| Oilseed is Brassica of Cruclferae, is one of main oil crops in the world and holds an important status in the oil crops. In our country, it is the most important of the five oil crops (oilseed, soybean, peanut, gingili, and sunflower), the largest planting area and the most products. It is an important source to the vegetable oil and meal protein and industry material. Brassica include three elementary species (Brassica campestris, AA 2n=20; Brassica oleracea CC, 2n=18 and Brassica nigra, BB, 2n=16) and three aggregate species (Brassica napus, AACC, 2n=38; Brassica. Juncea, AABB, 2n=34 and Brassica carinata, BBCC, 2n=36). The researchers have focused on yellow seed coat of B. napus since Liu firstly found in recombination between B. napus and B.rapa in 1975. Yellow seed of B. napus is an excellent fodder material with lower hull proportion and fibrin content, higher protein content in meal and less polyphenol than brown or black one. In the same genetic, yellow seed has higher 3.0-5.0% oil content and more transparent oil and lower producing cost than brown or black one. However, it is very slow advance, very low efficiency and very difficult improvement to the selection breeding of B. napus. Recent advances in DNA markers offer plant breeders a rapid and precise alternative approach to conventional selection schemes to improve quantitative traits.In the present study, the high-density genetic linkage maps have been constructed using SSR marker, RAPD markers, SRAP marker, TRAP marker and AFLP marker to RIL-1 population (GH06×Youyan 2) and RIL-2 population (GH 06×Zhongyou 821). WinQTL 2.5 has detected QTLs of quality about two populations in three environments (in Beibei in 2005 and in both Beibei and Wanzhou in 2006) with LOD value 2.0. The major QTL potential regions of the seed coat color have been primarily located. The mainly results were as following:DNA polymorphism among three parentsRIL-1: The 64 AFLP primer combinations yielded 4035 bands between Youyan 2 and GH 06 with 63 bands each primer. Among of the bands yielded 170 polymorphic bands with an average 2.66 polymorphic bands (between 1 and 12) informative AFLP per primer combination. 153 polymorphism primer pairs found among 777 SSR primer pairs and yielded 181 polymorphic bands with an average 1.15 polymorphic bands per primer. 121 SRAP primer combinations yielded 267 polymorphic bands with an average 2.21 polymorphic bands per primer combination. 6 TRAP primer combinations yielded 9 polymorphic bands with an average 1.83 polymorphic bands per primer combination.RIL-2: 152 polymorphism primer pairs found among 777 SSR primer pairs and yielded 172 polymorphic bands with an average 1.15 polymorphic bands per primer. 260 primer combinations yielded 466 polymorphic bands with an average 1.79 polymorphic bands per primer combination. 68 polymorphic primers yielded 106 polymorphic bands with an average 1.56 polymorphic bands per primer.Construction of the genetic linkage mapRIL-1: 621 polymorphic loci, including 261 SRAP markers, 181 SSR markers and 9 TRAP markers, were employed to perform linkage analysis using the RIL-1 population of B. napus. 502 markers (220 SRAP markers, 155 SSR markers, 123 AFLP markers and 9 TRAP markers) were mapped to 27 linkage groups ranging from 11 to 121 cM with an average length of 62.89 cM containing 3 to 90 markers in each linkage group. The map covered a total of 1698 cM with a coverage percentage of about 67.92% (Lombard and Delourme, 2001), and the average distance between two adjacent markers was 3.38 cM.RIL-2: 745 polymorphic loci, including 466 SRAP markers, 172 SSR markers, 106 RAPD markers and 2 morphological loci were employed to perform linkage analysis using the RIL-2 population of B. napus. 570 markers (365 SRAP markers, 134 SSR markers and 71 RAPD markers) were mapped to 27 linkage groups ranging from 27 to 163 cM with an average length of 74.48 cM containing 3 to 92 markers in each linkage group. The map covered a total of 2119 cM with a coverage percentage of about 84.76% (Lombard and Delourme, 2001), and the average distance between two adjacent markers was 3.72 cM.Analysis of traits of mapping parents and linesThree parents of two populations are broadly plant in China. GH 06 has a complete dominant main gene of yellow seed coat with 90 % degree of yellow seed and the trait of yellow seed shows very steady. Zhongyou 821 and Youyan 2 are two black-seeded parents by self-inbreded.Two populations were plant in different three environments (in Beibei in 2005 and in Beibei and Wanzhou in 2006). The traits had different phenotype in different environments. The phenotype of the traits showed the normal distribution and could be used to analysis of QTL. The variance analysis of the trait indicated that the some qualities of B. napus interacted between gene and environment, and other qualities had not significant interaction effect between gene and environment. Analysis of QTL effects based on interval mappingRIL-1: In Beibei in 2005, 4 QTLs of effecting lignin content were identified by interval mapping (IM) with one QTL explaining 5.51-10.18% of the lignin content variance and 7 QTLs of effecting single-plant weight were detected with explaining 5.21-8.23% of single-plant weight variation. 