ArticlePDF AvailableLiterature Review

Genetic mechanisms and evolutionary significance of natural variation in Arabidopsis

Authors:

Abstract and Figures

Genomic studies of natural variation in model organisms provide a bridge between molecular analyses of gene function and evolutionary investigations of adaptation and natural selection. In the model plant species Arabidopsis thaliana, recent studies of natural variation have led to the identification of genes underlying ecologically important complex traits, and provided new insights about the processes of genome evolution, geographic population structure, and the selective mechanisms shaping complex trait variation in natural populations. These advances illustrate the potential for a new synthesis to elucidate mechanisms for the adaptive evolution of complex traits from nucleotide sequences to real-world environments.
Content may be subject to copyright.
© 2006 Nature Publishing Group
Genetic mechanisms and evolutionary
significance of natural variation
in Arabidopsis
Thomas Mitchell-Olds
1
& Johanna Schmitt
2
Genomic studies of natural variation in model organisms provid e a bridge between molecular analyses of gene function
and evolutionary investigations of adaptation and natural selection. In the model plant species Arabidopsis thaliana,
recent studies of natural variation have led to the identification of genes underlying ecologically important complex
traits, and provided new insights about the processes of genome evolution, geographic popula tion structure, and the
selective mechan isms shaping complex trait variation in natural populations. These advances illustrate the potential for
a new synthesis to elucidate mechanisms for the adaptive evolution of complex traits from nucleotide sequences to
real-world environments.
T
he beginning of the twenty-first century is an exciting time for
biologists. Rapid advances in genomics have changed our
view of the biological world and fostered new links between
molecular biology, ecology and evolution. Genomic studies of
natural variation in model organisms are a crucial ingredient in this
new synthesis. Molecular biologists have begun to exploit natural
variation to identify the genetic mechanisms underlying complex
traits
1
. Simultaneously, these new genomic tools make it possible for
evolutionary biologists to study how ecologically important complex
traits evolve in natural environments. These advances now make it
possible to understand the adaptive evolution of complex trait
variation from molecular mechanisms to geographic patterns of
population structure and natural selection.
The diminutive weed Arabidopsis thaliana provides an ideal system
for such interdisciplinary synthesis. This species
a close relative of
Brassica crops such as mustard and broccoli
is a convenient genetic
model because of its short generation time and small genome. The
A. thaliana genome was the first plant genome to be sequenced, and
the ge nes and developmental pathways controlling ecologically
important traits such as germination, flowering time, pest resistance,
and stress tolerance are rapidly being elucidated. It is therefore
possible to identify candidate’ genes for adaptive variation in natural
populations. A. thaliana is a widespread annual weed of rocky places
and disturbed sites, native to Europe and central Asia and naturalized
in North America (Fig. 1). Across this geographic range, it experi-
ences a broad range of climatic conditions
2
and selective pressures.
Inbred stocks are available for many natural A. thaliana accessions
(‘ecotypes’), originating across the species’ range. Because the species
is habitually inbreeding, genomic and phenotypic data can be
combined from multiple exper iments with the same genotypes.
These genomic tools and resources have enabled a number of
important advances in molecular and evolutionary genetics. Here
we focus on advances in three complementary areas: (1) genomic
studies of molecular variation and population structure; (2) identi-
fication of genetic polymorphisms underlying natural variation in
complex traits; and, (3) ecolog ica l and evolutionary studies of
natural selection and adaptation. Taken together, these advances
now make it possible to identify the genetic mechanisms underlying
the adaptive evolution of complex traits in natural populations.
Molecular variation and population structure
How much molecular polymorphism exists in A. thaliana? Recent
genome-wide studies show that an average pair of alleles differs at
about seven nucleotides per kilobase (kb; nucleotide diversity ¼ 0.007;
refs 3, 4). T his is about 50% lower than polymorphi sm in the
outcrossing congener A. lyrata ssp. petraea
5
, roughly the same as
Drosophila melanogaster
6
, and nearly an order of magnitude higher
than humans
7
. A. thaliana has a high frequency of self-pollination in
the wild
8
, hence individuals are homozygous at most loci
3
. Such high
rates of self-pollination may influence patterns of linkage disequi-
librium, which provides the basis for association studies and linkage
disequilibrium mapping in human genetics and plant breeding (see
Box 1).
Patterns of nucleotide polymorphism contain a signature of
historical demography and natural selection (see Box 2). Genome-
wide information for A. thaliana has enabled fundamental advances
in our understanding of the evolutionary processes that influence
these patterns. In many species, a positive correlation exists between
local recombination rates and levels of nucleotide diversity
3
.In
regions of low recombination, genetic variation may be reduced
owing to ‘hitchhiking’ of neutral variation with nearby selected sites,
which will influence w ider chromosomal regions when recombina-
tion is low. However, this reduction in variation could be due either
to selective sweeps of advantageous mutations, or to background
selection, which eliminates deleterious mutations and the haplotypes
that carry them. Genome-wide polymorphism data make it possible to
distinguish these possibilities. The recent observation
3
that nucleotide
polymorphism is negatively correlated with gene density supports
background selection as the predominant mechanism. Gene-dense
regions show little sign of rare variants attributable to recent selective
sweeps, but the frequencies of non-synonymous polymorphisms
indicate purifying selection against deleterious mutations
9
.
REVIEWS
1
Department of Biology, PO Box 91000, Duke University, Durham, North Carolina 27708, USA.
2
Department of Ecology and Evolutionary Biology, Box G-W, Brown University,
Providence, Rhode Island 02912, USA.
Vol 441|22 June 2006|doi:10.1038/nature04878
947
© 2006 Nature Publishing Group
Nevertheless, surveys of A. thaliana ecotypes have identified loci
that may have undergone recent positive selection or selective sweeps
(Box 2)
10
. Certain other loci show unusually high levels of amino-
acid variation or too many intermediate-frequency nucleotide poly-
morphisms, which exceed neutral expectation and may have been
maintained by natural selection
11–13
. The selective mechanisms main-
taining such polymorphisms remain an important open question.
Allelic polymorphisms may be maintained within populations by
frequency-dependent selection (where common genotypes have low
fitness, and rare types are favoured), by temporal variation in
selection across seasons and years, or by epistatic selection in
which the fitness of an allele depends on genetic backg round
14
.
Alternatively, different alleles might be maintained in different
populations by local adaptation to geographically divergent selec-
tion, resulting in excess polymorphism species-wide, but little
variation within individual populations. Wide sur veys of A. thaliana
ecotypes cannot distinguish between these different ecological
mechanisms, because information is also needed about patterns of
variation within undisturbed natural populations. However, human
disturbance and admixture of different source pop ulations may
complicate such studies in most parts of the A. thaliana range. It is
therefore impor tant to understand the geographic population
structure of natural v ariation within the species, as well as the
distribution of molecular variation within and among populations
across the species range.
Genome-wide polymorphism data for ecotypes across the range of
A. thaliana have made it possible to investigate th e geographic
structure of molecular variation. The genetic divergence and geo-
graphic distance between pairs of populations is positively correlated
across the native range
3,15
. Such ‘isolation by distance’ reflects long-
term geographical isolation with limited gene flow. The pattern of
population ancestry of European ecotypes suggests that much of
the native range was colonized from several glacial refugia, with
admixture in the zones colonized from more than one source.
However, recent human disturbance tends to homogenize variation
among populations, especially in agricultural regions of Europe and
introduced populations in North America
15–17
.
