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
Plant PhysiologyÒ, January 2017, Vol. 173, pp. 269–279, www.plantphysiol.org Ó 2017 American Society of Plant Biologists. All Rights Reserved.
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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 am[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] Articles can be viewed without a subscription. 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 Plant Physiol. Vol. 173, 2017
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%). Plant Physiol. Vol. 173, 2017
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 271
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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 272
(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. Plant Physiol. Vol. 173, 2017
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 Plant Physiol. Vol. 173, 2017
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 273
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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 274
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. Plant Physiol. Vol. 173, 2017
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 Plant Physiol. Vol. 173, 2017
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 275
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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. 276
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. Plant Physiol. Vol. 173, 2017
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. Plant Physiol. Vol. 173, 2017
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. 277
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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