampal neuronal stem cells and cerebellar progenitors during development (Asher et al 2016, Edamakanti et al 2018)(Cvetanovic, Hu, and Opal 2017). Therefore, we evaluated whether proliferation of human cells at different stages of differentiation, including iPSCs, neural stem cells (NSCs) and pMNs, is impacted by expression of expanded ATXN1.

We used incorporation of thymidine analog bromodeoxyuridine (BrdU) to quantify proliferation. We have not found any significant change in the proliferation at any stage of differentiation, iPSC, NCS or pMNs (Supplementary Figure 5). These results indicate that mutant ATXN does not significantly affect proliferation of human iPSCs, NSCs or pMNs.

Neurite outgrowth is not altered in SCA1 pMNs or iMNs

Previous studies demonstrated reduced neurite outgrowth upon expression of expanded ATXN1[82Q] protein in cultured neurons (Cvetanovic, Kular, and Opal 2012). Therefore, we next investigated whether more moderate repeat expansion causing adult onset of SCA1 (42–43 repeats) can similarly impact neurite outgrowth in human neurons.

During MN differentiation, neurite outgrowth starts around Day 11 in culture and progresses rapidly so that by MN stage neurites form a thick network (Figure 1). To determine whether neurite outgrowth was disrupted during these initial stages of neurite outgrowth, we analyzed the relative extension of neurites in SCA1 pMN at days 12, 13, and 14, using staining with intermediate neurofilament marker SMI32 (Figure 3A). As expected, both SCA1 and unaffected pMNs extended neurites over subsequent days in culture. We found no differences in the length of the longest neurite per cell (considered a primary neurite), or the total neurite length (the summed length of all neurites and branches from a single cell) between SCA1 and unaffected pMNs (Figure 3B–C). This indicates that pMN neurite outgrowth is not affected by mutant ATXN1.

Figure 3. Mutant ATXN1 does not impact neurite outgrowth in SCA1 pMNs and MNs.

Figure 3.

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A. To assess neurite outgrowth over time, pMNs were passaged at day 11 and outgrowth was assayed through immunofluorescent staining for SMI32 at days 13, 14 and 15 (scale bar= 30uM). pMN primary outgrowth was measured as the length of the longest measurable neurite extending from the soma of a cell (B), and Total pMN outgrowth, including all measurable neurites from a single cell (C). D. To assess whether outgrowth was affected at iMNs stage cells were passaged at Day 18 and plated onto glass coverslips following the same paradigm as the pMN outgrowth experiment (scale bar = 100uM). E. The longest primary neurite. F. Total iMN outgrowth. N = 3 SCA1 and N = 3 Unaffected sibling controls. Data is mean ± SEM with dots representing individual cell lines. N = 3 SCA1 and N = 3 Unaffected sibling controls. Two-way ANOVA identified differences over time but not over genotype.

We next examined neurite outgrowth in immature motor neurons (iMNs). We replated iMNs at day 18 in culture and measured neurite length on days 19, 20, and 21. Day 18 was chosen as the optimal time point for replating as iMNs express characteristic MN markers but are not yet so densely clustered that neurites are hard to distinguish, nor so outgrown that the stress of passaging induces cell death. Comparison of growth across time revealed no effect of genotype on the length of the primary neurite (Figure 3E) or total neurite outgrowth (Figure 3F). These results suggest that human SCA1 MNs and pMNs expressing ATXN1 with ~42Q have normal neurite outgrowth.

Spontaneous and evoked calcium signaling is reduced in SCA1 MNs

Calcium signaling is one of the key signaling mechanisms that regulate many cellular processes and is also used as a measure of neuronal activity (Bootman and Bultynck 2020; Grienberger and Konnerth 2012; Brini et al. 2014). Moreover, calcium signaling is disrupted in many neurodegenerative diseases, including SCA1 (Egorova, Popugaeva, and Bezprozvanny 2015; Kasumu and Bezprozvanny 2012; Hisatsune, Hamada, and Mikoshiba 2018; Grekhnev, Kaznacheyeva, and Vigont 2022). Therefore, we examined whether expression of expanded ATXN1 might reduce basal/spontaneous or evoked calcium signaling in hiPSC-derived SCA1 MNs.

