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Quantitative Analysis of Fitness Costs Associated with the Development of
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Resistance to the Bt Toxin Cry1Ac in Helicoverpa armigera
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Guangchun Cao1☺, Hongqiang Feng2☺, Fang Guo1, Kongming Wu1*, Xianchun Li3,
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Gemei Liang1, Nicolas Desneux4
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1. State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant
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Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
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2. Institute of Plant Protection, Henan Academy of Agricultural Sciences, Zhengzhou,
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450002, China.
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3. Department of Entomology, University of Arizona, 85721 Tucson, AZ, USA.
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4. French National Institute for Agricultural Research (INRA), UMR1355-ISA, 06903
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Sophia-Antipolis, France.
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* Corresponding author. Fax: +86 1062815929. E-mail address: [email protected]
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☺ These authors contributed equally to this work.
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Supplementary text
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Methods
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Screen of 11 H. armigera strains
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Life talbes of the 11 strains on non-Bt diet
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Bayesian statistics of survival rate
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Analysis of the relationship between overall fitness cost and resistance level
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Multiple regressions
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Supplementary References
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Supplementary information
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Table S1. The resistance to Cry1Ac toxin and the intrinsic rate of population increase rm
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in eleven H. armigera strains.
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Table S2. Statistical mean and 95% Credible Interval for proportional data of fitness
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components (data used to produce Fig. 3).
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Table S3. Matrix of the posterior probability that {rc > rr}, where rc is the survival rate
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from neonates to the 6th instar larvae for strains listed in the first row, and rr is that for
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strains listed in the first column.
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Table S4. Matrix of the posterior probability that {rc > rr}, where rc is the survival from
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6th instar to pupa for strains listed in the first row, and rr is that for strains listed in the
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first column.
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Table S5. Matrix of the posterior probability that {rc > rr}, where rc is the emergence rate
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for strains listed in the first row, and rr is that for strains listed in the first column.
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Table S6. Matrix of the posterior probability that {rc > rr}, where rc is the copulation rate
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for strains listed in the first row, and rr is that for strains listed in the first column.
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Table S7. Matrix of the posterior probability that {rc > rr}, where rc is the hatching rate
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for strains listed in the first row, and rr is that for strains listed in the first column.
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Table S8. Matrix of the posterior probability that {rc > rr}, where rc is the proportion of
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female adults for strains listed in the first row, and rr is that for strains listed in the first
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column.
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Table S9 Fitness components of XX, LF and XJ strain series.
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Fig. S1. Pairplot (pairwise scatterplot with correlation coefficients) of all variables. The
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upper panel contains estimated pair-wise correlations, and the font size is proportional to
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the absolute value of the estimated correlation coefficient. The diagonal panel contains
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histograms and the lower panel scatterplots with a LOESS smoother added to aid visual
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interpretation. The thirteen influential variables were fitness cost in survival rate from the
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1st to 6th instar larvae R16, from the 6th instar larvae to pupae CR6p, pupal weight CWp,
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emergence rate to healthy moths CRe, sex ratio of male to female CRsex, copulation rate
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CRc, fecundity CFec, hatching rate CRh, larval duration CDl, developmental duration of
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female pupa CDpf, developmental duration of male pupa CDpm, developmental duration of
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female adults CDaf and developmental duration of male adults Dam.
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Fig. S2. Pairplot of all variables after combination of influential variables. The upper
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panel contains estimated pair-wise correlations, and the font size is proportional to the
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absolute value of the estimated correlation coefficient. The diagonal panel contains
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histograms and the lower panel scatterplots with a LOESS smoother added to aid visual
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interpretation. The ten influential variables were fitness cost in larval survival rate CRl,
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pupal weight CWp, emergence rate to healthy moths CRe, sex ratio of male to female CRsex,
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copulation rate CRc, fecundity CFec, hatching rate CRh, larval duration CDl, pupal duration
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CDp, and adult duration CDa.
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Fig. S3. The scatter plots of fitted overall fitness cost against observed data with line of y
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= x as a reference.
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Fig. S4. The scatter plots of fitted log resistance ratio with a multiple linear model against
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observed data with line of y = x as a reference.
