• candidate gene;
  • comparative genomics;
  • mutational load;
  • quantitative trait loci (QTLs);
  • resource allocation;
  • rice;
  • seed set;
  • synteny


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • • 
    Mutational load and resource allocation factors and their effects on limiting seed set were investigated in ryegrass by comparative mapping genomics and quantitative trait loci (QTL) analysis in two perennial ryegrass (Lolium perenne) mapping families sharing common genetic markers.
  • • 
    Quantitative trait loci for seed-set were identified on chromosome (LG) 7 in both families and on LG4 of the F2/WSC family. On LG7, seed-set and heading date QTLs colocalized in both families and cannot be unequivocally resolved. Comparative genomics suggests that the LG7 region is syntenous to a region of rice LG6 which contains both fertility (S5n) and heading date (Hd1, Hd3a) candidate genes. The LG4 region is syntenous to a region of rice LG3 which contains a fertility (S33) candidate gene. QTL maxima for seed-set and heading date on LG4 in the F2/WSC family are separated by c. 8 cm, indicating distinct genetic control.
  • • 
    Low seed set is under the control of recessive genes at both LG4 and LG7 locations.
  • • 
    The identification of QTLs associated with seed set, a major component of seed yield in perennial ryegrass, indicates that mutational load associated with these genomic regions can be mitigated through marker-assisted selection.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Considerable variation for seed set has been observed in nominally fertile crosses of perennial ryegrass (Lolium perenne L.); for example, Elgersma & Sniezko (1988) observed ranges from 8 to 73% in perennial ryegrass. Indeed, there is considerable variation for seed yield within most forage grass species (Elgersma, 1990; Elgersma & van Wijk, 1997). In fact, it is a paradigm of life-cycle evolution that perennial outcrossing species, in general, exhibit lower seed set in proportion to the available fertilization sites than self-fertile species (Wiens, 1984). Pollen availability affected by both spatial and temporal separation of pollen and receptive stigma may contribute to reduced seed-setting ability (Charlesworth, 1989). Two alternative explanations for reduced seed set are as follows: internal competition for resources between maturing fruits and other plant tissues; and the build-up of lethal and sublethal mutations (mutational load) in perennial plants, maintained by an effective outcrossing mechanism (Charlesworth & Charlesworth, 1987). Our study attempts to identify specific genetic components responsible for either cause of low seed set in perennial ryegrass.

The likeliest cause of reduced seed-setting ability is the genetic and/or environmental disruption of gamete or zygote development, leading to abortion of the seed (Leidl & Anderson, 1993). In ryegrass, seed abortion has been observed to be specific to floret location, with more distal florets producing less seed, suggesting that abortion is resource-dependent and that the florets closer to nutritional resources are favoured (Burbridge et al., 1978), similar to the situation observed in wheat (Bremner & Rawson, 1978). Yet from the studies of seed set in perennial ryegrass of Marshall & Ludlam (1989), it was concluded that abortion of c. 50% of ovules was random and possibly the result of mutational load associated with outbreeding. This is consistent with the generic findings of Wiens (1984), where percentage of ovules developing into seeds in perennial (predominantly outcrossing) species is c. 50%, compared with c. 85% in inbreeding species.

The presence of a two-locus self-incompatibility system can inhibit fertilization in specific crosses where both S and Z alleles are shared by the parents (Cornish et al., 1980), but is not likely to be of major significance in outcrossing populations of perennial ryegrass, as a high number of incompatibility alleles at both incompatibility loci is maintained by frequency-dependent selection (Devey et al., 1994; Fearon et al., 1994).

The two ryegrass families described in this paper have been used in a series of quantitative trait loci (QTL) and comparative genetic and genomic studies over a number of years, focusing on comparative genome analysis (Armstead et al., 2002; Jones et al., 2002), flowering (Armstead et al., 2004, 2005; Shinozuka et al., 2005), water-soluble carbohydrate accumulation (Turner et al., 2006), disease resistance (Thorogood et al., 2001), winter hardiness (Yamada et al., 2004), and self-incompatibility and self-fertility (Thorogood et al., 2002, 2005). The aims of this paper were: (i) to place the data acquired on fertility in the context of the existing knowledge of the genetics of flowering in these two populations; and (ii) to explore possible underlying causes of variation in fertility by distinguishing differential resource allocation factors from disruption of ovule, pollen and seed developmental processes.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Plant populations

The ILGI mapping population (n = 166) was derived from a cross between an anther-culture-derived di-haploid plant and a heterozygous plant from an elite breeding population, and was developed as described by Jones et al. (2002). The F2/WSC population (n = 188) was derived from selfing an F1 plant, which was in turn produced from a cross between two unrelated and morphologically contrasting self-fertile inbred lines and developed as described by (Turner et al., 2006).

Phenotype assessment

For each family, seed set, pollen fertility, anther dehiscence and flag leaf dimensions were all recorded in the same year. Heading date had been recorded in preceding years and was measured according to standard UPOV procedures (UPOV, 2006) as the date at which three inflorescences could be observed to have emerged above the flag leaf sheath.

Heading date  Heading date phenotype data were determined on unreplicated spaced plants in the field and were recorded after observation at 2–3 d intervals as the number of days after 1 April when three inflorescences had emerged above the flag leaf sheath (Armstead et al., 2004). Number of inflorescences per plant was also recorded.

Seed set  Single clonal propagules of each genotype were planted in 15-cm-diameter pots and vernalized under natural temperature and day-length conditions in an unlit, unheated glasshouse. Both families were allowed to flower and set seed in the glasshouse, and plants were staked so that inflorescences were held erect to allow maximum pollen distribution. Pollen source was not controlled, although plants from each family were grouped together on the same bench. For the F2/WSC family, seed set was recorded as the average number of seed per inflorescence taken over all inflorescences produced. For the ILGI family, seed set was recorded as the average number of seeds set per spikelet for five inflorescences selected at random from each plant genotype. Both measures are referred to as ‘seed set’ in the following text. In addition, the 100 seed weight (g) of each genotype in both families was recorded.

Pollen fertility/anther dehiscence  The F2/WSC family showed clear variation for pollen fertility and anther dehiscence phenotypes; hence in this family, pollen viability and anther dehiscence assessments were measured, as these traits are likely to have direct bearing on final seed setting ability. Pollen viability was determined by staining with aceto-carmine in anther squashes on glass slides and the proportion of viable pollen grains was determined by pollen counts in three low-power (×10) views and the percentages were then angularly transformed before QTL analysis. Anther dehiscence was scored on intact anthers still attached to the florets on a subjective 0–1 scale as follows: 0, nondehiscent; 1, fully dehiscent.

Flag leaf dimensions  Maximum flag leaf length and width were recorded in field-based spaced plants for both families and analysed as the mean score for three randomly selected flag leaves of each genotype. The measurements were taken after inflorescences were fully emerged.