We used the cell membrane permeable calcium indicator Fluo4-AM to quantify spontaneous and glutamate-evoked calcium activity (Figure 4A–B) (Bursch et al. 2019; Dafinca et al. 2020; Bianchi et al. 2018). We found a significant decrease in the average amplitude of spontaneous calcium events and in the area under the curve (AUC) as a more summative measure of spontaneous calcium signaling in SCA1 MNs compared to unaffected MNs. These results indicate a decrease in the spontaneous calcium activity in SCA1 MNs compared to control MNs (Figure 4C).

Figure 4. Spontaneous and glutamate-evoked calcium signaling is reduced in SCA1 MNs.

Figure 4.

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A. Representation of calcium imaging experimental paradigm using Fluo4-AM. B. Representative traces of spontaneous and glutamate-evoked calcium in unaffected (black) and SCA1 (red) MNs. C. Average amplitude and area under the of spontaneous calcium events in unaffected (black) and SCA1 (red) MNs. T-test. **** P < 0.001. N = 3 SCA1 and N = 3 unaffected MNs. D. Percent change in the average amplitude and area under the of curve from baseline after glutamate stimulation. One-way ANOVA with Tukey’s post hoc test * P < 0.05, ** P < 0.005, **** P < 0.0001.

We then used glutamate to examine whether evoked calcium activity might be perturbed in SCA1 MNs. As expected, glutamate elicited an increase in the amplitude and AUC of calcium events in unaffected MNs. However, this response was remarkably attenuated in SCA1 MNs (Figure 4D). Together, these suggest an attenuated calcium response to glutamate stimulation, as well as reduced spontaneous calcium activity in SCA1 MNs.

Mutant ATXN1 causes transcriptomic alterations in pMNs and MNs

Previous studies demonstrated that ATXN1 regulates gene expression and implicated critical role of transcriptional perturbations caused by mutant ATXN1 in SCA1 pathogenesis (Rousseaux et al. 2018; Handler et al. 2023; Coffin et al. 2023; Tejwani et al. 2024). Therefore, we next investigated how mutant ATXN1 impacts gene expression in human cells. Since our results indicate measurable ATXN1 expression in both motor neuron progenitors (pMN) and motor neurons (MN), we performed RNA sequencing of SCA1 and unaffected sibling control pMNs and MNs.

We identified 275 differentially expressed genes (DEGs, defined as absolute logFC ≥ 0.6 and P < 0.05) in SCA1 pMNs (Figure 5, Table 3). We found a slight preference toward gene upregulation in SCA1 pMNs (164 genes, 58.2% of total) (Figure 5B). Using RT-qPCR, we validated altered expression of the DEGs G protein receptor olfactory receptor 7D2 (OR7D2), neuronatin (NNAT), and down syndrome cell adhesion molecule (DSCAM) (Figure 5C).

Figure 5. Mutant ATXN1 perturbs transcription in pMNs.

Figure 5.

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RNA sequencing was performed on RNA isolated from day twelve pMNs. We identified 275 DEGs defined by p value < 0.05 and an absolute log fold change (LogFC) greater than 0.6. A. Heatmap of DEGS. B. Volcano plot of DEGs. C RT-qPCR was used to validate altered expressions of DSCAM, NNAT and OR7D2. N = 3 SCA1 and N = 3 unaffected sibling controls. Data is mean ± SD. * P < 0.05 unpaired Student’s t-test. D. Pathway analysis with first six GO: BP, next three GO:MF and last one KEGG.