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Supplementary text
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Methods
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Screen of 11 H. armigera strains
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The 96S was a strain susceptible to Bt originally collected from cotton fields in 1996
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at Xinxiang (Henan province, China) and has been reared under laboratory conditions on
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an artificial diet with no contact to any Bt toxinS1. BtR was a Bt-resistant strain selected
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from the 96S strain for 105 generations using Cry1Ac-contaminated artificial dietsS2
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(Cry1Ac toxin was provided by the Biotechnology Group, Chinese Academy of
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Agricultural Sciences). In this strain, the dose of Cry1Ac toxin imposed on each
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generation of H. armigera larvae increased gradually from 0.008 to 161 mg/L basing on
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the criteria that 70% of the neonates could successfully survive to adult stages and
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reproduce next genrationS3.
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LF was a series of Bt resistant strains which originated from a H. armigera
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population that was collected in 1998 at the Langfang experimental station (Hebei
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province, China). The field-collected population had been reared on a sequence of
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Bt-contaminated artificial diet containing up to 3.0 mg Cry1Ac / L for 38 generations
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under laboratory conditionsS4. From the 39th generation onward, it was subjected to
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selection through rearing on artificial diets containing Cry1Ac toxin at a dose of 5 mg
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Cry1Ac / LS3. When 80% pupation success was observed in 3 successive generations, the
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population was designated as the resistant strain LF5 (reached at 45th generation). At the
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46th generation, half of the LF5 larvae were reared continuously on the same dose of
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Cry1Ac-contaminated diet (i.e., 5 mg Cry1Ac / L) and the others was subjected to a
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higher Cry1Ac dose of 10 mg / L, to select a more resistant strain LF10 (reached at 56th
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generation). Similarly, the LF20, LF30 and LF60 strains were established using
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Cry1Ac-contaminated diets at concentrations of 20, 30 and 60 mg Cry1Ac/ L from the
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57th, 60th and 77th generations, respectively (Fig. 1).
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XJ was a series of strains originating from a H. armigera population collected in a
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cotton field at Xiajin (Shandong province, China) during the Cry1Ac resistance
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monitoring program carried out in 2004S5. The XJF strain was originated from the non-Bt
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fed progeny (the control treatment in resistance gene frequency monitoring) of the family
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that showed the highest resistance to Cry1Ac in our previous studyS5 and has been reared
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for 50 generations on non-Bt artificial diet in the lab since 2004. Using the same method
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as for LF series, the resistant strains XJ1, XJ5, and XJ10 were selected from the XJF
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strain using Cry1Ac-contaminated diet at concentrations of 1, 5, and 10 mg / L from the
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6th, 17th, and 20th generations, respectively (Fig. 1).
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During selection of resistance, the neonates were reared on the above described dose of
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toxin artificial diet for 7 days and then well-developed larvae were transferred to non-Bt
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artificial diet until moth emergence. The last generation of each strains were used in the
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present study (Fig. 1).
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Life talbes of the 11 strains on non-Bt diet
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Life tables were established for each H. armigera strains with rearing neonates on
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non-Bt diet. Two hundred forty H. armigera neonates of each strain were reared on a
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non-Bt artificial diet as described by Liang et al.S2. Each neonate was placed individually
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with 1.25±0.25g of artificial diet in plastic wells (depth: 1.5cm, vol. 3ml) using 24-well
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plates (they were covered with a plastic lid). On the 7th day, we counted and recorded
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larvae that had survived until the 3rd instar. The survivors were placed individually into
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clear glass tubes with non-Bt artificial diet until they pupated. The developmental
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duration and the survival from the 3rd to 6th instar and from 6th instar to pupa were
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recorded. Within 24-48h of pupation, pupae were weighed and sexed. The emergence of
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adults was recorded and 15 adult pairs from each strain were monitored daily for survival
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and oviposition until the death of female adults. The eggs were collected on the gauze
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that was covered in the plastic cup during mating, and the hatching rate of eggs was
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calculated as the number of newly hatched larvae divided by the number of eggs.
