油菜开花期QTL定位及与粒重的遗传关联性

doi:10.3864/j.issn.0578-1752.2016.16.002

Abstract

Abstract: 【Objective】The present research aimed to explore the major QTL controlling the flowering time in European and Chinese rapeseed materials, to analyze the genetic influence of flowering time on QTL for 1000-seeds weight, and thus to provide available information for breeding purpose.【Method】The doubled haploid (DH) Sollux/Gaoyou population with 282 lines was used. The data set of flowering time was obtained from nine environments and over seven years. QTL identification of flowering time was performed using WinQTLCart 2.5. The candidate genes underlining QTLs were screened out by transcriptome analysis using RNA-Seq and alignment between QTL regions and Arabidopsis. Further, conditional QTL estimation was adopted to dissect the genetic relationships between flowering time and seed weight. Finally, using selected DH lines with extreme phenotypes of flowering time, an association evaluation between marker genotypes and phenotypes of flowering time was performed. 【Result】 Seven major QTLs were detected, which showing significant at least in three environments. Their additive effects ranged from 0.58-3.85 days and together accounted for around 84% of the phenotypic variation in population. The sum of eight pairs of epistatic loci (additive × additive) accounted for 41.8% of the total additive effects. QTL by environmental interactions were significant only in few environments with small amount of genetic effects. Four critical orthologous genes of Arabidopsis thaliana for flowering time were mapped in the peak positions of three most significant QTL regions (qFTA2, qFTC2, and qFTC6). It provides valuable information to anchor candidate genes underling QTL. The conditional QTL analysis revealed large impact of flowering time on seed weight in four QTLs (qSWA2, qSWA3, qSWA4, and qSWC2). This partly explained the significant negative correlation between flowering time and 1000-seed weight. While the most important two (qSWA7 and qSWC8) showed independent without being interfered. Six markers linked with three major QTLs showed good fitness between marker genotypes and trait phenotypes (70%-100%), indicating their potentials for breeding purpose. The results demonstrated that the combination of early flowering alleles from qFTA2, qFTC2 and qFTC6 by marker assistant selection of ZAAS548, DNAPL, ZAAS619sa, ZAAS616s, ZAAS846a and C6SGFLO-22 induced not only early flowering but also significantly increased 1000-seed weight, while the oil content and seeds per silique between two extreme flowering time groups showed almost the same.【Conclusion】All seven QTLs of flowering time showed Chinese parent Gaoyou induced early flowering. Four important candidate genes homologous to Arabidopsis controlling flowering time (FT, FLC, AP1, and FY) were physically aligned and mapped underlining the peak positions of the three major QTL qFTA2, qFTC2 and qFTC6. The results indicated that the four loci corresponding to seed weight were genetically influenced by flowering time, however, the most important two (qSWA7 and qSWC8) were independent. Six markers linked to the 3 major QTL were of potentials in the practical breeding program.

Key words: Brassica napus L., QTL mapping, flowering time, 1000-seeds weight, conditional QTL mapping

HUANG Ji-xiang, XIONG Hua-xin, PAN Bing, NI Xi-yuan, ZHANG Xiao-yu, ZHAO Jian-yi. Mapping QTL of Flowering Time and Their Genetic Relationships with Seed Weight in Brassica napus[J].Scientia Agricultura Sinica, 2016, 49(16): 3073-3083.

References

[1] Zhao J Y, Becker H C, Ding H D, Zhang Y F, Zhang D Q, Ecke W. QTL of three agronomically important traits and their interactions with environment in a European×Chinese rapeseeed population. Acta Genetica Sinica, 2005, 32(9): 969-978.

[2] 刘后利. 几种芸薹属油菜的起源和进化. 作物学报, 1984, 10(1): 9-18.

Liu H L. Origin and evolution of Brassicarape. Acta Agronomica Sinica, 1984, 10(1): 9-18. (in Chinese)

[3] Detjen L R. A preliminary report on cabbage breeding. Proceedings of the American Society for Horticultural Science, 1926, 23: 325-332.

[4] Dickson M H. Eight newly described genes in broccoli. Proceedings of the American Society for Horticultural Science, 1968, 93: 356.

