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A study on the susceptibility of rice cultivars to Striga hermonthica and mapping of Striga tolerance quantitative trait loci in rice

2008; Wiley; Volume: 180; Issue: 1 Linguagem: Inglês

10.1111/j.1469-8137.2008.02568.x

1469-8137

Krittika Kaewchumnong, Adam H. Price,

Plant and animal studies

New PhytologistVolume 180, Issue 1 p. 206-216 Free Access A study on the susceptibility of rice cultivars to Striga hermonthica and mapping of Striga tolerance quantitative trait loci in rice Krittika Kaewchumnong, Krittika Kaewchumnong Institute of Biological and Environmental Sciences, University of Aberdeen, AB24 3UU, UK; (Present address) Department of Biology, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, 90112, ThailandSearch for more papers by this authorAdam H. Price, Adam H. Price Institute of Biological and Environmental Sciences, University of Aberdeen, AB24 3UU, UK;Search for more papers by this author Krittika Kaewchumnong, Krittika Kaewchumnong Institute of Biological and Environmental Sciences, University of Aberdeen, AB24 3UU, UK; (Present address) Department of Biology, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, 90112, ThailandSearch for more papers by this authorAdam H. Price, Adam H. Price Institute of Biological and Environmental Sciences, University of Aberdeen, AB24 3UU, UK;Search for more papers by this author First published: 02 September 2008 https://doi.org/10.1111/j.1469-8137.2008.02568.xCitations: 15 Author for correspondence:Krittika KaewchumnongTel:+66 (0) 74 288496 Fax:+66 (0) 74 212917Email: [email protected] AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Summary • Striga is a parasitic weed attacking mainly maize, sorghum, millet and cowpea. Studying the interaction between rice and Striga is valuable since rice is a model monocot. In this paper, the susceptibility of different rice cultivars to S. hermonthica was tested and quantitative trait loci (QTL) for Striga tolerance mapped on the Bala × Azucena F6 population. • Seven rice cultivars were grown with and without S. hermonthica for 14 wk. For the mapping experiment, 115 recombinant inbred lines (RILs), along with Azucena and Bala, were grown with and without Striga for 11 wk. • Rice cultivars tested had different susceptibilities to Striga, ranging from highly susceptible to completely resistant. Azucena and Bala differed in the speed of Striga emergence and the impact on host growth. A genomic region between positions 139 and 166 cM on chromosome 1 was identified containing strong QTL (LOD = 4.9–15.7) for all traits measured. • This indicates that genes for Striga tolerance exist in rice germplasm and the mapped QTL can be further studied to promote understanding of the nature of resistance/tolerance and breeding for Striga-resistant crop plants. Introduction Striga is an important weed distributed in Africa, Asia, Australia and some parts of the United States (Kroschel, 2001). S. hermonthica and S. asiatica parasitize monocotyledonous crops such as maize (Zea mays), sorghum (Sorghum bicolor) and pearl millet (Pennisetum glaucum), while S. gesnerioides parasitizes dicotyledonous crops, mainly cowpea (Vigna unguiculata) (Parker & Riches, 1993; Cechin, 1994; Humphrey et al., 2006). Although not a problem in irrigated rice (Oryza sativa), serious losses in upland rice caused by Striga species, including S. hermonthica, have been reported in sub-Saharan Africa (Johnson et al., 1997). Losses resulting from Striga can range from slight to total crop failure in heavily infested areas (Dugje et al., 2006). Losses in cereal production are as high as US$311 million annually (Ransom, 2000). Striga seeds in the soil will pass after-ripening and preconditioning periods to break dormancy (Parker & Riches, 1993). Then they will receive germination stimulants and haustorial inducing factors exuded from the host roots which stimulate seed germination and the attachment to the root using a specialized organ called the haustorium (Haussmann et al., 2000). The parasites will abstract water and nutrient from the host roots via the haustoria. Infected host