To predict the functional effect of these gene expression changes, we performed both KEGG and GO pathway analyses. KEGG analysis identified alteration in the extracellular matrix (ECM)-receptor interaction pathway in SCA1 pMNs (Figure 5D). Among altered GO pathways was integrin binding, further implicating altered interaction with extracellular matrix in SCA1 pMNs (Figure 5D). Additionally, DNA-binding transcription factor activity was altered, suggesting a role for ATXN1 in regulating transcription early in development of MNs.

The magnitude of transcriptomic disruption was larger at the MN stage, with a total of 525 DEGs (Table 4). Most DEGS were downregulated (414 or 78.9%) (Figure 6). This shift to downregulation suggests a potential change in the genes regulated by ATXN1 and/or increase in ATXN1 expression over the course of neuronal development. That said, there were several genes that were consistently altered in both pMNs and MNs, including the G protein receptor olfactory receptor 7D2 (OR7D2), neuronatin (NNAT), and down syndrome cell adhesion molecule (DSCAM) that we validated using qPCR (Figure 6C). KEGG and GO pathway analyses identified ECM alterations in the SCA1 MN stage with a larger number of affected genes in this pathway than at the pMN stage (Figure 6D). In addition to increased expression of DSCAM that promotes neuronal self-avoidance (Millard and Zipursky 2008), we also found decreased expression of genes that play a critical role in establishing cell-to-cell connections including two members of protocadherin gamma gene cluster, Protocadherin Gamma Subfamily A (PCDGA)1 and PCDGA4 thought to play a critical role in the establishment and function of synaptic connections in the CNS (Zhu et al. 2023). These ECM alterations may result in increased avoidance and decreased synaptic connectivity in SCA1 MNs. Using pre-and post-synaptic markers PSD95 and VGLUT2, we found a trending reduction in excitatory synapse density in SCA1 MNs cultures (Supplementary Figure 6). Interestingly, we also found a reduced expression of gene low density lipoprotein receptor-related protein 4 (LRP4) that plays an important role in the regulation of clustering of acetylcholine receptors at the skeletal muscles (Ohkawara et al. 2020). These gene expression changes likely contribute to decrease in the spontaneous calcium signaling that we observed in SCA1 MNs and may cause dysfunction of neuromuscular junction.

Figure 6. Mutant ATXN1 perturbs transcription in MNs.

Figure 6.

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RNA sequencing was performed on RNA isolated from day 35 MNs. We identified 525 DEGs defined by p value < 0.05 and an absolute Log2FC greater than 0.6. A. Heatmap of DEGs. B. Volcano plot of DEGs. C. RT-qPCR was used to validate altered expressions of DSCAM, NNAT and OR7D2. N = 3 SCA1 and N = 3 unaffected sibling controls. Data is mean ± SD. Unpaired Student’s t-test. D. KEGG and GO:MF pathway analyses.

In addition, using GO analysis we identified alterations in calcium ion binding pathway in SCA1 MNs. Among decreased genes in the calcium binding pathway were calcium binding proteins such as Synaptotagmins (SYT 15), as well as Inositol 1,4,5-trisphosphate receptor type 2 (ITPR2). ITPR2 protein mediates a release of calcium from the endoplasmatic reticulum (ER) in response to receptor signaling (such as Group I metabotropic glutamate receptors)(Ziegler et al. 2021), and decreased ITPR2 expression is likely to contribute to decreased glutamate response in SCA1 MNs. Additional impacted pathways included transforming growth factor beta binding, Wnt binding and Wnt receptor activity. Among top pathways identified by KEGG analysis were ECM-receptor interaction, Hippo signaling, protein digestion and absorption, PI3K-Akt signaling pathway, Wnt signaling pathway, cell cycle, TGF-beta signaling pathway, cellular senescence, and gap junction (Figure 4D). Changes in Wnt and PI3K-Akt signaling are particularly notable, as they recapitulate known signaling pathways disrupted in other brain regions in SCA1 (Luttik et al. 2022).

