欢迎访问作物学报,今天是

作物学报 ›› 2026, Vol. 52 ›› Issue (10): 2984-3005.doi: 10.3724/SP.J.1006.2026.63024

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

利用55K液相SNP芯片解析蜀麦753/孝感麦衍生品系的遗传构成

马婷婷1,2(), 郭晓江1,2(), 李豪1, 邓梅1, 蒲至恩3, 李伟3, 张亚洲1, 江千涛1,2, 马建1,2, 魏育明1,2, 王际睿1,2, 赵瑞凡4, 陈国跃1,2,*(), 蒋云峰1,2,*()   

  1. 1 四川农业大学小麦研究所, 四川成都 611130
    2 西南作物基因资源发掘与利用国家重点实验室, 四川成都 611130
    3 四川农业大学农学院, 四川成都 611130
    4 开鲁县农畜产品质量安全中心, 内蒙古通辽028400
  • 收稿日期:2026-02-24 接受日期:2026-07-15 出版日期:2026-10-12 网络出版日期:2026-07-23
  • 通讯作者: 蒋云峰, E-mail: jiangyunfeng@sicau.edu.cn;陈国跃, E-mail: gychen@sicau.edu.cn
  • 作者简介:马婷婷, E-mail: 2623455529@qq.com;
    郭晓江, E-mail: xiaojiang9945@icloud.com** 同等贡献
  • 基金资助:
    国家重点研发计划项目(2024YFD1201200);国家自然科学基金项目(32272059);四川省自然科学基金面上项目(2024NSFSC1212);四川省自然科学基金面上项目(2024NSFSC1341);四川省自然科学基金面上项目(2024NSFSC0328)

Dissection of the genetic composition of Shumai 753/Xiaoganmai-derived lines based on a 55K liquid SNP array

Ma Ting-Ting1,2(), Guo Xiao-Jiang1,2(), Li Hao1, Deng Mei1, Pu Zhi-En3, Li Wei3, Zhang Ya-Zhou1, Jiang Qian-Tao1,2, Ma Jian1,2, Wei Yu-Ming1,2, Wang Ji-Rui1,2, Zhao Rui-Fan4, Chen Guo-Yue1,2,*(), Jiang Yun-Feng1,2,*()   

  1. 1 Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
    2 State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, Sichuan, China
    3 College of Agronomy, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
    4 Kailu County Agricultural and Livestock Product Quality and Safety Center, Tongliao 028400, Inner Mongolia, China
  • Received:2026-02-24 Accepted:2026-07-15 Published:2026-10-12 Published online:2026-07-23
  • Contact: Jiang Yun-Feng, E-mail: jiangyunfeng@sicau.edu.cn;Chen Guo-Yue, E-mail: gychen@sicau.edu.cn
  • About author:** Contributed equally to this work
  • Supported by:
    National Key R&D Program of China(2024YFD1201200);National Natural Science Foundation of China(32272059);Science and Technology Department of Sichuan Province(2024NSFSC1212);Science and Technology Department of Sichuan Province(2024NSFSC1341);Science and Technology Department of Sichuan Province(2024NSFSC0328)

摘要:

来自湖北当阳的白粒农家种孝感麦(ZM011362)具多花多粒、多有效分蘖、稳定的穗发芽和成株期条锈病抗性的特点, 是可供当前小麦育种利用的潜在优异种质。前期研究以小麦农家种孝感麦为供体、携带全生育期条锈病抗性基因且综合性状良好的育成品系蜀麦753为受体, 通过杂交、回交及连续多代自交并利用育种目标性状“分段式”育种技术, 育成了178份蜀麦753/孝感麦衍生品系。本研究旨在分子水平上解析蜀麦753/孝感麦衍生品系的遗传基础, 明确控制其产量、抗病及耐逆性的关键染色体区段, 为利用小麦农家种进行遗传改良提供重要的分子依据。利用小麦55K液相SNP芯片对孝感麦、蜀麦753及其178份衍生品系进行全基因组扫描, 共获得52,779个有效纯合多态性SNP位点。通过多态性SNP位点对双亲及其衍生品系遗传相似性及遗传构成进行分析, 双亲遗传相似性系数仅为0.44, 表明孝感麦与蜀麦753在分子水平上遗传差异大。蜀麦753/孝感麦衍生品系在全基因组分子水平上与其系谱血缘构成基本吻合, 偏分离现象并不明显。基于标记-表型全基因组关联分析, 共鉴定出127个与株高(14个)、穗长(12个)、小穗数(21个)、有效分蘖(20个)、千粒重(25个)及相对籽粒发芽指数(35个)显著相关的染色体区段(位点)。亲本遗传贡献分析发现, 农家种孝感麦和蜀麦753传递至衍生品系的SNP位点占比变幅分别为7.88%~43.95%和56.05%~92.12%, 其平均占比分别为26.45%和73.55%。在衍生品系中, 共鉴定出来自孝感麦和蜀麦753染色体区段大小不等(0.01~108.75 Mb)、贡献率≥ 80%的高频选择区段分别为86个和259个, 且呈不均匀状态分布于小麦基因组的21条染色体上。结合全基因组关联分析发现, 来自孝感麦及蜀麦753的43个高频选择染色体区段与株高、穗长、小穗数、有效分蘖、千粒重及相对籽粒发芽指数显著相关, 其中, 16个区段同时控制着2个或以上性状, 具有多效性。进一步对14个优异衍生品系中的高频选择染色体区段遗传构成进行分析, 发现这些与重要产量相关性状显著关联的高频选择染色体区段在衍生后代中的优先传递及作为主要靶点进行定向选择, 是成功利用农家种孝感麦改良蜀麦753的产量结构并实现了产量与抗病耐逆协同改良的根本所在。

关键词: 小麦农家种, 遗传构成, 育种目标性状, 染色体区段, 55K液相SNP芯片

Abstract:

The wheat landrace Xiaoganmai (ZM011362), originating from Dangyang, Hubei Province, exhibits multiple desirable traits, including multi-floret and high-grain-number characteristics, numerous effective tillers, stable pre-harvest sprouting resistance, and adult-plant resistance to stripe rust, making it a potentially valuable germplasm resource for modern wheat breeding. In a previous study, 178 Shumai 753/Xiaoganmai-derived lines were developed using Xiaoganmai as the donor parent and the elite breeding line Shumai 753, which carries all-stage stripe rust resistance genes and shows good overall agronomic performance, as the recurrent parent through hybridization, backcrossing, continuous multi-generation selfing, and a segmented target-trait selection strategy. This study aimed to dissect the genetic basis of the Shumai 753/Xiaoganmai-derived lines at the molecular level, identify key chromosomal regions controlling yield, disease resistance, and stress tolerance, and provide molecular evidence for the genetic improvement of wheat using landraces. Whole-genome scans of Xiaoganmai, Shumai 753, and their 178 derivative lines were performed using the wheat 55K liquid SNP array, and a total of 52,779 valid homozygous polymorphic SNP loci were obtained. Genetic similarity and genetic composition of the parents and derivative lines were analyzed based on these polymorphic SNP loci. The genetic similarity coefficient between the two parents was only 0.44, indicating substantial genetic divergence between Xiaoganmai and Shumai 753 at the molecular level. Analysis of the genetic similarity and composition of the derivative lines showed that their whole-genome molecular profiles were largely consistent with their pedigree background, with no obvious bias in parental inheritance. Based on marker-trait genome-wide association analysis, 127 chromosomal regions or loci significantly associated with plant height (14), spike length (12), spikelet number per spike (21), effective tiller number (20), thousand-grain weight (25), and relative seed germination index (35) were identified. Analysis of parental genetic contributions revealed that the proportions of SNP loci inherited from Xiaoganmai and Shumai 753 in the derivative lines ranged from 7.88% to 43.95% and from 56.05% to 92.12%, with average proportions of 26.45% and 73.55%, respectively. In total, 86 and 259 high-frequency selected regions derived from Xiaoganmai and Shumai 753, respectively, with sizes ranging from 0.01 to 108.75 Mb and contribution rates ≥80%, were identified in the derivative lines and were unevenly distributed across the 21 wheat chromosomes. Combined with the genome-wide association mapping results, 43 high-frequency selected chromosomal regions derived from Xiaoganmai and Shumai 753 were significantly associated with plant height, spike length, spikelet number per spike, effective tiller number, thousand-grain weight, and relative seed germination index. Among these regions, 16 simultaneously controlled two or more traits, indicating pleiotropic effects. Further analysis of the genetic composition of high-frequency selected chromosomal regions in 14 elite derivative lines revealed that the preferential transmission of regions significantly associated with important yield-related traits, together with their targeted selection as key loci, underlies the successful utilization of the landrace Xiaoganmai to improve the yield structure of Shumai 753 and ultimately achieve coordinated improvement in yield, disease resistance, and stress tolerance.

