Journal: PLoS Genetics

Article Title: Retinoic Acid Signaling Regulates Differential Expression of the Tandemly-Duplicated Long Wavelength-Sensitive Cone Opsin Genes in Zebrafish

doi: 10.1371/journal.pgen.1005483

Figure Lengend Snippet: A. Statistical Analysis of Microarray (SAM) plot, at a 0.109 false discovery rate (FDR). B. Gene ontology (GO) analysis; selected GO categories shown. C. Venn diagram comparing differentially expressed genes in eyes of RA-treated embryos with those of RA-treated whole embryos during somitogenesis and with those of hearts of RA-treated larvae.

Article Snippet: The data were compared to those obtained using Affymetrix platform-based microarray analysis of RA treatments in zebrafish embryos, over different developmental times or in different tissues [ , ].

Techniques: Microarray

Journal: PLoS Genetics

Article Title: Retinoic Acid Signaling Regulates Differential Expression of the Tandemly-Duplicated Long Wavelength-Sensitive Cone Opsin Genes in Zebrafish

doi: 10.1371/journal.pgen.1005483

Figure Lengend Snippet: A. cyp26b1 . B. hoxb6a . C. socs3a . D. dkk1b . E. sfrp1a . F. wnt 11 . G. and J. opn1lw1 . H. and K. opn1lw2 . I. rod opsin ( RH1 ). White boxes, DMSO; gray boxes, at-RA (both in embryonic eye tissues); dark gray boxes, 9-cis RA (in whole embryos). In the boxplots, the boxes demarcate the 25 th and 75 th percentiles, dark horizontal lines designate the medians, and whiskers represent the upper and lower limits. Genes in A-C, E-G, were all identified as upregulated by the microarray; dkk1b was identified as downregulated; opn1w2 and rod opsin were not detected as differentially expressed. ***, p<0.001; **, p<0.01; *, p<0.05 (2-tailed Student’s t-test).

Article Snippet: The data were compared to those obtained using Affymetrix platform-based microarray analysis of RA treatments in zebrafish embryos, over different developmental times or in different tissues [ , ].

Techniques: Microarray

Journal: EBioMedicine

Article Title: H 2 S Regulates Hypobaric Hypoxia-Induced Early Glio-Vascular Dysfunction and Neuro-Pathophysiological Effects

doi: 10.1016/j.ebiom.2016.03.002

Figure Lengend Snippet: Weighted Gene Coexpression Network Analysis (WGCNA) of time series global expression data. A) Scheme of data mining employed for analyzing microarray data. The lists of differentially expressed genes were subjected to various softwares including DAVID (Online resource), BiNGO and GeneMANIA (as Cytoscape plugins) besides Weighted Gene Coexpression Network Analysis (WGCNA). The biological networks were then represented as ‘Degree sorted circular view’ and GO networks as ‘Perfused forced directed clusters’. B) Principal Component Analysis (PCA) of gene expression data sets from the hippocampus of animals exposed to HH (Days 1, 3 and 7) and Normoxia (Control) represented as two dimensional plot of PC1 (Component 1) and PC2 (Component 2). C) Hierarchical clustering of gene expression data. Color intensities correspond to log2 expression values of individual genes. D) Clustering dendrogram of samples based on their Euclidean distance. The trait Heat Map is depicted for the Path Length and Latency parameter of MWM test. E) Modules (represented with unique color) corresponding to branches of cluster tree generated from clustering dendrogram of genes with dissimilarity based on topological overlap. F) Dendrogram obtained by clustering of module Eigengenes with dissimilarity based on topological overlap. Red line indicates cut-off value (0.1) G) Cluster dendrogram showing merged module with Eigengene value < 0.1 represented by unique color. The original module color (as shown in panel E, utilized for dynamic tree cut) is also included for reference. H) Module-trait association plot representing relationship of modules with Latency (Time taken to reach the platform, in seconds) and Path Length (Distance (in m) travelled by the rat to reach the platform). Rows correspond to module Eigengene while columns to Latency and Path Length. Respective correlation and p-values are indicated in each cell. I) Clustered, over-represented groups of GO and functional terms identified from various modules using hyper geometric test in BiNGO (Cytoscape plug-in). The figure indicates gross annotation for GO term clusters identified by boxes. J) The top panel shows the bar graph obtained by plotting module Eigengene value (y-axis) plotted against time (HH Days 1, 3 & 7). The bottom panel represents heat map of expression values of genes composing respective modules.

