- 无标题文档
查看论文信息

中文题名:

 (新疆稻麦子×扬麦158)CSSL群体的SNP分型及控制穗部、籽粒性状相关QTL/基因的精细定位    

姓名:

 刘志鹏    

学号:

 2017101117    

保密级别:

 秘密    

论文语种:

 chi    

学科代码:

 090102    

学科名称:

 农学 - 作物学 - 作物遗传育种    

学生类型:

 硕士    

学位:

 农学硕士    

学校:

 南京农业大学    

院系:

 农学院    

专业:

 作物遗传育种    

研究方向:

 分子细胞遗传学    

第一导师姓名:

 王海燕    

第一导师单位:

 南京农业大学    

完成日期:

 2020-05-01    

答辩日期:

 2020-06-08    

外文题名:

 Analyzing the genotyping of CSSL population of (T. petropavlovskyi×Yangmai 158) and fine mapping of QTLs/ genes controlling spike- and grain-related traits of T. petropavlovskyi    

中文关键词:

 新疆稻麦子 ; 小麦55K SNP芯片 ; 长穗 ; 长颖 ; QTL定位    

外文关键词:

 Triticum petropavlovskyi Udacz. et Migusch. ; Axiom ; Wheat 55K Genotyping Arrays ; long spike ; long glume ; QTL mapping    

中文摘要:

新疆稻麦子(Triticum petropavlovskyi Udacz.et Migusch.,2n=6x=42,AABBDD)是上个世纪五十年代在我国新疆发现的一种特有的栽培裸粒小麦。新疆稻麦子在形态学方面与普通六倍体小麦有较明显的区别,具体表现为长穗、长颖、长粒和高千粒重等特征。目前国内外学者对新疆稻麦子的研究主要聚焦于其起源演化过程和长颖性状的遗传分析,而对其长穗、籽粒等产量相关性状研究较少。小麦产量三要素包括千粒重、穗粒数和单位面积穗数。新疆稻麦子作为普通小麦的初级基因库,通过与普通小麦杂交可以将新疆稻麦子中与小麦产量三因素相关的优异基因转移到栽培小麦背景中,通过提高小麦的穗长、粒长和千粒重从而提高产量。因此,通过对控制新疆稻麦子的长穗、长颖等性状进行QTL定位,不仅可以挖掘新疆稻麦子的有益基因,同时对拓宽栽培小麦遗传基础及提高小麦产量都具有十分重要的意义。

本实验室前期以新疆稻麦子洛浦(T. petropavlovskyi luopu)为母本,小麦栽培品种扬麦158为父本构建了一个包含208个家系的BC2F10染色体片段置换系(Chromosome Segment Substitution Line, CSSL)群体。在此基础上,本研究通过多年多重复对该群体的两个亲本及208个家系的穗长、护颖长、外颖长、内颖长、千粒重、粒长、粒宽及长宽比这8个性状的表型数据进行调查分析;利用小麦55K SNP芯片对(新疆稻麦子×扬麦158)CSSL群体各家系进行了基因分型分析;利用55K SNP分析,构建了(新疆稻麦子×扬麦158)CSSL群体高密度的遗传图谱;利用构建的遗传图谱,结合对(新疆稻麦子×扬麦158)CSSL群体双亲以及各家系的两年多重复的表型调查数据,对新疆小麦控制穗部、籽粒性状相关QTL/基因进行了QTL定位;进一步利用构建的F2次级分离群体,对新疆小麦7A染色体短臂上的QTL簇进行了进一步定位。主要研究结果如下:

1.利用小麦55K SNP芯片对CSSL群体各家系进行基因分型分析

根据小麦55K SNP芯片,首先筛选在双亲新疆稻麦子洛浦和扬麦158之间有多态的 SNP 位点;进一步利用软件GGT2 绘制染色体片段渐渗图;根据染色体片段渐渗图分析了(新疆稻麦子×扬麦158)CSSL群体各家系基因组内渐渗SNP的数目及分布规律。根据渐渗图,发现新疆稻麦子洛浦的染色体片段基本能够覆盖(新疆稻麦子×扬麦158)CSSL群体家系的21条染色体,说明该CSSL群体可以用于进一步的QTL定位分析。

2.利用55K SNP芯片构建了(新疆稻麦子×扬麦158CSSL群体高密度的遗传图谱

通过筛选小麦55K芯片中的SNP标记,共得到23,889个在双亲新疆稻麦子洛浦和扬麦158之间有多态的SNP标记。进一步利用IciMapping V4.1和JoinMap 4.0软件构建了覆盖新疆稻麦子洛浦21条染色体的遗传图谱。该遗传图谱共包含3,523个SNP标记,总遗传距离2,801.664 cM,平均遗传距离为0.795cM。其中A染色体组的遗传距离为878.648cM,包含1,162个SNP标记,占遗传图谱总标记数的32.98%,平均遗传距离为0.756cM;B染色体组的遗传距离为909.477cM,包含1,049个SNP标记,占遗传图谱总标记数的29.78%,平均遗传距离为0.867cM;D染色体组的遗传距离为1,013.539cM,包含1,312个SNP标记,占遗传图谱总标记数的37.24%,平均遗传距离为0.773cM。在21条染色体中,遗传距离最短的为4D染色体,为88.074 cM;遗传距离最长的为1D染色体,为210.605cM;在遗传图谱中,平均标记间的遗传距离为0.509 cM(6D)– 1.660 cM(4B)。

3.利用(新疆稻麦子×扬麦158CSSL群体对新疆小麦控制穗部、籽粒性状相关QTL/基因进行精细定位

利用构建的遗传图谱,结合对(新疆稻麦子×扬麦158)CSSL群体双亲以及各家系的两年多重复的表型调查数据,对新疆小麦控制穗部、籽粒性状相关QTL/基因进行了QTL初步定位。定位结果共检测到与控制穗长、护颖长、外颖长、内颖长、千粒重、粒长、粒宽和长宽比8个性状相关的97个QTL,位于小麦的21条染色体上,解释表型变异的范围为0.1824% -- 53.1912%。其中有14个QTL可以在两年中被重复检测到,分别位于2B、2D、3D、4A、7A、7B和7D染色体上,控制穗长、护颖长、外颖长、内颖长、千粒重、长宽比的且稳定的QTL分别有3、5、2、2、1、1个。其中位于7A染色体短臂127.5Mb – 133.2Mb(参考中国春基因组v1.0)之间有一个同时控制穗长、护颖长、外颖长的QTL簇。