Genetic mapping and marker development

Genetic mapping of both families was performed using JoinMap® 3.0 software (Van Ooijen et al., 2001) using map orders and distances generated by the first or second rounds of mapping. The genotype data used were produced as described by Jones et al. (2002) for the ILGI family and by Armstead et al. (2004), Skøt et al. (2005) and Turner et al. (2006) for the F2/WSC family. Additional markers used were developed using primer sequences from LpCk2a-1 and LpVrn-1 (chromosome 4) and Hd3a, 06g10880, 06g11020 and 06g11180 (chromosome 7). Primers for Hd3a (Hd3agt and Hd3a(LD)) and LpVrn-1 were based upon existing ryegrass genomic sequence (I. Armstead, unpublished) and for LpCk2a-1 upon GenBank accession number AB213316. Primers for 06g10880, 06g11020 and 06g11180 were based upon conserved regions in alignments of the TIGR rice loci LOC_Os06g610880, LOC_Os06g11020 and LOC_Os06g11180 with published orthologous sequences. Genomic DNA was PCR-amplified using conditions and primers described in the Supplementary material.

Identification of the S5n (inline image) region in the rice 6 pseudomolecule

The primer sequences J1–J25 detailed in Ji et al. (2005) were aligned with the rice 6 pseudomolecule using BLASTN searches against TIGR Rice Pseudomolecules and Genome Annotation, release 4 at with an ‘expect’ value of 1000.

QTL analysis

Interval mapping (IM) and multiple QTL mapping (MQM) QTL analysis with automatic cofactor selection was performed using MapQTL 4.0 (MQ) (Van Ooijen et al., 2002) and CIM QTL analysis with Windows QTL Cartographer, version 2.5 (WQC) (Wang et al., 2005). For MQ, the analysis was run using the default settings, except with a step size of 0.5. For WQC the CIM analysis was run using Model 6 with forward and backward regression (P = 0.1), a window size of 5 or 10 and a step size of 0.5. Genome-wide significance levels were estimated using the permutation test module of MQ.

Database information

Sequence information and BLAST searches were accessed through either GenBank ( or TIGR Rice Genome Annotation (release 4) ( QTL information was obtained from Gramene (, Graingenes ( or MaizeGDB (


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Phenotype data

The seed-set data for the F2/WSC family were previously transformed into a log10 score after adding 1 unit because of the presence of a large number of zero values and a number of high percentage values. Although the ILGI data showed a normal distribution, the F2/WSC distribution was bimodal. The heading date phenotype data for the F2/WSC family have been discussed previously (Armstead et al., 2004) and indicated bimodal distribution. The ILGI family has also been evaluated for heading date in a separate study in Japan and showed a similar normal distribution and range of heading dates (Yamada et al., 2004).

The frequency distributions of anther dehiscence and pollen fertility scores for the F2/WSC family were clearly bimodal.

Both flag leaf length and width were normally distributed in both populations but the flag leaf dimensions differed between populations: the flag leaves of the F2/WSC population were, on average, three times larger in surface area than the ILGI family but had similar length/width ratios. The phenotypic variation for flag leaf dimensions within the F2/WSC family was greater than that for the ILGI family (Table 1).

Table 1.  Summary statistics for flag leaf dimensions in the F2/WSC and ILGI populations
 Length (l, mm)Width (w, mm)l/wAreaa
  • a

    Length × width × 0.8.

WSC/F2 170.97.822.21078.3
Standard deviation29.61.33.8305.0
Standard deviation16.50.42.981.3

Genetic mapping and marker development

Genetic maps for these two populations have been reported previously and the results of the present study are substantially as described by Turner et al. (2006) for the F2/WSC population, and Jones et al. (2002) and Yamada et al. (2004) for the ILGI population. The genetic map positions for markers on chromosome 4 (LG4) and chromosome 7 (LG7) for both populations are detailed in the Supplementary material. Two additional markers to those previously reported were scored for LG4 on the F2/WSC population, Lpvrn-1 and LpCk2a-1, which targeted the ryegrass homologues of VRN-1 (Jensen et al., 2005) and the casein protein kinase 2 α-subunit, LpCk2a-1 (Shinozuka et al., 2005). These mapped to 30 and 27 cm, respectively, both of which were consistent with the previously reported map positions in ryegrass. Four additional markers were scored for LG7 on the ILGI and F2/WSC populations, two of which were common to both maps, Hd3a and 06g11020. In total, six markers were mapped in common for LG4 and eight for LG7, allowing the maps for these two chromosomes from each family to be aligned.

Identification of the S5n(inline image) region in the rice 6 pseudomolecule

The BLASTN alignments of the primer sequences J1–J26 detailed by Ji et al. (2005) against the rice 6 pseudomolecule identified regions of rice 6 consistent with the expected physical positions (Table 2). Having identified the nonrecombinant region with S5n, target sequences flanking and within this region were identified using and primers designed for marker development. One marker from within the nonrecombinant region, 06g11020, identified a polymorphism segregating in both the F2/WSC and ILGI families, thus allowing this region to be aligned on both genetic maps. Of the two flanking markers, one was mapped in the F2/WSC family (06g10880) and the other was mapped in the ILGI family (06g11180). The relative genetic positions of all these markers were consistent with the known syntenic relationship between these regions of ryegrass LG7 and rice LG6 (Armstead et al., 2004, 2005).

Table 2.  Relative physical positions within the rice LG6 pseudomolecule of markers associated with the rice inline image locus and markers mapped in Lolium perenne
MarkerPosition (bp) on rice LG6 pseudomoleculebTIGR rice locus
  • a

    Markers from Ji et al. (2005). Nonrecombinant rice markers with inline image are indicated in bold.

  • b

    Position of rice markers J1 to J25 delimited by BLAST alignments of forward and reverse primer sequences given in Ji et al. (2005). Position of the remainder of the rice markers and L. perenne markers is delimited by the size of the associated TIGR rice locus (TIGR Rice Pseudomolecules and Genome Annotation, release 4).–, no associated TIGR rice locus.

RiceaL. perenne
R1952R19522 260 721–2 261 739LOC_Os06g05120
C764C7642 773 038–2 770 074LOC_Os06g06030
Hd3aHd3a2 939 005–2 941 453LOC_Os06g06320
R1954 4 932 964–4 937 472LOC_Os06g09679
J1 5 126 927–5 125 685
J2 5 603 871–5 604 090
J3 5 625 671–5 625 872
J4 5 634 299–5 634 440LOC_Os06g10790
J5 5 629 868–5 630 147LOC_Os06g10780
J6 5 651 761–5 652 066
J7 5 656 869–5 656 998LOC_Os06g10850
06g108805 676 158–5 681 034LOC_Os06g10880
J8 5 673 742–5 674 003
J9 5 691 113–5 691 512
J10 5 694 900–5 695 057
J11 5 719 151–5 719 303LOC_Os06g10950
J12 5 739 739–5 739 938
J13 5 746 469–5 746 696
J14 5 754 500–5 754 725
J15 5 758 433–5 759 240LOC_Os06g11010
J26 5 759 412–5 760 116LOC_Os06g11010
06g110205 772 556–5 776 200LOC_Os06g11020
J16 5 772 666–5 772 837LOC_Os06g11020
J17 5 797 495–5 797 875
J18 5 813 643–5 813 907LOC_Os06g11090
06g111805 861 189–5 868 597LOC_Os06g11180
J19 5 869 477–5 869 713LOC_Os06g11190
R2349 5 894 074–5 894 449LOC_Os06g11240
J20 5 932 186–5 932 444
J21 5 949 577–5 949 225
J24 5 993 144–5 992 854
J23 6 026 903–6 026 726LOC_Os06g11420
J22 6 087 691–6 087 601LOC_Os06g11500
J25 6 203 726–6 203 914
RG213 6 283 401–6 283 916
RM8274 6 578 563–6 578 748
RM3370 6 628 983–6 629 178
RM6701 6 659 900–6 660 118
RZ144RZ1446 718 646–6 720 901LOC_Os06g12390
S2539S25399 327 207–9 325 054LOC_Os06g16350