How is molecular polymorphism distributed within and among
natural populations of A. thaliana? Recent studies have estimated the
proportion of total molecular polymorphism that is found within
populations to be near 45% in western Europe and North Amer-
ica
16–18
, but only 12% in less-disturbed parts of Norway
19
. Although
part of this difference may be attributable to loss of variability as
A. thaliana migrated north from circum-Mediterranean refugia,
comparisons across a 900-km north–south transect in Norway find
no latitudinal changes in genetic variation. Therefore, low variation
within Norwegian populations is probably not attributable to post-
Pleistocene founder events. Instead, high variability w ithin western
European populations probably reflects admixture resulting from
human disturbance
18
. Such admixture complicates our ability to
understand the evolutionary forces shaping genetic variation within
A. thaliana populations.
Finding the genes underlying trait variation
Natural selection operates on complex trait phenotypes. In order to
understand the evolution of ecologically important variation, we
Figure 1 | Arabidopsis habitats. a, b, Although commonly found in
disturbed sites, A. thaliana also grows in pine forests on sandy soils
(a; Bastan, western Siberia) and perennial grasslands in sites with sparse
vegetation (b; Stepnoje, western Siberia). c, Introduced populations in
North America may number in the millions. Here, the white flowers are
another species, but the interspersed vegetation is predominantly A. thaliana
(Michigan, USA). d, Even in western Europe it can be a long-term resident of
stone walls and other sites (Cologne, Germany). (Russia photographs by
M. Hoffmann; USA photograph by J. Bergelson; Ger many photograph by
A. Wilczek.)
Box 1 | Association studies
Association studies use linkage disequilibrium to identify
polymorphisms that may be responsible for complex trait variation.
Linkage disequilibrium quantifies statistical correlations between
polymorphic sites: when linkage disequilibrium is present then
information from one locus provides some predictive information
about the genotype at a second locus. Association studies take
advantage of recombinations accumulated over thousands of
generations, and hence may aid identification of individual genes
responsible for QTL. In the past (top panel), a new mutation
(triangle) occurs at a quantitative trait locus. The original population
contains an ancestral chromosome on which the new mutation
occurred (black line), as well as other chromosomes (grey lines).
After many generations of recombination, the present-day
population (lower panel) contains short chromosome regions
derived from the original population. Molecular markers near the
causal polymorphism (b) will be correlated with phenotype, whereas
distant markers (a, c) are uncorrelated because they have been
reshuffled by recombination. On average, in A. thaliana
polymorphisms separated by .50 kb are usually statistically
independent, whereas linkage disequilibrium is substantial between
sites separated by ,50 kb (ref. 71). Because these regions in
disequilibrium typically contain in the order of 10 genes, linkage
disequilibrium mapping and association studies with candidate
genes bring us close to the level of individual loci. These approaches
may be useful when pedigrees are small, as in human populations,
or when genotyped populations can be used by many researchers
for analysis of multiple phenotypes, as in A. thaliana. Several
challenging statistical issues remain for association studies in A.
thaliana. Population and pedigree structure can be incorporated into
analytical models
72
or homogeneous populations may be identified.
However, if ancestral populations have diverged for the trait of
interest, then statistical adjustment for population structure may
remove the very effects of interest
73
. Linkage disequilibrium
mapping and association studies also result in false negatives and
false positives
74
. Consequently, results from association studies
represent hypotheses that must be tested by independent
experiments
43
.
REVIEWS NATURE|Vol 441|22 June 2006
948
© 2006 Nature Publishing Group
must identify nucleotide polymorphisms with functional effects on
phenotypic differences. Such polymorphisms are also of great inter-
est to plant molecular biologists seeking to elucidate gene function
and genetic pathway structure
20
. Identification of natural variants is
particularly important for functional studies because some knockout
mutations may be lethal, or may lack detectable phenotypic effects
due to genetic redundancy
21
. These efforts will be greatly aided by
databases on genome-wide patterns of nucleotide polymorphism
3
,
gene expression
22
, and developmental phenotypes
23
.
The identification of natural polymorphisms controlling variation
in complex traits begins w ith screens of trait variation among
accessions. Once such variation is identified, the next step is to
identify polymorphic genomic regions (quantitative trait loci, or
QTL) associated with that variation. Recent advances in characteriz-
ing genome-wide polymorphism and population structure for a wide
range of A . thaliana ecotypes
3,15
may facilitate identification of
QTL through linkage disequilibrium mapping (Box 1). Recombinant
inbred lines (RILs) between divergent parental ecot ypes have already
proved extremely valuable for mapping QTL for a variety of eco-
logically important complex traits
20
. QTL of moderately large effect
have been identified in a number of studies, but chromosomal
regions with large phenotypic effects may actually contain multiple
linked QTL of smaller effect
24
. A substantial portion of genetic
variation for complex traits may actually correspond to polygenic
models of complex trait variation, with many genes o f small
effect
25,26
.
Recent advances in genomics make it possible to treat genome-
wide expression patterns as complex traits and screen for natural
variation in those patterns. Schmid et al.
22
studied expression of
22,000 genes in many developmental stages and tissues, providing
invaluable data on regulatory patterns in Arabidopsis and enabling
further functional
27
and evolutionary analyses. Patterns of gene
expression differ among Arabidopsis accessions
28,29
, and QTL influ-
encing cis-ortrans-regulatory polymorphisms can be identified
30
.
Cis-acting allele-specific transcriptional differences are apparently
common in Arabidopsis
30,31
and other organisms
32
. Progress in this
field requires experiments that relate transcriptional polymorphisms
to phenotypic variation at the whole-plant level.
One important lesson from QTL studies with A. thaliana is that the
expression of phenotypic differences between QTL alleles may
depend strongly on environmental conditions and genetic back-
ground. QTL–environment interactions are common; often, certain
QTL are expressed in some environments but not in others, or differ
in the magnitude of their allelic effects. Although such observations
are common in A. thaliana
33,34
, their molecular basis and relationship
to genotype–environment interactions at the whole-organism level
have rarely been elucidated. To date, antagonistic pleiotropy
in
which the alleles of a QTL change phenotypic rank across environ-
ments
35
seems to be rare in A. thaliana. Clearly, more work is
needed to understand the genetic basis of genotype–environment
interaction.
Epistasis, or interaction effects among different loci, is a funda-
mental force in many aspects of adaptive evolution
36
. At its simplest,
epistasis occurs when the genot ype at one locus influences the
magnitude of allelic effects at another lo cus. More intriguingly,
with sign epistasis the genot ype at one locus may reverse the direction
of allelic effects at another gene. There is now strong evidence that
both kinds of epistasis are important in A. thaliana
34,37–40
. In some
cases, the mechanisms of epistasis are known from functional
studies
41,42
. At the level of individual genes, sign epistasis influencing
juvenile growth rate (an important component of fitness) is caused
by genetic poly morphism at a serine/threonine protein kinase, and
patterns of nucleotide polymorphism suggest that balancing selec-
tion maintains elevated levels of genetic variation
25
. These obser-
vations suggest that epistasis may have a fundamental role in the
evolution of A. thaliana and other inbreeding species.
Once QTL regions have been identified, the next step is to find the
underlying genes and nucleotide polymorphisms causally associated
with trait variation. Rigorous standards of proof for determination of
the molecular basis of a QTL have been established
43
, and several
recent studies have used methods such as fine mapping and trans-
genic complementation to identify causal genes
25,44,45
. However, until
homologous recombination techniques for allelic replacement
become available for A. thaliana
46
, the variation introduced by
position effects may limit the power to detect minor allelic effects.
This is well illustrated by a study of the fitness effects of inserting a
transgene for Rpm1-mediated pathogen resistance
47
, where compari-
sons among five independent insertion lines found that fitness
differed by 37% among lines that varied only in the genomic location
of the transgene.
What sorts of molecular polymorphisms control quantitative trait
variation? Examples from A. thaliana span the full range of gene
function, including photoreceptor protein polymorphisms
44
, tran-
scriptio n factors
48
, cis-regulator y polymorphisms
30
, insertion/
deletion polymorphisms
42
, and copy-number variation in tandem
Box 2 | Sequence signatures
Until recently, cloning of QTL has been confined to laboratory model
systems, hence it has been impossible to measure the fitness effects
of QTL alleles in natural environments. As an alternative approach,
adaptive significance has been inferred from the sequence signature
of nucleotide polymorphism
5
. Population genetics theory can predict
patterns of nucleotide polymorphism on the basis of standard
neutral models for ideal, equilibrium populations. Statistical
hypothesis tests can then compare predictions from these standard
neutral models to observed variation at genes of interest. For
example, the figure shows ‘gene trees’ portraying the historical
relationship among alleles at a given locus. A typical selectively
neutral locus is shown on the left, with average levels of nucleotide
polymorphism. In contrast, balancing selection (centre) can
maintain high levels of variability for long periods of time. Such
polymorphisms are unusually old, and have accumulated high levels
of molecular variation. Finally, an advantageous mutation may out-
compete existing alleles in a ‘selective sweep’ (right), reducing
extant variation below neutral levels. Although these theoretical
predictions apply to ideal populations, non-standard or non-
equilibrium demographic conditions such as gene flow or changing
size
5
also influence allelic variation in real-world populations. With
data from only a single locus, statistical tests often cannot
determine whether differences between observed and predicted
patterns are due to natural selection, or instead reflect neutral
effects of demographic history. Fortunately, genome-wide patterns
of variation contain a signature of historical demographic processes,
because demography influences variation across the genome. In
contrast, the effects of natural selection are confined to the target
locus and adjacent regions. Consequently, putative natural selection
at genes of interest may be identified by comparison to a genome-
wide ‘empirical null distribution’ summarizing variability at many
loci, or by simulations based on plausible non-standard models.