4.利用F2次级分离群体对新疆小麦7A染色体短臂上的QTL簇进行精细定位

因为7A染色体短臂127.5Mb – 133.2Mb(参考中国春基因组v1.0)之间的QTL簇对穗长、护颖长、外颖长贡献率较高,所以为了精细定位该位点,以CSSL群体中2017CY92(典型长颖家系)为母本,以扬麦158为父本构建了F2次级分离群体。参考中国春7A染色体127.5Mb – 133.2Mb的基因组序列,进一步开发SNP引物和CAPS引物,利用这些引物在包含609个单株的F2次级分离群体中进行分析。根据交换单株2019LZP859-9、2019LZP907-3等的表型和分子标记分析结果最终将控制新疆小麦穗长和颖长的QTL缩小至SNP41698和CAPS36261之间。参考中国春基因组序列,最终将该QTL定位于128.8 - 130.3Mb之间,物理距离1.5Mb。

外文摘要:

Triticum petropavlovskyi Udacz.et Migusch. (2n=6x=42, AABBDD) is a kind of unique cultivated wheat found in Xinjiang province of China in the 1950s. It has distinctive morphological characters such as long spike, long glume, long grain and high grain weight. Up to now, researchers mainly focus on the origin and evolution of T. petropavlovskyi and the genetic analysis of long glume, but few on the analysis of the yield related characters such as long spike and grain traits. The three factors of wheat yield include 1,000 grain weight, the number of grains per spike and the number of spikes per unit area. T.petropavlovskyi is the primary germplasm of common wheat, and the excellent genes related to three factors of yeild in T.petropavlovskyi can be transferred into the background of cultivated wheat by crossing with common wheat. Therefore, QTL mapping for controlling the traits, spike- and grain-related traits of T.petropavlovskyi can not only excavate the beneficial genes of T.petropavlovskyi, but also broaden the genetic basis of cultivated wheat and improve the yield of wheat.

In this study, a BC2F10 (chromosome segment substitution line, CSSL) population derived from the cross of T. petropavlovskyi luopu and Yangmai158 was constructed and contained 208 lines. On this basis, the phenotypic data of 8 traits, including spike length, empty glume length, outer glume length, inner glume length, 1,000-grain-weight, kermel length, kernel width and kernel length/kernel width ratio, were investigated and analyzed in two parents and 208 families of this population in 2017-2018 and 2018-2019, respectively. Wheat 55K AXIOM ARRAY was used to genotype of (T. petropavlovskyi×Yangmai 158) CSSL population and constructed a high density genetic map of CSSL population. Based on the genetic map and the two-year repeated phenotypic data of their parents and families in (T. petropavlovskyi×Yangmai 158) CSSL population, the QTL/genes related to spike and grain characters in T. petropavlovskyi were located. Furthermore, the QTL clusters on the short arm of chromosome 7A of T. petropavlovskyi were fine mapped using the secondary F2 population. The main results are as follows:

1.Genotyping of CSSL population families using wheat 55K AXIOM ARRAY

According to wheat 55K AXIOM ARRAY, SNP loci with polymorphism between the T. petropavlovskyi luopu and Yangmai 158 were selected, and the chromosome segment introgression map of CSSL population was drawn using GGT2 . The number and distribution of introgressive SNPs were also analyzed in CSSL population. In the chromosome segment introgression map, the chromosome fragments of T. petropavlovskyi luopu basically covered 21 chromosomes of the CSSL population family, indicating that the CSSL population could be used for QTL mapping.

2.Construction of a high density genetic map based on (T. petropavlovskyi ×Yangmai158) CSSL population

A total of 23,889 polymorphic markers between T. petropavlovskyi luopu and Yangmai158 were obtained by selecting SNP markers in wheat 55K AXIOM ARRAY. A genetic map covering 21 chromosomes was constructed using IciMapping V4.1 and JoinMap 4.0, which contained 3,523 SNP markers. The total genetic distance was 2,801.664 cM and the average genetic distance was 0.795 cM. The genetic distance of the A genome was 878.648cM, which contained 1,162 SNP markers, accounting for 32.98% of the total number of markers in the genetic map, and the average genetic distance was 0.756cM. The genetic distance of the B genome was 909.477cM, which contained 1,049 SNP markers, accounting for 29.78% of the total number of markers in the genetic map and the average genetic distance was 0.867cM. The genetic distance of the D chromosome was 1,013.539cM, which contained 1,312 SNP markers, accounting for 37.24% of the total number of markers in the genetic map and the average genetic distance was 0.773cM. Among the 21 chromosomes, the shortest genetic distance was 4D chromosome, which was 88.074 cM. The longest genetic distance was 1D chromosome, which was 210.605 cM. The average genetic distance ranged from 0.509 cM (6D) to 1.660 cM (4B).

3.QTL mapping of spike- and grain-related traits using (T. petropavlovskyi luopu and Yangmai158 ) CSSL population.

Using the high density genetic map and the phenotypic data of the CSSL population for two years, a total of 97 QTLs controlling 8 traits including spike length, empty glume length, outer glume length, inner glume length, 1000-grain weight, kernel length, kernel width and kernel length/kernel width ratio were detected on all chromosomes of wheat, the phenotypic variance explained was from 0.1824% to 53.1912%. A total of 14 stable QTLs that 3 QTLs related to spike length, 5 QTLs related to empty glume length, 2 QTLs related to outer glume length, 2 QTLs related to inner glume length, 1 QTL related to 1,000-grain weight, and 1 QTLs related to kernel length/kernel width ratio could be repeatedly detected in two years, located at 2B、2D、3D、4A、7A、7B and 7D. Among them, a QTL cluster located between the 127.5Mb – 133.2Mb of the short arm of the 7A chromosome (referring to the Chinese spring genome v1.0) controlled spike length, empty glume length and outer glume length was detected, indicating that this region was significantly related to yield traits.