QTL analysis

The positions and magnitudes of QTLs for seed set and heading date detected by IM and MQM for LG4 and LG7 of the F2/WSC and ILGI families are summarized in Table 3. QTLs for number of seed set were detected on LG7 of both families in approximately the same position, associated with the Hd3a region. A QTL for this trait was also detected on LG4 of the F2/WSC family, with no equivalent QTL being identified on LG4 of the ILGI family. From the MQ analysis, the QTLs on LG7 accounted for 17.0 and 21.0% of the variance in the F2/WSC and ILGI families, respectively, and the QTLs on LG4 of the F2/WSC family accounted for 34.5% of the variance associated with the trait. In the F2/WSC family the LG7 QTLs accounted for a 4.1-fold increase in seed set associated with the early flowering ‘Aurora’ parental marker-type homozygous genotype over the ‘Perma’ marker genotype. The heterozygote was statistically indistinguishable from the higher-yielding ‘Aurora’ genotype class for both heading date and seed set. In the ILGI family, the equivalent QTLs on LG7 accounted for almost a 1.5-fold increase in seed set of the heterozygote marker genotypes over the homozygous genotypes, again with higher seed set associated with the early flowering genotypes (Table 4). The LG4 QTLs identified in the F2 family accounted for a 2.9- or 3.4-fold difference in seed set, depending on which linked marker was assessed, this time with the ‘Perma’ parental marker genotype associated with greater seed set (Table 5).

Table 3.  Peak positions and magnitude of quantitative trait loci (QTLs) for seed set, heading date, leaf length and width, pollen viability and anther dehiscence on chromosomes 4 and 7 of the F2/WSC (F2) and ILGI Lolium perenne mapping families calculated using MapQTL 4.0; (a) interval mapping; (b) multiple QTL mapping
(a)TraitFamilyLinkage groupPeak (cm)Interval or markerLOD significance thresholdLOD% variance
 Seed setF2438RYE122.63.69.1
ILGI735.8Hd3a-06g110202.5  519
Heading dateF2451.7RZ5372.61.6a0.8
Leaf lengthF2728.4Hd3a2.72.45.7
Leaf widthF2727.9C764-Hd3a2.78.920.4
Pollen viabilityF2441.9PSR9222.75.816.8
Anther dehiscenceF2442.4PSR922-C7462.65.215.3
(b)TraitFamilyLinkage groupPeak (cm)Interval or markerCo-factorLOD% variance
  • a

    Magnitude of the major QTLs for heading date in the F2/WSC family on LG7 obscured any interval mapping (IM) peak associated with the minor QTL which only became apparent after multiple QTL mapping (MQM).

 Seed setF2441.5RYE12-PSR922C74612.834.5
ILGI734.8Hd3aHd3a  621
Heading dateF2450.2rv0380CDO7954.7a2.2
Leaf lengthF2728.4Hd3aHd3a5.410.0
Leaf widthF2728.4Hd3aHd3a3.55.4
Pollen viabilityF2439.5RYE12-PSR922PSR9223.17.6
Anther dehiscenceF2419.8RV0454RV04542.34.5
Table 4.  Mean scores of marker classes for hd3a(LD) marker underlying significant quantitative trait loci (QTLs) on LG7 for F2/WSC and ILGI mapping populations
TraitF2 (hd3agt)ILGI (hd3(LD))
  1. Heading date, days after 1st April when three ears emerged above flag leaf; seed set (F2), log10 seeds per spike + 1; seed set (ILGI), seeds per spikelet; flag leaf length and width in mm. sed, Average standard error of difference.

Heading date39.242.761.11.5257.854.80.76
Seed set0.570.500.140.0631.612.210.13
Flag leaf width8.48.270.23   
Flag leaf length171815.80.579986.73.10
Table 5.  Mean scores of marker classes for markers underlying significant quantitative trait loci (QTLs) on LG4 for the F2/WSC population
TraitMarkerGenotype class
  1. Heading date, days after 1 April when three ears emerged above flag leaf; seed set (F2), log10 seeds per spike + 1; pollen viability, proportion of viable pollen grains: anther dehiscence, score for dehiscence (1, full dehiscence; 0, no dehiscence).

Heading datervo38049.748.047.0NS
Seed setRye120.180.400.520.068
Pollen viabilityRye120.280.600.580.056
Anther dehiscencervo4540.

Heading date QTLs were detected in the same positions on LG4 and LG7 of both families using interval, MQ and WQC mapping, except for the heading date QTL on LG4 of the F2/WSC family, which was below the level of significance using interval mapping, although it was positionally apparent using MQM mapping (Table 3). The below-significance LOD scores obtained for this QTL in the F2/WSC family are likely the result of the magnitude of the heading date QTL on LG7 in the F2/WSC family obscuring the effects of other regions of the genome. On LG7, the major QTLs for both families were associated with the Hd3a region and a second minor QTL was also associated with LG7 of the F2/WSC family (Table 3). The heading date QTLs on LG4 were also associated with approximately the same positions near marker CDO795. In both families, the QTLs on LG7 accounted for the largest proportion of the variance, although the degree of difference was much larger for the F2/WSC family than for the ILGI family (Table 3). For both families the QTL for seed set and heading date coincided with the major effects being associated with the Hd3a region. For LG4 of the F2/WSC family, however, the QTL maxima for seeds set and heading date were separated by c. 8 cm (Table 3).

The QTL data were also analysed using WQC and the results largely reflected the output from MQ and thus have not been presented in detail. However, a notable difference was that while WQC identified approximately the same maxima for the seed set and heading date QTLs on LG7 of the ILGI family, the spread of the QTL for the seed-set QTL was centred over 06g11020, whereas the spread of the QTL for heading date was centred upon Hd3a (Fig. 1).


Figure 1. Multiple quantitative trait loci mapping/interval mapping (MQM/CIM) LOD profiles on LG7 of the ILGI family for heading date (solid line), seed set (dashed line) and seed weight per spikelet (dotted line). LOD profiles generated using MapQTL (a) and QTL Cartographer (b).

Download figure to PowerPoint

Quantitative trait loci analyses of flag leaf size indicated a number of significant associations, although only the QTL identified on LG7 for leaf width and, to a lesser degree, leaf length in the F2/WSC family and leaf length in the ILGI family that cosegregate with the seed set QTL are reported here (Table 3). In the case of the F2/WSC family QTLs, a greater leaf width is associated with high seed set, but in the ILGI family the longer leaves are associated with reduced seed set (Table 4).

