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Life History Shapes Trait Heredity by Accumulation of Loss-of-Function Alleles in Yeast Enikö Zörgö, ,1 Arne Gjuvsland, ,2 Francisco A. Cubillos,3 Edward J. Louis,3 Gianni Liti,3,4 Anders Blomberg,5 Stig W. Omholt,6 and Jonas Warringer*,1,5 1 Abstract A fundamental question in biology is whether variation in organisms primarily emerges as a function of adaptation or as a function of neutral genetic drift. Trait variation in the model organism baker’s yeast follows population bottlenecks rather than environmental boundaries suggesting that it primarily results from genetic drift. Based on the yeast life history, we hypothesized that population-specific loss-of-function mutations emerging in genes recently released from selection is the predominant cause of trait variation within the species. As retention of one functional copy of a gene in diploid yeasts is typically sufficient to maintain completely unperturbed performance, we also conjectured that a crossing of natural yeasts from populations with different loss-of-function mutations would provide a further efficient test bed for this hypothesis. Charting the first species-wide map of trait inheritance in a eukaryotic organism, we found trait heredity to be strongly biased toward diploid hybrid performance exactly mimicking the performance of the best of the parents, as expected given a complete dominance of functional over nonfunctional alleles. Best parent heterosis, partial dominance, and negative nonadditivity were all rare phenomena. Nonadditive inheritance was observed primarily in crosses involving at least one very poor performing parent, most frequently of the West African population, and when molecularly dissected, loss-of-function alleles were identified as the underlying cause. These findings provide support for that population-specific loss-of-function mutations do have a strong impact on genotype–phenotype maps and underscores the role of neutral genetic drift as a driver for trait variation within species. Key words: loss-of-function, neutral variation, genetic drift, life history, yeast, nonadditive heredity, heterosis. Introduction A fundamental question in biology is how an organism’s life history shapes its genotype–phenotype map through accumulation of genetic variation that is adaptive, neutral, or deleterious in a particular ecological context. Baker’s yeast, Saccharomyces cerevisiae, possesses several life history features that together make it an interesting model for elucidation of this question: it is present over an enormous geographic range and a wide variety of habitats (Liti et al. 2009), its population dynamics is characterized by bursts of rapid expansion from small initial population sizes followed by massive cell death (Knop 2006), and it completes on average only one meiotic cycle for every 1,000 mitotic divisions with 99% of these sexual cycles corresponding to self-fertilization (Ruderfer et al. 2006; Tsai et al. 2008). Together, these features suggest that different populations are exposed to highly diverging selective pressures, that there are frequent and narrow population bottlenecks allowing neutral genetic variations to reach high frequencies within populations, and that mutations rarely spread laterally between populations. Based on these considerations and on theoretical predictions of loss-offunction variation emerging rapidly in genes that are dispensable for fitness in a population’s main habitat (Kawecki et al. 1997), we hypothesized that baker’s yeast accumulates population-specific loss-of-function mutations in genes not exposed to local selection (fig. 1A). As data suggest that only a minor portion of yeast genes contributes to fitness in a particular experimental condition (Hillenmeyer et al. 2008), we further hypothesized that such loss-of-function variations may be surprisingly common, causing large differences in fitness traits between populations and shaping the yeast genotype–phenotype map. For simplicity, we will refer to this hypothesis as © The Author 2012. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: [email protected] Mol. Biol. Evol. 29(7):1781–1789. 