Recently, several studies
3,4
have shown that variation in A. thaliana
does not conform to standard demographic models of ideal
populations. Instead, gene flow among populations, changing
population size, extinction, and recolonization evidently have
influenced polymorphism in A. thaliana.
NATURE|Vol 441|22 June 2006 REVIEWS
949
© 2006 Nature Publishing Group
gene families
12
. However, current examples are insufficient to draw
generalizations about the importance of regulatory versus coding
polymorphisms, especially because the QTL that have been cloned so
far have larger than average effects, and may not be representative of
small-effect QTL.
Natural selection for complex traits
How does natural selection act on trait variation in the real world?
The native range of A. thaliana spans a broad range of climates and
habitats. A. thaliana has evolutionarily expanded its range to warmer
climates from the cool temperate ‘climate space’ inhabited by other
Arabidopsis species
49
. This climatic range expansion may result from
A. thalianas evolutionary transition to an annual life history from
the perennial strateg y shown by i ts close relatives. The annual
strategy may increase tolerance of warmer climates by allowing
plants to survive summer conditions as seeds rather than as juvenile
or adult plants. However, the annual strategy necessitates germinat-
ing and flowering during favourable growing conditions, and the
seasonal timing of these events varies across the climatic range of
the species. Natural populations of A. thaliana are thus likely to
experience very different selective pressures across the species range.
If geographic variation in climate has resulted in local adaptation, we
should expect genetic associations between the phenotype of an
accession and the climate in its site of origin.
How much natural variation exists for ecologically important
traits in A. thaliana? Experiments with geographically diverse eco-
types under common garden conditions reveal remarkable genetic
variation in many ecologically important traits
20,23,48,50,51
. Much less is
known about the phenology and demography of natural A. thaliana
populations in situ, but it is clear that the species shows variation in
life history timing across its range. In particular, there is a life history
polymorphism between winter annual ecotypes
which overwinter
as small vegetative rosettes and flower in spring
and rapid cycling
ecotypes
which germinate and flower in late summer and again in
spring to produce two generations per year (ref. 52). This poly-
morphism has been attributed to loss of a vernalization requirement
conferred by mutation at the major flowering time loci, FRIGIDA
(FRI)
42,53
and FLOWERING LOCUS C (FLC)
54
, w ith additional
variation due to other loci
23,48,51
.
Does the observed genetic variation among natural populations
represent adaptive differentiation in response to heterogeneous
natural selection? This hypothesis can be tested with several different
lines of evidence (Table 1). First, is trait variation associated with
geographical variation in climate or other ecological factors? Second,
is the degree of quantitative variation among populations greater
than expected on the basis of differentiation at neutral markers?
Third, do local genotypes have higher fitness than foreign genotypes
in reciprocal transplant experiments, and if so, is this ‘home-court
advantage’ attributable to selection favouring the local phenotype of
the candidate trait? The first two questions have recently been
addressed by quantitative genetic studies in common garden
environments, and provide some support for the adaptive differen-
tiation hypothesis. However, the third question will require ev idence
from reciprocal transplant experiments and field studies of selection.
Several studies have detected latitudinal clines in A. thaliana growth
and morphology, seedling traits, flowering time, vernalization sensi-
tivity, and circadian period
23,55–58
. Such gradients in complex traits may
provide evidence of local adaptation, especially if the direction of
the cline is consistent with functional arguments
58
. However, clinal
variation may also result from non-adaptive phenomena such as
isolation by distance or admixture between two divergent founder
populations. Therefore, geographic tests of trait adaptation are most
compelling when combined with other forms of evidence.
If population differentiation in a trait is adaptive, the degree of
quantitative genetic differentiation in the trait among populations
should be greater than the genetic differentiation among populations
in neutral molecular markers
18
. (Typically, the proportion of genetic
variation found among populations for phenotypic traits and neutral
molecular markers is quantified by Q
st
and F
st
, respectively.) Using
this approach, Le Corre
18
measured trait variation within and among
natural populations in France. The Q
st
for bolting time was signifi-
cantly higher than the overall F
st
estimated from neutral molecular
markers, suggesting adaptive divergence among populations in
reproductive timing. Moreover, the F
st
for functional polymorphism
at the principal flowering time gene FRI was also significantly higher
than F
st
at marker loci, suggesting adaptive differentiation at that
locus. Because FRI confers a vernalization requirement, and is known
to be associated with flowering time in non-vernalized plants, these
Table 1 | Evidence for adaptation
Method Known
gene?
Advantages Disadvantages Reference Time
frame
Transgenic comparison
of candidate allele effects
Yes The gold standard for functional
verification and fitness
consequences
Transgene position effects
Regulatory complications with field
trials
47 Current
QTL, RILs, NILs No Does not require known gene
Modest regulatory requirements
Effects may be confounded with
flanking genes
40 Current
Sequence signature Yes Capable of detecting very weak
selection
Does not require
phenotypic information
Must control for demographic
history
Phenotype experiencing selection is
unknown
5 Historical
F
st
/Q
st
No F
st
can be calculated from
relatively few neutral loci
Does not require genome-wide
molecular markers
Difficult to detect local adaptation
when F
st
is large
18 Historical
Hitchhiking mapping No May localize chromosomal region
experiencing local adaptation
Phenotype experiencing selection
is unknown
75 Historical
Genotype–environment
association
No Can be applied when causal genes
are unknown
May be confounded with gene flow
or admixture
58 Historical
Multivariate selection
analyses
No Can be applied when causal genes
are unknown
May be confounded with unmeasured
traits
61 Current
Reciprocal transplants No With proper replication, may detect
local adaptation
Can be applied when causal genes
are unknown
Requires access to original populations
and environments
Further experiments needed to establish
mechanism
59 Historical and
current
Abbreviations: QTL, quantitative trait loci; RILs, recombinant inbred lines; NILs, near-isogenic lines; F
st
, the proportion of molecular marker polymorphism found among populations; Q
st
,the
proportion of quantitative genetic variation found among populations.
REVIEWS NATURE|Vol 441|22 June 2006
950
© 2006 Nature Publishing Group
results suggest that the adaptive divergence of flowering time occurred
through selection for loss of FRI function in certain populations.
Common garden studies may provide evidence for adaptive
population differentiation in complex traits, and suggest hypotheses
about selective mechanisms for such differentiation. However, direct
support for the local adaptation hypothesis requires reciprocal
transplants between natural populations
59
, and selective mechanisms
are best tested by measuring natural selection on traits of interest in
such experiments. Although this approach has proved to be very
powerful in other plant species, it has rarely been attempted for
A. thaliana, and evidence for local adaptation has been equivocal
60
.
A reciprocal-transplant approach could be very valuable for testing
hypotheses about local adaptation to climate across the native range
of A. thaliana.
Although direct experimental tests of local adaptation are still
lacking for A. thaliana, several field experiments provide strong
evidence for real-time natural selection on complex traits and specific
loci. Multivariate selection analysis
61
quantifies how natural selection
acts on variation in complex traits. Such studies are most valuable
when combined with ecological manipulations to test hypotheses
about the causes of selection
62
. For example, Donohue et al.
63
demonstrated geographical differences in selection on germination
timing for seeds of the same genot ypes experimentally dispersed in
Rhode Island and Kentucky, as well as seasonal differences in
selection between seeds dispersed in spring and autumn.
How does natural selection on complex traits act on specific loci?
