欢迎访问作物学报,今天是

作物学报 ›› 2023, Vol. 49 ›› Issue (2): 377-391.doi: 10.3724/SP.J.1006.2023.23021

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

玉米雌穗产量相关性状全基因组关联分析与候选基因鉴定

殷芳冰1(), 李雅楠1, 鲍建喜1, 马雅杰1, 秦文萱1, 王锐璞1, 龙艳1,2, 李金萍2, 董振营1,2,*(), 万向元1,2,*()   

  1. 1北京科技大学生物与农业研究中心 / 化学与生物工程学院 / 顺德研究生院 / 北京中智生物农业国际研究院, 北京 100083
    2北京首佳利华科技有限公司 / 主要作物生物育种北京市工程实验室 / 生物育种北京市国际科技合作基地, 北京 100192
  • 收稿日期:2022-02-27 接受日期:2022-05-05 出版日期:2022-05-26 网络出版日期:2022-05-26
  • 通讯作者: 董振营,万向元
  • 作者简介:E-mail: yinfangbing186@163.com
  • 基金资助:
    国家重点研发计划项目“农业生物种质资源挖掘与创新利用”重点专项(2021YFD1200700)

Genome-wide association study and candidate genes predication of yield related ear traits in maize

YIN Fang-Bing1(), LI Ya-Nan1, BAO Jian-Xi1, MA Ya-Jie1, QIN Wen-Xuan1, WANG Rui-Pu1, LONG Yan1,2, LI Jin-Ping2, DONG Zhen-Ying1,2,*(), WAN Xiang-Yuan1,2,*()   

  1. 1Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, School of Chemistry and Biological Engineering, Research Center of Biology and Agriculture, University of Science and Technology Beijing (USTB), Beijing 100083, China
    2Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co. Ltd., Beijing 100192, China
  • Received:2022-02-27 Accepted:2022-05-05 Published:2022-05-26 Published online:2022-05-26
  • Contact: DONG Zhen-Ying,WAN Xiang-Yuan
  • Supported by:
    National Key Research and Development Program of China(2021YFD1200700)

摘要:

玉米雌穗产量相关性状直接影响玉米最终产量, 解析其遗传机制可为玉米高产提供有益指导。本研究以733份玉米自交系作为关联群体, 在2个环境下随机区组种植, 调查穗行数(KRN)、穗长(EL)和穗粗(ED) 3个产量相关性状, 利用MaizeSNP3072芯片对其进行基因分型, 采用FarmCPU模型进行全基因组关联分析, 分别鉴定出16、13和24个与3个性状显著关联的单核苷酸多态性位点(SNP), 对表型变异的解释率分别为0.01%~7.08%、0.01%~5.34%和0.07%~4.34%。其中, 分别有6、2和5个与3个性状存在显著关联的高可信度(high confidence, HC) SNP, 而且有2个HC-SNP同时与KRN和ED显著相关, 1个KRN HC-SNP和3个ED HC-SNP为本研究首次报道。在所鉴定HC-SNP上下游200 kb范围内筛选出33个重要候选基因, 其中9号染色体SNP标记PZE-109003046所在基因PIN1a为控制生长素极性运输从而调控雌穗性状的已知基因。另一些候选基因编码不同转录因子, 以及参与生长素、赤霉素和乙烯等激素介导的信号转导、DNA甲基化和蛋白磷酸化等翻译后修饰过程的蛋白, 可能从不同方面调控雌穗相关性状。本研究所挖掘的11个HC-SNP与33个候选基因可以为进一步克隆雌穗性状功能基因、揭示相关分子调控机制以及利用分子标记辅助选择育种提供有益指导。

关键词: 玉米, 雌穗产量相关性状, 全基因组关联分析, 候选基因

Abstract:

Ear traits directly affect the final yield of maize, and the analysis of its genetic mechanisms can provide useful guidance for yield enhancement in maize. In this study, 733 maize inbred lines were planted in randomized block designs under two environments, and three yield-related traits, kernel row number (KRN), ear length (EL), and ear diameter (ED), were investigated. Genotyping was performed using MaizeSNP3072 chip and FarmCPU (fixed and random model circulating probability unification) model was used to conduct genome-wide association study (GWAS). 16, 13, and 24 single nucleotide polymorphism (SNP) loci significantly associated with the three traits were identified, and the values of phenotypic variation explained (PVE) for single locus were 0.01%-7.08%, 0.01%-5.34%, and 0.07%-4.34%, respectively. Further, six, two, and five high confidence (HC) SNPs that were repeatedly detected in multiple environments for KRN, EL, and ED were retrieved, among which two SNPs were simultaneously associated with KRN and ED traits, and one KRN HC-SNP and three ED HC-SNPs were firstly reported in this study. By searching 200 kb regions around the 11 HC-SNPs loci, 33 important candidate genes were identified, including a known gene PIN1a regulating ear development via auxin polar transport located in the confidence interval of chromosome 9 SNP marker PZE-109003046. Other candidate genes encoded transcription factors, hormone (such as auxin, gibberellin, and ethylene) pathway related proteins, DNA methylation, and protein phosphorylation related proteins, which might regulate ear traits by different mechanisms. The 11 HC-SNPs and 33 important candidate genes detected in this study can provide valuable information for further cloning of functional genes and reveal the molecular regulatory mechanisms and marker-assisted selection for ear trait in maize.

Key words: maize, yield related ear traits, genome-wide association study (GWAS), candidate gene

表1

穗行数、穗长和穗粗表型数据统计分析"

性状
Trait
环境
Environment
平均值
Mean
(cm)
最大值
Maximum (cm)
最小值
Minimum (cm)
范围
Range (cm)
标准差
Standard deviation
偏度
Skewness
峰度
Kurtosis
遗传力
h2
穗行数KRN 2019 13.80 21.33 8.00 13.33 1.93 0.632 0.810 0.80
2020 14.89 24.40 8.40 16.00 2.17 0.607 0.755
穗长EL 2019 13.11 21.83 6.78 15.04 1.95 0.293 0.798 0.65
2020 14.45 21.03 8.34 12.69 1.98 0.012 0.221
穗粗ED 2019 4.25 5.67 3.11 2.56 0.34 0.151 0.872 0.79
2020 4.44 5.83 3.09 2.73 0.36 0.073 0.998

图1

不同环境间穗行数、穗长和穗粗相关性分析和频率直方图 图中对角线表示穗行数、穗长和穗粗在2019年北京和2020年北京环境的频率直方图, 左下表示穗行数、穗长和穗粗在不同环境下的散点图, 右上表示相关性系数。**、***分别表示在P < 0.01、0.001水平上差异显著。KRN、EL和ED分别表示穗行数、穗长和穗粗。"

表2

穗行数、穗长和穗粗多环境联合方差分析"

性状
Trait
变异来源
Source
均方
Mean of square
F
F-value
P
P-value
穗行数KRN 基因型Genotype 22.271 13.694 <0.001
环境Environment 1273.476 783.028 <0.001
基因型与环境互作Genotype and environment interaction 4.392 2.701 <0.001
穗长EL 基因型Genotype 19.133 24.162 <0.001
环境Environment 1916.165 2419.761 <0.001
基因型与环境互作Genotype and environment interaction 6.260 7.905 <0.001
穗粗ED 基因型Genotype 0.649 23.762 <0.001
环境Environment 39.665 1451.942 <0.001
基因型与环境互作Genotype and environment interaction 0.124 4.546 <0.001

图2

733份玉米自交系主成分分析(a)与亲缘关系分析(b) HZS、NSS和SS分别表示黄早四群体、非坚秆群体和坚秆群体。"

图3

玉米穗行数、穗长、穗粗GWAS曼哈顿图(a, c, e)与QQ-plot图(b, d, f) BLUP表示最佳线性无偏预测值。KRN、EL和ED处理缩写同图1。"

附表1

不同环境下穗行数、穗长、穗粗显著关联SNP位点汇总"