plants show symptoms of stunting, chlorosis and even death in the most severe case of parasitism (Haussmann et al., 2000). The most effective way to control Striga is to use resistant crop cultivars (Verkleij & Kuijper, 2000). As a cheap and potentially durable control, they are suitable for subsistence farmers (Haussmann & Hess, 2001). Resistance to Striga has been found to be controlled by both major and minor genes. Kim (1994) studied the inheritance of tolerance and resistance to Striga in maize and found the traits to be polygenic and quantitative inherited. Vogler et al. (1996) used sorghum populations derived from the resistant line 'SRN-39' and three susceptible lines and found that the resistance to Striga was controlled by a single nuclear recessive gene. Haussmann et al. (2001) also used F2 and F3 recombinant inbred populations of sorghum and found the resistance to be controlled by a major recessive gene and some minor genes. Both groups have used an agar gel assay to determine the inheritance of low production of Striga germination stimulant, which is a trait with variability in sorghum. Xu et al. (2001) have mapped the gene for this trait using recombinant inbred lines (RILs) and found it to be located on linkage group J of the sorghum genome. Haussmann et al. (2004) have mapped several QTL for Striga resistance in sorghum. This revealed nine to 11 QTL, explaining 77–82% of the phenotypic variation. Of these, the most significant QTL corresponds to the major gene locus lgs for low stimulation of Striga seed germination in linkage group I. For rice, Gurney et al. (2006) have evaluated post-attachment resistance in a number of cultivars and found Nipponbare expressing a strong post-attachment resistance to Striga. In this cultivar, the parasites failed to form xylem–xylem connection to the host roots. A mapping experiment was conducted using backcross inbred lines derived from crosses between Nipponbare and a susceptible cultivar Kasalath. The results revealed seven QTL for resistance to Striga on chromosomes 1, 4, 5, 6, 7, 8 and 12, explaining 31% of the overall phenotypic variance. A second screen confirmed four of these QTL on chromosomes 4, 5, 6 and 12. Mapping of Striga resistance/tolerance QTL in rice will be an important step in reducing the impact of Striga in upland rice and in tropical cereals in general, the latter because rice is the model monocot. It has a small genome (c. 440 Mbp) (Delseny et al., 2001), complete genome sequence (Shimamoto & Kyozuka, 2002) and widespread availability of genetic and physical maps (Mohan et al., 1997), which are excellent for QTL studies. This can help in the transfer of resistance and tolerance genes from rice to other cereals such as maize, sorghum and millet by marker-assisted selection through the use of synteny (similarity in their chromosomal gene order), or once genes involved in rice–Striga interactions are identified and characterized. In this paper, experiments have been conducted to investigate the variation in susceptibility to S. hermonthica across several rice cultivars and to map Striga tolerance QTL in rice using the Bala × Azucena F6 mapping population. Materials and Methods Plant material Rice seeds of Oryza sativa L. cvs Azucena, Bala, IR64, Kasalath, Moroberekan and Nipponbare, and O. glaberrima (Steud.) cv. CG14 were obtained from the International Rice Research Institute (IRRI), the Philippines. For the mapping experiment, a mapping population of 115 F6 RILs derived from Bala × Azucena was used. The parents were originally obtained from IRRI. Full details of population production are given in Price et al. (2000). Striga seeds used in this project were S. hermonthica (Del.) Benth collected from sorghum host in Mali in 2003 for the experiment on different rice cultivars and in 2004 for the mapping experiment. Both batches of seeds were from similar geographical regions. They were purchased from Ibrahima Sissoko, ICRISAT, Mali. Variation in Striga susceptibility across different rice cultivars A previous experiment using variable Striga seed inocula (0, 200, 1000, 4000 and 10 000 viable seeds) in 13-cm-diameter (1 l) pots