<i>In vivo</i> capture of RNPs associated with <i>GPD1</i> and <i>STL1</i> mRNAs under osmotic stress.

<p>A) Schematic outline of the immunoprecipitation–mass spectrometry procedure. After growing the cells to exponential phase, the expression of MS2-CP-GFP fusion protein was induced by methionine depletion and osmotic stress was applied by addition of KCl to 0.6 M. Proteins were then directly cross-linked to mRNAs <i>in vivo</i> by formaldehyde addition, after which RNPs-mRNA-MS2L interacting with the MS2-CP-GFP fusion protein were purified using GFP-Trap beads. After elution from the beads and cross-linking reversal, the sample was divided and RNA and proteins extracted separately. The proteins were separated by SDS-PAGE and composition was analyzed by LC-MS/MS. B, C) Example of RNP capture experiment using an <i>STL1-MS2L</i> mRNA containing strain. B) Protein separation by SDS-PAGE before digestion and mass spectrometry. C) <i>STL1-MS2L</i> mRNA detection by RT-PCR in input, unbound (UB) and pull-down (PD) samples. A pair of primers complementary to <i>STL1</i> and flanking the MS2 loops insertion region was used in upper panel. The MS2L integration was detected by a 1.0 kb amplification product. As a control of the integrity of the mRNA, a pair of primers within the ORF was used in the bottom panel.</p

Detection of the mRNAs in the isolated RNP fractions by qPCR.

<p>Detection of the mRNAs in the isolated RNP fractions by qPCR.</p

<i>pat1</i> or <i>lsm1</i> deletion yields overaccumulation of ribosomes in the 5’-UTR region of the mRNAs in both control and osmotic stress conditions.

<p>5P-Seq was performed in <i>pat1</i> and <i>lsm1</i> mutants and wt strains before (control) and 30 min after addition of 0.6 M KCl (osmotic stress). A) Metagene analysis displaying the abundance of 5’P intermediates in reads per million (rpm) in relation to the ORF start (left panels) and stop codons (right panels), with (bottom panels) and without stress (upper panels). The graphics include the representation of the start region division in three windows of 45 nt each, upstream of the start codon (uS), downstream of the start codon including the ribosome paused at the start (dS) and, downstream of dS region (ddS); and the stop region in two windows, upstream of the stop codon including the ribosome paused at the stop (uE), and downstream of the stop (dE). B) Scatter plot representation and of log₂ ratios between window areas around the start codon (uSvsdS) or the stop codon (uEvsdE) without (upper panels) and with osmotic stress (bottom panels). Only genes with at least 20 5P-Seq reads in the defined regions were considered for the analyses. Scatter plots display values for <i>pat1</i> mutant (Y axis) vs wt strains (X axis). Corresponding <i>lsm1</i> mutant plots are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007563#pgen.1007563.s007" target="_blank">S7B and S7C Fig</a>) Cumulative representation of log₂ ratios for all the transcripts sequenced (ALL) and for “osmotic-stress induced” gene subset defined in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007563#pgen.1007563.s013" target="_blank">S6 Table</a> (OSR). Increments of the cumulative distribution medians between wt and <i>pat1</i> and <i>lsm1</i> mutants, before and after 30 min of osmotic stress (0.6 M KCl), are displayed under each graph.</p

Deletion of <i>PAT1</i> dysregulates synthesis of highly induced proteins under osmotic stress.

<p>The accumulation of specific GFP-tagged proteins was monitored in <i>pat1</i> (red line) mutants and wt (blue line) in control conditions (without stress) and under osmotic stress by addition of KCl (mild, 0.3 M; medium, 0.6 M; high, 1 M). Protein accumulation was expressed as the increment of fluorescence units relative to 5 min after addition of KCl. Green fluorescence emission (520 nm) and OD₆₀₀ was measured from the same well every 4 min for a period of 140 min in an Omega Polarstar fluorescence plate reader. To normalize the data, the OD₆₀₀ was used to remove the effect of growth differences between strains, and <i>pat1</i> and wt with no GFP-tagged protein growing in parallel were used to subtract the background fluorescence. Average and SE from at least three biological replicates are shown.</p

Proteins with enriched binding to the <i>STL1</i> and <i>GPD1</i> mRNAs identified by MS.

