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Published online 1 July 2008
Published in Crop Sci 48:1579-1585 (2008)
© 2008 Crop Science Society of America
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Phenological Characterization of Near-Isogenic Sunflower Families Bearing Two QTLs for Photoperiodic Response

C. Fontsa, F. H. Andradea,*, M. Grondonab, A. Hallc and A. J. Leónb

a Unidad Integrada INTA Balcarce, Facultad de Ciencias Agrarias UNMP, Ruta 226 Km 73.5 (7620) Balcarce, Buenos Aires, Argentina
b Advanta Semillas SAIC Ruta 226 Km 60.5 (7620) Balcarce, Buenos Aires, Argentina
c IFEVA, Facultad de Agronomía, Univ. de Buenos Aires/CONICET, Av. San Martín 4453 (1417), Buenos Aires, Argentina

* Corresponding author (fandrade{at}balcarce.inta.gov.ar).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Understanding the effects of environment and genotype on crop phenology is critical to achieving appropriate adaptation of cultivars to targeted production areas. The main objective of this work is to examine the phenology of near-isogenic sunflower (Helianthus annuus L.) families bearing all combinations of alleles for quantitative trait loci (QTLs) A and B associated with photoperiodic response growing in controlled environment chambers under short and extended photoperiods. Plants were harvested at intervals, the apices dissected out, and apex development from the start (apex transformation) to the end of floral differentiation scored using a 10-point scale of floral stages. Parental lines showed significant (p < 0.05) contrasting responses to photoperiod. The genotypes exhibited significant (p < 0.0001) effects of photoperiod, QTL, QTL x photoperiod, and QTL x QTL interactions for the timing of apex transformation (B0) and for the inverse of rate of development during floral differentiation (B1). The strong QTL A x QTL B interaction for both B0 and B1 reflects the much greater delay in development under both photoperiods when QTL A was derived from HA89 and QTL B from ZenB8. This effect on B1, but not on B0, increased under extended photoperiod in the same family, reflecting a three-factor (QTL A x QTL B x photoperiod) interaction acting on rate of development during the floral differentiation process. Given the weight of direct and interaction contributions associated with the two QTLs to the nonerror variability of both B0 and B1 across genotypes and photoperiods, we conclude both QTLs are important effectors in the photoperiodic control of flowering in sunflower.

Abbreviations: BC, backcross • DAE, days after emergence • DN, day neutral • LD, long day • PCR, polymerase chain reaction • PPFD, photosynthetic photon flux density • QTL, quantitative trait loci • RFLP, restriction fragment length polymorphism • SD, short day • SSR, simple sequence repeat


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
HIGH YIELDS FOR A SPECIFIC crop–environment combination can only be achieved if the cultivars used are phenologically adapted to the seasonal resource availability patterns of the target production region (Summerfield et al., 1991). An understanding of the nature of the effects of genotype and environment (and their underlying causes) on crop development is critical for any trait-based attempt at manipulating crop development to suit particular environments.

Photoperiod can affect the duration of the emergence–anthesis developmental phase in sunflower (Helianthus annuus L.) (Rawson and Hindmarsh, 1982; Goyne et al., 1977; Goyne and Schneiter, 1987) and in other crops (Slafer and Rawson, 1994; Kernich et al., 1996; Bertero et al., 1999). These effects have often been studied in terms of their impact on the duration of the emergence–floral initiation subphase, but more detailed work has shown that the duration of the post-floral initiation subphases can also respond to photoperiod (Bertero et al., 1999; González et al., 2005; MacDonough et al., 2004). Early work with sunflower (Rawson and Hindmarsh, 1982) identified cultivars that exhibited long-day (LD) or day-neutral (DN) responses for the duration of the emergence–floral initiation subphase. However, if the duration of the whole of the emergence–anthesis phase of those same cultivars was considered, the response type became short day (SD) or DN. Goyne and Schneiter (1987) reported SD, LD, DN, and ambiphotoperiodic responses for the duration of the emergence–first anthesis phase (E to R.5.1 on the Schneiter and Miller [1981] developmental scale). More detailed work on the photoperiod responses of sunflower (Balbi, 2002; MacDonough et al., 2004) focused on the durations of the emergence–start of floral initiation (E to FS1.3 on the Marc and Palmer [1981] developmental scale) and the start-end floral initiation (i.e., FS1.3 to FS8 on the same scale) subphases. That work has served to reveal some of the complexities of photoperiodic control of development in sunflower (which include, in addition to previously reported effects, changes in phyllochron duration, in the duration of the interval between the emergence of the last leaf and R.5.1, and changes in cultivar response rankings with time of sowing [spring vs. summer sowings]). In the context of the present study, important findings of the work of Balbi (2002) and MacDonough et al. (2004) were that cultivars exhibited differences in photoperiodic response for durations of both the E–FS1.3 and FS1.3–FS8 subphases.