Key words: wheat landrace, genetic component, breeding-target trait, chromosomal region, 55K liquid SNP array

图1

有效SNP位点在染色体上的分布"

图2

基于有效SNP位点对孝感麦、蜀麦753及其衍生品系的聚类分析 XG为孝感麦,SM753为蜀麦753;XG1-XG178代表蜀麦753/孝感麦衍生品系。"

表1

178份蜀麦753/孝感麦衍生品系重要育种目标性状全基因组关联分析"

性状
Trait
染色体
Chromosome
物理位置
Physical location (Mb)
SNP标记
SNP marker
位点来源
Origin of loci
贡献率
PVE (%)
效应值
Effect size
株高
PH
1A 505.77-506.89 1A_506515648-1A_506875512 蜀麦753
Shumai 753
14.73 -6.17
1A 537.47-541.80 1A_537553183-1A_542792251 8.72 -5.91
1B 346.59 1B_346589573 11.50 -3.53
1B 670.58-671.00 1B_670484381-1B_671554575 15.38 -7.59
1D 416.71 1D_416708035 10.86 -1.09
2B 165.96-166.35 2B_165964924-2B_166348576 8.22 -1.99
4A 751.83 4A_751827370 9.90 -6.87
4B 39.67-56.99 4B_39673795-4B_56997731 13.36 -7.07
4B 560.05-560.11 4B_560047443-4B_560106960 10.87 -3.47
4D 338.47-345.03 4D_338469331-4D_345027205 12.68 -1.57
5B 686.09-687.88 5B_686097427-5B_687879512 13.98 -6.16
6B 20.51-30.94 6B_20508577-6B_30935276 11.24 -3.40
6B 30.80-30.87 6B_30798633-6B_30869525 12.21 -2.81
7B 89.04-89.27 7B_89044330-7B_89268377 9.96 -2.41
穗长
SL
1B 508.73-538.98 1B_508002028-1B_540662511 蜀麦753
Shumai 753
11.33 1.61
1B 518.05 1B_518049414 12.72 1.90
1B 536.58 1B_536583042 9.06 2.12
1D 19.54 1D_19540914 12.09 1.48
1D 18.17-20.46 1D_18165741-1D_20446525 11.41 1.03
2A 781.67-785.13 2A_781665327-2A_785134205 14.76 3.77
2A 753.04-753.11 2A_753037657-2A_753110905 12.03 2.48
2B 192.77-216.82 2B_192766206-2B_216815508 11.69 0.50
4D 338.55-345.03 4D_338469331-4D_345027205 9.09 1.32
5B 448.57-463.51 5B_448572520-5B_463512589 9.94 2.43
6B 45.49 6B_45487968 12.02 1.75
7D 177.72-201.40 7D_177720351-7D_201399390 13.96 0.50
小穗数
NS
1B 34.09-36.18 1B_34087138-1B_36675048 孝感麦
Xiaoganmai
12.01 1.40
2B 60.13 2B_60129937 10.36 1.49
2D 138.97-143.23 2D_138970337-2D_143230708 7.64 1.36
3A 727.71-741.60 3A_727714919-3A_741602897 9.60 2.42
3A 701.08-703.91 3A_701084244-3A_707937650 12.35 1.58
3D 602.63-614.18 3D_602630974-3D_614175276 11.02 1.14
3D 554.20-556.91 3D_554200344-3D_556906014 12.41 1.60
4B 387.86-400.36 4B_387863420-4B_400357533 13.01 1.82
4D 2.51-4.08 4D_2509697-4D_4080175 14.52 1.04
4D 502.53-505.48 4D_502534085-4D_505482146 11.08 0.29
5B 58.52-62.03 5B_58519584-5B_62030504 9.49 1.64
5B 234.07-234.29 5B_234037645-5B_248867068 12.29 1.57
5B 420.44-425.37 5B_420327311-5B_425366028 13.27 1.56
5B 598.67-603.10 5B_598674322-5B_603454998 12.31 1.12
5B 668.98-673.47 5B_668976051-5B_673470410 11.67 1.44
5B 625.25-655.58 5B_625250023-5B_655579218 12.38 1.62
5D 236.60-244.79 5D_236599567-5D_244789232 10.40 1.61
5D 547.01-557.57 5D_547701647-5D_557566457 12.09 1.50
6A 1.40-1.76 6A_1402208-6A_1764936 7.72 1.37
7A 573.73-574.05 7A_574733874-7A_574004138 8.56 1.33
7B 680.95-695.60 7B_674236518-7B_696712991 9.19 1.14
有效分蘖
ETN
1D 244.55 1D_244524282 孝感麦
Xiaoganmai
11.20 2.03
2A 169.79-170.97 2A_169787228-2A_170971438 7.98 1.44
2D 342.96-360.28 2D_342959813-2D_360283509 11.53 1.26
3A 709.73-752.01 3A_709734991-3A_752012897 13.15 3.21
3A 727.71-741.60 3A_727708786-3A_741599101 11.22 1.07
3B 666.25-666.36 3B_666253086-3B_666362306 7.41 0.96
3D 602.63-614.18 3D_602630989-3D_619470276 16.01 1.08
4D 2.51-4.08 4D_2509728-4D_4317185 11.52 1.19
5A 667.47-712.17 5A_667465482-5A_712166943 10.98 1.30
5B 234.07-234.29 5B_230016625-5B_234648725 8.04 1.34
5B 420.44-425.37 5B_420440463-5B_425374816 7.27 1.30
5B 668.98-673.47 5B_659708238-5B_674599124 12.01 1.62
5B 598.67-603.10 5B_598671518-5B_603414385 13.08 2.15
5B 625.25-655.58 5B_625250045-5B_673875416 11.70 1.12
5D 547.01-557.57 5D_537701696-5D_558826457 12.15 1.27
6A 301.10-305.06 6A_301102120-6A_305057996 8.99 1.39
7A 501.94-504.85 7A_501019473-7A_506242999 9.86 1.28
7A 575.58-586.99 7A_574023878-7A_587461029 14.43 0.86
7B 680.95-695.60 7B_680948123-7B_697712932 11.69 1.30
7D 8.63-11.63 7D_8625395-7D_11631717 9.20 1.37
千粒重
TGW
1A 495.20-495.26 1A_495197351-1A_495264890 蜀麦753
Shumai 753
15.22 5.63
1A 535.43 1A_535438599 12.85 3.48
1B 696.63-696.70 1B_696635343-1B_696696335 11.53 1.99
2B 747.73 2B_747726725 12.35 3.90
2B 757.62 2B_757616431 13.31 3.82
2B 773.28 2B_773275836 13.29 3.78
4A 543.93-544.74 4A_543931465-4A_544742207 11.53 1.99
4B 39.67-56.99 4B_39203795-4B_58487731 8.83 4.42
4B 657.89 4B_657891306 11.04 2.86
4B 426.54 4B_426540892 14.62 2.12
5B 440.23-442.76 5B_440227955-5B_442759200 13.35 2.96
5B 534.73-542.43 5B_532676798-5B_545676966 7.41 3.04
5B 541.99 5B_541993106 16.49 2.67
5B 686.09-687.88 5B_686887427-5B_687884590 12.09 3.41
6B 20.51-30.94 6B_19668387-6B_34668463 17.42 5.08
1A 476.41-485.20 1A_476410898-1A_486380995 孝感麦
Xiaoganmai
13.80 2.02
1A 548.57 1A_548574481 10.55 3.67
3B 23.54 3B_23536164 9.29 1.94
3B 586.10 3B_586096691 14.15 1.34
5B 137.69-138.43 5B_137686239-5B_138428082 9.26 1.88
5B 420.44-425.37 5B_425992399-5B_426177431 10.74 4.09
5B 631.73-646.49 5B_630676252-5B_648686730 15.19 5.62
5D 553.24 5D_553241485 11.39 5.56
7A 501.90-516.44 7A_500917903-7A_520063412 7.98 1.66
7A 715.00-726.35 7A_714657615-7A_731665497 10.11 2.74
相对籽粒发芽指数
RSGI
1A 13.28-22.10 1A_13276331-1A_23576403 孝感麦
Xiaoganmai
9.35 -0.39
1A 42.09 1A_42085827 8.02 -0.49
1A 476.41-485.20 1A_475345497-1A_489353005 6.68 -0.93
1A 484.37-484.38 1A_484371829-1A_484380937 12.14 -2.14
1A 559.91-561.09 1A_559127900-1A_560932514 11.58 -0.25
2A 749.02-752.22 2A_748830046-2A_753436048 16.24 -1.11
2D 66.38-71.69 2D_66378429-2D_73460264 7.90 -0.18
2D 305.99 2D_305988045 9.45 -0.71
2D 609.69 2D_609685229 8.02 -0.22
3A 23.46 3A_23457903 12.30 -0.51
3A 727.71-741.60 3A_727942947-3A_741692968 13.81 -0.33
3D 602.63-614.18 3D_607260300-3D_617882100 10.57 -0.15
4D 2.51-4.08 4D_2509805-4D_4245285 9.48 -0.38
5A 28.04-34.04 5A_23555404-5A_31682098 9.35 -0.46
5B 39.40-49.61 5B_39399386-5B_55208825 8.18 -1.90
5B 234.07-234.29 5B_234062573-5B_234267936 10.45 -0.95
5B 420.44-425.37 5B_420440463-5B_428163623 13.12 -1.40
5B 547.63-565.62 5B_547771476-5B_566520011 10.02 -0.35
5B 566.21 5B_566206942 11.35 -1.18
5B 580.37-580.68 5B_579801844-5B_580751911 12.68 -0.36
5B 598.67-603.10 5B_598671562-5B_603680998 11.67 -1.58
5B 625.25-626.67 5B_623483228-5B_626681099 9.56 -0.30
5B 648.16-655.58 5B_646491015-5B_658163623 7.52 -0.48
5B 668.98-673.47 5B_668983049-5B_675983231 10.38 -0.24
5D 547.01-557.57 5D_545208825-5D_559035730 14.45 -1.24
5D 566.71 5D_566705595 9.40 -0.24
6B 126.39-127.90 6B_124267269-6B_127899708 7.58 -0.55
7A 15.13-16.78 7A_13457338-7A_16928345 9.30 -0.45
7A 501.90-516.44 7A_501935372-7A_522628657 14.44 -0.25
7A 621.25 7A_621252139 9.51 -0.24
7A 715.00-726.35 7A_706242963-7A_727207111 16.28 -0.25
7B 680.95-695.60 7B_674236518-7B_700948194 10.29 -0.31
7B 710.21 7B_710213115-7B_710213183 11.79 -0.19
7D 91.09-94.38 7D_91070058-7D_99670088 12.95 -0.83
7D 106.64 7D_106642434 10.06 -0.16