Recent field experiments with RILs have identified QTL influencing
fitness in different environments
40,64,65
. The same set of lines showed
largely different QTL for fitness in Georgia
40
, North Carolina, and
Rhode Island
65
, suggesting that natural selection acts on different
genomic regions in different geog raphic locations and seasonal
environments. These studies also revealed pervasive epistatic selec-
tion. For example, Malmberg and colleagues
40
found epistatic QTL to
be more common and more important than non-epistatic QTL, and
found a high frequency of sign epistasis for fecundity. Such epistatic
interactions can maintain genetic variation and constrain evolution-
ary responses to natural selection
36
, and may provide a possible
mechanism for the maintenance of polymorphism in A. thaliana.
These studies could not test hypotheses about local adaptation, as
the parents of the RILs were not native to the field sites. Rather, they
provide insights into how natural selection will act on the segregating
variation in different novel environments, a potentially relevant
scenario for this colonizing species. Such experiments also can test
whether fitness QTL co-localize with QTL for complex traits experi-
encing natural selection, thus provi ding insights into selective
mechanisms
64
. The next step is to take RILs from locally adapted
parental ecotypes and conduct selection experiments with the RILs in
the parental sites of origin. Such experiments can elucidate the selective
mechanisms and specific loci contributing to local adaptation
66
.
Near-isogenic lines (NILs) containing alternate alleles of poly-
morphic candidate genes provide another promising tool for testing
hypotheses about how selection acts on polymorphisms in ecological
time. Such studies will be particularly useful for polymorphisms that
show the molecular signature of balancing selection in genes of
known ecological function. For example, R-genes in A. thaliana
confer resistance to pathogens, and are often polymorphic for resistant
or susceptible alleles, with evidence for balancing selection at the
molecular level
13,67,68
. Experiments with NILs
69
and pairs of transgenics
that differed in the presence or absence of a resistant allele
47
were able to
demonstrate fitness costs of resistance allel es, which provide an
ecological mechanism for the maintenance of these polymorphisms.
This approach may be valuable for future studies of the selective
mechanisms acting to maintain variation at other candidate loci.
Future prospects
Future advances in our understanding of A. thaliana natural vari-
ation depend, in part, on improvements in resources and technology.
Among the highest priorities are expanded collections from well-
characterized environments, as well as possible undisturbed popu-
lations from Eurasia. On the technical side, the greatest need is for
straightfor ward protocols to reduce transgene position effects, such
as gene targeting
46
or alternative approaches
47,70
.
Arabidopsis research is poised to address fundamental questions in
evolution and ecology, including: What is the role of epistasis, and
how does it influence the evolution of developmental pathways? How
do ecological processes influence balancing selection within and
among populations? What are the frequencies and effects of QTL
alleles, and how is this influenced by evolutionar y forces? What are
the ecological and molecular mechanisms of local adaptation within
the native range of A. thaliana? How do real-time ecological processes
influence adaptive evolution in introduced and invasive populations?
As the field matures, research will focus increasingly on related
species, which will greatly improve our understanding of the genetic
basis and evolutionar y mechanisms of speciation.
Equally as important, Arabidopsis biology encourages (and
requires) interdisciplinary research and training. A new synthesis
of functional genomics with evolution and ecology will benefit each
component discipline, and will bring fundamental advances in our
understanding of biological mechanisms and processes. Such training
provides an essential component of science education for the future.
1. Alonso-Blanco, C., Mendez-Vigo, B. & Koornneef, M. From phenotypic to
molecular polymorphisms involved in naturally occurring variation of plant
development. Int. J. Dev. Biol. 49, 717–-732 (2005).
2. Hoffmann, M. H. Biogeography of Arabidopsis thaliana (L.) Heynh.
(Brassicaceae). J. Biogeogr. 29, 125–-134 (2002).
3. Nordborg, M. et al. The pattern of polymorphism in Arabidopsis thaliana. PLoS
Biol. 3, e196 (2005).
4. Schmid, K. J., Ramos-Onsins, S., Ringys-Beckstein, H., Weisshaar, B. &
Mitchell-Olds, T. A multilocus sequence survey in Arabidopsis thaliana reveals a
genome-wide departure from a neutral model of DNA sequence
polymorphism. Genetics 169, 1601–-1615 (2005).
5. Wright, S. I. & Gaut, B. S. Molecular population genetics and the search for
adaptive evolution in plants. Mol. Biol. Evol. 22, 506–-519 (2005).
6. Ometto, L., Glinka, S., De Lorenzo, D. & Stephan, W. Inferring the effects of
demography and selection on Drosophila melanogaster populations from a
chromosome-wide scan of DNA variation. Mol. Biol. Evol. 22, 2119–-2130
(2005).
7. Akey, J. M. et al. Population history and natural selection shape patterns of
genetic variation in 132 genes. PLoS Biol. 2, e286 (2004).
8. Abbott, R. J. & Gomes, M. F. Population genetic structure and outcrossing rate
of Arabidopsis thaliana (L.) Heynh. Heredity 62, 411–-418 (1989).
9. Bustamante, C. D. et al. The cost of inbreeding in Arabidopsis. Nature 416,
531–-534 (2002).
10. Shimizu, K. K. et al. Darwinian selection on a selfing locus. Science 306,
2081–-2084 (2004).
11. Cork, J. M. & Purugganan, M. D. High-diversity genes in the Arabidopsis
genome. Genetics 170, 1897–-1911 (2005).
12. Kroymann, J., Donnerhacke, S., Schnabelrauch, D. & Mitche ll-Olds, T.
Evolutionary dynamics of an Arabidopsis insect resistance quantitative trait
locus. Proc. Natl Acad. Sci. USA 100, 14587–-14592 (2003).
13. Tian, D., Araki, H., Stahl, E., Bergelson, J. & Kreitman, M. Signature of balancing
selection in Arabidopsis. Proc. Natl Acad. Sci. USA 99, 11525–-11530 (2002).
14. Turelli, M. & Barton, N. H. Polygenic variation maintained by balancing
selection: pleiotropy, sex-dependent allelic effects and G £ E interactions.
Genetics 166, 1053–-1079 (2004).
15. Schmid, K. et al. Evidence for a large-scale population structure of Arabidopsis
thaliana from genome-wide single nucleotide polymorphism markers. Theor.
Appl. Genet. 112, 1104–-1114 (2006).
16. Jorgensen, S. & Mauricio, R. Neutral genetic variation among wild North
American populations of the weedy plant Arabidopsis thaliana is not
geographically structured. Mol. Ecol. 13, 3403–-3413 (2004).
17. Bakker, E. G. et al. Distribution of genetic variation within and among local
populations of Arabidopsis thaliana over its species range. Mol. Ecol. 15,
1405–-1418 (2006).
18. Le Corre, V. Variation at two flowering time genes within and among
populations of Arabidopsis thaliana: comparison with markers and traits. Mol.
Ecol. 14, 4181–-4192 (2005).
19. Stenoien, H. K., Fenster, C. B., Tonteri, A. & Savolainen, O. Genetic variability in
natural populations of Arabidopsis thaliana in northern Europe. Mol. Ecol. 14,
137–-148 (2005).
20. Koornneef, M., Alonso-Blanco, C. & Vreugdenhil, D. Naturally occurring
genetic variation in Arabidopsis thaliana. Annu. Rev. Plant Biol. 55, 141–-172
(2004).
NATURE|Vol 441|22 June 2006 REVIEWS
951
© 2006 Nature Publishing Group
21. Bouche, N. & Bouchez, D. Arabidopsis gene knockout: phenotypes wanted. Curr.
Opin. Plant Biol. 4, 111–-117 (2001).
22. Schmid, M. et al. A gene expression map of Arabidopsis thaliana development.
Nature Genet. 37, 501–-506 (2005).
23. Lempe, J. et al. Diversity of flowering responses in wild Arabidopsis thaliana
strains. PLoS Genetics 1, e6 (2005).
24. Mackay, T. F. C. The genetic architecture of quantitative traits: lessons from
Drosophila. Curr. Opin. Genet. Dev. 14, 253–-257 (2004).
25. Kroymann, J. & Mitchell-Olds, T. Epistasis and balanced polymorphism
influencing complex trait variation. Nature 435, 95–-98 (2005).
