基于全基因组关联分析解析玉米籽粒大小的遗传结构

doi:10.3724/SP.J.1006.2022.13002

Abstract

Abstract:

Kernel size related traits are one of the important compounds of yield, and they are also complex quantitative traits regulated by multiple genes. Mining the key regulatory genes of maize kernel size related traits will help to improve the yield. In this study, 212 excellent maize inbred lines were selected as materials. The kernel length, kernel width, and kernel thickness were measured in 2018 and 2019, respectively, and we performed genome-wide association study (GWAS) based on 73,006 single nucleotide polymorphic (SNP) markers uniformly distributed in maize genome. Based on the FarmCPU algorithm, 47 SNP markers associated with kernel size related traits were detected on 10 chromosomes in maize. Combined with the public dynamic spatio-temporal transcriptional data of kernel development of B73 maize inbred line, 58 candidate genes related to kernel size were detected in the linkage disequilibrium (LD) region marked by significant SNP. The proteins encoded by candidate genes interacted with multiple proteins and participated in and regulated many biological processes closely related to kernel development. These results provide a new reference for understanding the molecular regulation mechanism of maize kernel development, improving kernel size and increasing crop yield.

Key words: maize, kernel size, genome-wide association study, gene expression

QU Jian-Zhou, FENG Wen-Hao, ZHANG Xing-Hua, XU Shu-Tu, XUE Ji-Quan. Dissecting the genetic architecture of maize kernel size based on genome-wide association study[J].Acta Agronomica Sinica, 2022, 48(2): 304-319.

Figures/Tables 13

Table 1

Fig. 1

Fig. 2

Table 2

SNPs of kernel length, kernel width, and kernel thickness in different years"