2012 doi:10.1093/molbev/mss019 Advance Access publication January 20, 2012 1781 Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 Research article Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences (UMB), Ås, Norway 2 Centre for Integrative Genetics (CIGENE), Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences (UMB), Ås, Norway 3 Centre for Genetics and Genomics, Queen’s Medical Centre, University of Nottingham, Nottingham, United Kingdom 4 Institute of Research on Cancer and Ageing of Nice (IRCAN), Centre national de la recherche scientifique (CNRS), Unité Mixte de Recherche 7284, Institut national de la santé et de la recherche médicale (INSERM), Unité 998, University of Nice, Nice, France 5 Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden 6 Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, Oslo, Norway These authors contributed equally to this work. *Corresponding author: E-mail: [email protected]. Associate editor: James McInerney MBE Zörgö et al. · doi:10.1093/molbev/mss019 the local neutrality hypothesis. Retention of one functional copy of a gene in diploid yeast is typically sufficient to maintain an unperturbed performance (Deutschbauer et al. 2005), implying that loss-of-function mutations as a rule are completely masked in diploid heterozygotes resulting from the merging of genomes exposed to different selective pressures. Due to this, we reasoned that a specieswide crossing of natural yeasts isolated from a wide range of populations would provide an efficient test bed for predictions following from the local neutrality hypothesis (fig. 1A). These are that 1) yeast heredity should be strongly biased toward positive nonadditivity, specifically toward diploid hybrid performance equaling the performance of the best parent, 2) best parent heterosis (BPH), the superior performance of first filial generation offspring relative to both parents, should be exceedingly rare, 3) yeast heredity should be strongly influenced by the incidence of low performance alleles and only weakly, or not at all, by overall genetic divergence, and 4) molecular level dissection should reveal loss-of-function alleles as the cause of nonadditively inherited traits. Charting the first species-wide 1782 map of trait inheritance in a eukaryotic organism, we confirm these predictions and thus propose that loss-offunction variation accumulated through neutral genetic drift in genes recently released from selection have a profound impact on the yeast genotype–phenotype map. Materials and Methods Haploid parental yeast isolates S288C, DBVPG6044, DBVPG6765, YPS128, YJM981, Y12, UWOPS03.461.4, 273614N, and L-1528 (supplementary table S2, Supplementary Material online) were mated on rich media in all pairwise combinations as well as to self. From each cross, two individual F1 hybrids were isolated and maintained separately; each was then tested in duplicate. F1 heterozygote hybrids (n 5 4) and their diploid homozygote parents (n 5 4) were clonally propagated by microcultivation in 56 diverse conditions (supplementary table S1, Supplementary Material online) as described (Warringer et al. 2008). In brief, strains were precultured in 350 ll of synthetic defined (SD) medium (0.14% yeast nitrogen base, Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 FIG. 1. A local neutrality model for the emergence of recessive loss-of-function alleles that shape trait heredity in yeast. (A) A local neutrality hypothesis for how the yeast life history promotes emergence of population-specific loss-of-function variation in genes not exposed to selection in local habitats. The hypothesis states that these alleles shape the yeast genotype–phenotype map. However, in experimental crosses between populations’ loss-of-function, variation will be completely masked. (B) Nine haploid yeast isolates (red circles), representing a wide variety of sources and geographic origins (Liti et al. 2009), were crossed in all pairwise combinations as well as to self to produce F1 hybrids as well as diploid parentals. Isolates encompassed all known yeast populations, the Malaysian (MA), West African (WA), North American (NA), European (WE), and Sake (SA) lineages, with three representatives of the European lineage and two genetically mosaic isolates. (C) The proliferative performance of the diploid heterozygous F1 hybrids and their respective diploid homozygous parents was measured by clonal propagation in 56 environments (supplementary table S1, Supplementary Material online). The proliferative rate (population doubling time, h), proliferative efficiency (total population increase, OD), and proliferation lag (adaptation time, h) were extracted from high-density growth curves and log2 transformed. (D) Schema describing the calculation of positive and negative deviations in F1 hybrid performance from the midparent expectation (MPH), as well as positive and negative deviations in F1 performance from both parents (BPH; WPH). Additive inheritance is shown for comparison. See also Box 1. MBE Yeast Heredity · doi:10.1093/molbev/mss019 A 0.3 B C 6 r=0.69 4 0 Negative MPH 0.1 0.08 MPH Frequency 0.2 Positive MPH Frequency 0.1 0.06 2 0 0.04 -2 0.02 r=-0.49 0 -4 0 -2 0 2 4 Heterosis coefficient 1 2 3 4 5 6 Parental trait distance (PD) 0.5% ammonium sulfate, and 1% succinic acid; 2% (w/v) glucose; 0.077% complete supplement mixture [ForMedium], pH set to 5.8 with NaOH or KOH) and incubated for 48 h at 30 °C. Precultures were diluted 35 to an optical density (OD) of 0.03–0.1 in 350 ll of SD medium and cultivated for 72 h in a Bioscreen