性状
Trait
标记名称
Maker name
染色体
Chr.
物理位置
Position (bp)
环境
Environment
P
P-value
表型变异解释率
PVE (%)
最小等位基因频率
MAF
穗行数KRN PZE-103149597 3 206,991,538 BLUP/2019 1.28E-06/1.60E-07 1.13/1.46 0.21
PZE-104041818 4 59,704,298 BLUP/2020 1.58E-06/1.52E-05 6.44/6.18 0.36
PZE-104124173 4 205,899,298 2019 7.02E-08 3.21 0.34
PZE-104126211 4 208,732,552 BLUP/2020 1.46E-10/4.08E-07 7.08/6.74 0.47
PZE-105105740 5 164,510,203 2019 1.90E-05 0.11 0.35
PZE-106038186 6 89,083,642 2020 4.83E-05 0.37 0.44
SYN4194 6 162,814,863 BLUP/2019 3.59E-06/8.91E-07 0.72/0.69 0.31
PZE-106115356 6 165,632,631 2019 2.94E-05 0.52 0.41
PZE-107055553 7 110,762,862 2020 6.93E-07 1.23 0.35
PZE-107116723 7 169,607,175 BLUP/2019/2020 7.09E-11/5.74E-09/4.43E-08 4.32/3.40/3.79 0.23
PZE-108005561 8 5,864,518 2019 9.98E-05 0.01 0.48
PZE-108080140 8 140,264,937 2019 9.53E-07 2.80 0.47
PZA03608.2 8 146,863,745 BLUP/2020 1.01E-06/5.53E-06 2.05/2.47 0.44
PZE-109037923 9 76,271,588 2019 9.78E-08 1.39 0.31
PZE-109061922 9 107,147,924 BLUP 5.78E-05 0.37 0.45
SYN20545 10 88,765,819 2019 7.29E-05 0.18 0.48
穗长
EL
PZE-101162306 1 208,334,343 BLUP/2019 2.91E-06/5.22E-05 2.88/1.86 0.35
PZE-102065179 2 45,039,241 BLUP 1.80E-05 3.15 0.46
SYN27033 2 227,085,703 2019 9.34E-05 2.92 0.32
PZE-104073430 4 148,150,704 2019 2.33E-05 2.56 0.40
PZE-104113905 4 193,372,982 BLUP/2019 4.72E-05/3.35E-06 0.01/0.33 0.38
PZE-104140854 4 234,265,598 2019 4.80E-05 0.99 0.16
PZE-105039536 5 25,111,571 2019 5.52E-05 0.57 0.20
PZE-105105086 5 163,308,887 BLUP 4.51E-06 1.73 0.30
SYN6220 6 151,019,477 2019 7.16E-05 1.81 0.26
SYN35928 8 93,549,629 2019 5.51E-05 2.56 0.38
PZE-108059570 8 108,903,711 BLUP 3.11E-05 1.56 0.40
PZE-108106737 8 165,505,598 2019 6.36E-05 0.01 0.41
PZE-108133100 8 178,781,276 2020 8.87E-05 5.34 0.45
穗粗
ED
PZB02058.1 1 28,614,062 BLUP 1.65E-05 0.31 0.39
PZE-102047851 2 27,664,781 2020 4.19E-05 2.97 0.12
PUT-163a-60393963-2893 2 32,965,430 2019 7.21E-05 0.98 0.44
PZE-102120444 2 168,965,413 2019 5.10E-05 0.07 0.49
PZE-103087199 3 145,604,315 2019 1.09E-05 4.34 0.28
SYN8382 4 45,460,142 BLUP 2.70E-05 2.20 0.45
PZE-104041818 4 59,704,298 2020 1.99E-07 3.02 0.36
PZE-104045413 4 69,980,490 2020 7.70E-05 1.17 0.44
PZE-104093153 4 172,487,553 BLUP/2020 2.92E-05/2.26E-05 1.62/1.87 0.32
PZE-104093898 4 173,802,472 BLUP 1.14E-05 1.54 0.19
PZE-104126211 4 208,732,552 BLUP/2020 1.00E-05/7.50E-05 0.19/0.66 0.47
SYN22663 5 3,212,673 2019 1.33E-05 0.92 0.47
PZE-105032165 5 18,159,660 2019 4.21E-06 0.34 0.49
PZE-105080632 5 95,622,206 2019 1.27E-06 2.06 0.36
SYN32729 5 200,052,824 BLUP/2019 5.19E-05/2.98E-05 4.00/3.84 0.49
SYN4194 6 162,814,863 BLUP/2019 2.89E-09/8.17E-07 2.56/2.66 0.31
PZE-107055553 7 110,762,862 2020 1.90E-07 2.79 0.35
SYN13511 7 125,838,654 2019 6.35E-05 1.00 0.48
PZE-107070986 7 131,255,494 2019 3.75E-05 0.07 0.44
PZE-108036722 8 57,892,012 2019 1.02E-05 2.88 0.43
PZE-109003046 9 3,291,982 BLUP/2020 1.21E-07/2.08E-10 3.90/4.01 0.26
PZB00235.1 9 36,013,505 2019 1.96E-05 2.80 0.48
PZE-109061922 9 107,147,924 BLUP 5.99E-05 0.07 0.45
PZE-110043433 10 82,662,170 BLUP 1.31E-05 1.37 0.46