Article Snippet: One-color microarray based gene expression analysis was performed utilizing Agilent microarray platform and all raw data sets were submitted to GEO (Accession number: GSE66287 ).

Techniques: Expressing, Microarray, Generated, Functional Assay

Journal: BMC Genomics

Article Title: MicroRNA expression in bone marrow-derived human multipotent Stromal cells

doi: 10.1186/s12864-017-3997-7

Figure Lengend Snippet: a Supervised principal component analysis of miR-572 and miR-638 for RT-qPCR data MSC set 1. b Supervised principal component analysis of miR-572 and miR-638 for RT-qPCR data MSC set 2. c Supervised principal component analysis of miR-572 and miR-638 for the microarray data (all donors and passages)

Article Snippet: Based on the analysis in this article, it was reported that the Agilent microarray platforms had the highest reproducibility out of 12 platforms with the Qiagen miScript platform ranking ninth.

Techniques: Quantitative RT-PCR, Microarray

Journal: Nature cell biology

Article Title: Synaptotagmin-Like Proteins Control Formation of a Single Apical Membrane Domain in Epithelial Cells

doi: 10.1038/ncb2541

Figure Lengend Snippet: (A) Experimental design for function screen of regulators of 3D epithelial polarity. MDCK cells cultured for 36h in 2D or 3D (n=3) and control (2D) and experimental (3D) samples were analyzed using the Affymetrix Canine Genome 2.0 platform. Significant data was determined by FDR-LIMMA (FDR<0.05). A set of significantly upregulated (>2-fold) genes was pooled with other genes of interest and then gene overexpression was validated by RT-qPCR. Bioinformatic pathway analyses revealed that some genes were connected in common functional pathways. A final set of 47 candidates were selected for stealth® siRNA design. MDCK cells were transfected with siRNAs individually or in pools and cultured to grow cysts. Silencing efficiency of the siRNA was determined by RT-qPCR. Then, cells were fixed and stained with Podxl, β-catenin and nuclei to quantify normal lumen formation. The RNAi screening finally resulted in 16 positive hits (see Methods) (B) RNAi screening for polarization regulation. Lumen formation efficiency was quantified for each of the listed 47 siRNA treatment. Green dotted line, ‘normal’ levels as found in control; red dotted line, the threshold considered for the definition of a positive hit (Lumen formation < 75 % of control; p<0.05,). Green stars, positive hits. Red dots, KDs where efficiency was below 60%. Asterisks represent statistical significance (p<0.05). n = 3; error bars represent SD. (C) Examples of phenotypes induced by RNAi in the screen. 72h MDCK cysts transfected with siRNA from 4 positive candidates (SMTNL2, CLDN2, RHOU, FUZ) and stained with apical marker Podxl (red), basolateral marker β-catenin (green), tight junction marker ZO-1 (white), and nuclei (blue). Bar, 5µm. (D) Epithelial cancers with downregulated 3D polarity gene set. The expression levels of the candidate-gene-set in all cancer vs. normal expression datasets were analyzed using Oncomine ( www.oncomine.org ). The graph shows the number of downregulated genes per type of indicated epithelial cancers (p<0.05, n varies in each tissue). (E) Frequency of gene downregulation in breast and kidney cancer data-sets. The graph indicates the % of data-sets with downregulated candidate gene in breast and kidney cancer vs. normal tissue microarray data-sets (Oncomine, p<0.05). Yellow arrowheads denote genes downregulated in both, breast and kidney cancer.

Article Snippet: A microarray-based differential expression analysis was conducted using the Affymetrix Canine Genome 2.0 platform.

Techniques: Cell Culture, Over Expression, Quantitative RT-PCR, Functional Assay, Transfection, Staining, Marker, Expressing, Microarray