Genetic Architecture of Flowering-Time Variation in
Brachypodium distachyon1[OPEN]
Daniel P. Woods, Ryland Bednarek, Frédéric Bouché, Sean P. Gordon, John P. Vogel, David F. Garvin,
and Richard M. Amasino
Laboratory of Genetics, University of Wisconsin-Madison, Madison, Wisconsin 53706 (D.P.W., R.M.A.); United
States Department of Energy Great Lakes Bioenergy Research Center, University of Wisconsin-Madison,
Madison, Wisconsin 53706 (D.P.W., R.M.A.); Department of Biochemistry, University of Wisconsin-Madison,
Madison, Wisconsin 53706 (D.P.W., R.B., F.B., R.M.A.); United States Department of Energy Joint Genome
Institute, Walnut Creek, California 94598 (S.P.G., J.P.V.); and USDA-ARS Plant Science Research Unit,
University of Minnesota, Department of Agronomy and Plant Genetics, St. Paul, Minnesota 55108 (D.F.G.)
ORCID IDs: 0000-0002-1498-5707 (D.P.W.); 0000-0002-8017-0071 (F.B.); 0000-0003-3431-5804 (S.P.G.); 0000-0003-1786-2689 (J.P.V.);
0000-0003-3068-5402 (R.M.A.).
The transition to reproductive development is a crucial step in the plant life cycle, and the timing of this transition is an important
factor in crop yields. Here, we report new insights into the genetic control of natural variation in flowering time in Brachypodium
distachyon, a nondomesticated pooid grass closely related to cereals such as wheat (Triticum spp.) and barley (Hordeum vulgare L.). A
recombinant inbred line population derived from a cross between the rapid-flowering accession Bd21 and the delayed-flowering
accession Bd1-1 were grown in a variety of environmental conditions to enable exploration of the genetic architecture of flowering
time. A genotyping-by-sequencing approach was used to develop SNP markers for genetic map construction, and quantitative trait
loci (QTLs) that control differences in flowering time were identified. Many of the flowering-time QTLs are detected across a range
of photoperiod and vernalization conditions, suggesting that the genetic control of flowering within this population is robust.
The two major QTLs identified in undomesticated B. distachyon colocalize with VERNALIZATION1/PHYTOCHROME C and
VERNALIZATION2, loci identified as flowering regulators in the domesticated crops wheat and barley. This suggests that
variation in flowering time is controlled in part by a set of genes broadly conserved within pooid grasses.
Proper timing of flowering is a major developmental
decision in the life history of plants, and the genetic
manipulation of flowering time has played a crucial
role in the domestication and spread of cereal crops
such as wheat (Triticum spp.), barley (Hordeum vulgare
L.), rice (Oryza sativa), and maize (Zea mays; Greenup
et al., 2009; Hung et al., 2012). Moreover, the modulation of flowering time has been important in the diversification of temperate (pooid) grasses into higher
latitudes with colder winters (Woods et al., 2016;
Fjellheim et al., 2014). An important environmental cue
that often affects flowering is day (d) length (photoperiod; Song et al., 2015). Many plants adapted to temperate regions flower in response to increasing day
lengths (long-d plants), in contrast to many plants from
the tropics that flower as day length decreases (short-d
plants). In addition, some plants adapted to temperate
climates have taken on a biennial/winter annual life
history strategy in which plants become established in
the fall, then overwinter and flower rapidly in the
spring as day lengths increase (Amasino 2010). Essential to this strategy is the prevention of flowering before
winter because cold temperatures could damage delicate floral structures, preventing reproduction. Thus,
plants have evolved ways to repress flowering in the
fall and alleviate this repression by sensing the passing of winter to establish competence to flower. This
process, by which the block to flowering is alleviated by
exposure to prolonged time in cold temperatures, is
known as vernalization (Chouard 1960).
Many varieties of wheat, barley, oats (Avena sativa),
and rye (Secale cereale) require vernalization to flower.
Winter annual cereal varieties require vernalization to
flower, whereas varieties that can flower in the absence
of vernalization are referred to as “spring annuals”.
Studying the allelic variation that exists between spring
and winter varieties has led to the identification of
genes involved in the pooid grass vernalization regulatory pathway. This molecular model of vernalization
responsiveness involves a leaf-specific regulatory loop involving VERNALIZATION1 (VRN1), VERNALIZATION2
(VRN2), and VERNALIZATION3 (VRN3; Greenup
et al., 2009; Distelfeld and Dubcovsky 2010). VRN3
is homologous to Arabidopsis (Arabidopsis thaliana)
FLOWERING LOCUS T (FT), a small mobile protein
known as “florigen”, that moves from leaves to the
shoot apical meristem to promote flowering (Corbesier
et al., 2007; Zeevaart 2008). During the growth of
winter-annual cereals in the fall, the CONSTANS-like
gene VRN2 represses FT to prevent flowering, and the
FRUITFULL-like MADS box transcription factor VRN1
is transcribed at very low levels (Yan et al., 2004;
Greenup et al., 2009). During winter, VRN1 is induced,
causing the repression of VRN2 and the consequent
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269
Woods et al.
derepression of FT (Distelfeld and Dubcovsky 2010;
Yan et al., 2003). In addition, FT requires long d to become activated by the pseudo-response regulator,
PHOTOPERIOD1 (PPD1), through yet unknown mechanisms; thus, flowering only occurs after winter during
the lengthening days of spring and early summer
(Turner et al., 2005; Shaw et al., 2013).