Considerable progress has been made in model species and crops other than sunflower in determining the molecular and genetic bases of photoperiodic response (Hay and Ellis, 1998; Blázquez, 2000; Appendino and Slafer, 2003; Valverde et al., 2004; Imaizumi and Key, 2006). In sunflower, advances have been more limited. Using restriction fragment length polymorphism markers (RFLP), Leon et al. (2000, 2001) performed a genetic linkage analysis for growing degree days to flowering and photoperiodic response in families derived from the cross between lines HA89 and ZENB8. They found two quantitative trait loci (QTLs) (A and B) highly associated with the photoperiod response that controls growing degree days to flowering. However, it is not known how these QTLs affect the responses to photoperiod of the moment of apex transformation and of the subsequent subphases.

The development and use of near-isogenic families that differ only in the traits of interest (Tanksley and Nelson, 1996; Guo et al., 2007) provide a useful tool for studying the effects of particular QTLs on plant behavior. The objectives of this study were (i) to develop and phenologically characterize near-isogenic families bearing combinations of QTLs A and B derived from HA89 and ZENB8, and (ii) to determine the responses of the near-isogenic families to contrasting photoperiods in terms of the duration of the E–FS1.3 subphase and the rate of development during the FS1.3 to the end of floral differentiation (FS10) subphase.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Selection of Near-Isogenic Families for QTL A and QTL B
The analysis of QTLs based on RFLP markers, reported by León et al. (2000), was updated with the information of additional simple sequence repeat (SSR) markers. Using composite interval mapping and the PlabQTL program (Utz and Melchinger, 1996), SSR flanking markers for QTLs A and B were identified (Table 1 ). Genetic material from the Advanta (Buenos Aires, Argentina) backcross program and molecular marker information (RFLP and SSRs) were used to obtain the near-isogenic families for the different combination of alleles at QTLs A and B. Briefly, ZENB8 and HA89 inbred lines with different photoperiod responses were crossed (León et al., 2000), obtaining an F1. From this F1, two consecutive backcrosses (BC) with ZENB8 were made to obtain BC2F1 seeds. The backcross plants were selected with the assistance of molecular markers as indicated below to ensure the highest homology with the recurrent parent and the presence of QTLs A and B in the heterozygous state. The plant with the highest homology with ZENB8 (83.2%) and heterozygous for both QTLs was selected and self-pollinated to obtain BC2F2 seed. With the aid of molecular markers, a single BC2F2 plant, heterozygous for both QTL A and QTL B, was selected and self-pollinated to obtain BC2F3 seeds. BC2F3 plants were again subjected to genomic DNA analysis, and families (with two to five individuals) for each of the four genotypic combinations for the two QTLs shown in Table 2 were selected. Selected plants were self-pollinated to obtain BC2F4 seed, and the latter self-pollinated once again to obtain the BC2F5 seeds used to study photoperiodic responses.


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  		Table 1. Genotypic combinations of the near-isogenic families at the quantitative trait loci (QTLs) of interest located in linkage groups A and B. Selection of these families was based on molecular markers.

 

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  		Table 2. Position of the simple sequence repeat (SSR) microsatellities flanking the quantitative trait loci (QTLs) of interest located in linkage groups A and B.

 
To genotypically characterize the different generations, tissue from young leaves was harvested, the samples lyophilized, and genomic DNA extracted from these samples according to the protocol of Haymes (1996) modified by Abratti (2004). The molecular marker scores were obtained from DNA amplification using polymerase chain reaction (PCR) (Model Gene AMP, PCR system 9700; Applied Biosystems, Foster City, CA) (Yu et al., 2003). The PCR products were separated in an automatic ABI 3100 sequencer (Applied Biosystems) and analyzed using the Genotyper program (Applied Biosystems).

