[1] "###############################################################################################" [1] "DMN_VegArea_d38" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.06 chr pos lod 1:70506336 1 204.8 1.333 7:8093862 2 206.2 1.945 3:23389564 3 147.0 1.239 13:13646557 4 141.2 1.907 14:22054723 5 303.4 1.020 6:38553759 6 63.7 0.391 7:20993029 7 34.3 1.202 8:47095870 8 175.5 2.871 1:47290936 9 119.3 1.807 10:21730628 10 146.9 2.030 11:37915596 11 142.8 2.573 4:1025016 12 47.4 1.527 0:10902661 13 138.9 1.722 14:10056720 14 76.6 1.644 8:17454589 15 224.4 3.470 9:2078323 16 228.6 2.481 [1] 4.063947 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "DMN_VegArea_d120" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.84 chr pos lod 7:45584108 1 86.27 1.746 7:8093862 2 206.20 3.191 4:8512571 3 34.84 2.221 13:13646557 4 141.20 5.634 5:22029888 5 331.48 1.528 15:13186532 6 38.57 1.400 7:52684392 7 103.06 0.810 8:47095870 8 175.47 1.084 9:61647771 9 316.70 0.881 2:49915311 10 73.57 2.515 11:37915596 11 142.83 1.381 12:27710929 12 366.16 1.999 13:2132329 13 51.94 2.518 3:26735632 14 5.26 1.757 10:18587313 15 256.94 4.566 4:58955253 16 228.15 5.328 [1] 3.842613 chr pos lod 13:13646557 4 141 5.63 10:18587313 15 257 4.57 4:58955253 16 228 5.33 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 725195 120865.83 14.07962 12.11679 4.653056e-12 6.312284e-12 Error 495 5259847 10625.95 Total 501 5985042 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 4@141.2 2 236066 4.786 3.944 11.108 0 1.91e-05 *** 15@249.5 2 213042 4.328 3.560 10.025 0 5.40e-05 *** 16@223.3 2 189725 3.863 3.170 8.927 0 0.000155 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 742.749 4.696 158.178 4@141.2a -34.750 7.373 -4.713 4@141.2d -3.428 10.442 -0.328 15@249.5a 30.075 6.916 4.348 15@249.5d -7.608 10.698 -0.711 16@223.3a 25.043 7.101 3.527 16@223.3d -21.268 10.223 -2.080 chr pos lod 12:44145163 4 136.5963 3.438595 13:13646557 4 141.2027 4.785761 4:69450355 4 142.8181 3.226194 chr pos lod 15:29528215 15 211.5335 3.224704 15:33145691 15 249.4854 4.328118 7:44106212 15 318.9988 2.983349 chr pos lod 9:39881977 16 200.4978 2.180352 16:35058866 16 223.2935 3.862701 6:13101118 16 232.6276 2.427582 [1] "###############################################################################################" [1] "DMN_VegArea_d339" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.09 chr pos lod 5:5548115 1 157.72 0.963 1:39109401 2 116.66 2.567 9:12785116 3 63.76 0.996 12:38343043 4 185.91 2.964 11:59480799 5 328.74 1.208 14:31827854 6 103.11 0.838 7:37937424 7 75.67 0.620 8:61377122 8 317.29 3.578 1:26159385 9 61.45 0.956 9:23631957 10 178.70 6.804 1:20990542 11 162.98 1.631 4:5937117 12 117.03 3.746 12:50035595 13 88.46 2.206 3:26735632 14 5.26 5.857 10:17987993 15 256.69 3.221 16:42089416 16 341.52 1.420 [1] 4.093486 chr pos lod 9:23631957 10 178.70 6.80 3:26735632 14 5.26 5.86 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 757157.7 189289.43 11.66636 10.14951 6.00705e-11 7.387424e-11 Error 497 6702886.6 13486.69 Total 501 7460044.4 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@178.7 2 366920 5.810 4.918 13.60 0 1.77e-06 *** 14@5.3 2 305747 4.862 4.098 11.34 0 1.54e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 388.355 5.203 74.646 10@178.7a 43.326 8.312 5.212 10@178.7d 3.503 11.415 0.307 14@5.3a 32.994 7.840 4.209 14@5.3d -23.804 11.538 -2.063 chr pos lod 10:22762714 10 153.5043 4.107660 9:23631957 10 178.7020 5.809557 10:10100994 10 239.5915 4.759583 chr pos lod 3:26748571 14 0.000000 3.372187 3:26735632 14 5.262673 4.862241 7:22290526 14 35.624209 2.764439 [1] "###############################################################################################" [1] "DMN_VegArea_d458" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.03 chr pos lod 1:67377169 1 190.39 1.21 1:39109401 2 116.66 1.57 3:22133857 3 123.49 2.90 12:44145163 4 136.60 1.92 5:12557744 5 204.73 1.45 6:32184811 6 46.72 1.11 7:1539484 7 5.19 2.71 16:44347421 8 361.89 1.72 6:9093640 9 216.20 1.03 2:46091293 10 240.14 1.56 11:40793705 11 151.69 2.77 12:27710929 12 366.16 2.99 16:36206535 13 40.69 2.73 9:6891625 14 302.08 1.66 15:10330648 15 170.70 1.76 1:92139438 16 303.66 2.30 [1] 4.033479 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "DMN_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4 chr pos lod 16:32977471 1 203.5 0.745 1:34656738 2 95.6 1.959 3:11635309 3 67.0 2.938 4:67833454 4 138.1 1.155 5:3341512 5 148.2 2.348 6:32210449 6 56.4 1.127 5:3831996 7 48.2 0.874 8:48321556 8 234.2 1.681 9:17933112 9 66.3 1.388 12:22407178 10 0.0 2.556 3:50002516 11 158.4 1.218 9:192355 12 70.5 1.874 5:34362578 13 356.6 1.411 5:2229593 14 72.4 1.518 4:59781115 15 213.3 11.094 1:25224019 16 111.7 1.582 [1] 4.003248 chr pos lod 4:59781115 15 213 11.1 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 3312.438 1656.21913 11.09423 9.676683 8.04945e-12 9.377166e-12 Error 499 30918.693 61.96131 Total 501 34231.132 Estimated effects: ----------------- est SE t Intercept 115.9345 0.3521 329.271 15@213.3a -3.7617 0.5466 -6.883 15@213.3d 1.5239 0.7839 1.944 chr pos lod 15:12653932 15 207.6340 7.699152 4:59781115 15 213.2960 11.094231 4:28190349 15 260.7535 9.776275 [1] "###############################################################################################" [1] "DMN_Y2_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.08 chr pos lod 9:43025346 1 174.74 1.959 2:41075816 2 270.38 1.836 5:27246322 3 123.90 1.610 1:83785785 4 150.62 1.022 13:10394124 5 10.12 0.702 6:30679731 6 108.53 0.526 4:36110007 7 84.13 3.609 3:7213159 8 250.57 3.453 9:50192961 9 214.55 2.678 2:37602534 10 176.38 1.712 8:47824143 11 192.66 1.747 1:59907104 12 413.03 2.366 10:11515211 13 68.82 2.069 14:1169849 14 9.45 3.069 15:7715776 15 184.26 2.684 9:39861065 16 210.73 1.268 [1] 4.079149 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "DMN_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.15 chr pos lod 1:71351069 1 228.6 0.798 2:34116491 2 197.6 2.809 3:30838568 3 176.2 0.794 4:81706482 4 234.0 0.762 5:3335042 5 141.5 2.178 4:53452068 6 33.5 1.317 7:43519203 7 89.9 2.040 4:18350867 8 165.4 2.773 6:9116814 9 234.4 3.072 2:37602534 10 176.4 5.476 8:47824143 11 192.7 1.859 1:59907104 12 413.0 0.922 13:32574275 13 272.1 0.977 11:13221618 14 54.9 0.717 12:7049090 15 258.6 6.319 10:36441807 16 117.8 1.438 [1] 4.148261 chr pos lod 2:37602534 10 176 5.48 12:7049090 15 259 6.32 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 4005.985 1001.49637 11.51289 10.02291 8.4449e-11 1.035618e-10 Error 497 35962.289 72.35873 Total 501 39968.274 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@176.4 2 1814 5.363 4.537 12.53 0 4.90e-06 *** 15@256.4 2 2048 6.037 5.124 14.15 0 1.05e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 237.8586 0.3809 624.536 10@176.4a 3.0040 0.6028 4.983 10@176.4d 0.6222 0.8373 0.743 15@256.4a -2.4484 0.5937 -4.124 15@256.4d 2.6666 0.8375 3.184 chr pos lod 2:10018142 10 164.7815 2.802005 2:37602534 10 176.3774 5.363043 2:47564341 10 215.9326 3.403974 chr pos lod 15:12653932 15 207.6340 4.260559 12:25363843 15 256.4413 6.037213 7:36623456 15 273.9779 3.935895 [1] "###############################################################################################" [1] "DMN_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.06 chr pos lod 1:45924408 1 104.1 1.55 1:34656738 2 95.6 1.85 11:42202822 3 90.5 1.83 4:81706482 4 234.0 1.10 5:3364109 5 147.1 4.53 6:24008520 6 10.4 1.30 7:2322473 7 0.0 2.40 4:18350867 8 165.4 2.29 9:61647771 9 