Welcome to Acta Agronomica Sinica,

Acta Agronomica Sinica ›› 2022, Vol. 48 ›› Issue (10): 2451-2462.doi: 10.3724/SP.J.1006.2022.13052

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

Dissecting the genetic basis of kernel size related traits and their combining ability based on a hybrid population in maize

LI Ting1,2(), WANG Ya-Peng1,2, DONG Yuan1,2, GUO Rui-Shi1, LI Dong-Mei1, TANG Ya-Ling1, ZHANG Xing-Hua1,2, XUE Ji-Quan1,2, XU Shu-Tu1,2,*()   

  1. 1Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling 712100, Shaanxi, China
    2Maize Engineering Technology Research Centre of Shaanxi Province, Yangling 712100, Shaanxi, China
  • Received:2021-09-07 Accepted:2022-02-25 Online:2022-10-12 Published:2022-03-22
  • Contact: XU Shu-Tu E-mail:ltstime@163.com;shutuxu@nwafu.edu.cn
  • Supported by:
    China Agriculture Research System (Maize, CARS-02-77) of MOF and MARA;Key Research and Development Program of Shaanxi Province(2021ZDLNY01-06)

Abstract:

Combining ability is a crucial index for evaluating elite inbred lines and selecting superior hybrids during maize breeding processes. Kernel size related traits are important components of grain yield. Therefore, dissecting the genetic basis of kernel size related traits and their combining ability is beneficial for improving maize yield. In this study, we performed genome-wide association study (GWAS) of kernel size related traits and their combining ability using 246 hybrids breed by designed as NCII mating. The broad-sense heritability of kernel length (KL), kernel width (KW), and kernel thickness (KT) was 76.20%, 86.52%, and 81.14%, respectively. The correlation coefficient between each trait and their combining ability was more than 0.58, indicating there was significant positive correlation. Based on the efficient mixed-model association expedited (EMMAX) algorithm, we identified 31, 21, and 5 significant single nucleotide polymorphisms (SNPs) associated with the best linear unbiased estimation (BLUE), general combining ability (GCA), and special combining ability (SCA) of kernel size related traits, respectively. Among these significant SNPs, 10 SNPs were co-located both kernel size related traits and their combining ability. The effect analysis of co-located significant SNPs showed that three SNPs were additive, four were partial dominance and one was overdominance. Further, 17 candidate genes were predicted from candidate regions of co-located SNPs or SNPs with large effect, such as shrunken 1, emp6 and so on. The results further dissect the genetic architecture of maize kernel size related traits and their combining ability and provide useful information for improving grain yield in maize breeding.

Key words: maize, hybrids, kernel size, combining ability, genome-wide association study

Table 1

Descriptive statistics analysis and analysis of variance of kernel size related traits (mm)"

来源 Source 粒长 KL 粒宽 KW 粒厚 KT
均值±标准差 Mean ± SD 12.62 ± 0.66 7.55 ± 0.44 4.30 ± 0.23
变异系数 CV 5.21% 5.78% 5.38%
偏度 Skewness 0.08 0.30 0.24
峰度 Kurtosis 0.15 0.41 -0.25
母本一般配合力 GCA female 2.22*** 0.26*** 1.55***
父本一般配合力 GCA male 25.86*** 3.89*** 6.60***
特殊配合力 SCA 0.56*** 0.08*** 0.18***
母本一般配合力×环境 GCA female × Environment 0.44 0.05** 0.11
父本一般配合力×环境GCA male × Environment 0.57 0.04 0.22*
特殊配合力×环境 SCA × Environment 0.35 0.04 0.09
基因型方差 $\sigma _{\text{g}}^{2}$ 0.31 0.17 0.04
基因型×环境方差 $\sigma _{\text{ge}}^{2}$ 0.02 0.00 0.00
广义遗传力 H2 (%) 76.20 86.52 81.14

Fig. 1

Correlation analysis of kernel size related traits and combining ability A: correlation analysis of kernel size related traits in different environments. B: correlation analysis between kernel size related traits and their combining ability. *, **, and *** indicate significant correlation at P < 0.05, P < 0.01, and P < 0.001, respectively; KL: kernel length; KW: kernel width; KT: kernel thickness; XY: Xunyi; YL: Yulin; BLUE: best linear unbiased estimation; GCA: general combining ability; SCA: special combining ability."

Fig. 2

Distribution of significant SNPs associated with kernel size related traits and their combining ability Abbreviations are the same as those given in Fig. 1."