analyzer C (Growth curves Oy, Finland) with OD measurements at every 20 min using a wideband (450–580 nm) filter. F1 meiotic progeny (recombinants) from all pairwise combinations of the strains DBVPG6765, YPS128, Y12, and DBVPG6044 were obtained and phenotyped as recently described (Cubillos et al. 2011). The fitness variables growth rate (population doubling time, h), growth efficiency (total population density change, OD units), and growth lag (adaptation time, h) were extracted from high-density growth curves (Warringer et al. 2008) and log2 transformed. In order to determine crosses and traits with differences between the three strains (P1, P2, and F1), we performed a simple analysis of variance (ANOVA) with strain as fixed effect (false discovery rate [FDR] 5 1%). Mid-parent heterosis (MPH), BPH, worst parent heterosis (WPH), and heterosis coefficients were calculated as indicated in Box 1. Significance was determined separately for positive and negative MPH, BPH, and WPH (one sided Student’s t-test, FDR 5 1%). Parental genetic distances were obtained from Liti et al. (2009). Detailed experimental procedures are available as Supplementary Material online. Results Yeast Heredity Is Strongly Biased toward Positive Nonadditivity and Complete Dominance To test the local neutrality hypothesis, a species-wide map of trait heredity in baker’s yeast was constructed by mating natural isolates from populations representing 64% of the known single nucleotide polymorphism variation (Liti et al. 2009) and 70% of the corresponding trait variation (Warringer et al. 2011) in all pairwise combinations to produce first filial (F1) generation hybrids (fig. 1B). Diploid F1 hybrids and their homozygotic parents (P1, P2) were propagated clonally in a wide array of ecological niche variations (supplementary table S1, Supplementary Material online), and the reproductive fitness components proliferation rate, lag, and efficiency were extracted (fig. 1C). Based on .24,000 measures of reproductive fitness in specific conditions, the overall frequency of significant positive and negative F1 hybrid deviations from the expected parent mean, referred to as MPH, was determined (fig. 1D, Box 1). Overall, we found nonadditive heredity to be pervasive with 30.2% of all the crosses resulting in positive or negative MPH at a conservative threshold for significance (FDR 5 1%). Consistent with the assumption of frequent loss-of-function mutations in parent lineages, we found a strong bias toward superior F1 hybrid performance relative the mid-parent expectation. On average, F1 hybrids performed 49% better than the mid-parent expectation, corresponding to a more than a 10-fold bias in favor of significant positive versus significant negative MPH (28% vs. 2.2%; fig. 2A, supplementary fig. S1, Supplementary Material online). A pronounced impact of loss-of-function mutations on the yeast genotype–phenotype map also predicted heredity in F1 hybrids to be defined by complete masking effects, that is, in the case of a single polymorphic locus, inheritance should tend toward complete rather than partial dominance or overdominance, for a functionally unperturbed allele. On the positive nonadditive side, complete dominance corresponds to a heterosis coefficient of one (Box 1) (Melchinger 1999). Although experimental noise and bias adds variation, we nevertheless expected the distribution of nonadditively inherited traits to be centered on a heterosis coefficient 5 1. Indeed, excluding cases where there were no trait differences (ANOVA, FDR 5 1%) either between the two parents or between parents and F1 hybrids, we found the distribution of heterosis coefficients to feature a very distinct peak centered on one (fig. 2B). As a direct consequence of this trend toward complete dominance, the degree of MPH in F1 hybrids was proportional to the trait differences between the parents (parental 1783 Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 FIG. 2. Trait heredity in yeast F1 hybrids is strongly biased toward positive MPH and complete dominance. (A) Frequencies of significant (onesided Student’s t-test, FDR 5 1%) positive and negative MPH. (B) Frequency distribution of heterosis coefficients for crosses and traits with significant differences (3,168 of 5,712) between the F1 hybrid and the parents or between parents (ANOVA, FDR 5 1%). White dotted line indicates a heterosis coefficient of one, meaning F1 hybrids performing equally well as the best performing parent. (C) Positive and negative MPH as a function of parental trait distances, PD. Linear correlations (Pearson correlation, r) are displayed. See also supplementary figure S1 (Supplementary Material online). MBE Zörgö et al. · doi:10.1093/molbev/mss019 Thus, F1 performance equals mid-parent performance if the heterosis coefficient 5 0, best parent performance if the heterosis coefficient 5 