## 3 Results
### Co-Expression Analysis of Coding and Non-Coding Transcripts  
To investigate the possible interactions between coding [32] and non-coding deregulated RNAs that emerged from RNA-Seq, we constructed a weighted gene co-expression network via WGCNA R package (see M&M section). In Nichoid-grown NPCs and standard floating conditions samples, three gene modules (brown, blue, and turquoise) in total were  
Figure 1: Change in morphology and transcription profiles in Neural Precursors Cells expanded inside the Nichoid. (**A**) On the left, in vivo direct light images (EVOS FL microscope, Euroclone) of NPCs neurospheres maintained in stem cells medium in standard floating conditions (Control NPCs) or grown, with the same medium, inside the Nichoid (Nichoid NPCs) for 7 days. Scale bar 400 \(\upmu\)m. Images are representative of observations obtained in more than 10 experiments. On the right, representative images of Nichoid-grown NPCs analyzed by Environmental Scanning Electron Microscope (ESEM). Scale bar 20 \(\upmu\)m. (**B**) For RNA-Seq, 3 samples for condition were analyzed. Specifically, three experiments were performed each including one sample of NPCs grown in standard floating conditions for 7 days and one sample of NPCs grown inside the Nichoid for 7 days. The graph shows the Heatmap and the PCA of non-coding differently expressed genes in NPCs grown on the Nichoid and in standard conditions. (**C**) Volcano plot showing only non-coding deregulated genes between NPCs grown on the Nichoid and in standard conditions. (**D**) Bar plot describing the classification of the non-coding deregulated genes found with RNA-Seq approach. Among the 357 non-coding deregulated genes, we identified 118 “unannotated genes”, 102 lncRNAs, 91 pseudogenes, and 46 small ncRNAs. identified (Figure 2A). Genes which are not co-expressed in any modules are assigned to the grey module. The turquoise module was the largest one with 89 genes, followed by the blue with 62 genes and the brown with 46 genes. For further analysis, we focused our attention on the turquoise and blue modules. According to the Pearson's correlation coefficient, the turquoise module seems positively correlated with Nichoid-grown NPCs samples (correlation value of 0.5 with the exception for NIC2_S7, where no correlation emerged) and negatively correlated with standard floating condition samples (correlation value of \(-0.5\)), as shown in Figure 2B. On the contrary, the blue module seems to be positively correlated with standard floating conditions (correlation value ranging from 0.4 and 0.5) and negatively correlated with Nichoid-grown NPCs (correlation value of \(-0.7\)) (Figure 2B). Furthermore, we constructed interaction networks for these two modules via Cytoscape to highlight the interactions between coding and non-coding genes altered by 3D NPCs expansion. Globally, among the 1577 total coding DE RNAs [32], 92 of them were found to be involved in the interaction with 22 non-coding genes (Table S1). This suggest that ncRNAs could exert their functions through a modulation of these interacting coding DE RNAs. In particular, Figure 3A displays the network built on the basis of the turquoise module. Here, seven lncRNAs (e.g., _6230400D17 Rik_, _Gm28592_, _Gm22_, _Gm27019_, _Gm23925_, _Gm45067_, _Gm21269_) and one antisense (e.g., _Gm45606_), highlighted respectively in light blue and in pink in Figure 3A, interact with each other and with 58 coding genes. Interestingly, all coding genes involved in this interaction are up-regulated and are thus represented in orange according to their fold change (Figure 3A). On the other hand, Figure 3B displays the network obtained when considering the blue module. Here, nine lncRNAs  
Figure 2: Weighted co-expression analysis network between the top 100 most deregulated coding and non-coding genes in terms of \(1\log\)2 FC\(1\). (**A**) Clustering dendrograms of genes, with dissimilarity based on topological overlap, together with assigned module colors.