pca and heatmaps  (RStudio)

Journal: iScience

Article Title: Gut microbiota differences in five-year-old children that were born preterm with a history of necrotizing enterocolitis: A pilot trial

doi: 10.1016/j.isci.2024.110325

Figure Lengend Snippet: The diversity index across groups (A) Pink area in Lorenz graph took a larger percentage of the total area in NEC group, which was representative of a high degree of inequality. (B) Example of Simpson index in NEC and control cases. (C) Significant lower Shannon index and higher Simpson index in NEC group. (D) Distribution of Shannon index for each case within each group. (E) Distribution of Simpson index for each case within each group. (F) Pink area in Lorenz graph took a larger percentage of the total area in surgical NEC treated group, which was representative of a high degree of inequality. (G) Example of Simpson index in NEC-medical and NEC-surgical cases. (H) Significant lower Shannon index and higher Simpson index in NEC-surgical group compared to the control group. (I) Distribution of Shannon index for each case within each group. (J) Distribution of Simpson index for each case within each group. (K) Significant higher Berger Parker Dominance index in NEC group compared to the control group. (L) Trend of increase in Berger Parker Dominance index in NEC-surgical group compared to the control group. (M) Distribution of Berger Parker Dominance index for each case within each group. (N) Distribution of Simpson index for each case within each group by considering treatment. (O) Principal component analysis (PCA) analysis of the similarity of microbiota (OTUs) between the control, medical, and surgical groups. (P) Cluster heatmap of beta diversity included NEC and control groups with no significant different clustering. (Q) Rarefaction curve based on Shannon H index. (R and S) No difference in richness between the groups. (T and U) Distribution of richness for each case within each group. Data are presented as median, 1–99th percentile. Statistical comparison between control ( n = 24) and NEC ( n = 15) groups was performed using the non-parametric Mann-Whitney test and between the control ( n = 24), NEC-medical ( n = 7) and NEC-surgical ( n = 8) groups was performed using the non-parametric and Kruskal-Wallis test. ∗ p < 0.05; ∗∗ p < 0.01. See also Figure S1 .

Article Snippet: All sequencing data were computed using the R-based interactive of iNEXT software, based on statistical estimation of the true Hill number of any order q ≥ 0 for diversity estimation., , Heatmap and PCA were generated by applying Qlucore Software (Lund, Sweden).

Techniques: Control, Comparison, MANN-WHITNEY

Journal: Scientific Reports

Article Title: Characterization of alternative mRNA splicing in cultured cell populations representing progressive stages of human fetal kidney development

doi: 10.1038/s41598-022-24147-z

Figure Lengend Snippet: RNA sequencing identifies a set of genes that are differentially expressed between the early, intermediate, and late developmental stages of the human fetal kidney, where cells at the early stage of human kidney development (NCAM-high/CD133-low, hFK1) have a mesenchymal gene expression profile that is similar to that observed in blastemal-predominant Wilms’ tumor patient-derived xenografts (WT-PDX). ( A ) A PCA biplot of gene expression levels. The three human fetal kidney cell fractions (hFK1, hFK2, and hFK3) lie on a trajectory (dotted black arrow) along which the epithelial-associated genes (CDH1, EPCAM, and PROM1 [= CD133]) increase and mesenchymal-associated genes (CDH11, ZEB1, NCAM1, SIX2) decrease. Note the large spread of Wilms’ tumor xenografts in gene expression space, which indicates a large variability between tumors from different patients. ( B ) Hierarchical clustering of 67 selected genes that were previously found to be related to kidney development. It can be seen that the blastemal-predominant Wilms’ tumor patient-derived xenografts (WT37, WT14, and WT11) are similar to hFK1—the cell fraction that represents the most immature fraction of the human fetal kidney—in that they overexpress mesenchymal related genes and under-express epithelial related genes. The order of genes and the dendrogram were determined by hierarchical clustering of the human fetal kidney samples only (hFK1, hFK2, and hFK3). Note that although most epithelial associated genes that are over-expressed in hFK3, the podocyte markers PODXL, NPHS1/2, and SYNPO are only high in the early developmental stages (hFK1) and decrease with differentiation to hFK2 and hFK3. This is probably due to the fact podocytes cannot be cultured in the serum-free media that was used to culture the hFK cells. ( C ) Barplots of selected mesenchymal and epithelial associated genes involved in kidney development show sequential decrease in mesenchymal-associated genes and sequential increase in epithelial-associated genes in the fetal kidney samples (hFK1, hFK2, and hFK3), whereas the three Wilms’ tumor xenografts (WT11, WT14, and WT37) all have high expression of mesenchymal associated genes and relatively low expression of epithelial-associated genes. ( D ) Gene Ontology (GO) enrichment analysis for 395 genes that were upregulated at least twofold (log2foldChange > 1) in hFK3 (the mature fetal developmental fraction) with respect to hFK1, WT11, WT14, and WT37 (see Fig. ) shows that they are related to epithelial differentiation (see Table ). Likewise, Gene Set Enrichment Analysis (GSEA) showed that genes that are over-expressed in the early developmental cell fraction hFK1 (with respect to late fraction hFK3) are related to the Epithelial to Mesenchymal transition (EMT).