4.Fine mapping of QTL cluster in the chromosome 7AS of T. petropavlovskyi by a secondary F2 population.

    Because the QTL cluster on the short arm of chromosome 7A 127.5Mb - 133.2Mb (refer to Chinese Spring genome v1.0) had a high contribution to spike length, empty glume length and outer glume length. To fine mapping the QTL cluster, we built a F2 population derived from 2017CY92(a long glume CSSL line) and Yangmai 158. According to the sequence of 7A 127.5Mb - 133.2Mb of Chinese Spring, we developed SNP primers and CAPS primers to analysis the F2 population. According to the phenotype and molecular marker analysis of recombinant individual 2019LZP859-9 and 2019LZP907-3, etc., the QTL cluster controlling spike length, empty glume length and outer glume length of T.petropavlovskyi was finally located to the region between SNP41698 and CAPS36261.The QTL cluster was narrowed to the region between 128.8 - 130.3 Mb with a physical distance of 1.5 Mb.

参考文献:

1. 曹晓凤.基于unigene遗传图谱的小麦产量性状QTL分析[D].山东农业大学, 2019.

2. 陈佳慧, 兰进好, 王晖, 等.小麦籽粒形态及千粒重性状的QTL初步定位[J].麦类作物学报, 2011, 31(6): 1001-1006.

3. 陈建省, 陈广凤, 李青芳, 等.利用基因芯片技术进行小麦遗传图谱构建及粒重QTL分析[J].中国农业科学, 2014, 47(24): 4769-4779.

4. 陈谦.基于波兰小麦和节节麦人工合成六倍体小麦SHW-DPW探讨新疆稻麦的起源[D].四川农业大学, 2014.

5. 陈勤, 孙雨珍, 董玉琛.“新疆小麦”种间杂种的细胞遗传学研究[J].作物学报,1985, 11(1): 23-29.

6. 陈庆富.中国特有小麦中杂种黄化基因Chl和提型胞质育性恢复基因的分布研究[J].广西植物, 1998, 18(4): 325-330.

7. 陈树林.扬麦13背景的N533染色体片段导入系的培育、评价及矮巧密穗突变体Rht23的鉴定和定位[D].南京农业大学, 2014.

8. 陈稳良, 景蕊莲, 刘惠民, 等.晋麦47背景回交导入系的遗传选择与性状分析[J].麦类作物学报, 2009, 29(2): 206-211.

9. 陈喜红, 温权州, 甘丹阳, 等.水稻温敏核不育系 HD9802S不育基因的 SSR 标记定位[J].湖北大学学报, 2019, 41(3): 234-240.

10. 陈妍.栽培小麦高密度连锁图谱构建及穗、粒相关性状的QTL定位[D].南京农业大学, 2018.

11. 邓小锋, 周永红, 杨瑞武, 等.新疆吐鲁番矮秆波兰小麦穗长基因的染色体定位[J].四川农业大学学报, 2005, 23(1): 12-14.

12. 丁安明.小麦关联RIL群体遗传连锁图普构建及产量相关性状的QTL定位[D].山东农业大学, 2011.

13. 董青.水稻第1染色体长臂上两个连锁粒型QTL的分解和精细定位[D].华中农业大学, 2018.

14. 董玉琛.小麦的稀有种及其在育种中的利用[J].中国农业科学, 1979(3): 1-7.

15. 盖江涛, 党志国, 王鹏.作物染色体片段代换系的研究进展[J].大麦与谷类科学, 2017, 34(1): 1-5.

16. 高明刚.小麦高密度遗传图谱的构建和产量相关性状的QTL分析[D].山东农业大学, 2014.

17. 高尚, 莫洪军, 石浩然, 等.利用SNP基因芯片技术进行小麦遗传图谱构建及重要农艺性状QTL分析[J].应用与环境生物学报, 2016, 22(1): 85-94.

18. 何婷婷.小麦-节节麦D组染色体片段代换系的构建及籽粒性状的QTL定位[D].河南大学,

2017.

19. 侯立江.小麦穗长性状的QTL分析[D].西北农林科技大学, 2015.

20. 黄鲁豫.节节麦-小麦代换系群体农艺性状调查及相关QTL定位[D].河南大学, 2018.

21. 活泼, 田新玲, 文如镜, 等.新疆稻穗麦籽粒蛋白质生化分析[J].新疆农业科学, 1989(5): 7-8.

22. 江千涛.小麦种子贮藏蛋白基因的分子鉴定与进化研究[D].四川农业大学, 2009.

23. 李柏云.大豆四向重组自交系群体产量相关性状QTL单标记分析[D].东北农业大学, 2015.

24. 李聪, 马建, 刘航, 等.基于小麦55K SNP芯片检测小麦穗长和株高性状QTL[J].麦类作物学报, 2019, 39(11): 1284-1292.

25. 李丹丹.基于SNP芯片的“潍麦8号/安农91186”RIL群体农艺及产量性状QTL定位[D].山东农业大学, 2017.

26. 李浩川, 陈琼, 杨继伟, 等.基于双单倍体群体的玉米株高和穗位高 QTL分析[J].河南农业大学学报, 2016, 50(2): 161-166.

27. 李磊, 贡豪, 顾世梁, 等.小麦中基于转录组测序SNP的dCAPS标记的高通量开发及验证[J].扬州大学学报, 2018, 39(4): 86-90.

28. 李美霞.小麦籽粒相关性状QTL分析[D].西北农林科技大学, 2015.

29. 李清峰.基于SRAP标记的小麦籽粒性状QTL定位[D].西北农林科技大学, 2012.

30. 李伟.干旱胁迫条件下小麦冠层及产量相关性状的QTL定位[D].河南农业大学, 2008.

31. 李永明.玉米重要农艺性状QTL的近等基因系选育和遗传效应分析[D].河南农业大学, 2013.

32. 李志远.KASP标记用于甘蓝指纹图谱构建及杂种优势群划分[D].中国农业科学院, 2018.