using maize and rice identified 4000 Striga seeds as a suitable inoculum to observe the effect of Striga on both crops (Kaewchumnong, 2007). The treatment with 4000 Striga seeds had the same effect on the host as that using 10 000 seeds, and the Striga emerged earlier than in the treatment with 1000 seeds. Another experiment testing the effect of different pot sizes (diameters 3.5, 6, 8 and 13 cm) on the interaction between Striga and rice cvs Azucena, Bala and IR64 identified a 13 cm pot as a suitable pot size to detect distinct effects of Striga on rice (Kaewchumnong, 2007). Therefore, 13-cm-diameter pots and 4000 Striga seeds were used in this experiment. The pots were filled with John Innes No. 2 soil and sand mixture in 50 : 50 ratio in three layers. The bottom (3 cm) and top (2 cm) layers were filled with soil and sand mixture. The middle layer (5 cm) was filled with soil and sand mixed with 0 (control) or 4000 Striga seeds per pot. The pots were placed on a damp capillary mat to keep moist in a completely randomized design, watered, and left for 10 d to precondition the Striga seeds. After that, five replicates of the rice seedlings (pregerminated for 3 d at 37°C) of the seven cultivars were sown, one seedling per pot. The experiment was set up in August 2004 in a glasshouse at 25°C minimum, 50–70% humidity, supplied with supplementary light of 120–150 µmol m−2 s−1 PAR at plant height for 12 h d−1. Approximately 50 ml of Phostrogen (PBI Home & Garden Ltd., Herts, UK) (1 g l−1) was added to each pot once a week from week 6 onwards as a supplementary nutrient. Rice plant height to the highest ligule was measured and Striga number per pot was counted every week from week 5 to 14 after sowing. At harvest, the dry weights of the rice stem, leaf, flower and root were measured, as was leaf area (Area Measurement System, Delta-T Devices Ltd, Cambridge, UK). Mapping Striga tolerance QTL in rice A total of 115 RILs and five plants of each Azucena and Bala were used in each replicate. Five replicates were used for Striga-infected treatment and three replicates for control. The experiment was conducted in two runs; the first, sown on 7 November 2005, contained three Striga and one control replicate, whilst the second, sown on 28 February 2006, contained two of each. The pots and Striga application were as described earlier. A single germinated rice seedling was sown in each pot. Plants were grown in a controlled environment room at 25°C, 50% humidity, 580 µmol m−1 s−1 PAR at plant height for 12 h d−1. The plants were watered every day and supplied with Phostrogen at the same rate as the previous experiment at 4, 7 and 9 wk after sowing. Emerged Striga plants in each pot were counted every week. The height of rice plants to the highest ligule was measured at 5 and 9 wk after sowing. At harvest (11 wk after sowing), rice leaf, stem and grain dry weights were measured and leaf/stem ratio calculated. Striga dry weight was also measured. Data handling Rice shoot dry weight was calculated from the sum of leaf, stem and grain dry weights. Leaf/stem ratio was calculated from the division of leaf dry weight by stem dry weight for each plant. In the QTL experiment, the time of first Striga emergence was reported as the earliest day of Striga emergence over all five replicates. They could not be calculated as an average day of first emergence among all replicates because of the absence of Striga emergence in some of the replicates. Data were analysed by one-way analysis of variance (ANOVA, Minitab 14). Comparisons of means were conducted by Tukey's test with family error rate of 5%. For the QTL mapping, relative values for rice plant height, leaf dry weight, stem dry weight, shoot dry weight and leaf/stem ratio were calculated as the mean value of the Striga-treated replicates divided by the mean of the control replicates. The relative values for leaf dry weight, stem dry weight and shoot dry weight were square-root-transformed to achieve normal distribution while leaf/stem ratio was transformed using log10(x) before QTL analysis. The data for Striga dry weight, Striga number per pot and time of first Striga emergence could not be fully normalized. However, they were transformed using square root, log10(x + 1) and log10(x), respectively, as these produced the closest approximation to normal distribution. Broad-sense heritability was computed from two-way analysis of variance (factors: genotype and replicate) of the F6 from the estimates of genetic () and residual () variance derived from the expected mean squares as H2 = /( + /k), where k was the number of replications. QTL analysis The identification of QTL was by composite interval mapping (CIM) using the program QTLCartographer version 1.15 (C. J. Basten, B. S. Weir and Z.