1, and worst parent performance if the heterosis coefficient 5 1. distance, PD) and increased or decreased linearly with a slope close to k 5 ±0.5 (fig. 2C). These observations are consistent with that yeast heredity in F1 hybrids is largely defined by completely recessive low performance alleles, as expected under the local neutrality hypothesis. BPH Is Exceedingly Rare in Crosses between Yeast Populations Given that relaxations of ancestral selective constraints are population specific, recent loss-of-function mutations affecting a trait should tend to be confined to one individual population (fig. 1A). This translates into a prediction of reciprocal masking of recessive loss-of-function alleles in both parents being a rare phenomenon when different yeast populations are crossed. As such reciprocal masking is expected to be the primary cause of BPH in natural isolates (Charlesworth and Willis 2009), that is, of F1 hybrids performing better than both their parents (fig. 1D, Box 1), we also expected significant BPH to be rare. Comparing the 1784 BPH Frequency 2 0.4 0.2 Parents 0.78 F1 Non-siblings Permutation test Observed mean 0.74 F1 Siblings Parents F1 recombinants 0.82 Non-parents 0.2 F1 hybrids 0.86 Pearson correlation 0.4 -7 -5 -3 -1 1 3 Mean performance of parents Parents WPH BPH Variance 0 E 0.6 0 These classical measures of heterosis depend on measurement scale and cannot be compared directly between crosses. To provide a measure of the degree of nonadditivity, we include the PD and formulate a heterosis coefficient analogous to the degree of dominance measure for a single locus: MPH ; where PD 5 jYP1 þ YP2 j: Heterosis coefficient 5 PD=2 1:4 0.02 0.6 FIG. 3. BPH is rare in F1 hybrids from crosses between yeast populations. (A) Frequencies of significant (one-sided Student’s t-test, FDR 5 1%) BPH and WPH. (B) BPH as a function of the parent trait mean, YPi þ YPj =2 (for all traits with significant BPH (Student’s t-test, FDR 5 1%). Linear correlations (Pearson correlation, r) are displayed. (C) Trait variance was calculated separately for the 9 parents and for the 34 F1 hybrids for each trait. An average over all traits is displayed. (D) Ninety-six F1 recombinants were obtained from all crosses between YPS128, Y12, DBVPG6765, and DBVPG6044, propagated mitotically, and compared with their haploid parents in 23 environments (N 5 2) (Cubillos et al. 2011). Trait variance was calculated separately among parents and among F1 recombinants, for each trait, and averaged over all traits. (E) Correlations (Pearson correlation, r) between (left panel) F1 hybrid and parent/nonparent trait profiles and between (right panel) F1 hybrid and half sibling/nonsibling trait profiles were calculated. Mean correlations are displayed (dots). Box plots show spread in mean values for a permutation test (1,000 permutations) randomizing relationships. Top and bottom of the box represents the 25th and 75th quartile in the test, the band represents test median, and whiskers show the full extent of the permutated data sets. performance of F1 hybrids with that of both their parents, we found significant (FDR 5 1%) BPH for less than 5% of all traits (fig. 3A, supplementary fig. S1, Supplementary Material online). This is far lower than the 30–90% typically observed in F1 crosses between plant breeds (Barth et al. 2003; Flint-Garcia et al. 2009), where adaptive gain-of-function, rather than loss-of-function, alleles have been selected for and shapes trait variation (Troyer 2006; Springer and Stupar 2007). Interestingly, and in contrast to the situation for MPH, these rare instances of BPH showed no correlation (Pearson correlation r 5 0.03) to the trait difference between parents (PD). Instead, the degree of BPH was inversely correlated to the parent trait mean (Pearson correlation r 5 0.51, fig. 3B): the lower the performance of the parents, the higher the BPH. This observation is Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 WPH denotes the hybrid deviation from the worst parent phenotypic value: WPH 5 YF1 YWP ; where YWP 5 minðYP1 ; YP2 Þ: 1:3 4 0.04 0.8 0 D BPH denotes the hybrid deviation from the better parent phenotypic value: BPH 5 YF1 YBP ; where YBP 5 maxðYP1 ; YP2 Þ: 1:2 C 6 0 The starting point for measuring heterosis in a classical F1 cross are the mean phenotypes YP1 , YP2 , and YF1 of the two parental lines P1 and P2 and the diploid F1 hybrid for a quantitative trait Y. MPH denotes the hybrid deviation from mid-parent performance: ðYP1 þ YP2 Þ : 1:1 MPH 5 YF1 Yp; where Yp 5 2 0.06 Trait variance B A BOX 1. Measures of Heterosis Yeast Heredity · doi:10.1093/molbev/mss019 Yeast Heredity Is Defined by the Incidence of Low Performance Alleles and Not Genetic Divergence Hybrid heterozygosity, reflecting the genetic distance between parents, has been suggested to be a good predictor of heredity deviations from the