33. 廖祥政, 王瑾, 周荣华, 等.发掘人工合成小麦中千粒重 QTL 的有利等位基因[J].作物学报, 2008, 34(11): 1877?1884.

34. 刘丹, 孙玉友, 魏才强, 等.InDel分子标记及其在水稻研究中的应用[J].种子, 2017, 36(9): 47-59.

35. 刘会宇.小麦重要农艺性状近等基因导入系的构建及其QTL分析[D].四川农业大学, 2010.

36. 刘凯, 邓志英, 李青芳, 等.利用高密度SNP遗传图谱定位小麦穗部性状基因[J].作物学报 , 2016, 42(6): 820-831.

37. 刘书含, 侯立江, 华冠勋, 等.大穗材料高麦1号/密小穗F2群体穗长性状的QTL初步定位[J].麦类作物学报, 2016, 36(4): 409-414.

38. 卢翔, 张锦鹏, 王化俊, 等.小麦-冰草衍生后代3558-2穗部相关性状的遗传分析和QTL定位[J].植物遗传资源学报, 2011, 12(1): 86-91.

39. 逯腊虎, 杨斌, 张婷, 等.冬小麦旗叶大小及籽粒相关性状的QTL分析[J].华北农学报, 2018, 35(5): 1-8.

40. 蒲艳艳, 宫永超, 李娜娜, 等.中国小麦作物遗传多样性研究进展[J].作物种质资源, 2016, 32(30): 7-13.

41. 沈金雄, 易斌, 傅廷栋, 等.植物数量性状基因定位研究概述[J].植物学通报, 2003, 20(3): 257-263.

42. 施卫萍.小麦染色体片段渐渗系的构建及相关农艺性状的QTL鉴定[D].扬州大学, 2014.

43. 苏萍萍.小麦品种秦农142成株期抗条锈病QTL定位[D].西北农林科技大学, 2017.

44. 孙中沛, 刘天相, 左希亚, 等.普通小麦穗部性状QTL分析[J].麦类作物学报, 2017, 37(4): 452-457.

45. 田再民, 张立平, 孙庆林, 等.小麦数量性状基因定位研究进展[J].植物学通报, 2007(3): 68-71.

46. 王海燕, 王秀娥, 陈佩度, 等.云南、西藏与新疆小麦高分子量谷蛋白亚基组成及遗传多样性分析[J].中国农业科学, 2005, 38(2): 228-233.

47. 王海燕.云南、西藏与新疆小麦的遗传多样性研究[D].南京农业大学, 2005.

48. 王晖, 兰进好, 田纪春.不同发育时期小麦粒重性状QTL的动态分析[J].植物遗传资源学报, 2012, 13(6): 1055-1060.

49. 王慧茹, 王光达, 昌小平, 等.不同水分环境条件下小麦遗传和关联性分析[J].华北农学报, 2013, 28(4): 53-61.

50. 王佳佳, 王盈盈, 张照贵, 等.小麦穗部性状和株高的 QTL 定位[J].分子植物育种, 2015, 13(1): 77-84.

51. 王建康.数量性状基因的完备区间作图方法[J].作物学报,2009,35(2): 239-245.

52. 王瑾, 廖祥政, 杨学举, 等.人工合成小麦Am3大穗多粒QTL的发掘与利用[J].植物遗传资源学报, 2008, 9(3): 277-282.

53. 王霖.小麦遗传连锁图谱构建及主要农艺和品质性状QTL定位[D].山东农业大学, 2012.

54. 吴龙芬, 包莹莹, 张青霞, 等.植物遗传连锁图谱构建最新研究进展[J].科学技术创新, 2019(01): 16-18.

55. 吴秋红, 陈娇娇, 陈永兴, 等.燕大 1817/北农 6 号重组自交系群体穗部性状的 QTL 定位[J].作物学报, 2015, 41(3): 349-358.

56. 吴田田.陆地棉×毛棉种间BC1群体遗传连锁图谱构建[D].西南大学, 2018.

57. 吴新儒, 刘树兵, 刘爱峰, 等.小麦重要农艺性状QTL近等基因导入系的选育[J].麦类作物学报, 2007, 27(4): 583-588.

58. 武炳瑾, 简俊涛, 张德强, 等.利用90K芯片技术进行小麦穗部性状QTL定位[J].作物学报, 2017, 43(7): 1087-1095.

59. 谢辉, 东丽, 肖艳云, 等.水稻数量性状定位研究进展[J].园艺与种苗, 2015(6): 82-87.

60. 谢晓玲, 邓自发, 解俊峰.小麦新种质 241主要特异性状的遗传性[J].广西科学院学报, 2002, 18(2): 77-83.

61. 徐小婷.扬麦16/中麦895双单倍体群体高密度遗传图谱构建与抗白粉病QTL定位[D].中国农业科学院, 2019.

62. 许睿.基于染色体置换系的普通野生稻(O.rufipogon Griff.)耐盐性QTL定位[D].中国农业科学院, 2019

63. 闫林.大穗小麦西农9814主要性状遗传分析及性状改良研究[D].西北农林科技大学, 2009.

64. 严俊, 张玲玲, 万兵, 等.硬粒小麦与野生二粒小麦重组自交系群体穗部性状的QTL定位[J].四川农业大学学报, 2011, 29(2): 147-153.

65. 杨瑞武, 周永红, 郑有良, 等.波兰小麦醇溶蛋白遗传差异及其与新疆稻麦的关系[J].麦类作物学报, 1998, 18(4): 325-330.

66. 杨睿.波兰小麦×普通小麦系中13RIL群体重要农艺性状的QTL定位[D].西北农林科技大学, 2012.

67. 杨文利.小麦株高与产量性状分子标记的研究[D].河北农业大学, 2002.

68. 杨武云, 颜济, 杨俊亮.中国几个特有普通小麦起源研究[J].四川农业大学学报, 1992, 10(1): 12-1

69. 杨宜豪.水稻精米蛋白质含量QTLqPC-10精细定位和候选基因分析[D].扬州大学, 2016.

70. 姚景侠, 杨芳彬, 师素云, 等.小麦属的新种-新疆稻穗麦之研究[J].遗传, 1983(5): 17-20.