Previous studies indicated that the enhanced interaction of polyglutamine-expanded ATXN1 with the transcriptional repressor CIC drives cerebellar Purkinje cell pathogenesis in SCA1 mouse models (Rousseaux et al 2018). However, a recent study demonstrated that CIC-expanded ATXN1 interactions may play less of an important role in the spinal cord of SCA1 mice (Coffin et al 2023). To determine the importance of CIC-expanded ATXN1 interaction in pMNs and MNs, we examined how expression of CIC regulated genes is altered in human SCA1 pMNs and MNs (Supplementary Figure 7, Table 5). None of the CIC targets were significantly altered in either SCA1 pMNs or MNs, indicating that CIC may not be critical for SCA1 pathogenesis in these cells.

Discussion

We have created a human motor neuron model of SCA1 to provide insight into the impact of mutant ATXN1 on human motor neurons and to characterize SCA1 pathology in an understudied cell type thought to contribute to the lethality of SCA1.

We found that ATXN1 mRNA and protein are expressed in iPSCs-derived motor neurons but have not found any differences in ATXN1 mRNA or protein expression between SCA1 and unaffected cultures. CAG repeat expansion diseases are characterized by the presence of inclusions or aggregates. ATXN1 inclusions are seen in postmortem SCA1 patient tissues and are detectable at later stages of disease in SCA1 mouse models. As we have not detected inclusions or aggregates in SCA1 hiPSC-derived MN, considering the early developmental stage of these cells it is possible that longer time in culture and further maturation are needed to detect aggregates. Intriguingly, a recent study found aggregates forming in generic neuronal cultures derived from different set of SCA1 patient-derived iPSCs (Buijsen et al., 2023). Future studies could address whether motor neurons are more resistant to forming aggregates than generic iPSCs-derived SCA1 neurons.

Given the evidence supporting the critical role of mutant ATXN1 in transcriptional perturbations in SCA1 mouse models (Handler et al. 2023; Rousseaux et al. 2018; Coffin et al. 2023; Tejwani et al. 2024), we hypothesized that mutant ATXN1 would alter the transcriptional profiles of human SCA1 pMNs and MNs. Indeed, we identified transcriptional changes in both SCA1 pMN and MN, with the number of DEGs increasing as cells matured over time in culture. Notably, several genes were dysregulated in both SCA1 pMNs and MNs, including the upregulation of the cell adhesion molecule DSCAM and the GPCR OR7D2 as well as the downregulation of the proteolipid neuronatin (NNAT). NNAT has previously been identified as a significantly downregulated gene in bulk RNAsequencing of both the 10wk brainstem and 26wk medulla in SCA1 knock in mice (Handler et al. 2023; Coffin et al. 2023). In addition to NNAT, we have also identified NUPR1 and ITPR2, which are significantly altered in 26wk mouse brain stem samples. Together, these could suggest a degree of overlap in the molecular pathology of this disease relevant brain region between mouse brainstem and human motor neurons. While previous studies indicated that the interaction of polyglutamine-expanded ATXN1 with the transcriptional repressor CIC drives cerebellar Purkinje cell pathogenesis, our results indicate a limited role for CIC in the transcriptional alterations in SCA1 pMNs and MNs, at least in the examined stages. However, among genes regulated by CIC we found an interesting trending decrease in KCNC3 potassium channel mutated in SCA13. Considering the genetic variability and early developmental stage of these cells it is possible that more lines and/or longer time in culture and further maturation are needed to detect CIC’s role in SCA1 human MNs.

Intriguingly, pathway analysis of both MNs and pMNs demonstrates that a large proportion of disrupted genes are involved in the regulation of the ECM (Supplementary Figure 8). During early neural development and into adulthood, ECM regulation contributes to neuron projection formation, which is critical to the establishment of connections and effective cellular communication. While it is reasonable to assume that perturbations in ECM pathway will impact neuronal outgrowth in SCA1 cultures, we found that SCA1 pMNs and iMNs were indistinguishable from control cells in the relative length of extending neurites. One possible explanation is that rich matrix support needed for iPSCs differentiation is masking measurable effects of ECM disruption on neurite growth. Future work could explore this by using assays of minimal matrix support for growing cells.