26. Fishman, L., Kelly, A. & Willis, J. Minor quantitative trait loci underlie floral
traits associated with mating system divergence in Mimulus. Evolution 56,
2138–-2155 (2002).
27. Gachon, C. M. M., Langlois-Meurinne, M., Henry, Y. & Saindrenan, P.
Transcriptional co-regulation of secondary metabolism enzymes in Arabidopsis:
functional and evolutionary implications. Plant Mol. Biol. 58, 229–-245 (2005).
28. Kliebenstein, D. J. et al. Genomic survey of gene expression diversity in
Arabidopsis thaliana. Genetics 172, 1179–-1189 (2006).
29. Vuylsteke, M., van Eeuwijk, F., Van Hummelen, P., Kuiper, M. & Zabeau, M.
Genetic analysis of variation in gene expression in Arabidopsis thaliana . Genetics
171, 1267–-1275 (2005).
30. DeCook, R., Lall, S., Nettleton, D. & Howell, S. H. Genetic regulation of gene
expression during shoot development in Arabidopsis. Genetics 172, 1155–-1164
(2006).
31. de Meaux, J., Goebel, U., Pop, A. & Mitchell-Olds, T. Allele-specific assay
reveals functional variation in the Chalcone Synthase promoter of Arabidopsis
thaliana that is compatible with neutral evolution. Plant Cell 17, 676–-690
(2005).
32. Gibson, G. & Weir, B. The quantitative genetics of transcription. Trends Genet.
21, 616–-623 (2005).
33. Ungerer, M. C., Halldorsdottir, S. S., Purugganan, M. D. & Mackay, T. F. C.
Genotype–-environment interactions at quantitative trait loci affecting
inflorescence development in Arabidopsis thaliana. Genetics 165, 353–-365
(2003).
34. Juenger, T. E., Sen, S., Stowe, K. A. & Simms, E. L. Epistasis and genotype–-
environment interaction for quantitative trait loci affecting flowering time in
Arabidopsis thaliana. Genetica 123, 87–-105 (2005).
35. Dilda, C. L. & Mackay, T. F. C. The genetic architecture of Drosophila sensory
bristle number. Genetics 162, 1655–-1674 (2002).
36. Weinreich, D., Watson, R. & Chao, L. Sign epistasis and genetic constraint on
evolutionary trajectories. Evolution 59, 1165–-1174 (2005).
37. Syed, N. H. & Chen, Z. J. Molecular marker genotypes, heterozygosity and
genetic interactions explain heterosis in Arabidopsis thaliana. Heredity 94,
295–-304 (2004).
38. Hausmann, N. J. et al. Quantitative trait loci affecting delta C-13 and response
to differential water availability in Arabidopsis thaliana. Evolution 59, 81–-96
(2005).
39. Kearsey, M., Pooni, H. & Syed, N. Genetics of quantitative traits in Arabidopsis
thaliana. Heredity 91, 456–-464 (2003).
40. Malmberg, R. L., Held, S., Waits, A. & Mauricio, R. Epistasis for fitness-related
quantitative traits in Arabidopsis thaliana grown in the field and in the
greenhouse. Genetics 171, 2013–-2027 (2005).
41. Michaels, S. D. & Amasino, R. M. Loss of FLOWERING LOCUS C activity
eliminates the late-flowering phenotype of FRIGIDA and autonomous pathway
mutations but not responsiveness to vernalization. Plant Cell 13, 935–-942 (2001).
42. Johanson, U. et al. Molecular analysis of FRIGIDA, a major determinant of
natural variation in Arabidopsis flowering time. Science 290, 344–-347 (2000).
43. Weigel, D. & Nordborg, M. Natural variation in Arabidopsis. How do we find the
causal genes? Plant Physiol. 138, 567–-568 (2005).
44. El-Assal, S. E.-D., Alonso-Blanco, C., Peeters, A. J. M., Raz, V. & Koornneef,
M. A. QTL for flowering time in Arabidopsis reveals a novel allele of CRY2 .
Nature Genet. 29, 435–-440 (2001).
45. Werner, J. D. et al. Quantitative trait locus mapping and DNA array
hybridization identify an FLM deletion as a cause for natural flowering-time
variation. Proc. Natl Acad. Sci. USA 102, 2460–-2465 (2005).
46. Puchta, H. & Hohn, B. Green light for gene targeting in plants. Proc. Natl Acad.
Sci. USA 102, 11961–-11962 (2005).
47. Tian, D., Traw, M., Chen, J., Kreitman, M. & Bergelson, J. Fitness costs of R-
gene-mediated resistance in Arabidopsis thaliana. Nature 423, 74–-77 (2003).
48. Werner, J. D. et al. FRIGIDA-independent variation in flowering time of natural
Arabidopsis thaliana accessions. Genetics 170, 1197–-1207 (2005).
49. Hoffmann, M. H. Evolution of the realized climatic niche in the genus
Arabidopsis (Brassicaceae). Evolution 59, 1425–-1436 (2005).
50. Pigliucci, M. in The Arabidopsis Book (eds Somerville, C. R. & Meyerowitz, E. M.)
(American Society of Plant Biologists, Rockville, Maryland, 2002) doi:10.1199/
tab.0009 kwww.aspb.org/publications/arabidopsis/l (2002).
51. Shindo, C. et al. Role of FRIGIDA and FLOWERING LOCUS C in determining
variation in flowering time of Arabidopsis. Plant Physiol. 138, 1163–-1173 (2005).
52. Thompson, L. The spatiotemporal effects of nitrogen and litter on the
population dynamics of Arabidopsis thaliana. J. Ecol. 82, 63–-68 (1994).
53. Simpson, G. G. & Dean, C. Arabidopsis, the Rosetta stone of flowering time?
Science 296, 285–-289 (2002).
54. Michaels, S. D., He, Y., Scortecci, K. C. & Amasino, R. M. Attenuation of
FLOWERING LOCUS C activity as a mechanism for the evolution of summer-
annual flowering behavior in Arabidopsis . Proc. Natl Acad. Sci. USA 100,
10102–-10107 (2003).
55. Maloof, J. N. et al. Natural variation in light sensitivity of Arabidopsis. Nature
Genet. 29, 441–-446 (2001).
56. Michael, T. P. et al. Enhanced fitness conferred by naturally occurring variation
in the circadian clock. Science 302, 1049–-1053 (2003).
57. Stenoien, H. K., Fenster, C. B., Kuittinen, H. & Savolainen, O. Quantifying
latitudinal clines to light responses in natural populations of Arabidopsis
thaliana (Brassicaceae). Am. J. Bot. 89, 1604–-1608 (2002).
58. Stinchcombe, J. R. et al. A latitudinal cline in flowering time in Arabidopsis
thaliana modulated by the flowering time gene FRIGIDA. Proc. Natl Acad. Sci.
USA 101, 4712–-4717 (2004).
59. Kawecki, T. J. & Ebert, D. Conceptual issues in local adaptation. Ecol. Lett. 7,
1225–-1241 (2004).
60. Callahan, H. S. & Pigliucci, M. Shade-induced plasticity and its ecological
significance in wild populations of Arabidopsis thaliana. Ecology 83, 1965–-1980
(2002).
61. Rausher, M. D. The measurement of selection on quantitative traits
biases
due to environmental covariances between traits and fitness. Evolution 46,
616–-626 (1992).
62. Wade, M. J. & Kalisz, S. The causes of natural selection. Evolution 44,
1947–-1955 (1990).
63. Donohue, K. et al. The evolutionary ecology of seed germination of Arabidopsis
thaliana: variable natural selection on germination timing. Evolution 59,
758–-770 (2005).
64. Callahan, H. S., Dhanoolal, N. & Ungerer, M. C. Plasticity genes and plasticity
costs: a new approach using an Arabidopsis recombinant inbred population.
New Phytol. 166, 129–-139 (2005).
65. Weinig, C. et al. Heterogeneous selection at specific loci in natural
environments in Arabidopsis thaliana. Genetics 165, 321–-329 (2003).
66. Verhoeven, K. J. F., Vanhala, T. K., Biere, A., Nevo, E. & Van Damme, J. M. M.
The genetic basis of adaptive population differentiation: a quantitative trait
locus analysis of fitness traits in two wild barley populations from contrasting
habitats. Evolution 58, 270–-283 (2004).