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Bayesian statistics of survival rate
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Basing Bayesian methodS6, the expectation of survival rate E[θ|y] = (a + y)/(a + b
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+ n), where y is the number of survivors, n is the total number of tested individuals, a and
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b are the parameters of prior distribution of beta(a = 1, b = 1). The 95% credible interval
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of survival rate was obtained from the 0.025 and 0.975 quantiles of posterior distribution
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beta(a + y, b + n - y), that was calculated with R function qbeta(c(0.025, 0.975), a + y, b
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+ n - y). While comparing two survival rates, a sequence of 10000000 Monte Carlo
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samples from the beta(a + y, b + n - y) distribution was produced with R function rbeta(a
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+ y, b + n - y) for each survival rates, i.e., theta1 and theta2. The probalility of survival
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rate theta1 > survival rate theta2 was calculated with R function mean(theta1 > theta2).
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Analysis of the relationship between overall fitness cost and resistance level
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When analyzed for each series, the overall fitness cost, C, showed a positive linear
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trend with log10 transformed resistance ratio Log10Rr for the LF and XJ series; however,
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neither one was significant (C = -15.42 + 15.62 Log10Rr [p = 0.153] for the LF series; C =
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-51.02 + 41.38 Log10Rr [p = 0.164] for the XJ series). Because there were only two data
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points for XX series, no regression can be performed for this series. When the data from
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the three series were pooled together, the fitted linear model C = 0.09 + 8.71 Log10Rr was
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not significantly different from the linear model for the LF (F = 1.60, p = 0.375) or for
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the XJ (F = 1.04, p = 0.572) series, but it was statistically significant (p = 0.023) (Fig. 2).
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This indicated that there was no significant difference in linear tendency between series
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and it is better to analyze pooled data than to analyze data for each series separately.
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When visually interpreted, the overall fitness cost of H. armigera logistically
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increased with the resistance level to Cry1Ac for the pooled data of the three series
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(pairwise scatter plot with a LOESS [local regression] smoother, Fig. S1ON). Therefore,
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we first fitted a four-parameter logistic model C = A + (B – A)/(1 + exp((xmid -
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Log10Rr)/scal)) to the pooled data. In the four-parameter logistic model, parameter A was
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not significantly different from zero (A = - 0.26, SE = 8.67, t = -0.03, p = 0.977); thus,
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again, a three-parameter logistic model C = Asym/(1 + exp((xmid - Log10Rr)/scal)) was
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fitted to the pooled data. In the three-parameter logistic model, Asym = 24.47 (SE = 5.22,
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t = 4.69, p = 0.00157), xmid = 1.57 (SE = 0.18, t = 8.64, p = 2.5e-05), and scal = 0.20 (SE
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= 0.16, t = 1.30, p = 0.231). Because the parameter scal was not significant, a
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two-parameter logistic model C = Asym/(1 + exp(xmid - Log10Rr)) was fitted to the pooled
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data again, but the AIC (Akaike’s Information Criterion) value rose.
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Among the linear and nonlinear (logistic) models, the three-parameter logistic model
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had the lowest AIC value and was chosen to describe the relationship between overall
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fitness cost and resistance level.
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Multiple regressions
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Because there were more influential variables (i.e., 13 fitness component costs) than
the number of data points i.e., 11 overall fitness costs or resistance levels, and there was
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no mathematic algorithm to estimate the regression coefficient parameters under such
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situation. Therefore, we need to exclude influential variables. The proportion of females
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(sex ratio) was neither significantly different among each strain (Fig. 3) nor different
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from 50% (with sex ratio of 1:1) for all strains; thus, this factor was confidently excluded
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from the multiple regression analyses. The developmental duration of female and male
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adults was not significantly different among strains and thus datasets were pooled. When
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datasets for both sexes were pooled to produce one single variable, CDa, the cost in
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developmental duration of adults, the correlation between overall fitness cost and
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development duration increased from 0.5 for each sex separately (Fig. S1LO & KO) to
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0.6 for both sexes (Fig. S2IL). Thus, the two variables were combined into one variable
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CDa rather than being discarded. So, three approaches were carried out for multiple
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regressions.
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Approach 1. The thirteen influential variables measured were divided into 6 groups
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based on developmental stages (i.e. stage of larva, pupa, adult, larva to pupa, pupa to
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adult, and adult to larva) to explain the overall fitness cost or resistance ratio, respectively.