Article Snippet: Heatmaps, PCA biplots, and barplots were performed in Matlab (Mathworks) and R. Gene Ontology (GO) enrichment analysis was done with ToppGene ( https://toppgene.cchmc.org ) .

Techniques: RNA Sequencing, Gene Expression, Wilms Tumor Assay, Derivative Assay, Cell Culture, Expressing

Journal: Scientific Reports

Article Title: Characterization of alternative mRNA splicing in cultured cell populations representing progressive stages of human fetal kidney development

doi: 10.1038/s41598-022-24147-z

Figure Lengend Snippet: RNA sequencing identifies a set of transcripts that are alternatively spliced between the early, intermediate, and late developmental stages of the human fetal kidney, where cells at the early stage of human kidney development (NCAM-high/CD133-low, hFK1) have a mesenchymal splice-isoform profile that is similar to that observed in blastemal-predominant Wilms’ tumor patient-derived xenografts (WT-PDX). ( A ) Hierarchical clustering of the inclusion levels of 36 selected cassette exons that were manually found to be alternatively spliced between hFK1 and hFK3—the two cell populations that represent early (hFK1) and late (hFK3) developmental stages in the fetal human kidney. Note that the late-stage fetal kidney cell fractions hFK2 and hFK3 are grouped in one cluster, whereas hFK1, the early-stage fraction, is grouped with the Wilms’ tumor xenograft samples. The 36 cassette exons were selected as follows: We chose cassette exons that were significantly differentially spliced (FDR < 1E−9 and difference in inclusion levels > 0.1) between hFK1 and hFK3, and from these we selected 36 cassette exons that also showed clear alternative splicing by manual inspection in the IGV genome browser. ( B ) Barplots and sashimi plots for selected cassette exons show the change in inclusion levels between the different cell fractions. Exons within the genes MYL6 and CLSTN1 are high in Wilms' tumors and early fetal kidney cells (hFK1) and decrease during kidney development (hFK2 and hFK3), while those within ENAH and SLK are low in Wilms' tumors and early fetal kidney cells (hFK1) and increase during kidney development (hFK2 and hFK3). ( C ) A PCA biplot of exon inclusion levels that were calculated by rMATS. Each point represents a different cell fraction. The three human fetal kidney samples (hFK1, hFK2, and hFK3) lie on a trajectory (dotted black arrow) along which the epithelial-associated exons within the genes CD44 and ENAH sequentially increase, and a mesenchymal-associated exon within the gene CTNND1 sequentially decreases. For PCA analysis we used all cassette exons that were detected by rMATS. ( D ) Gene Ontology (GO) enrichment analysis for the genes containing the 36 selected cassette exons indicates that they are related to mesenchymal or epithelial characteristics (e.g. cell motility and cell to cell junctions) and that alternative splicing in a significant fraction of these genes is regulated by the RNA binding proteins ESRP1 and ESRP2 (see Table ).

Article Snippet: Heatmaps, PCA biplots, and barplots were performed in Matlab (Mathworks) and R. Gene Ontology (GO) enrichment analysis was done with ToppGene ( https://toppgene.cchmc.org ) .

Techniques: RNA Sequencing, Wilms Tumor Assay, Derivative Assay, Alternative Splicing, RNA Binding Assay