标记名称 SNP ID	年份 Year	性状 Trait	基因型 Genotype	最小等位基因频率 MAF	染色体 Chr.	位置 Position	P值 P-value	表型贡献率 R² (%)
Affx-291392839	2018	KL	C/T	0.45	2	205,144,469	1.29E-05	0.36
Affx-291410933	2018	KL	A/C	0.23	2	191,587,706	1.35E-05	4.52
Affx-291385262	2018	KL	C/T	0.40	4	188,701,278	8.25E-06	6.96
Affx-158858862	2018	KL	A/G	0.47	7	132,422,651	5.35E-07	20.90
Affx-88989857	2019	KL	C/A	0.43	5	172,855,146	1.02E-05	11.64
Affx-291391022	2019	KL	T/C	0.41	9	207,693,32	8.33E-06	14.53
Affx-291390553	BLUP	KL	C/T	0.46	1	14,651,295	6.14E-06	1.24
Affx-291430755	BLUP	KL	T/G	0.26	1	52,391,689	5.62E-07	13.31
Affx-291442609	BLUP	KL	G/A	0.37	2	134,763,888	2.39E-06	8.31
Affx-291378135	BLUP	KL	C/T	0.10	3	210,753,912	2.08E-07	5.97
Affx-291412195	BLUP	KL	C/T	0.30	3	128,909,025	4.11E-07	16.92
Affx-291417243	BLUP	KL	G/T	0.20	5	132,317,996	6.14E-10	13.73
Affx-291423518	BLUP	KL	A/G	0.36	5	10,908,609	2.63E-09	22.90
Affx-159157467	BLUP	KL	G/A	0.38	9	20,345,047	4.14E-06	12.08
Affx-291421141	2018	KW	T/C	0.21	1	244,696,518	6.28E-11	18.69
Affx-291429284	2018	KW	C/A	0.45	1	95,971,671	4.07E-08	18.38
Affx-291434526	2018	KW	C/T	0.21	3	212,098,697	1.14E-05	0.62
Affx-291383862	2018	KW	T/C	0.42	4	229,953,723	3.18E-06	14.42
Affx-291396984	2018	KW	T/C	0.44	4	118,709,183	3.67E-06	2.38
Affx-291430867	2018	KW	G/A	0.33	4	74,628,134	1.30E-05	11.78
Affx-291433635	2018	KW	G/A	0.33	4	186,554,980	7.87E-06	19.65
Affx-291390831	2019	KW	A/G	0.23	2	7,631,038	1.63E-07	6.09
Affx-291416165	2019	KW	G/A	0.27	2	41,515,971	4.32E-07	1.50
Affx-291388322	2019	KW	A/G	0.36	6	94,087,816	5.57E-08	5.08
Affx-291396454	2019	KW	G/A	0.07	6	21,380,243	9.41E-07	15.80
Affx-291421141	BLUP	KW	T/C	0.23	1	244,696,518	4.18E-09	18.51
Affx-291391782	BLUP	KW	G/A	0.49	2	214,513,500	6.90E-12	18.84
Affx-291386982	BLUP	KW	G/A	0.38	3	140,660,245	7.62E-10	4.90
Affx-291443225	BLUP	KW	C/T	0.47	5	1,250,179	5.12E-07	1.73
Affx-291416220	BLUP	KW	G/A	0.41	6	98,426,114	1.09E-05	1.67
Affx-291424033	2018	KT	G/A	0.32	1	279,751,443	1.88E-06	7.04
Affx-291437625	2018	KT	C/T	0.23	1	246,781,098	1.58E-06	8.62
Affx-291442339	2018	KT	T/G	0.10	1	198,355,431	2.82E-06	13.41
Affx-291423488	2018	KT	G/A	0.39	3	117,603,753	5.43E-08	14.05
Affx-123595299	2018	KT	T/C	0.46	4	33,851,115	6.28E-08	3.06
Affx-291407692	2018	KT	C/T	0.47	4	68,756,350	2.42E-10	7.53
Affx-291421461	2018	KT	T/G	0.24	5	190,291,719	7.78E-07	12.80
Affx-291440347	2018	KT	T/C	0.27	5	46,983,911	2.69E-07	3.51
Affx-291431852	2018	KT	C/T	0.09	8	33,721,488	1.07E-12	11.05
Affx-291393756	2018	KT	T/C	0.17	10	144,450,832	2.09E-06	4.11
Affx-291392059	2019	KT	A/T	0.47	1	204,796,933	1.16E-05	19.87
Affx-291380154	2019	KT	T/C	0.13	2	196,175,692	1.10E-05	19.15
Affx-291409744	BLUP	KT	A/G	0.37	1	181,908,322	1.49E-06	3.75
Affx-291424033	BLUP	KT	G/A	0.31	1	279,751,443	1.17E-09	10.20
Affx-291384679	BLUP	KT	C/A	0.32	3	56,819,365	7.59E-06	8.77
Affx-291424461	BLUP	KT	T/C	0.39	4	43,693,955	1.31E-06	1.38
Affx-291442826	BLUP	KT	G/A	0.29	4	38,973,447	2.77E-06	15.91
Affx-291427217	BLUP	KT	T/C	0.46	5	59,748,660	3.61E-06	6.66
Affx-291432324	BLUP	KT	A/G	0.08	8	18,220,008	1.22E-07	14.41

Table 2

Table 3

Candidate genes and their annotations of KL, KW, and KT in maize"

