Journal: Nature Communications

Article Title: A fast-acting lipid checkpoint in G1 prevents mitotic defects

doi: 10.1038/s41467-024-46696-9

Figure Lengend Snippet: A Diagram depicting cell-cycle phases and workflow. Expected lipid changes and timing of the lipid checkpoint are indicated. B Lipidome analysis at different time points of EGF-released MCF-10A cells. Center: Clustergram shows log 2 fold-change time course of lipid abundance compared to unreleased cells (blue is increased, red is decreased). Top: 4 groups of lipids based on clustergram (MATLAB). Bar graphs show the number of lipids per class per group. Lipid classes are color-coded. Bottom: Individual lipid examples shown as lipid concentration (normalized peak area) over time. C Fold enrichment of saturated (Sat.) or unsaturated (Unsat.) lipids for the individual lipid groups from ( B ). D Schematic summary of the data showing early and late increased (blue and light blue) and decreased (red and light red) lipid classes during the cell-cycle progression (summary for S/G2/M is extrapolated based on the data for G1). Lipid classes are color-coded as in ( B ). E Schematic depicting workflow of EGF release and inhibitor treatment. F Lipidome analysis of cells treated with C75 (30 µM) for 3 or 6 h. Values are shown as log 2 fold-change relative to DMSO control treated cells. Each dot represents a lipid species, background and dots are color-coded per lipid class. Dot size indicates significance. Data are combined of four independent experiments and represented as mean. G Top: Cumulative log 2 fold-change of each lipid species measured after C75 treatment (blue: 3 and red: 6 h). The order of the lipids and the three lipid groups are based on clustergram (MATLAB). Dark gray bars indicate saturated lipid species. Bar graphs show fold enrichment of saturated and unsaturated lipids per lipid group across all 250 lipids measured. B , C , G P values are calculated using two-sided Fisher’s Exact test for enrichment across 250 lipids. Data are from four independent experiments. FC fold-change, ns not significant, PUFA polyunsaturated, MUFA monounsaturated, SFA saturated.

Article Snippet: These data sets were then used to calculate the correlation values (Supplementary Data ) and clustered based on their similarities using the clustergram function in Matlab.

Techniques: Concentration Assay, Control

Journal: Nature Communications

Article Title: A fast-acting lipid checkpoint in G1 prevents mitotic defects

doi: 10.1038/s41467-024-46696-9

Figure Lengend Snippet: A Scatter plots show example correlations between relative lipid abundance and S phase percentage over the different inhibitor treatments and time points. Line indicates linear fit. Dots are labeled based on inhibitor treatment and time point. B Left: Nodes of the network are color-coded based on the correlations between relative lipid abundance and S phase percentage. Right: For orientation the lipid map shows the nodes of the network color-coded by lipid classes. A , B Data are combined of at least three independent experiments and shown as mean. C Top: Hierarchical clustering of lipid-mRNA abundance correlations. Rows: 250 lipids, columns: 3739 differentially expressed genes after C75 treatment. Bottom: Rug plot represents the distribution of ATF4-dependent genes and the gray area shows the percentage of ATF4-dependent genes per gene cluster. 3739 genes are divided into 11 gene clusters (clustergram - MATLAB) based on their lipid correlation. Clusters 5 and 6 are significantly enriched for ATF-dependent genes as calculated by two-sided Fisher’s exact test. D – F Example correlations of selected genes with 250 lipids color-coded on the circular network. Different clusters show different distribution of correlations across the network. G Bar plot shows fold enrichment for Gene Ontology (GO) Terms (BP direct) among genes significantly upregulated in cells treated with C75 for 3 h at 9 h after EGF release (mRNA sequencing data, significant in at least 3 replicates, p.adj <0.05, filtered for increased expression in starved cells and at least twofold upregulated compared to DMSO control). P values were calculated using EASE score (Fisher’s Exact test). Processes sorted by false discovery rate (FDR)–adjusted P value. Redundant processes omitted. H Volcano plot shows differentially regulated genes after 3 h of C75 treatment. Differentially expressed genes (log 2 (fold-change) | > 1, p.adj. <0.014) in blue (genes associated with the ER stress pathway based on GO terms) or magenta (ATF4-dependent genes ) or both (blue-magenta). CDKN1A (p21) is highlighted in red as the ER stress-cell cycle link. G , H P. adj. values are Benjamini-Hochberg adjusted p values calculated using the two-sided Wald test. Inhibitor concentrations used: C75 (30 µM), GSK2194069 (50 µM), SCDi (32 µM). FC, fold-change.

Article Snippet: These data sets were then used to calculate the correlation values (Supplementary Data ) and clustered based on their similarities using the clustergram function in Matlab.

Techniques: Labeling, Sequencing, Expressing, Control

Journal: PLoS ONE

Article Title: Deep Annotation of Populus trichocarpa microRNAs from Diverse Tissue Sets

doi: 10.1371/journal.pone.0033034

Figure Lengend Snippet: Clustering of smallRNA sequencing runs by miRNA expression. [miRNA expression = (Raw Abundance)/(Number of Mappable Reads)×1,000,000] reveals that xylem and mechanically treated xylem (MTX) are most similar. MATLAB clustergram algorithm was used for expression clustering.

Article Snippet: Hierarchical clustering of the four sequenced datasets based on annotated miRNAs and expression levels of these miRNAs was performed using MATLAB's Clustergram algorithm ( ) , .

Techniques: Sequencing, Expressing