Evaluation of Photoperiodic Response of HA89, ZENB8, and the Near-Isogenic Families
The experiments were conducted in two controlled environment chambers (Snijders Scientific) under two contrasting photoperiods: 10 h at 200 µmol m–2 s–1 photosynthetic photon flux density (PPFD) at the level of the upper leaves of the plants, and an extended photoperiod treatment which received a further 6 h at 35 µmol m–2 s–1 PPFD. Chambers were run at 23 ± 3°C and 60% relative humidity.

The responses of the near isogenic families and the parental lines were evaluated using a split-plot design with two time-sequenced replications. The main plot corresponded to the photoperiodic treatments and the subplots to the genotypes. Each controlled environment chamber was randomly assigned to the daylength treatment in each of the two replications (blocks). There were 30 plants per genotype within each replication. Seeds were treated with fungicide, prehydrated in a high humidity environment, and germinated. After germination seedlings were transplanted (three plants per pot) to 5-L pots filled with a mixture of perlite, soil, and worm compost and placed in the growth chambers. The positions of the pots within each chamber were randomly assigned, and pots were rotated periodically to avoid border effects. Pots were irrigated as required, alternating water and Hoagland solution.

To determine the developmental progress, one plant per treatment was harvested, dissected, and observed under a binocular microscope at an interval of 2 or 3 d during the period from V6 stage to the end of floral differentiation (FS10). The reproductive development was described using the macroscopic scale of vegetative and reproductive stages (Schneiter and Miller, 1981) and the microscopic scale of floral differentiation stages (Marc and Palmer, 1981). The FS10 stage in the Marc and Palmer (1981) scale coincides with the bud visible stage [R1] on the Schneiter and Miller (1981) macroscopic scale.

Statistical Analyses
A two-step analysis was performed. In the first step, the significance of the responses to photoperiod (in the units of days after emergence [DAE]) was analyzed using a covariance model with floral stage as a quantitative variable (covariable) and genotype, photoperiodic treatment, and replications as classification variables. Interactions among variables were included.

In the second step, the data for each combination of genotype and photoperiod treatment within a replicate experiment were reduced to two parameters (B0 and B1) derived from a linear regression fitted to the DAE vs. floral stage relationship. Before fitting, the floral-stage variable was adjusted by subtracting 1.3 (which represents the FS1.3 stage) from the development score assigned to each observation. This approach facilitates interpretation, as the intercept on the DAE axis (B0) is an estimate of the timing (in DAE) of apex change, and the regression coefficient (B1) is inversely related to the average rate of development during the floral differentiation subphase (i.e., from FS1.3 to FS10). The estimates of the two regression parameters, B0 and B1, were analyzed separately using analysis of variance that assumed a linear model with genotype and the photoperiodic treatments as main effects. In this approach, the genotypes were classified according to the allelic composition at each QTL; that is, the genotype corresponds to the combination of two factors: QTL A and QTL B. These statistical analyses were performed using the R computational statistics program (Gentleman and Ihaka, 2007).


   RESULTS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The covariance analysis for the time progress of floral differentiation in near-isogenic families and parental lines under contrasting photoperiods indicated significant (p < 0.0001) genotype, photoperiod, and photoperiod x genotype interaction effects. Some of the treatments did not achieve FS10 within the time frame of the experiments, but the principal effects identified by the covariance analysis can be visualized in the plots of time against floral stage for the parental lines and the near-isogenic families (Fig. 1 ) by comparing treatment combinations for the most advanced floral stage achieved in each experiment. The genotype effect on development was largely (but not solely; see text relating to Table 3 below) attributable to the behavior of the AHBZ family, which had the slowest rate of development under both photoperiods. The significant photoperiod effect reflects the delay in development evoked by extended photoperiod (i.e., an SD response) in three of the four near-isogenic families and in ZenB8. By contrast, an acceleration of development (i.e., an LD response) was observed under extended photoperiod in HA89. The significant (p < 0.0001) genotype x photoperiod interaction was largely attributable (i) to the contrasting responses to photoperiod of HA89 with respect to the near-isogenic families and ZenB8, and (ii) to the strong average response to photoperiod of the AHBZ family.


Figure 1
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  		Figure 1. Relationship between floral stage and days after emergence for the near-isogenic families AHBH, AHBZ, AZBH, and AZBZ, and for sunflower parental lines HA89 and ZENB8 grown under extended (triangles) and short (circles) photoperiods. Each point indicates an individual observation. Floral stages are from Marc and Palmer (1981). Continuous (short photoperiod) and dashed (extended photoperiod) lines are fitted linear regressions. Upper and lower panels are from replicate experiments.