标记名称 SNP ID	基因 Gene	性状 Trait	染色体 Chr.		位置 Position	功能注释 Annotation	模块 Module
Affx-291430755	GRMZM2G033570	KL	1		52,391,689	ETHYLENE-INSENSITIVE3-like 1 protein	M1
Affx-291410933	GRMZM2G014313	KL	2		191,587,706	Protein pob	M2
Affx-291410933	GRMZM2G007885	KL	2		191,587,706	Myosin heavy chain-related protein	M3
Affx-291410933	GRMZM2G150319	KL	2		191,587,706	O-fucosyltransferase family protein	M4
Affx-291392839	GRMZM5G821439	KL	2		205,144,469	Chitin-inducible gibberellin-responsive protein 1	M5
Affx-291392839	GRMZM2G046011	KL	2		205,144,469	60S ribosomal protein L38	M6
Affx-291392839	GRMZM2G163233	KL	2		205,144,469	Male sterile 32	M7
Affx-291412195	GRMZM2G122443	KL	3		128,909,025	OS-9-like protein	M8
Affx-291412195	GRMZM2G122481	KL	3		128,909,025	Cytochrome c oxidase subunit 5C	M9
Affx-291412195	GRMZM2G138077	KL	3		128,909,025	Uncharacterized protein	—
Affx-291378135	AC230013.2_FG007	KL	3		210,753,912	60S ribosomal protein L18a	—
Affx-291378135	GRMZM2G150631	KL	3		210,753,912	Transducin/WD40 repeat-like superfamily protein	M10
Affx-88989857	GRMZM2G119517	KL	5		172,855,146	ACT domain-containing protein ACR3	M11
Affx-291423518	GRMZM2G145854	KL	5		10,908,609	NADH-ubiquinone oxidoreductase subunit	M12
Affx-291423518	GRMZM2G569855	KL	5		10,908,609	Threonine dehydratase 1 biosynthetic	M13
Affx-291423518	GRMZM2G109383	KL	5		10,908,609	Phosphoglucomutase 2	M14
Affx-291391022	GRMZM5G829544	KL	9		20,769,332	Fatty acyl-ACP thioesterase 2	M15
Affx-291391022	GRMZM2G147399	KL	9		20,769,332	Early nodulin 93	M16
Affx-291391022	GRMZM2G131421	KL	9		20,769,332	Early nodulin 93	M17
Affx-291391022	GRMZM2G404897	KL	9		20,769,332	Zinc finger protein	M18
Affx-159157467	GRMZM2G173693	KL	9	20,345,047	Pre-mRNA-splicing factor 38B-like		M19
Affx-291416165	GRMZM2G325131	KW	2	41,515,971	Anthranilate synthase homolog 1		M20
Affx-291391782	GRMZM2G049347	KW	2	214,513,500	Synaptotagmin-5		M21
Affx-291434526	GRMZM2G152686	KW	3	212,098,697	Pyruvate kinase		M22
Affx-291434526	GRMZM2G070360	KW	3	212,098,697	V-type proton ATPase subunit E-like		M23
Affx-291430867	GRMZM2G117755	KW	4	74,628,134	Hypersensitive-induced response protein 2		M24
Affx-291383862	GRMZM2G162992	KW	4	229,953,723	KH domain-containing protein		M25
Affx-291443225	GRMZM2G034326	KW	5	1,250,179	DNA-directed RNA polymerases II, IV, and V subunit 8B		M26
Affx-291443225	GRMZM2G069916	KW	5	1,250,179	LUC7 related protein		M27
Affx-291443225	GRMZM2G138676	KW	5	1,250,179	Shaggy-related protein kinase kappa		M28