Additional QTL analyses were performed on pollen viability and anther dehiscence in the F2/WSC family, as there was clear variation for both characters, most plants exhibiting one of the two extremes for both traits which were also highly correlated (r = 0.73, P < 0.001). Two significant QTLs (Table 3) were identified on LG4 that accounted for c. 19% of the total variation for dehiscence score. A QTL for angularly transformed pollen viability percentage was also detected on LG4 of the WSC/F2 family, which colocalized with the seed-set QTL, and another which colocalized with one of the anther dehiscence QTLs (Table 3).


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

There remains a great deal of genetic variation for seed yield even in elite breeding populations of the Lolium forage grasses (Elgersma, 1990). The major focus for selection has been on the improvement of the vegetative sward (Wilkins, 1991). Furthermore, in contrast to self-fertile annual grain crops, outbreeding perennial species carry high mutational load manifested by, among other things, low seed set caused by gamete and seed developmental abnormalities (Charlesworth, 1989). However, dependable and predictable seed yield is a vital component of the production of commercially viable forage grass varieties, as farm-scale propagation is achieved almost exclusively via seed. Consequently, this report of the position of QTLs influencing seed yield in Lolium populations has potential significance for the future manipulation of this important trait.

Initial analyses of these ryegrass mapping families suggested that, while the two traits were measured in different years, the genomic regions associated most closely with seed set and heading date were closely linked. Consequently, one of the main aims of the present study was to carry out a detailed analysis to determine if this linkage could be further clarified. Additionally, previous analysis of heading date in the F2/WSC populations highlighted the close syntenic relationship between the region of ryegrass LG7 which contained the major heading date QTL and the region of rice LG6 which contains the Hd3 and Hd1 heading date QTLs and their controlling genes, Hd3a and Hd1 (Yano et al., 2000; Monna et al., 2002; Armstead et al., 2004, 2005). Recently, Ji et al. (2005) and Qiu et al. (2005) identified that this same region of rice 6 also contained the S5n (S5n) gene, originally identified by Ikehashi & Araki (1988), which confers wide compatibility in rice and is particularly useful in overcoming the fertility barrier in indica/japonica hybrids. While, in general, there are few problems in crossing between ryegrasses, it is well established that the species possesses a high mutational load leading to a high magnitude of inbreeding depression for many traits (Corkill, 1956), probably because of the high likelihood of the build-up of somatic deleterious mutations resulting from the extended vegetative growth phases associated with perennial crop management. These mutations are maintained by an effective outcrossing system. Therefore, it is expected that seed setting is always considerably short of its full potential. In rice, the combination of an S5i and an S5j allele from indica and japonica subspecies results in partial fertility and seed setting of c. 50%, as opposed to the expected seed setting of (or nearly) 100% (Qiu et al., 2005). Although the overall seed setting figures for our perennial ryegrass populations were lower than this (as a consequence of the outcrossing nature of the species), the QTLs on LG7 accounted for a similar difference in magnitude for partial fertility. Consequently, another major aim of the present investigation was to determine if the orthologous region to inline image in ryegrass could be identified; if its position was consistent with the known syntenic relationships between rice and ryegrass; and if this locus might contribute to the genetic control of seed yield in the forage grasses.

The association of seed set, heading date and flag leaf dimension QTLs on chromosome 7

In an outcrossing species with an effective self-incompatibility system, it might be expected that seed setting could be affected simply by pollen limitation through the spatial and temporal separation of pollen and receptive compatible stigma. In terms of spatial separation, this is unlikely to affect a particular heading date phenotype over another. In the worst case, pollen limitation might randomly affect some plants more than others in a particular experimental design and reduce the size of QTLs, or even make them less likely to be identified, but it would not affect the positioning of the QTLs. Temporal effects are also likely to be minimal as, although specific heading dates are scored for each genotype, based on the ear emergence date of the first three inflorescences, individual perennial ryegrass plants will flower over a much longer period, with pollen being produced over a period of 2–3 wk ensuring panmixis. Furthermore, in the ILGI population, the difference in heading date between the early and the late Hd3 marker genotypes is only 3 d; in the F2 family, heading date range is much greater, but all of the F2 plants capable of producing viable pollen were in fact self-fertile (Thorogood et al., 2005), ensuring close proximity of stigma with compatible self pollen. As an empirical test of the independence of seed set and flowering time per se, correlations were determined between seed set and flowering time for Hd3 marker genotype classes ‘aa’, ‘ab’ and ‘bb’ for the F2/WSC family and ‘aa’ and ‘ab’ for the ILGI family. All correlations, although negative, were nonsignificant. The correlations for the three F2/WSC genotype classes were −0.344, −0.212 and −0.196, with 22, 64 and 93 degrees of freedom, respectively, and those for the ILGI family were −0.070 and −0.233, with 54 and 43 degrees of freedom, respectively.

As grass fertility is affected by numerous environmental factors, such as nitrogen availability (Griffith et al., 1997), water availability (Martiniello, 1998) and disease incidence (Barker et al., 2003), the timing of flowering in relation to these external factors is of possible significance. Therefore, a gene which has a major influence on the timing of flowering could have a considerable indirect influence on seed yield. This is more likely in the F2/WSC family with a wide heading date range, whereas the smaller heading date range in the ILGI family implies a smaller window for variable environmental influence on seed set associated with flowering time.

It is interesting to note that the QTLs for seed set are very similar in magnitude in both families, accounting for 17 and 21% of the variance in the F2/WSC and ILGI families, respectively (Table 3), in contrast to the heading date QTLs that account for 77.9 and 20.2% of the total variation for the trait. Heading date in the F2/WSC and ILGI families was not measured in the same year as seed set but shows consistent patterns of heading date phenotype segregation from year to year when measured at the same site (M. Humphreys, pers. comm.). Furthermore, heading date has been shown to have reasonably high heritability (0.70 and 0.50) in two parent-offspring regression studies (Rogers, 1989; Wedderburn et al., 1992), and Cooper (1954) showed that although genetic variation can be revealed if temperature and photoperiod conditions are changed, heading behaviour is consistent when growing populations on the same site under similar environmental conditions, as is the case with the mapping populations in this study. It seems unlikely, therefore, that seed set would be equally affected by environmental factors in both populations when the potential for environmental variation, as determined by the flowering date QTLs, is so much larger in one of the populations than the other. Therefore, we propose an independent genetic mechanism influencing seed yield in both families. Figure 1 illustrates the LOD profiles for heading date, seed set and seed weight/inflorescence for the ILGI family on LG7 when analysed using MQ (with automatic cofactor selection) and WQC. MQ suggests that heading date and seed set colocalize, and seed weight/spikelet is slightly offset. By contrast, WQC suggests that seeds/inflorescence and seed weight/inflorescence colocalize and that heading date is slightly offset. From these results, and bearing in mind the different years in which the traits were measured, it is not possible to draw a firm conclusion as to whether the locus that is influencing heading date (for which Hd3a is a candidate gene) is the same locus that is directly influencing seed set. If two loci are involved then S5n would be a candidate gene for the latter trait. It is also quite possible that there might be a direct or indirect interaction between a pathway integrator gene involved in flowering induction (Hd3a) and a gene involved in fertility which would contribute to the problems involved in resolving the effects of two closely linked loci in this region.