-B. Zeng, Department of Statistics, North Carolina State University, NC, USA). CIM used model 6 using the default parameters and 'forward stepwise regression with backward elimination' to identify background markers (maximum 10). Permutation testing (1000 permutations) using QTLCartographer on some of the traits indicated that a LOD score of 3.2–3.4 is suitable as the genome-wide 5% significant threshold for this set of data. These QTL with LOD ≥ 3.2 are shown in Table 4. The sign of the LOD score indicates the effect of the Azucena allele (i.e. if the LOD score value is positive, the Azucena allele increases the trait value). Putative QTL revealed at LOD 2.5–3.1 are also shown in Fig. 3 because they could be true QTL given the high thresholds used in QTL analysis used to eliminate false-positives. These putative QTL are not considered biologically significant unless other evidence validates them. Table 4. Quantitative trait loci (QTL) for traits associated with Striga tolerance revealed by composite interval mapping Trait Chromosome QTL position in cM LOD R 2 (%) Donor of QTL Above (−) or below (+) nearest marker From the top of linkage group HS/C 1 C1370−5 143 7.8 20.8 Az 2 RG171+14 74 4.9 22.4 Az 6 P0457F09+6 157 4.9 14.8 Az 11 RZ141−4 18 5.8 16.8 Az LDWS/C 1 C1370+2 150 10.4 30.4 Az SDWS/C 1 C1370+2 150 7.0 22.8 Az SHDWS/C 1 C1370 148 15.7 26.1 Az 2 RG171+12 72 8.0 22.2 Az 4 RG163+2 83 8.8 15.3 Ba 8 P0498H04 6 4.5 8.8 Az 9 G385−5 55 6.3 13.0 Az 11 RZ141−6 16 4.2 8.8 Az L/S of S/C 1 C1370−1 147 6.8 22.0 Ba 6 P0457F09 151 3.5 10.3 Ba STDW 1 R2417 156 4.9 11.0 Ba 6 a123618 96 4.8 11.2 Ba SN 1 R2417 156 7.6 18.4 Ba TFE 1 C1370+2 150 5.8 14.4 Az 2 RM211 0 3.9 12.9 Ba 2 P0654B04+2 152 4.0 9.8 Ba 11 R642+2 2 3.6 10.0 Az 12 C449−1 86 4.9 12.3 Ba HS/C, rice plant height of Striga/control treatment; LDWS/C, rice leaf dry weight of Striga/control treatment; SDWS/C, rice stem dry weight of Striga/control treatment; SHDWS/C, rice shoot dry weight of Striga/control treatment; L/S of S/C, rice leaf/stem ratio of Striga/control treatment; STDW, Striga dry weight; SN, Striga number at week 11; TFE, time of first Striga emergence. Figure 3Open in figure viewerPowerPoint Molecular maps with RFLP and microsatellite markers indicated (name of AFLP markers omitted unless mentioned in the text), showing quantitative trait loci (QTL) for Striga tolerance traits. The boxes represent the 1 LOD interval and the number above or below the box indicates the LOD score for the QTL. A positive LOD value indicates that Azucena alleles increase the value of the trait. Results Variation in Striga susceptibility across different rice cultivars Striga number per pot differed significantly between genotypes from day 49 onwards (Fig. 1; P ≤ 0.001 until day 86, ≤ 0.01 until day 95, ≤ 0.05 until day 105). The rice cultivars can be separated into three groups. Striga emerged early in Bala and IR64 (mean of 46.4 and 47.6 d after sowing, respectively), while in Azucena and Kasalath they emerged later but had a higher number (mean of 10.6 and 8.8 plants per pot at the highest, respectively). CG14, Moroberekan and Nipponbare form the third group with none or a low number of Striga. The measurement of plant height revealed a significant reduction of height in Bala and IR64 from week 5, in Azucena from week 7 and in Moroberekan from week 14 onwards (data not shown). In the other varieties, height was not significantly affected by treatment. Figure 1Open in figure viewerPowerPoint Striga number per pot of rice cvs