Life History Shapes Trait Heredity by Accumulation ofLoss-of-Function Alleles in Yeast

Eniko Zorgo,�,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

1Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences(UMB), As, Norway2Centre for Integrative Genetics (CIGENE), Department of Mathematical Sciences and Technology, Norwegian University of LifeSciences (UMB), As, Norway3Centre for Genetics and Genomics, Queen’s Medical Centre, University of Nottingham, Nottingham, United Kingdom4Institute of Research on Cancer and Ageing of Nice (IRCAN), Centre national de la recherche scientifique (CNRS), Unite Mixte deRecherche 7284, Institut national de la sante et de la recherche medicale (INSERM), Unite 998, University of Nice, Nice, France5Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden6Centre 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: jonas.Warringer@cmb.gu.se.

Associate editor: James McInerney

Abstract

A fundamental question in biology is whether variation in organisms primarily emerges as a function of adaptation or asa function of neutral genetic drift. Trait variation in the model organism baker’s yeast follows population bottlenecksrather 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 isthe predominant cause of trait variation within the species. As retention of one functional copy of a gene in diploid yeastsis typically sufficient to maintain completely unperturbed performance, we also conjectured that a crossing of naturalyeasts from populations with different loss-of-function mutations would provide a further efficient test bed for thishypothesis. Charting the first species-wide map of trait inheritance in a eukaryotic organism, we found trait heredity to bestrongly biased toward diploid hybrid performance exactly mimicking the performance of the best of the parents, asexpected 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 involvingat 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-specificloss-of-function mutations do have a strong impact on genotype–phenotype maps and underscores the role of neutralgenetic drift as a driver for trait variation within species.

Key words: loss-of-function, neutral variation, genetic drift, life history, yeast, nonadditive heredity, heterosis.

IntroductionA fundamental question in biology is how an organism’s lifehistory shapes its genotype–phenotype map throughaccumulation of genetic variation that is adaptive, neutral,or deleterious in a particular ecological context. Baker’syeast, Saccharomyces cerevisiae, possesses several life his-tory features that together make it an interesting modelfor elucidation of this question: it is present over an enor-mous geographic range and a wide variety of habitats (Litiet al. 2009), its population dynamics is characterized bybursts of rapid expansion from small initial population sizesfollowed by massive cell death (Knop 2006), and it com-pletes on average only one meiotic cycle for every 1,000mitotic divisions with 99% of these sexual cycles cor-responding to self-fertilization (Ruderfer et al. 2006;Tsai et al. 2008). Together, these features suggest that dif-ferent populations are exposed to highly diverging selective

pressures, that there are frequent and narrow populationbottlenecks allowing neutral genetic variations to reachhigh frequencies within populations, and that mutationsrarely spread laterally between populations. Based on theseconsiderations and on theoretical predictions of loss-of-function variation emerging rapidly in genes that aredispensable for fitness in a population’s main habitat(Kawecki et al. 1997), we hypothesized that baker’s yeastaccumulates population-specific loss-of-function muta-tions in genes not exposed to local selection (fig. 1A).As data suggest that only a minor portion of yeast genescontributes to fitness in a particular experimental condi-tion (Hillenmeyer et al. 2008), we further hypothesized thatsuch loss-of-function variations may be surprisingly com-mon, causing large differences in fitness traits betweenpopulations and shaping the yeast genotype–phenotypemap. For simplicity, we will refer to this hypothesis as

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Research

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the local neutrality hypothesis. Retention of one functionalcopy of a gene in diploid yeast is typically sufficient tomaintain an unperturbed performance (Deutschbaueret al. 2005), implying that loss-of-function mutations asa rule are completely masked in diploid heterozygotesresulting from the merging of genomes exposed to differentselective pressures. Due to this, we reasoned that a species-wide crossing of natural yeasts isolated from a wide range ofpopulations would provide an efficient test bed for predic-tions following from the local neutrality hypothesis (fig.1A). These are that 1) yeast heredity should be stronglybiased toward positive nonadditivity, specifically towarddiploid hybrid performance equaling the performance ofthe best parent, 2) best parent heterosis (BPH), the superiorperformance of first filial generation offspring relative toboth parents, should be exceedingly rare, 3) yeast heredityshould be strongly influenced by the incidence of low per-formance alleles and only weakly, or not at all, by overallgenetic divergence, and 4) molecular level dissectionshould reveal loss-of-function alleles as the cause of non-additively inherited traits. Charting the first species-wide

map of trait inheritance in a eukaryotic organism, weconfirm these predictions and thus propose that loss-of-function variation accumulated through neutral geneticdrift in genes recently released from selection have aprofound impact on the yeast genotype–phenotype map.