Table 2

Associated SNPs of kernel size related traits and their combining ability including general combining ability (GCA) and special combining ability (SCA)"

序号
Number
性状
Trait
SNP标记
SNP marker
染色体
Chr.
位置
Position
等位基因
Allele
P
P-value
模型
Model
表型解释率
R2 (%)
1 KL_BLUE Affx-291427653 2 172,900,382 A/C 1.17E-05 加性Additive 2.65
2 KL_BLUE Affx-291399192 2 174,990,230 C/T 6.00E-05 显性Dominance 5.20
3 KL_BLUE Affx-291415239 2 188,723,861 A/G 1.23E-04 加性Additive 3.36
4 KL_BLUE Affx-291421576 3 4,667,059 C/T 1.17E-04 显性Dominance 0.59
5 KL_BLUE Affx-291388159 4 161,189,573 G/T 9.25E-05 显性Dominance 7.87
6 KL_BLUE Affx-291414096 5 19,152,693 G/A 1.12E-04 显性Dominance 7.50
7 KL_BLUE Affx-291382102 5 45,936,956 A/T 6.34E-05 显性Dominance 0.75
8 KL_BLUE Affx-291430485 5 199,891,583 T/C 3.77E-05 显性Dominance 0.84
序号
Number
性状
Trait
SNP标记
SNP marker
染色体
Chr.
位置
Position
等位基因
Allele
P
P-value
模型
Model
表型解释率
R2 (%)
9 KL_GCA Affx-88981164 2 109,561,515 G/A 2.62E-05 加性Additive 25.52
10 KL_GCA Affx-291438859 2 147,075,651 C/T 1.25E-04 加性Additive 7.29
11 KL_GCA Affx-291381936 2 172,197,055 G/A 7.39E-05 加性Additive 13.35
12 KL_GCA Affx-291427653 2 172,900,382 A/C 7.93E-07 加性Additive 0.80
13 KL_GCA Affx-291383897 2 173,344,526 G/C 1.86E-05 加性Additive 0.90
14 KL_GCA Affx-291399192 2 174,990,230 C/T 3.45E-05 加性Additive 0.03
15 KL_GCA Affx-291400614 2 177,112,609 C/T 4.06E-05 加性Additive 1.11
16 KL_GCA Affx-291415239 2 188,723,861 A/G 4.76E-06 加性Additive 0.42
17 KL_GCA Affx-291419252 2 194,294,110 T/C 9.17E-06 加性Additive 0.02
18 KL_SCA Affx-291414096 5 19,152,693 G/A 6.68E-05 显性Dominance 3.54
19 KW_BLUE Affx-291445199 1 180,428,491 C/T 1.16E-04 显性Dominance 10.90
20 KW_BLUE Affx-158946352 1 224,324,098 G/A 5.83E-05 加性Additive 0.65
21 KW_BLUE Affx-291438736 1 292,427,178 C/A 4.06E-05
5.00E-11
加性Additive
显性Dominance
28.23
0.07
22 KW_BLUE Affx-291386203 2 28,660,634 C/A 3.98E-05
2.31E-05
加性Additive
显性Dominance
3.79
0.44
23 KW_BLUE Affx-291438094 2 235,818,735 C/G 1.09E-05 显性Dominance 0.07
24 KW_BLUE Affx-291404824 3 1,338,197 C/A 2.84E-05
8.58E-06
加性Additive
显性Dominance
6.41
12.47
25 KW_BLUE Affx-291426461 4 35,122,656 T/C 3.23E-05 显性Dominance 0.11
26 KW_BLUE Affx-159061154 5 2,145,982 T/G 8.59E-05 显性Dominance 0.15
27 KW_BLUE Affx-291435207 7 277,626 A/G 5.33E-05 加性Additive 12.96
28 KW_BLUE Affx-291438357 9 38,415,742 T/C 8.18E-05 显性Dominance 0.18
29 KW_GCA Affx-291445199 1 180,428,491 C/T 1.34E-04 加性Additive 16.83
30 KW_GCA Affx-158946352 1 224,324,098 G/A 1.36E-04 加性Additive 6.47
31 KW_GCA Affx-158948129 1 235,021,563 C/T 7.38E-05 加性Additive 10.69
32 KW_GCA Affx-291438736 1 292,427,178 C/A 4.28E-06 加性Additive 16.97
33 KW_GCA Affx-291385173 2 5,147,139 T/C 3.83E-05 加性Additive 1.67
34 KW_GCA Affx-291420744 5 80,480,359 A/C 3.51E-05 加性Additive 7.50
35 KW_GCA Affx-291401044 9 129,309,960 A/G 2.72E-05 加性Additive 8.28
36 KW_SCA Affx-291436386 2 27,498,155 C/T 1.11E-04 显性Dominance 2.92
37 KT_BLUE Affx-291413666 1 118,986,201 A/C 8.08E-05 显性Dominance 7.95
38 KT_BLUE Affx-159032175 1 262,226,149 T/C 6.04E-06 显性Dominance 0.37
39 KT_BLUE Affx-291390855 1 262,368,074 C/T 4.17E-05
1.60E-05
加性Additive
显性Dominance
12.47
7.33
40 KT_BLUE Affx-158839028 1 280,195,356 C/A 7.78E-05 显性Dominance 3.39
41 KT_BLUE Affx-291410051 1 285,592,051 C/T 5.51E-05 显性Dominance 4.21
42 KT_BLUE Affx-291443747 2 23,623,257 G/A 8.77E-05 加性Additive 25.58
43 KT_BLUE Affx-291388256 2 195,694,458 C/T 1.19E-04 显性Dominance 0.34
44 KT_BLUE Affx-291401517 2 235,207,369 G/A 1.26E-05 显性Dominance 0.26
45 KT_BLUE Affx-291441620 3 85,891,477 T/C 6.06E-06 显性Dominance 2.57
46 KT_BLUE Affx-291422512 9 11,615,037 G/A 1.36E-04 显性Dominance 0.53
47 KT_BLUE Affx-291445448 9 15,315,557 A/C 8.53E-05 显性Dominance 3.25
48 KT_BLUE Affx-291438777 9 107,428,822 G/A 2.59E-05 显性Dominance 0.04
49 KT_BLUE Affx-291378767 10 144,701,539 C/A 1.09E-04 显性Dominance 2.76
50 KT_GCA Affx-291399215 1 104,625,663 C/T 3.57E-05 加性Additive 21.69
序号
Number
性状
Trait
SNP标记
SNP marker
染色体
Chr.
位置
Position
等位基因
Allele
P
P-value
模型
Model
表型解释率
R2 (%)
51 KT_GCA Affx-291390855 1 262,368,074 C/T 7.69E-05 加性Additive 10.71
52 KT_GCA Affx-291418355 3 1,713,800 A/G 1.18E-04 加性Additive 9.51
53 KT_GCA Affx-291442108 4 12,611,068 G/A 9.26E-05 加性Additive 0.03
54 KT_GCA Affx-291425118 5 37,099,257 C/T 1.14E-04 加性Additive 4.83
55 KT_SCA Affx-291399798 3 11,407,826 G/A 9.19E-05 显性Dominance 3.52
56 KT_SCA Affx-291422512 9 11,615,037 G/A 4.99E-05 显性Dominance 5.84
57 KT_SCA Affx-291438777 9 107,428,822 G/A 8.20E-05 显性Dominance 1.66