The above model is primarily based on the study of
epistatic relationships among VRN1, VRN2, PPD1, and
FT in domesticated varieties of wheat and barley
(Trevaskis et al., 2003; Yan et al., 2003, 2004, 2006;
Dubcovsky et al., 2005; Karsai et al., 2005; Turner et al.,
2005). Some varieties of spring barley and spring wheat
that do not require vernalization either carry deletions
of the VRN2 locus or point mutations within its conserved CCT domain (Yan et al., 2004; Dubcovsky et al.,
2005; Karsai et al., 2005; von Zitzewitz et al., 2005).
Therefore, the activity of VRN2 is necessary for a vernalization requirement that was recently proven in hexaploid
wheat (Kippes et al., 2016). Other spring varieties have
dominant alleles of VRN1 or FT that are constitutively
activated and epistatic to functional VRN2 alleles (Yan
et al., 2003, 2004, 2006; Fu et al., 2005; Loukoianov et al.,
2005; von Zitzewitz et al., 2005). In barley, allelic variation
at the PPD1 locus results in two types of spring varieties
that are either sensitive to photoperiod and early flowering (PPD-H1), or insensitive to photoperiod and later
flowering (ppd-h1; Turner et al., 2005).
Due to its small, fully sequenced diploid genome
(IBI, 2010), its small physical stature, and its high recombination rate (Brkljacic et al., 2011; Brutnell et al.,
1
R.M.A.’s laboratory was funded by the National Science Foundation under grant no. IOS-1258126, and the Great Lakes Bioenergy
Research Center (Department of Energy Biological and Environmental Research Office of Science grant no. DE-FCO2-07ER64494); D.P.W.
was funded in part by a National Institutes of Health-sponsored predoctoral training fellowship to the University of Wisconsin Genetics
Training Program; F.B. thanks the Belgian American Educational
Foundation (BAEF) for their post-doctoral fellowship; J.P.V. and
S.P.G. were funded by the U.S. Department of Energy Joint Genome
Institute (a Department of Energy Office of Science User Facility),
which is supported under contract no. DE-AC02-05CH11231, with
additional funding provided by Office of Biological and Environmental Research, Office of Science, U.S. Department of Energy, under
interagency agreement no. DE-SC0006999; and D.F.G. was supported
by USDA-ARS CRIS project no. 5062-21000-030-00D.
* Address correspondence to [email protected].
The author responsible for distribution of materials integral to the
findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is:
Richard Amasino ([email protected]).
D.P.W., D.F.G., and R.M.A. conceived and designed research
plans; D.F.G. developed the RIL population and conducted preliminary phenotyping on earlier generations during RIL development;
D.P.W. and R.B. phenotyped population and prepared samples for
sequencing; S.P.G. and J.P.V. developed the genetic map; F.B. performed QTL analysis and prepared all figures with input from D.P.W.,
R.B., and R.M.A.; D.P.W., R.B., and R.M.A. wrote the article with
contributions and approval of all authors.
[OPEN]
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www.plantphysiol.org/cgi/doi/10.1104/pp.16.01178
2015), B. distachyon is an attractive model plant for
studying a number of different traits including flowering. Like wheat and barley, B. distachyon accessions
exhibit a considerable amount of natural variation in
flowering responses (Ream et al., 2014; Tyler et al., 2014).
However, unlike wheat and barley, which fall into two
broad categories for flowering requirements (winter
and spring varieties), most of the B. distachyon accessions studied to date are likely to be some form of winter
annual in their native environments because they all
require vernalization to flower rapidly when grown
in native photoperiods in growth chambers: under artificial 20-h-long d, accessions such as Bd21 will flower
quite rapidly without vernalization (Vogel et al., 2006;
Ream et al., 2014); however, when grown under 14 h d to
15 h d, Bd21 requires a very short (2 to 3 weeks) period of
vernalization to flower rapidly (Ream et al., 2014). In
contrast, many B. distachyon accessions such as Bd1-1 are
delayed in flowering even under artificially long d and
require an extended period of cold (at least 6 weeks) to
saturate their vernalization requirement (Ream et al.,
2014). This considerable natural variation in flowering
time can be used to explore the genetic architecture of
flowering in an undomesticated pooid grass and contribute insights into the evolution of the vernalization
response within pooids. Furthermore, unlike wheat
and barley, little is known about the molecular basis of
natural variation in flowering-time responses in other
pooid grasses including B. distachyon.
In this study, we developed a recombinant inbred
line (RIL) population from a cross between Bd21 (rapidflowering accession) and Bd1-1 (delayed-flowering accession) to explore the genetic architecture of flowering
time in B. distachyon. We observed significant variation
in flowering behavior among the 142 RILs in response
to various environmental conditions. We used genotype by sequencing (GBS) to create a genetic map for the
RIL population, and then conducted a quantitative trait
locus (QTL) analysis to determine the genetic architecture of flowering regulation in this population. We
identified six significant QTLs, several of which were
present in multiple environments tested. Interestingly,
VRN1 and VRN2 underlie two of the six QTLs. We also
identified QTL in which no flowering-time candidate
genes are present, and thus represent novel loci regulating flowering time. The development and genotyping
of this RIL population may prove useful in the dissection
of other traits in B. distachyon.
RESULTS
Development of a Recombinant Inbred Line Population
from a Cross between Two Diverse B. distachyon
Accessions that Have Different Flowering Behaviors
The accessions Bd21 and Bd1-1 differ considerably in
flowering time and requirement for vernalization. We
previously characterized Bd21 as “extremely rapid
flowering” because it flowers in less than 40 d after
germination in both 16-h d and 20-h day lengths
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Flowering-Time QTL in B. distachyon
Figure 1. Vernalization time course in B. distachyon accessions Bd21 and Bd1-1. A and C, Photographs of representative plants
taken after 60 d of growth. Imbibed seeds of Bd21 and Bd1-1 were cold treated at 5°C in soil in an 8-h photoperiod for the indicated length of time (weeks), followed by outgrowth in a growth chamber set to 16-h light/8-h dark (A) or 20-h light/4-h dark (C).