71. 叶亚琼.小麦株高和千粒重QTL定位及其元分析[D].甘肃农业大学, 2015.

72. 余马.人工合成六倍体小麦遗传你图谱构建及重要育种目标性状QTL定位研究[D].四川农业大学, 2013.

73. 余曼丽.小麦籽粒性状的QTL定位分析[D].中国农业科学院, 2014.

74. 翟俊鹏, 李海霞, 毕惠惠, 等.普通小麦主要农艺性状的全基因组关联分析[J].作物学报, 2019, 45(10): 1488-1502.

75. 翟立红, 周兰庭, 韩鹏, 等.玉米穗行数基因的QTL定位与分析[J].江苏农业科学, 2016, 44(2): 69-72.

76. 张灿灿.野生二粒小麦面粉加工品质相关形状的全基因组关联分析及高分子量谷蛋白亚基基因1Ax1的克隆[D].河南大学, 2019.

77. 张桂芝.利用大粒突变体进行小麦籽粒大小和产量性状的QTL分析[D].山东农业大学, 2011.

78. 张海泉, 张宝石.山羊草及普通小麦遗传多样性的研究[J].沈阳农业大学学报, 2004-06, 35(3): 165-169.

79. 张坤普, 徐宪斌, 田纪春.小麦籽粒产量及穗部相关性状的[J].作物学报, 2009, 35(2): 270-278.

80. 张秋.普通小麦遗传图谱构建及重要农艺性状的QTL定位[D].山东农业大学, 2012.

81. 张新业.小麦粒重基因TaGW2-6A的功能验证及粒重相关性状的QTL分析[D].山东农业大学, 2012.

82. 张瑶尧.利用F2:3家系定位小麦苗期耐盐相关的 [D].内蒙古师范大学, 2019.

83. 郑殿升, 孙雨珍.小麦属各个种简介(五)[J].作物种质资源, 1986a(4): 35-37.

84. 郑有良, 颜济, 杨俊良.普通小麦穗长基因定位研究[J].Theoretical and Applied Genetics , 1992, 10(4): 570-573.

85. 周小鸿, 马建, 罗伟, 等.西藏半野生小麦粒型性状的QTL定位[J].麦类作物学报, 2016, 36(1): 27-35.

86. 朱军.数量性状基因定位的混合线性模型分析方法[J].遗传,1998(20): 137-138.

87. 朱尚尚, 刘晓丽, 刘二宝, 等.利用宁粳1号/R254 的CSSL群体定位水稻产量相关性状 QTL[J].基础理论, 2019, 34(6): 52-61.

88. 朱元君.水稻千粒重QTLqTGW10-20.8的精细定位[D].华中农业大学, 2019.

89. Akond M, Watanabe N, Furuta Y. Comparative genetic diversity of Triticum aestivum–Triticum polonicum introgression lines with long glume and Triticum petropavlovskyi by AFLP-based assessment[J]. Genetic Resources and Crop Evolution, 2008(55): 133-141.

90. Ammiraju J, Dholakia B, Santra D, et al. Identification of inter simple sequence repeat (ISSR) markers associated with seed size in wheat[J]. Theoretical and Applied Genetics, 2001(102): 726-732.

91. Arbuzova VS, Efremova T, Laikova L, et al. The development of precise genetic stocks in two wheat cultivars and their use in genetic analysis[J]. Euphytica, 1996(89): 11-15.

92. Assanga S, Fuentealba M, Zhang GR, et al. Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs[J]. PLoS One, 2017, 12(12): e0189669.

93. B?rner A, Schumann E, Fürste A, et al. Mapping of quantitative trait loci determining agronomic important characters in hexaploid wheat (Triticum aestivum L.)[J]. Theoretical and Applied Genetics, 2002(105): 921-936.

94. Bozzini and Giorgi B. Genetic analysis of tetraploid and hexaploid wheat by utilization of monopentaploid hybrids[J]. Theoretical and Applied Genetics, 1971(41): 67-74.

95. Breseghello F and Sorrells M. QTL analysis of kernel size and shape in two hexaploid wheat mapping populations[J]. Field Crops Research, 2007(101): 172-179.

96. Campbell K, Bergman C, Gualberto D, et al. Quantitative trait loci associated with kernel traits in a Soft ×Hard wheat cross[J]. Crop Science, 1999(39): 1184-1195.

97. Chai LL, Chen ZY, Bian RL, et al. Dissection of two quantitative trait loci with pleiotropic effects on plant height and spike length linked in coupling phase on the short arm of chromosome 2D of common wheat (Triticum aestivum L.)[J]. Theoretical and Applied Genetics, 2019(132): 1815-1831.

98. Chang JZ, Zhang JN, Mao XG, et al. Polymorphism of TaSAP1-A1 and its association with agronomic traits in wheat[J]. Planta, 2013(237): 1495-1508.

99. Chao S, Sharp P, Worland E, et al. RFLP-based genetic maps of wheat homoeologous group 7 chromosomes[J]. Theoretical and Applied Genetics, 1989(78): 495-504.

100. Chen Q, Kang HY, Fan X, et al. Evolutionary history of Triticum petropavlovskyi Udacz.et Migusch. inferred from the sequences of the 3-Phosphoglycerate kinase gene[J]. PLoS One, 2013, 8(8): e71139.

101. Chen RR, Kong ZX, Zhang LW, et al. Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population[J]. Theoretical and Applied Genetics, 2017(130): 1405-1414.

102. Cheng XJ, Chai LL, Chen ZY, et al. Identification and characterization of a high kernel weight mutant induced by gamma radiation in wheat (Triticum aestivum L.)[J]. BMC Genetics, 2015(16): 127.

103. Coulson A, Sulston J, Brenner S. Toward a physical map of the genome of the nematode Caenorhabditis elegans[J]. Proceedings of the National Academy of Sciences of the United States of America, 1986(83): 7281-7825.

104. Cui F, Ding AM, Li J, et al. QTL detection of seven spike-related traits and their genetic correlations in wheat using two related RIL populations[J]. Euphytica, 2012(186): 177-192.