Table 3

Effects analysis of co-located SNPs between BLUE and their combining ability including general combining ability (GCA) and special combining ability (SCA)"

序号
Number
性状
Trait
SNP名称
SNP marker
染色体
Chr.
位置
Position
显性度
Dominance effect index
效应
Effect
1 KL_BLUE, KL_GCA Affx-291427653 2 172,900,382 0.03 加性 Additive
2 KL_BLUE, KL_GCA Affx-291399192 2 174,990,230 -0.12 加性 Additive
3 KL_BLUE, KL_GCA Affx-291415239 2 188,723,861 -0.55 部分显性 Partial dominance
4 KL_BLUE, KL_SCA Affx-291414096 5 19,152,693 2.64 超显性 Overdominance
5 KW_BLUE, KW_GCA Affx-291445199 1 180,428,491
6 KW_BLUE, KW_GCA Affx-158946352 1 224,324,098 -0.08 加性Additive
7 KW_BLUE, KW_GCA Affx-291438736 1 292,427,178 -0.57 部分显性 Partial dominance
8 KT_BLUE, KT_GCA Affx-291390855 1 262,368,074
9 KT_BLUE, KT_SCA Affx-291422512 9 11,615,037 -0.60 部分显性 Partial dominance
10 KT_BLUE, KT_SCA Affx-291438777 9 107,428,822 -0.57 部分显性 Partial dominance

Fig. 3

Allele distribution and phenotypic difference of co-located SNPs between traits and their combine ability ** and *** indicate significant difference at P < 0.01 and P < 0.001, respectively. Abbreviations are the same as those given in Table 1."

Fig. 4

Functional enrichment analysis of genes expressed in kernel in the candidate interval. A: GO analysis; B: KEGG pathway analysis. BP: biological process; CC: cellular component; MF: biological process."