表3

穗行数、穗长和穗粗性状高可信度(high confidence, HC) SNP位点与候选基因"

性状
Trait
标记名称
Marker name
染色体
Chr.
位置
Position (bp)
最小等位基因频率
MAF
环境
Environment
表型变异解释率
PVE (%)
候选基因
Candidate gene
基因注释
Gene annotation
穗行数
KRN
PZE-103149597 3 206,991,538 0.21 BLUP 2019 1.46 Zm00001d043674 Cytidine deaminase
Zm00001d043675 Reversion-to-ethylene sensitivity1 like2
Zm00001d043681 Amino_oxidase domain-containing protein
PZE-104041818 4 59,704,298 0.36 BLUP 2020 6.44 Zm00001d050016 bHLH transcription factor
PZE-104126211 4 208,732,552 0.47 BLUP 2020 7.08 Zm00001d053006 C2H2-like zinc finger protein
Zm00001d053004 Auxin transporter-like protein
Zm00001d053003 ARM repeat superfamily protein
Zm00001d053011 Putative DUF869 domain containing family protein
SYN4194 6 162,814,863 0.31 BLUP 2019 0.72 Zm00001d038699 O-methyltransferase ZRP4
Zm00001d038698 Auxin response factor
Zm00001d038695 Gibberellin 2-oxidase7
Zm00001d038690 Non-specific serine/threonine protein kinase
Zm00001d038693 C2C2-DOF transcription factor
PZE-107116723 7 169,607,175 0.23 BLUP
2019 2020
4.32 Zm00001d022077 Probable 6-phosphogluconolactonase
Zm00001d022071 Nuclear transport factor 2 (NTF2) family protein with RNA binding (RRM-RBD-RNP motifs) domain
Zm00001d022075 Cytochrome P-450 17
PZA03608.2 8 146,863,745 0.44 BLUP 2020 2.47 Zm00001d011329 DNA methyl transferase
Zm00001d011323 Agamous-like MADS-box protein AGL62
Zm00001d011326 Plant Tudor-like RNA-binding protein
Zm00001d011327 Plant Tudor-like RNA-binding protein
Zm00001d011328 GTP-binding nuclear protein
穗长
EL
PZE-101162306 1 208,334,343 0.35 BLUP 2019 2.88 Zm00001d031973 Phosphatidylinositol-3-phosphatase myotubularin-1
Zm00001d031981 Evolutionarily conserved C-terminal region 5
PZE-104113905 4 193,372,982 0.38 BLUP 2019 0.33 Zm00001d052570 Cation-chloride cotransporter 1
Zm00001d052561 mRNA-decapping enzyme-like protein
Zm00001d052564 Putative NAC domain transcription factor superfamily protein
Zm00001d052578 Putative F-box protein
Zm00001d052584 Protein kinase domain containing protein expressed
穗粗
ED
PZE-104093153 4 172,487,553 0.32 BLUP 2020 1.87 Zm00001d051856 O-fucosyltransferase family protein
Zm00001d051861 AT-hook motif nuclear-localized protein
PZE-104126211 4 208,732,552 0.47 BLUP 2020 0.66 Zm00001d053006 C2H2-like zinc finger protein
Zm00001d053004 Auxin transporter-like protein
Zm00001d053003 ARM repeat superfamily protein
Zm00001d053011 Putative DUF869 domain containing family protein
SYN32729 5 200,052,824 0.49 BLUP 2019 4.00 Zm00001d017573 Transcription factor bHLH157
Zm00001d017575 Dof zinc finger protein DOF2.5
SYN4194 6 162,814,863 0.31 BLUP 2019 2.66 Zm00001d038699 O-methyltransferase ZRP4
Zm00001d038698 Auxin response factor
Zm00001d038695 Gibberellin 2-oxidase7
Zm00001d038690 Non-specific serine/threonine protein kinase
Zm00001d038693 C2C2-DOF transcription factor
PZE-109003046 9 3,291,982 0.26 BLUP 2020 4.01 Zm00001d044812 Auxin efflux carrier component

