Welcome to Acta Agronomica Sinica，

Acta Agronomica Sinica ›› 2023, Vol. 49 ›› Issue (2): 377-391.doi: 10.3724/SP.J.1006.2023.23021

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

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 Online:2022-05-26 Published:2022-05-26
  • Contact: DONG Zhen-Ying,WAN Xiang-Yuan E-mail:yinfangbing186@163.com;zydong@ustb.edu.cn;wanxiangyuan@ustb.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2021YFD1200700)

RichHTML407

29

PDF

319

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

Table 1

Statistical analysis of KRN, EL, and ED traits"

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

Fig. 1

Correlation analysis and frequency histogram of KRN, EL, and ED in different environments The diagonal line and lower left show the frequency histogram and scatter diagram of KRN, EL, and ED traits in different environments, respectively. The upper right shows the correlation coefficients between different traits. ** and *** indicate significance at P < 0.01 and P < 0.001, respectively. KRN, EL, and ED represent kernel row number, ear length, and ear diameter, respectively."

Table 2

Multi-environment analysis of variance for KRN, EL, and ED traits"

性状
Trait		 变异来源
Source		 均方
Mean of square		 F值
F-value		 P值
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

Fig. 2

Principal components (a) and genetic relationship (b) of the 733 maize inbred lines HZS, NSS, and SS represent the heterotic groups of Huangzaosi, non-stiff stick, and stiff stick, respectively."

Fig. 3

Manhattan plot (a, c, e) and QQ plot (b, d, f) for KRN, EL, and ED GWAS in maize BLUP represents best linear unbiased prediction. Abbreviations of KRN, EL, and ED are the same as those given in Fig. 1."

Table S1

Summary of the SNPs significantly associated with KRN, EL, and ED in different environments"

性状
Trait		 标记名称
Maker name		 染色体
Chr.		 物理位置
Position (bp)		 环境
Environment		 P值
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

Table 3

High confidence SNPs and candidate genes for KRN, EL, and ED traits"

