Genetic mapping of MAPK-mediated complex traits Across S. cerevisiae.

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants

Data from: Genetic mapping of MAPK-mediated complex traits across S. cerevisiae

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants

Analyses of QTL identified in the round-robin cross.

<p>(<b>A</b>) LOD score distribution of QTL detected in both of the MATa and MATα selections experiments compared to that of QTL only found in either of the two experiments. The majority of QTL that miss replication have LOD scores close to the threshold used to call QTL. (<b>B</b>) Histogram of the number of crosses per QTL group. Theoretically, assuming purely additive effects and perfect detection, each QTL should be observed in at least two crosses. (<b>C</b>) LOD scores of the QTL belonging to different classes of grouped QTL. Identification of QTL in only one cross is only partially explained by the lower LOD scores of this class of QTL (pearson correlation 0.417, <i>p</i> = 2.6×10⁻⁶).</p

Design of round-robin cross to map salt and caffeine resistance.

<p>(<b>A</b>) Phenotyping of 65 diverse strains. Growth under the indicated condition (YPD plus 1 M sodium chloride (NaCl) or 15 mM caffeine) was adjusted for growth under the permissive YPD condition (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004913#pgen.1004913.s005" target="_blank">S1 Table</a>). We picked strains (filled symbols) that are representative of the genetic and phenotypic diversity and crossed them according to a round-robin design (<b>B</b>). Strains were crossed independent of phenotype and genetic relationship. Strain name colors indicate mating type (Green  =  MATa, Red  =  MATα).</p

Leveraging the Round Robin design to identify causative variants.

<p>(<b>A</b>) A QTL on chromsome 15 affects salt and caffeine resistance in crosses 7 and 8 (with smaller effects in other crosses). The CLIB219 is shared between the two crosses and in both cases it contributes the allele is selected against, suggesting that the causative variant is private to CLIB219. (<b>B</b>) We determined the association of coding variants within this QTL interval with the observed pattern of LOD scores. The highest association scores were exhibited by four variants private to CLIB219; one a frame-shift mutation in <i>WHI2</i>. (<b>C</b>) Allele replacements of <i>WHI2</i> in the CLIB219 strain background. The CLIB219-specific frame shift mutation resulted in decreased growth in the presence of both high salt and caffeine. (<b>D</b>) Identification of a quantitative trait nucleotide (QTN) within the caffeine resistance QTL on chromosome 10. The QTL was identified in eight crosses and is multi-allelic as specific alleles were beneficial or deleterious depending on a particular cross. (<b>E</b>) Measuring the association of variants and LOD scores confirmed that no single variant could explain the observed pattern of QTL and indicated a <i>TOR1</i> SNP (3875 G -> A) as a QTN (red circle). (<b>F</b>) Introduction of the <i>TOR1³⁸⁷⁵</i>^{<b><i>A</i></b>} variant into two strain backgrounds, YJM269 and 273614x, reduced resistance to caffeine. For each allele replacements two independent transformants are shown.</p

Fluorescent markers for the isolation of recombinant haploids.

<p>(<b>A</b>) Utilizing fluorescent mating type markers to generate large mapping populations. The fluorophores mCitrine and mCherry were placed under the control of the MATa-specific <i>STE2</i> and the MATα-specific <i>STE3</i> promoters, respectively, and combined into a single construct. Introduction of this construct into MATa cells results in green fluorescence, while MATα cells exhibit red fluorescence. Neither of the two reporters is active in diploid or tetrad cells, but after germination the markers are expressed and enable the isolation of MATa and MATα populations of recombinant haploids. (<b>B–E</b>) Validation of the fluoresent markers. Flow cytometry of (<b>B</b>) MATa cells and (<b>C</b>) MATα cells that carried a plasmid with the combined fluorescent mating type markers. MATa cells were green fluorescent, while MATα cells presented with red fluorescence. (<b>D</b>) A culture of BY/RM recombinant haploids with the mating type marker plasmid as assessed during FACS. Green MATa and red MATα cells were isolated based on their fluorescence. Gates shown represent approximate gates used during cell sorting. (<b>E</b>) The allele frequency spectrum across the genome within the isolated MATa and MATα cell populations was determined by sequencing. On chromosome three MATa populations were highly enriched for the MATa allele, while MATα populations were highly enriched for the MATα allele. Other large allele frequency skews correspond to previously identified BY/RM growth QTL.</p

Treusch et al. Data

The data archive contains VCF files derived from the sequenced X-QTL samples, allele frequency measurements based on the VCF files and the R scripts used to process the allele frequency measurements to map and plot QTL

Mating type dependent QTL.

<p>Comparison of allele frequencies within MATa and MATα populations revealed loci that affect growth in a mating type dependent manner. The QTL on chromosome 8 encompasses <i>GPA1</i>, a negative regulator of the mating pathway that affects fitness in different strain backgrounds <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004913#pgen.1004913-Lang1" target="_blank">[50]</a>. Chromosome 3 was omitted as it contains the mating type locus itself (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004913#pgen.1004913.s012" target="_blank">S8 Table</a> for all mating type dependent QTL identified).</p

Genetic architectures of resistance identified in the round-robin crosses.

<p>Genome-wide LOD scores for (<b>A</b>) sodium chloride and (<b>B</b>) caffeine experiments are plotted jointly for the 12 Round Robin crosses to illustrate the how QTL are shared among the different crosses (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004913#pgen.1004913.s004" target="_blank">S4 Fig</a>. for individual plots). The large effects of the multi allelic <i>ENA</i> locus on salt and <i>TOR1</i> on caffeine resistance are readily apparent. At each position the minimum of replicate selections is plotted for each cross. Tick marks on the upper axis indicate peak positions of QTL identified (QTL are listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004913#pgen.1004913.s008" target="_blank">S4 Table</a>).</p