High seed set is, in both families, associated with early flowering. If it is found that a separate locus (such as an S5n homologue) is responsible for seed-set determination, then the linkage between heading date and seed set could theoretically be broken, allowing plant breeders to select high seed-setting plants of both late and early flowering types. However, if both traits are determined directly by the Hd3a locus, they may be restricted (at least at this locus) to selecting for early flowering genotypes.

It is of interest to note that the S5n allele restores fertility over the semisterile condition of indica/japonica rice hybrids even in heterozygous form (Yanagihara et al., 1995), which is in accordance with our observations of dominance of high seed-setting-associated marker alleles over low ones in our F2/WSC ryegrass mapping family.

Differential resource allocation was approached specifically through a concurrent QTL analysis of flag leaf morphology, and the coincidence of QTLs for flag leaf dimensions in both families with the LG7 QTL for heading date and seed setting might partly explain the sizeable association of flag leaf width with seed yield in the closely related grass species Festuca pratensis, observed by Fang et al. (2004). It is likely that flowering phenology will have a significant influence on the development of vegetative organs. Wider flag leaf widths in the F2/WSC family associated with the ‘Aurora’ parent-derived alleles of the LG7 markers are also associated with the early ‘Aurora’ parent-derived flowering alleles, concomitant with early flowering being associated partly with faster growth rates. However, the relationship between flag leaf length and the heading date QTL on LG7 in the ILGI family is such that longer leaves are associated with later flowering. Therefore, there does not appear to be a direct functional link between heading date and flag leaf size, at least in this family. However, it is worth noting that the QTLs for leaf length and leaf width on LG7 of both families can be associated with the positions of Hd3a and/or S2539/Rz144, markers that are associated with the flowering control genes Hd3a (FT) and Hd1 (CONSTANS), respectively. Thus, there may be a possible linked induction of leaf growth and flowering onset.

There also does not appear to be a simple physiological relationship (i.e. in supply of photosynthate from the flag leaves) between the flag leaf size and seed set, even though the QTLs for these traits on LG7 are closely associated. Although higher seed set is associated with larger leaves in the F2/WSC family, the opposite is the case in the ILGI family. Thus, the association is most likely the result of genetic linkage, rather than physiological coupling.

Quantitative trait loci analyses of inflorescence number and number of spikelets per inflorescence did not reveal any significant QTLs for either family (unpublished results). With no discernible genetic variation for these traits, we assume that, at least in these mapping families, they cannot influence seed set through diversion or dilution of resources that would otherwise be used to maximize seed set.

Genetics and comparative genomics of seed set and heading date QTLs on chromosome 4

The pollen viability data are strongly indicative of a major recessive gene underlying the QTL on LG4 in the F2/WSC family (Table 5). Increased pollen viability derives from the ‘Perma’ (‘bb’) parent. Obligate selfing over four generations was practised to derive the two parent inbred lines of the F2/WSC population, and widespread pollen sterility was observed in the ‘Aurora’ lines (M. Humphreys, pers. comm.). The normal outcrossing nature of perennial ryegrass results in a high mutational load and considerable inbreeding depression upon selfing, thought to be a result of exposure of deleterious recessive genes. Although we cannot be certain, we postulate that the original ‘Aurora’ parent was heterozygous (normal phenotype) for the viability factor and, further, that the F1 plant, selfed to produce the F2/WSC mapping population, was also heterozygous (normal phenotype). The fact that a seed-set QTL is also revealed in this location despite viable pollen being readily available in an open pollinated situation indicates that female gametophyte and/or embryo development is also affected. An anther dehiscence QTL is also present on LG4 and this effect is also associated with the pollen viability/seed-set region (Table 3). Furthermore, poor anther dehiscence appears to be a recessive trait associated with poor pollen viability deriving from the ‘Aurora’ parent (Table 5). However, MQ mapping positioned the major anther dehiscence effect away from the pollen viability/seed-set region and most closely associates it with marker R2702B and a second, less significant QTL for pollen viability (Table 3). Thus, LG4 of the F2/WSC family may contain two distinct loci which can have significant effects on male and female gametophyte development.

In contrast to LG7, on LG4 the loci affecting seed set and heading date in the F2/WSC family were genetically separated, with 8 cm between the two QTL maxima. While the exact position of the heading date QTL on LG4 of the F2/WSC family is always likely to be problematic, given the high percentage variance accounted for by the QTL on LG7 in that family, the fact that a QTL was identified in approximately the same position in the ILGI family does support this location. No seed-set QTL was detected on LG4 in the ILGI family, so the position of the seed-set QTL in the F2/WSC family is not corroborated by the two crosses. However, comparative genomic/QTL analysis with rice does indicate some interesting parallels. It has been established that there is a syntenic relationship between ryegrass LG4 and rice LG3 (Jones et al., 2002; Sim et al., 2005), and 20 comparative markers mapped to ryegrass LG4 in the present study could be aligned with the rice 3 pseudomolecule on the basis of physical position after BLASTN alignments (Fig. 2), although the relationship is by no means absolute, as nine comparative markers could not be assigned to the rice 3 pseudomolecule (F2/WSC: Rz395, PSR922, RZ537, CDO1380; ILGI: BCD1421, PSR305, C764, CDO241, PSR922, PSR144). However, using the relationship described in Fig. 2 as a guide, there are a number of seed yield-associated and heading date QTLs that have been mapped to rice LG3 whose position can be inferred on ryegrass LG4. These results suggest that the ryegrass LG4 seed-set QTL may be equivalent to the rice LG3 gn3 (grains/panicle), spkfrt (spikelet fertility) and gy (grain yield/plant, main effect and epistatic interaction) QTLs; additionally, a recent fine-mapping study (Jing et al., 2007) identified that the rice pollen fertility locus, S33(t), was also associated with this region. A similar comparative analysis also indicates that the ryegrass LG4 heading date QTL may be equivalent to the dth3.3 and dthd days to heading QTLs (see Fig. 2 for references). It has been noted previously that ryegrass LG4 shows a degree of synteny with both Triticeae LG4 and LG5 (Jones et al., 2002; Alm et al., 2003; Jensen et al., 2005) and there are a number of QTLs for seed yield-related traits and heading date that map to these chromosomes in both wheat and barley (see Graingenes; Borner et al., 2002; Pillen et al., 2003; Quarrie et al., 2005). Unfortunately, the lack of common markers between the ryegrass mapping populations and many Triticeae experimental populations means that it is not possible to infer the comparative positions of QTLs with any certainty. However, Bins 5.02–5.03 of maize which include the interval CDO795-CDO542 (see Maize Bins QTL 2005/Cornell Wilson 1999 comparison at; Wilson et al., 1999) are associated with a number of grain yield and seed-weight QTLs, and hence a possible comparative relationship may exist (Veldboom & Lee, 1994; Melchinger et al., 1998, Gramene QTL Acc. ID AQFS1064, AQFS976, AQFS1248 and AQFS977).