316.7 2.06 2:43914108 10 212.6 5.35 6:1816309 11 0.0 1.05 8:38023810 12 341.2 2.08 2:24999810 13 281.7 4.93 14:10096054 14 80.5 2.35 9:48242797 15 232.6 6.44 4:78112277 16 129.6 1.51 [1] 4.062162 chr pos lod 5:3364109 5 147 4.53 2:43914108 10 213 5.35 2:24999810 13 282 4.93 9:48242797 15 233 6.44 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 87945.13 10993.1408 19.62253 16.47383 4.440892e-16 6.661338e-16 Error 493 445902.51 904.4676 Total 501 533847.64 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 5@147.1 2 14699 3.535 2.753 8.126 0 0.000337 *** 10@166.3 2 21515 5.137 4.030 11.894 0 9.02e-06 *** 13@276.0 2 18083 4.333 3.387 9.996 0 5.55e-05 *** 15@219.4 2 22325 5.325 4.182 12.342 0 5.89e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 173.035 1.355 127.734 5@147.1a 8.266 2.067 3.999 5@147.1d -2.267 3.038 -0.746 10@166.3a 10.407 2.139 4.866 10@166.3d 1.780 2.996 0.594 13@276.0a 9.029 2.096 4.308 13@276.0d 4.523 2.997 1.509 15@219.4a -9.291 2.123 -4.377 15@219.4d 6.336 2.992 2.118 chr pos lod 9:43976150 5 23.19892 2.468072 5:3364109 5 147.08320 3.535404 3:17551498 5 156.31182 2.360991 chr pos lod 2:32704639 10 156.9299 4.060506 6:17008091 10 166.2545 5.136691 11:43192432 10 214.1223 4.123742 chr pos lod 13:31303787 13 258.1781 3.307078 13:40112209 13 276.0026 4.333357 4:61642288 13 301.2866 3.252867 chr pos lod 15:29528215 15 211.5335 4.253919 10:18367752 15 219.3767 5.325471 7:37742497 15 285.1133 3.481639 [1] "###############################################################################################" [1] "DMN_Y2_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.97 chr pos lod 2:50950465 1 285.23 0.988 10:12261824 2 135.46 0.796 3:22133857 3 123.49 0.954 4:81706482 4 234.01 2.339 5:2792503 5 93.18 1.652 3:42517193 6 4.34 0.916 7:17238130 7 26.32 1.588 4:34790402 8 290.73 3.747 11:13931772 9 155.17 2.265 7:29772093 10 202.70 3.447 11:40901234 11 145.79 5.172 4:77631572 12 482.37 0.639 13:15074312 13 86.95 2.718 8:52230082 14 6.85 4.475 7:37742497 15 285.11 2.639 16:3256374 16 243.19 1.838 [1] 3.966741 chr pos lod 11:40901234 11 145.79 5.17 8:52230082 14 6.85 4.48 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 83977.35 20994.338 9.365785 8.233088 9.71987e-09 1.145813e-08 Error 497 936020.83 1883.342 Total 501 1019998.18 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 11@145.8 2 42950 4.891 4.211 11.403 0 1.44e-05 *** 14@6.8 2 36708 4.193 3.599 9.745 0 7.05e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 287.2444 1.9436 147.786 11@145.8a 13.8215 2.9299 4.717 11@145.8d 3.0290 4.3439 0.697 14@6.8a 13.0569 2.9588 4.413 14@6.8d 0.1305 4.3055 0.030 chr pos lod 11:32320512 11 130.7533 3.804904 11:40901234 11 145.7878 4.890541 11:47380649 11 198.1109 2.873416 chr pos lod 3:26735632 14 5.262673 3.082436 8:52230082 14 6.847201 4.193291 4:37985409 14 22.179699 3.100837 [1] "###############################################################################################" [1] "DMN_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.07 chr pos lod 2:50950465 1 285.23 0.897 2:13466641 2 109.82 1.459 9:11862600 3 44.76 0.789 4:81706482 4 234.01 3.006 5:2792503 5 93.18 3.227 3:42517193 6 4.34 1.257 1:77036244 7 117.74 2.229 8:43778381 8 154.77 2.318 9:4256867 9 0.00 2.426 4:22109353 10 206.97 6.463 4:46616602 11 136.20 2.336 12:14569762 12 259.99 1.058 13:31767966 13 267.39 3.790 8:52230082 14 6.85 3.142 15:21105622 15 277.72 5.415 5:21547273 16 124.12 1.955 [1] 4.072929 chr pos lod 4:22109353 10 207 6.46 15:21105622 15 278 5.42 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 141524.1 35381.031 11.53491 10.04109 8.042178e-11 9.866319e-11 Error 497 1267926.0 2551.159 Total 501 1409450.1 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@207.0 2 73439 6.138 5.210 14.39 0 8.38e-07 *** 15@249.5 2 60389 5.072 4.285 11.84 0 9.52e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 461.083 2.298 200.604 10@207.0a 18.071 3.512 5.146 10@207.0d 8.418 5.267 1.598 15@249.5a -13.274 3.398 -3.907 15@249.5d 13.335 5.202 2.563 chr pos lod 2:10018142 10 164.7815 3.923059 4:22109353 10 206.9730 6.137717 2:47564341 10 215.9326 4.457061 chr pos lod 11:12951583 15 216.7998 3.472408 15:33145691 15 249.4854 5.072028 7:37547201 15 295.5078 1.767797 [1] "###############################################################################################" [1] "DMN_PC1_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.95 chr pos lod 1:40883977 1 99.1 0.846 7:8093862 2 206.2 2.699 11:16006307 3 97.5 2.561 4:67833454 4 138.1 2.810 10:11680427 5 134.7 1.960 6:24008520 6 10.4 1.416 7:52684392 7 103.1 1.945 8:48321556 8 234.2 1.332 9:61647771 9 316.7 1.878 2:49915311 10 73.6 2.702 11:40901234 11 145.8 1.662 8:38023810 12 341.2 1.990 15:18808016 13 257.2 2.798 14:23794211 14 169.1 1.001 10:17987993 15 256.7 13.026 8:13165488 16 139.7 3.214 [1] 3.952877 chr pos lod 10:17987993 15 257 13 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 171.9909 85.995428 13.02604 11.26327 9.414691e-14 1.126876e-13 Error 499 1355.0155 2.715462 Total 501 1527.0063 Estimated effects: ----------------- est SE t Intercept 0.02119 0.07360 0.288 15@256.7a -0.84186 0.11377 -7.400 15@256.7d 0.42276 0.16164 2.615 chr pos lod 11:12951583 15 216.7998 11.77365 10:17987993 15 256.6860 13.02604 4:28190349 15 260.7535 11.90689 [1] "###############################################################################################" [1] "DMN_PC2_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.96 chr pos lod 6:4032237 1 164.33 0.924 1:34656738 2 95.63 3.816 3:23389564 3 147.01 0.567 12:38343043 4 185.91 1.699 6:24818696 5 154.84 2.723 6:32204397 6 58.31 0.508 9:22568048 7 134.75 0.732 8:47095870 8 175.47 4.462 1:67175015 9 195.19 1.160 1:47699013 10 211.17 9.157 6:1816309 11 0.00 2.532 12:14569762 12 259.99 1.194 16:15205749 13 391.82 2.293 8:52230082 14 6.85 2.770 15:13730182 15 205.23 0.919 8:62825665 16 356.09 1.878 [1] 3.956343 chr pos lod 8:47095870 8 175 4.46 1:47699013 10 211 9.16 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 137.582 34.395490 13.30306 11.48849 1.574185e-12 1.995182e-12 Error 497 1059.981 2.132759 Total 501 1197.563 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 8@175.5 2 41.09 4.146 3.432 9.634 0 7.85e-05 *** 10@211.2 2 89.55 8.841 7.478 20.995 0 1.77e-09 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 0.01007 0.06554 0.154 8@175.5a 0.34695 0.09913 3.500 8@175.5d 0.38468 0.14948 2.573 10@211.2a 0.66751 0.10407 6.414 10@211.2d 0.16087 0.14480 1.111 chr pos lod 7:7615595 8 156.7334 2.786296 8:47095870 8 175.4730 4.146293 16:28725138 8 216.6054 2.876209 chr pos lod 10:31584236 10 176.7865 7.607971 1:47699013 10 211.1679 8.841174 2:47564341 10 215.9326 7.021924 [1] "###############################################################################################" [1] "DMN_PC3_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.09 chr pos lod 1:45895930 1 106.7 1.537 10:31111966 2 227.1 2.072 11:42202822 3 90.5 1.307 4:59660137 4 218.0 0.710 9:43976150 5 23.2 1.720 6:26304119 6 8.0 0.235 7:2322473 7 0.0 3.225 8:7255573 8 11.0 1.880 9:12308191 9 17.4 1.103 9:57278172 10 26.5 2.212 11:49723125 11 208.7 1.875 12:31231309 12 371.5 0.748 0:10902661 13 138.9 2.133 9:6891625 14 302.1 2.954 7:37531607 15 300.0 1.456 9:2078323 16 228.6 1.900 [1] 4.091474 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "DMN_sqrt_VegArea_d38" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.99 chr pos lod 1:70506336 1 204.8 1.285 7:8093862 2 206.2 1.711 3:23389564 3 147.0 1.043 1:83785785 4 150.6 1.985 