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Stepwise regression was performed to choose the best model for each group. The most
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significant variables from each group were then chosen to explain the overall fitness cost
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or resistance ratio. Stepwise regression was performed again to choose the best model.
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Approach 2. The fitness components with highly correlated fitness cost (Pearson
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correlation coefficient  0.6) were combined into one biological parameter (e.g., the
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survival rate for the 1st-6th instars, and the 6th instar to pupae were combined to produce
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one fitness component: larval survival rate). We obtained ten influential variables,
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representing fitness cost for ten fitness components, to explain overall fitness cost, C, and
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resistance ratio, Rr (log10 transformed). The ten influential variables were fitness cost in
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larval survival rate, CRl, pupal weight, CWp, emergence rate to healthy moths, CRe, sex
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ratio of male to female, CRsex, copulation rate, CRc, fecundity, CFec, hatching rate, CRh,
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larval duration, CDl, pupal duration, CDp, and adult duration, CDa.
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The data were first fitted with a full multiple regression model:
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Yi =α + Σ(βij×Xij) + εi
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where Y represents the response variables (i.e. overall fitness cost, C, or log10
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transformed resistance ratio, Rr. X represents influential variables CRl, CWp, CRe, CRsex, CRc,
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CFec, CRh, CDl, CDp and CDa, α, and β are coefficients, and ε the error.
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Approach 3. A polynomial model was fitted. To make a polynomial model, we selected
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influential variables using the following criteria. (1) Those influential variables highly
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correlated with the response variables (Pearson correlation coefficient ≥ 0.6 or significant
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variables in multiple regression models established in approach 2 or approach 3) were
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selected first. (2) If the higher order variables representing multiple instances of the
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above first order variables, such as quadratic, cubic, and bi-quadratic variables, were
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highly correlated with the response variables (the Pearson correlation coefficient was ≥
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0.6), they were selected as influential variables too.
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For multiple linear regressions, collinearity of influential variables was diagnosed
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using three tools: Pairwise scatterplots, correlation coefficients, and variance inflation
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factors (VIF). Pair-wise correlations between each fitness component cost were
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investigated with a correlation matrix produced by function pairs in library AEDS7 of RS8.
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When variables showed VIF value > 10 (which indicated serious collinearityS9), the
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variables with the highest VIF value were removed until the collinearity was eliminated.
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The CRh and CDp had clearly high correlation as indicated by the correlation coefficient of
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0.9 (Fig. S2AE). The VIF (variance inflation factors) of these two factors were similar
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but both higher than that of others. Because the CRh and CDp had a similar VIF and were
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both thought to be important influential factors to overall fitness cost (correlation
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coefficient = 0.6 for both, Fig. S2AL & EL), thus, they were discarded in turn to
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eliminate collinearity of each.
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The model was then subjected to a stepwise backward selection process using AIC
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as a selection criterion. In each approach, the residuals were computed to diagnose the
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assumptions of normality and homogeneity of variance in residuals. The AIC was used to
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select the best model through the three approaches.
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References
244
S1. Liang, G.M., Tan, W.J. & Guo, Y.Y. An improvement in the technique of artificial
245
246
rearing cotton bollworm. Plant Protec. 25, 15-17 (1999).
S2. Liu, N.N., Zhu, F., Xu, Q., Pridgeon, J.W. & Gao, X.W. Behavioral change,
247
physiological modification, and metabolic detoxification: mechanisms of insecticide
248
resistance. Acta. Entom. Sin. 49, 671-679 (2006).
249
S3. Liang, G.M., Tan, W.J. & Guo, Y.Y. Studies on the resistance screening and
250
cross-resistance of cotton bollworm to Bacillus thuringiensis (Berliner). Sci. Agric.
251
Sci. 33, 46-53 (2000).
252
S4. Wu, K.M. & Guo, Y.Y. Changes in susceptibility to conventional insecticides of a
253
Cry1Ac-selected population of Helicoverpa armigera (Hubner) (Lepidoptera:
254
Noctuidae). Pest Manag. Sci. 60, 680-684 (2004).