Azucena, Bala, CG14, IR64, Kasalath, Moroberekan and Nipponbare between 34 and 105 d after planting. Vertical bars presented above the main plot represent the pooled SD from one-way ANOVA (which approximates to the one-sided 95% confidence interval for each cultivar). At harvest, Azucena, Bala and IR64 had significantly reduced leaf area, stem, leaf, flower + grain and plant dry weight as a result of the Striga treatment (Table 1). Bala, IR64, Kasalath and Nipponbare had higher leaf/stem and root/shoot ratios upon Striga treatment. Striga did not affect any harvest trait of CG14 and Moroberekan. It should be noted, however, that the data for growth traits in Moroberekan are rather varied because one plant of the Striga treatment (which did not have any visible Striga) grew very well, which was in marked contrast to the four plants with visible Striga, which had plant mass ranging from 13 to 46% of the mean control value. Thus the conclusions on this cultivar cannot be considered robust. Three Nipponbare plants treated with Striga also had no visible Striga and yet all grew more poorly than the smallest control plant and had higher leaf/stem ratios than all control plants. Fig. 2 shows a regression of the mean time when Striga first appeared in a pot against relative plant mass of Striga-infected/control plants. It shows that the speed of Striga emergence was the main determinant of its effect on host growth. CG14 is the most resistant cultivar, while IR64 and Bala are the most susceptible. Nipponbare is resistant because Striga appears late and it supports low Striga numbers. Kasalath is a tolerant cultivar as Striga appears relatively early and it supports a large number of Striga but still has high Striga-infected/control plant mass. Azucena appears to be more tolerant than Bala, as the effect of Striga on host traits is reduced and Striga appears later. Table 1. The effect of Striga on traits at harvest of different rice cultivars Cultivar Treatment Stem dry wt (g) Leaf dry wt (g) Flower + grain dry wt (g) Root dry wt (g) Plant dry wt (g) Leaf/stem ratio Root/shoot ratio Leaf area (cm2) Azucena Striga 3.11 ± 0.56* 3.90 ± 0.45* na 7.04 ± 1.42 14.0 ± 2.3* 1.33 ± 0.15* 1.00 ± 0.12 418 ± 44* control 15.55 ± 3.92 9.32 ± 0.93 na 19.65 ± 7.38 44.5 ± 11.3 0.68 ± 0.11 0.73 ± 0.22 929 ± 103 Bala Striga 0.74 ± 0.33* 1.16 ± 0.34* 0.00 ± 0.00* 2.97 ± 1.47 4.9 ± 2.1* 2.00 ± 0.36* 1.45 ± 0.30* 226 ± 59* control 12.12 ± 1.34 6.83 ± 0.70 3.13 ± 1.13 6.73 ± 0.92 28.8 ± 2.9 0.63 ± 0.13 0.30 ± 0.03 915 ± 74 CG14 Striga 9.84 ± 2.03 5.13 ± 0.67 3.21 ± 1.13 4.98 ± 1.02 23.2 ± 3.8 0.59 ± 0.10 0.27 ± 0.03 610 ± 67 control 10.78 ± 1.50 5.12 ± 0.83 1.94 ± 0.87 4.65 ± 1.28 22.5 ± 4.4 0.48 ± 0.06 0.25 ± 0.02 599 ± 60 IR64 Striga 1.23 ± 0.34* 2.18 ± 0.49* 0.09 ± 0.04* 1.83 ± 0.38* 5.3 ± 1.1* 1.93 ± 0.20* 0.55 ± 0.05* 314 ± 56* control 9.87 ± 1.53 5.04 ± 0.97 8.21 ± 1.27 5.03 ± 0.87 28.1 ± 3.6 0.52 ± 0.10 0.22 ± 0.04 719 ± 72 Kasalath Striga 5.54 ± 1.11* 5.21 ± 0.49 0.89 ± 0.51 8.70 ± 1.56 20.3 ± 2.4 1.05 ± 0.14* 0.80 ± 0.13* 594 ± 35 control 15.04 ± 3.11 6.13 ± 1.01 1.61 ± 0.71 5.18 ± 1.66 28.0 ± 5.6 0.43 ± 0.04 0.23 ± 0.05 614 ± 100 Moroberekan Striga 5.27 ± 2.52 3.25 ± 1.03 na 6.33 ± 3.64 14.8 ± 7.1 1.01 ± 0.28 0.66 ± 0.10 349 ± 78 control 8.98 ± 1.85 6.66 ± 1.08 na 11.23 ± 4.17 26.9 ± 6.5 0.77 ± 0.06 0.66 ± 0.22 622 ± 85 Nipponbare Striga 5.54 ± 0.56* 2.51 ± 0.27 4.11 ± 0.70* 3.72 ± 0.60 15.9 ± 1.7* 0.46 ± 0.04* 0.30 ± 0.02* 386 ± 64 control 8.85 ± 0.74 2.34 ± 0.07 8.10 ± 0.70 2.59 ± 0.28 21.9 ± 0.7 0.27 ± 0.02 0.13 ± 0.01 333 ± 36 Data are means ± SE.na, not applicable.