 

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  		Table 3. Timing of apex differentiation (B0, in the units days after emergence) and the slope of the time/floral stage (B1, in the units of days per unit advance in floral stage [FS]) for the sunflower parental lines HA89 and ZENB8 grown under two photoperiods. Values are means of the two replications ± 95% confidence interval.

 
Separation of the overall responses to photoperiod of the duration of the E–FS10 phase into its components (the timing of apex change [B0] and the rate of development during floral differentiation [1/B1]) permitted a more detailed analysis of photoperiod and genotype effects on these two variables. León et al. (2001) observed the responses to photoperiod of the duration of the emergence to flowering phase in HA89 and ZenB8 but did not make observations on the duration of component subphases. In our experiments, the parental lines exhibited different responses to photoperiod for these two variables (Table 3). HA89 exhibited a DN response for timing of apex differentiation (B0) and LD response for rate of development during the FS1.3–FS10 subphase (B1). By contrast, ZenB8 exhibited an SD response for both B0 and B1.

The plots of time from emergence against floral stage (Fig. 1) highlight the strong average SD response of the AHBZ family for rate of development during the floral differentiation subphase particularly in Replication 2. None of the near-isogenic families exhibited the LD response for B1 found in HA89, not even in the AHBH family bearing both QTLs from HA89. By contrast, the responses of the AZBZ family were similar to those of ZenB8.

The regressions shown in Fig. 1 were recalculated after discarding observed values lower than FS1.3 and greater than FS9, resulting in little effect on the patterns of variation of B0 and B1 across treatments (photoperiod and genotype). We are therefore confident that computed estimates of B0 and B1 using the data shown in Fig. 1 are not biased by possible effects of including observations that, by excessive margins, either preceded FS1.3 or were delayed after achievement of FS10 (both errors could have affected the estimates of B0 and B1).

The analysis of variance for B0 showed that QTL A, QTL B, and their interaction accounted for about two-thirds of the nonerror variability for B0, while photoperiod and its interaction with QTL B accounted for almost one-quarter of this variability (Table 4 ). Alleles from HA89 in QTL A had a strong delaying effect on the moment of apex differentiation (Fig. 2 ). The extended photoperiod tended to lengthen B0 in all genotypes (Fig. 2) (i.e., an SD response for this variable similar to that exhibited by ZenB8; Table 3). The difference in the duration of B0 in AHBZ with respect to that of other allele combinations under both photoperiods was a major contributor to the significant QTL A x QTL B interaction (Fig. 2; Table 4). There was a significant replicate effect on B0 (Table 4), probably due to small errors in fixing the date of emergence or to differences between replicates in ambient temperature in the period before seedlings were transferred to the growth chambers. This variation between replicate experiments of B0 (mean value of the difference between experiments = 2.8 d) did not involve changes in the rank order of genotypes between replicates and thus does not affect the inferences drawn from the results.


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  		Table 4. Analysis of variance for the effects of allele constitution at quantitative trait loci (QTLs) A and B and photoperiod on the estimated timing of apex differentiation (B0, days after emergence).

 

Figure 2
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  		Figure 2. Timing of apex differentiation (B0) expressed in days after emergence as a function of allele constitution at quantitative trait loci (QTLs) A and B under short (continuous line) and extended (dashed line) photoperiods. Data points indicate values for each replicate experiment. AHBH and AZBZ include data from HA89 and ZenB8, respectively, because of similar allele constitution at QTLs A and B.

 
Effects of QTL A, QTL B, and their interaction accounted for about two-thirds of the nonerror variability for B1 with roughly similar contributions from each of these three factors. Photoperiod, photoperiod x QTL B interaction, and photoperiod x QTL A x QTL B interaction accounted for about one-third of the nonerror variability. As illustrated in Fig. 3 , photoperiod responses for B1, where present, were of the SD type (i.e., more days per unit advance in floral stage under extended photoperiod), as found in ZenB8 (Table 3). The interactions were mainly reflected in the large increase in B1 under extended photoperiod exhibited by AHBZ, in contrast to small or nil responses to extended photoperiod in the other three allele constitutions. As was the case for B0 (Table 4), there was no QTL A x photoperiod interaction for B1 (Table 5 ). In contrast, the three-factor interaction (QTL A x QTL B x photoperiod) was significant for B1 but not for B0. The strong QTL A x QTL B interaction for both B0 and B1 reflects the much greater delay in development under both photoperiods when QTL A was derived from HA89 and QTL B from ZenB8. This effect on B1 was increased under extended photoperiod in the same allele constitution, reflecting a three-factor (QTL A x QTL B x photoperiod) interaction acting on rate of development.