Table 4

Putative candidate genes of kernel size related traits and their combining ability including general combining ability (GCA) and special combining ability (SCA)"

序号
Number
性状
Trait
SNP标记
SNP marker
染色体
Chr.
候选基因
Candidate gene
注释
Description
1 KT_GCA Affx-291399215 1 GRMZM2G025157 Putative pentatricopeptide repeat-containing protein
2 KW_BLUE, KW_GCA Affx-291445199 1 GRMZM2G085474 Thiolase1 (thl1)
3 KW_BLUE, KW_GCA Affx-158946352 1 GRMZM2G031572 Putative serine peptidase S28 family protein
4 KW_GCA Affx-158948129 1 GRMZM2G464680 Xyloglucan galactosyltransferase KATAMARI 1
5 KT_BLUE, KT_GCA Affx-291390855 1 GRMZM2G022997 Inositol hexakisphosphate and diphosphoinositol- pentakisphosphatekinase VIP2
6 KW_BLUE, KW_GCA Affx-291438736 1 GRMZM2G450920 Protein SCAR2
7 KT_BLUE Affx-291443747 2 GRMZM2G505380 Protein O-glucosyltransferase 1
8 KL_GCA Affx-88981164 2 GRMZM2G158043 Pullulanase-type starch debranching enzyme1 (zpu1)
9 KL_BLUE, KL_GCA Affx-291427653 2 GRMZM2G014106 Enhancer of polycomb-like transcription factor
10 KL_GCA Affx-291381936 2 GRMZM2G104546 Aspartate kinase homoserine dehydrogenase 2
11 KL_BLUE, KL_GCA Affx-291399192 2 AC203957.3_FG004 BZIP-transcription factor 40
12 KL_BLUE, KL_GCA Affx-291415239 2 GRMZM2G048392 Empty pericarp6 (emp6)
13 KW_BLUE Affx-291404824 3 GRMZM2G175218 Beta amylase4 (amyb4)
14 KL_BLUE, KL_SCA Affx-291414096 5 GRMZM2G081221 Protein phosphatase 1 regulatory inhibitor
15 KW_BLUE Affx-291435207 7 GRMZM5G800488 Laccase20 (lac20)
16 KT_BLUE, KT_SCA Affx-291422512 9 GRMZM2G089713 Sucrose synthase (shrunken1)
17 KT_BLUE, KT_SCA Affx-291438777 9 GRMZM2G048472 Homogentisate phytyltransferase VTE2-1
[1] Troyer A F. Development of Hybrid Corn and the Seed Corn Industry. Handbook of Maize. New York: Springer, 2009. pp 87-114.
[2] Zhang R Y, Xu G, Li J S, Yan J B, Li H H, Yang X H. Patterns of genomic variation in Chinese maize inbred lines and implications for genetic improvement. Theor Appl Genet, 2018, 131: 1207-1221.
doi: 10.1007/s00122-018-3072-z
[3] Sprague G F, Tatum L A. General vs specific combining ability in single crosse of corn. J Am Soc Agron, 1942, 34: 923-932.
doi: 10.2134/agronj1942.00021962003400100008x
[4] Reif J C, Gumpert F M, Fischer S, Melchinger A E. Impact of interpopulation divergence on additive and dominance variance in hybrid populations. Genetics, 2007, 176: 1931-1934.
pmid: 17507673
[5] Chen J X, Zhou H, Xie W B, Xia D, Gao G J, Zhang Q L, Wang G W, Lian X M, Xiao J H, He Y Q. Genome-wide association analyses reveal the genetic basis of combining ability in rice. Plant Biotechnol J, 2019, 17: 2211-2222.
doi: 10.1111/pbi.13134
[6] Geng X L, Sun G F, Qu Y J, Sarfraz Z, Jia Y H, He S P, Pan Z E, Sun J L, Iqbal M S, Wang Q L. Genome-wide dissection of hybridization for fiber quality-and yield-related traits in upland cotton. Plant J, 2020, 104: 1285.
[7] Zhou Z Q, Zhang C S, Lu X H, Wang L W, Hao Z F, Li M S, Zhang D G, Yong H J, Zhu H Y, Weng J F. Dissecting the genetic basis underlying combining ability of plant height related traits in maize. Front Plant Sci, 2018, 9: 1117.
[8] Lu X, Zhou Z Q, Yuan Z H, Zhang C S, Hao Z F, Wang Z H, Li M S, Zhang D G, Yong H J, Han J N, Li X H, Weng J F. Genetic dissection of the general combining ability of yield-related traits in maize. Front Plant Sci, 2020, 11: 788.