B and D, Flowering time measured as the number of days to spike emergence from the end of cold treatment. Arrows indicate
treatments where plants did not flower within 120 d of the experiment.
without vernalization (Ream et al., 2014; Fig. 1, A–D). In
contrast, Bd1-1 does not flower rapidly without vernalization (greater than 120 d to flower in 20-h and 16-h
photoperiod) and requires 6 weeks of cold to saturate
its vernalization requirement (Ream et al., 2014; Fig. 1,
A–D). A cross between these two phenotypically diverse
accessions was used to develop a RIL population (see
Material and Methods for details of RIL development).
To develop a genetic map of the Bd21 X Bd1-1 RIL
population, we utilized reduced representation genotype by sequencing (Elshire et al., 2011). After several
filtering steps, 1693 markers covering the entire genome
were selected (Fig. 2A). The analysis of the recombination frequency between markers identified five major
linkage groups corresponding to the five chromosomes
of B. distachyon, and confirmed the absence of largescale rearrangements between the genomes of Bd21
and Bd1-1 (Fig. 2B). The final genetic map consists of
1693 SNP markers and a cumulative size of 1456.4 cM
(Fig. 2C, Supplemental Table S1), which is similar to
previously characterized RIL populations of Bd3-1 and
Bd21 (Cui et al., 2012; Des Marais et al., 2016), and
confirms the high recombination rate of B. distachyon
compared with other grass species. The observed heterozygosity of selected markers (1.5%) matches expected frequencies for an F7 population (1.7%).
Variation in Flowering Time in the Bd21 X Bd11 RIL Population
We characterized the F7 RILs using various vernalization and photoperiod treatments. Specifically, we
grew the RIL population in 16-h and 20-h photoperiods
after 0, 2, 3, and 6 weeks of vernalization and scored
days to heading and the number of leaves on the primary culm at flowering (Supplemental Figs. S1 and
S2; 6-week vernalization data not shown because no
flowering-time variation in the population was observed). Previous studies in several species have found
a strong positive correlation between days to heading
and the number of leaves at flowering (leaf number
provides a developmental assessment; Salomé et al.,
2011; Ream et al., 2014), indicating that these two traits
are highly correlated in natural accessions. Under all
conditions we observed a similar linear relationship
between days to heading and leaf number, indicating
that later flowering plants were indeed developmentally delayed (Supplemental Fig. S3). We observed
flowering variation within the RIL population under all
conditions except after 6 weeks of vernalization, in which
all plants flowered rapidly as expected (Fig. 3; 6-week
vernalization data not shown). The greatest range in
flowering times was observed in 20-h nonvernalized and
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Woods et al.
Figure 2. Graphical representation of the estimated linkage map for the Bd21 X Bd1-1 RIL mapping population. A, Physical
position of selected markers along B. distachyon chromosomes. B, Pairwise recombination fraction (upper-left triangle) and LOD
scores for all pairs of markers ordered according to their position on the genome shown in (A). Yellow indicates linked markers;
dark blue indicate unlinked markers. Axes show marker numbers. C, Genetic map of selected markers. Distances are shown in
centimorgans. Mb, megabase; cM, centimorgans.
16-h 2-week vernalized conditions, in which some lines
flowered as early as 15 d while others failed to flower by
the end of the 120 d experiment (Fig. 3; Supplemental Fig.
S1). Additionally, considerable flowering-time variation
was observed in the RIL population under 20-h 2-week
vernalization conditions, in which flowering occurred as
early as 17 d in some lines and as late as 109 d in other
lines (Fig. 3). The majority of nonvernalized lines grown
under 16 h of light flowered between 60 and 120 d,
whereas after 3 weeks of vernalization the majority of the
populations flowered between 20 d and 30 d with the
latest lines flowering around d 50 (Fig. 3).
QTL Mapping of Flowering Time in B. distachyon
To identify regions of the B. distachyon genome contributing to the observed flowering variation in the RIL
population, we performed a QTL analysis on the population for those photoperiod and vernalization treatments resulting in phenotypic variation for flowering.
We detected two major flowering QTLs that correlate
with flowering-time differences in multiple environmental conditions (Fig. 4; Supplemental Table S2).
Flowering-time related traits such as days to heading
and leaf number were highly correlated and confidence intervals of QTL peaks for these traits usually
overlapped within the various environmental conditions (Fig. 4). The two major QTLs were found on
chromosome 1 (QTL1) and chromosome 3 (QTL2) and
were robustly observed across several different environments. QTL1 was detected under 20 h nonvernalized,
20-h 2-week vernalized, and 16-h 3-week vernalized
conditions. Also, QTL1 was close to reaching the
computed significance threshold under 16-h 2-week
vernalized conditions. Depending upon the condition,
QTL1 (peak marker Bd1_6006000) explains between
1.8% and 20.5% of the phenotypic variance observed
in this mapping population (Supplemental Table S2).