Figure 3
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  		Figure 3. Slope of the relationship between days after emergence and floral stage (B1) as a function of allele constitution at quantitative trait loci (QTLs) A and B under short (continuous line) and long (dashed line) photoperiods. Data points indicate values for each replicate experiment. AHBH and AZBZ include data from HA89 and ZenB8, respectively, because of similar allele constitution at QTLs A and B.

 

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  		Table 5. Analysis of variance for the effects of allele constitution at quantitative trait loci (QTLs) A and B and photoperiod on the estimated inverse of rate of development during floral differentiation (B1, in the units days per unit increment in floral stage [FS]).

 

   DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The responses to photoperiod of the parental lines and near-isogenic families found here are broadly consistent with previous reports indicating genetic variability for these effects, which encompasses SD, LD, and DN responses within the species (Goyne and Schneiter, 1987; Rawson and Hindmarsh, 1982; MacDonough et al., 2004). Short-day responses for the duration of B0 and the rate of floral differentiation (B1) predominated in the combinations we examined (Table 3; Fig. 2 and 3), but HA89 exhibited a DN response for B0 and an LD response for B1 (Table 3). Our results highlight once again the need to treat B0 and B1 as separate and potentially independent sources of variation in the overall rate of development between emergence and anthesis. This need emerges clearly from the screening conducted by MacDonough et al. (2004) but, notably, present results show for the first time that QTL B, QTL A, and their interactions can have a strong effect on these two variables.

Present results confirm the findings of León et al. (2000, 2001) that QTLs A and B affect photoperiod response; they also extend the work of these authors in showing that developmental processes that occur well before anthesis (i.e., B0 and B1) explain the variability in the duration of the emergence–anthesis phase found in their experiments. The greatest value of B0 and B1 were observed under extended photoperiods in the family selected for HA89 alleles in QTL A and ZenB8 alleles in QTL B (Fig. 2 and 3). This result agrees with the additive effects of both QTLs on growing degree days to flowering found by León et al. (2001). Present work also shows strong QTL A x QTL B interactions for both B0 and B1 (Tables 4 and 5) not reported by León et al. (2001). Possible reasons for this difference in results may lie in (i) the fact that León et al. (2001) looked at the overall duration of the emergence–anthesis phase and did not examine the early subphases of development as we did, and (ii) the lack of statistical power in detecting interaction effects between QTLs in the QTL mapping procedure.

The QTL B interacted significantly with photoperiod for B0 and B1, whereas QTL A did not (Tables 4 and 5). This result appears to contrast with the results of León et al. (2000, 2001), who found interactions with photoperiod for both QTLs, with the additive effect of QTL A decreasing and that of QTL B increasing as photoperiod lengthened. The nonappearance of the QTL A x photoperiod interaction in our work may reflect the preponderance of the ZenB8 genetic background in our near-isogenic families. The nonappearance of the LD response exhibited by HA 89 (Table 3) in any of the near-isogenic families (Fig. 3) may be another reflection of the same phenomenon. A variation of the work reported here using backcrossing to HA89 to develop near-isogenic families may throw some light on this issue.

The quantitatively important contributions of some interactions (i.e., QTL x QTL, QTL x photoperiod, QTL x QTL x photoperiod) in accounting for the variance, across near-isogenic families and parental lines, of the responses of B0 and B1 to photoperiod (Tables 4 and 5) are consistent with our present understanding of the complex web of processes controlling flowering responses to photoperiod (Blázquez, 2000; Valverde et al., 2004; Turner et al., 2005; Imaizumi and Key, 2006).

Our work has shown that the alleles of both QTL A and QTL B are strong effectors of early developmental subphases in sunflower. Equally, the importance of the various interactions detected in this work and the possible importance of the genetic background in modulating responses would help in modeling development and control of photoperiod responses in this species and developing marker assisted strategies to assist breeding for adaptation, through optimal timing of flowering, to particular patterns of resource availability.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Received for publication November 5, 2007.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 





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