[9] Liu X G, Hu X J, Li K, Liu Z F, Wu Y J, Feng G, Huang C L, Wang H W. Identifying quantitative trait loci for the general combining ability of yield-relevant traits in maize. Breed Sci, 2021, 71: 217-228.
doi: 10.1270/jsbbs.20008
[10] 刘文童, 监立强, 郭晋杰, 赵永锋, 黄亚群, 陈景堂, 祝丽英. 玉米穗部性状及其一般配合力的关联分析. 植物遗传资源学报, 2020, 21: 706-715.
Liu W T, Jian L Q, Guo J J, Zhao Y F, Huang Y Q, Chen J T, Zhu L Y. Association analysis of ear-related traits and their general combining ability in maize. J Plant Genet Resour, 2020, 21: 706-715. (in Chinese with English abstract)
[11] Li C H, Li Y X, Sun B C, Peng B, Liu C, Liu Z Z, Yang Z Z, Li Q C, Tan W W, Zhang Y. Quantitative trait loci mapping for yield components and kernel-related traits in multiple connected RIL populations in maize. Euphytica, 2013, 193: 303-316.
doi: 10.1007/s10681-013-0901-7
[12] Peng B, Li Y X, Wang Y, Liu C, Liu Z Z, Tan W W, Zhang Y, Wang D, Shi Y S, Sun B C. QTL analysis for yield components and kernel-related traits in maize across multi-environments. Theor Appl Genet, 2011, 122: 1305-1320.
doi: 10.1007/s00122-011-1532-9 pmid: 21286680
[13] Liu M, Tan X L, Yang Y, Liu P, Zhang X X, Zhang Y C, Wang L, Hu Y, Ma L L, Li Z L. Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping. Plant Biotechnol J, 2020, 18: 207-221.
doi: 10.1111/pbi.13188
[14] Lan T R, He K H, Chang L G, Cui T T, Zhao Z X, Xue J Q, Liu J C. QTL mapping and genetic analysis for maize kernel size and weight in multi-environments. Euphytica, 2018, 214: 119.
[15] 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.
[16] 倪先林, 张涛, 蒋开锋, 杨莉, 杨乾华, 曹应江, 文春阳, 郑家奎. 杂交稻特殊配合力与杂种优势、亲本间遗传距离的相关性. 遗传, 2009, 31: 849-854.
Ni X L, Zhang T, Jiang K F, Yang L, Yang Q H, Cao Y J, Wen C Y, Zheng J K. Correlations between specific combining ability, heterosis and genetic distance in hybrid rice. Hereditas, 2009, 31: 849-854. (in Chinese with English abstract)
[17] Knapp S J, Stroup W W, Ross W M. Exact confidence intervals for heritability on a progeny mean basis 1. Crop Sci, 1985, 25: 192-194.
doi: 10.2135/cropsci1985.0011183X002500010046x
[18] Murray M G, Thompson W F. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res, 1980, 8: 4321-4326.
pmid: 7433111
[19] Danecek P, Auton A, Abecasis G, Albers C A, Banks E, Depristo M A, Handsaker R E, Lunter G, Marth G T, Sherry S T. The variant call format and VCFtools. Bioinformatics, 2011, 27: 2156-2158.
doi: 10.1093/bioinformatics/btr330 pmid: 21653522
[20] Ayres D L, Darling A, Zwickl D J, Beerli P, Holder M T, Lewis P O, Huelsenbeck J P, Ronquist F, Swofford D L, Cummings M P. BEAGLE: an application programming interface and high- performance computing library for statistical phylogenetics. Syst Biol, 2012, 61: 170-173.
doi: 10.1093/sysbio/syr100
[21] Zhou X, Stephens M. Genome-wide efficient mixed-model analysis for association studies. Nat Genet, 2012, 44: 821-824.
doi: 10.1038/ng.2310
[22] Huang X H, Yang S H, Gong J Y, Zhao Y, Feng Q, Gong H, Li W J, Zhan Q L, Cheng B Y, Xia J H. Genomic analysis of hybrid rice varieties reveals numerous superior alleles that contribute to heterosis. Nat Commun, 2015, 6: 6258.
[23] Gao X Y, Starmer J, Martin E R. A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms. Genet Epidemiol, 2008, 32: 361-369.
doi: 10.1002/gepi.20310
