Linkage Map Construction And Identification Of QTL For Oil Content And Related Quality Traits In Brassica Napus

The rapeseed is the third biggest source of vegetable oil, and the fifth largest crop after paddy rice, wheat, maize and soybean in China. Low-erucic rapeseed oil is not only nutritional edible oil for human, but also the ideal raw material of biodiesel. To enlarge rape production and increase rapeseed benefit is of the most importance for the elevation of health and resolution of energy shortage problems which is restricting the economic growth in our country.Increase of oil content in rapeseed varieties in an important approach for the elevation of rapeseed production benefit. During the past five years, the number of rapeseed varieties with high oil content had increased. But quite a number of vanities still had low oil content. Thus, the elevation of oil content has become a major objective of rapeseed breeding. Meanwhile, the protein of double low rapeseed is suitable for animal feeding, containing abundant nutrition with reasonable amimo acid composition. High glucosinolate content in feed is harmful to animal. Oleic acid belongs to monounsaturated fatty acid, and is beneficial to cardiovascular health. Besides, oil with high oleic acid content can be easily transesterifitied, so it is an ideal source of biodiesel. Therefore, study on quality triats such as oil, protein, glucosinolate and oleic acid contents is of significant importance for rapeseed breeding.The materials used in this study are two F₂ populations derived from the reciprocal crosses of 8908BxRl. Oil, protein, glucosinolate and oleic acid contents are analysed. Based on 118 F₂ plants, a genetic linkage map is constructed and the OTL of oil, protein, glucosinolate and oleic acid content are identified. The main resultss are as following:1. In F₂ population, the protein content ranged from 24.56% to 34.73%. The range of oil content is bigger, which was between 26.72% and 44.31%. The oil content of 58.97% individual in this population exceeded the averagel value. The change of glucosinolate content was also obvious, the range reached 27.71umol/g, with most individuals contained glucosinolate between 13.69umol/g and 21.69umol/g.2. In F₂ population of the reciprocal cross, the oil content of individuals comcentrated between 37.94% and 42.44%, with an average of 38.84%. The range of protein content is between 25.08% and 34.94%. The variation of glucosinolate content is also obvious, with a minimum value of 1.56umol/g, and maximum value of 22.81umol/g. The value of oleic acid content was between 53.18% and 65.87%, with 46.15% individuals above the mean.3. In the two populations, the coefficient of correlation between oil content and protein content was negative, meaning with the increase of protein content, the oil content decrease significantly. In F₂ population of reciprocal cross, the coefficient of correlation between protein content and glucosinolate content was—0.45, which was significant at 0.01 level. The coefficient of correlation between protein content and oleic acid content was—0.18, which was significant at 0.05 level. The correlativity between glucosinolate content and oleic acid content was positive, the coefficient of correlation is 0.30 and the correlativity is significant at 0.01 level.4. Based on 118 F₂ plants, a genetic linkage map of Brassica napus L. was constructed, which was made up of 21 linkage groups, including 121 markers, covering 1298.7cM in total with an average interval of 12.99cM between adjacent loci. As for the different linkage groups, the length varied from LG21 of 11.0 cM to LG14 of 165.5 cM, the average marker interval distance varied from 5.50 cM (LG21) to 25.70cM CLG19) . The number of marker in LG4 and LG14 is 11, but LG21 has only 2 markers.5. Using this map, three mapping methods were employed in QTL analysis of oil content. A total of three QTLs affecting oil content were detected in two linkage groups including LG10 and LG20 with the single marker mapping; four QTLs located on LG8, LG10, LG11 and LG20 contributed to phenotypic variance ranged from 1.9% to 25.4% were found by the analysis of the interval mapping; two QTLs were were detected via the composite interval mapping, locating on LG8 and LG10. The LOD score were 3.2 and 4.6. The phenotypic variation explained by single component was 4.8% and 13.7%, respectively.6. Eight QTLs were responsible for protein content detected by means of the single marker mapping, amongist five QTLs were located on LGl, two QTLs in LG3 and one QTL in LG18. Making use of the interval mapping, two QTLs were mapped. One locating on LG1 with positive additive effect was aquired which accounted for 15.2% of the phenotypic variation.The other locating on LG3 showed negative additive effect which accounted for 14.1% of the phenotypic variation. No QTL was found by the composite interval mapping.7. For glucosinolate content, only one QTL locating on LG20 was obtained by the single marker mapping. Using the interval mapping, two OTLs on LG20 were mapped with positive additive effect, explaining 12.2% and 10.8% of the phenotypic variation, respectively. With the composite interval mapping, four QTLs were detected, locating on LG4, LG8 and LG20, and the single contribution to phenotypic variance ranged from 1.9% to 25.4%. Three loci showed positive additive effect, but the other one showed negative additive effect.