Although several genes are within the QTL interval
(46 cM to 61cM in 20 h nonvernalized conditions), the
tightly linked flowering-time genes VRN1 and PHYC
are likely candidates because previous reverse and
forward genetic studies have shown that both genes
play important roles in flowering-time regulation
in B. distachyon as well as in wheat (Woods et al.,
2014b, 2016; Chen and Dubcovsky 2012; Chen et al.,
2014). The major QTL on chromosome 3 (QTL2) was
detected only under 16-h nonvernalized and 20-h nonvernalized conditions with peak LOD scores under
16-h (LOD 5.42) and 20-h (LOD 5.23; Fig. 4). QTL2
(peak marker Bd3_8505000) explains between 6.5%
and 20.1% of the phenotypic variance observed within
the mapping population and, like QTL1, its mapping
interval (60cM-78cM in 16-h nonvernalized) spans
several genes including the floral repressor VRN2
(Woods et al., 2016), which is a likely candidate gene
for the flowering-time differences (Fig. 4).
When data from the 20-h nonvernalized condition were analyzed using a two-QTL model, we observed strong additive effects of QTL1 and QTL2
(Supplemental Fig. S5). Bd21 alleles at QTL1 and QTL2
were associated with rapid flowering, whereas RILs
with the Bd1-1 alleles at both QTL1 and QTL2 were
typically the most delayed flowering lines within the
population (Fig. 5). Despite this general trend for
delayed flowering with the Bd1-1 alleles for QTL1 and
QTL2, there were several RILs, which were still rapidflowering (Fig. 5). Furthermore, if a particular RIL was
mixed for either the Bd21 or Bd1-1 genotype at QTL1
and QTL2, this resulted on average in an intermediate
flowering time of approximately 50 d, but with high
variability (Fig. 5). Thus, although the Bd21 genotype at
QTL1 and QTL2 is associated with rapid flowering and
the Bd1-1 genotype at QTL1 and QTL2 is associated
with delayed flowering, there are exceptions, suggesting the presence of additional loci that are likely to
be contributing to flowering-time variation between
B. distachyon accessions.
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Flowering-Time QTL in B. distachyon
Figure 3. Flowering-time distribution within the RIL population under five environmental treatments: 16-h long d nonvernalized
(16-h LD NV), 20-h long d nonvernalized (20-h LD NV), 16- and 20-h long d after 2-week vernalization (16- and 20-h LD 2W
Vern), and 16-h long d after 3 weeks of vernalization (16-h LD 3W Vern). Days to heading (x axis) indicate the number of days to
spike emergence once plants germinated. The number of lines within the RIL population that flowered within ranges of 10 d is
indicated by the y axis. White arrows indicate the average days to heading for Bd21 plants (n = 12) and black arrows indicate the
average days to for Bd1-1 plants (n = 12).
In addition to the two major QTLs described above,
we also detected four minor QTLs present in at least one
environmental condition (Fig. 4; Supplemental Table
S2). QTL3 was detected under 20-h nonvernalized and
20-h 2-week vernalized conditions. QTL3 explains 1.5%
to 14.3% of the phenotypic variance observed in this
mapping population. Interestingly QTL3 colocalizes
with FD, approximately 10 cM from the end of chromosome 3 (Fig. 4). FD is a basic Leu zipper domain
transcription factor that, in Arabidopsis, interacts with
FT to turn on floral homeotic genes (Abe et al., 2005).
Three other minor QTLs (QTL4, 5, and 6) are also present on chromosome 3 and contribute from 5.8% to
12.8% of the phenotypic variance in vernalized populations, and no previously identified flowering-time loci
are within these QTL intervals (Fig. 4; Supplemental
Fig. S6; Supplemental Table S2).
Sequence Variants in VRN1, PHYC, VRN2, and FD
We explored the sequence variation around candidate flowering-time genes VRN1, PHYC, VRN2, and
FD, which colocalize to the most significant QTL peaks
(QTL1, 2, and 3). We identified several sequence variants in different alleles of these genes; however, we did
not find any obvious variants that might disrupt gene
function such as large deletions within the coding region or nonsynonymous changes leading to a premature stop codon, which have been found between the
VRN1 and VRN2 genes of spring and winter annual
varieties of wheat and barley (Supplemental Fig. S7).
We did, however, find several indels within both the
promoter and the first intron of VRN1 (Supplemental
Fig. S7). In wheat and barley, the first intron has been
shown to play an important regulatory role, and indels
within this intron have been associated with the
spring annual habit (Yan et al., 2003; Fu et al., 2005;
von Zitzewitz et al., 2005; Yan et al., 2004). Indeed
previous reports have shown that VRN1 mRNA levels
are higher in Bd21 than Bd1-1 under 20-h nonvernalized
conditions and after 3 weeks of vernalization, which
may reflect the effect of the sequence variants detected
(Ream et al., 2014).
DISCUSSION
In this study we developed a RIL population between
a rapid (Bd21) and a delayed flowering (Bd1-1) accession of B. distachyon (Ream et al., 2014; Vogel et al., 2006)
and used it to evaluate the genetic architecture of
flowering time under a range of environmental conditions. For this study, we developed a high-resolution
genetic map containing 1693 SNP markers using genotyping by sequencing. Flowering times of RILs ranged
from as early as 20 d to greater than 120 d in some environments. We found two major QTLs (QTL1 and
QTL2) and four minor-effect QTLs (QTL3 to QTL6) that
account for most of the observed flowering-time differences. The two major QTLs coincide with the location of
the genes VRN1 and PHYC on chromosome 1 (QTL1)
and VRN2 on chromosome 3 (QTL2). These genes have
previously been shown to play important roles in
flowering-time regulation in B. distachyon, and contribute to variation in flowering-time responses in wheat
and barley (Woods et al., 2014b, 2016; Woods and
Amasino 2015; Distelfeld et al., 2009). Thus, it appears
that allelic variation in VRN1 and VRN2 likely contributes to flowering differences in an undomesticated pooid
grass. However, further fine mapping and functional
analyses will be required to unequivocally establish the
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Woods et al.