Affx-291396454	GRMZM2G060856	KW	6	21,380,243	Membrane protein		M29
Affx-291442339	GRMZM2G318475	KT	1	198,355,431	Eukaryotic translation initiation factor 6		M30
Affx-291442339	GRMZM2G017110	KT	1	198,355,431	Glutamate decarboxylase		M31
Affx-291437625	GRMZM2G012119	KT	1	246,781,098	Post-illumination chlorophyll fluorescence increase		M32
Affx-291437625	GRMZM2G013600	KT	1	246,781,098	DNA-directed RNA polymerases I, II, and III polypeptide		M33
Affx-291437625	GRMZM2G146819	KT	1	246,781,098	Uncharacterized protein		M34
Affx-291437625	GRMZM2G146818	KT	1	246,781,098	40S ribosomal protein		—
Affx-291437625	GRMZM2G146589	KT	1	246,781,098	Lysine-tRNA ligase		M35
Affx-291437625	GRMZM2G146486	KT	1	246,781,098	P-loop containing nucleoside triphosphate hydrolase Superfamily protein		M36
Affx-291437625	GRMZM2G034417	KT	1	246,781,098	Inositol-phosphate phosphatase		M37
Affx-291424033	GRMZM2G047456	KT	1	279,751,443	Peroxidase 35		M38
Affx-291424033	GRMZM2G307252	KT	1	279,751,443	SecY protein transport family protein		M39
Affx-291392059	GRMZM2G357804	KT	1	204,796,933	UDP-N-acetylglucosamine-peptide N-acetylglucosaminyltransferase SPINDLY		M40
Affx-291392059	GRMZM2G057608	KT	1	204,796,933	40S ribosomal protein S25-1		M41
Affx-291392059	GRMZM2G167548	KT	1	204,796,933	Multiple myeloma tumor-associated protein 2		M42
Affx-291392059	GRMZM2G167836	KT	1	204,796,933	Vesicle-associated membrane protein 727		M43
Affx-291380154	GRMZM2G073942	KT	2	196,175,692	Uncharacterized protein		—
Affx-291423488	GRMZM2G138268	KT	3	117,603,753	Auxin-responsive protein IAA 10		M44
Affx-123595299	GRMZM2G139550	KT	4	33,851,115	Aldolase superfamily protein		M45
Affx-123595299	GRMZM5G870572	KT	4	33,851,115	BSD domain containing protein		M46
Affx-291442826	GRMZM2G064807	KT	4	38,973,447	Pentatricopeptide repeat-containing protein		M47
Affx-291442826	GRMZM2G158153	KT	4	38,973,447	KH domain-containing protein		M48
Affx-291421461	GRMZM2G004847	KT	5	190,291,719	Pectin lyase-like superfamily protein		M49
Affx-291427217	GRMZM2G102447	KT	5	59,748,660	WAS/WASL-interacting protein family member 1-like		M50
Affx-291431852	GRMZM2G180990	KT	8	33,721,488	Ligatin		M51
Affx-291432324	GRMZM2G107696	KT	8	18,220,008	Ubiquitin carboxyl-terminal hydrolase		M52
Affx-291432324	GRMZM2G107639	KT	8	18,220,008	Transaminase		M53
Affx-291393756	GRMZM2G086030	KT	10	144,450,832	Tetratricopeptide repeat (TPR)-like superfamily protein		M54