Figure 2. Diagrammatic representation of the relative genetic positions of markers mapped onto Lolium perenne chromosome 4 with their physical position on the rice 3 pseudomolecule (bold type) in relation to the inferred positions of selected rice LG3 quantitative trait loci (QTLs). Markers in normal type to the left of the rice 3 axis have been associated with the QTLs on the right of the axis (italics) in rice. LOD profiles are for heading date (solid line) and seeds per spikelet (dashed line). ×, genetic position of L. perenne markers not aligned with rice LG3 pseudomolecule. Hd6, heading date 6 (Yamamoto et al., 2000); gy, grain yield per plant (Li et al., 2001); spkfrt, spikelet fertility (Gramene QTL Acc. ID AQCU108) dthd, days to heading (Gramene QTL Acc. ID AQFW130); dth3.3, days to heading (Thomson et al., 2003); gn3, grains per panicle (Xing et al., 2002); gw3.1, grain weight (Thomson et al., 2003); yld3.1, yield per plant (Thomson et al., 2003); f3, hybrid fertility (Wang et al., 1998); gpp3.1, grains per panicle (Septiningsih et al., 2003); spp3.1, spikelets per panicle (Septiningsih et al., 2003); Hd8, heading date 8 (Takeuchi et al., 2003); Hd9, heading date 9 (Lin et al., 2002).

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Heading date QTLs on chromosomes 4 and 7

The major QTL on LG7 of the F2/WSC population and its association with the positions of the gene Hd3a and Hd1 has been discussed previously (Armstead et al., 2004, 2005). However, it is worth noting that other studies have also detected a QTL in a similar position (Inoue et al., 2004; Jensen et al., 2005). Interestingly, the study that Yamada et al. (2004) undertook on the ILGI population in Japan identified a QTL on LG4, but they reported no QTL on LG7. This underlines the importance of environmental conditions on the genetic control of flowering time, even when putatively identified major genes are concerned.

Quantitative trait loci on LG4 have also been identified in a number of studies on ryegrass populations (Inoue et al., 2004; Yamada et al., 2004; Jensen et al., 2005) and the closely related grass species meadow fescue (Festuca pratensis) (Ergon et al., 2006). Jensen et al. (2005) demonstrated that the ryegrass equivalent of the Triticeae VRN1 vernalization gene mapped to LG4 and could be associated with a QTL for vernalization responsiveness; Shinozuka et al. (2005) showed that the LpCk2α-1 locus also mapped to LG4 and was associated with days to heading. Previously, the lack of common markers between studies has made it difficult to draw many cross-family and/or cross-environment conclusions. However, both VRN1 and LpCk2α-1 have been mapped on the F2/WSC population and the results indicate the QTL peak on LG4 of the F2/WSC population is not directly associated with these two candidate genes. In addition, comparative mapping with rice indicates that it is probably not equivalent to any of the identified rice heading date QTLs Hd6/OsCk2α (Yamamoto et al., 2000; Takahashi et al., 2001), Hd8 (Takeuchi et al., 2003) or Hd9 (Lin et al., 2002). For the ILGI population, the heading date QTL detected on LG4 in the present study colocalized with the LG4 QTL in the F2/WSC family. However, in the study of Yamada et al., 2004) on the ILGI population with phenotype assessment in Japan, the QTL peak was associated more directly with the putative position of VRN1, indicating a second environmental influence on QTL position in this family. Future work within the Lolium/Festuca complex will allow us to clarify further the genetic basis of heading date determination on LG4.


This study has identified two genomic regions with major influence on reduced seed-setting ability. The first, on LG4, identified as a recessive mutation in a finished variety of perennial ryegrass and which results in almost complete sterility, is an example of the high mutational load that outcrossing perennial ryegrass carries. The second, on LG7, although clearly at least partially recessive in nature, is more difficult to identify phenotypically and requires accurate seed-set determination and, in future, an anatomical investigation of the seed developmental process. Evidence from the only two populations that have so far been studied for seed setting in perennial ryegrass suggests that there is selectable variation at this locus that could significantly increase seed-setting ability in commercial cultivars. Molecular markers for this gene, including those developed in this study, will be useful for identifying favourable allelic variants in these and other populations, with the aim of incorporating them into different breeding populations. In rice, it is likely that the S5n locus is determined by one of five candidate genes (Qiu et al., 2005) and, although we cannot preclude the involvement of the Hd3 gene, the same gene may well be responsible for the seed-setting QTL on ryegrass LG7. Further research to identify allelic variation within the orthologous ryegrass genes, either by direct sequencing or by utilizing an eco-tilling approach (Mejlhede et al., 2006), will prove useful towards both validating the gene/trait relationship and developing molecular markers for selection within ryegrass populations.

The discovery of loci with a major effect on seed setting also has a practical application: much breeding effort has been focused on improving the vegetative characteristics of grasses used for forage (Wilkins & Humphreys, 2003) and ornamental and sports turf. Yet seed yield is also an important trait, as seed growers are reluctant to grow poor-yielding cultivars even if the contracting seed company is willing to pay a premium price for the seed produced. Selection for seed production traits that are dependent on preferable allocation of resources from vegetative to reproductive organs will inevitably be detrimental to agronomic traits determined by good vegetative yield and quality, and so will be negatively correlated with agronomic performance (Wilkins, 1991). However, seed set (i.e. the proportion of florets that produce a seed, sensu strictu caryopsis) and seed retention are two reproductive traits that are independent of vegetative growth performance traits (Wilkins, 1991) which breeders of outcrossing forage crops should focus on.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