附表1

蜀麦753和小麦农家种孝感麦对其178个衍生品系遗传贡献率"

衍生品系
Derivative line
蜀麦753 Shumai 753 孝感麦 Xiaoganmai
A基因组
A genome
B基因组
B genome
D基因组
D genome
全基因组
Whole genome
A基因组
A genome
B基因组
B genome
D基因组
D genome
全基因组
Whole genome
XG1 72.09 82.20 76.72 77.94 27.91 17.80 23.28 22.06
XG2 81.26 81.29 82.77 81.43 18.74 18.71 17.23 18.57
XG3 76.38 83.64 87.62 81.37 23.62 16.36 12.38 18.63
XG4 76.05 84.66 77.15 80.80 23.95 15.34 22.85 19.20
XG5 81.16 81.35 84.90 81.62 18.84 18.65 15.10 18.38
XG6 72.53 82.72 77.01 78.42 27.47 17.28 22.99 21.58
XG7 76.77 80.90 89.50 80.26 23.23 19.10 10.50 19.74
XG8 50.70 72.68 35.58 60.74 49.30 27.32 64.42 39.26
XG9 71.15 80.73 35.82 72.80 28.85 19.27 64.18 27.20
XG10 74.67 83.55 88.34 80.68 25.33 16.45 11.66 19.32
XG11 80.04 86.03 85.32 83.66 19.96 13.97 14.68 16.34
XG12 76.98 88.28 93.29 84.36 23.02 11.72 6.71 15.64
XG13 79.29 82.76 85.66 81.74 20.71 17.24 14.34 18.26
XG14 52.87 67.02 35.71 58.86 47.13 32.98 64.29 41.14
XG15 52.83 67.04 35.66 58.85 47.17 32.96 64.34 41.15
XG16 54.68 66.14 35.77 58.83 45.32 33.86 64.23 41.17
XG17 78.90 83.67 92.34 82.65 21.10 16.33 7.66 17.35
XG18 66.22 77.90 34.31 70.37 33.78 22.10 65.69 29.63
XG19 79.72 82.12 85.81 81.58 20.28 17.88 14.19 18.42
XG20 79.65 76.97 85.85 78.81 20.35 23.03 14.15 21.19
XG21 72.51 73.51 79.25 73.71 27.49 26.49 20.75 26.29
XG22 81.16 81.31 83.76 81.49 18.84 18.69 16.24 18.51
XG23 54.31 72.92 35.65 62.45 45.69 27.08 64.35 37.55
XG24 67.15 81.18 40.53 72.09 32.85 18.82 59.47 27.91
XG25 78.49 85.09 89.22 83.07 21.51 14.91 10.78 16.93
XG26 60.67 63.28 61.23 62.13 39.33 36.72 38.77 37.87
XG27 54.55 73.57 35.60 62.86 45.45 26.43 64.40 37.14
XG28 74.25 82.34 77.01 78.87 25.75 17.66 22.99 21.13
XG29 81.00 81.72 86.09 81.89 19.00 18.28 13.91 18.11
XG30 79.53 79.66 85.48 80.21 20.47 20.34 14.52 19.79
XG31 50.38 65.28 35.55 56.80 49.62 34.72 64.45 43.20
XG32 50.27 64.38 35.56 56.35 49.73 35.62 64.44 43.65
XG33 79.70 81.12 85.27 81.00 20.30 18.88 14.73 19.00
XG34 72.55 82.75 77.01 78.45 27.45 17.25 22.99 21.55
XG35 61.65 73.57 34.41 65.37 38.35 26.43 65.59 34.63
XG36 81.27 81.26 85.00 81.63 18.73 18.74 15.00 18.37
XG37 80.94 82.39 85.53 82.14 19.06 17.61 14.47 17.86
XG38 89.12 88.40 87.05 88.56 10.88 11.60 12.95 11.44
XG39 54.89 73.51 35.54 62.94 45.11 26.49 64.46 37.06
XG40 73.13 80.91 40.34 74.11 26.87 19.09 59.66 25.89
XG41 91.84 92.44 90.03 92.12 8.16 7.56 9.97 7.88
XG42 70.20 74.97 35.85 69.33 29.80 25.03 64.15 30.67
XG43 72.54 82.73 76.89 78.43 27.46 17.27 23.11 21.57
XG44 81.31 81.35 84.77 81.67 18.69 18.65 15.23 18.33
XG45 61.05 73.12 35.67 65.07 38.95 26.88 64.33 34.93
XG46 71.31 78.85 35.83 71.78 28.69 21.15 64.17 28.22
XG47 79.74 83.66 85.45 82.38 20.26 16.34 14.55 17.62
XG48 50.65 73.00 35.58 60.98 49.35 27.00 64.42 39.02
XG49 69.06 73.14 41.88 68.58 30.94 26.86 58.12 31.42
XG50 70.11 77.41 40.09 71.08 29.89 22.59 59.91 28.92
XG51 66.98 71.92 42.63 67.13 33.02 28.08 57.37 32.87
XG52 68.19 73.89 44.49 68.91 31.81 26.11 55.51 31.09
XG53 78.13 88.08 93.90 84.89 21.87 11.92 6.10 15.11
XG54 78.67 78.88 86.66 79.57 21.33 21.12 13.34 20.43
XG55 61.25 72.93 34.38 64.92 38.75 27.07 65.62 35.08
XG56 50.63 72.90 35.63 60.92 49.37 27.10 64.37 39.08
XG57 82.40 92.32 81.69 87.92 17.60 7.68 18.31 12.08
XG58 80.03 74.90 85.31 77.88 19.97 25.10 14.69 22.12
XG59 64.35 77.60 40.44 69.15 35.65 22.40 59.56 30.85
XG60 76.30 85.06 77.02 81.13 23.70 14.94 22.98 18.87
XG61 70.34 85.22 70.97 79.15 29.66 14.78 29.03 20.85
XG62 50.46 66.76 35.66 57.73 49.54 33.24 64.34 42.27
XG63 60.03 73.69 43.76 65.78 39.97 26.31 56.24 34.22
XG64 76.21 84.76 42.12 77.91 23.79 15.24 57.88 22.09
XG65 77.60 84.62 77.21 81.31 22.40 15.38 22.79 18.69
XG66 81.39 80.98 82.61 81.29 18.61 19.02 17.39 18.71
XG67 77.52 83.79 76.79 80.85 22.48 16.21 23.21 19.15
XG68 72.47 82.68 76.76 78.36 27.53 17.32 23.24 21.64
XG69 49.63 73.58 36.14 61.69 50.37 26.42 63.86 38.31
XG70 54.63 70.83 35.51 60.95 45.37 29.17 64.49 39.05
XG71 53.02 70.86 35.54 60.99 46.98 29.14 64.46 39.01
XG72 79.50 82.91 86.02 81.92 20.50 17.09 13.98 18.08
XG73 76.07 87.53 68.76 82.45 23.93 12.47 31.24 17.55
XG74 67.87 73.25 36.68 67.88 32.13 26.75 63.32 32.12
XG75 72.54 82.72 76.95 78.43 27.46 17.28 23.05 21.57
XG76 65.44 73.55 35.30 66.81 34.56 26.45 64.70 33.19
XG77 79.83 75.68 85.32 78.20 20.17 24.32 14.68 21.80
XG78 70.39 74.86 41.86 69.96 29.61 25.14 58.14 30.04
XG79 72.40 82.68 76.90 78.36 27.60 17.32 23.10 21.64
XG80 64.21 73.36 34.48 66.26 35.79 26.64 65.52 33.74
XG81 83.69 79.67 78.86 81.09 16.31 20.33 21.14 18.91
XG82 70.74 71.74 34.59 67.44 29.26 28.26 65.41 32.56
XG83 52.68 71.78 35.51 60.98 47.32 28.22 64.49 39.02
XG84 72.48 73.50 79.36 73.71 27.52 26.50 20.64 26.29
XG85 55.39 73.58 35.29 63.17 44.61 26.42 64.71 36.83
XG86 68.59 73.37 37.64 68.39 31.41 26.63 62.36 31.61
XG87 70.87 80.16 34.83 72.00 29.13 19.84 65.17 28.00
XG88 72.37 73.35 40.39 69.69 27.63 26.65 59.61 30.31
XG89 63.95 73.35 34.03 66.12 36.05 26.65 65.97 33.88
XG90 73.35 79.57 37.97 73.17 26.65 20.43 62.03 26.83
XG91 77.32 80.98 88.01 80.26 22.68 19.02 11.99 19.74
XG92 77.78 83.25 89.28 81.82 22.22 16.75 10.72 18.18
XG93 76.53 80.90 87.94 79.93 23.47 19.10 12.06 20.07
XG94 67.07 74.98 41.65 68.82 32.93 25.02 58.35 31.18
XG95 81.33 81.06 85.47 81.59 18.67 18.94 14.53 18.41
XG96 69.55 73.14 34.12 67.97 30.45 26.86 65.88 32.03
