Clusters of Temporal Discordances Reveal Distinct Embryonic Patterning Mechanisms in Drosophila and Anopheles

Evolving organs are seen as clusters of discordant genes on the heatmaps representing cross-species comparisons of developmental gene expression data

Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front.

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We re-engineered co-detection by indexing (CODEX) for paraffin-embedded tissue microarrays, enabling simultaneous profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating how complex biological processes, such as antitumoral immunity, occur through concerted actions of cells and spatial domains

Bringing Open Data to Whole Slide Imaging

Supplementary information associated with Besson et al. (2019) ECDP 2019 Faced with the need to support a growing number of whole slide imaging (WSI) file formats, our team has extended a long-standing community file format (OME-TIFF) for use in digital pathology. The format makes use of the core TIFF specification to store multi-resolution (or "pyramidal") representations of a single slide in a flexible, performant manner. Here we describe the structure of this format, its performance characteristics, as well as an open-source library support for reading and writing pyramidal OME-TIFFs

Time warping of evolutionary distant temporal gene expression data based on noise suppression

<p>Abstract</p> <p>Background</p> <p>Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution.</p> <p>Results</p> <p>We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (<it>Saccharomyces cerevisiae</it>) and fission (<it>Schizosaccharomyces pombe</it>) yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping) properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment.</p> <p>Conclusion</p> <p>Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.</p

A set of Drosophila genes expressed in the yolk is maternal in mosquito.

<p>(A) Temporal expression patterns of a set of genes, which are co-expressed at mid-embryogenesis in Drosophila and are coincidently maternal in mosquito. (B,C) Example of an ortholog pair (AGAP005948-CG1555) from (A) analyzed by RNA situ hybridization. Top panels correspond to freshly laid eggs; bottom panel corresponds to mid-embryogenesis. (D,E) Another example of an ortholog pair from (A) (AGAP004451-CG9232). Top panels correspond to freshly laid eggs; bottom panel corresponds to mid-embryogenesis. (F and G) Line graph representation of genes analyzed in (B,C) and (D,E) (expression profiles of mosquito genes are in blue; the fruitfly genes are in red). (H) Other examples of genes from (A), only the fruit fly RNA in situ hybridizations are shown.</p

Clusters on the discordance map reflect the presence of new cell types in one of the organisms.

<p>(A) Discordance heatmaps for mosquito versus fruitfly development (discordance cutoff  = 1.7). Horizontal and vertical axis correspond to relative temporal position and length of the window used for discordance analysis. The color corresponds to the number of orthologous gene pairs within this window with discordance values above the cutoff. (B) Discordance heatmaps for the datasets without the mosquito serosal genes (as defined in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000584#pbio.1000584-Goltsev2" target="_blank">[22]</a>) and their fruitfly orthologues. Note the disappearance of the cluster 15 (marked by transparent black rectangle around the cluster) on the map of the genes upregulated in mosquito. (C) Discordance heatmaps constructed for the datasets made exclusively from the mosquito serosal genes (taken from <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000584#pbio.1000584-Goltsev2" target="_blank">[22]</a>) and their fruitfly orthologues. (D) Enrichment of the serosal genes in the ranked gene list extracted from cluster 15 at different discordance cutoffs (from 0 to 3). Small cutoffs (<1) produced large gene lists (>100 genes) with small enrichments (<20%), and large cutoffs (>1.7) produced small gene clusters (<25 genes) with good enrichment (>30%). (E) Receiver Operating Characteristic (ROC) curve for ranked gene lists extracted from cluster 15 at a range of discordance cutoffs (from 0 to 3).</p

Linear correspondence between the fruitfly and the mosquito development.

<p>(A) Isometric view of the Pearson similarity matrix for normalized, log2- and z-transformed datasets, resampled to 100 points and Gaussian-smoothed in the window of 20 points (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000584#s4" target="_blank">Methods</a>). <i>x</i>- and <i>y</i>-axis correspond to series of individual time points examined by gene expression screens in both species. Heatmap colors (blue, similar; red, dissimilar) correspond to numerical distance between the corresponding stretches of the datasets calculated by <i>Time-warp</i>. (B) 2D view of Pearson similarity matrix. White path indicates the automatic alignment (correspondence between the individual time-points in orthologous datasets) generated by time warping. Black path shows the correspondence between the sampling times in both organisms established on the assumption of linear correlation of developmental time. (C) Clusters of best correlating genes in both organisms after the transformation of datasets by global alignment. Under the cluster map is the diagram of the relative duration of <i>Drosophila</i> developmental stages <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000584#pbio.1000584-Hartenstein1" target="_blank">[36]</a>.</p