Additional file 1 of Transcriptomics of Gabra4 knockout mice reveals common NMDAR pathways underlying autism, memory, and epilepsy
Creators: name: Fan, Cuixia
name: Gao, Yue
name: Liang, Guanmei
name: Huang, Lang
name: Wang, Jing
name: Yang, Xiaoxue
name: Shi, Yiwu
name: Dräger, Ursula
name: Zhong, Mei
name: Gao, Tian-Ming
name: Yang, Xinping
Publisher: name: figshare
Year: 2020
Subjects: subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Neuroscience
subject: Biological Sciences not elsewhere classified
subject: Mental Health
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Plant Biology
subject: Computational Biology

description: Additional file 1: Figure S1. Genotyping of Gabra4-/- mice and behavior tests. A Mutants were identified by Sanger sequencing. B Gabra4-/- mice showed no significant preference for the both chambers on the left and right (n = 16 for WT, and n = 8 for Gabra4-/-). No significance, Student’s t test. C Gabra4-/- mice (n = 11) and wild type mice (n = 11) traveled similar total distance during 30-minute open field test. D During the first 5 minutes in open field test, Gabra4-/- mice spent less time in the center zone compared to wild type mice. No significance, n = 19 for WT, n = 11 for Gabra4-/-, Student’s t test. E Both WT and Gabra4-/- buried similar number of marbles. No significance, n = 10 for WT, n = 9 for Gabra4-/- mice, Student’s t test. F-G Gabra4-/- mice showed similar percentage of freezing time during training (F) and test day (G) as WT mice. No significance, n = 9 for WT, n = 7 for Gabra4-/-, Student’s t test. H Gabra4-/- and WT displayed the similar velocity. No significance, n = 13 for WT, n = 16 for Gabra4-/-, Student’s t test. All data presented as mean ± SEM. Figure S2. Increased excitatory synapses. A The representative pictures of spine density of the hippocampus from wild type mice and Gabra4-/- mice. Brain tissues from mice 10 weeks old were used for Golgi-Cox staining and dendritic spines were examined in Ix71 inverted microscope with a 100× objective oil immersion lens (Olympus Life Science). The number of spines per 30 μm of dendrite was compared between genotypes. B Quantification of dendritic spine density in WT versus Gabra4-/- neurons. Data are presented as scatter grams (with mean ± SEM superimposed), each point corresponds to the mean spine density for a single neuron. Gabra4-/- mice showed increased spine density (WT, n = 39 neurons from 3 animals, Gabra4-/-, n = 50 neurons from 4 animals, p = 0.0403, Student’s t test). C The representative electron micrograph shows the postsynaptic densities of the hippocampus from wild type mice and Gabra4-/- mice. Scale bar, 200 nm. D Cumulative frequency distribution of PSD length in postsynaptic density of WT and Gabra4-/- mice, respectively. No significant difference between WT and mutant mice (n = 58 for WT, and n = 48 for Gabra4-/- mice, Student’s t test). E Cumulative frequency distribution of PSD thickness in postsynaptic density of WT and Gabra4-/- mice, respectively. No significant difference between WT and mutant mice (n = 59 for WT, and n = 48 for Gabra4-/- mice, Student’s t test). Figure S3. PCA analysis of RNAseq data, clustering of DEGs and expression level of GABA receptors and glutamate receptors. A PCA analysis of RNAseq data was performed on genes with more than 1 raw counts in at least 4 samples using plotPCA DEseq2. B Heatmap of DEGs was plotted on log2-transformed expression data using pheatmap1.0.10 package. C-E Expression levels of GABA receptors (C) and glutamate receptors (D and E) were represented by the FPKM values calculated from the RNAseq data. The p Values were calculated using Student's t-test. F-H Real-time PCRs were carried out on the differentially expressed GABA receptor Gabra2 (F) and glutamate receptors Grin1 (G) and Grin2c (H). All data presented as mean ± SEM; n = 7 for WT and n = 5 for Gabra4-/- mice; The p Values were calculated using Student's t-test. Figure S4. Distinct functions between upregulated and downregulated genes (DEGs). A Schizophrenia candidate genes are enriched in Gabra4-/- differential expression genes. Error bars represent the standard error of the fraction, estimated using bootstrapping method with 100 resamplings. **p &lt; 0.01, Fisher’s exact test. B The enriched cellular components of GO terms with DEGs. The top 10 enriched terms with