Fig. 1
From: Common and distinct transcriptional signatures of mammalian embryonic lethality
Experimental strategy and data processing. a Experimental workflow for E9.5 baseline and mutant line analysis. For the baseline, wild-type mice from heterozygous incrosses generated as part of the DMDD project were outcrossed (WT strain cross) and embryos from these crosses were collected. This was to produce embryos with a similar genetic background to the mutants. For the mutant lines, embryos were obtained from heterozygous intercrosses (Het mutant cross). The processed data can be viewed using Baseline CompaRe. The baseline data are available in Expression Atlas. b Clustered gene expression network identifies co-expressed genes across the baseline samples. The gene expression data are displayed using BioLayout Express3D as a network of genes (nodes) with edges connecting nodes whose expression values over all the samples have a Pearson correlation coefficient of ≥0.85. Nodes represent 9265 genes and are coloured according to Markov clustering (MCL). Surrounding graphs show expression of genes in a selection of clusters with individual embryos ordered by somite number on the x-axis, and gene expression in the cluster (unit variance scaled with standard deviation) on the y-axis. Batch outliers (top left) are genes that were blacklisted from further analysis. Decreasing/increasing genes are the ones most indicative of stage as they change the most across the time course, whereas the cluster labelled Stable is more consistent. Highly variable and decreasing is a set of genes that have high variance even among embryos at the same stage. Single embryo signal is a cluster of genes that are expressed at high levels in just one embryo. Xist, Y chr genes and MT genes (genes encoded by the mitochondrial chromosome) were removed due to high variability. c Venn diagram of the categories of novel (previously unannotated) genes identified using all RNA-seq data across all embryos. d Heatmap of expression profiles of the novel genes. Each row is a gene and each column a sample in somite number order. In each row, expression data are scaled to the maximum value (set to 1) for that row. The genes are ordered by hierarchical clustering. Source data are provided as a Source Data file