Materials and MethodsHaploid parental yeast isolates S288C, DBVPG6044,DBVPG6765, YPS128, YJM981, Y12, UWOPS03.461.4,273614N, and L-1528 (supplementary table S2, Supplemen-tary Material online) were mated on rich media in allpairwise combinations as well as to self. From each cross,two individual F1 hybrids were isolated and maintainedseparately; each was then tested in duplicate. F1 heterozy-gote hybrids (n5 4) and their diploid homozygote parents(n5 4) were clonally propagated by microcultivation in 56diverse conditions (supplementary table S1, Supplemen-tary Material online) as described (Warringer et al.2008). In brief, strains were precultured in 350 ll ofsynthetic defined (SD) medium (0.14% yeast nitrogen base,

FIG. 1. A local neutrality model for the emergence of recessive loss-of-function alleles that shape trait heredity in yeast. (A) A local neutralityhypothesis for how the yeast life history promotes emergence of population-specific loss-of-function variation in genes not exposed toselection in local habitats. The hypothesis states that these alleles shape the yeast genotype–phenotype map. However, in experimental crossesbetween populations’ loss-of-function, variation will be completely masked. (B) Nine haploid yeast isolates (red circles), representing a widevariety of sources and geographic origins (Liti et al. 2009), were crossed in all pairwise combinations as well as to self to produce F1 hybrids aswell 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) Theproliferative performance of the diploid heterozygous F1 hybrids and their respective diploid homozygous parents was measured by clonalpropagation 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 growthcurves and log2 transformed. (D) Schema describing the calculation of positive and negative deviations in F1 hybrid performance from the mid-parent expectation (MPH), as well as positive and negative deviations in F1 performance from both parents (BPH; WPH). Additive inheritance isshown for comparison. See also Box 1.

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0.5% ammonium sulfate, and 1% succinic acid; 2% (w/v)glucose; 0.077% complete supplement mixture [ForMedi-um], pH set to 5.8 with NaOH or KOH) and incubatedfor 48 h at 30 �C. Precultures were diluted 35� to an opticaldensity (OD) of 0.03–0.1 in 350 ll of SD medium andcultivated for 72 h in a Bioscreen analyzer C (Growth curvesOy, Finland) with OD measurements at every 20 min usinga wideband (450–580 nm) filter. F1 meiotic progeny(recombinants) from all pairwise combinations of thestrains DBVPG6765, YPS128, Y12, and DBVPG6044 wereobtained and phenotyped as recently described (Cubilloset al. 2011). The fitness variables growth rate (populationdoubling time, h), growth efficiency (total population den-sity 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 todetermine crosses and traits with differences betweenthe three strains (P1, P2, and F1), we performed a simpleanalysis of variance (ANOVA) with strain as fixed effect(false discovery rate [FDR] 5 1%). Mid-parent heterosis(MPH), BPH, worst parent heterosis (WPH), and heterosiscoefficients were calculated as indicated in Box 1. Signifi-cance was determined separately for positive and negativeMPH, BPH, and WPH (one sided Student’s t-test, FDR 5

1%). Parental genetic distances were obtained from Litiet al. (2009). Detailed experimental procedures are availableas Supplementary Material online.

Results

Yeast Heredity Is Strongly Biased toward PositiveNonadditivity and Complete DominanceTo test the local neutrality hypothesis, a species-wide mapof trait heredity in baker’s yeast was constructed by matingnatural isolates from populations representing 64% of theknown single nucleotide polymorphism variation (Liti et al.2009) and 70% of the corresponding trait variation(Warringer et al. 2011) in all pairwise combinations toproduce first filial (F1) generation hybrids (fig. 1B). Diploid

F1 hybrids and their homozygotic parents (P1, P2) werepropagated clonally in a wide array of ecological nichevariations (supplementary table S1, SupplementaryMaterial online), and the reproductive fitness componentsproliferation rate, lag, and efficiency were extracted (fig. 1C).Based on .24,000 measures of reproductive fitness inspecific conditions, the overall frequency of significantpositive and negative F1 hybrid deviations from theexpected parent mean, referred to as MPH, was determined(fig. 1D, Box 1). Overall, we found nonadditive heredity tobe pervasive with 30.2% of all the crosses resulting inpositive or negative MPH at a conservative threshold forsignificance (FDR 5 1%). Consistent with the assumptionof frequent loss-of-function mutations in parent lineages,we found a strong bias toward superior F1 hybrid perfor-mance relative the mid-parent expectation. On average, F1

hybrids performed 49% better than the mid-parent expec-tation, corresponding to a more than a 10-fold bias in favorof significant positive versus significant negative MPH (28%vs. 2.2%; fig. 2A, supplementary fig. S1, SupplementaryMaterial online).