105. Cuthbert J, Somers D, Babel A, et al. Molecular mapping of quantitative trait loci for yield and yield components in spring wheat (Triticum aestivum L.)[J]. Theoretical and Applied Genetics, 2008(117): 595-608.

106. Dholakia B, Ammiraju J, Singh H, et al. Molecular marker analysis of kernel size and shape in bread wheat[J]. Plant Breeding, 2003(122): 392-395.

107. Dong LL, Wang FM, Liu T, et al. Natural variation of TaGASR7-A1 affects grain length in common wheat under multiple cultivation conditions[J]. Molecular Breeding, 2014(34): 937-947.

108. Efremova T, Maysuenko O, Arbuzova V, et al. Genetic analysis of glume colour in common wheat cultivars from the former USSR[J]. Euphytica, 1998(102): 211-218.

109. Eitan M, Moshe J. Effects of removing floral organs, light[J]. Annals of Botany, 1984(53): 261-269.

110. Gao FM, Wen WE, Liu JD, et al. Genome-wide linkage mapping of QTL for yeild components, plant height and yeild-related physiological traits in the Chinese wheat cross Zhou 8425B/Chinese Spring[J]. Frontiers in Plant Science, 2015(6): 1099.

111. Giura N, Saulescu NN. Chromosomal location of genes controlling grain size in a large grained selection of wheat (Triticum aestivum L.)[J]. Euphytica, 1996(89): 77-80.

112. Grewal S, Edwards H, Yang CY et al. Rapid identification of homozygosity and site of wild relative introgressions in wheat through chromosome-relative introgressions in wheat through chromosome specific KASP genotyping assays[J]. Plant Biotechnology Journal, 2020(18): 743-755.

113. Gu LQ, Wei B, Fan RC, et al. Development, identification and utilization of introgression lines using Chinese endemic and synthetic wheat as donors[J]. Journal of Integrative Plant Biology, 2015, 57(8): 688-697.

114. Guo Y, Sun JJ, Zhang GZ, et al. Haplotype, molecular marker and phenotype effects associated with mineral nutrient and grain size traits of TaGS1a in wheat[J]. Field Crops Research, 2013(154): 119-125.

115. Heidari B, Tabatabaei B, Saeidi G, et al. Mapping QTL for grain yield, yield components, and spike features in a doubled haploid population of bread wheat[J]. Genome, 2011(54): 517-527.

116. Hu JH, Wang XQ, Zhang GX, et al. QTL mapping for yield?related traits in wheat based on four RIL populations[J]. Theoretical and Applied Genetics, 2020(133): 917-933.

117. Hu MJ, Zhang HP, Liu K, et al. Cloning and characterization of TaTGW-7A gene associated with grain weight in wheat via SLAF-seq-BSA[J]. Frontiers in Plant Science, 2016(7): 1902.

118. Huang XQ, Cloutier S, Lycar L, et al. Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)[J]. Theoretical and Applied Genetics, 2006(113): 753-766.

119. Jain A, Roorkiwal M, Kale S, et al. InDel markers: an extended marker resource for molecular breeding in chickpea[J]. PLoS One, 2019, 14(3): e0213999.

120. Jantasuriyarat C, Vales M, Watson C, et al. Identification and mapping of genetic loci affecting the free-threshing habit and spike compactness in wheat (Triticum aestivum L.)[J]. Theoretical and Applied Genetics, 2004(108): 261-273.

121. Jia HY, Wan HS, Yang SH, et al. Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding[J]. Theoretical and Applied Genetics, 2013(126): 2123-2139.

122. Jiang QY, Hou J, Hao CY, et al. The wheat (T. aestivum) sucrose synthase 2 gene (TaSus2) active in endosperm development is associated with yield traits[J]. Functional & Integrative Genomics, 2011(11): 49-61.

123. Kang GZ, Liu GQ, Peng XQ, et al. Increasing the starch content and grain weight of common wheat by overexpression of the cytosolic AGPase large subunit gene[J]. Plant Physiology and Biochemistry, 2013(73): 93-98.

124. Kang HY, Fan X, Zhang HQ, et al. The origin of Triticum petropavlovskyi Udacz. et Migusch.:demonstration of the utility of the genes encoding plastid acetyl-CoA carboxylase sequence[J]. Molecular Breeding, 2010(25): 381-395.

125. Kearsey M, Pooni H. The genetical analysis of quantitative traits[J]. Journal of Medical Genetics, 1996(33): 976.

126. Kosuge K, Watanabe N, Kuboyma T. Genetic mapping of loci determining long glumes in the genus Triticum[J]. Genetic Resources and Crop Evolution, 2010(57): 611-618.

127. Kosuge K, Watanabe N, Kuboyama T, et al. Recombination around the P locus for long glume phenotype in experimental introgression lines of Triticum aestivum –Triticum polonicum[J]. Genetic Resources and Crop Evolution, 2010(57): 611-618.

128. Kumar A, Mantovani E, Seetan R, et al. Dissection of genetic factors underlying wheat kernel shape and size in an Elite×Nonadapted cross using a high density SNP linkage map[J]. The Plant Genome, 2016, 9(1): 1-22.

129. Kumar N, Kulwal P, Balyan H, et al. QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat[J]. Molecular Breeding, 2007(19): 163-177.

130. Kumar N, Kulwal P, Gaur A, et al. QTL analysis for grain weight in common wheat[J]. Euphytica, 2006(151): 135-144.

131. Kumari S, Jaiswal V, Mishra V, et al. QTL mapping for some grain traits in bread wheat (Triticum aestivum L.)[J]. Physiology and Molecular Biology of Plants, 2018, 24(5): 909-920.

132. Kumari S, Jaiswal V, Mishra V, et al. QTL mapping for some grain traits in bread wheat (Triticum aestivum L.)[J]. Physiology and Molecular Biology of Plants, 2018, 24(5): 909-920.

133. Lander E, Botstein D. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps[J]. Genetics, 1989(121): 185-199

134. Lee HS, Jung JU, Kang CS, et al. Mapping of QTL for yield and its related traits in a doubled haploid population of Korean wheat[J]. Plant Biotechnology Report, 2014(8): 443-454.