10
255
S5. Li, G.P. et al. Increasing tolerance to Cry1Ac cotton from cotton bollworm,
256
Helicoverpa armigera, was confirmed in Bt cotton farming area of China. Ecol.
257
Entomol. 32, 366–375 (2007).
258
259
260
261
262
263
264
265
S6. Hoff, P.D. A First Course in Bayesian Statistical Methods. (Springer, New York
2009).
S7. Zuur, A.F., Ieno, E.N., Walker, N.J., Saveliev, A.A., Smith, G.M. Mixed effects
models and extensions in ecology with R. (Springer, New York. 2009)
S8. R Development Core Team. R: A language and environment for statistical computing.
(2013) Date of access: 19/05/2013. URL http://www.R-project.org/.
S9. Logan, M. Biostatistical Design and Analysis Using R: A Practical Guide.
(Wiley-Blackwell, Oxford, UK. 2010)
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267
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Table S1. The resistance to Cry1Ac toxin and the intrinsic rate of population increase rm in eleven
H. armigera strains.
Strain
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LC50 (µg/ml)*
Resistance ratio
(95%confidence limits)
(RR)
rm
LDP line
96S
y=6.1434+2.3611x
0.33(0.27--0.40)a
1
0.058
XJF
y=3.9850+1.1855x
7.18(5.36--9.63)b
21.76
0.057
LF5
y=3.003+2.3626x
7(5.99--8.18)b
21.21
0.053
XJ1
y=3.3521+1.3554x
16.44(12.14—22.25)c
49.82
0.041
LF10
y=3.6073+1.0922x
18.84(11.19--31.74)c
57.09
0.057
LF20
y=1.9773+2.3513x
19.30(16.22--22.96)c
58.48
0.048
XJ5
y=1.7645+2.4729x
20.34(17.29--23.92)c
61.64
0.048
XJ10
y=2.6502+1.6122x
28.73(21.68--38.08)d
95.77
0.042
LF30
y=2.4732+1.3728x
69.29(53.76--89.31)e
209.97
0.047
LF60
y=0.9170+2.1266x
83.16(71.74--96.40)f
277.20
0.043
BtR
y=-0.0245+1.6606x
1060.95(798.62--1409.45)h
3536.50
0.043
* LC50 values followed by same letters within this column are not significantly different.
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Table S2. Statistical mean and 95% Credible Interval for proportional data of fitness components (data used to produce Fig. 3).
Strain
Survival rate (1 - 6th
instar larvae)
n
Mean CI1 CI2
Survival from 6th
instar larvae to pupa
n
Mean CI1 CI2
96S
240
0.91
0.87
0.94
219
0.93
0.89
BtR
240
0.83
0.79
0.88
201
0.85
LF5
240
0.91
0.87
0.94
219
LF10
240
0.93
0.89
0.96
LF20
240
0.92
0.88
LF30
240
0.90
LF60
240
XJF
emergence rate
copulation rate
n
Mean
CI1
CI2
0.96
204
0.94
0.91
0.79
0.89
171
0.79
0.92
0.88
0.95
202
224
0.97
0.94
0.99
0.95
221
0.98
0.95
0.86
0.93
216
0.94
0.88
0.84
0.92
212
240
0.91
0.87
0.94
XJ1
240
0.83
0.78
XJ5
240
0.83
XJ10
240
0.89
n
hatching rate
proportion of female
adults
n
Mean CI1 CI2
Mean
CI1
CI2
n
Mean
CI1
CI2
0.97 15
0.94
0.79
1.00
5510
0.69
0.68
0.70 164
0.52
0.45
0.60
0.73
0.85 15
0.65
0.41
0.85
2553
0.62
0.60
0.63 134
0.55
0.47
0.63
0.93
0.89
0.96 15
0.71
0.48
0.89
2510
0.67
0.66
0.69 153
0.55
0.48
0.63
218
0.83