XG97 68.00 73.91 41.74 68.60 32.00 26.09 58.26 31.40
XG98 75.19 71.82 40.37 69.94 24.81 28.18 59.63 30.06
XG99 55.59 72.69 34.63 62.80 44.41 27.31 65.37 37.20
XG100 74.38 73.91 41.40 70.97 25.62 26.09 58.60 29.03
XG101 58.02 70.97 36.76 63.20 41.98 29.03 63.24 36.80
XG102 59.10 73.59 34.44 64.53 40.90 26.41 65.56 35.47
XG103 54.17 73.24 35.51 62.55 45.83 26.76 64.49 37.45
XG104 54.63 70.54 35.52 61.29 45.37 29.46 64.48 38.71
XG105 69.91 73.44 34.09 68.28 30.09 26.56 65.91 31.72
XG106 77.77 84.88 89.36 82.77 22.23 15.12 10.64 17.23
XG107 72.30 76.74 41.71 71.69 27.70 23.26 58.29 28.31
XG108 79.35 83.70 85.21 82.23 20.65 16.30 14.79 17.77
XG109 83.80 87.07 74.53 84.97 16.20 12.93 25.47 15.03
XG110 75.22 73.93 43.43 71.42 24.78 26.07 56.57 28.58
XG111 81.29 81.25 85.37 81.66 18.71 18.75 14.63 18.34
XG112 70.68 74.17 41.86 69.73 29.32 25.83 58.14 30.27
XG113 72.88 84.68 76.87 79.56 27.12 15.32 23.13 20.44
XG114 90.02 93.00 90.55 91.83 9.98 7.00 9.45 8.17
XG115 77.56 83.97 76.91 80.97 22.44 16.03 23.09 19.03
XG116 79.81 79.51 85.27 80.20 20.19 20.49 14.73 19.80
XG117 80.45 81.50 85.93 81.55 19.55 18.50 14.07 18.45
XG118 50.57 71.95 35.59 60.56 49.43 28.05 64.41 39.44
XG119 78.87 92.01 82.10 87.43 21.13 7.99 17.90 12.57
XG120 78.90 81.70 85.83 81.06 21.10 18.30 14.17 18.94
XG121 79.62 81.47 85.24 81.16 20.38 18.53 14.76 18.84
XG122 79.64 78.63 85.63 79.72 20.36 21.37 14.37 20.28
XG123 74.38 80.86 87.63 79.05 25.62 19.14 12.37 20.95
XG124 79.26 84.06 85.77 82.47 20.74 15.94 14.23 17.53
XG125 72.99 85.05 77.16 79.87 27.01 14.95 22.84 20.13
XG126 81.03 81.33 86.05 81.68 18.97 18.67 13.95 18.32
XG127 75.97 73.37 35.59 70.80 24.03 26.63 64.41 29.20
XG128 75.84 82.63 77.22 79.65 24.16 17.37 22.78 20.35
XG129 74.66 85.05 89.31 81.66 25.34 14.95 10.69 18.34
XG130 78.29 84.14 57.02 79.66 21.71 15.86 42.98 20.34
XG131 81.12 81.20 86.10 81.65 18.88 18.80 13.90 18.35
XG132 67.19 80.13 40.50 71.47 32.81 19.87 59.50 28.53
XG133 79.10 80.26 85.92 80.39 20.90 19.74 14.08 19.61
XG134 74.63 83.70 80.61 80.07 25.37 16.30 19.39 19.93
XG135 72.49 73.40 79.22 73.64 27.51 26.60 20.78 26.36
XG136 78.10 84.31 89.30 82.53 21.90 15.69 10.70 17.47
XG137 66.42 73.29 35.32 67.06 33.58 26.71 64.68 32.94
XG138 76.30 77.38 40.05 73.29 23.70 22.62 59.95 26.71
XG139 52.76 70.48 35.52 60.27 47.24 29.52 64.48 39.73
XG140 78.40 84.89 76.75 81.71 21.60 15.11 23.25 18.29
XG141 75.77 73.93 34.56 70.76 24.23 26.07 65.44 29.24
XG142 62.75 80.32 36.98 69.70 37.25 19.68 63.02 30.30
XG143 79.73 72.90 85.25 76.63 20.27 27.10 14.75 23.37
XG144 79.23 83.35 48.79 78.84 20.77 16.65 51.21 21.16
XG145 69.49 73.24 34.26 68.06 30.51 26.76 65.74 31.94
XG146 93.98 91.75 70.86 90.87 6.02 8.25 29.14 9.13
XG147 50.53 66.92 35.70 57.85 49.47 33.08 64.30 42.15
XG148 72.54 73.47 79.30 73.70 27.46 26.53 20.70 26.30
XG149 60.74 63.37 61.35 62.21 39.26 36.63 38.65 37.79
XG150 60.03 73.17 34.81 64.72 39.97 26.83 65.19 35.28
XG151 71.09 80.33 37.29 72.76 28.91 19.67 62.71 27.24
XG152 70.80 73.67 44.59 69.71 29.20 26.33 55.41 30.29
XG153 65.07 73.41 35.37 66.61 34.93 26.59 64.63 33.39
XG154 72.46 73.56 44.51 70.26 27.54 26.44 55.49 29.74
XG155 50.79 70.20 35.51 59.68 49.21 29.80 64.49 40.32
XG156 72.52 82.78 77.04 78.46 27.48 17.22 22.96 21.54
XG157 75.58 74.01 42.35 71.54 24.42 25.99 57.65 28.46
XG158 79.53 78.49 95.08 80.63 20.47 21.51 4.92 19.37
XG159 54.68 64.31 35.62 57.97 45.32 35.69 64.38 42.03
XG160 62.38 73.54 37.55 66.47 37.62 26.46 62.45 33.53
XG161 70.38 73.73 44.04 69.57 29.62 26.27 55.96 30.43
XG162 58.01 64.07 35.07 59.05 41.99 35.93 64.93 40.95
XG163 75.44 79.15 42.01 73.68 24.56 20.85 57.99 26.32
XG164 50.39 63.70 35.44 56.05 49.61 36.30 64.56 43.95
XG165 76.56 73.78 37.36 71.23 23.44 26.22 62.64 28.77
XG166 79.83 80.38 85.22 80.65 20.17 19.62 14.78 19.35
XG167 67.89 73.53 35.18 67.68 32.11 26.47 64.82 32.32
XG168 50.55 73.61 35.52 61.38 49.45 26.39 64.48 38.62
XG169 53.31 64.75 35.66 57.75 46.69 35.25 64.34 42.25
XG170 81.89 90.82 82.93 86.48 18.11 9.18 17.07 13.52
XG171 80.55 81.96 84.10 81.66 19.45 18.04 15.90 18.34
XG172 54.46 72.57 35.70 62.34 45.54 27.43 64.30 37.66
XG173 52.46 66.18 35.78 58.16 47.54 33.82 64.22 41.84
XG174 52.74 77.59 47.26 66.00 47.26 22.41 52.74 34.00
XG175 72.54 82.66 77.06 78.40 27.46 17.34 22.94 21.60
XG176 77.58 80.87 76.84 79.27 22.42 19.13 23.16 20.73
XG177 90.18 89.71 85.37 89.39 9.82 10.29 14.63 10.61
XG178 76.69 82.52 76.98 79.82 23.31 17.48 23.02 20.18
平均值
Average value (%)
70.67 77.90 60.13 73.55 29.33 22.10 39.78 26.45
理论值
Theoretical value (%)
75.00 75.00 75.00 75.00 25.00 25.00 25.00 25.00

表2

蜀麦753或小麦农家种孝感麦高频选择区段在基因组及染色体上的分布"

亚基因组
Sub-genome
染色体
Chromosome
孝感麦
Xiaoganmai
蜀麦753
Shumai 753
合计
Total
片段长度
Fragment length (Mb)
A亚基因组
A sub-genome
1A 11 18 29 0.05-19.09
2A 2 16 18 0.12-12.80
3A 9 19 28 0.20-23.40
4A 1 14 15 0.29-26.50
5A 8 9 17 0.01-57.51
6A 0 1 1 6.26
7A 15 10 25 0.19-11.42
合计Total 46 87 133
B亚基因组
B sub-genome
1B 0 26 26 0.42-34.03
2B 0 26 26 0.45-50.54
3B 4 19 23 1.13-35.98
4B 0 21 21 0.01-18.95
5B 13 18 31 0.23-14.94
6B 3 34 37 0.31-42.99
7B 3 1 4 0.86-14.66
合计Total 23 145 168
D亚基因组
D sub-genome
1D 2 9 11 0.53-16.52
2D 6 2 8 0.57-12.76
3D 3 0 3 0.15-6.92
4D 2 2 4 0.74-23.48
5D 3 1 4 2.43-19.64
6D 0 4 4 0.01-0.98
7D 1 9 10 1.36-108.75
合计Total 17 27 44