135. Li FJ, Wen WE, He ZH, et al. Genome?wide linkage mapping of yield?related traits in three Chinese bread wheat populations using high?density SNP markers[J]. Theoretical and Applied Genetics, 2018(131): 1903-1924.

136. Li SS, Jia JZ, Wei XY, et al. A intervarietal genetic map and QTL analysis for yield traits in wheat[J]. Molecular Breeding, 2007(20): 167-178.

137. Li WL, Nelson J, Chu CY, et al. Chromosomal locations and genetic relationships of tiller and spike characters in wheat[J]. Euphytica, 2002(125): 357-366.

138. Li XJ, Li LQ, Wang H, et al. Quantitative trait loci analysis for kernel length and width in wheat (Triticum aestivum L.)[J]. Journal of Northwest A &F University, 2009, 37(3): 95-100.

139. Liu GL, Jia LJ, Lu LH, et al. Mapping QTLs of yield?related traits using RIL population derived from common wheat and Tibetan semi?wild wheat[J]. Theoretical and Applied Genetics, 2014(127): 2415-2432.

140. Liu JL, Xu ZB, Fan XL, et al. A Genome-wide association study of wheat spike related traits in China[J]. Frontiers in Plant Science, 2018(9): 1584.

141. Liu JL, Xu ZB, Fan XL, et al. Genome?wide linkage mapping of yield?related traits in three Chinese bread wheat populations using high?density SNP markers[J]. Theoretical and Applied Genetics, 2018, 131(9): 1903-1924.

142. Liu SB, Zhou RH, Dong YC, et al. Development, utilization of introgression lines using a synthetic wheat as donor[J]. Theoretical and Applied Genetics, 2006(112): 1360-1373.

143. Ma DY, Yan J, He ZH, et al. Characterization of a cell wall invertase gene TaCwi-A1 on common wheat chromosome 2A and development of functional markers[J]. Molecular Breeding, 2012(29): 43-52.

144. Ma J, Ding PY, Qin P, et al. Structure and expression of the TaGW7 in bread wheat (Triticum aestivum L.)[J]. Plant Growth Regulation, 2017(82): 281-291.

145. Ma M, Wang Q, Cheng HH, et al. Expression of TaCYP78A3, a gene encoding cytochrome P450 CYP78A3 protein in wheat (Triticum aestivum L.), affects seed size[J]. The Plant Journal, 2015(83): 312-325.

146. Ma MJ, Zhang HP, Cao JJ, et al. Characterization of an IAA-glucose hydrolase gene TaTGW6 associated with grain weight in common wheat (Triticum aestivum L.)[J]. Molecular Breeding, 2016(36): 25.

147. Marza F, Bai GH, Carver B, et al. Quantitative trait loci for yield and related traits in the wheat population Ning7840×Clark[J]. Theoretical and Applied Genetics, 2006(112): 688–698.

148. McCartney C, Somers D, Humphreys D, et al. Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 × ‘AC Domain’[J]. Genome, 2005(48): 870-883.

149. Mir R, Kumar N, Jaiswal V, et al. Genetic dissection of grain weight in bread wheat through quantitative trait locus interval and association mapping[J]. Molecular Breeding, 2012(29): 963-972.

150. Okamoto Y, Takumi S. Pleiotropic effects of the elongated glume gene P1 on grain and spikelet shape-related traits in tetraploid wheat[J]. Euphytica, 2013(194): 207-218.

151. Patil R, Tamhankar S, Oak M, et al. Mapping of QTL for agronomic traits and kernel characters in durum wheat (Triticum durum Desf.)[J]. Euphytica, 2013(190): 117-129.

152. Peng JH, Ronin Y, Fahima T, et al. Domestication quantitative trait loci in Triticum dicoccoides, the progenitor of wheat[J]. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100(5): 2489-2494.

153. Ramya P, Chaubal A, Kulkarni K, et al. QTL mapping of 1000-kernel weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.)[J]. Journal of Applied Genetics, 2010, 51(4): 421-429.

154. Rasheed A, Xia XC. From markers to genome?based breeding in wheat[J]. Theoretical and Applied Genetics, 2019(132): 767-784.

155. Ren TH, Hu YS, Tang YZ, et al. Utilization of a Wheat55K SNP Array for mapping of major QTL for temporal expression of the tiller number[J]. Frontier in Plant Science, 2018(9): 333.

156. R?der M, Huang XQ, B?rner A, et al. Fine mapping of the region on wheat chromosome 7D controlling grain weight[J]. Functional & Integrative Genomics, 2008(8): 79-86.

157. R?der M, Korzun V, Wendehake K, et al. A microsatellite map of wheat[J]. Genetics, 1998(149): 2007-2023.

158. Sakai Y, Cao LZ, Funata R, et al. QTLs for agronomic traits detected in recombinant inbred lines derived from a bread wheat × spelt cross[J]. Breeding Science, 2018(68): 587-595.

159. Shao QL, Liu AY, Kong LL, et al. QTL mapping and genetic effect of chromosome segment substitution lines with excellent fiber quality from Gossypium hirsutum×Gossypium barbadense[J]. Molecular Genetics and Genomics, 2019(294): 1123-1136.

160. Smoers D, Isaac P, Edwards K, et al. A high-density microsatellite consensus map for bread wheat(Triticum aestivum L.) [J]. Theoretical and Applied Genetics, 2004(109): 1105-1114.

161. Su ZQ, Hao CY, Wang LF, et al. Identification and development of a functional marker of TaGW2 associated with grain weight in bread wheat (Triticum aestivum L.)[J]. Theoretical and Applied Genetics, 2011(122): 211-223.

162. Sun XY, Wu K, Zhao Y, et al. QTL analysis of kernel shape and weight using recombinant inbred lines in wheat[J]. Euphytica, 2009(165): 615-624.

163. Tanksley SD, Grandillo S, Fulyon TM, et al. Advanced backcross QTL analysis in a cross between an elite processing line of tomato and its wild relative L.pimpinellifolium[J]. Theoretical and Applied Genetics, 1996(92): 213-224.