1:56437288 5 331.5 0.919 6:38553759 6 63.7 0.241 7:17238130 7 26.3 1.227 8:47095870 8 175.5 2.899 1:47290936 9 119.3 1.673 10:21730628 10 146.9 2.006 11:37915596 11 142.8 2.623 4:53353111 12 392.7 1.403 13:28411786 13 223.1 1.563 14:10056720 14 76.6 2.020 14:699798 15 308.5 2.987 9:2078323 16 228.6 3.287 [1] 3.990492 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "DMN_sqrt_VegArea_d120" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.94 chr pos lod 7:45584108 1 86.27 1.960 7:8093862 2 206.20 3.085 4:8512571 3 34.84 2.035 13:13646557 4 141.20 4.816 5:22029888 5 331.48 0.963 15:13186532 6 38.57 1.013 7:52684392 7 103.06 0.979 8:47095870 8 175.47 0.959 1:47290936 9 119.35 0.750 2:49915311 10 73.57 2.300 11:37915596 11 142.83 1.207 12:27710929 12 366.16 1.507 13:2132329 13 51.94 2.442 3:26735632 14 5.26 1.647 15:33145691 15 249.49 3.731 4:58955253 16 228.15 5.115 [1] 3.943939 chr pos lod 13:13646557 4 141 4.82 4:58955253 16 228 5.11 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 118.3454 29.586351 8.872464 7.816851 2.874419e-08 3.357891e-08 Error 497 1395.6325 2.808114 Total 501 1513.9779 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 4@141.2 2 48.95 3.758 3.233 8.716 0 0.00019 *** 16@228.1 2 52.91 4.056 3.495 9.421 0 9.65e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 26.23988 0.07555 347.304 4@141.2a -0.50168 0.12024 -4.172 4@141.2d -0.01958 0.16941 -0.116 16@228.1a 0.30187 0.11413 2.645 16@228.1d -0.54531 0.17091 -3.191 chr pos lod 12:19997567 4 111.8620 2.714013 13:13646557 4 141.2027 3.757872 12:38343043 4 185.9087 2.375506 chr pos lod 9:39881977 16 200.4978 2.478987 4:58955253 16 228.1478 4.056027 6:13101118 16 232.6276 2.281967 [1] "###############################################################################################" [1] "DMN_sqrt_VegArea_d339" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.01 chr pos lod 9:38204178 1 113.71 0.800 1:39109401 2 116.66 2.362 4:8512571 3 34.84 0.922 12:38343043 4 185.91 2.794 11:59480799 5 328.74 1.141 14:31827854 6 103.11 0.954 7:2322473 7 0.00 0.617 8:61377122 8 317.29 3.781 1:67175015 9 195.19 0.755 2:37602534 10 176.38 7.246 1:20990542 11 162.98 1.400 4:5937117 12 117.03 3.470 12:50035595 13 88.46 2.057 3:26735632 14 5.26 6.162 11:12951583 15 216.80 3.259 16:42089416 16 341.52 0.964 [1] 4.007706 chr pos lod 2:37602534 10 176.38 7.25 3:26735632 14 5.26 6.16 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 551.2726 137.818161 12.51423 10.84565 9.124479e-12 1.139777e-11 Error 497 4531.6168 9.117941 Total 501 5082.8894 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@176.4 2 271.9 6.353 5.350 14.91 0 5.14e-07 *** 14@5.3 2 224.4 5.268 4.415 12.30 0 6.09e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 17.8444 0.1354 131.836 10@176.4a 1.1717 0.2151 5.448 10@176.4d 0.2012 0.2960 0.680 14@5.3a 0.9041 0.2038 4.436 14@5.3d -0.6124 0.2998 -2.043 chr pos lod 10:22762714 10 153.5043 4.392972 2:37602534 10 176.3774 6.352623 2:41208781 10 210.9362 5.020793 chr pos lod 3:26748571 14 0.000000 4.006649 3:26735632 14 5.262673 5.268192 7:22290526 14 35.624209 3.166006 [1] "###############################################################################################" [1] "DMN_sqrt_VegArea_d458" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.01 chr pos lod 5:5548115 1 157.72 1.582 1:39109401 2 116.66 0.988 5:27246322 3 123.90 3.267 12:44145163 4 136.60 1.979 5:12557744 5 204.73 1.543 6:32184811 6 46.72 0.738 7:24220424 7 7.62 1.716 13:5256500 8 336.32 2.202 1:67186377 9 194.87 1.424 7:29772093 10 202.70 1.764 2:6349679 11 172.27 2.786 12:27710929 12 366.16 2.875 1:89064188 13 91.11 2.874 3:26735632 14 5.26 1.978 15:10330648 15 170.70 1.839 1:92139438 16 303.66 2.016 [1] 4.011534 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "DMN_sqrt_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.86 chr pos lod 9:59284271 1 338.48 0.639 1:34656738 2 95.63 1.990 11:16006307 3 97.54 2.589 4:32106393 4 9.81 1.349 5:3341512 5 148.23 2.208 12:35293994 6 10.77 1.216 1:27219384 7 148.06 1.167 8:48321556 8 234.15 2.119 15:26388047 9 88.10 1.688 2:43914108 10 212.64 2.877 3:50002516 11 158.38 1.364 9:192355 12 70.54 1.735 5:34362578 13 356.64 1.843 14:10096054 14 80.55 1.545 10:17987993 15 256.69 9.965 1:25224019 16 111.70 1.466 [1] 3.856207 chr pos lod 10:17987993 15 257 9.97 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 9.174209 4.5871045 9.965053 8.73619 1.083796e-10 1.243081e-10 Error 499 95.839637 0.1920634 Total 501 105.013846 Estimated effects: ----------------- est SE t Intercept 10.70943 0.01957 547.121 15@256.7a -0.19453 0.03026 -6.429 15@256.7d 0.09731 0.04299 2.264 chr pos lod 15:12653932 15 207.6340 6.749062 10:17987993 15 256.6860 9.965053 4:28190349 15 260.7535 8.873840 [1] "###############################################################################################" [1] "DMN_sqrt_Y2_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.03 chr pos lod 9:43025346 1 174.7 2.064 2:41075816 2 270.4 2.450 11:23714171 3 125.5 1.419 1:83785785 4 150.6 1.357 5:12557744 5 204.7 0.571 6:30679731 6 108.5 0.657 4:36110007 7 84.1 4.122 3:7213159 8 250.6 3.223 9:49360707 9 196.1 2.073 10:22722460 10 151.6 1.678 8:47870541 11 190.9 1.703 4:73151497 12 469.5 2.204 10:11515211 13 68.8 1.781 5:2229593 14 72.4 3.164 15:7715776 15 184.3 2.706 1:44911888 16 40.9 1.155 [1] 4.026512 chr pos lod 4:36110007 7 84.1 4.12 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 0.5753068 0.28765342 4.121968 3.710748 7.55147e-05 7.992172e-05 Error 499 14.9284919 0.02991682 Total 501 15.5037987 Estimated effects: ----------------- est SE t Intercept 10.89353 0.00776 1403.855 7@84.1a 0.03963 0.01197 3.311 7@84.1d 0.04218 0.01702 2.477 chr pos lod 7:37937424 7 75.66990 1.419642 4:36110007 7 84.13474 4.121968 7:43406998 7 87.49862 3.087816 [1] "###############################################################################################" [1] "DMN_sqrt_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.04 chr pos lod 1:45924408 1 104.1 0.871 2:41075816 2 270.4 2.891 3:30838568 3 176.2 0.601 4:81706482 4 234.0 0.661 5:3335042 5 141.5 2.029 4:53452068 6 33.5 1.025 7:43519203 7 89.9 2.628 4:18350867 8 165.4 2.153 6:9116814 9 234.4 2.604 2:37602534 10 176.4 5.452 8:47824143 11 192.7 2.015 1:59907104 12 413.0 0.870 13:32574275 13 272.1 1.143 5:2229593 14 72.4 0.947 12:7049090 15 258.6 5.124 8:62825665 16 356.1 1.527 [1] 4.035856 chr pos lod 2:37602534 10 176 5.45 12:7049090 15 259 5.12 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 6.65154 1.6628851 10.27477 8.995121 1.309787e-09 1.570046e-09 Error 497 67.29455 0.1354015 Total 501 73.94609 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@176.4 2 3.256 5.151 4.404 12.02 0 7.94e-06 *** 15@258.6 2 3.044 4.823 4.117 11.24 0 1.68e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 15.37049 0.01648 932.650 10@176.4a 0.12697 0.02609 4.866 10@176.4d 0.03138 0.03618 0.867 15@258.6a -0.09077 0.02591 -3.503 15@258.6d 0.11054 0.03640 3.036 chr pos lod 2:10018142 10 164.7815 2.799969 2:37602534 10 176.3774 5.151223 2:47564341 10 215.9326 3.234578 chr pos lod 15:12653932 15 207.6340 3.247779 12:7049090 15 258.5511 4.822768 7:36623456 15 273.9779 2.897358 [1] "###############################################################################################" [1] "DMN_sqrt_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.02 chr pos lod 1:45924408 1 104.07 1.75 1:34656738 2 95.63 2.23 11:42202822 3 90.47 2.24 2:38305808 4 9.47 1.28 5:3364109 5 147.08 4.63 3:42517193 6 4.34 1.43 