40 QTLs of effecting oil content were detected by IM with explaining 5.39-15.66% of oil content variance in different environments (in Beibei in 2005 and in both Beibei and Wanzhou in 2006). 28 QTLs of effecting protein content were detected with one QTL explaining 5.1-25.76% of protein content variance. 23 QTLs of effecting hull proportion were detected with one QTL explaining 5.26-11.59% of hull proportion variance. 14 QTLs of effecting kilo-seeds weight were detected with one QTL explaining 5.36-11.45% of kilo-seeds weight variance. 12 QTLs of effecting seed coat color were detected with one QTL explaining 5.39-59.61% of seed coat color variance. 6 QTLs of effecting anthocyanidin content were detected in both Beibei and Wanzhou in 2006 with one QTL explaining 5.39-59.61% of anthocyanidin content variance. 6 QTLs of effecting total phenol content were detected with one QTL explaining 5.65-13.03% of total phenol content variance. 6 QTLs of effecting melanin content were detected with one QTL explaining 5.46-10.47% of melanin content variance.RIL-2: In Beibei in 2005, 6 QTLs of efffecting lignin content were detected by IM with one QTL explaining 5.96-8.79% of lignin content variance and 9 QTLS of effecting single-plant weight were detected with explaining 5.03-10.59% of single-plant weight variance. 34 QTLs of effecting oil content were detected by IM with explaining 5.27-11.69% of oil content variance in different environments (in Beibei in 2005 and in both Beibei and Wanzhou in 2006). 25 QTLs of effecting protein content were detected with one QTL explaining 5.19-10.4% of protein content variance. 18 QTLs of effecting hull proportion were detected with one QTL explaining 5.65-26.55% of hull proportion variance. 14 QTLs of effecting kilo-seeds weight were detected with one QTL explaining 5.08-11.51% of kilo-seeds weight variance. 27 QTLs of effecting seed coat color were detected with one QTL explaining 5.39-80.63% of seed coat color variance. 2 QTLs of effecting anthocyanidin content were detected by IM in both Beibei and Wanzhou in 2006 with one QTL explaining 10.54 percent and 9.86% of anthocyanidin content variance. 10 QTLs of effecting total phenol content were detected with one QTL explaining 7.24-25.80% of total phenol content variance. 14 QTLs of effecting flavonoid content were detected with one QTL explaining 6.03-28.92% of flavonoid content variance. 13 QTLs of effecting melanin content were detected with one QTL explaining 5.98-36.84% of melanin content variance.Analysis of QTL effects based on composite interval mappingRIL-1: In Beibei in 2005, 6 QTLs of effecting lignin content were detected by composite intrval mapping (CIM) with one QTL explaining 4.12-11.77% of variance and 13 QTLS of effecting single-plant weight were detected with explaining 3.88-12.44% of single-plant weight variance. 38 QTLs of effecting oil content were detected by CIM with explaining 2.92-12.93% of oil content variance in different environments (in Beibei in 2005 and in both Beibei and Wanzhou in 2006). 18 QTLs of effecting protein content were detected with one QTL explaining 3.93-25.31% of protein content variance. 22 QTLs of effecting hull proportion were detected with one QTL explaining 3.83-13% of hull proportion variance. 16 QTLs of effecting kilo-seeds weight were detected with one QTL explaining 4.69-11.64% of kilo-seeds weight variance. 17 QTLs of effecting seed coat color were detected with one QTL explaining 4.01-13.43% of seed coat color variance. 7 QTLs of efecting anthocyanidin content were detected by CIM in both Beibei and Wanzhou in 2006 with one QTL explaining 4.36-57.8% of anthocyanidin content variance. 7 QTLs of flavonoid content were detected by CIM with one QTL explaining 7.13-62.35% of flavonoid content variance. 11 QTLs of effecting total phenol content were detected with one QTL explaining 5.07-12.64% of total phenol content variance. 11 QTLs of effecting melanin content were detected with one QTL explaining 5.26-16.91% of melanin content variance.RIL-2: In Beibei in 2005, 7 QTLs of effecting lignin content were detected by CIM with one QTL explaining 4.71-7.64% of lignin content variance and 4 QTLS of effecting single-plant weight were detected with explaining 4.65-6.42% of single-plant weight variance. 