A pronounced impact of loss-of-function mutations onthe yeast genotype–phenotype map also predicted hered-ity in F1 hybrids to be defined by complete masking effects,that is, in the case of a single polymorphic locus, inheri-tance should tend toward complete rather than partialdominance or overdominance, for a functionally unper-turbed allele. On the positive nonadditive side, completedominance corresponds to a heterosis coefficient of one(Box 1) (Melchinger 1999). Although experimental noiseand bias adds variation, we nevertheless expected the dis-tribution of nonadditively inherited traits to be centered ona heterosis coefficient 5 1. Indeed, excluding cases wherethere were no trait differences (ANOVA, FDR 5 1%) eitherbetween the two parents or between parents and F1 hy-brids, we found the distribution of heterosis coefficientsto feature a very distinct peak centered on one (fig. 2B).As a direct consequence of this trend toward completedominance, the degree of MPH in F1 hybrids was propor-tional to the trait differences between the parents (parental

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FIG. 2. Trait heredity in yeast F1 hybrids is strongly biased toward positive MPH and complete dominance. (A) Frequencies of significant (one-sided Student’s t-test, FDR 5 1%) positive and negative MPH. (B) Frequency distribution of heterosis coefficients for crosses and traits withsignificant differences (3,168 of 5,712) between the F1 hybrid and the parents or between parents (ANOVA, FDR 5 1%). White dotted lineindicates a heterosis coefficient of one, meaning F1 hybrids performing equally well as the best performing parent. (C) Positive and negativeMPH as a function of parental trait distances, PD. Linear correlations (Pearson correlation, r) are displayed. See also supplementary figure S1(Supplementary Material online).

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distance, PD) and increased or decreased linearly witha slope close to k 5 ±0.5 (fig. 2C). These observationsare consistent with that yeast heredity in F1 hybrids islargely defined by completely recessive low performancealleles, as expected under the local neutrality hypothesis.

BPH Is Exceedingly Rare in Crosses between YeastPopulationsGiven that relaxations of ancestral selective constraints arepopulation specific, recent loss-of-function mutationsaffecting a trait should tend to be confined to one individ-ual population (fig. 1A). This translates into a prediction ofreciprocal masking of recessive loss-of-function alleles inboth parents being a rare phenomenon when differentyeast populations are crossed. As such reciprocal maskingis expected to be the primary cause of BPH in naturalisolates (Charlesworth and Willis 2009), that is, of F1 hybridsperforming better than both their parents (fig. 1D, Box 1),we also expected significant BPH to be rare. Comparing the

performance of F1 hybrids with that of both their parents,we found significant (FDR 5 1%) BPH for less than 5% of alltraits (fig. 3A, supplementary fig. S1, Supplementary Materialonline). This is far lower than the 30–90% typically observedin 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 selectedfor and shapes trait variation (Troyer 2006; Springer andStupar 2007). Interestingly, and in contrast to the situationfor MPH, these rare instances of BPH showed no correlation(Pearson correlation r 5 0.03) to the trait differencebetween parents (PD). Instead, the degree of BPH wasinversely correlated to the parent trait mean (Pearsoncorrelation r 5 �0.51, fig. 3B): the lower the performanceof the parents, the higher the BPH. This observation is

BOX 1. Measures of HeterosisThe starting point for measuring heterosis in a classicalF1 cross are the mean phenotypes YP1

, YP2, and YF1

of thetwo parental lines P1 and P2 and the diploid F1 hybrid fora quantitative trait Y. MPH denotes the hybrid deviationfrom mid-parent performance:

MPH 5 YF1� Y�p;where Y�p 5

ðYP1 þ YP2Þ2

: 1:1

BPH denotes the hybrid deviation from the better par-ent phenotypic value:

BPH 5 YF1� YBP;where YBP 5maxðYP1

; YP2Þ: 1:2

WPH denotes the hybrid deviation from the worstparent phenotypic value:

WPH 5 YF1� YWP;where YWP 5minðYP1

; YP2Þ: 1:3

These classical measures of heterosis depend on mea-surement scale and cannot be compared directly be-tween crosses. To provide a measure of the degree ofnonadditivity, we include the PD and formulate a heter-osis coefficient analogous to the degree of dominancemeasure for a single locus:

Heterosis coefficient 5MPH

PD=2;where PD 5 jYP1

þ YP2j:

1:4

Thus, F1 performance equals mid-parent performanceif the heterosis coefficient 5 0, best parent performanceif the heterosis coefficient 5 1, and worst parent perfor-mance if the heterosis coefficient 5 �1.