mid-parent expectation (Melchinger 1999). However, the local neutrality hypothesis predicts the incidence of loss-of-function alleles, which in turn is a function of the degree to which ancestral selective pressures have been relaxed, not overall heterozygosity, to be the key determinant of nonadditive heredity. Indeed, although the frequency of significant MPH and BPH varied dramatically between crosses (supplementary fig. S2, Supplementary Material online), no overall correlation between these variables and hybrid heterozygosity was observed (fig. 4A). As expected, however, the three F1 hybrids descending from crosses within the European populations, where parental lines share the vast majority of loss-of-function alleles, had fewer cases of significant MPH than other F1 hybrids (Fisher’s exact test, P 5 3 1013). Furthermore, using the population’s frequency of low performance traits to estimate the prevalence of loss-of-function alleles, we predicted descendants of the West African population, which is low performing for more than 35% (and high performing for less than 0.5%) of reproductive traits to stand out as nonadditive extremes (Warringer et al. 2011). Indeed, the incidence of both significant MPH, excluding cases of BPH, and BPH were highly parent dependent: for both these categories, the West African DBVPG6044, accounting for 31% of MPH traits and 40% of BPH traits, stood out as the most extreme (fig. 4B and C). Loss-of-Function Alleles Constitute the Molecular Basis for Yeast Nonadditive Inheritance In some cases, allele structures underlying trait variation between parents are known, enabling direct molecular interpretation of observed heredity patterns. This is especially true for utilization of the monosaccharide galactose, a relatively rare carbohydrate found in habitats rich in certain plant species, such as sugar beets, natural gum, and succulents. Among natural S. cerevisiae lineages, little variability in the capacity to utilize galactose is observed with the exception for three lineages that feature pronounced defects (Warringer et al. 2011). These defects are all monogenic and caused by lineage-specific loss-of-function mutations in key galactose utilization pathway components: the permease GAL2 (S288C; missense mutation), the galactokinase GAL1 (273614N; gene loss), and the key transcriptional regulator GAL3 (DBVPG6044; nonsense mutation). These mutations are completely environment specific and have no pleiotropic effects, even as regards the utilization of related carbon substrates (Warringer et al. 2011). Thus, they are likely to reflect lineage-specific relaxation of selective pressure for galactose utilization. Here, we found hybrids deriving from unions between any of these three lineages and all other isolates to proliferate as well as the high performing parent on galactose, reflecting the completely recessive nature of the loss-of-function alleles (fig. 5A). Moreover, hybrids between parents carrying different loss-of-function alleles showed perfect proliferation on galactose, and thus extreme BPH, reflecting complete reciprocal masking of the negative alleles. Hence, heredity patterns for galactose utilization were defined by loss-of-function alleles and provided a case-specific molecular verification of the model. 1785 Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 consistent with the rare cases of BPH being due to reciprocal masking of different loss-of-function mutations affecting a trait, as expected if parental populations, with little gene flow between them, have experienced independent relaxed selection for this trait. Taken together, our findings suggest that reciprocal masking of loss-of-function mutations is a primary cause of BPH in yeast but that such events are rare, supporting the local neutrality hypothesis. Significant WPH (fig. 1D, Box 1), denoting cases where F1 hybrids perform significantly (FDR 5 1%) worse than both parents, was extremely rare. Only 0.1% of significant WPH could be detected (fig. 3A, supplementary fig. S1, Supplementary Material online), consistent with dominant lossof-function alleles being rare and the presence of such alleles for the same trait in both parents exceptional. The low frequency of both positive and negative transgression has two direct implications for our understanding of natural yeast ecology. First, it means that hybridization across population boundaries results in F1 hybrid populations with traits that overall are less extreme than the parent populations’. In our experimental setup, the reduction in the width of phenotype distributions in hybrid populations was in fact dramatic: trait variance among yeast F1 hybrids was 42% lower than among the parents (fig. 3C). This loss of phenotypic width in F1 hybrid populations persisted also after meiosis, as evidenced by sporulation of a subset of these F1 hybrids, and