7:2322473 7 0.00 2.15 4:18350867 8 165.43 1.91 9:61647771 9 316.70 1.91 2:43914108 10 212.64 5.57 6:1816309 11 0.00 1.15 8:38023810 12 341.23 1.84 2:24999810 13 281.68 5.24 14:10096054 14 80.55 1.97 15:33131222 15 256.03 8.44 1:13834614 16 129.89 1.39 [1] 4.023007 chr pos lod 5:3364109 5 147 4.63 2:43914108 10 213 5.57 2:24999810 13 282 5.24 15:33131222 15 256 8.44 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 245.8161 30.727008 21.78418 18.11385 0 0 Error 493 1111.2453 2.254047 Total 501 1357.0614 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 5@147.1 2 38.55 3.718 2.841 8.552 0 0.000223 *** 10@176.4 2 53.53 5.128 3.944 11.874 0 9.20e-06 *** 13@280.5 2 44.34 4.265 3.267 9.835 0 6.48e-05 *** 15@256.7 2 77.79 7.376 5.732 17.255 0 5.71e-08 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 12.603104 0.067521 186.655 5@147.1a 0.426366 0.103250 4.129 5@147.1d -0.072740 0.151790 -0.479 10@176.4a 0.518646 0.106540 4.868 10@176.4d 0.007767 0.148318 0.052 13@280.5a 0.449792 0.103180 4.359 13@280.5d 0.161080 0.148925 1.082 15@256.7a -0.545483 0.104979 -5.196 15@256.7d 0.371641 0.148020 2.511 chr pos lod 13:125333 5 26.60209 2.711872 5:3364109 5 147.08320 3.717884 3:17551498 5 156.31182 2.559105 chr pos lod 10:21730628 10 146.9442 3.465762 2:37602534 10 176.3774 5.128235 2:47564341 10 215.9326 3.764031 chr pos lod 13:31303787 13 258.1781 3.130079 13:32547493 13 280.5347 4.264830 5:47352174 13 384.2351 3.110854 chr pos lod 4:59784427 15 214.4111 6.104834 10:17987993 15 256.6860 7.375532 7:36623456 15 273.9779 5.820206 [1] "###############################################################################################" [1] "DMN_sqrt_Y2_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.93 chr pos lod 9:42276096 1 173.97 1.162 2:34116491 2 197.60 0.757 11:23714171 3 125.48 1.484 11:64101328 4 150.62 2.280 5:2792503 5 93.18 1.482 3:42517193 6 4.34 0.877 7:17238130 7 26.32 1.575 4:34790402 8 290.73 4.266 11:13931772 9 155.17 2.513 7:29772093 10 202.70 3.427 11:40901234 11 145.79 4.652 13:3648874 12 467.22 0.807 13:15074312 13 86.95 2.843 8:52230082 14 6.85 4.820 15:13730182 15 205.23 1.776 4:70104853 16 7.55 1.511 [1] 3.932149 chr pos lod 4:34790402 8 290.73 4.27 11:40901234 11 145.79 4.65 8:52230082 14 6.85 4.82 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 86.89728 14.482880 12.75538 11.04266 8.108925e-11 1.066933e-10 Error 495 700.02584 1.414194 Total 501 786.92312 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 8@290.7 2 23.07 3.534 2.931 8.155 0 0.000328 *** 11@151.7 2 28.26 4.315 3.592 9.993 0 5.56e-05 *** 14@6.8 2 26.64 4.071 3.385 9.418 0 9.68e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 16.48262 0.05365 307.240 8@290.7a 0.31448 0.07973 3.944 8@290.7d 0.07779 0.11837 0.657 11@151.7a 0.32323 0.07876 4.104 11@151.7d 0.20233 0.11931 1.696 14@6.8a 0.35409 0.08190 4.323 14@6.8d -0.02891 0.11800 -0.245 chr pos lod 6:32057188 8 241.6810 2.372537 4:34790402 8 290.7330 3.533830 8:61981784 8 379.7943 2.610025 chr pos lod 11:32320512 11 130.7533 2.931353 11:40793705 11 151.6855 4.314752 11:47380649 11 198.1109 3.015654 chr pos lod 3:26735632 14 5.262673 2.886063 8:52230082 14 6.847201 4.071080 4:73303164 14 24.433726 2.833581 [1] "###############################################################################################" [1] "DMN_sqrt_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.97 chr pos lod 1:46548927 1 109.23 0.937 2:28474508 2 111.97 1.855 9:11862600 3 44.76 0.841 4:81706482 4 234.01 3.176 5:2792503 5 93.18 3.158 3:42517193 6 4.34 1.210 7:17238130 7 26.32 2.215 4:34790402 8 290.73 2.324 9:35216134 9 140.05 2.490 4:22109353 10 206.97 7.840 4:46616602 11 136.20 2.010 12:14569762 12 259.99 1.569 13:31767966 13 267.39 4.192 8:52230082 14 6.85 3.306 15:21105622 15 277.72 4.633 5:21547273 16 124.12 1.503 [1] 3.970384 chr pos lod 4:22109353 10 207 7.84 13:31767966 13 267 4.19 15:21105622 15 278 4.63 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 152.2962 25.382703 16.00877 13.65841 7.027712e-14 9.969803e-14 Error 495 962.7399 1.944929 Total 501 1115.0361 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@166.3 2 69.93 7.644 6.272 17.978 0 2.90e-08 *** 13@391.8 2 38.86 4.314 3.485 9.990 0 5.58e-05 *** 15@277.7 2 37.70 4.187 3.381 9.692 0 7.43e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 21.05336 0.06273 335.628 10@166.3a 0.55656 0.09919 5.611 10@166.3d 0.33156 0.13851 2.394 13@391.8a 0.39291 0.09645 4.074 13@391.8d 0.31404 0.13946 2.252 15@277.7a -0.36381 0.09882 -3.682 15@277.7d 0.31212 0.13906 2.245 chr pos lod 5:22962490 10 157.5322 6.452659 6:17008091 10 166.2545 7.643625 2:41208781 10 210.9362 6.549561 chr pos lod 13:30406241 13 263.5035 3.181508 16:15205749 13 391.8175 4.313621 5:44660479 13 423.6247 1.466608 chr pos lod 11:12951583 15 216.7998 2.535825 15:21105622 15 277.7161 4.187368 7:37547201 15 295.5078 1.400409 [1] "###############################################################################################" [1] "DMN_PC1_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.02 chr pos lod 1:45924408 1 104.1 1.31 1:34656738 2 95.6 2.52 12:19394979 3 176.6 1.71 4:81706482 4 234.0 1.35 5:3335042 5 141.5 3.58 6:24008520 6 10.4 1.49 1:77036244 7 117.7 2.01 4:18350867 8 165.4 1.89 9:61647771 9 316.7 1.91 2:43914108 10 212.6 6.70 6:1816309 11 0.0 1.43 8:38023810 12 341.2 1.52 13:32574275 13 272.1 3.26 14:10096054 14 80.5 1.53 15:33131222 15 256.0 10.01 14:20415062 16 133.5 1.99 [1] 4.018419 chr pos lod 2:43914108 10 213 6.7 15:33131222 15 256 10.0 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 198.3989 49.599725 16.2818 13.8744 1.998401e-15 2.664535e-15 Error 497 1231.5648 2.477998 Total 501 1429.9637 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@196.0 2 73.15 6.289 5.115 14.76 0 5.93e-07 *** 15@256.7 2 117.85 9.962 8.242 23.78 0 1.37e-10 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 0.02000 0.07122 0.281 10@196.0a 0.56374 0.10482 5.378 10@196.0d 0.15027 0.17041 0.882 15@256.7a -0.66648 0.10918 -6.104 15@256.7d 0.46702 0.15522 3.009 chr pos lod 2:10018142 10 164.7815 3.780432 10:26264083 10 196.0259 6.289319 2:47564341 10 215.9326 4.466550 chr pos lod 15:33135990 15 218.9955 8.957703 10:17987993 15 256.6860 9.961918 4:28190349 15 260.7535 8.918364 [1] "###############################################################################################" [1] "DMN_PC2_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.89 chr pos lod 6:4032237 1 164.33 1.454 1:34670247 2 96.70 2.290 3:23389564 3 147.01 2.059 11:64088454 4 165.30 3.079 5:12468384 5 204.32 1.393 14:31827854 6 103.11 0.509 7:2322473 7 0.00 0.537 2:3707283 8 232.82 3.213 1:67186377 9 194.87 0.892 10:34658541 10 189.71 3.969 11:37899301 11 140.28 1.653 12:27710929 12 366.16 1.390 1:89064188 13 91.11 2.710 3:26735632 14 5.26 3.663 10:17987993 15 256.69 3.391 1:92139438 16 303.66 2.095 [1] 3.888284 chr pos lod 10:34658541 10 190 3.97 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 47.97441 23.987207 3.968532 3.575118 0.0001075148 0.0001135493 Error 499 1293.92295 2.593032 Total 501 1341.89737 Estimated effects: ----------------- est SE t Intercept 0.009185 0.071968 0.128 10@189.7a -0.492521 0.114976 -4.284 10@189.7d -0.076580 0.160126 -0.478 chr pos lod 2:30462916 10 142.1406 2.694376 10:34658541 10 189.7106 3.968532 2:46091293 10 240.1407 3.211265 [1] "###############################################################################################" [1] "DMN_PC3_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.04 chr pos lod 1:31590441 1 88.8 1.401 