[5] Teutonico R A, Osborn T C. Mapping loci controlling vernalization requirement in Brassica rapa. Theoretical and Applied Genetics, 1995, 91(8): 1279-1283.

[6] Ferreira M E, Satagopan J, Yandell B S, Williams P H, Osborn T C. Mapping loci controlling vernalization requirement and flowering time in Brassica napus. Theoretical and Applied Genetics, 1995, 90(5): 727-732.

[7] Osborn T C, Kole C, Parkin A P, Sharpe A G, Kuiper M, Lydiate D J, Trick M. Comparison of flowering time genes in Brassica rapa, B. napus and Arabidopsis thaliana. Genetics, 1997, 146(3): 1123-1129.

[8] A Linkage analysis of molecular markers and quantitative trait loci in populations of inbred backcross lines of Brassica napus L.. Genetics, 1999, 153(2): 949-964.

[9] Long Y, Shi J, Qiu D, Li R, Zhang C, Wang J, Choi S R. Flowering time quantitative trait loci analysis of oilseed Brassica in multiple environments and genome wide alignment with Arabidopsis. Genetics, 2007,177(4): 2433-2444.

[10] 蔡长春, 傅廷栋, 陈宝元, 涂金星. 甘蓝型油菜遗传图谱的构建及开花期的QTL分析. 中国油料作物学报, 2007, 29(1): 1-8.

Cai C C, Fu T D, Chen B Y, Tu J X. Construction of a genetic linkagemap and its use for QTL analysis of flowering time in Brassica napus L.. Chinese Journal of Oil Crop Science, 2007, 29(1): 1-8. (in Chinese)

[11] Xu L P, Hu K N, Zhang Z Q, Guan C Y, CHEN S, HUA W, LI J N, WEN J, YI B, SHEN J X , MA C Z, TU J X , FU T D . Genome-wide association study reveals the genetic architecture of flowering time in rapeseed (Brassica napus L.). DNA Research, 2016, 23(1): 43-52.

[12] Wei D, Mei J, Fu Y, Disi J O, Li J, Qian W. Quantitative trait loci analyses for resistance to Sclerotinia sclerotiorum and flowering time in Brassica napus. Molecular Breeding, 2014, 34(4): 1797-1804.

[13] Nelson M N, Rajasekaran R, Smith A, Chen S, Beeck C P, Siddique K H, Cowling W A. Quantitative trait loci for thermal time to flowering and photoperiod responsiveness discovered in summer annual-type Brassica napus L.. PloS One, 2014, 9(7): e102611.

[14] Wang J, Long, Y, Wu B, Liu J, Jiang C, Shi L, ZHAO J , GRAHAM J K, Meng J. The evolution of Brassica napus FLOWERING LOCUS paralogues in the context of inverted chromosomal duplication blocks. BMC Evolutionary Biology, 2009, 9(1): 271.

[15] Zou J, Raman H, Guo S, Hu D, Wei Z, Luo Z, SHI W, FU Z, DU D, Meng J. Constructing a dense genetic linkage map and mapping QTL for the traits of flower development in Brassica carinata. Theoretical and Applied Genetics, 2014, 127(7): 1593-1605.

[16] Fornara F, Montaigu A, Coupland G. SnapShot: control of flowering in Arabidopsis. Cell, 2010, 141(3): 550-550.

[17] Raman H, Raman R, Eckermann P, Coombes N, Manoli S, Zou X, Batley J. Genetic and physical mapping of flowering time loci in canola (Brassica napus L.). Theoretical and Applied Genetics, 2013, 126(1): 119-132.

[18] Hou J, Long Y, Raman H, Zou X, Wang J, Dai S, XIAO Q , LI C, FAN L , LIU B，Meng J. A Tourist-like MITE insertion in the upstream region of the BnFLC. A10 gene is associated with vernalization requirement in rapeseed (Brassica napus L.). BMC Plant Biology, 2012, 12: 238.

[19] 刘玉霞, 汪义龙, 丁瑜, 陈飞, 黄吉祥, 倪西源, 赵坚义. 油菜种子成熟度对千粒重和含油量性状的影响. 浙江农业学报, 2011, 23(3): 465-469.