phenotyping 92 germinated recombinants resulting from each cross. We found trait variance among the meiotically recombined F1 haploids to be 31% lower than among their corresponding haploid parents (fig. 3D). Hence, although F1 hybrid and F1 recombinant phenotypic extremes do emerge at a low frequency in crosses between populations (Cubillos et al. 2011), such outcrossing generally produces offspring less exceptional and consequently less specialized than the parents. Second, the low frequency of transgressive effects implies that F1 hybrids should tend to resemble their parents. Indeed, comparing the trait profiles of all F1 hybrids with those of their respective parents, we found F1 hybrids to be 9% more similar to their parents than to nonparents from the parent generation, well outside the confidence limits of a Monte Carlo permutation test (fig. 3E). Furthermore, F1 hybrids were 5% more similar to their respective half-siblings, that is, F1 hybrids with which they share one parent, than to nonsiblings. This overall resemblance between parents and offspring as regards fitness traits is a nontrivial observation; although the inheritance traits between generations has been considered essential since Aristotle (Mayr 1982), such resemblance between parents and offspring is not an obvious evolutionary necessity in a species where outcrossing and hybridization across population boundaries are very infrequent, as in yeast. MBE MBE Zörgö et al. · doi:10.1093/molbev/mss019 A B 6 UWOPS03.461.4 UWOPS03.461.4 273614N 273614N DBVPG6765 Y12 YJM981 S288C S288C YPS128 YPS128 YJM981 Y12 L-1528 L-1528 0.4 DBVPG6765 0.3 DBVPG6044 0.2 DBVPG6044 0.1 0 MPH Frequency of BPH 0.4 0.3 0.2 0.1 0 4 2 C Frequency of positive MPH 0 -2 0.00734, 0.00749 0.00671, 0.00734 0.00579, 0.00671 Parent genetic divergence (variations/nucleotide site) FIG. 4. Yeast trait heredity is strongly influenced by the incidence of low performance alleles in parents but not by overall genetic divergence. (A) Box plot of F1 hybrid MPH as a function of genetic divergence between parents. F1 hybrids were divided into equally sized bins depending on degree of parent genetic similarity (Liti et al. 2009). Top and bottom of the box represents the 25th and 75th quartile, the band represents the bin median, whiskers extend to 1.5 times the interquartile range, and dots correspond to outliers not contained within these boundaries. (B–C) Frequency of significant (Student’s t-test, FDR 5 1%) positive MPH, excluding cases of significant BPH, and BPH in F1 hybrids descending from a specific parental lineage. (B) Positive MPH, excluding cases of significant BPH. (C) BPH. See also supplementary figure S2 (Supplementary Material online). In contrast to galactose, heat tolerance is a highly variable among natural S. cerevisiae isolates with the West African DBVPG6044 featuring the gravest defects (Warringer et al. 2011). This polygenic deficiency is due to the combined effect of multiple loss-of-function alleles in the RAS/cAMP pathway, in conjunction with a low performance quantitative trait locus (QTL) in the subtelomeric region of chromosome XII (Parts et al. 2011). In hybrids descending from unions between the West African DBVPG6044 and the heat tolerant strains that do not contain these loss-of-function mutations, heat proliferation mimic that of the well-performing parents (fig. 5B). Hence, the multiple loss-of-function mutations are completely masked. In contrast, when DBVPG6044 was crossed to other isolates also unable to tolerate heat, extreme BPH emerged, and the F1 hybrid consistently showed unperturbed heat performance, strongly suggesting reciprocal masking effects. For both galactose utilization and heat tolerance, the proliferative rate and efficiency showed identical heredity patterns. This agreement reflected a strong overall trend: the degree of nonadditive inheritance is highly correlated (Pearson correlation, r 5 0.70) for the rate and efficiency of mitotic proliferation (fig. 5C). This is consistent with the observation that these two variables covary over natural isolates in a range of environments (Warringer et al. 2011) and refutes assumptions of a general trade-off between these key fitness components (Novak et al. 2006). However, the hereditary coupling of rate and efficiency is not absolute as evidenced by the inheritance of melibiose, a rare plant disaccharide, utilization. Although the 1786 ability to utilize melibiose is prevalent among others yeasts, only the Malaysian S. cerevisiae population has retained this trait. The loss of melibiose utilization associates with complete loss of melibiase (MEL1), catalyzing the conversion of melibiose to galactose and glucose (Warringer et al. 2011). Whereas F1 hybrids descending from the Malaysian UWOPS03461.4 and strains lacking MEL1 showed complete dominance for the efficiency of melibiose