13:20487913 2 240.2 1.578 11:42202822 3 90.5 1.676 4:59660137 4 218.0 1.023 13:121536 5 0.0 1.291 6:30679731 6 108.5 0.281 7:2322473 7 0.0 2.059 8:61981784 8 379.8 2.215 6:9116814 9 234.4 0.759 2:7811612 10 23.2 2.679 11:49723125 11 208.7 2.370 2:42492525 12 498.5 0.881 3:6021877 13 228.6 2.541 4:32890845 14 59.9 4.269 7:28140741 15 49.8 2.051 9:2078323 16 228.6 3.221 [1] 4.038048 chr pos lod 4:32890845 14 59.9 4.27 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 16.9418 8.4709006 4.269388 3.840879 5.377886e-05 5.703295e-05 Error 499 424.1500 0.8499999 Total 501 441.0918 Estimated effects: ----------------- est SE t Intercept 0.009876 0.041453 0.238 14@59.9a -0.264336 0.062557 -4.226 14@59.9d -0.168800 0.094184 -1.792 chr pos lod 1:58435253 14 52.76660 2.689965 4:32890845 14 59.91980 4.269388 2:26246583 14 65.97425 2.946473 [1] "###############################################################################################" [1] "GFL_VegArea_d9" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.9 chr pos lod 2:50973146 1 307.58 2.254 2:50659160 2 247.72 0.738 6:3850109 3 52.39 1.014 4:35446116 4 15.48 1.366 5:3114617 5 96.00 0.891 3:17111948 6 3.06 1.037 7:38150109 7 69.39 1.183 8:63047006 8 323.21 2.861 1:92735986 9 359.23 1.941 10:11235009 10 93.27 0.633 4:79393101 11 148.31 2.315 4:70311165 12 441.43 1.455 12:37152189 13 254.80 1.170 4:32890845 14 59.92 4.505 15:3164473 15 48.99 1.738 1:44911888 16 40.87 3.258 [1] 3.895056 chr pos lod 4:32890845 14 59.9 4.51 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 245.3365 122.66824 4.505497 4.048932 3.122504e-05 3.322219e-05 Error 499 5813.9522 11.65121 Total 501 6059.2887 Estimated effects: ----------------- est SE t Intercept 21.3382 0.1535 139.036 14@59.9a 1.0105 0.2316 4.363 14@59.9d 0.6225 0.3487 1.785 chr pos lod 2:48747814 14 42.49033 3.132535 4:32890845 14 59.91980 4.505497 2:26222046 14 67.26205 3.425258 [1] "###############################################################################################" [1] "GFL_VegArea_d119" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.97 chr pos lod 3:60661981 1 300.7 2.225 2:34251230 2 210.9 0.655 3:30838568 3 176.2 1.854 8:31577684 4 114.4 1.008 1:18842978 5 193.1 2.680 3:42539317 6 0.0 1.424 1:27622820 7 142.8 0.513 3:24563723 8 0.0 1.730 1:89625376 9 312.6 1.568 6:17008091 10 166.3 1.599 11:56631671 11 255.4 1.385 13:8187658 12 288.2 2.295 2:33454787 13 202.0 2.124 3:26748571 14 0.0 3.334 15:952339 15 12.6 1.775 9:39881977 16 200.5 2.046 [1] 3.974556 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_VegArea_d235" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.03 chr pos lod 7:2928057 1 29.6 1.910 11:42378122 2 214.4 1.200 3:11027167 3 37.7 0.631 4:47743750 4 95.0 1.708 2:50830987 5 67.0 0.614 6:28337837 6 42.0 1.369 7:52104137 7 94.0 0.934 9:28946744 8 266.1 1.222 9:56240364 9 271.4 2.532 2:10018142 10 164.8 2.104 11:31209255 11 111.1 2.113 14:19671886 12 242.7 1.134 5:18425901 13 235.2 1.654 14:23176255 14 157.3 1.066 12:25588091 15 20.4 14.749 16:9508199 16 54.3 0.867 [1] 4.030458 chr pos lod 12:25588091 15 20.4 14.7 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 318550.3 159275.159 14.74939 12.65511 1.776357e-15 2.220446e-15 Error 499 2198616.6 4406.045 Total 501 2517166.9 Estimated effects: ----------------- est SE t Intercept 202.009 2.973 67.953 15@20.4a 36.990 4.490 8.238 15@20.4d -17.096 6.685 -2.557 chr pos lod 10:623262 15 0.00000 14.684367 12:25588091 15 20.35904 14.749391 1:87502908 15 37.45411 9.820661 [1] "###############################################################################################" [1] "GFL_VegArea_d354" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.94 chr pos lod 8:29253506 1 208.5 1.097 4:16569653 2 257.3 1.853 5:27246322 3 123.9 0.591 4:39776408 4 28.8 0.733 13:515601 5 33.7 1.323 12:41843752 6 67.0 1.121 2:37456337 7 152.6 0.450 8:52686829 8 225.0 0.638 8:62862087 9 116.6 1.438 10:5184667 10 32.3 0.954 11:47380649 11 198.1 0.930 2:8199842 12 459.3 1.261 10:11482250 13 65.0 0.821 10:38224588 14 199.5 0.625 15:952339 15 12.6 1.540 16:45237289 16 362.2 1.644 [1] 3.936794 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_VegArea_d452" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.82 chr pos lod 1:74535467 1 237.07 1.286 2:39532686 2 273.70 0.772 12:19394979 3 176.56 0.961 10:23633888 4 44.95 0.878 13:515601 5 33.70 0.772 14:31827854 6 103.11 0.128 7:52684392 7 103.06 0.606 12:43434052 8 52.61 0.471 2:39267648 9 123.08 0.730 2:46116765 10 226.93 0.931 3:66820321 11 265.93 0.555 2:8199842 12 459.28 1.112 13:23600995 13 164.19 0.766 8:52230082 14 6.85 1.652 15:952339 15 12.56 1.513 16:45237289 16 362.16 1.085 [1] 3.823906 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 9:53060101 1 278.1 1.418 2:9834455 2 89.0 1.236 3:28566249 3 173.3 0.810 1:66045356 4 37.7 1.210 4:66400127 5 254.6 1.906 14:29215898 6 19.5 0.764 7:16482696 7 27.5 1.346 16:15698827 8 60.3 1.469 1:80176394 9 337.2 1.199 2:46629904 10 168.0 15.277 11:44218681 11 184.3 0.650 12:12548239 12 232.0 4.871 13:28156590 13 208.6 1.693 4:37985409 14 22.2 1.324 15:4065533 15 80.6 6.942 3:16346453 16 262.2 5.986 [1] 4.103402 chr pos lod 2:46629904 10 168.0 15.28 12:12548239 12 232.0 4.87 15:4065533 15 80.6 6.94 3:16346453 16 262.2 5.99 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 57215.65 7151.9557 30.58645 24.46615 0 0 Error 493 176640.71 358.2976 Total 501 233856.36 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@168.0 2 23367 13.543 9.992 32.61 0 5.02e-14 *** 12@333.4 2 7456 4.507 3.188 10.41 0 3.75e-05 *** 15@80.6 2 10838 6.491 4.634 15.12 0 4.22e-07 *** 16@267.4 2 7410 4.479 3.169 10.34 0 3.99e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 101.1454 0.8542 118.412 10@168.0a -10.3624 1.3697 -7.566 10@168.0d 4.7893 1.8889 2.535 12@333.4a -5.8175 1.2829 -4.535 12@333.4d -0.9534 1.9120 -0.499 15@80.6a -4.1626 1.3288 -3.133 15@80.6d 8.8896 1.9037 4.670 16@267.4a -5.7290 1.2599 -4.547 16@267.4d 0.1637 1.8886 0.087 chr pos lod 2:10018142 10 164.7815 10.52985 2:46629904 10 167.9995 13.54284 11:20297183 10 173.3347 11.73978 chr pos lod 1:1617682 12 225.2268 2.819270 8:58495823 12 333.4273 4.506972 8:8029939 12 351.8307 3.359488 chr pos lod 15:3164473 15 48.98831 5.327713 15:4065533 15 80.60422 6.491156 1:40459361 15 85.43222 5.153672 chr pos lod 1:11525457 16 257.8200 2.525021 12:47751016 16 267.4168 4.479466 4:4586140 16 283.4219 3.145974 [1] "###############################################################################################" [1] "GFL_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.18 chr pos lod 1:50310321 1 321.35 1.070 9:37557975 2 84.75 1.324 3:28566249 3 173.33 0.825 1:66045356 4 37.72 1.048 4:66400127 5 254.62 1.666 14:29215898 6 19.53 0.981 7:16482696 7 27.53 1.581 16:15698827 8 60.31 1.546 1:80176394 9 337.24 0.889 2:46629904 10 168.00 15.769 11:836231 11 4.69 0.591 12:12548239 12 232.02 4.642 13:28156590 13 208.62 1.994 4:37985409 14 22.18 1.247 15:4065533 15 80.60 6.853 12:47751016 16 267.42 5.924 [1] 4.176565 chr pos lod 2:46629904 10 168.0 15.77 12:12548239 12 232.0 4.64 15:4065533 15 80.6 6.85 12:47751016 16 267.4 5.92 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 35301.94 4412.7422 30.88631 24.67364 0 0 Error 493 107773.56 218.6076 Total 501 143075.49 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@168.0 2 15029 14.231 10.504 34.38 0 1.07e-14 *** 12@333.4 2 4197 4.165 2.934 9.60 0 8.12e-05 *** 15@80.6 2 6607 6.486 4.618 15.11 0 4.27e-07 *** 16@267.4 2 4710 4.663 3.292 10.77 0 