This work was supported by the Biotechnology and Biological Sciences Research Council, UK.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • Alm V, Fang C, Busso CS, Devos KM, Vollan K, Grieg Z, Rognli OA. 2003. A linkage map of meadow fescue (Festuca pratensis Huds.) and comparative mapping with other Poaceae species. Theoretical and Applied Genetics 108: 2540.
  • Armstead IP, Skøt L, Turner LB, Skøt K, Donnison IS, Humphreys MO, King IP. 2005. Identification of perennial ryegrass (Lolium perenne (L.) and meadow fescue (Festuca pratensis (Huds.) candidate orthologous sequences to the rice Hd1 (Se1) and barley HvCO1 CONSTANS-like genes through comparative mapping and microsynteny. New Phytologist 167: 239247.
  • Armstead IP, Turner LB, Farrell M, Skøt L, Gomez P, Montoya T, Donnison IS, King IP, Humphreys MO. 2004. Synteny between a major flowering date QTL in perennial ryegrass (Lolium perenne L.) and the Hd3 flowering date locus in rice. Theoretical and Applied Genetics 108: 822828.
  • Armstead IP, Turner LB, King IP, Cairns AJ, Humphreys MO. 2002. Comparison and integration of genetic maps generated from F-2 and BC1-type mapping populations in perennial ryegrass. Plant Breeding 121: 501507.
  • Barker RE, Wender WF, Welty RE. 2003. Selection for stem rust resistance in tall fescue and its correlated response with seed yield. Crop Science 43: 7579.
  • Borner A, Schumann E, Furste A, Coster H, Leithold B, Roder MS, Weber WE. 2002. Mapping of quantitative trait loci determining agronomic important characters in hexaploid wheat (Triticum aestivum L.). Theoretical and Applied Genetics 105: 921936.
  • Bremner PM, Rawson HM. 1978. Weights of individual grains of wheat ear in relation to their growth potential, supply of assimilate and interaction between grains. Australian Journal of Plant Physiology 5: 6172.
  • Burbridge A, Hebblethwaite PD, Ivins JD. 1978. Lodging studies in Lolium perenne grown for seed. 2. Floret site utilisation. Journal of Agricultural Science 90: 269274.
  • Charlesworth D. 1989. Why do plants produce so many more ovules than seeds? Nature 338: 2122.
  • Charlesworth D, Charlesworth B. 1987. Inbreeding depression and its evolutionary consequences. Annual Review of Ecology and Systematics 18: 237268.
  • Cooper JP. 1954. Studies on growth and development in Lolium IV. Genetic control of heading responses in local populations. Journal of Ecology 42: 521556.
  • Corkill L. 1956. The basis of synthetic strains of cross-pollinated grasses. Proceedings 7th International Grassland Congress. Palmerston North, New Zealand: Massey Agricultural College, 427438.
  • Cornish MA, Hayward MD, Lawrence MJ. 1980. Self-incompatibility in ryegrass IV. Seed set in diploid Lolium perenne L. Heredity 44: 333340.
  • Devey F, Fearon CH, Hayward MD, Lawrence MJ. 1994. Self-incompatibility in ryegrass. 11. Number and frequency of alleles in a cultivar of Lolium perenne L. Heredity 73: 262264.
  • Elgersma A. 1990. Genetic variation for seed yield in perennial ryegrass (Lolium perenne L.). Plant Breeding 105: 117125.
  • Elgersma A, Sniezko R. 1988. Cytology of seed development related to floret position in perennial ryegrass (Lolium perenne L.). Euphytica Suppl. S5968.
  • Elgersma A, Van Wijk AJP. 1997. Breeding for higher seed yields in grasses and forage legumes. In: FaireyDT, HamptonJG, eds. Forage seed production: temperate species, Vol. 1. Alberta, Canada: CABI, 243270.
  • Ergon Å, Fang C, Jørgensen Ø, Aamlid TS, Rognli OA. 2006. Quantitative trait loci controlling vernalisation requirement, heading time and number of panicles in meadow fescue (Festuca pratensis Huds.). Theoretical and Applied Genetics 112: 232242.
  • Fang C, Aamlid TS, Jorgensen O, Rognli OA. 2004. Phenotypic and genotypic variation in seed production traits within a full-sib family of meadow fescue. Plant Breeding 123: 241246.
  • Fearon CH, Cornish MA, Hayward MD, Lawrence MJ. 1994. Self-incompatibility in ryegrass. 10. Number and frequency of alleles in a natural-population of Lolium perenne L. Heredity 73: 254261.
  • Griffith SM, Alderman SC, Streeter DJ. 1997. Italian ryegrass and nitrogen source fertilisation in Western Oregon in two contrasting climatic years. 1. Growth and seed yield. Journal of Plant Nutrition 20: 419428.
  • Ikehashi H, Araki H. 1988. Multiple alleles controlling F1-sterility in remote crosses of rice (Oryza sativa). Japanese Journal of Breeding 38: 283291.
  • Inoue M, Gao ZS, Hirata M, Fujimori M, Cai HW. 2004. Construction of a high-density linkage map of Italian ryegrass (Lolium multiflorum Lam.) using restriction fragment length polymorphism, amplified fragment length polymorphism, and telomeric repeat associated sequence markers. Genome 47: 5765.
  • Jensen LB, Andersen JR, Frei U, Xing YZ, Taylor C, Holm PB, Lubberstedt TL. 2005. QTL mapping of vernalization response in perennial ryegrass (Lolium perenne L.) reveals co-location with an orthologue of wheat VRN1. Theoretical and Applied Genetics 110: 527536.
  • Ji Q, Lu JF, Chao Q, Gu MH, Xu ML. 2005. Delimiting a rice wide-compatibility gene inline imageto a 50 kb region. Theoretical and Applied Genetics 111: 14951503.
  • Jing W, Zhang WW, Jiang L, Chen LM, Zhai HQ, Wan JM. 2007. Two novel loci for pollen sterility in hybrids between the weedy strain Ludao and the Japonica variety Akihikari of rice (Oryza sativa L.). Theoretical and Applied Genetics 114: 915925.
  • Jones ES, Mahoney NL, Hayward MD, Armstead IP, Jones JG, Humphreys MO, King IP, Kishida T, Yamada T, Balfourier F et al . 2002. An enhanced molecular marker based genetic map of perennial ryegrass (Lolium perenne) reveals comparative relationships with other Poaceae genomes. Genome 45: 282295.
  • Leidl B, Anderson MO. 1993. Reproductive barriers: identification, uses, and circumvention. Plant Breeding Review 11: 11154.
  • Li ZK, Luo LJ, Mei HW, Wang DL, Shu QY, Tabien R, Zhong DB, Ying CS, Stansel JW, Khush GS et al . 2001. Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice. I. Biomass and grain yield. Genetics 158: 17371753.
  • Lin HX, Ashikari M, Yamanouchi U, Sasaki T, Yano M. 2002. Identification and characterization of a quantitative trait locus, Hd9, controlling heading date in rice. Breeding Science 52: 3541.
  • Marshall C, Ludlam D. 1989. The pattern of abortion of developing seeds in Lolium perenne L. Annals of Botany 63: 1927.
  • Martiniello P. 1998. Influence of agronomic factors on the relationship between forage production and seed yield in perennial forage grasses and legumes in a Mediterranean environment. Agronomie 18: 591601.
  • Mejlhede N, Kyjovska Z, Backes G, Burhenne K, Rasmussen SK, Jahoor A. 2006. EcoTILLING for the identification of allelic variation in the powdery mildew resistance genes mlo and Mla of barley. Plant Breeding 125: 461467.
  • Melchinger AE, Kreps R, Spath R, Klein D, Schulz B. 1998. Evaluation of early-maturing European maize inbreds for resistance to the European corn borer. Euphytica 99: 115125.