[24] Liu H J, Wang Q, Chen M J, Ding Y H, Yang X R, Liu J, Li X H, Zhou C C, Tian Q L, Lu Y Q. Genome-wide identification and analysis of heterotic loci in three maize hybrids. Plant Biotechnol J, 2020, 18: 185-194.
doi: 10.1111/pbi.13186
[25] 渠建洲, 冯文豪, 张兴华, 徐淑兔, 薛吉全. 基于全基因组关联分析解析玉米籽粒大小的遗传结构. 作物学报, 2022, 48: 304-319.
doi: 10.3724/SP.J.1006.2022.13002
Qu J X, Feng W H, Zhang X H, Xu S T, Xue J Q. Dissecting the genetic architecture of maize kernel size based on genome-wide association study. Acta Agron Sin, 2022, 48: 304-319. (in Chinese with English abstract)
[26] Chen J, Zeng B, Zhang M, Xie S J, Wang G K, Hauck A, Lai J S. Dynamic transcriptome landscape of maize embryo and endosperm development. Plant Physiol, 2014, 166: 252-264.
doi: 10.1104/pp.114.240689
[27] Huerta-Cepas J, Forslund K, Coelho L P, Szklarczyk D, Jensen L J, von Mering C, Bork P. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol Biol Evol, 2017, 34: 2115-2122.
doi: 10.1093/molbev/msx148 pmid: 28460117
[28] Yu G C, Wang L G, Han Y Y, He Q Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS, 2012, 16: 284-287.
doi: 10.1089/omi.2011.0118
[29] Chettoor A M, Yi G, Gomez E, Hueros G, Meeley R B, Becraft P W. A putative plant organelle RNA recognition protein gene is essential for maize kernel development. J Integr Plant Biol, 2015, 57: 236-246.
doi: 10.1111/jipb.12234
[30] Qu Z, Li L Z, Luo J Y, Wang P, Yu S B, Mou T M, Zheng X F, Hu Z L. QTL mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses. PLoS One, 2012, 7: e28463.
[31] Qi H H, Huang J, Zheng Q, Huang Y Q, Shao R X, Zhu L Y, Zhang Z X, Qiu F Z, Zhou G C, Zheng Y L. Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines. Theor Appl Genet, 2013, 126: 369-377.
doi: 10.1007/s00122-012-1985-5
[32] 王博新, 王亚辉, 陈朋飞, 冯志前, 郝引川, 张仁和, 张兴华, 薛吉全. 源于陕A群、陕B群玉米自交系在不同密度条件下配合力分析. 作物学报, 2017, 43: 1328-1336.
doi: 10.3724/SP.J.1006.2017.01328
Wang B X, Wang Y H, Chen P F, Feng Z Q, Hao Y C, Zhang R H, Zhang X H, Xue J Q. Combining ability of maize inbred lines from Shaan A group and Shaan B group under different density conditions. Acta Agron Sin, 2017, 43: 1328-1336. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2017.01328
[33] Jiang Y, Schmidt R H, Zhao Y, Reif J C. A quantitative genetic framework highlights the role of epistatic effects for grain-yield heterosis in bread wheat. Nat Genet, 2017, 49: 1741-1746.
doi: 10.1038/ng.3974 pmid: 29038596
[34] Li C H, Li Y X, Sun B C, Peng B, Liu C, Liu Z Z, Yang Z Z, Li Q C, Tan W W, Zhang Y. Quantitative trait loci mapping for yield components and kernel-related traits in multiple connected RIL populations in maize. Euphytica, 2013, 193: 303-316.
doi: 10.1007/s10681-013-0901-7
[35] Raihan M S, Liu J, Huang J, Guo H, Pan Q C, Yan J B. Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng 58 × SK maize population. Theor Appl Genet, 2016, 129: 1465-1477.
doi: 10.1007/s00122-016-2717-z
[36] Liu Y, Wang L W, Sun C L, Zhang Z X, Zheng Y L, Qiu F Z. Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments. Theor Appl Genet, 2014, 127: 1019-1037.
doi: 10.1007/s00122-014-2276-0
[37] Dinges J R, Colleoni C, James M G, Myers A M. Mutational analysis of the pullulanase-type debranching enzyme of maize indicates multiple functions in starch metabolism. Plant Cell, 2003, 15: 666-680.
pmid: 12615940