2.63e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 103.1310 0.6672 154.571 10@168.0a -8.4190 1.0699 -7.869 10@168.0d 3.4114 1.4755 2.312 12@333.4a -4.3757 1.0021 -4.367 12@333.4d -0.5483 1.4935 -0.367 15@80.6a -3.2288 1.0379 -3.111 15@80.6d 6.9604 1.4870 4.681 16@267.4a -4.5429 0.9841 -4.616 16@267.4d -0.5088 1.4752 -0.345 chr pos lod 2:10018142 10 164.7815 11.15434 2:46629904 10 167.9995 14.23074 11:20297183 10 173.3347 12.21580 chr pos lod 1:1617682 12 225.2268 2.488548 8:58495823 12 333.4273 4.164953 8:8029939 12 351.8307 3.063404 chr pos lod 2:22467490 15 66.33515 5.274233 15:4065533 15 80.60422 6.485880 1:40459361 15 85.43222 4.777609 chr pos lod 1:11525457 16 257.8200 2.556776 12:47751016 16 267.4168 4.662914 16:45237289 16 362.1596 3.467509 [1] "###############################################################################################" [1] "GFL_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.97 chr pos lod 1:95543161 1 364.9 2.361 1:45939251 2 236.5 1.715 11:23714171 3 125.5 1.560 1:66045356 4 37.7 1.705 5:5169798 5 169.2 2.179 14:29215898 6 19.5 0.705 15:14170433 7 37.3 1.279 3:1453631 8 341.5 2.172 1:12699190 9 201.0 1.459 2:46629904 10 168.0 6.728 1:17818780 11 150.5 1.239 8:58495823 12 333.4 4.755 15:18808016 13 257.2 2.742 7:22290526 14 35.6 1.426 15:952339 15 12.6 14.074 3:16346453 16 262.2 6.016 [1] 3.971351 chr pos lod 2:46629904 10 168.0 6.73 8:58495823 12 333.4 4.75 15:952339 15 12.6 14.07 3:16346453 16 262.2 6.02 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 435293.8 54411.726 31.4873 25.08779 0 0 Error 493 1299788.3 2636.487 Total 501 1735082.1 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@166.3 2 75095 6.123 4.328 14.24 0 9.71e-07 *** 12@333.4 2 80830 6.576 4.659 15.33 0 3.48e-07 *** 15@12.6 2 198586 15.499 11.445 37.66 0 6.66e-16 *** 16@269.8 2 59725 4.897 3.442 11.33 0 1.55e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 182.472 2.337 78.085 10@166.3a -19.361 3.682 -5.259 10@166.3d 3.639 5.118 0.711 12@333.4a -19.221 3.481 -5.522 12@333.4d 2.177 5.173 0.421 15@12.6a -26.943 3.392 -7.944 15@12.6d 20.172 5.288 3.815 16@269.8a -16.195 3.404 -4.757 16@269.8d 1.158 5.148 0.225 chr pos lod 2:10018142 10 164.7815 3.907415 6:17008091 10 166.2545 6.122718 10:10100994 10 239.5915 4.709272 chr pos lod 4:43604136 12 329.6277 5.492772 8:58495823 12 333.4273 6.576459 12:34335470 12 361.2224 5.136362 chr pos lod 10:623262 15 0.00000 12.34934 15:952339 15 12.55858 15.49864 1:87509607 15 81.32707 14.46495 chr pos lod 1:11525457 16 257.8200 3.487569 9:13212653 16 269.8129 4.897220 4:4586140 16 283.4219 3.712073 [1] "###############################################################################################" [1] "GFL_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.97 chr pos lod 1:95543161 1 364.9 2.416 2:21384751 2 164.6 1.866 11:23714171 3 125.5 1.753 1:66045356 4 37.7 1.214 14:22054723 5 303.4 1.896 6:24008520 6 10.4 0.734 15:14170433 7 37.3 1.665 3:1453631 8 341.5 1.974 1:12699190 9 201.0 1.782 2:46629904 10 168.0 8.156 1:17818780 11 150.5 0.587 8:58495823 12 333.4 4.768 15:18808016 13 257.2 3.149 3:26748571 14 0.0 1.616 4:36755013 15 79.7 12.666 3:16346453 16 262.2 5.373 [1] 3.968276 chr pos lod 2:46629904 10 168.0 8.16 8:58495823 12 333.4 4.77 4:36755013 15 79.7 12.67 3:16346453 16 262.2 5.37 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 365806.6 45725.822 31.60974 25.17189 0 0 Error 493 1087428.1 2205.737 Total 501 1453234.7 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@166.3 2 88427 8.522 6.085 20.045 0 4.27e-09 *** 12@333.4 2 68728 6.681 4.729 15.579 0 2.75e-07 *** 15@79.7 2 153227 14.370 10.544 34.734 0 7.77e-15 *** 16@269.8 2 43668 4.292 3.005 9.899 0 6.10e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 183.2972 2.1212 86.411 10@166.3a -21.2801 3.3669 -6.320 10@166.3d 0.6730 4.6792 0.144 12@333.4a -17.4869 3.1828 -5.494 12@333.4d 4.6555 4.7449 0.981 15@79.7a -24.6118 3.3123 -7.431 15@79.7d 19.6040 4.7004 4.171 16@269.8a -13.8671 3.1170 -4.449 16@269.8d 0.6984 4.7102 0.148 chr pos lod 2:10018142 10 164.7815 6.038622 6:17008091 10 166.2545 8.522309 10:31584236 10 176.7865 7.484002 chr pos lod 2:39398521 12 330.3208 5.371809 8:58495823 12 333.4273 6.680557 8:8029939 12 351.8307 5.266962 chr pos lod 10:623262 15 0.00000 11.42438 4:36755013 15 79.66509 14.36984 1:40459361 15 85.43222 12.98795 chr pos lod 10:30378449 16 245.2382 2.868462 9:13212653 16 269.8129 4.291857 4:4586140 16 283.4219 3.054803 [1] "###############################################################################################" [1] "GFL_PC1_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.07 chr pos lod 1:50310321 1 321.3 1.878 2:21382317 2 165.9 1.564 3:28566249 3 173.3 1.234 1:66045356 4 37.7 1.106 4:39433340 5 261.8 2.076 14:29215898 6 19.5 0.958 7:15935889 7 28.8 1.467 3:1453631 8 341.5 1.737 1:12699190 9 201.0 1.225 2:46629904 10 168.0 11.738 11:20575629 11 246.8 0.663 12:13739640 12 236.2 5.216 13:28156590 13 208.6 2.429 3:26748571 14 0.0 1.529 15:4065533 15 80.6 8.991 3:16346453 16 262.2 6.479 [1] 4.068102 chr pos lod 2:46629904 10 168.0 11.74 12:13739640 12 236.2 5.22 15:4065533 15 80.6 8.99 3:16346453 16 262.2 6.48 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 459.7225 57.465310 31.26169 24.93259 0 0 Error 493 1384.1392 2.807585 Total 501 1843.8617 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@166.3 2 146.02 10.933 7.919 26.01 0 1.83e-11 *** 12@333.4 2 80.50 6.162 4.366 14.34 0 8.88e-07 *** 15@80.6 2 127.07 9.575 6.892 22.63 0 3.95e-10 *** 16@269.8 2 66.96 5.150 3.631 11.92 0 8.77e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept -0.004507 0.075628 -0.060 10@166.3a 0.844351 0.120122 7.029 10@166.3d -0.225886 0.166910 -1.353 12@333.4a 0.608010 0.113554 5.354 12@333.4d -0.009368 0.169247 -0.055 15@80.6a 0.579865 0.117522 4.934 15@80.6d -0.808685 0.168309 -4.805 16@269.8a 0.539952 0.111203 4.856 16@269.8d -0.101939 0.168033 -0.607 chr pos lod 2:10018142 10 164.7815 8.314825 6:17008091 10 166.2545 10.933035 11:20297183 10 173.3347 9.570500 chr pos lod 2:39398521 12 330.3208 5.133278 8:58495823 12 333.4273 6.162181 8:37992066 12 347.6905 5.144251 chr pos lod 10:623262 15 0.00000 6.447721 15:4065533 15 80.60422 9.574550 1:40459361 15 85.43222 7.858982 chr pos lod 1:11525457 16 257.8200 3.413444 9:13212653 16 269.8129 5.149559 4:4586140 16 283.4219 4.053695 [1] "###############################################################################################" [1] "GFL_PC2_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.88 chr pos lod 1:74535467 1 237.1 1.865 2:53721287 2 287.4 0.885 3:30838568 3 176.2 1.267 10:23633888 4 45.0 0.624 13:515601 5 33.7 1.282 4:10883143 6 67.0 0.655 7:52684392 7 103.1 0.633 8:54668569 8 252.7 0.813 9:34671254 9 124.4 0.933 2:46116765 10 226.9 0.949 11:47380649 11 198.1 0.770 2:8199842 12 459.3 0.903 13:28411786 13 223.1 1.179 11:13221618 14 54.9 0.919 15:2032615 15 27.9 1.526 16:20293855 16 162.9 0.998 [1] 3.877626 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_PC3_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.05 chr pos lod 1:79154628 1 254.48 2.911 6:39733052 2 283.99 0.577 3:23346148 3 149.45 2.121 2:53753680 4 8.33 0.921 13:23208510 5 295.56 1.364 3:42539317 6 0.00 1.173 4:36110007 7 84.13 1.825 3:7203861 8 247.62 2.232 1:92735986 9 359.23 1.072 2:26517709 10 119.44 1.190 11:40901234 11 145.79 3.010 1:82317505 12 484.34 1.161 13:28411786 13 223.12 0.519 11:13221618 14 54.93 2.549 15:1635552 15 46.88 6.247 9:39881977 16 200.50 1.795 [1] 4.053236 chr pos lod 15:1635552 15 46.9 6.25 