图3

蜀麦753或小麦农家种孝感麦高频选择区段在染色体上的分布 XG为孝感麦, SM753为蜀麦753; 蓝色和深红色区段分别代表来自农家种孝感麦和蜀麦753的高频选择区段, 灰色区段代表来自农家种孝感麦或蜀麦753的非高频选择区段。"

表3

高频选择片段与表型关联分析"

性状
Trait
物理位置
Physical location (Mb)
片段大小
Fragment size (Mb)
染色体
Chromosome
片段来源
Origin of fragment
株高PH 505.77-506.85 1.08 1A 蜀麦753 Shumai 753
537.47-541.80 4.33 1A 蜀麦753 Shumai 753
670.58-671.00 0.42 1B 蜀麦753 Shumai 753
穗长SL 508.73-538.98 30.25 1B 蜀麦753 Shumai 753
18.17-20.46 2.29 1D 蜀麦753 Shumai 753
781.67-785.13 3.46 2A 蜀麦753 Shumai 753
192.77-216.82 24.06 2B 蜀麦753 Shumai 753
448.57-463.51 14.94 5B 蜀麦753 Shumai 753
177.72-201.40 23.68 7D 蜀麦753 Shumai 753
小穗数NS 573.73-574.05 0.32 7A 孝感麦 Xiaoganmai
有效分蘖ETN 501.94-504.85 2.92 7A 孝感麦 Xiaoganmai
575.58-586.99 11.42 7A 孝感麦 Xiaoganmai
千粒重TGW 631.73-646.49 14.76 5B 孝感麦 Xiaoganmai
534.73-542.43 7.70 5B 蜀麦753 Shumai 753
相对籽粒发芽指数RSGI 559.91-561.09 1.18 1A 孝感麦 Xiaoganmai
13.28-22.10 8.82 1A 孝感麦 Xiaoganmai
749.02-752.22 3.20 2A 孝感麦 Xiaoganmai
66.38-71.69 5.31 2D 孝感麦 Xiaoganmai
28.04-34.04 6.00 5A 孝感麦 Xiaoganmai
580.37-580.68 0.32 5B 孝感麦 Xiaoganmai
625.25-626.67 1.42 5B 孝感麦 Xiaoganmai
648.16-655.58 7.42 5B 孝感麦 Xiaoganmai
39.40-49.61 10.21 5B 孝感麦 Xiaoganmai
547.63-565.62 17.99 5B 孝感麦 Xiaoganmai
126.39-127.90 1.51 6B 孝感麦 Xiaoganmai
15.13-16.78 1.65 7A 孝感麦 Xiaoganmai
91.09-94.38 3.29 7D 孝感麦 Xiaoganmai
株高、千粒重 PH, TGW 39.67-56.99 17.33 4B 蜀麦753 Shumai 753
686.09-687.88 1.79 5B 蜀麦753 Shumai 753
20.51-30.94 10.43 6B 蜀麦753 Shumai 753
千粒重、相对籽粒发芽指数TGW, RSGI 715.00-726.35 11.35 7A 孝感麦 Xiaoganmai
501.90-516.44 14.54 7A 孝感麦 Xiaoganmai
476.41-485.20 8.79 1A 孝感麦 Xiaoganmai
小穗数、有效分蘖NS, ETN 625.25-655.58 30.33 5B 孝感麦 Xiaoganmai
小穗数、有效分蘖、相对籽粒发芽指数
NS, ETN, RSGI
727.71-741.60 13.89 3A 孝感麦 Xiaoganmai
602.63-614.18 11.55 3D 孝感麦 Xiaoganmai
2.51-4.08 1.57 4D 孝感麦 Xiaoganmai
234.07-234.29 0.23 5B 孝感麦 Xiaoganmai
598.67-603.10 4.42 5B 孝感麦 Xiaoganmai
668.98-673.47 4.49 5B 孝感麦 Xiaoganmai
680.95-695.60 14.66 7B 孝感麦 Xiaoganmai
小穗数、有效分蘖、千粒重、相对籽粒发芽指数NS, ETN, TGW, RSGI 420.44-425.37 4.93 5B 孝感麦 Xiaoganmai
547.01-557.57 10.56 5D 孝感麦 Xiaoganmai

表4

蜀麦753高频选择染色体区段在其14个优异衍生品系中的分布"

亚基因组
Sub-genome
染色体
Chromosome
XG9 XG11 XG12 XG35 XG52 XG95 XG139
A亚基因组
A sub-genome
1A 16 6 6 17 17 8 17
2A 17 13 11 25 8 14 10
3A 16 15 12 18 18 20 18
4A 14 10 1 14 14 10 14
5A 8 7 9 8 8 6 8
6A 0 0 1 0 0 0 0
7A 9 4 9 9 10 5 9
合计Total 80 55 49 91 75 63 76
B亚基因组
B sub-genome
1B 25 12 2 25 25 23 25
2B 23 22 11 26 26 26 26
3B 15 11 14 16 17 12 8
4B 21 14 2 21 20 18 21
5B 21 9 2 17 18 9 18
6B 32 14 14 30 31 32 28
7B 1 1 0 1 1 1 1
合计Total 138 83 45 136 138 121 127
D亚基因组
D sub-genome
1D 8 8 2 8 8 9 7
2D 1 1 3 1 1 1 1
3D 0 0 0 0 0 0 0
4D 2 1 0 2 2 1 2
5D 1 1 0 1 0 9 1
6D 1 3 4 2 4 3 4
7D 8 4 6 6 7 7 6
合计Total 21 18 15 20 22 30 21
亚基因组
Sub-genome
染色体
Chromosome
XG141 XG142 XG147 XG151 XG154 XG157 XG164
A亚基因组
A sub-genome
1A 17 14 16 14 17 16 16
2A 17 17 10 16 17 17 10
3A 18 16 18 14 18 18 18
4A 14 14 14 14 14 14 14
5A 8 3 8 4 8 8 8
6A 0 0 0 0 0 0 0
7A 17 10 9 9 10 9 9
合计Total 91 74 75 71 84 82 75
B亚基因组
B sub-genome
1B 25 25 25 25 25 25 25
2B 26 26 26 26 26 26 26
3B 17 12 7 13 17 17 4
4B 21 21 21 21 21 21 20
5B 18 23 18 22 18 18 18
6B 31 32 29 32 31 30 28
7B 1 1 1 1 1 1 1
合计Total 139 140 127 140 139 138 122
D亚基因组
D sub-genome
1D 8 7 7 7 8 8 7
2D 1 1 1 1 1 1 1
3D 0 0 0 0 0 0 0
4D 2 2 2 2 2 2 2
5D 1 1 1 1 1 1 1
6D 1 4 3 4 4 2 4
7D 7 7 6 7 7 7 6
合计Total 20 22 20 22 23 21 21

表5

小麦农家种孝感麦高频选择染色体区段在其14个优异衍生品系中的分布"

亚基因组
Sub-genome
染色体
Chromosome
XG9 XG11 XG12 XG35 XG52 XG95 XG139
A亚基因组
A sub-genome
1A 8 5 3 8 8 5 8
2A 1 2 0 3 7 2 2
3A 10 5 1 10 9 6 10
4A 1 1 1 1 1 2 1
5A 2 1 1 2 2 6 2
6A 0 0 0 0 0 0 0
7A 5 10 1 6 15 10 15
合计Total 27 24 7 30 42 31 38
B亚基因组
B sub-genome
1B 0 0 0 0 0 0 0
2B 3 0 0 0 0 0 0
3B 2 2 0 0 0 2 0
4B 0 0 1 0 0 0 0
5B 8 0 0 12 12 4 12
B亚基因组
B sub-genome
6B 2 0 2 3 3 2 6
7B 2 1 0 3 3 1 3
合计Total 17 3 3 18 18 9 21
D亚基因组
D sub-genome
1D 0 0 0 0 0 0 0
2D 6 5 4 6 5 5 6
3D 3 2 0 3 3 2 3
4D 2 2 0 2 2 2 2
5D 2 0 0 2 2 0 2
6D 3 0 0 0 0 0 0
7D 1 0 0 1 1 0 1
合计Total 17 9 4 14 13 9 14
亚基因组
Sub-genome
染色体
Chromosome
XG141 XG142 XG147 XG151 XG154 XG157 XG164
A亚基因组
A sub-genome
1A 8 10 9 10 8 9 9
2A 1 1 7 2 1 1 7
3A 9 10 10 12 9 10 9
4A 1 1 1 1 1 1 1
5A 2 10 2 9 2 2 2
6A 0 0 0 0 0 0 0
7A 6 6 15 5 15 6 15
合计Total 27 38 44 39 36 29 43
B亚基因组
B sub-genome
1B 0 0 0 0 0 0 0
2B 0 0 0 0 0 0 0
3B 0 4 14 4 0 0 17
4B 0 0 0 0 0 0 0
5B 12 7 12 7 12 12 12
6B 3 2 3 2 3 3 6
7B 3 2 3 2 3 3 3
合计Total 18 15 32 15 18 18 38
D亚基因组
D sub-genome
1D 0 0 0 0 0 0 0
2D 6 6 6 6 5 5 6
3D 3 3 3 3 3 3 3
4D 2 2 2 2 2 2 2
5D 2 2 2 2 2 2 2
6D 3 0 0 0 0 1 0
7D 1 1 1 1 0 1 2
合计Total 17 14 14 14 12 14 15