图4

显著关联SNP位点等位变异表型效应分析 NS表示P > 0.05, *、**和***分别表示0.05、0.01和 0.001水平差异显著。KRN、EL和ED处理缩写同图1。"

[1] 宁慧云, 连晋, 赵玉坤, 连吉明, 高根来. 不同玉米品种雌穗性状及产量的灰关联评价研究. 农学学报, 2013, 3(6): 13-16.
Ning H Y, Lian J, Zhao Y K, Lian J M, Gao G L. Grey relational evaluation study in ear traits and yield of different maize varieties. J Agric, 2013, 3(6): 13-16. (in Chinese with English abstract)
[2] 王帮太, 吴建宇, 丁俊强, 席章营. 玉米产量及产量相关性状QTL的图谱整合. 作物学报, 2009, 35: 1836-1843.
Wang B T, Wu J Y, Ding J Q, Xi Z Y. Map integration of QTLs for grain yield and its related traits in maize. Acta Agron Sin, 2009, 35: 1836-1843. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2009.01836
[3] 吴律, 代力强, 董青松, 施婷婷, 王丕武. 玉米行粒数的全基因组关联分析. 作物学报, 2017, 43: 1559-1564.
Wu L, Dai L Q, Dong Q S, Shi T T, Wang P W. Genome-wide association analysis of kernel number per row in maize. Acta Agron Sin, 2017, 43: 1559-1564 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2017.01569
[4] 张焕欣, 翁建峰, 张晓聪, 刘昌林, 雍洪军, 郝转芳, 李新海. 玉米穗行数全基因组关联分析. 作物学报, 2014, 40: 1-6.
doi: 10.3724/SP.J.1006.2014.00001
Zhang H X, Weng J F, Zhang X C, Liu C L, Yong H J, Hao Z F, Li X H. Genome-wide association analysis of kernel row number in maize. Acta Agron Sin, 2014, 40: 1-6. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2014.00001
[5] Li F, Jia H T, Liu L, Zhang C X, Liu Z J, Zhang Z X. Quantitative trait loci mapping for kernel row number using chromosome segment substitution lines in maize. Genet Mol Res, 2014, 13: 1707-1716.
doi: 10.4238/2014.January.17.1 pmid: 24535896
[6] Choi J K, Sa K J, Park D H, Lim S E, Ryu S H, Park J Y, Park K J, Rhee H I, Lee M, Lee J K. Construction of genetic linkage map and identification of QTLs related to agronomic traits in DH population of maize (Zea mays L.) using SSR markers. Genes Genomics, 2019, 41: 667-678.
doi: 10.1007/s13258-019-00813-x
[7] Zhou B, Zhou Z J, Ding J Q, Zhang X C, Mu C, Wu Y B, Gao J Y, Song Y X, Wang S W, Ma J L, Li X T, Wang R X, Xia Z L, Chen J F, Wu J Y. Combining three mapping strategies to reveal quantitative trait loci and candidate genes for maize ear length. Plant Genome, 2018, 11: 170107.
doi: 10.3835/plantgenome2017.11.0107
[8] Zhang X X, Guan Z R, Li Z L, Liu P, Ma L L, Zhang Y C, Pan L, He S J, Zhang Y L, Li P, Ge F, Zou C Y, He Y C, Gao S B, Pan G T, Shen Y O. A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments. Theor Appl Genet, 2020, 133: 2881-2895.
doi: 10.1007/s00122-020-03639-4 pmid: 32594266
[9] Xu Y, Xu C, Xu S. Prediction and association mapping of agronomic traits in maize using multiple omic data. Heredity, 2017, 119: 174-184.
doi: 10.1038/hdy.2017.27 pmid: 28590463
[10] Li T, Qu J Z, Tian X K, Lao Y H, Wei N N, Wang Y H, Hao Y C, Zhang X H, Xue J Q, Xu S T. Identification of ear morphology genes in maize (Zea mays L.) using selective sweeps and association mapping. Front Genet, 2020, 11: 747.
doi: 10.3389/fgene.2020.00747