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 30.61116 15.305578 6.247105 5.569751 5.661028e-07 6.169197e-07 Error 499 518.98538 1.040051 Total 501 549.59654 Estimated effects: ----------------- est SE t Intercept -0.01145 0.04568 -0.251 15@46.9a -0.37349 0.06900 -5.413 15@46.9d -0.01127 0.10305 -0.109 chr pos lod 10:623262 15 0.00000 4.186212 15:1635552 15 46.88030 6.247105 15:4148540 15 72.19039 4.464907 [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d9" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.09 chr pos lod 2:8088841 1 255.4 2.398 6:39733052 2 284.0 0.601 6:3850109 3 52.4 1.283 4:35446116 4 15.5 1.331 5:3114617 5 96.0 1.279 6:27390344 6 15.6 0.722 7:38150109 7 69.4 1.823 8:63047006 8 323.2 2.456 1:92735986 9 359.2 1.858 10:11235009 10 93.3 0.365 4:79393101 11 148.3 1.899 4:77631572 12 482.4 1.459 13:28411786 13 223.1 1.247 11:13221618 14 54.9 5.203 15:3164473 15 49.0 1.711 12:20206887 16 130.8 3.085 [1] 4.088425 chr pos lod 11:13221618 14 54.9 5.2 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 2.074741 1.03737037 5.203463 4.661334 6.259466e-06 6.724092e-06 Error 499 42.434855 0.08503979 Total 501 44.509596 Estimated effects: ----------------- est SE t Intercept 4.30677 0.01305 330.009 14@54.9a 0.09811 0.02042 4.805 14@54.9d 0.03984 0.03019 1.320 chr pos lod 2:48747814 14 42.49033 3.748910 11:13221618 14 54.92732 5.203463 12:12174740 14 68.50538 4.186159 [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d119" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.08 chr pos lod 3:60661981 1 300.7 2.238 2:6785840 2 49.9 0.698 3:28566249 3 173.3 1.755 8:31577684 4 114.4 1.072 1:18842978 5 193.1 3.550 1:41446848 6 89.4 1.422 7:15935889 7 28.8 0.368 14:11190817 8 176.8 1.683 1:89625376 9 312.6 1.599 1:17915261 10 175.4 1.306 12:21021394 11 45.4 1.605 13:8187658 12 288.2 2.424 2:33454787 13 202.0 2.265 3:26748571 14 0.0 2.661 15:952339 15 12.6 1.533 7:34222220 16 190.3 2.594 [1] 4.078382 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d235" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.06 chr pos lod 7:2928057 1 29.6 2.087 10:12265037 2 132.7 1.368 16:29082818 3 87.0 0.580 4:47743750 4 95.0 1.177 8:22064942 5 275.3 0.403 6:28337837 6 42.0 1.208 7:52104137 7 94.0 0.864 5:2065439 8 130.6 1.261 9:55859039 9 297.7 1.837 11:20297183 10 173.3 2.164 6:3845373 11 43.5 2.058 5:40311951 12 496.0 0.930 5:18425901 13 235.2 2.203 14:24512898 14 159.3 0.932 15:2032615 15 27.9 13.442 11:35268581 16 349.7 1.111 [1] 4.062566 chr pos lod 15:2032615 15 27.9 13.4 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 358.3282 179.164102 13.44244 11.60159 3.608225e-14 4.352074e-14 Error 499 2730.2852 5.471514 Total 501 3088.6135 Estimated effects: ----------------- est SE t Intercept 11.5691 0.1055 109.707 15@27.9a 1.2370 0.1552 7.972 15@27.9d -0.4709 0.2375 -1.982 chr pos lod 10:623262 15 0.00000 13.176093 15:2032615 15 27.88446 13.442440 1:87502908 15 37.45411 9.832566 [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d354" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.02 chr pos lod 1:12716854 1 232.1 1.261 4:16569653 2 257.3 1.872 11:23714171 3 125.5 0.655 2:19635388 4 0.0 0.326 13:515601 5 33.7 0.851 12:41843752 6 67.0 1.362 7:50338720 7 112.0 0.841 4:59676731 8 32.2 0.621 1:47290936 9 119.3 0.805 4:22109353 10 207.0 0.854 5:15086802 11 268.0 1.277 12:13770743 12 232.6 1.392 5:18309048 13 247.7 1.245 6:24245239 14 206.8 0.979 15:4151672 15 76.4 2.788 16:45237289 16 362.2 3.106 [1] 4.018795 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d452" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.03 chr pos lod 1:74535467 1 237.07 1.032 2:39532686 2 273.70 0.928 9:11862600 3 44.76 0.929 10:23633888 4 44.95 1.173 3:63545474 5 116.74 0.575 3:42539317 6 0.00 0.219 7:52684392 7 103.06 0.795 16:10193874 8 32.25 0.357 1:78198341 9 264.27 0.910 11:43192432 10 214.12 0.561 5:15086802 11 267.97 0.874 16:28465828 12 452.11 1.189 13:28411786 13 223.12 1.417 8:52230082 14 6.85 1.606 15:952339 15 12.56 1.362 16:45237289 16 362.16 1.898 [1] 4.031689 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_sqrt_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.12 chr pos lod 1:75264338 1 246.2 1.302 2:9834455 2 89.0 0.830 3:23009306 3 181.1 0.764 1:66045356 4 37.7 0.901 4:66400127 5 254.6 1.873 15:13186532 6 38.6 0.919 7:16482696 7 27.5 1.602 16:15698827 8 60.3 1.293 1:80251910 9 342.5 0.825 13:37130721 10 169.1 13.319 11:44218681 11 184.3 0.691 12:12548239 12 232.0 5.193 5:43079211 13 368.9 1.936 4:37985409 14 22.2 1.115 15:4065533 15 80.6 8.905 3:16346453 16 262.2 6.548 [1] 4.115378 chr pos lod 13:37130721 10 169.1 13.32 12:12548239 12 232.0 5.19 15:4065533 15 80.6 8.91 3:16346453 16 262.2 6.55 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 257.1711 32.14639 30.84559 24.6455 0 0 Error 493 786.3102 1.59495 Total 501 1043.4813 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@169.1 2 88.23 11.593 8.456 27.661 0 4.12e-12 *** 12@236.8 2 31.89 4.334 3.056 9.998 0 5.54e-05 *** 15@80.6 2 56.08 7.510 5.374 17.580 0 4.22e-08 *** 16@267.4 2 33.77 4.584 3.237 10.588 0 3.15e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 9.38410 0.05693 164.828 10@169.1a -0.62493 0.09150 -6.830 10@169.1d 0.33146 0.12617 2.627 12@236.8a -0.35302 0.08795 -4.014 12@236.8d -0.23332 0.12454 -1.874 15@80.6a -0.36010 0.08876 -4.057 15@80.6d 0.57398 0.12623 4.547 16@267.4a -0.38670 0.08417 -4.595 16@267.4d 0.05091 0.12613 0.404 chr pos lod 2:10018142 10 164.7815 8.807396 13:37130721 10 169.0766 11.593203 11:20297183 10 173.3347 10.372133 chr pos lod 1:1617682 12 225.2268 3.202079 12:12537031 12 236.8235 4.333933 8:8029939 12 351.8307 3.065620 chr pos lod 10:623262 15 0.00000 5.573708 15:4065533 15 80.60422 7.509708 15:11700211 15 110.28246 5.537370 chr pos lod 1:11525457 16 257.8200 2.701382 12:47751016 16 267.4168 4.584483 4:4586140 16 283.4219 3.085170 [1] "###############################################################################################" [1] "GFL_sqrt_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.99 chr pos lod 9:58652168 1 347.9 1.162 2:17139447 2 285.1 0.896 11:22351227 3 82.7 0.755 8:45726224 4 97.5 0.890 4:66400127 5 254.6 1.751 15:13186532 6 38.6 1.040 7:16482696 7 27.5 1.767 16:15698827 8 60.3 1.350 1:80251910 9 342.5 0.709 13:37130721 10 169.1 13.756 3:66820321 11 265.9 0.681 12:12548239 12 232.0 5.147 2:3094010 13 238.5 2.018 4:37985409 14 22.2 1.081 15:4065533 15 80.6 8.968 3:16346453 16 262.2 6.542 [1] 3.990096 chr pos lod 13:37130721 10 169.1 13.76 12:12548239 12 232.0 5.15 15:4065533 15 80.6 8.97 3:16346453 16 262.2 6.54 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 198.8032 24.850403 31.35609 24.99757 0 0 Error 493 596.4870 1.209913 Total 501 795.2902 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@169.1 2 69.96 12.089 8.797 28.91 0 1.34e-12 *** 12@236.8 2 23.52 4.216 2.958 9.72 0 7.24e-05 *** 15@80.6 2 43.26 7.632 5.439 17.88 0 3.20e-08 *** 16@267.4 2 26.07 4.663 3.278 10.77 0 2.63e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 9.45738 0.04959 190.725 10@169.1a -0.56048 0.07969 -7.033 10@169.1d 0.28177 0.10989 2.564 12@236.8a -0.30256 0.07660 -3.950 12@236.8d -0.20213 0.10847 -1.864 15@80.6a -0.31525 0.07730 -4.078 15@80.6d 0.50537 0.10995 4.596 16@267.4a -0.34026 0.07331 -4.642 16@267.4d 0.02049 0.10985 0.187 chr pos lod 2:10018142 10 164.7815 9.27787 13:37130721 10 169.0766 12.08924 11:20297183 10 173.3347 10.76896 chr pos lod 1:1617682 12 225.2268 3.058288 12:12537031 12 236.8235 4.215834 8:37992066 12 347.6905 3.187664 chr