67. Mauricio, R. et al. Natural selection for polymorphism in the disease resistance
gene Rps2 of Arabidopsis thaliana. Genetics 163, 735–-746 (2003).
68. Shen, J., Araki, H., Chen, L., Chen, J.-Q. & Tian, D. Unique evolutionary
mechanism in R-genes under the presence/absence polymorphism in
Arabidopsis thaliana. Genetics 172, 1243–-1250 (2006).
69. Korves, T. & Bergelson, J. A novel cost of R gene resistance in the presence of
disease. Am. Nat. 163, 489–-504 (2004).
70. Siegal, M. L. & Hartl, D. L. Transgene coplacement and high efficiency site-
specific recombination with the Cre/loxP system in Drosophila. Genetics 144,
715–-726 (1996).
71. Plagnol, V., Padhukasahasram, B., Wall, J. D., Marjoram, P. & Nordborg, M.
Relative influences of crossing-over and gene conversion on the pattern of
linkage disequilibrium in Arabidopsis thaliana. Genetics 172, 2441-2448
(2005).
72. Yu, J. et al. A unified mixed-model method for association mapping that
accounts for multiple levels of relatedness. Nature Genet. 38, 203–-208 (2006).
73. Remington, D. L. et al. Structure of linkage disequilibrium and phenotypic
associations in the maize genome. Proc. Natl Acad. Sci. USA 98, 11479–-11484
(2001).
74. Aranzana, M. et al. Genome-wide association mapping in Arabidopsis identifies
previously known flowering time and pathogen resistance genes. PLoS Genetics
1, e60 (2005).
75. Schlotterer, C. Hitchhiking mapping
functional genomics from the population
genetics perspective. Trends Genet. 19, 32–-38 (2003).
Acknowledgements We thank M. Noor, M. Nordborg and our collaborators and
laboratory members for discussion and comments. T.M.-O. and J.S. were
supported by Duke University and the National Science Foundation,
respectively.
Author Information Reprints and permissions information is availabl e at
npg.nature.com/reprintsandpermissions. The authors declare no competing
financial interests. Correspondence should be addressed to T.M.-O.
(tmo1@duke.edu).
REVIEWS NATURE|Vol 441|22 June 2006
952
... The "neutral theory" of molecular evolution holds that most polymorphisms within species are in mutation-drift equilibrium, and that differentiation is not the result of adaptation [9,10]. Based on population structure, the identification of genome-wide variation loci to indicate the impact of natural selection on specific loci can contribute to a better understanding of polymorphism and adaptation [11,12]. ...
... To date, most plant species do not conform to the population statistical assumptions of standard equilibrium neutral models and deviations from neutral expectations are relatively common [11]. Analyzing highly divergent genomic regions and exploring how selection drives speciation have been a hot spot in speciation and population evolution studies [8,16]. ...
Article
Full-text available
Seagrasses are higher flowering plants that live entirely in marine environments, with the greatest habitat variation occurring from land to sea. Genetic structure or population differentiation history is a hot topic in evolutionary biology, which is of great significance for understanding speciation. Genetic information is obtained from geographically distributed subpopulations, different subspecies, or strains of the same species using next-generation sequencing techniques. Genetic variation is identified by comparison with reference genomes. Genetic diversity is explored using population structure, principal component analysis (PCA), and phylogenetic relationships. Patterns of population genetic differentiation are elucidated by combining the isolation by distance (IBD) model, linkage disequilibrium levels, and genetic statistical analysis. Demographic history is simulated using effective population size, divergence time, and site frequency spectrum (SFS). Through various population genetic analyses, the genetic structure and historical population dynamics of seagrass can be clarified, and their evolutionary processes can be further explored at the molecular level to understand how evolutionary processes contributed to the formation of early ecological species and provide data support for seagrass conservation.
... In a population of mixed diploid and tetraploid Chamerion angustifoilum (Onagraceae), opportunities for intercytotype mating were drastically reduced (by 47%) due to the combined effects of flowering asynchrony and insect foraging behaviour contributing to prezygotic mating isolation among cytotypes (Husband and Schemske 2000). Population level studies of local adaptation involving floral asynchrony show that floral phenology can evolve quite rapidly (Mitchell-Olds and Schmitt 2006;Franks et al. 2007), and it has been suggested that further divergence can lead to initial phenological differences to be strengthened by divergent selection (Chapurlat et al. 2020). In two closely related Gymnadenia orchid species that have been shown to introgress, flowering time and scent emission are under different selection regimes (Joffard et al. 2022), a scenario that is consistent with floral asynchrony playing an important role in maintaining species boundaries between closely related species (Chapurlat et al. 2020). ...
Article
Full-text available
Background and aims – The study of factors and processes involved in evolutionary divergence can inform how biodiversity is generated and maintained. We evaluate shifts in phenology or in pollination systems as potential barriers to gene exchange and thus promoters of divergence at the population-species boundary in the plant ring-species Euphorbia tithymaloides in the Caribbean. Material and methods – Combining collections-based and field-based observations and measurements, we evaluate evidence supporting that shifts in tempo of reproductive activity (floral phenology) or pollinator guilds (using visitation as a proxy) could be acting as mechanisms promoting divergence in E. tithymaloides . We focus on the geographic region where evolutionary divergence in this species has been documented: Greater and Lesser Antilles. Phenology data were derived from herbaria and online databases, for a total of 376 records across the Greater and Lesser Antilles. We quantified and characterized reward (nectar n = 13 sites) and gathered visitation data using direct observation (n = 12 sites) for a total of over 133 hours of observation/site. Key results – The peak of floral activity of E. tithymaloides is in winter, when days are short (~late October–late May). Under natural conditions, plants in the Antilles produce up to 22.4 µL of nectar, with mean sugar concentrations of ~ 46.5 ºBrix that amount to up to 10.3 mg of total sugars, with no significant differences observed between plants of the Lesser and Greater Antilles. Hummingbirds are the main floral visitors of E. tithymaloides in both areas: Greater Antilles: 61%, Lesser Antilles: 85%, and network analyses support a floral visitor community turnover across islands/countries. Conclusion – Evolutionary divergence in Caribbean E. tithymaloides along the Greater and Lesser Antilles is not accompanied by shifts in floral phenology or pollinator systems. Other factors, like pollinator turnover or pollinator-plant trait matching, might be at play. We outline hypotheses to this effect.
... To address those problems, the method of genome-wide association (GWA) mapping emerged through the recent development of next-generation sequencing (NGS) technologies. Taking advantage of recombination events that have accumulated over thousands of generations (Mitchell-Olds and Schmitt, 2006;Nordborg and Weigel, 2010), GWA mapping uses natural linkage disequilibrium (LD) to identify polymorphisms that are associated with phenotypic variation. Although its power is reduced to detect rare alleles or weakeffect alleles in GWA mapping populations, this issue is counterbalanced by the greater advantage of fine mapping (down to the gene level) and common alleles associated with phenotypic variation at the species level (Bergelson and Roux, 2010). ...
Article
Full-text available
The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA) mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes). In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.
... During long-term evolution, genes derived from the same ancestor (that is, the sequences of different members of the same gene family) become different, and each gene exhibits different expression regulation patterns and plays different functions (Mitchell-Olds and Schmitt, 2006). The study of gene families can help in understanding the evolutionary history of a class of genes, in determining whether there is a specific gene family in a species, and in discovering important functional genes (Thornton and DeSalle, 2000). ...