图4

蜀麦753或小麦农家种孝感麦高频选择区段在优异衍生品系染色体上的分布 蓝色和深红色区段分别代表来自农家种孝感麦和蜀麦753的高频选择区段, 灰色区段代表来自农家种孝感麦或蜀麦753的非高频选择区段; XG为孝感麦, SM753为蜀麦753; A-N分别代表蜀麦753/孝感麦优异衍生品系XG9、XG11、XG12、XG35、XG52、XG95、XG139、XG141、XG142、XG147、XG151、XG154、XG157和XG164。"

[1] Godfray H C J, Beddington J R, Crute I R, et al. Food security: the challenge of feeding 9 billion people. Science, 2010, 327: 812-818.
doi: 10.1126/science.1185383 pmid: 20110467
[2] Tilman D, Balzer C, Hill J, et al. Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci USA, 2011, 108: 20260-20264.
doi: 10.1073/pnas.1116437108 pmid: 22106295
[3] Ray D K, Mueller N D, West P C, et al. Yield trends are insufficient to double global crop production by 2050. PLoS One, 2013, 8: e66428.
[4] Cheng S F, Feng C, Wingen L U, et al. Harnessing landrace diversity empowers wheat breeding. Nature, 2024, 632: 823-831.
doi: 10.1038/s41586-024-07682-9
[5] 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. 中国农学通报, 2016, 32(30): 7-13.
doi: 10.11924/j.issn.1000-6850.casb16060069
Pu Y Y, Gong Y C, Li N N, et al. A review of genetic diversity of wheat crops in China. Chin Agric Sci Bull, 2016, 32(30): 7-13 (in Chinese with English abstract).
doi: 10.11924/j.issn.1000-6850.casb16060069
[6] 刘三才, 郑殿升, 曹永生, 等. 中国小麦选育品种与地方品种的遗传多样性. 中国农业科学, 2000, 33: 20-24.
doi: 10.3864/j.issn.0578-1752.2000-33-4-22-26
Liu S C, Zheng D S, Cao Y S, et al. Genetic diversity of landrace and bred varieties of wheat in China. Sci Agric Sin, 2000, 33: 20-24 (in Chinese with English abstract).
[7] 郑殿升. 中国作物遗传资源的多样性. 中国农业科技导报, 2000, 2(2): 45-49.
Zheng D S. Diversity of crop genetic resources in China. J Agric Sci Technol, 2000, 2(2): 45-49 (in Chinese with English abstract).
[8] Bonman J M, Babiker E M, Cuesta-Marcos A, et al. Genetic diversity among wheat accessions from the USDA national small grains collection. Crop Sci, 2015, 55: 1243-1253.
doi: 10.2135/cropsci2014.09.0621
[9] 曹廷杰, 谢菁忠, 吴秋红, 等. 河南省近年审定小麦品种基于系谱和SNP标记的遗传多样性分析. 作物学报, 2015, 41: 197-206.
doi: 10.3724/SP.J.1006.2015.00197
Cao T J, Xie J Z, Wu Q H, et al. Genetic diversity of registered wheat varieties in Henan province based on pedigree and single-nucleotide polymorphism. Acta Agron Sin, 2015, 41: 197-206 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2015.00197
[10] 马艳明, 娄鸿耀, 陈朝燕, 等. 新疆冬小麦地方品种与育成品种基于SNP芯片的遗传多样性分析. 作物学报, 2020, 46: 1539-1556.
doi: 10.3724/SP.J.1006.2020.91077
Ma Y M, Lou H Y, Chen Z Y, et al. Genetic diversity assessment of winter wheat landraces and cultivars in Xinjiang via SNP array analysis. Acta Agron Sin, 2020, 46: 1539-1556 (in Chinese with English abstract).
[11] 程斌, 丁延庆, 曹宁, 等. 基于120K液相芯片对310份小麦种质的遗传多样性分析. 麦类作物学报, 2024, 44: 1104-1114.
Cheng B, Ding Y Q, Cao N, et al. Genetic diversity analysis of 310 wheat accessions based on 120K liquid-phase SNP array. J Triticeae Crops, 2024, 44: 1104-1114 (in Chinese with English abstract).
[12] Jaganathan D, Bohra A, Thudi M, et al. Fine mapping and gene cloning in the post-NGS era: advances and prospects. Theor Appl Genet, 2020, 133: 1791-1810.
doi: 10.1007/s00122-020-03560-w pmid: 32040676
[13] Zeng Q D, Wu J H, Huang S, et al. SNP-based linkage mapping for validation of adult plant stripe rust resistance QTL in common wheat cultivar Chakwal 86. Crop J, 2019, 7: 176-186.
doi: 10.1016/j.cj.2018.12.002
[14] Huang S, Zhang Y B, Ren H, et al. High density mapping of wheat stripe rust resistance gene QYrXN3517-1BL using QTL mapping, BSE-Seq and candidate gene analysis. Theor Appl Genet, 2023, 136: 39.
doi: 10.1007/s00122-023-04282-5 pmid: 36897402
[15] Eltaher S, Baenziger P S, Belamkar V, et al. GWAS revealed effect of genotype×environment interactions for grain yield of Nebraska winter wheat. BMC Genom, 2021, 22: 2.
doi: 10.1186/s12864-020-07308-0
[16] Joukhadar R, Hollaway G, Shi F, et al. Genome-wide association reveals a complex architecture for rust resistance in 2300 worldwide bread wheat accessions screened under various Australian conditions. Theor Appl Genet, 2020, 133: 2695-2712.
doi: 10.1007/s00122-020-03626-9 pmid: 32504212
[17] Zhang P P, Yan X C, Gebrewahid T W, et al. Genome-wide association mapping of leaf rust and stripe rust resistance in wheat accessions using the 90K SNP array. Theor Appl Genet, 2021, 134: 1233-1251.
doi: 10.1007/s00122-021-03769-3
[18] 杨子博, 王安邦, 冷苏凤, 等. 小麦新品种淮麦33的遗传构成分析. 中国农业科学, 2018, 51: 3237-3248.
doi: 10.3864/j.issn.0578-1752.2018.17.001
Yang Z B, Wang A B, Leng S F, et al. Genetic analysis of the novel high-yielding wheat cultivar Huaimai 33. Sci Agric Sin, 2018, 51: 3237-3248 (in Chinese with English abstract).
[19] 李家乐, 李绍祥, 邬陈芳, 等. 高产优质弱筋小麦新品种云麦114的遗传构成及其重要性状遗传基础解析. 种子, 2025, 44(8): 196-203.
Li J L, Li S X, Wu C F, et al. Analysis on genetic composition and genetic basis of important traits of a new high-yielding and high-quality weak-gluten wheat cultivar Yunmai 114. Seed, 2025, 44(8): 196-203 (in Chinese with English abstract).
[20] 李式昭, 王琴, 郑建敏, 等. 利用基因芯片分析西南麦区主栽小麦品种川麦104的遗传构成. 麦类作物学报, 2021, 41: 665-672.
Li S Z, Wang Q, Zheng J M, et al. Analysis of genetic components in the major wheat cultivar Chuanmai 104 in southwest wheat region based on three wheat SNP arrays. J Triticeae Crops, 2021, 41: 665-672 (in Chinese with English abstract).
[21] 王昊, 孙妮娜, 王矗, 等. 烟农系列小麦高产遗传基础解析. 作物学报, 2023, 49: 1584-1600.
doi: 10.3724/SP.J.1006.2023.21033
Wang H, Sun N N, Wang C, et al. Genetic basis analysis of high-yielding in Yannong wheat varieties. Acta Agron Sin, 2023, 49: 1584-1600 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2023.21033
[22] 陈晓杰, 范家霖, 程仲杰, 等. 高产优质中强筋小麦新品种豫丰11的遗传构成及其特异区段解析. 种子, 2023, 42(6): 14-18.
Chen X J, Fan J L, Cheng Z J, et al. Analysis on genetic component and specific regions of new wheat variety Yufeng 11 with high yield and good quality medium gluten. Seed, 2023, 42(6): 14-18 (in Chinese with English abstract).
[23] Zhou Y, Tang H, Cheng M P, et al. Genome-wide association study for pre-harvest sprouting resistance in a large germplasm collection of Chinese wheat landraces. Front Plant Sci, 2017, 8: 401.
doi: 10.3389/fpls.2017.00401 pmid: 28428791
[24] 姚方杰. 小麦种质资源条锈病抗性表型鉴定及其全基因组关联分析. 四川农业大学博士学位论文, 四川雅安, 2022.