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FIG. 3. BPH is rare in F1 hybrids from crosses between yeastpopulations. (A) Frequencies of significant (one-sided Student’st-test, FDR 5 1%) BPH and WPH. (B) BPH as a function of theparent trait mean, YPi þ YPj=2 (for all traits with significant BPH(Student’s t-test, FDR 5 1%). Linear correlations (Pearsoncorrelation, r) are displayed. (C) Trait variance was calculatedseparately 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, andcompared with their haploid parents in 23 environments (N 5 2)(Cubillos et al. 2011). Trait variance was calculated separatelyamong parents and among F1 recombinants, for each trait, andaveraged over all traits. (E) Correlations (Pearson correlation, r)between (left panel) F1 hybrid and parent/nonparent trait profilesand between (right panel) F1 hybrid and half sibling/nonsibling traitprofiles were calculated. Mean correlations are displayed (dots). Boxplots show spread in mean values for a permutation test (1,000permutations) randomizing relationships. Top and bottom of thebox represents the 25th and 75th quartile in the test, the bandrepresents test median, and whiskers show the full extent of thepermutated data sets.

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consistent with the rare cases of BPH being due to recip-rocal masking of different loss-of-function mutationsaffecting a trait, as expected if parental populations, withlittle gene flow between them, have experienced indepen-dent relaxed selection for this trait. Taken together, ourfindings suggest that reciprocal masking of loss-of-functionmutations is a primary cause of BPH in yeast but that suchevents 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 bothparents, was extremely rare. Only 0.1% of significant WPHcould be detected (fig. 3A, supplementary fig. S1, Supple-mentary Material online), consistent with dominant loss-of-function alleles being rare and the presence of suchalleles for the same trait in both parents exceptional. Thelow frequency of both positive and negative transgressionhas two direct implications for our understanding of naturalyeast ecology. First, it means that hybridization across pop-ulation boundaries results in F1 hybrid populations withtraits that overall are less extreme than the parent popula-tions’. In our experimental setup, the reduction in the widthof phenotype distributions in hybrid populations was in factdramatic: trait variance among yeast F1 hybrids was 42%lower than among the parents (fig. 3C). This loss of pheno-typic width in F1 hybrid populations persisted also after mei-osis, as evidenced by sporulation of a subset of these F1

hybrids, and phenotyping 92 germinated recombinants re-sulting from each cross. We found trait variance amongthe meiotically recombined F1 haploids to be 31% lower thanamong their corresponding haploid parents (fig. 3D). Hence,although F1 hybrid and F1 recombinant phenotypic extremesdo emerge at a low frequency in crosses between popula-tions (Cubillos et al. 2011), such outcrossing generally pro-duces offspring less exceptional and consequently lessspecialized than the parents. Second, the low frequency oftransgressive effects implies that F1 hybrids should tendto resemble their parents. Indeed, comparing the trait pro-files of all F1 hybrids with those of their respective parents, wefound F1 hybrids to be 9% more similar to their parents thanto nonparents from the parent generation, well outside theconfidence limits of a Monte Carlo permutation test (fig. 3E).Furthermore, F1 hybrids were 5% more similar to theirrespective half-siblings, that is, F1 hybrids with which theyshare one parent, than to nonsiblings. This overall resem-blance between parents and offspring as regards fitness traitsis a nontrivial observation; although the inheritance traitsbetween generations has been considered essential sinceAristotle (Mayr 1982), such resemblance between parentsand offspring is not an obvious evolutionary necessity ina species where outcrossing and hybridization across popu-lation boundaries are very infrequent, as in yeast.

Yeast Heredity Is Defined by the Incidence of LowPerformance Alleles and Not Genetic DivergenceHybrid heterozygosity, reflecting the genetic distance be-tween parents, has been suggested to be a good predictorof heredity deviations from the mid-parent expectation(Melchinger 1999). However, the local neutrality hypothesis

predicts the incidence of loss-of-function alleles, which inturn is a function of the degree to which ancestral selectivepressures have been relaxed, not overall heterozygosity, to bethe key determinant of nonadditive heredity. Indeed,although the frequency of significant MPH and BPH varieddramatically between crosses (supplementary fig. S2, Supple-mentary Material online), no overall correlation betweenthese variables and hybrid heterozygosity was observed(fig. 4A). As expected, however, the three F1 hybrids descend-ing from crosses within the European populations, whereparental lines share the vast majority of loss-of-functionalleles, had fewer cases of significant MPH than other F1

hybrids (Fisher’s exact test, P 5 3 � 10�13). Furthermore,using the population’s frequency of low performance traitsto estimate the prevalence of loss-of-function alleles, wepredicted descendants of the West African population,which is low performing for more than 35% (and highperforming for less than 0.5%) of reproductive traits to standout as nonadditive extremes (Warringer et al. 2011). Indeed,the incidence of both significant MPH, excluding cases ofBPH, and BPH were highly parent dependent: for both thesecategories, the West African DBVPG6044, accounting for31% of MPH traits and 40% of BPH traits, stood out asthe most extreme (fig. 4B and C).

