Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis

A combination of yeast genetics, synthetic genetic array analysis, and high-throughput screening reveals that sumoylation of Mcm21p promotes disassembly of the mitotic spindle

Data from: Systematic analysis of complex genetic interactions

To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship

Legislative Documents

Also, variously referred to as: Senate bills; Senate documents; Senate legislative documents; legislative documents; and General Court documents

AdditionalDataS5

This file contains the complete list of yeast strains present on the diagnostic array, which was used for genetic interaction screens in this study

AdditionalDataS6

This file contains the trigenic interactions list of MDY2-MTC1 and digenic interaction list of MDY2 and MTC1 corresponding to Fig. 3. The ‘Tetrad Analysis’ tab contains confirmations results obtained from tetrad analysis: SS is synthetic sick, SL is synthetic lethal. The ‘Genetic interactions’ tab contains columns that are annotated with ‘CellMap’ since they contain genetic interactions from (7) downloaded from theCellMap.org (26) as well as scores derived in this study

Data File S3. Genetic interaction profile similarity matrices

Matrix files containing genetic interaction profile similarity values (as measured by Pearson correlation) for every pair of mutant strains in the dataset. Similarity values were computed for essential (ExE), non-essential (NxN) and the global similarity network derived from a combined set of all genetic interactions (ExE, NxN, ExN) as described above (see "Constructing genetic interaction profile similarity networks"). Each matrix contains 2 sets of row and column headers, providing a unique allele name for every mutant strain (row & column header #1) as well as a systematic ORF name (row & column header #2)

Data File S4. GO bioprocess functions predicted by the nonessential and essential similarity networks using a K-nearest neighbor approach

This file reports the performance of gene function prediction for non-essential or essential genes based on genetic interaction profiles. For both classes of genes (either nonessential or essential), the performance of a KNN classifier is reported as the Precision at 25% Recall based on interactions derived from TS queries (PR_TSQ) or nonessential deletion queries (PR25_SN). Although analyses were performed using complete genetic interaction profiles (e.g. negative and positive genetic interactions), similar prediction performance was obtained using genetic interaction profiles based on negative interactions alone