Figure 4. Location of flowering-time QTLs under five different environmental conditions. QTLs based on days to heading are
indicated by a solid line whereas the QTLs based on leaf count on the parent culm are indicated by a dotted line. The red
horizontal line represents the threshold of significance (see Materials and Methods). The phenotyping of the mapping population
was repeated, which resulted in similar segregation of flowering-time phenotypes and QTL peaks (data not shown). The name
attributed to the different QTLs (QTL1 to QTL6) and the candidate flowering-time genes underlying each QTL (bold red line)
are shown at the bottom of the diagram. Orange vertical lines indicate candidate flowering-time genes that are not correlated
with QTLs.
genes responsible for the QTLs identified. Additional
minor-effect QTLs we identified indicates that additional
loci contribute to the flowering-time difference between
Bd21 and Bd1-1.
The Genetic Architecture of Flowering Time in
B. distachyon
Characterizing this RIL population enabled us to
evaluate if flowering was controlled by many genes
with small effects, such as in maize (Buckler et al., 2009),
or by a few genes with large effects, such as in Arabidopsis (Salomé et al., 2011), and to determine if the loci
controlling flowering are the same under different day
lengths and vernalization treatments. Under a given
environment, only two to three significant QTLs were
identified, indicating that flowering-time variation
between Bd21 and Bd1-1 is controlled by only a few
genes, similar to what has been shown in wheat, barley,
and Arabidopsis (Distelfeld et al., 2009; Salomé et al.,
2011). QTL1 was the only locus that was uniformly
identified under both vernalized and nonvernalized
conditions and under both 16-h d and 20-h d. In contrast, QTL2 was only identified under nonvernalized
conditions in both 16-h and 20 h conditions. The Bd21
genotype at QTL1 and QTL2 is associated with rapid
flowering RILs and the Bd1-1 allele is associated with
delayed flowering RILs. Although the Bd1-1 genotype
at QTL1 and QTL2 was strongly associated with
delayed flowering, there were several RILs containing
these QTLs that still flowered rapidly, suggesting additional genes contribute to promoting flowering, and
these RILs provide an entry point for molecularly
identifying these additional loci.
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Flowering-Time QTL in B. distachyon
LOCUS C and FRIGIDA, two genes responsible for
much of the flowering-time variation among accessions
of Arabidopsis. FRIGIDA and FLOWERING LOCUS C
were later identified after additional well admixed
Arabidopsis populations were included (Salomé
et al., 2011). The increase in the number of sequenced
B. distachyon accessions will help enhance the resolution
of GWAS, thus improving the identification of flowering candidate genes.
Candidate Flowering-Time Genes Underlying the QTL
Figure 5. Phenotype by genotype influence on flowering for nonvernalized plants grown in 20-h-long d. Phenotype by genotype plot for
the two major loci (QTL1, VRN1/PHYC candidate and QTL2, VRN2
candidate) influencing flowering time in the Bd21 X Bd1-1 RIL population grown in 20 h nonvernalized conditions in which both QTLs are
simultaneously present. Days to heading results indicate that presence
of the Bd21 genotype at both QTL1 and QTL2 results in rapid flowering
whereas presence of the Bd1-1 genotype at both loci results in delayed
flowering. Difference in letters above box plots (a, b, a,b, c) indicate
statistical significance based on the mean days to heading values between the various genotypes at QTL1 and QTL2 computed with an
ANOVA Tukey’s HSD test (P # 0.01).
An additional study in this focus issue on flowering
and reproduction also characterized flowering time in a
RIL population from a cross between Bd21 and another
delayed flowering accession ABR6 (Bettgenhaeuser
et al., 2016). They also found only a few QTLs with large
effect. One of their major QTL overlaps with QTL2 from
this study, which colocalizes with VRN2, and another
QTL overlaps with QTL4 from this study, which contains no candidate flowering-time genes. Interestingly,
Bettgenhaeuser et al. (2016) did not identify a QTL that
overlaps with QTL1, but they identified a major QTL
that colocalizes under FT. This indicates that VRN2 and
the unknown loci underlying QTL4 are robust across
different environmental conditions and may contribute
to flowering-time variation broadly within Brachypodium.
However, it also highlights that variation in different
genes can also influence flowering-time variation in
different populations that have unique genetic histories and adapted to different environments.
Genome-wide association studies (GWAS) are another approach to decipher the genetic architecture of
traits (Weigel and Nordborg, 2015). Recently, two
flowering-time GWAS in B. distachyon identified nine
and five associated peaks, none of which overlap with
the QTLs identified in this study (Tyler et al., 2016;
Wilson et al., 2015). Thus, the QTL identified in our RIL
population may represent rare alleles that do not surface in GWAS, or the GWAS that was conducted contains too few accessions or compounding population
structures (issues that are common when conducting
GWAS in in-breeding species; Weigel and Nordborg
2015). For example, initial GWAS flowering studies
in Arabidopsis had difficulty identifying FLOWERING
As described above, two previously identified vernalization genes, VRN1 and VRN2, colocalized to
QTL1 and QTL2, respectively. However, no candidate
flowering-time genes underlie QTL4 to QTL6, and thus
these QTLs are likely to be novel loci contributing to
flowering-time variation in B. distachyon. There was no
sequence variation within the coding region of VRN1
between Bd21 and Bd1-1, suggesting that VRN1 is
functional in both accessions. However, we did find
several indels and SNPs within the first intron of VRN1
(Supplemental Fig. S6). Studies of allelic variation of
VRN1 in wheat and barley have shown that indels
within the first intron, influence VRN1 expression (Fu
et al., 2005; Yan et al., 2006). Indeed, there are differences in BdVRN1 expression patterns between Bd21
and Bd1-1 that correlate with differences in flowering
behavior. For example, the length of cold required to
saturate the vernalization response is 2 to 3 weeks in
Bd21 but in Bd1-1 is 6 to 7 weeks (Ream et al., 2014).