*Significant differences between Striga and control pairs at P = 0.05 by Tukey's test, n = 5. Figure 2Open in figure viewerPowerPoint Regression of the day that Striga first appeared against percentage of Striga-infected/control plant mass. Bars represent SE. #, note that in pots where no Striga were observed (one Moroberekan, three Nipponbare and all five CG14 replicates), 105 d was used to produce this graph. Mapping Striga tolerance QTL in rice Comparison of trait mean values Table 2 shows the comparison of mean values and heritabilities of traits for Striga tolerance. In the control treatment, Azucena and Bala had comparable mean values for rice plant height, leaf dry weight, stem dry weight, shoot dry weight and leaf/stem ratio of rice. The F6 mapping population also had comparable mean values to the Azucena and Bala. By contrast, Azucena and Bala had different mean values for all traits under Striga treatment. In the Striga treatment, Azucena had significantly higher mean values for rice plant height, leaf dry weight, stem dry weight, shoot dry weight and time of first Striga emergence than Bala, while Bala had significantly higher mean values for leaf/stem ratio, Striga dry weight and Striga number per pot. This shows that Bala is more susceptible to Striga than Azucena, in terms of both Striga growth and effects on the host plants. The F6 mapping population mean values in this treatment were between the parents. Mean values for the F6 in the Striga-infected treatment were lower than the control for rice plant height, leaf dry weight, stem dry weight and shoot dry weight, and higher for leaf/stem ratio, indicating the effectiveness of the Striga treatment in affecting the plants. Broad-sense heritabilities of traits for Striga-infected treatment were much higher than control (61–70% compared with 37–45%; Table 2), except for leaf/stem ratio where the values were comparable (61% for Striga-infected treatment compared with 62% for control). This shows that traits for Striga tolerance are highly heritable except for Striga dry weight and Striga number per pot, where the heritabilities were rather low (28% for Striga dry weight and 38% for Striga number per pot; it is our experience that the growth of the Striga is always very variable in these experiments). The heritability of the time of first Striga emergence could not be calculated because of the lack of replication. Table 2. Mean values (± SD) and percentage of broad-sense heritability (H2) for traits at harvest of rice cultivars Azucena, Bala and mapping population (F6) Trait Striga-infected treatment Control treatment Mean and range for Striga/control treatment value of F6 Azucena (n = 25) Bala (n = 24) F6 (n = 115) H 2 Azucena (n = 15) Bala (n = 15) F6 (n = 114) H 2 H (cm) 33.7 ± 5.5a 25.1 ± 5.9b 28.0 ± 6.8 67 34.1 ± 4.8a 33.6 ± 5.2a 36.6 ± 7.0 45 0.76; 0.42–1.24 LDW (g) 2.60 ± 1.20a 1.06 ± 0.72b 1.39 ± 0.80 70 2.07 ± 0.99a 1.93 ± 1.06a 2.08 ± 0.87 37 0.67; 0.08–1.63 SDW (g) 2.04 ± 1.30a 0.75 ± 0.79b 1.06 ± 0.83 68 1.35 ± 0.76a 1.62 ± 0.87a 1.75 ± 0.92 41 0.60; 0.04–2.45 SHDW (g) 4.63 ± 2.48a 1.81 ± 1.49b 2.50 ± 1.63 70 3.42 ± 1.72a 3.55 ± 1.93a 3.91 ± 1.80 38 0.64; 0.06–2.43 L/S 1.46 ± 0.44b 2.08 ± 0.85a 1.99 ± 0.60 61 1.63 ± 0.33a 1.21 ± 0.22b 1.33 ± 0.28 62 1.50; 0.62–3.48 STDW (mg) 7.4 ± 29.8b 58.8 ± 114.9a 32.4 ± 40.4 28 na na na na na SN 0.1 ± 0.4b 1.0 ± 1.4a 0.8 ± 0.8 38 na na na na na TFE (das) 63 28 56 ± 2 na na na na na na H, rice plant height at week 9; LDW, leaf dry weight; SDW, stem dry weight; SHDW, shoot dry weight; L/S, leaf/stem ratio; STDW, Striga dry weight; SN, Striga number per pot at week 11; TFE, time of first Striga emergence (d after sowing); H2, broad-sense heritability. Numbers followed by the same letter are not significantly different for each trait between Azucena and Bala pairs within treatment at P = 0.05 by Tukey's test. na, not applicable. Correlation between traits Phenotypic correlations among Striga number per pot, Striga dry weight, time of first Striga emergence, shoot dry weight and leaf/stem ratio of both the Striga-infected and control treatments were calculated for the F6 population. Striga number per pot was highly correlated with Striga dry weight (R = 0.757; P < 0.001). Time of first Striga emergence was moderately correlated with Striga number per pot and Striga dry weight (R = −0.432 and −0.410, respectively; P < 0.001 for both correlations). The later the first Striga emerged, the fewer Striga were present in a pot and the lower was the Striga dry weight. Concerning the effects on rice plants, shoot dry weight and leaf/stem ratio of Striga-infected treatment were moderately correlated with Striga number per pot, Striga dry weight and time of first