164. Tsilo T, Hareland G, Simsek S, et al. Genome mapping of kernel characteristics in hard red spring wheat breeding lines [J]. Theoretical and Applied Genetics, 2010(121): 717-730.

165. Tyagi S, Mir R, Balyan H, et al. Interval mapping and meta-QTL analysis of grain traits in common wheat (Triticum aestivum L.) [J]. Euphytica, 2015(201): 367-380.

166. Varshney R, Prasad M, Roy J, et al. Identification of eight chromosomes and a microsatellite marker on 1AS associated with QTL for grain weight in bread wheat[J]. Theoretical and Applied Genetics, 2000(100): 1290-1294.

167. Wang HJ, Huang XQ, R?der MS et al. Genetic mapping of loci determining long glumes in the genus Triticum[J]. Euphytica, 2002(123): 287-293.

168. Wang HY, Wang XE, Chen PD, et al. Assessment of genetic diversity of Yunnan, Tibetan, and Xinjiang wheat using SSR markers[J]. Journal of Genetics and Genomics, 2007, 34(7): 623-633.

169. Wang JS, Liu WH, Wang H, et al. QTL mapping of yield-related traits in the wheat germplasm 3228 [J]. Euphytica, 2011(177): 277-292.

170. Wang LF, Ge HM, Hao CY, et al. Identifying loci influencing 1,000-Kernel weight in wheat by microsatellite screening for evidence of selection during breeding[J]. PLoS One, 2012, 7(2): e29432.

171. Wang RX, Hai L, Zhang XY, et al. QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai×Yu8679 [J]. Theoretical and Applied Genetics, 2009(118): 313-325.

172. Wang SS, Zhang XF, Chen F, et al. A single-nucleotide polymorphism of TaGS5 gene revealed its association with kernel weight in Chinese bread wheat[J]. Frontiers in Plant Science, 2015(6): 1166.

173. Wang SX, Zhu YL, Zhang DX, et al. Genome-wide association study for grain yield and related traits in elite wheat varieties and advanced lines using SNP markers[J]. PLoS One, 2017, 12(11): e0188662.

174. Watanabe N, Bannikova SV, Goncharov NP, et al. Inheritance and chromosomal location of the gene for long glume phenotype found in Portuguese landraces of hexaploid wheat, “Arrancada”[J]. Journal of Animal Breeding and Genetics, 2004(58): 00-00.

175. Watanabe N, Sekiya T, Sugiyama K, et al. Telosomic mapping of the homoeologous genes for the long glume phenotype in tetraploid wheat[J]. Euphytica, 2002(128): 129-134.

176. Watanabe N, Yotani Y, Furuta Y. The inheritance and chromosomal location of a gene for long glume in durum wheat[J]. Euphytica, 1996(91): 235-239.

177. Watanabe N. Genetic control of the long glume phenotype in tetraploid wheat by homoeologous chromosomes[J]. Euphytica, 1999(106): 39-43.

178. Watanabe N, Imamura I. Genetic control of long glume phenotype in tetraploid wheat derived from Triticum petropavlovskyi Udacz. et Migusch. [J]. Euphytica, 2002(128): 211-217.

179. Wu QH, Chen YX, Zhou SH, et al. High-density genetic linkage map construction and QTL mapping of grain shape and size in the wheat population Yanda1817 × Beinong6 [J]. PLoS One, 2015, 10(2): e0118144.

180. Yan XF, Zhao L, Ren Y, et al. Genome-wide association study revealed that the TaGW8 gene was associated with kernel size in Chinese bread wheat[J]. Scientific Reports, 2019(9): 2702.

181. Yang HY, Wang WB, He QY, et al. Identifying a wild allele conferring small seed size, high protein content and low oil content using chromosome segment substitution lines in soybean [J]. Theoretical and Applied Genetics, 2019(132): 2793-2807.

182. Yu K, Liu DC, Chen Y, et al. Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling[J]. Journal of Experimental Botany, 2019, 70(18): 4671-4688.

183. Zeng ZB. Precision mapping of quantitative trait loci[J]. Genetics, 1993(136): 1457-1468.

184. Zhang B, Shang LG, Ruan BP, et al. Development of three sets of high-throughput genotyped rice chromosome throughput genotyped rice chromosome mapping for eleven traits [J]. Rice, 2019(12): 33.

185. Zhang L, Zhao YL, Gao LF, et al. TaCKX6-D1, the ortholog of rice OsCKX2, is associated with grain weight in hexaploid wheat[J]. New Phytologist, 2012(195): 574-584.

186. Zhang PP, Li X. QTL mapping of adult-plant resistance to leaf and stripe rust in wheat cross SW 8588/Thatcher using the wheat 55K SNP Array[J]. Plant Disease, 2019, 103(12): 3041-3049.

187. Zhang YJ, Liu JD, Xia XC, et al. TaGS-D1, an ortholog of rice OsGS3, is associated with grain weight and grain length in common wheat[J]. Molecular Breeding, 2014(34): 1097-1107.

188. Zhang ZG, Lv GD, Li B, et al. Isolation and characterization of the TaSnRK2.10 gene and its association with agronomic traits in wheat (Triticum aestivum L.)[J]. PLoS One, 2017, 12(3): e0174425.

189. Zheng J, Liu Hong, Wang YQ, et al. TEF-7A, a transcript elongation factor gene, influences yield-related traits in bread wheat (Triticum aestivum L.)[J]. Journal of Experimental Botany, 2014, 65(18): 5351-5365.

190. Zhou SH, Zhang JP, Che YH, et al. Construction of Agropyron Gaertn. genetic linkage maps using a wheat 660K SNP array reveals a homoeologous relationship with the wheat genome[J]. Plant Biotechnology Journal, 2018(16): 818-827.

191. Zhou YP, Conway B, Miller D, et al. Quantitative trait loci mapping for spike characteristics in hexaploid wheat [J]. Plant Genome, 2017, 10(2)

中图分类号:

 S33    

开放日期:

 2022-06-19    

无标题文档

   建议浏览器: 谷歌 火狐 360请用极速模式,双核浏览器请用极速模式