Loss-of-Function Alleles Constitute the MolecularBasis for Yeast Nonadditive InheritanceIn some cases, allele structures underlying trait variationbetween parents are known, enabling direct molecular in-terpretation of observed heredity patterns. This is especiallytrue for utilization of the monosaccharide galactose, a rel-atively rare carbohydrate found in habitats rich in certainplant species, such as sugar beets, natural gum, and succu-lents. Among natural S. cerevisiae lineages, little variabilityin the capacity to utilize galactose is observed with the ex-ception for three lineages that feature pronounced defects(Warringer et al. 2011). These defects are all monogenic andcaused by lineage-specific loss-of-function mutations in keygalactose utilization pathway components: the permeaseGAL2 (S288C; missense mutation), the galactokinaseGAL1 (273614N; gene loss), and the key transcriptional reg-ulator GAL3 (DBVPG6044; nonsense mutation). These mu-tations are completely environment specific and have nopleiotropic effects, even as regards the utilization of relatedcarbon substrates (Warringer et al. 2011). Thus, they arelikely to reflect lineage-specific relaxation of selective pres-sure for galactose utilization. Here, we found hybrids deriv-ing from unions between any of these three lineages and allother isolates to proliferate as well as the high performingparent on galactose, reflecting the completely recessivenature of the loss-of-function alleles (fig. 5A). Moreover,hybrids between parents carrying different loss-of-functionalleles showed perfect proliferation on galactose, and thusextreme BPH, reflecting complete reciprocal masking of thenegative alleles. Hence, heredity patterns for galactoseutilization were defined by loss-of-function alleles and pro-vided a case-specific molecular verification of the model.

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In contrast to galactose, heat tolerance is a highlyvariable among natural S. cerevisiae isolates with the WestAfrican DBVPG6044 featuring the gravest defects(Warringer et al. 2011). This polygenic deficiency is dueto the combined effect of multiple loss-of-function allelesin the RAS/cAMP pathway, in conjunction with a lowperformance quantitative trait locus (QTL) in the subtelo-meric region of chromosome XII (Parts et al. 2011). Inhybrids descending from unions between the West AfricanDBVPG6044 and the heat tolerant strains that do notcontain these loss-of-function mutations, heat proliferationmimic that of the well-performing parents (fig. 5B). Hence,the multiple loss-of-function mutations are completelymasked. In contrast, when DBVPG6044 was crossed toother isolates also unable to tolerate heat, extreme BPHemerged, and the F1 hybrid consistently showed unper-turbed heat performance, strongly suggesting reciprocalmasking effects.

For both galactose utilization and heat tolerance, theproliferative rate and efficiency showed identical hereditypatterns. This agreement reflected a strong overall trend:the degree of nonadditive inheritance is highly correlated(Pearson correlation, r5 0.70) for the rate and efficiency ofmitotic proliferation (fig. 5C). This is consistent with theobservation that these two variables covary over naturalisolates in a range of environments (Warringer et al.2011) and refutes assumptions of a general trade-off be-tween these key fitness components (Novak et al. 2006).However, the hereditary coupling of rate and efficiencyis not absolute as evidenced by the inheritance of meli-biose, a rare plant disaccharide, utilization. Although the

ability to utilize melibiose is prevalent among others yeasts,only the Malaysian S. cerevisiae population has retained thistrait. The loss of melibiose utilization associates with com-plete loss of melibiase (MEL1), catalyzing the conversion ofmelibiose to galactose and glucose (Warringer et al. 2011).Whereas F1 hybrids descending from the MalaysianUWOPS03461.4 and strains lacking MEL1 showed completedominance for the efficiency of melibiose utilization, theproliferative rate when using melibiose as carbon sourcewas inherited additively (fig. 5D, supplementary fig. S3,Supplementary Material online). This hereditary uncou-pling of the rate and efficiency of utilization of a carbonsource suggests that half the normal number of proteinmolecules of a proliferation limiting enzyme, in this casemelibiase, is generally enough to maintain the efficiency,but not the rate, of the metabolic machinery.

DiscussionLoss-of-function alleles can emerge either through theoccurrence of pleiotropy and selection for antagonistictraits (Elena and Sanjuan 2003) or due to a combinationof genetic drift and relaxation of ancestral selective pres-sures (Kawecki et al. 1997). We hypothesized that thepeculiar yeast life history should promote genetic driftin those parts of the genome that are not exposed toselection in each population’s main habitat, resulting ina high incidence of population-specific loss-of-functionalleles. Although locally neutral, these variations aredeleterious in a broader ecological context and shouldimpact profoundly on the yeast genotype–phenotype

CAM

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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 dependingon degree of parent genetic similarity (Liti et al. 2009). Top and bottom of the box represents the 25th and 75th quartile, the band representsthe 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 descendingfrom a specific parental lineage. (B) Positive MPH, excluding cases of significant BPH. (C) BPH. See also supplementary figure S2 (SupplementaryMaterial online).