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

Fig. 4

Phenotypic effect analysis of the allelic variation in associated loci NS: P > 0.05. *, **, and *** indicate significance at the 0.05, 0.01, and 0.001 probability levels, respectively. Abbreviations of KRN, EL, and ED are the same as those given in Fig. 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] YANG Jun-Fang, WANG Zhou, QIAO Lin-Yi, WANG Ya, ZHAO Yi-Ting, ZHANG Hong-Bin, SHEN DengGao, WANG HongWei, CAO Yue. QTL mapping of seed size traits based on a high-density genetic map in castor [J]. Acta Agronomica Sinica, 2023, 49(3): 719-730.
[2] XU Jia-Bo, WU Peng-Hao, HUANG Bo-Wen, CHEN Zhan-Hui, MA Yue-Hong, REN Jiao-Jiao. QTL locating and genomic selection for tassel-related traits using F2:3 lineage haploids [J]. Acta Agronomica Sinica, 2023, 49(3): 622-633.
[3] MA Ya-Jie, BAO Jian-Xi, GAO Yue-Xin, LI Ya-Nan, QIN Wen-Xuan, WANG Yan-Bo, LONG Yan, LI Jin-Ping, DONG Zhen-Ying, WAN Xiang-Yuan. Genome-wide association analysis of plant height and ear height related traits in maize [J]. Acta Agronomica Sinica, 2023, 49(3): 647-661.
[4] LIU Yue, MING Bo, LI Yao-Yao, WANG Ke-Ru, HOU Peng, XUE Jun, LI Shao-Kun, XIE Rui-Zhi. Analysis on high yield planting density of spring maize in Northeast China from root and shoot coordinated development [J]. Acta Agronomica Sinica, 2023, 49(3): 795-807.
[5] LIU Shan-Shan, PANG Ting, YUAN Xiao-Ting, LUO Kai, CHEN Ping, FU Zhi-Dan, WANG Xiao-Chun, YANG Feng, YONG Tai-Wen, YANG Wen-Yu. Effects of row spacing on root nodule growth and nitrogen fixation potential of different nodulation characteristics soybeans in intercropping [J]. Acta Agronomica Sinica, 2023, 49(3): 833-844.
[6] FANG Ya-Ting, REN Tao, ZHANG Shun-Tao, ZHOU Xiang-Qi, ZHAO Jian, LIAO Shi–Peng, CONG Ri-Huan, LU Jian-Wei. Different effects of nitrogen, phosphorus and potassium fertilizers on oilseed rape yield and nutrient utilization between continuous upland and paddy-upland rotations#br# [J]. Acta Agronomica Sinica, 2023, 49(3): 772-783.
[7] DENG Zhao, JIANG Huan-Qi, CHENG Li-Sha, LIU Rui, HUANG Min, LI Man-Fei, DU He-Wei. Identification of abiotic stress-related gene co-expression networks in maize by WGCNA [J]. Acta Agronomica Sinica, 2023, 49(3): 672-686.
[8] SONG Jie, WANG Shao-Xiang, LI Liang, HUANG Jin-Ling, ZHAO Bin, ZHANG Ji-Wang, REN Bai-Zhao, LIU Peng. Effects of potassium application rate on NPK uptake and utilization and grain yield in summer maize (Zea mays L.) [J]. Acta Agronomica Sinica, 2023, 49(2): 539-551.
[9] LIU Meng, ZHANG Yao, GE Jun-Zhu, ZHOU Bao-Yuan, WU Xi-Dong, YANG Yong-An, HOU Hai-Peng. Effects of nitrogen application and harvest time on grain yield and nitrogen use efficiency of summer maize under different rainfall years [J]. Acta Agronomica Sinica, 2023, 49(2): 497-510.
[10] XU Tong, LYU Yan-Jie, SHAO Xi-Wen, GENG Yan-Qiu, WANG Yong-Jun. Effect of different times of spraying chemical regulator on the canopy structure and grain filling characteristics of high planting densities [J]. Acta Agronomica Sinica, 2023, 49(2): 472-484.
[11] YANG Shuo, WU Yang-Chun, LIU Xin-Lei, TANG Xiao-Fei, XUE Yong-Guo, CAO Dan, WANG Wan, LIU Ting-Xuan, QI Hang, LUAN Xiao-Yan, QIU Li-Juan. Fine mapping of qPRO-20-1 related to high protein content in soybean [J]. Acta Agronomica Sinica, 2023, 49(2): 310-320.
[12] SUN Zhi-Chao, ZHANG Ji-Wang. Physiological mechanism and regulation effect of low light on maize yield formation [J]. Acta Agronomica Sinica, 2023, 49(1): 12-23.
[13] CHEN Bing-Jie, ZHANG Fu-Liang, YANG Shuo, LI Xiao-Li, HE Tang-Qing, ZHANG Chen-Xi, TIAN Ming-Hui, WU Mei, HAO Xiao-Feng, ZHANG Xue-Lin. Effects of arbuscular mycorrhizae fungi on maize physiological characteristics during grain filling stage, yield, and grain quality under different nitrogen fertilizer forms [J]. Acta Agronomica Sinica, 2023, 49(1): 249-261.
[14] ZHANG Jing, WANG Hong-Zhang, REN Hao, YIN Fu-Wei, WU Hong-Yan, ZHAO Bin, ZHANG Ji-Wang, REN Bai-Zhao, DAI Ai-Bin, LIU Peng. Relationship between root architecture and root pulling force of summer maize [J]. Acta Agronomica Sinica, 2023, 49(1): 188-199.
[15] WANG Rui-Pu, DONG Zhen-Ying, GAO Yue-Xin, BAO Jian-Xi, YIN Fang-Bing, LI Jin-Ping, LONG Yan, WAN Xiang-Yuan. Genome-wide association study and candidate gene prediction of kernel starch content in maize [J]. Acta Agronomica Sinica, 2023, 49(1): 140-152.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Add: No. 80 Xueyuan South Rd, Beijing 100081, P. R. China E-mail: zwxb301@caas.cn
Supported by Beijing Magtech Co.Ltd