Correspondingly, after a 2- to 3-week cold exposure,
BdVRN1 levels are higher in Bd21 than Bd1-1. In addition, in the absence of vernalization, Bd21 flowers
rapidly in 20-h day lengths but Bd1-1 is extremely
delayed. This is correlated with the higher levels of
BdVRN1 mRNA in nonvernalized Bd21 versus Bd1-1.
These expression differences coincide with the QTL1
peak identified after 3 weeks of cold and 20-h nonvernalized conditions, suggesting that the more rapid
flowering of Bd21 after shorter vernalization treatments
followed by 16-h day lengths and in 20-h day lengths
without vernalization may be due to the elevated expression of VRN1. VRN1 and FT form a positive feedback loop to promote flowering in B. distachyon, wheat,
and barley (Ream et al., 2014; Woods et al., 2016; Yan
et al., 2006; Sasani et al., 2009; Shimada et al., 2009;
Distelfeld and Dubcovsky 2010); however, we did not
identify a QTL peak around FT, so the elevated FT expression may be due to the indirect effect of variation in
VRN1 in this population.
PHYC is another candidate gene underlying QTL1,
which might also influence flowering in this mapping
population. PHYC is an essential light receptor for
photoperiodic flowering in pooids (Woods et al., 2014b;
Chen et al., 2014) and allelic variation of PHYC in barley
and pearl millet (Pennisetum glaucum) has been implicated in influencing flowering in these species (Nishida
et al., 2013; Pankin et al., 2014; Saïdou et al., 2014). Allelic
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Woods et al.
variation at PHYC included a single nonsynonymous
variant as well as several SNPs within the promoter region between Bd21 and Bd1-1, which might influence
PHYC function. Mutations in PHYC result in a nonflowering phenotype in B. distachyon even after prolonged
exposure to cold (Woods et al., 2014b); thus, the variants
are unlikely to cause a loss of PHYC function given that
both Bd21 and Bd1-1 respond to vernalization.
As discussed above, VRN2, the candidate gene underlying QTL2, is a floral repressor that is conserved in
grasses (Woods et al., 2016). It was initially hypothesized that Bd21 has a nonfunctional VRN2 allele due
to the rapid flowering of Bd21 when grown under
16-h d or 20-h d (Higgins et al., 2010; Schwartz et al.,
2010). However, Bd21 and other “spring” or “rapidflowering” accessions, such as Bd21-3 and Bd3-1, fail
to flower without vernalization when grown under
shorter more “native” inductive photoperiods (e.g. 14-h d)
without vernalization, revealing a facultative vernalization requirement; thus, all B. distachyon accessions
studied to date may behave as winter annuals in native
environments (Ream et al., 2014; Colton-Gagnon et al.,
2014). Consistent with this winter-annual behavior,
Bd21 has a functional VRN2 ortholog (Ream et al., 2012;
Woods et al., 2016). In support of BdVRN2 being a
repressor of flowering in rapid flowering accessions,
in Bd21-3 BdVRN2 RNAi knock-down lines are
more rapid-flowering and overexpression of BdVRN2
delays flowering (Woods et al., 2016). Despite being a
floral repressor, BdVRN2 mRNA levels in both Bd21
and Bd1-1 do not decrease during vernalization as in
wheat and barley, but in fact increase during the cold
(Ream et al., 2014). Furthermore, BdVRN2 is not repressed by BdVRN1 as it is in wheat and barley (Woods
et al., 2016). Thus, the role of VRN2 as a repressor of
flowering that is necessary for a vernalization requirement is conserved in pooids, but the cold-mediated repression of VRN2 by VRN1 most likely occurred after
B. distachyon diverged from core pooids comprised of
Tritaceae and Poeae tribes (Woods et al., 2016).
These QTL results as well as the recent functional
studies (described above) demonstrating BdVRN2 is
indeed a repressor of flowering in B. distachyon suggest that BdVRN2 provides a basal repressive signal
preventing flowering in the absence of vernalization.
After vernalization, this repression is overcome by the
strong flowering inductive signal provided by BdVRN1
and the BdPHYC-mediated photoperiod pathway. This
model is consistent with our finding that the BdVRN2
peak is only significant in the absence of vernalization
whereas the BdVRN1/PHYC peak is significant under
highly inductive conditions (i.e. 20-h photoperiod
without vernalization and 16-h photoperiod with prior
short vernalization). Hence, we hypothesize that an
increase in the signals from the photoperiod and vernalization pathways overcomes the BdVRN2-mediated
repression of flowering.
As noted above, our QTL results indicate that allelic
variation in a region containing BdVRN2 influences the
difference in flowering time between Bd21 and Bd1-1.
Because BdVRN2 mRNA levels do not vary between
rapid and delayed flowering accessions and the expression before, during, and after cold is the same between Bd21 and Bd1-1 (Ream et al., 2014), it is tempting
to speculate that perhaps BdVRN2 is less biochemically
active in Bd21 versus Bd1-1 and thus, the repression
by BdVRN2 is easier to overcome by BdVRN1/PHYC
leading to more rapid flowering in Bd21 relative to
Bd1-1 without vernalization. If this hypothesis is correct, it is unlikely that variation within the promoter
region or intron of BdVRN2 contributes to flowering differences between Bd21 and Bd1-1. We did, however, find
amino acid variation within the conserved CCT domain
between Bd21 and Bd1-1. A point mutation within this
domain in diploid wheat results in a spring-annual habit
(Yan et al., 2004), and thus structural variants identified in
the CCT domain might also be causative for floweringtime differences between Bd21 and Bd1-1.