[11] Tian H L, Wang F G, Zhao J R, Yi H M, Wang L, Wang R, Yang Y, Song W. Development of maizeSNP3072, a high-throughput compatible SNP array, for DNA fingerprinting identification of Chinese maize varieties. Mol Breed, 2015, 35: 136.
doi: 10.1007/s11032-015-0335-0
[12] Zhu X M, Shao X Y, Pei Y H, Guo X M, Li J, Song X Y, Zhao M A. Genetic diversity and genome-wide association study of major ear quantitative traits using high-density SNPs in maize. Front Plant Sci, 2018, 9: 966.
doi: 10.3389/fpls.2018.00966
[13] Zhang C S, Zhou Z Q, Yong H J, Zhang X C, Hao Z F, Zhang F J, Li M S, Zhang D G, Li X H, Wang Z H, Weng J F. Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping. Theor Appl Genet, 2017, 130: 1011-1029.
doi: 10.1007/s00122-017-2867-7 pmid: 28215025
[14] Xue Y D, Warburton M L, Sawkins M, Zhang X H, Setter T, Xu Y B, Grudloyma P, Gethi J, Ribaut J M, Li W C, Zhang X B, Zheng Y L, Yan J B. Genome-wide association analysis for nine agronomic traits in maize under well-watered and water-stressed conditions. Theor Appl Genet, 2013, 126: 2587-2596.
doi: 10.1007/s00122-013-2158-x pmid: 23884600
[15] Pandis N. Linear regression. Am J Orthod Dentofacial Orthop, 2016, 149: 431-434.
doi: 10.1016/j.ajodo.2015.11.019
[16] Carraro N, Forestan C, Canova S, Traas J, Varotto S. ZmPIN1a and ZmPIN1b encode two novel putative candidates for polar auxin transport and plant architecture determination of maize. Plant Physiol, 2006, 142: 254-264.
pmid: 16844839
[17] Forestan C, Meda S, Varotto S. ZmPIN1-mediated auxin transport is related to cellular differentiation during maize embryogenesis and endosperm development. Plant Physiol, 2010, 152: 1373-1390.
doi: 10.1104/pp.109.150193 pmid: 20044449
[18] 马娟, 曹言勇, 李会勇. 玉米穗轴粗全基因组关联分析. 作物学报, 2021, 47: 1228-1238.
doi: 10.3724/SP.J.1006.2021.03048
Ma J, Cao Y Y, Li H Y. Genome-wide association study of ear cob diameter in maize. Acta Agron Sin, 2021, 47: 1228-1238. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2021.03048
[19] 殷芳冰, 王成, 龙艳, 董振营, 万向元. 玉米雌穗性状遗传分析与形成机制. 中国生物工程杂志, 2021, 41(12): 30-46.
Yin F B, Wang C, Long Y, Dong Z Y, Wan X Y. Progress on dissecting genetic architecture and formation mechanism of maize ear traits. China Biotechnol, 2021, 41(12): 30-46. (in Chinese with English abstract)
[20] Lu M, Xie C X, Li X H, Hao Z F, Li M S, Weng J F, Zhang D G, Bai L, Zhang S H. Mapping of quantitative trait loci for kernel row number in maize across seven environments. Mol Breed, 2011, 28: 143-152.
doi: 10.1007/s11032-010-9468-3
[21] Karen S P, Lopes S C J, Pereira S A, Augusto F G A. QTL mapping for yield components in a tropical maize population using microsatellite markers. Hereditas, 2008, 145: 194-203.
doi: 10.1111/j.0018-0661.2008.02065.x
[22] Tian B H, Wang J H, Wang G Y. Confirmation of a major QTL on chromosome 10 for maize kernel row number in different environments. Plant Breed, 2014, 133: 184-188.