Striga emergence (R values in the range 0.281–0.536; P < 0.001). The higher the Striga number per pot and Striga dry weight or the earlier the first Striga emerged, the lower the shoot dry weight and the higher the leaf/stem ratio found in the rice plants. The correlations of Striga traits to the shoot dry weight and leaf/stem ratio of rice for the control treatment were not statistically significant, except for control shoot dry weight with both Striga number per pot and Striga dry weight (R = 0.232 and 0.224, respectively; P < 0.05 for both correlations). Note, however, this weak positive correlation contrasts with the negative correlation when comparing the shoot dry weight of Striga-treated plants. Plants that tended to have higher shoot dry weight in the control treatment seemed to have more Striga per pot and lower shoot dry weight in the Striga-infected treatment. It is probable that the stronger rice plants (thus higher control shoot dry weight and lower leaf/stem ratio) will support a greater number of Striga. Best subsets regression of Striga number and time of first Striga emergence on shoot dry weight and leaf/stem ratio of Striga-infected treatment showed that Striga number per pot and time of first Striga emergence together better explained the effect on rice shoot dry weight and leaf/stem ratio than each factor alone (R2(adj.) = 24.5 and 25.2 for regressions on shoot dry weight and leaf/stem ratio, respectively; Table 3). In both cases, however, the time of first Striga emergence appeared to be more important than the number of Striga. Table 3. Best subsets regressions of Striga number per pot and time of first Striga emergence on shoot dry weight and leaf/stem ratio of Striga-infected treatment Trait Striga factor R 2(adj.) Shoot dry weight SN 8.6 TFE 24.3 SN and TFE 24.5 Leaf/stem ratio SN 15.3 TFE 20.9 SN and TFE 25.2 SN, Striga number per pot; TFE, time of first Striga emergence. QTL mapping Quantitative trait loci mapping was conducted on the relative values for each trait, that is for each F6 RIL, the mean value of the Striga-treated replicates over the mean value of the control replicates (S/C). Table 2 shows the range and overall mean of these values and indicates very substantial variation in the effect of Striga on different RILs. A summary of statistics for all significant QTL with LOD ≥ 3.2 is given in Table 4. These QTL, along with putative QTL, are also presented in Fig. 3. QTL for rice plant height of S/C treatment QTL for rice plant height at 9 wk after sowing with positive effects from Azucena included a strong QTL (LOD = 7.8, R2 = 20.8%) on chromosome 1 at 143 cM, near marker C1370. Other QTL with LOD scores between 4.8 and 5.8 were on chromosomes 2, 6 and 11. A putative QTL (LOD = 3.0) was found on chromosome 9. Two putative QTL with positive effects from Bala were detected on chromosomes 2 and 5 (LOD = 3.0 and 2.7, respectively). QTL for leaf dry weight of S/C treatment Two QTL with positive effects from Azucena were detected. These included a very strong QTL (LOD = 10.4, R2 = 30.4%) on chromosome 1 at 150 cM near marker C1370 and a putative QTL (LOD = 2.6) on chromosome 9. QTL for stem dry weight of S/C treatment Only one strong QTL (LOD = 7.0, R2 = 22.8%) for stem dry weight was detected on chromosome 1 at 150 cM near marker C1370. This QTL had positive effects from Azucena. QTL for shoot dry weight of S/C treatment QTL with positive effects from Azucena included a very strong QTL (LOD = 15.7, R2 = 26.1%) on chromosome 1 at 148 cM on marker C1370, a strong QTL (LOD = 8.0, R2 = 22.2%) on chromosome 2 at 72 cM on marker RG171, three moderate QTL (LOD in the range 4.2–6.3) on chromosomes 8, 9 and 11, and two putative QTL (LOD = 2.5 and 3.0) on chromosomes 6 and 8, respectively. QTL with positive effects from Bala included a strong QTL (LOD = 8.8, R2 = 15.3%) on chromosome 4 at 83 cM near marker RG163 and four putative QTL (LOD in the range 2.9–3.0) on chromosomes 1 (two QTL), 6 and 9. QTL for leaf/stem ratio of S/C treatment Two QTL with positive effects from Bala were detected for this trait. These included a rather strong QTL (LOD = 6.8, R2 = 22.0%) on chromosome