up- and down-regulated genes. C The enriched molecular functions of GO terms with DEGs. The top 10 enriched terms with up- and down-regulated genes. Figure S5. Construction of hippocampal interactome network and extraction of DEG subnetwork, ASD subnetwork, LM subnetwork and EP subnetwork. The mouse hippocampal interactome, which contained 4,202 nodes and 9,205 edges, was constructed by integrating the hippocampal expressed genes and a protein interaction data from BioGRID (Biological General Repository for Interaction Datasets). Four subnetworks were extracted by mapping the “seeds” (DEGs, ASD candidate genes, LM-related genes or EP candidate genes) on to the hippocampal interactome network to include the interconnected “seeds” and their co-expressed neighbors in the hippocampal interactome network. Figure S6. Subnetworks extracted from randomized PPI networks compared to real subnetworks. Mouse PPI interactome from BioGRID was randomized for 1,000 times by shuffling nodes and 4 sets of seeds (DEGs, ASD candidates, EP candidates, LM candidates) were mapped onto the 1,000 randomized networks to extract subnetworks as controls. The size distribution of each control set of subnetworks was plotted in comparison with the size of each real subnetwork. Blue lines indicate the mean sizes of the control subnetworks, and red arrows indicate the sizes of the real subnetworks. A Node counts distribution of DEG subnetworks extracted from randomized networks. B Edge counts distribution of DEG subnetworks extracted from randomized networks. C Node counts distribution of ASD subnetworks extracted from randomized networks. D Edge counts distribution of ASD subnetworks extracted from randomized networks. E Node counts distribution of EP subnetworks extracted from randomized networks. F Edge counts distribution of EP subnetworks extracted from randomized networks. G Node counts distribution of LM subnetworks extracted from randomized networks. H Edge counts distribution of LM subnetworks extracted from randomized networks. Figure S7. Comparison of the enriched pathways with ASD, epilepsy and LM subnetworks. The comparison of enriched KEGG pathways with the three subnetworks. There are 37 enriched pathways shared by three subnetworks. The enrichment analysis was performed using DAVID bioinformatics tool with a p-value cutoff of 0.05 and FDR less than 0.05. ASD: autism; EP: epilepsy; LM: learning/memory. Figure S8. Gene-pathway bipartite networks for DEGs, ASD candidates, EP candidates, LM-related genes. A DEG-pathway bipartite subnetwork. DEGs were mapped onto the hippocampal expressed gene-pathway bipartite network to extract a subnetwork including DEGs and their involved pathways, and the pathways significantly enriched with DEGs (p &lt; 10-6) and containing at least 10 seed genes were kept. B Comparison of enriched pathways in DEGs PPI subnetwork and DEG-pathway bipartite subnetwork. C ASD gene-pathway bipartite subnetwork. ASD candidate genes were mapped onto the hippocampal expressed gene-pathway bipartite network to extract a subnetwork including ASD candidate genes and their involved pathways, and the pathways significantly enriched with ASD candidate genes (p &lt; 10-6) and containing at least 10 seed genes were kept. D Comparison of pathways enriched in ASD PPI subnetwork and ASD gene-pathway bipartite subnetwork. E EP gene-pathway bipartite subnetwork. EP candidate genes were mapped onto the hippocampal expressed gene-pathway bipartite network to extract a subnetwork including EP candidate genes and their involved pathways, and the pathways significantly enriched with EP candidate genes (p &lt; 10-6) and containing at least 10 seed genes were kept. F Comparison of pathways involved in EP PPI subnetwork and EP gene-pathway bipartite subnetwork. G LM gene-pathway bipartite subnetwork. LM-related genes were mapped onto the hippocampal expressed gene-pathway bipartite network to extract a subnetwork including LM-related genes and their involved pathways, and the pathways significantly enriched with LM-related genes (p &lt; 10-6) and containing at least 10 seed genes were kept. H Comparison of pathways involved in LM PPI subnetwork and LM gene-pathway bipartite subnetwork. I The network module shared by all three gene-pathway bipartite subnetworks. Fisher’s exact test was used for calculating all the p values.