0.77
0.87 15
0.65
0.41
0.85
4431
0.65
0.63
0.66 172
0.53
0.46
0.61
0.99
217
0.86
0.81
0.91 15
0.71
0.48
0.89
2965
0.63
0.62
0.65 150
0.51
0.43
0.59
0.91
0.97
205
0.92
0.88
0.95 15
0.76
0.54
0.93
3081
0.60
0.58
0.61 173
0.56
0.49
0.63
0.99
0.97
1.00
211
0.88
0.83
0.92 15
0.71
0.48
0.89
1946
0.52
0.50
0.54 164
0.55
0.48
0.63
219
0.90
0.86
0.94
199
1.00
0.98
1.00 15
0.88
0.70
0.98
5605
0.70
0.69
0.71 158
0.54
0.47
0.62
0.88
200
0.91
0.86
0.94
182
0.78
0.71
0.83 15
0.53
0.30
0.75
2058
0.61
0.59
0.63 116
0.54
0.45
0.63
0.79
0.88
201
0.91
0.86
0.94
183
0.83
0.78
0.88 15
0.53
0.30
0.75
3735
0.55
0.54
0.57 140
0.52
0.44
0.60
0.85
0.92
214
0.88
0.83
0.92
189
0.87
0.82
0.91 15
0.65
0.41
0.85
2470
0.52
0.50
0.54 148
0.53
0.45
0.61
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Table S3. Matrix of the posterior probability that {rc > rr}, where rc is the survival rate
from neonates to the 6th instar larvae for strains listed in the first row, and rr is that for
strains listed in the first column.
LF10
LF20
96S
LF5
XJF
LF30
XJ10
LF60
XJ5
BtR
XJ1
LF10
NA
0.698
0.801
0.801
0.801
0.905
0.945
0.970
1.000
1.000
1.000
LF20
NA
NA
0.628
0.628
0.628
0.785
0.861
0.915
0.997
0.997
0.998
96S
NA
NA
NA
0.500
0.500
0.679
0.776
0.852
0.993
0.993
0.995
LF5
NA
NA
NA
NA
0.500
0.679
0.777
0.852
0.993
0.993
0.995
XJF
NA
NA
NA
NA
NA
0.679
0.776
0.852
0.993
0.993
0.995
LF30
NA
NA
NA
NA
NA
NA
0.616
0.720
0.978
0.978
0.984
XJ10
NA
NA
NA
NA
NA
NA
NA
0.613
0.958
0.958
0.968
LF60
NA
NA
NA
NA
NA
NA
NA
NA
0.925
0.925
0.941
XJ5
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.500
0.549
BtR
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.549
XJ1
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
14
Table S4. Matrix of the posterior probability that {rc > rr}, where rc is the survival from
6th instar to pupa for strains listed in the first row, and rr is that for strains listed in the
first column.
LF60
LF20
LF10
LF30
96S
LF5
XJ5
XJ1
XJF
XJ10
BtR
LF60
NA
0.883
0.960
0.998
1.000
1.000
1.000
1.000
1.000
1.000
1.000
LF20
NA
NA
0.721
0.968
0.995
0.998
1.000
1.000
1.000
1.000
1.000
LF10
NA
NA
NA
0.900
0.979
0.992
0.997
0.997
0.998
1.000
1.000
LF30
NA
NA
NA
NA
0.776
0.868
0.938
0.939
0.947
0.993
1.000
96S
NA
NA
NA
NA
NA
0.641
0.787
0.792
0.808
0.957
0.996
LF5
NA
NA
NA
NA
NA
NA
0.671
0.677
0.694
0.914
0.990
XJ5
NA
NA
NA
NA
NA
NA
NA
0.506
0.522
0.815
0.967
XJ1
NA
NA
NA
NA
NA
NA
NA
NA
0.515
0.810
0.965
XJF
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.806
0.966
XJ10
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.834
BtR
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
15
Table S5. Matrix of the posterior probability that {rc > rr}, where rc is the emergence
rate for strains listed in the first row, and rr is that for strains listed in the first column.