pos lod 10:623262 15 0.00000 5.242193 15:4065533 15 80.60422 7.631599 1:40459361 15 85.43222 6.208890 chr pos lod 1:11525457 16 257.8200 2.694180 12:47751016 16 267.4168 4.662845 4:4586140 16 283.4219 3.083514 [1] "###############################################################################################" [1] "GFL_sqrt_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.04 chr pos lod 5:1929280 1 294.8 2.177 1:45939251 2 236.5 1.805 3:28566249 3 173.3 1.306 1:66045356 4 37.7 1.090 5:22669524 5 349.6 2.022 14:29215898 6 19.5 0.761 7:15935889 7 28.8 1.119 3:1453631 8 341.5 1.546 1:12699190 9 201.0 0.979 2:46629904 10 168.0 8.620 11:40793705 11 151.7 0.985 12:12548239 12 232.0 5.189 3:6004309 13 255.1 3.240 3:26748571 14 0.0 1.062 7:28140741 15 49.8 17.821 3:16346453 16 262.2 7.618 [1] 4.035731 chr pos lod 2:46629904 10 168.0 8.62 12:12548239 12 232.0 5.19 7:28140741 15 49.8 17.82 3:16346453 16 262.2 7.62 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 1263.959 157.994814 39.87485 30.63569 0 0 Error 493 2861.812 5.804893 Total 501 4125.771 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@168.0 2 238.2 8.715 5.773 20.52 0 2.76e-09 *** 12@333.4 2 188.5 6.954 4.569 16.24 0 1.48e-07 *** 15@49.8 2 557.5 19.403 13.513 48.02 0 < 2e-16 *** 16@262.2 2 167.6 6.202 4.061 14.43 0 8.11e-07 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 11.74166 0.10879 107.927 10@168.0a -1.10738 0.17390 -6.368 10@168.0d 0.10702 0.24090 0.444 12@333.4a -0.92776 0.16300 -5.692 12@333.4d 0.06835 0.24306 0.281 15@49.8a -1.54082 0.16733 -9.208 15@49.8d 0.96349 0.24656 3.908 16@262.2a -0.85626 0.16185 -5.290 16@262.2d 0.25456 0.23926 1.064 chr pos lod 2:10018142 10 164.7815 6.025716 2:46629904 10 167.9995 8.714967 10:31584236 10 176.7865 7.587646 chr pos lod 4:43604136 12 329.6277 5.814575 8:58495823 12 333.4273 6.954357 8:8029939 12 351.8307 5.752639 chr pos lod 10:623262 15 0.00000 15.52417 7:28140741 15 49.84107 19.40254 15:4223921 15 58.08093 15.26291 chr pos lod 1:11525457 16 257.8200 4.740555 3:16346453 16 262.1557 6.202275 3:9557110 16 272.4681 5.168114 [1] "###############################################################################################" [1] "GFL_sqrt_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.01 chr pos lod 5:1929280 1 294.8 2.111 1:45939251 2 236.5 1.807 11:23714171 3 125.5 1.352 1:66045356 4 37.7 0.966 5:22669524 5 349.6 1.917 14:29215898 6 19.5 0.773 7:15935889 7 28.8 1.220 3:1453631 8 341.5 1.466 1:43627844 9 197.3 1.050 2:46629904 10 168.0 9.276 11:40793705 11 151.7 0.603 12:12548239 12 232.0 5.364 3:6004309 13 255.1 3.252 3:26748571 14 0.0 1.293 15:3540634 15 51.1 17.912 3:16346453 16 262.2 7.333 [1] 4.008138 chr pos lod 2:46629904 10 168.0 9.28 12:12548239 12 232.0 5.36 15:3540634 15 51.1 17.91 3:16346453 16 262.2 7.33 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 975.1133 121.889167 40.40628 30.97303 0 0 Error 493 2173.1522 4.408017 Total 501 3148.2655 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@168.0 2 200.0 9.596 6.352 22.68 0 3.77e-10 *** 12@333.4 2 141.6 6.882 4.498 16.06 0 1.74e-07 *** 15@49.8 2 427.5 19.578 13.580 48.50 0 < 2e-16 *** 16@262.2 2 121.8 5.947 3.870 13.82 0 1.45e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 11.80736 0.09480 124.546 10@168.0a -1.01770 0.15154 -6.716 10@168.0d 0.05245 0.20992 0.250 12@333.4a -0.80335 0.14204 -5.656 12@333.4d 0.07898 0.21181 0.373 15@49.8a -1.34687 0.14582 -9.237 15@49.8d 0.85322 0.21485 3.971 16@262.2a -0.73018 0.14104 -5.177 16@262.2d 0.21708 0.20850 1.041 chr pos lod 2:10018142 10 164.7815 6.725147 2:46629904 10 167.9995 9.595733 2:37602534 10 176.3774 8.587201 chr pos lod 4:43604136 12 329.6277 5.649525 8:58495823 12 333.4273 6.882012 8:8029939 12 351.8307 5.540886 chr pos lod 15:1635552 15 46.88030 17.22741 7:28140741 15 49.84107 19.57778 5:43755021 15 80.39419 18.35449 chr pos lod 1:11525457 16 257.8200 4.554786 3:16346453 16 262.1557 5.946634 8:48795474 16 273.0617 4.746276 [1] "###############################################################################################" [1] "GFL_PC1_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.12 chr pos lod 1:50310321 1 321.3 1.642 6:19610156 2 236.5 1.429 3:28566249 3 173.3 1.096 1:66045356 4 37.7 0.766 4:39433340 5 261.8 2.011 14:29215898 6 19.5 1.000 7:16482696 7 27.5 1.459 16:15679358 8 57.8 1.297 1:80251910 9 342.5 0.844 2:46629904 10 168.0 11.055 11:63173585 11 267.0 0.777 12:12548239 12 232.0 5.798 3:6004309 13 255.1 2.682 3:26748571 14 0.0 1.317 4:36755013 15 79.7 11.167 3:16346453 16 262.2 7.413 [1] 4.116148 chr pos lod 2:46629904 10 168.0 11.06 12:12548239 12 232.0 5.80 4:36755013 15 79.7 11.17 3:16346453 16 262.2 7.41 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 520.143 65.017876 33.15727 26.22668 0 0 Error 493 1463.116 2.967781 Total 501 1983.259 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@168.0 2 140.51 9.996 7.085 23.67 0 1.53e-10 *** 12@333.4 2 81.55 5.912 4.112 13.74 0 1.56e-06 *** 15@80.6 2 162.40 11.474 8.189 27.36 0 5.39e-12 *** 16@267.4 2 76.83 5.579 3.874 12.94 0 3.32e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept -0.0008179 0.0777399 -0.011 10@168.0a -0.8367963 0.1246570 -6.713 10@168.0d 0.2157228 0.1719133 1.255 12@333.4a -0.6119457 0.1167600 -5.241 12@333.4d -0.0157594 0.1740108 -0.091 15@80.6a -0.6786111 0.1209364 -5.611 15@80.6d 0.8821298 0.1732533 5.092 16@267.4a -0.5805498 0.1146618 -5.063 16@267.4d 0.1128554 0.1718821 0.657 chr pos lod 2:10018142 10 164.7815 7.452333 2:46629904 10 167.9995 9.995667 2:37602534 10 176.3774 8.426529 chr pos lod 12:13739640 12 236.1540 4.668642 8:58495823 12 333.4273 5.912167 8:37992066 12 347.6905 4.657251 chr pos lod 10:623262 15 0.00000 8.168713 15:4065533 15 80.60422 11.473982 1:40459361 15 85.43222 9.719682 chr pos lod 1:11525457 16 257.8200 3.985973 12:47751016 16 267.4168 5.579111 4:4586140 16 283.4219 4.496807 [1] "###############################################################################################" [1] "GFL_PC2_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.02 chr pos lod 1:75727209 1 248.9 2.022 2:39532686 2 273.7 0.779 9:11862600 3 44.8 0.974 10:23633888 4 45.0 0.692 1:70796418 5 194.3 1.112 4:10883143 6 67.0 0.703 7:52684392 7 103.1 0.967 8:32562407 8 116.5 1.268 1:78198341 9 264.3 0.921 11:43192432 10 214.1 1.071 8:47870541 11 190.9 0.961 16:28465828 12 452.1 0.987 13:28411786 13 223.1 2.130 11:13221618 14 54.9 0.901 10:623262 15 0.0 2.525 16:45237289 16 362.2 1.295 [1] 4.020837 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_PC3_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.07 chr pos lod 2:50973146 1 307.6 3.057 2:6785840 2 49.9 0.884 6:3850109 3 52.4 1.600 4:35446116 4 15.5 0.817 13:23208510 5 295.6 1.550 1:41442793 6 90.3 0.783 7:38150109 7 69.4 2.253 9:29002295 8 269.3 1.987 1:92735986 9 359.2 1.160 2:26517709 10 119.4 1.706 11:40901234 11 145.8 2.215 4:77433624 12 482.8 1.748 12:22927756 13 286.9 0.764 11:13221618 14 54.9 3.151 15:1635552 15 46.9 7.794 7:34222220 16 190.3 1.953 [1] 4.067142 chr pos lod 15:1635552 15 46.9 7.79 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 502 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 37.37224 18.686120 7.793828 6.900169 1.607579e-08 1.789571e-08 Error 499 504.24117 1.010503 Total 501 541.61341 Estimated effects: ----------------- est SE t Intercept -0.0122439 0.0450277 -0.272 15@46.9a -0.4131740 0.0680155 -6.075 15@46.9d 0.0002676 0.1015776 0.003 chr pos lod 1:87502908 15 37.45411 6.244219 15:1635552 15 46.88030 7.793828 15:4148540 15 72.19039 5.884609