Liu Y X, Wang Y L, Ding Y, Chen F, Huang J X, Ni X Y, Zhao J Y. Effects of seed maturity on seed weight and oil content in Brassica napus. Acta Agiculturae Zhejiang Gensis, 2011, 23(3): 465-469. (in Chinese)

[20] 郑本川, 张锦芳, 李浩杰, 蒲晓斌, 崔成, 柴靓, 蒋俊, 牛应泽, 蒋梁材. 甘蓝型油菜生育期天数与产量构成性状的相关分析. 中国油料作物学报, 2013, 35(3): 240-245.

Zheng B C, Zhang J F, Li H J, Pu X B, Cui C, Chai L, Jiang J, Niu Y Z, Jiang L C. Correlation between duration of growth periods and yield components of Brassica napus L.. Chinese Journal of Oil Crop Sciences, 2013, 35(3): 240-245. (in Chinese)

[21] Zhang L W, Yang G S, Liu P W, Hong D F, LI S P, He Q B. Genetic and correlation analysis of silique-traits in Brassica napus L. by quantitative trait locus mapping. Theoretical and Applied Genetics, 2011, 122(1): 21-31.

[22] Yang P, Shu C, Chen L, Xu J S, Wu J, Liu K D. Identification of a major QTL for silique length and seed weight in oilseed rape (Brassica napus L.). Theoretical and Applied Genetics, 2012, 125(2): 285-296.

[23] Fan C, Cai G, Qin, J, Li Q, Yang M, Wu J, FU T, LIU K, Zhou Y. Mapping of quantitative trait loci and development of allele-specific markers for seed weight in Brassica napus. Theoretical and Applied Genetics, 2010, 121(7): 1289-1301.

[24] Li N, Shi J, Wang X, Liu G, Wang H. A combined linkage and regional association mapping validation and fine mapping of two major pleiotropic QTLs for seed weight and silique length in rapeseed (Brassica napus L.). BMC Pant Biology, 2014, 14(1): 1-14.

[25] Liu J, Hua W, Hu Z, Yang H, Zhang L, Li R, DENG L , SUN X, WANG X，Wang H. Natural variation in ARF18 gene simultaneously affects seed weight and silique length in polyploid rapeseed. Proceedings of the National Academy of Sciences of the USA,2015, 112(37): E5123-E5132.

[26] Zhao J Y, Huang J X, Chen F, Xu F, Ni X, Xu H, WANG Y, JIANG C, WANG H, XU A, Huang R, LI D, MENG J. Molecular mapping of Arabidopsis thaliana lipid-related orthologous genes in Brassica napus. Theoretical and Applied Genetics, 2012, 124(2): 407-421.

[27] Zhu J. Analysis of conditional genetic effects and variance components in developmental genetics. Genetics, 1995, 141(4): 1633-1639.

[28] Wang S C, Bastern J, Zeng Z B. Window QTL Cartographer 2.5. Raleigh, NC: Department of Statistics, North Carolina State University, 2007, http://Statgen.ncsu.edu/ qtlcart/ WQTLCart. htm.

[29] Yang J, Zhu J, Williams R W. Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics, 2007, 23(12): 1527-1536.

[30] Wang D L, Zhu J, Li K L, PATERSON A H. Mapping QTLs with epistatic effects and QTL× environmrnt interactions by mixed linear model approaches. Theoretical and Applied Genetics, 1999, 99(7/8): 1255-1264.

[31] Chalhoub B, Denoeud F, Liu S, Parkin I A, Tang H, Wang X, Corréa M. Early allopolyploid evolution in the post- Neolithic Brassica napus oilseed genome. Science, 2014, 345(6199): 950-953.

[32] Koornneef M, Vries H, Hanhart C, Soppe W, Peeters T. The phenotype of some late-flowering mutants is enhanced by a locus on chromosome 5 that is not effective in the Landsberg erecta wild-type. The Plant Journal, 1994, 6(6): 911-919.

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Mapping QTL of Flowering Time and Their Genetic Relationships with Seed Weight in Brassica napus

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