| In this study,a single segment substitution lines(SSSLs)and their parents were used as field test materials.The panicle related traits,plant architecture and flowering time related traits under nitrogen and non-nitrogen application were evaluated.Then,QTL for different traits of maize were identified by using the interval mapping method.Detail results were listed as follows:1.A total of 123 QTLs for panicle related traits were identified.Among them,59 QTLs were identified under N + condition,13 was related with the yield;10 was related with the ear length;6 was related with the ear wide;7 was related with ear row number;8 was related with kernel number per row;9 was related with the grain weight;6 was related with the effective panicle per plant.In addition,a total of 64 QTLs were identified under the N-conditions,15 was related with the yield;9 was related with the ear length;5 was related with the ear wide;3 was related with ear row number;12 was related with kernel number per row;12 was related with the grain weight;8 was related with the effective panicle per plant.16 QTLs were repeatedly detected in 3 test environments with a detection rate of 13.01%.Comparing showed that,the common were found among three environments.Including panicle related QTL: N + condition,qYP1 f of the yield;qEL1a,qEL3 a of ear length;qED1 of ear wide;qRN1b of ear row number;qKN1a of kernel number per row;qKW2b,qKW8 b,qKW9b of 100-seed weight;qEP1c of the effective panicle per plant,with 31.73%,14.91%,13.94%,7.08%,11.34%,15.82%,12.28%,15.45%,13.1% and 18.73% contribution of phenotypic variation respectably.N-condition,qYP1 b of the yield;qEL1a,qEL3 a of ear length;qRN1 of ear row number;qKN1a,qKN3 a of kernel number per row,with 43.29%,11.18%,14.08%,9.77%,12.25% and 14.16% contribution of phenotypic variation respectably.2.A total of 68 QTLs plant architecture related traits and 13 QTLs chlorophyll content.Among them,37 QTLs were identified under N + condition,9 was with plant height;10 was with ear height;8 was with the leaf area;5 was with number of green leaves;5 was with chlorophyll.In addition,a total of 44 QTLs were identified under N-condition,9 was with plant height;11 was with high ear height;9 was with leaf area;7 was with number of green leaves;8 was with chlorophyll.15 QTLs were repeatedly detected in 3 test environments with a detection rate of 18.52%.Comparing showed that,the common were found among three environments.Including plant architecture related and chlorophyll content QTL: N + condition,qPH3 a of plant height;qEH3a,qEH3 d,qEH6 and qEH10 of high ear height;qLAI1b of leaf area;qLN7a,qLN7 b of the number of green leaves,with 10.57%,14.7%,15.84%,16.83%,16.15%,15.09%,35.73% and 34.23% contribution of phenotypic variation respectably.N-condition,qPH3 b of plant height;qEH3b,qEH3 c of high ear height;qLAI3b of leaf area;qLN7a,qLN9 of the number of green leaves;qCHL4a of chlorophyll,with 12.99%,18.99%,19.02%,15.47%,64.6%,64.18% and 13.21% contribution of phenotypic variation respectably.3.A total of 36 QTLs controlling flowering time related traits were identified.Among them,17 QTLs were identified under N + condition,6 was related with DTP,7 was related with DTS,and 4 was related with ASI.In addition,a total of 19 QTLs were identified under N-condition,7 was related with DTP,8 was related with DTS,and 4 was related with ASI.5 QTLs were repeatedly detected in 3 test environments with a detection rate of 13.89%.Comparing showed that,the common were found among three environments.Including controlling flowering time related QTL: N + condition,qDTS9 a of DTS;qASI10a of ASI,with 3.05% and 30.74% contribution of phenotypic variation respectably.N-condition,qDTP9 of DTP,qDTS9 a of DTS,qASI10 of ASI,with 3.43%,4.08% and 50.28% contribution of phenotypic variation respectably.4.Some common QTL among different enviro nments and N levels were identified,which located in Bin1.03(qEL1a and qKN1 a,flanking markers bnlg1203 ~ phi001 ~ phi095,could explain 8.12%-19.29% of ear length variation and 8.17%-22.47% of ear row number,respectively.qRN1 b with flanking markers to be phi095 ~ bnlg182 ~ umc2217 ~ bnlg2295,which can explain 5.83%-16.89% of kernel number per row);Bin3.04(qEL3a,with flanking markers to be Umc1425 ~ umc2000 ~ umc1307 ~ umc1954,which can explain 9.64%-24.41% of ear length variation);Bin3.08(qEH3d,with flanking markers to be umc1844 ~ umc1320 ~ bnlg1182,which can explain 14.99%-20.11% of ear height variation);Bin7.01(qLN7a,with flanking markers to be umc1642 ~ umc2160 ~ umc1929,which can explain 19.12%-95.5% of green leaves number under the panicle);Bin9.02(qDTS9a,with flanking markers to be umc1170 ~ umc1636 ~ bnlg1401 ~ umc1271,which can explain 2.47%-5.96% of DTS variation;)and Bin10.04(qASI10a,with flanking markers to be umc1077 ~ umc1053 ~ umc2350,which can explain 13.64%-80% of the ASI variation).These regions would contain some mainly QTL related with maize nitrogen absorbing,transporting and using.Which could be treated as some importantly candidate targets for fine mapping and nitrogen genes' clone in the future work. |
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