utilization, the proliferative rate when using melibiose as carbon source was inherited additively (fig. 5D, supplementary fig. S3, Supplementary Material online). This hereditary uncoupling of the rate and efficiency of utilization of a carbon source suggests that half the normal number of protein molecules of a proliferation limiting enzyme, in this case melibiase, is generally enough to maintain the efficiency, but not the rate, of the metabolic machinery. Discussion Loss-of-function alleles can emerge either through the occurrence of pleiotropy and selection for antagonistic traits (Elena and Sanjuan 2003) or due to a combination of genetic drift and relaxation of ancestral selective pressures (Kawecki et al. 1997). We hypothesized that the peculiar yeast life history should promote genetic drift in those parts of the genome that are not exposed to selection in each population’s main habitat, resulting in a high incidence of population-specific loss-of-function alleles. Although locally neutral, these variations are deleterious in a broader ecological context and should impact profoundly on the yeast genotype–phenotype Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 0.00408, 0.00579 Bin range 0.000915, 0.00408 -4 Yeast Heredity · doi:10.1093/molbev/mss019 MBE map. Several observations support such a hypothesis. First, the enormous genetic variability observed between species and populations in the yeast clade (Kellis et al. 2003; Liti et al. 2009) is widely considered to reflect that neutral genetic drift is the main driving force behind yeast genome evolution (Dujon 2010). This genetic variability frequently takes the form of nonsense and frameshift mutations impairing protein functionality (Zia and Moses 2011). Extensive variability in fitness traits have also been observed between natural S. cerevisiae populations (Warringer et al. 2011). Most of this variability corresponds to low performance of an individual population in a particular condition, implying the action of population-specific loss-of-function alleles. In yeast species such as Schizosaccharomyces pombe, which is found in a much more restricted set of habitats, trait variation is much lower (Brown et al. 2011). Finally, as much as 7– 12% of nonsynonymous polymorphisms within baker’s yeast occur in sites where little variability is observed over longer evolutionary time scales (Doniger et al. 2008). Hence, much of recently acquired genetic variation has been exposed to purifying selection in ancestral populations, directly suggesting population-specific relaxation of selective constraints. The distribution patterns of polymorphisms in conserved sites remarkably well predicts yeast phenotype patterns, strongly supporting that they are the main cause of phenotypic variation within baker’s yeast (Jelier et al. 2011). We also conjectured that loss-of-function mutations should be reflected in a similar pronounced impact on yeast trait heredity. Gene knockouts mimic loss-of-function mutations (Hillenmeyer et al. 2008); hence, if trait heredity in natural yeast populations is indeed shaped by loss-offunction variation, we expect it to adhere closely to heredity patterns emerging from crosses between single gene knockouts and unperturbed parents which show that retention of one functional copy of a gene is enough to maintain a completely unperturbed fitness (Deutschbauer et al. 2005; Delneri et al. 2008; Springer et al. 2010). Hence, we predicted trait heredity in crosses between natural yeast populations to be heavily biased toward positive nonadditivity and complete rather than partial dominance or BPH. Charting the first species-wide map of heredity of natural traits in any organism, we found these and other predictions based on loss-of-function alleles to be confirmed. Furthermore, in cases for which the molecular basis of traits could be dissected, like in the case of galactose utilization and heat tolerance (fig. 5), loss-of-function alleles indeed emerged as determinants of this complete dominance. The obtained results were thus fully consistent with frequent loss-of-function alleles shaping the overall pattern of yeast heredity. However, the evaluated model is a model of gene action at individual loci, whereas the species-wide data necessarily reflect phenotypes for which the genetic basis is poorly understood. Hence, it is fair to ask whether the observed trait heredity patterns could be caused by 1787 Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 FIG. 5. Yeast traits defined by loss-of-function alleles. (A) Proliferative efficiency using galactose as carbon source in crosses between the galactose low performing strains DBVPG6044 (GAL3 nonsense mutation), 273614N (GAL1 complete loss), and S288C (GAL2 missense mutation) and the galactose high performing strains L-1528, UWOPS03.461.4, and DBVPG6765, which all lack deleterious GAL