<p>Proteins with enriched binding to the <i>STL1</i> and <i>GPD1</i> mRNAs identified by MS.</p

Data File S9. High and low interaction degree genes

This file lists the negative and positive interaction degree associated with every nonessential deletion (sn#), essential TS (tsq#), and DAmP (damp#) query mutant strain screened against the DMA (“query degree X DMA” tab) and/or TSA (“query degree X TSA” tab). A subset of strains were found to carry a second, spontaneous suppressor mutation that affected fitness of the query mutant strain. Strains carrying a suppressor mutation mapped through SGA analysis are indicated (“-supp”). Query mutants comprising the 20% highest and lowest degree groups of strains are indicated. Furthermore, a “Co-batch signal” rank is provided for every query (see “Co-batch filtering of query mutant strains”). Low ranks correspond to evidence for lingering batch effects. Another column, “ Gene with correlated GI profiles that are co-annotated with the query gene (%)", provides the percent of correlated gene pairs that are co-annotated to the particular query. A low negative interaction degree (e.g. 20% lowest negative interaction degree) coupled with a low co-batch rank (e.g. < ~0.2) and a low fraction of correlated pairs that share a similar functional annotation with a given query strain (e.g. < ~0.15) may be indicative of a low confidence screen. However, these criteria should be considered as loose indicators and not definitive metrics of screen quality and thus, should not be used as strict filters on the global interaction dataset. Another list (“Queries removed - batch effects” tab) indicates ~300 query strains that exhibited severe systematic batch effects and thus were removed from the indicated data set. Finally, two additional tabs provide the negative and positive interaction degree associated with every nonessential (“nonessential array degree” tab) and essential (“essential array degree” tab) array mutant, respectively

Data File S6. Genetic profile similarity-based hierarchy analysis

The first tab (“Gene to hierarchy cluster mapping”) lists the clusters identified at each level of the genetic interaction-based hierarchy and the deletion and TS allele array mutants assigned to each cluster. Examples of clusters described in the main text are highlighted. The subsequent 9 tabs indicate enrichment of clusters resolved at the specified profile similarity range for specific cell compartments (Cyclops_enrich), biological processes (GO BP_enrich), protein complexes (complex_enrich) and KEGG pathways (KEGG_enrich). The final tab in the file indicates the clusters used to map the functional distribution of negative and positive interactions shown in Fig. 5D

Data File S15. Protein complex interaction enrichment and bias

This file indicates fold enrichment and biases in positive vs. negative interaction frequency for protein complexes and is described in detail above (see ìAnalysis of protein complexes exhibiting a positive interaction enrichment biasî). Rows highlighted in yellow indicate protein complexes that show > 1.5X enrichment for positive interactions (ìE_fold_pos) stronger enrichment for positive versus negative interactions when screened against the essential TSA. The file consists of the following columns: (A) Protein complex name (B) Number of complex member-encoding query genes screened against the DMA (ìqueries_vs_DMAî). (C) Number of complex member-encoding query genes screened against the TSA (ìqueries_vs_TSAî). (D) Nonessential-negative GI fold enrichment (ìN_fold_negî): negative interaction fold enrichment for a complex of interest with nonessential genes not in the complex. (E) Essential-negative GI fold enrichment (ìE_fold_negî): negative interaction fold enrichment for a complex of interest with essential genes not in the complex. (F) Nonessential-positive GI fold enrichment (ìN_fold_posî): positive interaction fold enrichment for a complex of interest with nonessential genes not in the complex. (G) Essential-positive GI fold enrichment (ìE_fold_posî): positive interaction fold enrichment for a complex of interest with essential genes not in the complex. Complexes with a positive GI enrichment > 1.5X are highlighted in yellow. These values were used to generate Fig. 8C. (H) Positive GI bias with essential genes (ìposGI_bias_with_Eî): the relative positive:negative enrichment ratio of essential to nonessential genes for the complex of interest (calculated as [D/E]/[F/G]). Complexes with a positive GI enrichment > 1 and a positive GI bias > 1.5 are highlighted in yellow. These values were used to generate Fig. 8D. (I) Positive GI bias with nonessential genes (posGI_bias_with_Nî): the relative positive:negative enrichment ratio of nonessential to essential genes for the complex of interest (calculated as [F/G]/[D/E])

Data File S10. Correlation analysis of query strain GI degree

As a complement to analysis of array strains (fig. S11-S12), GI degrees were calculated for query strains by counting negative interactions (tab 1, interactions with DMA strains; tab 2, interactions with TSA strains) and by counting positive interactions (tab 3, interactions with DMA strains; tab 4, interactions with TSA strains). Essential and nonessential queries were analyzed separately and results are labeled by grouped column headers. Wilcoxon rank-sum tests compared the GI degree in paired gene sets defined by absence and presence of each binary feature tested (top table). If the P-value is significant (< 0.05), the “Test result” column describes the degree of the set of genes for which the listed binary feature is true (compared to the set for which the feature is false). Tests were not performed, indicated by “N/A”, if data were present for fewer than 50 strains; strains with missing data were excluded from the tests. Pearson’s correlation (column labeled “r”) was used to measure associations between GI degree and features that are continuous or counts (bottom table). Uncorrected P-values are shown. The features examined in this analysis are described above (see Methods section entitled, “ Genetic interaction degree and frequency analysis”). Given that analysis of different features required using different statistical tests and some features are not expected to be independent of each other, no multiple hypotheses correction procedures were used. We do note that 31 gene features were tested

Data File S8. Mass spectrometric evidence for Ipa1 interactions

This file lists proteins identified with high confidence as specific physical interactors with strains expressing Ipa1-GFP from its endogenous locus or Ipa1-HA from a galactose-inducible plasmid