doi: 10.1111/pbr.12132
[23] Liu L, Du Y F, Huo D A, Wang M, Shen X M, Yue B, Qiu F Z, Zheng Y L, Yan J B, Zhang Z X. Genetic architecture of maize kernel row number and whole genome prediction. Theor Appl Genet, 2015, 128: 2243-2254.
doi: 10.1007/s00122-015-2581-2 pmid: 26188589
[24] Ma X Q, Tang J H, Teng W T, Yan J B, Meng Y J, Li J S. Epistatic interaction is an important genetic basis of grain yield and its components in maize. Mol Breed, 2007, 20: 41-51.
doi: 10.1007/s11032-006-9071-9
[25] Yang C, Liu J, Rong T Z. Detection of quantitative trait loci for ear row number in F2 populations of maize. Genet Mol Res, 2015, 14: 14229-14238.
doi: 10.4238/2015.November.13.6 pmid: 26600480
[26] Yan J B, Tang H, Huang Y Q, Zheng Y L, Li J S. Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica, 2006, 149: 121-131.
doi: 10.1007/s10681-005-9060-9
[27] Brown P J, Upadyayula N, Mahone G S, Tian F, Bradbury P J, Myles S, Holland J B, Flint-Garcia S, McMullen M D, Buckler E S, Rocheford T R. Distinct genetic architectures for male and female inflorescence traits of maize. PLoS Genet, 2011, 7: e1002383.
doi: 10.1371/journal.pgen.1002383
[28] Huo D A, Ning Q, Shen X M, Liu L, Zhang Z X. QTL mapping of kernel number-related traits and validation of one major QTL for ear length in maize. PLoS One, 2016, 11: e0155506.
doi: 10.1371/journal.pone.0155506
[29] Yang N, Lu Y L, Yang X H, Huang J, Zhou Y, Ali F, Wen W W, Liu J, Li J S, Yan J B. Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel. PLoS Genet, 2014, 10: e1004573.
doi: 10.1371/journal.pgen.1004573
[30] Gallavotti A, Barazesh S, Malcomber S, Hall D, Jackson D, Schmidt R J, McSteen P. Sparse inflorescence1 encodes a monocot-specific YUCCA-like gene required for vegetative and reproductive development in maize. Proc Natl Acad Sci USA, 2008, 105: 15196-15201.
doi: 10.1073/pnas.0805596105
[31] Phillips K A, Skirpan A L, Liu X, Christensen A, Slewinski T L, Hudson C, Barazesh S, Cohen J D, Malcomber S, McSteen P. Vanishing tassel2 encodes a grass-specific tryptophan aminotransferase required for vegetative and reproductive development in maize. Plant Cell, 2011, 23: 550-566.
doi: 10.1105/tpc.110.075267
[32] Barazesh S, McSteen P. Barren inflorescence1 functions in organogenesis during vegetative and inflorescence development in maize. Genetics, 2008, 179: 389-401.
doi: 10.1534/genetics.107.084079 pmid: 18493061
[33] McSteen P, Hake S. Barren inflorescence2 regulates axillary meristem development in the maize inflorescence. Development, 2001, 128: 2881-2891.
doi: 10.1242/dev.128.15.2881 pmid: 11532912
[34] McSteen P, Malcomber S, Skirpan A, Lunde C, Wu X T, Kellogg E, Hake S. Barren inflorescence2 encodes a co-ortholog of the PINOID serine/threonine kinase and is required for organogenesis during inflorescence and vegetative development in maize. Plant Physiol, 2007, 144: 1000-1011.