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map. Several observations support such a hypothesis. First,the enormous genetic variability observed between speciesand populations in the yeast clade (Kellis et al. 2003; Litiet al. 2009) is widely considered to reflect that neutralgenetic drift is the main driving force behind yeast genomeevolution (Dujon 2010). This genetic variability frequentlytakes the form of nonsense and frameshift mutationsimpairing protein functionality (Zia and Moses 2011).Extensive variability in fitness traits have also beenobserved between natural S. cerevisiae populations(Warringer et al. 2011). Most of this variability correspondsto low performance of an individual population ina particular condition, implying the action of popula-tion-specific loss-of-function alleles. In yeast speciessuch as Schizosaccharomyces pombe, which is found ina much more restricted set of habitats, trait variation ismuch lower (Brown et al. 2011). Finally, as much as 7–12% of nonsynonymous polymorphisms within baker’syeast occur in sites where little variability is observed overlonger evolutionary time scales (Doniger et al. 2008).Hence, much of recently acquired genetic variation hasbeen exposed to purifying selection in ancestral popula-tions, directly suggesting population-specific relaxationof selective constraints. The distribution patterns of poly-morphisms in conserved sites remarkably well predictsyeast phenotype patterns, strongly supporting that theyare the main cause of phenotypic variation within baker’syeast (Jelier et al. 2011).

We also conjectured that loss-of-function mutationsshould be reflected in a similar pronounced impact onyeast trait heredity. Gene knockouts mimic loss-of-functionmutations (Hillenmeyer et al. 2008); hence, if trait heredityin natural yeast populations is indeed shaped by loss-of-function variation, we expect it to adhere closely to hered-ity patterns emerging from crosses between single geneknockouts and unperturbed parents which show that re-tention of one functional copy of a gene is enough to main-tain a completely unperturbed fitness (Deutschbauer et al.2005; Delneri et al. 2008; Springer et al. 2010). Hence, wepredicted trait heredity in crosses between natural yeastpopulations to be heavily biased toward positive nonaddi-tivity and complete rather than partial dominance or BPH.Charting the first species-wide map of heredity of naturaltraits in any organism, we found these and other predic-tions based on loss-of-function alleles to be confirmed. Fur-thermore, in cases for which the molecular basis of traitscould be dissected, like in the case of galactose utilizationand heat tolerance (fig. 5), loss-of-function alleles indeedemerged as determinants of this complete dominance.The obtained results were thus fully consistent with fre-quent loss-of-function alleles shaping the overall patternof yeast heredity. However, the evaluated model is a modelof gene action at individual loci, whereas the species-widedata necessarily reflect phenotypes for which the geneticbasis is poorly understood. Hence, it is fair to ask whetherthe observed trait heredity patterns could be caused by

FIG. 5. Yeast traits defined by loss-of-function alleles. (A) Proliferative efficiency using galactose as carbon source in crosses between the galactoselow performing strains DBVPG6044 (GAL3 nonsense mutation), 273614N (GAL1 complete loss), and S288C (GAL2 missense mutation) and thegalactose high performing strains L-1528, UWOPS03.461.4, and DBVPG6765, which all lack deleterious GAL pathway alleles. Bars represent theperformance of the parental strains (blue and green) and the F1 hybrid (red). N5 4, error bars 5 standard error. (B) Proliferative efficiency in hightemperatures (40 �C) in crosses involving the heat sensitive DBVPG6044, carrying multiple deleterious alleles in the RAS/cAMP pathway. Crossesto the heat tolerant YPS128, Y12, and S288C as well as to the heat sensitive UWOPS03.461.04, 273614N, and YJM981 are displayed. Bars representthe performance of the parental strains (blue and green) and the F1 hybrid (red). N 5 4, error bars 5 standard error. (C) Correlation betweenMPH 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 theEuropean DBVPG6765 (N 5 4, error bars 5 standard error). See also supplementary figure S3, Supplementary Material online.