Yao F J. Identification and Genome-Wide Association Studies of Stripe Rust Resistance in Wheat Germplasm. PhD Dissertation of Sichuan Agricultural University, Ya’an, Sichuan, China, 2022 (in Chinese with English abstract).
[25] 陈国跃, 蒋云峰, 李豪, 等. 一种利用小麦农家种进行条锈病抗性与产量协同改良创制新种质的育种方法. 中国专利: ZL202311276757.9, 2025-10-14.
Chen G Y, Jiang Y F, Li H, et al. A breeding method for creating new germplasm with coordinated improvement of stripe rust resistance and yield using wheat landraces. Chinese Patent: ZL202311276757.9, 2025-10-14 (in Chinese).
[26] 马婷婷, 郭晓江, 李豪, 等. 利用小麦农家种孝感麦协同改良蜀麦753产量与抗病耐逆性的育种实践. 作物学报, 2026, 52: 56-71.
doi: 10.3724/SP.J.1006.2026.51065
Ma T T, Guo X J, Li H, et al. Breeding strategy for synergistic improvement of yield, disease resistance, and stress tolerance in Shumai 753 using the wheat landrace Xiaoganmai. Acta Agron Sin, 2026, 52: 56-71 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2026.51065
[27] Hill-Ambroz K L, Brown-Guedira G L, Fellers J P. Modified rapid DNA extraction protocol for high throughput microsatellite analysis in wheat. Crop Sci, 2002, 42: 2088-2091.
doi: 10.2135/cropsci2002.2088
[28] Sun C W, Dong Z D, Zhao L, et al. The Wheat 660K SNP array demonstrates great potential for marker-assisted selection in polyploid wheat. Plant Biotechnol J, 2020, 18: 1354-1360.
doi: 10.1111/pbi.13361 pmid: 32065714
[29] Bradbury P J, Zhang Z W, Kroon D E, et al. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23: 2633-2635.
doi: 10.1093/bioinformatics/btm308 pmid: 17586829
[30] van Berloo R. GGT 2.0: versatile software for visualization and analysis of genetic data. J Hered, 2008, 99: 232-236.
doi: 10.1093/jhered/esm109 pmid: 18222930
[31] Nei M. Genetic distance between populations. Am Nat, 1972, 106: 283-292.
doi: 10.1086/282771
[32] Christopher M, Mace E, Jordan D, et al. Applications of pedigree-based genome mapping in wheat and barley breeding programs. Euphytica, 2007, 154: 307-316.
doi: 10.1007/s10681-006-9199-z
[33] 李小军, 徐鑫, 刘伟华, 等. 利用SSR标记探讨骨干亲本欧柔在衍生品种的遗传. 中国农业科学, 2009, 42: 3397-3404.
Li X J, Xu X, Liu W H, et al. Genetic diversity of the founder parent orofen and its progenies revealed by SSR markers. Sci Agric Sin, 2009, 42: 3397-3404 (in Chinese with English abstract).
[34] 韩俊, 张连松, 李静婷, 等. 小麦骨干亲本“胜利麦/燕大1817”杂交组合后代衍生品种遗传构成解析. 作物学报, 2009, 35: 1395-1404.
Han J, Zhang L S, Li J T, et al. Molecular dissection of core parental cross “Triumph/Yanda 1817” and its derivatives in wheat breeding program. Acta Agron Sin, 2009, 35: 1395-1404 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2009.01395
[35] 袁园园, 王庆专, 崔法, 等. 小麦骨干亲本碧蚂4号的基因组特异位点及其在衍生后代中的传递. 作物学报, 2010, 36: 9-16.
doi: 10.3724/SP.J.1006.2010.00009
Yuan Y Y, Wang Q Z, Cui F, et al. Specific loci in genome of wheat milestone parent Bima 4 and their transmission in derivatives. Acta Agron Sin, 2010, 36: 9-16 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2010.00009
[36] 崔法, 赵春华, 鲍印广, 等. 冬小麦种质矮孟牛第一部分同源群染色体遗传差异分析. 作物学报, 2010, 36: 1450-1456.
doi: 10.3724/SP.J.1006.2010.01450
Cui F, Zhao C H, Bao Y G, et al. Genetic differences in homoeologous group 1 of seven types of winter wheat Aimengniu. Acta Agron Sin, 2010, 36: 1450-1456 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2010.01450
[37] 赵春华, 崔法, 李君, 等. 冬小麦种质“矮孟牛”姊妹系遗传差异. 作物学报, 2011, 37: 1333-1341.
doi: 10.3724/SP.J.1006.2011.01333
Zhao C H, Cui F, Li J, et al. Genetic difference of siblines derived from winter wheat germplasm “Aimengniu”. Acta Agron Sin, 2011, 37: 1333-1341 (in Chinese with English abstract).
[38] 肖永贵, 殷贵鸿, 李慧慧, 等. 小麦骨干亲本“周8425B”及其衍生品种的遗传解析和抗条锈病基因定位. 中国农业科学, 2011, 44: 3919-3929.
doi: 10.3864/j.issn.0578-1752.2011.19.001
Xiao Y G, Yin G H, Li H H, et al. Genetic diversity and genome-wide association analysis of stripe rust resistance among the core wheat parent Zhou 8425B and its derivatives. Sci Agric Sin, 2011, 44: 3919-3929 (in Chinese with English abstract).
[39] 王玉心, 牟春生. 鲁麦14号的生育特点与高产栽培. 山东农业科学, 1992, 24(6): 13-14.
Wang Y X, Mu C S. Growing characteristics and high-yield cultivation of Lumai 14. Shandong Agric Sci, 1992, 24(6): 13-14 (in Chinese).
[40] 庄巧生. 中国小麦品种改良及系谱分析. 北京: 中国农业出版社, 2003.
Zhuang Q S. Chinese Wheat Improvement and Pedigree Analysis. Beijing: China Agriculture Press, 2003 (in Chinese).
[41] 盖红梅, 李玉刚, 王瑞英, 等. 鲁麦14对山东新选育小麦品种的遗传贡献. 作物学报, 2012, 38: 954-961.
doi: 10.3724/SP.J.1006.2012.00954
Ge H M, Li Y G, Wang R Y, et al. Genetic contribution of Lumai 14 to novel wheat varieties developed in Shandong province. Acta Agron Sin, 2012, 38: 954-961 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2012.00954
[42] 何中虎, 夏先春, 陈新民, 等. 中国小麦育种进展与展望. 作物学报, 2011, 37: 202-215.
doi: 10.3724/SP.J.1006.2011.00202
He Z H, Xia X C, Chen X M, et al. Progress of wheat breeding in China and the future perspective. Acta Agron Sin, 2011, 37: 202-215 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2011.00202
[43] 魏益民, 张波, 关二旗, 等. 中国冬小麦品质改良研究进展. 中国农业科学, 2013, 46: 4189-4196.
doi: 10.3864/j.issn.0578-1752.2013.20.002
Wei Y M, Zhang B, Guan E Q, et al. Advances in study of quality property improvement of winter wheat in China. Sci Agric Sin, 2013, 46: 4189-4196 (in Chinese with English abstract).
[44] 李振声. 我国小麦育种的回顾与展望. 中国农业科技导报, 2010, 12(2): 1-4.
Li Z S. Retrospect and prospect of wheat breeding in China. J Agric Sci Technol, 2010, 12(2): 1-4 (in Chinese with English abstract).
[45] 乔玲, 刘成, 郑兴卫, 等. 小麦骨干亲本临汾5064单元型区段的遗传解析. 作物学报, 2018, 44: 931-937.
doi: 10.3724/SP.J.1006.2018.00931
Qiao L, Liu C, Zheng X W, et al. Genetic analysis of haplotype-blocks from wheat founder parent Linfen 5064. Acta Agron Sin, 2018, 44: 931-937 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2018.00931
[46] 刘泽厚, 万洪深, 杨凡, 等. 西南麦区骨干亲本川麦42重要基因组区段的确定及其对衍生品种的遗传贡献. 西南农业学报, 2024, 37: 897-912.
Liu Z H, Wan H S, Yang F, et al. Identification of important genomic regions for foundational parent Chuanmai 42 of southwest wheat-growing zone and their genetic contribution. Southwest China J Agric Sci, 2024, 37: 897-912 (in Chinese with English abstract).
[47] 赵春华, 樊小莉, 王维莲, 等. 小麦候选骨干亲本科农9204遗传构成及其传递率. 作物学报, 2015, 41: 574-584.
doi: 10.3724/SP.J.1006.2015.00574
Zhao C H, Fan X L, Wang W L, et al. Genetic composition and its transmissibility analysis of wheat candidate backbone parent Kenong 9204. Acta Agron Sin, 2015, 41: 574-584 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2015.00574
