Analysis For Genetic Basis Of Rapeseed Flowering Time In Multiple RIL Populations

Rapeseed is one of the most important oil crops in the world. It is not only an important source of edible vegetable oil and industrial raw materials, but also an important raw material for biodiesel. Mature time is one of the important factors must be considered in rapeseed breeding, flowering time is an important indicator for rapeseed to decide whether mature time is sooner or later, appropriate flowering time is of great significance to improve the yield. Meanwhile, Prematurity is an important goal of rapeseed breeding, especially for the agricultural development of the south double-cropping rice planting area of China. So the study for flowering time of rapeseed is of great importance. Flowering is a trait controlled by polygenic, regulated by multiple physiological biochemical pathways, and under the influence of illumination and temperature, and other environmental factors. Up to now, the understanding of molecular mechanisms controlling rapeseed flowering is poor.By the hybridization of the common male parent to 15 varieties of rapeseed（Brassica napus L.） with wide diversity, and selfing for five generations, 15 RIL populations were built, forming a NAM population composed of 2139 lines. In our study, the flowering time of NAM population in four environments were investigated. And QTL mapping and epistatic analysis for flowering time were conducted. Thus the genetic basis of rapeseed flowering time was analysised preliminary. The main research results are as follows:1. By reduced representation sequencing, 30213 SNPs were identified in NAM population. The marker loci distance on average of each RIL is between 0.80 cM and 1.80 cM. And map total length of each RIL is between 1565 cM to 2446 cM.2. The flowering time difference for parents of RIL2- RIL5, RIL8 and RIL11 was significant, with a gap more than 7 days. Flowering time of 15 RIL population all exist transgressive segregation phenomenon. The flowering time of four populations（RIL3-RIL5 and RIL9） had a larger variance（variation coefficient is greater than 8% at least in two environments）. Two-factor variance analysis results showed that the flowering time of 15 RIL population were all influenced by genotype, and achieving a significant level. The influence of environment to flowering time was on a extremely significant level in 14 RIL populations, except for RIL9. The heritability of 15 RIL was between 71% and 95%.3. QTL mapping was conducted for flowering time of each RIL population in each environment respectively. For a comprehensive understanding of the regulation network of flowering time, two types of QTL were collected: first type was called SL-QTL（significant level QTL） whose LOD value achieving threshold; second type was called MR-QTL（Micro-real QTL） whose LOD value is less than the threshold value, but greater than 2.5, and detected in at least two environments. 188 SL-QTL and 25 MR-QTL were detected for 15 RIL in four environments. They were collectively known as identified-QTL. Integrating the identified-QTL in each RIL detected in different environment with overlapping interval, resulting in 56 QTLs called consensus QTL. In addition, there were 65 QTL detected in only one environment called environment specific QTL. In the end, 121 QTL（56 consistency QTL and 65 environment specific QTL） were detected in 15 RIL population, the contribution rate of individual QTL were between 5% and 32%. These 121 QTL were distributed on 18 linkage groups other than C6. The number of QTL detected on linkage groups A2, A3, A6, A10, C2 and C8 were 10 or more than 10. They were 18, 10, 13, 16, 13 and 16, respectively. QTL detected in different RIL population were overlapped, forming 22 QTL clusters which involved 71 QTL.4. No epistatic interactions were detected in RIL3. 33 epistatic interactions were detected in the rest 14 RIL population, involving 58 interacting loci, including seven loci interacted with two or three interacting loci. In total, 4 QTL/QTL interacting pairs, 7 QTL/non-QTL interacting pairs, 22 non-QTL/non-QTL interacting pairs were detected. 12 interacting pairs within A genome, 3 interacting pairs within C genome and 18 interacting pairs between A and C genome were detected. Interacting loci RIL9₃-22, RIL8₁0-99 and RIL13₁7-51 were the same loci as RIL1₃-40, RIL9₁0-73 and RIL15₁7-37, respectively. These three sites were detected in two populations at the same time. These loci regulated flowering time by interacting with different loci in different genetic background.QTL and epistasis analysis results showed that the flowering time of Brassica napus was regulated by a complex network, the regulation network involves a lot of QTL loci and interaction loci. Some QTL not only influenced flowering time alone, but also participated in the regulation of flowering time in the way of epistatic interactions.