Download Life History Shapes Trait Heredity by Accumulation of

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
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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
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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
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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,
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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.
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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
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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 (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).
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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
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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
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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.
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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.
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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
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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
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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
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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.
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