[48] 白彦明, 李龙, 王绘艳, 等. 蚂蚱麦和小白麦衍生系的遗传多样性分析. 作物学报, 2019, 45: 1468-1477.
doi: 10.3724/SP.J.1006.2019.91012
Bai Y M, Li L, Wang H Y, et al. Genetic diversity assessment in derivative offspring of Mazhamai and Xiaobaimai wheat. Acta Agron Sin, 2019, 45: 1468-1477 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2019.91012
[49] Cavalet-Giorsa E, González-Muñoz A, Athiyannan N, et al. Origin and evolution of the bread wheat D genome. Nature, 2024, 633: 848-855.
doi: 10.1038/s41586-024-07808-z
[50] Mirzaghaderi G, Mason A S. Broadening the bread wheat D genome. Theor Appl Genet, 2019, 132: 1295-1307.
doi: 10.1007/s00122-019-03299-z pmid: 30739154
[51] 吕国锋, 范金平, 吴素兰, 等. 早熟小麦品种扬麦37主要目标性状的遗传构成分析. 作物学报, 2025, 51: 1538-1547.
doi: 10.3724/SP.J.1006.2025.41063
Lyu G F, Fan J P, Wu S L, et al. Genetic analysis of key target traits in the early-maturing wheat cultivar Yangmai 37. Acta Agron Sin, 2025, 51: 1538-1547 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2025.41063
[52] 任勇, 李生荣, 罗建明, 等. 绵麦37特异位点在其衍生品种中的遗传贡献率分析. 遗传, 2014, 36: 145-151.
Ren Y, Li S R, Luo J M, et al. Frequency and contribution of specific genetic loci transferred from wheat cultivar Mianmai 37 to its derivatives. Hereditas (Beijing), 2014, 36: 145-151 (in Chinese with English abstract).
doi: 10.3724/SP.J.1005.2014.00145
[53] 李俊, 万洪深, 杨武云, 等. 小麦新品种川麦104的遗传构成分析. 中国农业科学, 2014, 47: 2281-2291.
doi: 10.3864/j.issn.0578-1752.2014.12.001
Li J, Wan H S, Yang W Y, et al. Dissection of genetic components in the new high-yielding wheat cultivar Chuanmai 104. Sci Agric Sin, 2014, 47: 2281-2291 (in Chinese with English abstract).
[54] 邹少奎, 殷贵鸿, 唐建卫, 等. 小麦新品种周麦23号的遗传构成分析及其特异引物筛选. 中国农业科学, 2015, 48: 3941-3951.
doi: 10.3864/j.issn.0578-1752.2015.19.016
Zou S K, Yin G H, Tang J W, et al. Genetic analysis of new wheat variety Zhoumai 23 and screening of specific primers. Sci Agric Sin, 2015, 48: 3941-3951 (in Chinese with English abstract).
[55] 罗江陶, 郑建敏, 邓清燕, 等. 重要育种亲本川麦44对衍生品种的遗传贡献. 中国农业科学, 2021, 54: 4255-4270.
doi: 10.3864/j.issn.0578-1752.2021.20.001
Luo J T, Zheng J M, Deng Q Y, et al. The genetic contribution of the important breeding parent Chuanmai 44 to its derivatives. Sci Agric Sin, 2021, 54: 4255-4270 (in Chinese with English abstract).
doi: 10.3864/j.issn.0578-1752.2021.20.001
[56] Li T, Tang Y Y, Lin Z X, et al. Identification and development of KASP markers for genetic loci controlling plant height in bread wheat and evaluation their effects using near isogenic lines. BMC Plant Biol, 2025, 25: 832.
doi: 10.1186/s12870-025-06820-3 pmid: 40604427
[57] 刘宾, 赵亮, 张坤普, 等. 小麦株高发育动态QTL定位. 中国农业科学, 2010, 43: 4562-4570.
Liu B, Zhao L, Zhang K P, et al. Genetic dissection of plant height at different growth stages in common wheat. Sci Agric Sin, 2010, 43: 4562-4570 (in Chinese with English abstract).
[58] 姚琦馥, 陈黄鑫, 周界光, 等. 基于16K SNP芯片的小麦株高QTL鉴定及其遗传分析. 中国农业科学, 2023, 56: 2237-2248.
doi: 10.3864/j.issn.0578-1752.2023.12.001
Yao Q F, Chen H X, Zhou J G, et al. QTL identification and genetic analysis of plant height in wheat based on 16K SNP array. Sci Agric Sin, 2023, 56: 2237-2248 (in Chinese with English abstract).
doi: 10.3864/j.issn.0578-1752.2023.12.001
[59] Liu Y Y, Chen J, Yin C B, et al. A high-resolution genotype-phenotype map identifies the TaSPL17 controlling grain number and size in wheat. Genome Biol, 2023, 24: 196.
doi: 10.1186/s13059-023-03044-2
[60] Ding H K, Wang C Y, Cai Y B, et al. Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits. BMC Plant Biol, 2024, 24: 292.
doi: 10.1186/s12870-024-04963-3 pmid: 38632554
[61] Zhang X Y, Jia H Y, Li T, et al. TaCol-B5 modifies spike architecture and enhances grain yield in wheat. Science, 2022, 376: 180-183.
doi: 10.1126/science.abm0717 pmid: 35389775
[62] 赵聪豪. 小麦品系S849-8小穗数位点的解析与利用评价. 四川农业大学硕士学位论文, 四川雅安, 2024.
Zhao C H. Genetic Analysis and Utilization Value Evaluation of Loci for Spikelet Number Per Spike from a Wheat Line S849-8MS Thesis of Sichuan Agricultural University, Ya’an, Sichuan, China, 2024 (in Chinese with English abstract).
[63] 马天航, 蔡益彪, 熊永星, 等. 小麦不育小穗数QTL-qSsnps- 5D遗传及育种选择效应解析. 植物遗传资源学报, 2022, 23: 811-822.
doi: 10.13430/j.cnki.jpgr.20211203002
Ma T H, Cai Y B, Xiong Y X, et al. Genetic effect of sterile spikelet number-related QTL-qSsnps-5D and its use in wheat varieties. J Plant Genet Resour, 2022, 23: 811-822 (in Chinese with English abstract).
[64] Liu H X, Li T, Hou J, et al. TaWUS-like-5D affects grain weight and filling by inhibiting the expression of sucrose and trehalose metabolism-related genes in wheat grain endosperm. Plant Biotechnol J, 2025, 23: 2018-2033.
doi: 10.1111/pbi.70015 pmid: 40048350
[65] 马靖福. 旱地小麦粒重性状遗传解析与候选基因发掘. 甘肃农业大学博士学位论文, 甘肃兰州, 2025.
Ma J F. Genetic Dissection and Candidate Gene Mining of Kernel Weight-Related Traits in Dryland Wheat. PhD Dissertation of Gansu Agricultural University, Lanzhou, Gansu, China, 2025 (in Chinese with English abstract).
[66] Ramanpreet R, Kaur G, Tuan P A, et al. Genetic loci and novel candidate causal genes for preharvest sprouting resistance in wheat (Triticum aestivum L.). Theor Appl Genet, 2025, 138: 169.
doi: 10.1007/s00122-025-04958-0 pmid: 40600988
[67] Tai L, Wang H J, Xu X J, et al. Pre-harvest sprouting in cereals: genetic and biochemical mechanisms. J Exp Bot, 2021, 72: 2857-2876.
doi: 10.1093/jxb/erab024 pmid: 33471899
[1] 马婷婷, 郭晓江, 李豪, 邓梅, 蒲至恩, 李伟, 张亚洲, 王凤涛, 崔凤娟, 魏育明, 王际睿, 蒋云峰, 陈国跃. 利用小麦农家种孝感麦协同改良蜀麦753产量与抗病耐逆性的育种实践[J]. 作物学报, 2026, 52(1): 56-71.
[2] 吕国锋, 范金平, 吴素兰, 张晓, 赵仁慧, 李曼, 王玲, 高德荣, 别同德, 刘健. 早熟小麦品种扬麦37主要目标性状的遗传构成分析[J]. 作物学报, 2025, 51(6): 1538-1547.
[3] 孟祥宇, 刁邓超, 刘雅睿, 李云丽, 孙玉晨, 吴玮, 赵雯, 汪妤, 吴建辉, 李春莲, 曾庆东, 韩德俊, 郑炜君. 小麦新品种西农877高产稳产的遗传特性解析[J]. 作物学报, 2025, 51(5): 1261-1276.
[4] 黄林玉, 张潇月, 李豪, 邓梅, 康厚扬, 魏育明, 王际睿, 蒋云峰, 陈国跃. 小麦农家种成株期条锈病抗性QTL定位及其育种效应解析[J]. 作物学报, 2024, 50(9): 2167-2178.
[5] 赵春华,樊小莉,王维莲,张玮,韩洁,陈梅,纪军,崔法,李俊明. 小麦候选骨干亲本科农9204遗传构成及其传递率[J]. 作物学报, 2015, 41(04): 574-584.
[6] 李小军,冯素伟,李淦,董娜,陈向东,宋杰, 茹振钢. 应用SSR分子标记分析小麦品种(系)的遗传重组[J]. 作物学报, 2013, 39(02): 238-248.
[7] 韩俊,张连松,李静婷,石丽娟,解超杰,尤明山,杨作民,刘广田,孙其信,刘志勇. 小麦骨干亲本“胜利麦/燕大1817”杂交组合后代衍生品种遗传构成解析[J]. 作物学报, 2009, 35(8): 1395-1404.
[8] 黄承彦;颜廷进;张存良;沈立. 不同世代小麦花药培养的遗传效应分析[J]. 作物学报, 1991, 17(04): 304-310.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!