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gain-of-function mutations and positive selection ratherthan by loss-of-function mutations and neutral drift.Unfortunately, the impact of adaptive gain-of-function mu-tations on traits and trait heredity is much less understoodthan the impact of loss-of-function mutations due to thedifficulty of mimicking such variation using reversegenetics. Hence, no empirical framework within which sucha model could be contemplated currently exists. Neverthe-less, several lines of evidence suggest that a model wheregain-of-function adaptive variation shapes the overall struc-ture of the yeast genotype–phenotype map is improbable.First, variation in yeast traits tends to follow populationboundaries with no or only marginal influence of the sourceenvironments from which strains were isolated (Warringeret al. 2011). This strongly suggests that the trait-defining ge-netic variation results from population-specific neutral driftrather than from adaptation to these source environments.Second, neutrality tests have consistently failed to detect anyevidence for recent adaptive alleles in a wide variety of yeastgenomes (Kellis et al. 2003; Gu et al. 2005; Doniger et al. 2008;Liti et al. 2009). These failures contrast sharply against the54%, 56%, and 57% of positively selected amino acid substi-tutions detected in fruit fly (Begun et al. 2007), enteric bac-teria (Charlesworth and Eyre-Walker 2006), and mouse(Halligan et al. 2010). Thus, although estimates of a completeabsence of adaptive variation in yeast is likely to be overlyconservative, as evidenced by a recent report demonstratingthe existence of coevolved cis and trans expression QTLs inyeast (Fraser et al. 2010), it seems clear that adaptive gain-of-function mutations historically are much less common thandeleterious variation. Thus, even if it is not yet possible tostringently reject a model where positively selected gain-of-function mutations form the basis for recently emergedyeast trait variation, we argue that such a model is implau-sible. Recent methodological advances (Ehrenreich et al.2010; Parts et al. 2011), allowing direct identification of caus-ative alleles, promise a future species-wide genetic dissectionof natural yeast traits and may allow a definite verification ofto what degree loss-of-function variation indeed shapes theyeast genotype–phenotype map.

The bias toward self-fertilization and asexual vegetativeproliferation, together with enormous within-speciesvariability in habitat composition, sets yeasts apart frommany higher organisms. Nevertheless, the overall impactof deleterious loss-of-function alleles on trait heredity isgenerally deemed to be substantial also in higherorganisms, as suggested by wide-spread inbreeding depres-sion (Charlesworth and Willis 2009) and an excess ofheterozygotes in natural populations (Hansson andWesterberg 2002). Unfortunately, empirical studies of traitheredity in higher species have focused almost exclusivelyon commercial breeds rather than natural populations.Commercial breeds are strongly depleted of deleteriousvariation and enriched for adaptive alleles, meaning thatboth trait heredity patterns and the genetic basis for theseheredity patterns are likely to differ drastically from thoseof natural populations (Springer and Stupar 2007). Hence,large scale tracing of trait heredity in crosses between natural

populations will be necessary to illuminate the question ofwhether the here reported impact of loss-of-functionvariation prevails in other branches of the tree-of-life andcontributes to ecological specialization.

Supplementary MaterialSupplementary figures S1–S3, table S1, and Materials andMethods are available at Molecular Biology and Evolutiononline (http://www.mbe.oxfordjournals.org/).

AcknowledgmentsG.L. was supported by Centre national de la recherchescientifique (CNRS), Programme Atip–Avenir, and theAssociation pour la Recherche sur le Cancer (ARC). J.W.was supported by the Royal Swedish Academy of Sciencesand the Carl Trygger Foundation.

ReferencesBarth S, Busimi AK, Friedrich Utz H, Melchinger AE. 2003. Heterosis

for biomass yield and related traits in five hybrids of Arabidopsisthaliana L. Heynh. Heredity 91:36–42.

Begun DJ, Holloway AK, Stevens K, et al. (13 co-authors). 2007.Population genomics: whole-genome analysis of polymorphismand divergence in Drosophila simulans. PLoS Biol. 5:e310.

Brown WRA, Liti G, Rosa C, et al. (17 co-authors). 2011. Ageographically diverse collection of Schizosaccharomyces pombeisolates shows limited phenotypic variation but extensivekaryotypic diversity. G3: Genes, Genomes, Genetics 1:615–626.

Charlesworth D, Willis JH. 2009. The genetics of inbreedingdepression. Nat Rev Genet. 10:783–796.

Charlesworth J, Eyre-Walker A. 2006. The rate of adaptive evolutionin enteric bacteria. Mol Biol Evol. 23:1348–1356.

Cubillos FA, Billi E, Zorgo E, Parts L, Fargier P, Omholt S, Blomberg A,Warringer J, Louis EJ, Liti G. 2011. Assessing the complexarchitecture of polygenic traits in diverged yeast populations.Mol Ecol. 20:1401–1413.

Delneri D, Hoyle DC, Gkargkas K, et al. (12 co-authors). 2008.Identification and characterization of high-flux-control genes ofyeast through competition analyses in continuous cultures. NatGenet. 40:113–117.

Deutschbauer AM, Jaramillo DF, Proctor M, Kumm J,Hillenmeyer ME, Davis RW, Nislow C, Giaever G. 2005.Mechanisms of haploinsufficiency revealed by genome-wideprofiling in yeast. Genetics 169:1915–1925.

Doniger SW, Kim HS, Swain D, Corcuera D, Williams M, Yang SP,Fay JC. 2008. A catalog of neutral and deleterious polymorphismin yeast. PLoS Genet. 4:e1000183.

Dujon B. 2010. Yeast evolutionary genomics. Nat Rev Genet.11:512–524.

