Additional file 1: of Humanized yeast genetic interaction mapping predicts synthetic lethal interactions of FBXW7 in breast cancer
Creators: name: Kirzinger, Morgan
name: Vizeacoumar, Frederick
name: Haave, Bjorn
name: Gonzalez-Lopez, Cristina
name: Bonham, Keith
name: Kusalik, Anthony
name: Vizeacoumar, Franco
Publisher: name: Figshare
Year: 2019
Subjects: subject: Biochemistry
subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics
subject: Molecular Biology
subject: Evolutionary Biology
subject: 69999 Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Cancer
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Figure S1. Twenty-two GO Slim terms and the interactions between them are represented in this table. The interactions were translated from yeast. Cells are colour-coded according to the number of interactions between two groups of GO terms, where the dark red cells represent more interactions and white cells represent fewer interactions. Figure S2. Schematic showing overlap between this work and the work of Deshpande et al. [9]. The interactions in the two networks generated in this work (HYGIN and the breast cancer specific subnetwork) are compared to the “Complete Set” from the Deshpande et al. research. Figure S3. FBXW7 Orthologs. Two searches of the InParanoid database were conducted to verify that FBXW7 has a strict one-to-one mapping. A) The human genome was searched for the protein MET30 (the yeast protein that is orthologous to FBXW7 in humans). As expected, a single ortholog mapping was identified between Saccharomyces cerevisiae and Homo sapiens. B) The protein CDC4, a synonym for FBXW7, in humans was subsequently searched for in humans. Finding no ortholog in human, InParanoid reported “hits” in other organisms. Results showed that there is no entry for CDC4 in humans, which means that there is no additional FBXW7 ortholog in Saccharomyces cerevisiae. Figure S4. P-values for gene up- and down-regulation of the 15 genes found to be down-regulated in breast cancer. The 15 genes that are the basis for the breast cancer subnetwork were analyzed across 24 different cancer types. The 19 cancer types where the majority of the 15 genes are down-regulated are depicted here. Significant values in blue denote statistically significant lower expression in pooled cancer tissue when compared to pooled normal tissue, values in red denote statistically higher expression in cancer, and NS values denote a non-significant change in gene expression between cancer and normal tissues. All P-values were calculated using the Mann-Whitney U test. Figure S5. Gene expression calculated by RNA-seq by expectation-maximization (log2) for ABCG2, ABHD6, ADHFE1, and AIFM2 for 24 different cancer types. Box plots are colour-coded in pairs based on cancer type where the boxplot on the left is gene expression in cancer and the plot on the right is gene expression in normal tissue. Labels on the x-axis represent the abbreviation of the cancer type, whether the sample represents tumor (T) or normal (N) tissue, and the sample size. Figure S6. Same as description as in Additional file 1: Figure S5, except for AMT, CAT, HAAO, and LARP6. Figure S7. Same as description as in Additional file 1: Figure S5, except for LDHD, MGLL, MSRA, and PEMT. Figure S8. Same as description as in Additional file 1: Figure S5, except for RGN and UPG2. (PDF 5032 kb)