Article
Full-text available
FHY3 and its homologous protein FAR1 are the founding members of FRS family. They exhibited diverse and powerful physiological functions during evolution, and participated in the response to multiple abiotic stresses. FRF genes are considered to be truncated FRS family proteins. They competed with FRS for DNA binding sites to regulate gene expression. However, only few studies are available on FRF genes in plants participating in the regulation of abiotic stress. With wide adaptability and high stress-resistance, barley is an excellent candidate for the identification of stress-resistance-related genes. In this study, 22 HvFRFs were detected in barley using bioinformatic analysis from whole genome. According to evolution and conserved motif analysis, the 22 HvFRFs could be divided into subfamilies I and II. Most promoters of subfamily I members contained abscisic acid and methyl jasmonate response elements; however, a large number promoters of subfamily II contained gibberellin and salicylic acid response elements. HvFRF9, one of the members of subfamily II, exhibited a expression advantage in different tissues, and it was most significantly upregulated under drought stress. In-situ PCR revealed that HvFRF9 is mainly expressed in the root epidermal cells, as well as xylem and phloem of roots and leaves, indicating that HvFRF9 may be related to absorption and transportation of water and nutrients. The results of subcellular localization indicated that HvFRF9 was mainly expressed in the nuclei of tobacco epidermal cells and protoplast of arabidopsis. Further, transgenic arabidopsis plants with HvFRF9 overexpression were generated to verify the role of HvFRF9 in drought resistance. Under drought stress, leaf chlorosis and wilting, MDA and O2 ⁻ contents were significantly lower, meanwhile, fresh weight, root length, PRO content, and SOD, CAT and POD activities were significantly higher in HvFRF9-overexpressing arabidopsis plants than in wild-type plants. Therefore, overexpression of HvFRF9 could significantly enhance the drought resistance in arabidopsis. These results suggested that HvFRF9 may play a key role in drought resistance in barley by increasing the absorption and transportation of water and the activity of antioxidant enzymes. This study provided a theoretical basis for drought resistance in barley and provided new genes for drought resistance breeding.
... This broad geographic distribution encompasses substantial variation in nucleotide sequences, and even subtle differences induce large variation in phenotypic traits such as stress tolerance (20)(21)(22)(23). Studies of A. thaliana accessions have provided new insights into genome evolution, differentiation among geographic populations, and selective mechanisms that shape complex trait variation in nature (21,24,25). Quantitative trait loci for high-temperature germination and fertility under heat stress have been reported (26,27), yet the variation in heat tolerance during postgermination growth and the underlying mechanisms remain underexplored. ...
Article
Full-text available
Natural genetic variation has facilitated the identification of genes underlying complex traits such as stress tolerances. We here evaluated the long-term (L-) heat tolerance (37°C for 5 days) of 174 Arabidopsis thaliana accessions and short-term (S-) heat tolerance (42°C, 50 min) of 88 accessions and found extensive variation, respectively. Interestingly, L-heat–tolerant accessions are not necessarily S-heat tolerant, suggesting that the tolerance mechanisms are different. To elucidate the mechanisms underlying the variation, we performed a chromosomal mapping using the F2 progeny of a cross between Ms-0 (a hypersensitive accession) and Col-0 (a tolerant accession) and found a single locus responsible for the difference in L-heat tolerance between them, which we named Long-term Heat Tolerance 1 (LHT1). LHT1 is identical to MAC7, which encodes a putative RNA helicase involved in mRNA splicing as a component of the MOS4 complex. We found one amino acid deletion in LHT1 of Ms-0 that causes a loss of function. Arabidopsis mutants of other core components of the MOS4 complex—mos4-2, cdc5-1, mac3a mac3b, and prl1 prl2—also showed hypersensitivity to L-heat stress, suggesting that the MOS4 complex plays an important role in L-heat stress responses. L-heat stress induced mRNA processing–related genes and compromised alternative splicing. Loss of LHT1 function caused genome-wide detrimental splicing events, which are thought to produce nonfunctional mRNAs that include retained introns under L-heat stress. These findings suggest that maintaining proper alternative splicing under L-heat stress is important in the heat tolerance of A. thaliana.
... Despite the limitations of GEA, an extension to the RDA framework has been shown to accurately predict multivariate quantitative traits from landscape genomic data across a range of demographic and selection scenarios and complex genomic architectures 51 . Finally, additional evidence is needed to corroborate genetic-environment associations and their involvement in climate adaptation, including experimental approaches that provide evidence of fitness differences associated with candidate variants 56,57 . For example, in common garden experiments, individuals from different environments are reared in a common environment to elucidate the genetic and environmental components that underlie phenotypic differences. ...
Article
Full-text available
All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.
... These disturbed ecosystems are in accordance with the ecology of A. thaliana, known as an opportunistic weed and pioneer colonizer of poor, ruderal soils. This is in line with the classification of A. thaliana as an early succession plant species, having a rapid life cycle and high levels of phenotypic plasticity [22,23]. This early succession strategy is in contrast with those of more competitive mid and late succession plant species that sequentially replace early succession plant species after several years without disturbance [24]. ...
Article
Full-text available
Background: Soil microbiomes are increasingly acknowledged to affect plant functioning. Research in molecular model species Arabidopsis thaliana has given detailed insights of such plant-microbiome interactions. However, the circumstances under which natural A. thaliana plants have been studied so far might represent only a subset of A. thaliana's full ecological context and potential biotic diversity of its root-associated microbiome. Results: We collected A. thaliana root-associated soils from a secondary succession gradient covering 40 years of land abandonment. All field sites were situated on the same parent soil material and in the same climatic region. By sequencing the bacterial and fungal communities and soil abiotic analysis we discovered differences in both the biotic and abiotic composition of the root-associated soil of A. thaliana and these differences are in accordance with the successional class of the field sites. As the studied sites all have been under (former) agricultural use, and a climatic cline is absent, we were able to reveal a more complete variety of ecological contexts A. thaliana can appear and sustain in. Conclusions: Our findings lead to the conclusion that although A. thaliana is considered a pioneer plant species and previously almost exclusively studied in early succession and disturbed sites, plants can successfully establish in soils which have experienced years of ecological development. Thereby, A. thaliana can be exposed to a much wider variation in soil ecological context than is currently presumed. This knowledge opens up new opportunities to enhance our understanding of causal plant-microbiome interactions as A. thaliana cannot only grow in contrasting soil biotic and abiotic conditions along a latitudinal gradient, but also when those conditions vary along a secondary succession gradient. Future research could give insights in important plant factors to grow in more ecologically complex later-secondary succession soils, which is an impending direction of our current agricultural systems.
Article
Taking advantage of natural variation promotes our understanding of phenotypic diversity and trait evolution, ultimately accelerating plant breeding, in which the identification of causal variations is critical. To date, sequence variations in the coding region and transcription level polymorphisms caused by variations in the promoter have been prioritized. An upstream open reading frame (uORF) in the 5' untranslated region (5' UTR) regulates gene expression at the post-transcription or translation level. In recent years, studies have demonstrated that natural uORF variations shape phenotypic diversity. This opinion article highlights recent researches and speculates on future directions for natural uORF variation in plants.
Article
As the global climate crisis continues, predictions concerning how wild populations will respond to changing climate conditions are informed by an understanding of how populations have responded and/or adapted to climate variables in the past. Changes in the local biotic and abiotic environment can drive differences in phenology, physiology, morphology and demography between populations leading to local adaptation, yet the molecular basis of adaptive evolution in wild non-model organisms is poorly understood. We leverage comparisons between two lineages of Calochortus venustus occurring along parallel transects that allow us to identify loci under selection and measure clinal variation in allele frequencies as evidence of population-specific responses to selection along climatic gradients. We identify targets of selection by distinguishing loci that are outliers to population structure and by using genotype-environment associations across transects to detect loci under selection from each of nine climatic variables. Despite gene flow between individuals of different floral phenotypes and between populations, we find evidence of ecological specialization at the molecular level, including genes associated with key plant functions linked to plant adaptation to California's Mediterranean climate. Single-nucleotide polymorphisms (SNPs) present in both transects show similar trends in allelic similarity across latitudes indicating parallel adaptation to northern climates. Comparisons between eastern and western populations across latitudes indicate divergent genetic evolution between transects, suggesting local adaptation to either coastal or inland habitats. Our study is among the first to show repeated allelic variation across climatic clines in a non-model organism.
Article
Full-text available
Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.