doi: 10.1104/pp.107.098558 pmid: 17449648
[35] Kato H, Nishihama R, Weijers D, Kohchi T. Evolution of nuclear auxin signaling: lessons from genetic studies with basal land plants. J Exp Bot, 2018, 69: 291-301.
doi: 10.1093/jxb/erx267 pmid: 28992186
[36] Gallavotti A, Zhao Q, Kyozuka J, Meeley R B, Ritter M K, Doebley J F, Pè M E, Schmidt R J. The role of barren stalk1 in the architecture of maize. Nature, 2004, 432: 630-635.
doi: 10.1038/nature03148
[37] Sigmon B, Vollbrecht E. Evidence of selection at the ramosa1 locus during maize domestication. Mol Ecol, 2010, 19: 1296-1311.
doi: 10.1111/j.1365-294X.2010.04562.x
[38] 肖朝文, 傅永福. AT-hook蛋白的研究进展. 中国农业科技导报, 2009, 11(5): 12-16.
Xiao C W, Fu Y F. Research progress in AT-hook proteins. J Agric Sci Technol, 2009, 11(5): 12-16. (in Chinese with English abstract)
[39] Gallavotti A, Malcomber S, Gaines C, Stanfield S, Whipple C, Kellogg E, Schmidt R J. BARREN STALK FASTIGIATE1 is an AT-hook protein required for the formation of maize ears. Plant Cell, 2011, 23: 1756-1771.
doi: 10.1105/tpc.111.084590
[40] Jia H T, Li M F, Li W Y, Liu L, Jian Y N, Yang Z X, Shen X M, Ning Q, Du Y F, Zhao R, Jackson D, Yang X H, Zhang Z X. A serine/threonine protein kinase encoding gene KERNEL NUMBER PER ROW6 regulates maize grain yield. Nat Commun, 2020, 11: 988.
doi: 10.1038/s41467-020-14746-7
[1] 杨俊芳, 王宙, 乔麟轶, 王亚, 赵宜婷, 张宏斌, 申登高, 王宏伟, 曹越. 基于高密度遗传图谱的蓖麻种子大小性状QTL定位[J]. 作物学报, 2023, 49(3): 719-730.
[2] 许加波, 吴鹏昊, 黄博文, 陈占辉, 马月虹, 任姣姣. 利用F2:3家系来源单倍体定位玉米雄穗相关性状QTL及全基因组选择[J]. 作物学报, 2023, 49(3): 622-633.
[3] 马雅杰, 鲍建喜, 高悦欣, 李雅楠, 秦文萱, 王彦博, 龙艳, 李金萍, 董振营, 万向元. 玉米株高和穗位高性状全基因组关联分析[J]. 作物学报, 2023, 49(3): 647-661.
[4] 刘月, 明博, 李姚姚, 王克如, 侯鹏, 薛军, 李少昆, 谢瑞芝. 基于根冠协调发展的东北春玉米高产种植密度分析[J]. 作物学报, 2023, 49(3): 795-807.
[5] 刘姗姗, 庞婷, 袁晓婷, 罗凯, 陈平, 付智丹, 王小春, 杨峰, 雍太文, 杨文钰. 种间距对不同结瘤特性套作大豆根瘤生长及固氮潜力的影响[J]. 作物学报, 2023, 49(3): 833-844.
[6] 方娅婷, 任涛, 张顺涛, 周橡棋, 赵剑, 廖世鹏, 丛日环, 鲁剑巍. 氮磷钾肥对旱地和水田油菜产量及养分利用的影响差异[J]. 作物学报, 2023, 49(3): 772-783.
[7] 邓照, 蒋环琪, 程丽沙, 刘睿, 黄敏, 李曼菲, 杜何为. 利用WGCNA鉴定玉米非生物胁迫相关基因共表达网络[J]. 作物学报, 2023, 49(3): 672-686.
[8] 宋杰, 王少祥, 李亮, 黄金苓, 赵斌, 张吉旺, 任佰朝, 刘鹏. 施钾量对夏玉米氮、磷、钾吸收利用和籽粒产量的影响[J]. 作物学报, 2023, 49(2): 539-551.
[9] 刘梦, 张垚, 葛均筑, 周宝元, 吴锡冬, 杨永安, 侯海鹏. 不同降雨年型施氮量与收获期对夏玉米产量及氮肥利用效率的影响[J]. 作物学报, 2023, 49(2): 497-510.
[10] 徐彤, 吕艳杰, 邵玺文, 耿艳秋, 王永军. 不同时期化控对密植玉米冠层结构及籽粒灌浆特性的影响[J]. 作物学报, 2023, 49(2): 472-484.
[11] 杨硕, 武阳春, 刘鑫磊, 唐晓飞, 薛永国, 曹旦, 王婉, 刘亭萱, 祁航, 栾晓燕, 邱丽娟. 大豆蛋白含量主效位点qPRO-20-1的精细定位[J]. 作物学报, 2023, 49(2): 310-320.
[12] 孙智超, 张吉旺. 弱光胁迫影响玉米产量形成的生理机制及调控效应[J]. 作物学报, 2023, 49(1): 12-23.
[13] 徐凯, 郑兴飞, 张红燕, 胡中立, 宁子岚, 李兰芝. 基于NCII遗传交配设计的籼稻抽穗期全基因组关联分析[J]. 作物学报, 2023, 49(1): 86-96.
[14] 陈冰洁, 张富粮, 杨硕, 李晓立, 何堂庆, 张晨曦, 田明慧, 吴梅, 郝晓峰, 张学林. 不同形态氮肥下丛枝菌根真菌对玉米灌浆期生理特性及产量和品质的影响[J]. 作物学报, 2023, 49(1): 249-261.
[15] 张静, 王洪章, 任昊, 殷复伟, 吴红燕, 赵斌, 张吉旺, 任佰朝, 戴爱斌, 刘鹏. 夏玉米根系构型与抗根倒性能间的关系[J]. 作物学报, 2023, 49(1): 188-199.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!