Joubert Syndrome-derived induced pluripotent stem cells show altered neuronal differentiation in vitro

Introduction
This database includes the script used for the differential gene expression (DGE) analysis linked with the paper "Joubert Syndrome-derived induced pluripotent stem cells show altered neuronal differentiation in vitro." published on "Cell and tissue research". 
In this paper we analyzed the differentiation steps of  JS patient-derived iPSCs towards cerebellar granule cells. We demonstrated that JS patient-derived iPSCs have an impaired expression of the genes of neuronal differentiation, analyzed through real time pcr and immunofluorescence in four different time points from D0, starting day, till D31 end of the differentiation protocol. This data were confirmed by transcriptomic analysis showing an impaired progression along the differentiation time course of the JS-patients derived IPSCs respect to control cells. We also analyzed cilia length and numbers in both patients and control cells, demonstrating notable ciliary defects in all differentiating JS patient-derived iPSCs compared to controls. Taken together our results shows that patient-derived iPSCs are an accessible and relevant in vitro model to analyze cellular phenotypes connected to the presence of JS gene mutations in a neuronal context. 

Methods
Gene expression data from an RNA-seq experiment (Illumina platform) were initially processed with command line interface to align reads on the reference genomes and to count reads falling on coding regions (gene expression counts), with the pipeline outlined in the Materials and Methods section of the paper. The metadata contained sample names, mutated genes defining experimental conditions and time points for each sample.
This script, written with the R programming language, performed a comprehensive analysis of the processed next-generation sequencing data (read counts). To ensure the reproducibility of our analysis, we initialized the R environment by setting a specific seed for random number generation.
Several R libraries were used in our analysis, including edgeR, RColorBrewer, DESeq2, ggplot2, openxlsx, readxl, and ggrepel. These libraries provided essential functions for statistical analysis, data visualization, and manipulation.
The workflow contained in this script consisted of several steps: we generated count-per-million (CPM) values and filtered out genes with low expression. Reads Per Kilobase Million (RPKM) values were then calculated to account for gene length and normalize the data, to ensure compatibility of expression levels across experiments and genes. Differential gene expression was performed using the DESeq2 package, through the creation of a DESeqDataSet object, the estimation of size factors and dispersions, and the fitting of models. Differentially expressed genes between different conditions and time points were visualized with a volcano and heatmap plot.

Results
Results of the transcriptomic analysis show differences in the expression of genes relating to the central nervous system development already at D8, in particular cerebellum markers (LMX1A, OLIG3) being expressed only in controls cells. At D24, differences in gene expression became more evident, underlining for control samples the expression of genes specific to the terminal phases of cerebellar differentiation (ASTN2, CNTN1, WNT3, PLXNA2, LMX1B) and the expression of genes encoding proteins of neuronal functionality (GRIA4, SYT8, GRIK1, P2RX2, PCP4, GRIK2). In contrast, expression of these genes was significantly lower in JS lines, which showed early differentiation markers still predominantly expressed (ITGB1, CXCL12, HIF1A, EN2, GBX2, BMPR1B, CUL2, RPL37, RPL39, RPL35, PSMD2, and PSMD3). Taken together, these data support the observations, obtained with the other assays in our paper, that JS-iPSC lines show an impaired progression along the differentiation time course and a reduced ability to reach the maturation state seen in controls.