  • Monna L, Lin HX, Kojima S, Sasaki T, Yano M. 2002. Genetic dissection of a genomic region for a quantitative trait locus, Hd3, into two loci, Hd3a and Hd3b, controlling heading date in rice. Theoretical and Applied Genetics 104: 772778.
  • Pillen K, Zacharias A, Leon J. 2003. Advanced backcross QTL analysis in barley (Hordeum vulgare L.). Theoretical and Applied Genetics 107: 340352.
  • Qiu SQ, Liu KD, Jiang JX, Song X, Xu CG, Li XH, Zhang QF. 2005. Delimitation of the rice wide compatibility gene S5n to a 40-kb DNA fragment. Theoretical and Applied Genetics 111: 10801086.
  • Quarrie SA, Steed A, Calestani C, Semikhodskii A, Lebreton C, Chinoy C, Steele N, Pljevljakusic D, Waterman E, Weyen J et al . 2005. A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring, X SQ1 and its use to compare QTLs for grain yield across a range of environments. Theoretical and Applied Genetics 110: 865880.
  • Rogers ME. 1989. Variation in turf-type morphology characters. Australian Journal of Agricultural Research 40: 851859.
  • Septiningsih EM, Prasetiyono J, Lubis E, Tai TH, Tjubaryat T, Moeljopawiro S, McCouch SR. 2003. Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon. Theoretical and Applied Genetics 107: 14191432.
  • Shinozuka H, Hisano H, Ponting RC, Cogan NOI, Jones ES, Forster JW, Yamada T. 2005. Molecular cloning and genetic mapping of perennial ryegrass casein protein kinase 2 alpha-subunit genes. Theoretical and Applied Genetics 112: 167177.
  • Sim S, Chang T, Curley J, Warnke SE, Barker RE, Jung G. 2005. Chromosomal rearrangements differentiating the ryegrass genome from the Triticeae, oat, and rice genomes using common heterologous RFLP probes. Theoretical and Applied Genetics 110: 10111019.
  • Skøt L, Humphreys MO, Armstead I, Heywood S, Skøt KP, Sanderson R, Thomas ID, Chorlton KH, Hamilton NRS. 2005. An association mapping approach to identify flowering time genes in natural populations of Lolium perenne (L.). Molecular Breeding 15: 233245.
  • Takahashi Y, Shomura A, Sasaki T, Yano M. 2001. Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the alpha subunit of protein kinase CK2. Proceedings of the National Academy of Sciences, USA 98: 79227927.
  • Takeuchi Y, Lin SY, Sasaki T, Yano M. 2003. Fine linkage mapping enables dissection of closely linked quantitative trait loci for seed dormancy and heading in rice. Theoretical and Applied Genetics 107: 11741180.
  • Thomson MJ, Tai TH, McClung AM, Lai XH, Hinga ME, Lobos KB, Xu Y, Martinez CP, McCouch SR. 2003. Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson. Theoretical and Applied Genetics 107: 479493.
  • Thorogood D, Armstead IP, Turner LB, Humphreys MO, Hayward MD. 2005. Identification and mode of action of self-compatibility loci in Lolium perenne L. Heredity 94: 356363.
  • Thorogood D, Kaiser WJ, Jones JG, Armstead I. 2002. Self-incompatibility in ryegrass 12. Genotyping and mapping the S and IX loci of Lolium perenne L. Heredity 88: 385390.
  • Thorogood D, Paget MF, Humphreys MO, Turner LB, Armstead IP, Roderick HW. 2001. QTL analysis of crown rust resistance in perennial ryegrass – implications for breeding. International Turfgrass Society Research Journal 9: 218223.
  • Turner LB, Cairns AJ, Armstead IP, Ashton J, Skøt K, Whittaker D, Humphreys MO. 2006. Dissecting the regulation of fructan metabolism in perennial ryegrass (Lolium perenne) with quantitative trait locus mapping. New Phytologist 169: 4557.
  • UPOV (International Union for the Protection of New Varieties of Plants). 2006. Ryegrass. guidelines for the conduct of tests for distinctness, uniformity and stability. [] (accessed: 29-10-07.)
  • Van Ooijen JW, Boer MP, Jansen RC, Maliepaard C. 2001. JoinMap® 3.0, Software for the calculation of genetic linkage maps. Wageningen, the Netherlands: Plant Research International.
  • Van Ooijen JW, Boer MP, Jansen RC, Maliepaard C. 2002. Map QTL4.0, Software for the calculation of QTL positions on genetic maps. Wageningen, the Netherlands: Plant Research International.
  • Veldboom LR, Lee M. 1994. Molecular-marker-facilitated studies of morphological traits in maize. 2. Determination of QTLs for grain-yield and yield components. Theoretical and Applied Genetics 89: 451458.
  • Wang SCJ, Basten CJ, Zeng Z-B. 2005. Windows QTL cartographer 2.5. Raleigh, NC, USA: Department of Statistics, North Carolina State University.
  • Wang J, Liu KD, Xu CG, Li XH, Zhang QF. 1998. The high level of wide compatibility of variety ‘Dular’ has a complex genetic basis. Theoretical and Applied Genetics 97: 407412.
  • Wedderburn ME, Smith DR, Pengelly WJ, Greaves LA. 1992. Heritability of response to moisture stress in a New Zealand North Island hill country ryegrass collection grown with and without nitrogen fertiliser. New Zealand Journal of Agricultural Research 35: 4150.
  • Wiens D. 1984. Ovule survivorship, brood size, life-history, breeding systems, and reproductive success in plants. Oecologia 64: 4753.
  • Wilkins PW. 1991. Breeding perennial ryegrass for agriculture. Euphytica 52: 201214.
  • Wilkins PW, Humphreys MO. 2003. Progress in breeding perennial forage grasses for temperate agriculture. Journal of Agricultural Science 140: 129150.
  • Wilson WA, Harrington SE, Woodman WL, Lee M, Sorrells ME, McCouch SR. 1999. Inferences on the genome structure of progenitor maize through comparative analysis of rice, maize and the domesticated panicoids. Genetics 153: 453473.
  • Xing YZ, Tan YF, Hua JP, Sun XL, Xu CG, Zhang Q. 2002. Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theoretical and Applied Genetics 105: 248257.
  • Yamada T, Jones ES, Cogan NOI, Vecchies AC, Nomura T, Hisano H, Shimamoto Y, Smith KF, Hayward MD, Forster JW. 2004. QTL analysis of morphological, developmental, and winter hardiness-associated traits in perennial ryegrass. Crop Science 44: 925935.
  • Yamamoto T, Lin HX, Sasaki T, Yano M. 2000. Identification of heading date quantitative trait locus Hd6 and characterization of its epistatic interactions with Hd2 in rice using advanced backcross progeny. Genetics 154: 885891.
  • Yanagihara S, McCouch SR, Ishikawa K, Ogi Y, Maruyama K, Ikehashi H. 1995. Molecular analysis of the inheritance of the S-5 locus, conferring wide compatibility in Indica/Japonica hybrids of rice (O. sativa L.). Theoretical and Applied Genetics 90: 182188.
  • Yano M, Katayose Y, Ashikari M, Yamanouchi U, Monna L, Fuse T, Baba T, Yamamoto K, Umehara Y, Nagamura Y et al . 2000. Hd1, a major photoperiod sensitivity quantitative trait locus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS. Plant Cell 12: 24732483.

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Table S1 Primer sequences for newly designed markers in the LG4 and LG7 regions coinciding with heading date and seed-set quantitative trait loci, and the map positions of all LG4 and LG7 markers used in both mapping families

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NPH_2413_sm_Suppmat.doc123KSupporting info item