[38] Zheng Y X, Yuan F, Huang Y Q, Zhao Y F, Jia X Y, Zhu L Y, Guo J J. Genome-wide association studies of grain quality traits in maize. Sci Rep, 2021, 11: 9797.
[39] Liu J, Huang J, Guo H, Lan L, Wang H Z, Xu Y C, Yang X H, Li W Q, Tong H, Xiao Y J. The conserved and unique genetic architecture of kernel size and weight in maize and rice. Plant Physiol, 2017, 175: 774-785.
doi: 10.1104/pp.17.00708
[40] Zhang K, Wang F, Liu B Y, Xu C Z, He Q X, Cheng W, Zhao X Y, Ding Z H, Zhang W, Zhang K W. ZmSKS13, a cupredoxin domain-containing protein, is required for maize kernel development via modulation of redox homeostasis. New Phytol, 2021, 229: 2163-2178.
doi: 10.1111/nph.16988 pmid: 33034042
[1] DUAN Can-Xing, CUI Li-Na, XIA Yu-Sheng, DONG Huai-Yu, YANG Zhi-Huan, HU Qing-Yu, SUN Su-Li, LI Xiao, ZHU Zhen-Dong, WANG Xiao-Ming. Precise characterization and analysis of maize germplasm resources for resistance to Fusarium ear rot and Gibberella ear rot [J]. Acta Agronomica Sinica, 2022, 48(9): 2155-2167.
[2] ZHANG Zhen-Bo, QU Xin-Yue, YU Ning-Ning, REN Bai-Zhao, LIU Peng, ZHAO Bin, ZHANG Ji-Wang. Effects of nitrogen application rate on grain filling characteristics and endogenous hormones in summer maize [J]. Acta Agronomica Sinica, 2022, 48(9): 2366-2376.
[3] GUO Yao, CHAI Qiang, YIN Wen, FAN Hong. Research progress of photosynthetic physiological mechanism and approaches to application in dense planting maize [J]. Acta Agronomica Sinica, 2022, 48(8): 1871-1883.
[4] WANG Sha-Sha, HUANG Chao, WANG Qing-Chang, CHAO Yue-En, CHEN Feng, SUN Jian-Guo, SONG Xiao. Cloning and functional identification of TaGS2 gene related to kernel size in bread wheat [J]. Acta Agronomica Sinica, 2022, 48(8): 1926-1937.
[5] WANG Tian-Bo, HE Wen-Xue, ZHANG Jun-Ming, LYU Wei-Zeng, LIANG Yu-Huan, LU Yang, WANG Yu-Lu, GU Feng-Xu, SONG Ci, CHEN Jun-Ying. ROS production and ATP synthase subunit mRNAs integrity in artificially aged maize embryos [J]. Acta Agronomica Sinica, 2022, 48(8): 1996-2006.
[6] XIA Xiu-Zhong, ZHANG Zong-Qiong, YANG Xing-Hai, ZHUANG Jie, ZENG Yu, DENG Guo-Fu, SONG Guo-Xian, HUANG Yu-Xiao, NONG Bao-Xuang, LI Dan-Ting. Genome wide association study of salt tolerance at the germination stage for core Germplasm of rice landrace in Guangxi, China [J]. Acta Agronomica Sinica, 2022, 48(8): 2007-2015.
[7] PEI Li-Zhen, CHEN Yuan-Xue, ZHANG Wen-Wen, XIAO Hua, ZHANG Sen, ZHOU Yuan, XU Kai-Wei. Effects of organic material returned on photosynthetic performance and nitrogen metabolism of ear leaf in summer maize [J]. Acta Agronomica Sinica, 2022, 48(8): 2115-2124.
[8] YANG Ying-Xia, ZHANG Guan, WANG Meng-Meng, LU Guo-Qing, WANG Qian, CHEN Rui. Molecular characterization of transgenic maize GM11061 based on high-throughput sequencing technology [J]. Acta Agronomica Sinica, 2022, 48(7): 1843-1850.
[9] WANG Dan, ZHOU Bao-Yuan, MA Wei, GE Jun-Zhu, DING Zai-Song, LI Cong-Feng, ZHAO Ming. Characteristics of the annual distribution and utilization of climate resource for double maize cropping system in the middle reaches of Yangtze River [J]. Acta Agronomica Sinica, 2022, 48(6): 1437-1450.
[10] YANG Huan, ZHOU Ying, CHEN Ping, DU Qing, ZHENG Ben-Chuan, PU Tian, WEN Jing, YANG Wen-Yu, YONG Tai-Wen. Effects of nutrient uptake and utilization on yield of maize-legume strip intercropping system [J]. Acta Agronomica Sinica, 2022, 48(6): 1476-1487.