Previous work in the SCA1 mouse model has shown that ATXN1 expansion alters the activity of Purkinje cells and the expression of glutamate receptor genes in the cerebellum (Rousseaux et al. 2018; Handler et al. 2023; Tejwani et al. 2024). We have found here that amplitudes of both basal/spontaneous and glutamate evoked calcium signaling are reduced in SCA1 MNs. There are several possible explanations for the reduced glutamate response seen in SCA1 MNs. First, there is a consistent reduction in the expression of calcium regulating genes such as ITPR2, which might drive reduction in calcium release from ER in SCA1 MNs. Additionally, perturbation of ECM genes may alter the ability of neurons to form stable glutamatergic synapses. This is supported by the trending decrease in the number of excitatory VGLUT2/PSD95+ synapses seen in SCA1 MN cultures compared to controls. In addition, both pMNs and MNs exhibit a decreased expression of NNAT (Tables 1 and 2), known for its critical role in regulating ion channels during development (Pitale, Howse, and Gorbatyuk 2017). Reduced expression of NNAT may indicate perturbation in electrophysiological development in human SCA1 MNs as previously seen in cerebellum and cortex of SCA1 mice (Hatanaka et al. 2015; Edamakanti et al. 2018).

Finally, one of the advantages of using hiPSC-derived cells to study neurodegenerative disease is that they model early stages of disease, which are difficult to investigate in patients. While symptoms are not seen in SCA1 patients until around 30 years of age, our results further indicate that ATXN1 is expressed early in development and that transcriptomic disruption is likely occurring from very early ages in patients with SCA1. Mouse models also provided critical insight that the early stages of disease present most effective therapeutic window for SCA1 (Zu et al. 2004; Friedrich et al. 2018). The results of our study further indicate that early transcriptional disruptions may alter neuronal activity and responsivity. These functional changes may allow further insight into the underlying mechanisms affecting neuronal health in patients with SCA1.

Supplementary Material

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Supplementary Figure 1. A. Cell lines used to derive pMNs and MN and number of CAG repeats (over 39 CAG causes SCA1). B. RepPCR confirming expansion of CAG repeats in iPSCs lines. C. Overview of the differentiation protocol.

Supplementary Figure 2. Assessment of average RPKM values for ATXN1 expression across the developing human brain (solid line, bars represent SD) demonstrates a steady increase in expression (dotted line) with time but with a high degree of variability likely attributable to changing regional and temporal patterning. Derived from BrainSpan: Atlas of the Developing Human Brain.

Supplementary Figure 3. ATXN1 expression in NPCs, iMNs and MNs. Western blots of proteins extracted from SCA1 and unaffected siblings control lines at different stages of iPSCs to MN differentiation: NPC (A), iMNs (B), MNs (C). We included protein extracts from WT and ATXN1 null mice in C to indicate ATXN1 band. The lower band is Tubulin, used to normalize ATXN1 expression during quantification presented in Figure 2.

Supplementary Figure 4. ATXN1 and SMI32 immunocytochemistry in SCA1 MNs.

Supplementary Figure 5. Proliferation of early progenitor stages. A.-C. Proliferation was assessed via BrdU incorporation. A. Human iPSCs were stained for BrdU and the proportion of cells that were BrdU+ compared to the total number of DAPI+ nuclei were assessed via immunofluorescence. Scale bar = 100uM. B. Colorimetric assay was used to quantify BrdU incorporation. P values are from unpaired student t-test, Welch’s correction. C. Cell counts were assessed across passages at pMN transition (unpaired students t-test, p = 0.3797) or the iMN transition (unpaired student’s t-test, p = 0.7428). Data is mean ± SEM with dots representing individual cell lines. N = 3 SCA1 and N = 3 Unaffected sibling controls.