In conclusion, we developed a RIL population between two genotypically and phenotypically diverse
accessions (Vogel et al., 2009; Gordon et al., 2014) and
used this population to explore the genetic architecture
of flowering time. We identified six QTLs that control
flowering within this population. Three of these QTLs
are not associated with previously described floweringtime genes, and thus offer an opportunity to expand our
molecular understanding of the control of floweringtime regulation in grasses. Two other QTLs colocalize
with well-described flowering-time genes, demonstrating evolutionary conservation for some molecular aspects of flowering-time regulation between domesticated
and undomesticated pooid grasses. The development of
the RIL population together with its high-density SNP
map should also greatly help in deciphering the genetic
control of other plant traits that vary between Bd21 and
Bd1-1 such as lemma hair formation, cell wall composition, height, and dormancy, to name but a few (Vogel
et al., 2009; Cass et al., 2016; Ream et al., 2014; Barrero
et al., 2012).
MATERIALS AND METHODS
Development of the Bd21 X Bd1-1 Recombinant Inbred
Line Population
A Brachypodium distachyon RIL population was generated from a cross between inbred lines Bd21 (female) and Bd1-1 (male). A single F1 plant was selfpollinated and the resulting F2 seeds were propagated by single-seed descent to
the F6 generation. Individual F6 plants were then selfed to produce 142 F6:7 RILs
for use in genetic analysis and gene mapping (Fig. 3A). Several F7:8 plants per
line were planted to bulk F8 seed.
Growth Conditions and Flowering-Time Phenotyping
Seeds imbibed distilled water overnight at 5°C before they were sowed.
Individual plants were grown in MetroMix 360 (Sungrow) in square 6.5 cm
plastic pots and fertilized every other week after one month of growth with
Peters Excel 15-5-15 Cal-Mag and Peters 10-30-20 Blossom Booster (RJ Peters).
Growth chamber temperatures averaged 22°C during the light period and 18°C
during the dark period. Plants were grown under four T5 fluorescent bulbs
(5000 K; Phillips), and light intensities averaged approximately 150 mmol m22 s–1
at plant level.
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Flowering-Time QTL in B. distachyon
Eight individuals of each of the 142 RILs and both parental lines were grown
in both 20 and 16 h after 0, 2, 3, and 6 weeks of vernalization as imbibed seed in soil
at 5°C under 8-h day lengths. To minimize light intensity differences, individuals within a given RIL and different RILs were randomly assigned different
locations throughout the growth chamber, and plants were rotated two times
per week throughout the growth chamber. (Note: with an imbibed seed, the
photoperiod does not influence the vernalization response (Ream et al., 2014)).
None of the lines had germinated at the end of the vernalization treatment.
Nonvernalized RILs imbibed for 2 d at 4°C, and were sown at the end of the
vernalization treatment for nonvernalized and vernalized plants to be grown in
parallel. Phenotyping of the RIL population in all conditions was repeated with
similar results (data not shown).
Flowering time (days to heading) was measured as the number of days from
emergence of the coleoptile to d 1 that emergence of the spike was detected
(Zadoks scale = 50; Zadoks et al., 1974). The number of leaves derived from the
main (parent) culm was recorded at the time of heading to provide a developmental assessment. Most often the first culm to flower was derived from the
main (parent) culm. Lines that did not flower by the end of the 120 d experiment
were scored as 120 d and 20 leaves, as all plants had greater than or equal to
20 leaves. See Supplemental Table S4 for raw phenotypic data.
Development of a Genetic Map for the Bd21XBd11 RIL Population
DNA Extraction and Sequencing
Leaves from 12 F8 plants per RIL line were harvested and bulked to reconstitute the F7 genotype. Specifically, a 2 cm portion of each leaf was harvested
and placed into 1.2 mL polycarbonate tubes (designed for multiple sample
processing) in liquid nitrogen. Samples were stored at 280°C before being
pulverized to a fine powder by adding a single metal bead and 2X CTAB-PVP
extraction buffer (0.1 M Tris-HCl pH 8.0, 1.4 M NaCl, 0.02 M EDTA, polyvinylpyrrolidone 0.1%, CTAB 2%) to each tube followed by shaking in a bead
mill for 3 min. Samples were then placed at 65°C for 1 h before conducting a
chloroform/isoamyl alcohol (24:1) extraction followed by DNA precipitation
using NaCl and 95% ethanol. DNA concentration was verified using the
Quant-iT PicoGreen dsDNA Kit (Life Technologies).
Libraries were prepared as in Elshire et al. (2011) at the WI-Madison
Biotechnology Center with minimal modification. In short, 50 ng of DNA
was digested using the 5-bp cutter ApeKI (New England Biolabs) after
which bar-coded adapters amenable to Illumina sequencing were added by
ligation with T4 ligase (New England Biolabs). The 96 adapter-ligated
samples were pooled, amplified to provide sufficient DNA (2 mM) for sequencing, and adapter dimers were removed by SPRI bead purification.