Article
Full-text available
— The genetic basis of species differences provides insight into the mode and tempo of phenotypic divergence. We investigate the genetic basis of floral differences between two closely related plant taxa with highly divergent mating systems,Mimulus guttatus (large-flowered outcrosser) andM. nasutus (small-flowered selfer). We had previously constructed a framework genetic linkage map of the hybrid genome containing 174 markers spanning approximately 1800 cM on 14 linkage groups. In this study, we analyze the genetics of 16 floral, reproductive, and vegetative characters measured in a large segregating M. nasutus X M. guttatus F2 population (N= 526) and in replicates of the parental lines and F1 hybrids. Phenotypic analyses reveal strong genetic correlations among floral traits and epistatic breakdown of male and female fertility traits in the F2 hybrids. We use multitrait composite interval mapping to jointly locate and characterize quantitative trait loci (QTLs) underlying interspecific differences in seven floral traits. We identified 24 floral QTLs, most of which affected multiple traits. The large number of QTLs affecting each trait (mean = 13, range = 11–15) indicates a strikingly polygenic basis for floral divergence in this system. In general, QTL effects are small relative to both interspecific differences and environmental variation within genotypes, ruling out QTLs of major effect as contributors to floral divergence between M. guttatus andM. nasutus. QTLs show no pattern of directional dominance. Floral characters associated with pollinator attraction (corolla width) and self-pollen deposition (stigma-anther distance) share several pleiotropic or linked QTLs, but unshared QTLs may have allowed selfing to evolve independently from flower size. We discuss the polygenic nature of divergence between M. nasutus and M. guttatus in light of theoretical work on the evolution of selfing, genetics of adaptation, and maintenance of variation within populations.
Article
Phenotypic plasticity and genotype-environment interactions (GEI) play a prominent role in plant morphological diversity and in the potential functional capacities of plant life-history traits. The genetic basis of plasticity and GEI, however, is poorly understood in most organisms. In this report, inflorescence development patterns in Arabidopsis thaliana were examined under different, ecologically relevant photoperiod environments for two recombinant inbred mapping populations (Ler × Col and Cvi × Ler) using a combination of quantitative genetics and quantitative trait locus (QTL) mapping. Plasticity and GEI were regularly observed for the majority of 13 inflorescence traits. These observations can be attributable (at least partly) to variable effects of specific QTL. Pooled across traits, 12/44 (27.3%) and 32/62 (51.6%) of QTL exhibited significant QTL × environment interactions in the Ler × Col and Cvi × Ler lines, respectively. These interactions were attributable to changes in magnitude of effect of QTL more often than to changes in rank order (sign) of effect. Multiple QTL × environment interactions (in Cvi × Ler) clustered in two genomic regions on chromosomes 1 and 5, indicating a disproportionate contribution of these regions to the phenotypic patterns observed. High-resolution mapping will be necessary to distinguish between the alternative explanations of pleiotropy and tight linkage among multiple genes.
Article
The use of regression techniques for estimating the direction and magnitude of selection from measurements on phenotypes has become widespread in field studies. A potential problem with these techniques is that environmental correlations between fitness and the traits examined may produce biased estimates of selection gradients. This report demonstrates that the phenotypic covariance between fitness and a trait, used as an estimate of the selection differential in estimating selection gradients, has two components: a component induced by selection itself and a component due to the effect of environmental factors on fitness. The second component is shown to be responsible for biases in estimates of selection gradients. The use of regressions involving genotypic and breeding values instead of phenotypic values can yield estimates of selection gradients that are not biased by environmental covariances. Statistical methods for estimating the coefficients of such regressions, and for testing for biases in regressions involving phenotypic values, are described.
Article
We discuss the necessary and sufficient conditions for identifying the cause of natural selection on a phenotypic trait. We reexamine the observational methods recently proposed for measuring selection in natural populations and illustrate why the multivariate analysis of selection is insufficient for identifying the causal agents of selection. We discuss how the observational approach of multivariate selection analysis can be complemented by experimental manipulations of the phenotypic distribution and the environment to identify not only how selection is operating on the phenotypic distribution but also why it operates in the observed manner. A significant point of departure of our work from recent discussions is in regard to the role of the environment in the study of natural selection. Instead of viewing the environment as a source of unwanted variation that obscures the relationship between phenotype and fitness, we view fitness as arising from the interaction of the phenotype with the environment. The biotic and abiotic environment is the context that gives rise to the relationship between phenotype and fitness (selection). The analysis of the causes of selection is in essence a problem in ecology. The experimental study of the association between selection gradients and environmental characteristics is necessary to identify the agents of natural selection. We recommend research methods for identifying the agency of selection that depend upon a reciprocity between the observational approach of multivariate selection analysis and the manipulative approach of field experiments in evolutionary ecology.
Article
The combined knowledge of the Arabidopsis genome and transcriptome now allows to get an integrated view of the dynamics and evolution of metabolic pathways in plants. We used publicly available sets of microarray data obtained in a wide range of different stress and developmental conditions to investigate the co-expression of genes encoding enzymes of secondary metabolism pathways, in particular indoles, phenylpropanoids, and flavonoids. We performed hierarchical clustering of gene expression profiles and found that major enzymes of each pathway display a clear and robust co-expression throughout all the conditions studied. Moreover, detailed analysis evidenced that some genes display co-regulation in particular physiological conditions only, certainly reflecting their modular recruitment into stress- or developmentally regulated biosynthetic pathways. The combination of these microarray data with sequence analysis allows to draw very precise hypotheses on the function of otherwise uncharacterized genes. To illustrate this approach, we focused our analysis on secondary metabolism glycosyltransferases (UGTs), a multigenic family involved in the conjugation of small molecules to sugars like glucose. We propose that UGT74B1 and UGT74C1 may be involved in aromatic and aliphatic glucosinolates synthesis, respectively. We also suggest that UGT75C1 may function as an anthocyanin-5-O-glucosyltransferase in planta. Therefore, this data-mining approach appears very powerful for the functional prediction of unknown genes, and could be transposed to virtually any other gene family. Finally, we suggest that analysis of expression pattern divergence of duplicated genes also provides some insight into the mechanisms of metabolic pathway evolution.
Article
The evolution of the realized climatic niche in the genus Arabidopsis was studied using an almost complete phylogenetic tree based on DNA sequences of the ribosomal internal transcribed spacers. The realized climatic niche (climate space) was determined by the intersections of the distribution ranges of the taxa with climate data and is presented in temperature/precipitation diagrams. A positive correlation exists between the climate spaces of the taxa and their range sizes. The diagrams revealed a core climate; that is, a climate space in which all taxa co-exist. This core climate is almost identical to the most parsimonious reconstruction of the genus' ancestral climate space and may be considered an ancestral state of these characters. Mapping the evolutionary changes occurring in the realized climatic space on the phylogenetic tree from the core climate proved to be the most parsimonious procedure. The character complex is homoplastic; that is, many parallel evolutionary events have occurred in the subclades. With the exception of A. thaliana, which is sister to the other species of the genus and occupies a very large climate space, the late-diverged taxa of the other subclades experienced great evolutionary changes whereas the realized climate space of the taxa that diverged earlier resembles the core climate. The latter also show some parallel contractions in the climate space. It is hypothesized that the diversification of Arabidopsis may have started from small to midsized ranges in a temperate climate.
Article
Abstract Germination timing of Arabidopsis thaliana displays strong plasticity to geographic location and seasonal conditions experienced by seeds. We identified which plastic responses were adaptive using recombinant inbred lines in a field manipulation of geographic location (Kentucky, KY; Rhode Island, RI), maternal photoperiod (14-h and 10- h days), and season of dispersal (June and November). Transgressive segregation created novel genotypes that had either higher fitness or lower fitness in certain environments than either parent. Natural selection on germination timing and its variation explained 72% of the variance in fitness among genotypes in KY, 30% in June-dispersed seeds in RI, but only 4% in November-dispersed seeds in RI. Therefore, natural selection on germination timing is an extremely efficient sieve that can determine which genotypes can persist in some locations, and its efficiency is geographically variable and depends on other aspects of life history. We found no evidence for adaptive responses to maternal photoperiod during seed maturation. We did find adaptive plasticity to season of seed dispersal in RI. Seeds dispersed in June postponed germination, which was adaptive, while seeds dispersed in November accelerated germination, which was also adaptive. We also found maladaptive plasticity to geographic location for seeds dispersed in June, such that seeds dispersed in KY germinated much sooner than the optimum time. Consequently, bet hedging in germination timing was favorable in KY; genotypes with more variation in germination timing had higher fitness because greater variation was associated with postponed germination. Selection on germination timing varied across geographic location, indicating that germination timing can be a critical stage in the establishment of genotypes in new locations. The rate of evolution of germination timing may therefore strongly influence the rate at which species can expand their range.