[11] CHEN Jing, REN Bai-Zhao, ZHAO Bin, LIU Peng, ZHANG Ji-Wang. Regulation of leaf-spraying glycine betaine on yield formation and antioxidation of summer maize sowed in different dates [J]. Acta Agronomica Sinica, 2022, 48(6): 1502-1515.
[12] SHAN Lu-Ying, LI Jun, LI Liang, ZHANG Li, WANG Hao-Qian, GAO Jia-Qi, WU Gang, WU Yu-Hua, ZHANG Xiu-Jie. Development of genetically modified maize (Zea mays L.) NK603 matrix reference materials [J]. Acta Agronomica Sinica, 2022, 48(5): 1059-1070.
[13] WANG Hai-Bo, YING Jing-Wen, HE Li, YE Wen-Xuan, TU Wei, CAI Xing-Kui, SONG Bo-Tao, LIU Jun. Identification of chromosome loss and rearrangement in potato and eggplant somatic hybrids by rDNA and telomere repeats [J]. Acta Agronomica Sinica, 2022, 48(5): 1273-1278.
[14] XU Jing, GAO Jing-Yang, LI Cheng-Cheng, SONG Yun-Xia, DONG Chao-Pei, WANG Zhao, LI Yun-Meng, LUAN Yi-Fan, CHEN Jia-Fa, ZHOU Zi-Jian, WU Jian-Yu. Overexpression of ZmCIPKHT enhances heat tolerance in plant [J]. Acta Agronomica Sinica, 2022, 48(4): 851-859.
[15] LIU Lei, ZHAN Wei-Min, DING Wu-Si, LIU Tong, CUI Lian-Hua, JIANG Liang-Liang, ZHANG Yan-Pei, YANG Jian-Ping. Genetic analysis and molecular characterization of dwarf mutant gad39 in maize [J]. Acta Agronomica Sinica, 2022, 48(4): 886-895.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] WANG Li-Yan;ZHAO Ke-Fu. Some Physiological Response of Zea mays under Salt-stress[J]. Acta Agron Sin, 2005, 31(02): 264 -268 .
[2] WANG Chun-Mei;FENG Yi-Gao;ZHUANG Li-Fang;CAO Ya-Ping;QI Zeng-Jun;BIE Tong-De;CAO Ai-Zhong;CHEN Pei-Du. Screening of Chromosome-Specific Markers for Chromosome 1R of Secale cereale, 1V of Haynaldia villosa and 1Rk#1 of Roegneria kamoji[J]. Acta Agron Sin, 2007, 33(11): 1741 -1747 .
[3] YANG Yan;ZHAO Xian-Lin; ZHANG Yong;CHEN Xin-Min;HE Zhong-Hu;YU Zhuo;XIA Lan-Qin
. Evaluation and Validation of Four Molecular Markers Associated with Pre-Harvest Sprouting Tolerance in Chinese Wheats[J]. Acta Agron Sin, 2008, 34(01): 17 -24 .
[4] Wang Dong;Yu Zhenwen;Wang Xudong. Effects of Sulfur on Protein Accumulation in Kernels of Winter Wheat[J]. Acta Agron Sin, 2003, 29(06): 878 -883 .
[5] ZHAO Xiang;WANG Yan-Liang;WANG Ya-Jing;WANG Xi-Li;ZHANG Xiao. Effects of Exogenous Ca2+ on Somatal Movement and Plasma Membrane K+ Channels of Vicia Guard Cell under Salt Stress[J]. Acta Agron Sin, 2008, 34(11): 1970 -1976 .
[6] Ye Xiaoli;Li Xuegang;Li Jiana. Mechanism of Melanin Synthesis in Seed Coat of Brassica napus L.[J]. Acta Agron Sin, 2002, 28(05): 638 -643 .
[7] XU Ning;CHENG Xu-Zhen;WANG Su-Hua;WANG Li-Xia;ZHAO Dan. Establishment of an Adzuki Bean (Vigna angularis) Core Collection Based on Geographical Distribution and Phenotypic Data in China[J]. Acta Agron Sin, 2008, 34(08): 1366 -1373 .
[8] Meng Jinling;Liu Houli. THE EFFECTS OF SUCCESSIVE INBREEDING ON THE EMBRYO DEVELOPMENT OF BRASSICA NAPUS L[J]. Acta Agron Sin, 1986, 12(02): 79 -86 .
[9] Li Changbao;Liu Yanhua;Du Changqing;Kong Lingrang. Embryological Studies on the Fertility of the Original and Reciprocal Crosses between T.aestivumand Ae.tauschii[J]. Acta Agron Sin, 2002, 28(02): 170 -174 .
[10] Hu Hongkai;Ma Shangyao;Shi Yanhua. THE DISCOVERY OF A DOMINANT MALE-STERILE GENE IN MILLET(SETARIA ITALIICA)[J]. Acta Agron Sin, 1986, 12(02): 73 -78 .