XJF
96S
LF5
LF30
LF60
XJ10
LF20
XJ5
LF10
BtR
XJ1
XJF
NA
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
96S
NA
NA
0.737
0.833
0.990
0.994
0.997
1.000
1.000
1.000
1.000
LF5
NA
NA
NA
0.629
0.955
0.972
0.984
0.998
0.999
1.000
1.000
LF30
NA
NA
NA
NA
0.914
0.945
0.967
0.995
0.998
1.000
1.000
LF60
NA
NA
NA
NA
NA
0.604
0.679
0.902
0.933
0.989
0.996
XJ10
NA
NA
NA
NA
NA
NA
0.574
0.843
0.883
0.976
0.991
LF20
NA
NA
NA
NA
NA
NA
NA
0.803
0.852
0.969
0.988
XJ5
NA
NA
NA
NA
NA
NA
NA
NA
0.557
0.838
0.911
LF10
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.812
0.897
BtR
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.634
XJ1
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
16
Table S6. Matrix of the posterior probability that {rc > rr}, where rc is the copulation
rate for strains listed in the first row, and rr is that for strains listed in the first column.
96S
XJF
LF30
LF5
LF20
LF60
LF10
XJ10
BtR
XJ5
XJ1
96S
NA
0.758
0.949
0.978
0.978
0.978
0.991
0.991
0.991
0.999
0.999
XJF
NA
NA
0.834
0.914
0.914
0.914
0.958
0.959
0.958
0.992
0.992
LF30
NA
NA
NA
0.657
0.657
0.657
0.783
0.783
0.784
0.932
0.932
LF5
NA
NA
NA
NA
0.500
0.500
0.648
0.648
0.648
0.863
0.863
LF20
NA
NA
NA
NA
NA
0.500
0.648
0.648
0.648
0.863
0.863
LF60
NA
NA
NA
NA
NA
NA
0.648
0.648
0.648
0.863
0.863
LF10
NA
NA
NA
NA
NA
NA
NA
0.500
0.500
0.764
0.764
XJ10
NA
NA
NA
NA
NA
NA
NA
NA
0.500
0.764
0.764
BtR
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.764
0.764
XJ5
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.500
XJ1
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
17
Table S7. Matrix of the posterior probability that {rc > rr}, where rc is the hatching rate
for strains listed in the first row, and rr is that for strains listed in the first column.
XJF
96S
LF5
LF10
LF20
BtR
XJ1
LF30
XJ5
LF60
XJ10
XJF
NA
0.758
0.983
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
96S
NA
NA
0.941
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
LF5
NA
NA
NA
0.988
0.999
1.000
1.000
1.000
1.000
1.000
1.000
LF10
NA
NA
NA
NA
0.887
0.997
0.999
1.000
1.000
1.000
1.000
LF20
NA
NA
NA
NA
NA
0.928
0.962
0.999
1.000
1.000
1.000
BtR
NA
NA
NA
NA
NA
NA
0.650
0.938
1.000
1.000
1.000
XJ1
NA
NA
NA
NA
NA
NA
NA
0.851
1.000
1.000
1.000
LF30
NA
NA
NA
NA
NA
NA
NA
NA
1.000
1.000
1.000
XJ5
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.985
0.993
LF60
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.538
XJ10
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
18
Table S8. Matrix of the posterior probability that {rc > rr}, where rc is the proportion of
female adults for strains listed in the first row, and rr is that for strains listed in the first
column.
LF30
LF5
LF60
BtR
XJF
XJ1
LF10
XJ10
96S
XJ5
LF20
LF30
NA
0.537
0.543
0.560
0.618
0.617
0.685
0.685
0.748
0.755
0.802
LF5
NA
NA
0.504
0.523
0.579
0.581
0.645
0.647
0.710
0.720
0.769
LF60
NA
NA
NA
0.519
0.576
0.578
0.643
0.646
0.710
0.720
0.769
BtR
NA
NA
NA
NA
0.553
0.558
0.618
0.621
0.683
0.694
0.743
XJF
NA
NA
NA
NA
NA
0.509
0.568
0.573
0.639
0.653
0.706
XJ1
NA
NA
NA
NA
NA
NA
0.554
0.559
0.620
0.634
0.684
LF10
NA
NA
NA
NA
NA
NA
NA
0.508
0.576
0.593
0.650
XJ10
NA
NA
NA
NA
NA
NA
NA
NA
0.566
0.583
0.638
96S
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.521
0.578
XJ5
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.555
LF20
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
19
Table S9 Fitness components of XX, LF and XJ strain series.