Ehrenreich IM, Torabi N, Jia Y, Kent J, Martis S, Shapiro JA,Gresham D, Caudy AA, Kruglyak L. 2010. Dissection ofgenetically complex traits with extremely large pools of yeastsegregants. Nature 464:1039–1042.

Elena SF, Sanjuan R. 2003. Evolution. Climb every mountain? Science302:2074–2075.

Flint-Garcia SA, Buckler ES, Tiffin P, Ersoz E, Springer NM. 2009.Heterosis is prevalent for multiple traits in diverse maizegermplasm. PLoS One 4:e7433.

Fraser HB, Moses AM, Schadt EE. 2010. Evidence for widespreadadaptive evolution of gene expression in budding yeast. ProcNatl Acad Sci U S A. 107:2977–2982.

Zorgo et al. · doi:10.1093/molbev/mss019 MBE

1788

at Goteborgs U

niversitet on July 17, 2012http://m

be.oxfordjournals.org/D

ownloaded from

Gu Z, David L, Petrov D, Jones T, Davis RW, Steinmetz LM. 2005.Elevated evolutionary rates in the laboratory strain of Saccharo-myces cerevisiae. Proc Natl Acad Sci U S A. 102:1092–1097.

Halligan DL, Oliver F, Eyre-Walker A, Harr B, Keightley PD. 2010.Evidence for pervasive adaptive protein evolution in wild mice.PLoS Genet. 6:e1000825.

Hansson B, Westerberg L. 2002. On the correlation betweenheterozygosity and fitness in natural populations. Mol Ecol.11:2467–2474.

Hillenmeyer ME, Fung E, Wildenhain J, et al. (14 co-authors). 2008.The chemical genomic portrait of yeast: uncovering a phenotypefor all genes. Science 320:362–365.

Jelier R, Semple JI, Garcia-Verdugo R, Lehner B. 2011. Predictingphenotypic variation in yeast from individual genome sequences.Nat Genet. 43:1270–1274.

Kawecki TJ, Barton NH, Fry JD. 1997. Mutational collapse of fitnessin marginal habitats and the evolution of ecological specialisa-tion. J Evol Biol. 10:407–429.

Kellis M, Patterson N, Endrizzi M, Birren B, Lander ES. 2003.Sequencing and comparison of yeast species to identify genesand regulatory elements. Nature 423:241–254.

Knop M. 2006. Evolution of the hemiascomycete yeasts: on life stylesand the importance of inbreeding. Bioessays 28:696–708.

Liti G, Carter DM, Moses AM, et al. (26 co-authors). 2009.Population genomics of domestic and wild yeasts. Nature458:337–341.

Mayr E. 1982. The growth of biological thought: diversity, evolution,and inheritance. Cambridge (MA): Harvard University Press. p. 637.

Melchinger AE. 1999. Genetic diversity and heterosis. In: Coors JG,Pandey S, editors. The genetics and exploitation of heterosis in

crops. Madison (WI): Crop Science Society of America. p.99–118.

Novak M, Pfeiffer T, Lenski RE, Sauer U, Bonhoeffer S. 2006.Experimental tests for an evolutionary trade-off between growthrate and yield in E. coli. Am Nat. 168:242–251.

Parts L, Cubillos F, Warringer J, et al. (14 co-authors). 2011. Revealingthe genetic structure of a trait by sequencing a populationunder selection. Genome Res. 21:1131–1138.

Ruderfer DM, Pratt SC, Seidel HS, Kruglyak L. 2006. Populationgenomic analysis of outcrossing and recombination in yeast. NatGenet. 38:1077–1081.

Springer M, Weissman JS, Kirschner MW. 2010. A general lack ofcompensation for gene dosage in yeast. Mol Syst Biol. 6:368.

Springer NM, Stupar RM. 2007. Allelic variation and heterosis inmaize: how do two halves make more than a whole? GenomeRes. 17:264–275.

Troyer AF. 2006. Adaptedness and heterosis in corn and mulehybrids. Crop Sci. 46:528–543.

Tsai IJ, Bensasson D, Burt A, Koufopanou V. 2008. Populationgenomics of the wild yeast Saccharomyces paradoxus: quanti-fying the life cycle. Proc Natl Acad Sci U S A. 105:4957–4962.

Warringer J, Anevski D, Liu B, Blomberg A. 2008. Chemogeneticfingerprinting by analysis of cellular growth dynamics. BMCChem Biol. 8:3.

Warringer J, Zorgo E, Cubillos FA, et al. (13 co-authors). 2011. Traitvariation in yeast is defined by population history. PLoS Genet.7:e1002111.

Zia A, Moses AM. 2011. Ranking insertion, deletion and nonsensemutations based on their effect on genetic information. BMCBioinformatics. 12:299.

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