Supplementary Figure 6. Quantification of excitatory presynaptic VGLUT2+, postsynaptic PSD95+ and co-localized VGLUT2/PSD95 puncta. Data is mean ± SEM with dots representing individual cell lines. N = 2 SCA1 and N = 3 Unaffected sibling controls. Student’s t-test.

Supplementary Figure 7. Expression of genes regulated by Capicua (CIC) in MNs and pMNs.

Supplementary Figure 8. Comparison of KEGG and GO pathways altered at pMNs and MNs stages.

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4

Highlights:

  1. Using iPSCs derived from SCA1 patients and unaffected siblings fibroblasts, we created human SCA1 MNs.

  2. Expanded ATXN1 did not impact proliferation of progenitors (iPSCs, NSC, pMNs), or neurite outgrowth of pMNs and MNs.

  3. SCA1 MNs exhibited decreased spontaneous and glutamate-evoked calcium activity compared to unaffected control MNs.

  4. RNAsequencing identified dysregulation of genes regulating calcium signaling and ECM in SCA1 MNs.

Acknowledgments:

We acknowledge all the members of the Orr and Cvetanovic laboratories for thoughtful discussions and feedback on the study. Work in this study was aided by the Genomics Core at the University of Minnesota. This work was supported by the National Institute of Health NINDS award (NS197387 to M.C.), National Ataxia Award 76855 to MC, and Doctoral Dissertation Fellowship award (to CS).

Footnotes

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Conflict of interest statement:

The authors declare no competing financial interests.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1

Supplementary Figure 1. A. Cell lines used to derive pMNs and MN and number of CAG repeats (over 39 CAG causes SCA1). B. RepPCR confirming expansion of CAG repeats in iPSCs lines. C. Overview of the differentiation protocol.

Supplementary Figure 2. Assessment of average RPKM values for ATXN1 expression across the developing human brain (solid line, bars represent SD) demonstrates a steady increase in expression (dotted line) with time but with a high degree of variability likely attributable to changing regional and temporal patterning. Derived from BrainSpan: Atlas of the Developing Human Brain.

Supplementary Figure 3. ATXN1 expression in NPCs, iMNs and MNs. Western blots of proteins extracted from SCA1 and unaffected siblings control lines at different stages of iPSCs to MN differentiation: NPC (A), iMNs (B), MNs (C). We included protein extracts from WT and ATXN1 null mice in C to indicate ATXN1 band. The lower band is Tubulin, used to normalize ATXN1 expression during quantification presented in Figure 2.

Supplementary Figure 4. ATXN1 and SMI32 immunocytochemistry in SCA1 MNs.

Supplementary Figure 5. Proliferation of early progenitor stages. A.-C. Proliferation was assessed via BrdU incorporation. A. Human iPSCs were stained for BrdU and the proportion of cells that were BrdU+ compared to the total number of DAPI+ nuclei were assessed via immunofluorescence. Scale bar = 100uM. B. Colorimetric assay was used to quantify BrdU incorporation. P values are from unpaired student t-test, Welch’s correction. C. Cell counts were assessed across passages at pMN transition (unpaired students t-test, p = 0.3797) or the iMN transition (unpaired student’s t-test, p = 0.7428). Data is mean ± SEM with dots representing individual cell lines. N = 3 SCA1 and N = 3 Unaffected sibling controls.

Supplementary Figure 6. Quantification of excitatory presynaptic VGLUT2+, postsynaptic PSD95+ and co-localized VGLUT2/PSD95 puncta. Data is mean ± SEM with dots representing individual cell lines. N = 2 SCA1 and N = 3 Unaffected sibling controls. Student’s t-test.

Supplementary Figure 7. Expression of genes regulated by Capicua (CIC) in MNs and pMNs.

Supplementary Figure 8. Comparison of KEGG and GO pathways altered at pMNs and MNs stages.

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