pathway alleles. Bars represent the performance of the parental strains (blue and green) and the F1 hybrid (red). N 5 4, error bars 5 standard error. (B) Proliferative efficiency in high temperatures (40 °C) in crosses involving the heat sensitive DBVPG6044, carrying multiple deleterious alleles in the RAS/cAMP pathway. Crosses to the heat tolerant YPS128, Y12, and S288C as well as to the heat sensitive UWOPS03.461.04, 273614N, and YJM981 are displayed. Bars represent the performance of the parental strains (blue and green) and the F1 hybrid (red). N 5 4, error bars 5 standard error. (C) Correlation between MPH for proliferative rate and MPH for proliferative efficiency, over all traits. Red line 5 linear regression (Pearson correlation, r 5 0.70). (D) Heredity of rate and efficiency of proliferation using melibiose as a carbon source in a cross between the Malaysian UWOPS03.461.4 and the European DBVPG6765 (N 5 4, error bars 5 standard error). See also supplementary figure S3, Supplementary Material online. MBE Zörgö et al. · doi:10.1093/molbev/mss019 1788 populations will be necessary to illuminate the question of whether the here reported impact of loss-of-function variation prevails in other branches of the tree-of-life and contributes to ecological specialization. Supplementary Material Supplementary figures S1–S3, table S1, and Materials and Methods are available at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/). Acknowledgments G.L. was supported by Centre national de la recherche scientifique (CNRS), Programme Atip–Avenir, and the Association pour la Recherche sur le Cancer (ARC). J.W. was supported by the Royal Swedish Academy of Sciences and the Carl Trygger Foundation. References Barth S, Busimi AK, Friedrich Utz H, Melchinger AE. 2003. Heterosis for biomass yield and related traits in five hybrids of Arabidopsis thaliana L. Heynh. Heredity 91:36–42. Begun DJ, Holloway AK, Stevens K, et al. (13 co-authors). 2007. Population genomics: whole-genome analysis of polymorphism and divergence in Drosophila simulans. PLoS Biol. 5:e310. Brown WRA, Liti G, Rosa C, et al. (17 co-authors). 2011. 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Downloaded from http://mbe.oxfordjournals.org/ at Pennsylvania State University on May 12, 2016 gain-of-function mutations and positive selection rather than by loss-of-function mutations and neutral drift. Unfortunately, the impact of adaptive gain-of-function mutations on traits and trait heredity is much less understood than the impact of loss-of-function mutations due to the difficulty of mimicking such variation using reverse genetics. Hence, no empirical framework within which such a model could be contemplated currently exists. Nevertheless, several lines of evidence suggest that a model where gain-of-function adaptive variation shapes the overall structure of the yeast genotype–phenotype map is improbable. First, variation in yeast traits tends to follow population boundaries with no or only marginal influence of the source environments from which strains were isolated (Warringer et al. 2011). This strongly suggests that the trait-defining genetic variation results from population-specific neutral drift rather than from adaptation to these source environments. Second, neutrality tests have consistently failed to detect any evidence for recent adaptive alleles in a wide variety of yeast genomes (Kellis et al. 2003; Gu et al. 2005; Doniger et al. 2008; Liti et al. 2009). These failures contrast sharply against the 54%, 56%, and 57% of positively selected amino acid substitutions detected in fruit fly (Begun et al. 2007), enteric bacteria (Charlesworth and Eyre-Walker 2006), and mouse (Halligan et al. 2010). Thus, although estimates of a complete absence of adaptive variation in yeast is likely to be overly conservative, as evidenced by a recent report demonstrating the existence of coevolved cis and trans expression QTLs in yeast (Fraser et al. 2010), it seems clear that adaptive gain-offunction mutations historically are much less common than deleterious variation. Thus, even if it is not yet possible to stringently reject a model where positively selected gainof-function mutations form the basis for recently emerged yeast trait variation, we argue that such a model is implausible. Recent methodological advances (Ehrenreich et al. 2010; Parts et al. 2011), allowing direct identification of causative alleles, promise a future species-wide genetic dissection of natural yeast traits and may allow a definite verification of to what degree loss-of-function variation indeed shapes the yeast genotype–phenotype map. The bias toward self-fertilization and asexual vegetative proliferation, together with enormous within-species variability in habitat composition, sets yeasts apart from many higher organisms. 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