Series
Strain
96S
XX
BtR
Statistics within
the XX series
F1
P
LF5
LF10
LF
LF20
LF30
LF60
Statistics within
the LF series
F4
P
XJF
XJ1
XJ
XJ5
XJ10
Larva
15.7±0.2
Bc
17.1±0.3
Aa
17.34
0.0031
14.8±0.1
Dc
15.4±0.1
Cc
16.8±0.1
A ab
16.3±0.2
Bb
15.6±0.1
Cc
47.50
<0.0001
16.3±0.4
Ab
16.4±0.4
Ab
16.6±0.1
A ab
16.9±0.4
A ab
1.03
0.3879
13.34
<0.0001
Developmental duration (days)
Pupa
Adult
♀
♂
♀
♂
11.9±0.1
Ce
13.1±0.1
Ac
105.48
<0.0001
11.2±0.1
Bf
10.7±0.1
Ch
11.4±0.1
Bf
11.1±0.2
B fg
14.4±0.1
Ab
205.58
<0.0001
10.9±0.1
C gh
11.9±0.2
Be
11.9±0.1
Be
15.4±0.1
Aa
1132.16
<0.0001
301.92
<0.0001
12.6±0.2
Bd
13.74±0.1
Ac
40.59
0.0002
12.3±0.1
B ed
11.8±0.1
Cf
12.4±0.1
B ed
12.2±0.1
B ed
16.5±0.1
Ab
345.04
<0.0001
11.7±0.1
Cf
12.2±0.4
Be
12.2±0.1
Be
17.0±0.1
Aa
1177.75
<0.0001
333.35
<0.0001
6.7±2.3
A ab
7.1±1.7
A ab
0.07
0.7879
5.8±1.6
Bb
6.6±1.8
AB ab
6.8±2.6
AB ab
7.6±1.8
Aa
7±1.7
AB ab
1.57
0.1912
5.7±1.4
Bb
6.9±1.4
A ab
7.0±1.7
A ab
6.9±1.8
A ab
3.03
0.059
1.33
0.2249
5.7±2.0
A ab
6.1±1.8
A ab
0.24
0.6292
5.6±1.6
A ab
6.2±1.8
A ab
6.0±1.6
A ab
6.2±1.8
A ab
6.9±1.4
Aa
1.18
0.3261
5.2±1.2
Ab
6.2±1.3
A ab
6.7±1.2
A ab
6.0±1.8
A ab
2.28
0.1152
1.14
0.3356
Pupal weight
(mg/pest)
Effective fecundity
(eggs/female)
256.9±2.0
Af
256.0±5.6
Af
0.02
0.88
229.0±3.0
D bc
271.7±2.6
C de
287.8±2.3
Bb
276.8±2.9
C cd
315.3±2.7
Aa
134.28
<0.0001
265.4±3.1
B ef
267.5±3.8
B ef
285.7±2.5
A bc
295.1±5.5
Ab
14.83
0.0006
49.11
<0.0001
785.1±246.3
A bc
452.32±91.43
Bf
15.75
0.0011
502.0±94.8
Bf
958.9±277.5
A ab
573.5±122.6
B ef
471.9±178.5
Bf
583.3±70.2
B def
9.90
<0.0001
822.1±219.8
B bc
566.1±128.4
B ef
1049.4±265.6
Aa
773.6±192.0
B bcd
3.4
0.0533
9.65
<0.0001
Statistics within
F3
the XJ series
P
Statistics with all
F10
strains
P
Means (±SE) followed by different uppercase letters are significantly different within each groups. Means (±SE) followed by different lowercase letters
within columns are significantly different among the 11 strains (ANOVA followed by Tukey’s HSD posthoc test, P < 0.05 level).
Fig. S1.
Fig. S2.
25
20
15
10
0
5
Fitted fitness cost (%)
0
5
10
15
20
Observed fitness cost (%)
Fig. S3.
25
30
3.5
3.0
2.5
2.0
1.5
Pedicted log10 resistance ratio
1.0
0.5
0.0
0.5
1.0
1.5
2.0
2.5
Observed log10 resistance ratio
Fig. S4.
3.0
3.5