14 QTLs of effecting oil content were detected by CIM with explaining 4.47-12.21% of oil content variance in different environments (in Beibei in 2005 and in both Beibei and Wanzhou in 2006). 13 QTLs of effecting protein content were detected with one QTL explaining 4.01-9.40% of protein content variance. 16 QTLs of effecting hull proportion were detected with one QTL explaining 3.36-11.86% of hull proportion variance. 15 QTLs of effecting kilo-seeds weight were detected with one QTL explaining 4.03-11.03% of kilo-seeds weight variance. 28 QTLs of effecting seed coat color were detected with one QTL explaining 2.46-24.52% of seed coat color variance. 4 QTLs of effecting anthocyanidin content were detected by IM in both Beibei and Wanzhou in 2006 with one QTL explaining 5.25-9.94% of anthocyanidin content variance. 12 QTLs of effecting total phenol content were detected with one QTL explaining 3.72-16.23% of total phenol content variance. 7 QTLs of effecting flavonoid content were detected with one QTL explaining 3.38-14.31% of flavonoid content variance. 12 QTLs of effecting melanin content were detected with one QTL explaining 3.72-16.23% of melanin content variance.Comparing to QTL effect in different environmentsBased on IM: The most QTLs of RIL-1 and RIL2 in three different environments (in Beibei in 2005 and in Beibei and Wanzhou in 2006) could not be repeatedly identified in three environments. Some QTLs could be repeatedly detected in near region of the same linkage group in three environments, which were 12 QTLs (8.28% of all QTLs) of RIL-1 and 35 QTLs (18.13%) of RIL-2.Based on CIM: The QTLs of RIL-1 and RIL2 that were identified in three different environments were repeated in these environments could be repeatedly detected in near region of the same linkage group in three environments, which were 14 QTLs (8.43% of all QTLs) of RIL-1 and 21 QTLs (15.22%) of RIL-2.Comparing to QTL effect in different mapping methods145 quality QTLs of RIL-1 were identified by IM and 166 QTLs were identified by CIM, the QTL numbers by CIM were more 21 than the numbers by IM. 193 quality QTLs of RIL-2 were identified by IM and 138 QTLs were identified by CIM, the QTL number by IM were more 55 than the numbers by CIM. It is very different to between IM and CIM, but they could detect the QTL with explaining =10% of phenotypic variance.QTL distributionThe QTLs of oil content and oil content related traits(hull proportion, kilo-seed weight and protein content) clustered in some linkage groups as well as the QTLs of seed coat color and seed coat color related to traits(anthocyanidin content, flavonoid content, total phenol content and melanin content). Such as, in the linkage groups of RIL-1 they mainly distributed in LG 12 and LG 17 and mainly distributed in LG 1 and LG18 in ones of RIL-2. Added to this, QTLs of all quality distributed both A genome and C genome.Primary location QTL of seed coat colorSeed coat color is very significant negative correlation to four kinds of pigments (anthocyanidin, flavonoid, total phenol and melanin), but four kinds of pigments is very significant positive correlation to each other.11 significant QTLs of seed coat color were identified in four linkage groups (LG 2, 9, 14 and 18) with a LOD value threshold of 2.0 by CIM in Beibei in 2005. In Wanzhou 9 significant QTLs were identified in four linkage groups (LG 2, 9, 18 and 22) in 2006 and 8 significant QTLs were identified in four linkage groups (LG 2,11,12 and 18) in Beibei in 2006. The QTL in the LG 2 and LG18 could be detected in three environments.5 significant QTLs of flavonoid content, 8 significant QTLs of total phenol content and 6 significant QTLs of melanin content were detected in Beibei in 2006 and QTL of anthocyanidin content was not detected. In Wanzhou in 2006, 4 significant QTLs of anthocyanidin content, 2 significant QTLs of flavonoid content, 4 significant QTLs of total phenol content and 4 significant QTLs of melanin content were detected.These QTLs of seed coat color and pigment that could be detected in three environments is near to some marker, such as sNRD03/120, EM40ME13/260, S455/500, EM13ME22/270, EM13ME22/270, and located 90-144 cM in the 18th linkage group. Cloned SRAP marker sequence in the region, and gained 9 sequence with length ranging from 115bp to 491, 7 sequence among of these sequences have homology with 5th chromosome of Arabidopsis thaliana. These homologous areas are scattered among the 11 transparent testa (77) genes in 5th chromosome of A. thaliana. So one gene or some genes, which are homologous with one TT gene or some TT gene, regulate and control the expression of the seed coat color gene.
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