Quality and quantity of the finished libraries was assessed using the Agilent
Bioanalyzer High Sensitivity Chip (Agilent Technologies) and Qubit
dsDNA HS Assay Kit (Life Technologies), respectively. Cluster generation
was performed using HiSeq SR Cluster Kit v3 cBot kits (Illumina). Flowcells
were sequenced using single read, 100 bp sequencing and a HiSeq SBS Kit v3
(50 Cycle; Illumina) on a HiSeq2000 sequencer. Images were analyzed using
the standard Illumina Pipeline software (v1.8.2).
SNP Development and Genotyping
Deep Illumina resequencing data of the parental inbred lines Bd21
and Bd1-1 was used to identify SNP variants (Gordon et al., 2014). Parental
reads were mapped to the Bd21 version 2 B. distachyon genome assembly
(Goodstein et al., 2012) using BWA (v0.6.2, Li and Durbin 2010) and the
genotype and position of SNP markers were determined using SAMtools
(v0.1.19; Li and Durbin 2010). Barcoded RIL data were demultiplexed using
barcode sequences and ApeKI cut site using GBSX (v1.0.1, Herten et al., 2015)
and partitioned for each line. Illumina data for each RIL individual was
queried for 813,363 parental markers and a genotype was assigned when
assayed. To improve the accuracy of genotyping and summarize the genotyping of markers with close physical position, consensus genotypes for 7 kb
windows tiling the genome were determined by calculating genotype ratios
in each window and assigning the consensus genotype according to majority
rule, requiring that the consensus genotype be supported by twice the
number of individual genotyped sites as the next most probable consensus
genotype, if there was one. This analysis yielded 7469 consensus genotypes
tiling the B. distachyon genome assembly, some with high levels of missing
data across the population.
Data Filtering
Genotypic data were compiled for 2664 SNP markers spanning the entire
B. distachyon genome. Because RIL populations should be nearly homozygous,
heterozygous calls made by markers were scored as missing data. We tested
2664 markers and removed markers with more than 15% of missing data
(Supplemental Figs. S4, A and B), for a total of 1693 markers used in the analysis. The parental genotypes were both equally represented across all 142 independent lines (Supplemental Figs. S4, C and D); however, 18 lines were
removed, 17 due to greater than 30% of missing genotypic data and one due to
greater than 90% identity to another RIL. The final QTL analysis was completed
using GBS data from 124 independent lines of the Bd21 X Bd1-1 RIL population.
Genetic Map
A high-density genetic map was built using the ML objective function and
Haldane distance function of MSTmap (Wu et al., 2008) using the 1693 filtered
markers described above. Inferred marker order from the genetic data agreed
with the physical map of the B. distachyon genome assembly, supporting the
accuracy of the population genotyping. See Supplemental Table S3 for genotypic dataset.
QTL Analysis
QTL analysis was performed in R using the R\qtl package (Broman et al.,
2003). First, QTL mapping was computed using simple interval mapping, using
the Haley and Knott regression method (Haley and Knott, 1992). The empirical
LOD threshold was computed using 10,000 permutations (a = 0.05), which
resulted in a LOD score around 3.2. Graphs were created using the ggplot2
package (Wickham, 2009). Peak interaction was computed using a twodimensional genome scan (scantwo() function; Haley and Knott regression),
and the significance of QTL interaction was computed using 1000 permutations
(a = 0.05).The contribution of individual peaks to the observed phenotypic
variance was obtained using the fitqtl() function (Haley and Knott regression)
and a single-peak model.
Identification of Variants within Candidate FloweringTime Genes
Variants were identified using a Variant Call Format (VCF) file comparing
Bd1-1 to the Bd21 reference genome (Gordon et al., 2014). We used VCFtools
and Vcflib command line tools to retrieve the region of interest, select homozygous variants, and remove low-quality calls (i.e. calls with a GQ value
less than 90) from the VCF file. All gene models (PHYC: Bradi1g08400.v2.1;
VRN1: Bradi1g08340.v2.1; VRN2: Bradi3g10010.v2.1 ; FD: Bradi3g00300),
which include 2 Kb upstream and 200 bp downstream of the transcribed region, were obtained from the Brachypodium genome Version 2 (Bd2.1_V283;
http://phytozome.jgi.doe.gov; Goodstein et al., 2012).
The supplemental data sets, including the raw phenotypic and raw genotypic data as well as the R script used for the QTL analysis can be found here:
https://zenodo.org/record/61660.
Accession Numbers
Raw Illumina sequencing files have been uploaded to the NCBI sequence
read archive SUB1982345.
Supplemental Data
The following supplemental materials are available.
Supplemental Figure S1. Days to heading of individual recombinant inbred lines.
Supplemental Figure S2. Number of leaves at flowering for individual
recombinant inbred lines.
Supplemental Figure S3. Correlation between the number of days and the
leaves at flowering.
Supplemental Figure S4. Filtering steps for the selection of markers and
recombinant inbred lines included in the analysis.
Supplemental Figure S5. Interaction between QTL peaks using a two-QTL
model.
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Woods et al.
Supplemental Figure S6. Location of the flowering-time candidate genes
compared to the QTL experiment.
Supplemental Figure S7. Sequence variant comparison in candidate genes
underlying QTL1, QTL2, and QTL3.
Supplemental Table S1. SNP-based genetic map.
Supplemental Table S2. QTL variance explained.
Supplemental Table S3. Genotypic data.
Supplemental Table S4. Phenotypic data.
Supplemental Material. VRN2 alignment file.
ACKNOWLEDGMENTS
The authors thank the University of Wisconsin Biotechnology Center DNA
Sequencing Facility for providing GBS facilities and services. Mention of trade
names or commercial products in this publication is solely for the purpose of
providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.
Received July 28, 2016; accepted October 10, 2016; published October 14, 2016.
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