Table 3

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. S1

Fig. S2

Fig. S3

References 46

[1]	Godfray H C, Beddington J R, Crute I R, Haddad L, Lawrence D, Muir J F, Pretty J, Robinson S, Thomas S M, Toulmin C. Food security: the challenge of feeding 9 billion people. Science, 2010,327:812-818.
[2]	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, Wang D, Shi Y S, Song Y C, Wang T Y, Li Y. Quantitative trait loci mapping for yield components and kernel-related traits in multiple connected RIL populations in maize. Euphytica, 2013,193:303-316.
[3]	Liu Z, Garcia A, McMullen M D, Flint-Garcia S A. Genetic analysis of kernel traits in maize-teosinte introgression populations. G3: Genes Genet Genom(Bethesda), 2016,6:2523-2530.
[4]	Liu M, Tan X, Yang Y, Liu P, Zhang X, Zhang Y, Wang L, Hu Y, Ma L, Li Z, Zhang Y, Zou C, Lin H, Gao S, Lee M, Lubberstedt T, Pan G, Shen Y. Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping. Plant Biotechnol J, 2020,18:207-221.
[5]	Yan J, Warburton M, Crouch J. Association Mapping for Enhancing Maize (Zea mays L.) genetic improvement. Crop Sci, 2011,51:433-449.
[6]	Xiao Y, Liu H, Wu L, Warburton M, Yan J. Genome-wide association studies in maize: praise and stargaze. Mol Plant, 2017,10:359-374.
[7]	Yang C, Zhang L, Jia A, Rong T. Identification of QTL for maize grain yield and kernel-related traits. J Genet, 2016,95:239-247.
[8]	Pang J, Fu J, Zong N, Wang J, Song D, Zhang X, He C, Fang T, Zhang H, Fan Y, Wang G, Zhao J. Kernel size-related genes revealed by an integrated eQTL analysis during early maize kernel development. Plant J, 2019,98:19-32.
[9]	Qin W, Li Y X, Wu X, Li X, Chen L, Shi Y S, Song Y C, Zhang D F, Wang T Y, Li Y. Fine mapping of qKL1.07, a major QTL for kernel length in maize. Mol Breed, 2016,36:8.
[10]	Li Q, Yang X H, Bai G H, Warburton M L, Mahuku G, Gore M, Dai J R, Li J S, Yan J B. Cloning and characterization of a putative GS3 ortholog involved in maize kernel development. Theor Appl Genet, 2010,120:753-763.
[11]	Li Q, Li L, Yang X H, Warburton M L, Bai G H, Dai J R, Li J S, Yan J B. Relationship, evolutionary fate and function of two maize co-orthologs of rice GW2 associated with kernel size and weight. BMC Plant Biol, 2010,10:143.
[12]	Li T, Qu J Z, Wang Y H, Chang L G, He K H, Guo D, Zhang X H, Xu S T, Xue J Q. Genetic characterization of inbred lines from Shaan A and B groups for identifying loci associated with maize grain yield. BMC Genet, 2018,19:63.
[13]	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.
[14]	Knapp S J, Stroup W W, Ross W M. Exact confidence intervals for heritability on a progeny mean basis. Crop Sci, 1985,25:192-194.
[15]	Murray M G, Thompson W F. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res, 1980,8:4321-4325.
[16]	Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M A, Bender D, Maller J, Sklar P, de Bakker P I, Daly M J, Sham P C. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet, 2007,81:559-575.
[17]	Yang J, Lee S H, Goddard M E, Visscher P M. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet, 2011,88:76-82.
[18]	Zhang C, Dong S S, Xu J Y, He W M, Yang T L. PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics, 2019,35:1786-1788.
[19]	Tang Y, Liu X, Wang J, Li M, Wang Q, Tian F, Su Z, Pan Y, Liu D, Lipka A E, Buckler E S, Zhang Z,. GAPIT Version 2: an enhanced integrated tool for genomic association and prediction. Plant Genome, 2016, 9: doi: 10.3835/plantgenome2015.11.20.
[20]	Liu X, Huang M, Fan B, Buckler E S, Zhang Z. Iterative usage of fixed and random effect models for powerful and efficient genome-wide association studies. PLoS Genet, 2016,12:e1005767.
[21]	Chen J, Zeng B, Zhang M, Xie S, Wang G, Hauck A, Lai J. Dynamic transcriptome landscape of maize embryo and endosperm development. Plant Physiol, 2014,166:252-264.
[22]	Shannon P, Markiel A, Ozier O, Baliga N S, Wang J T, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res, 2003,13:2498-2504.
[23]	Du Z, Zhou X, Ling Y, Zhang Z, Su Z. agriGO: a GO analysis toolkit for the agricultural community. Nucleic Acids Res, 2010,38:W64-W70.
[24]	Wang M, Yan J, Zhao J, Song W, Zhang X, Xiao Y, Zheng Y. Genome-wide association study (GWAS) of resistance to head smut in maize. Plant Sci, 2012,196:125-131.
[25]	Liu Y, Wang L, Sun C, Zhang Z, Zheng Y, Qiu F. Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments. Theor Appl Genet, 2014,127:1019-1037.
[26]	Raihan M S, Liu J, Huang J, Guo H, Pan Q, Yan J. 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.
[27]	Zhong S, Zhao M, Shi T, Shi H, An F, Zhao Q, Guo H. EIN3/EIL1 cooperate with PIF1 to prevent photo-oxidation and to promote greening of Arabidopsis seedlings. Proc Natl Acad Sci USA, 2009,106:21431-21436.
[28]	Zhu Z, An F, Feng Y, Li P, Xue L, A M, Jiang Z, Kim J, To T, Li W, Zhang X, Yu Q, Dong Z, Chen W Q, Seki M, Zhou J, Guo H. Derepression of ethylene-stabilized transcription factors (EIN3/EIL1) mediates jasmonate and ethylene signaling synergy in Arabidopsis. Proc Natl Acad Sci USA, 2011,108:12539-12544.
[29]	He W, Brumos J, Li H, Ji Y, Ke M, Gong X, Zeng Q, Li W, Zhang X, An F, Wen X, Li P, Chu J, Sun X, Yan C, Yan N, Xie D, Raikhel N, Yang Z, Stepanova A, Alonso J, Guo H. A small-molecule screen identifies L-kynurenine as a competitive inhibitor of TAA1/TAR activity in ethylene-directed auxin biosynthesis and root growth in Arabidopsis. Plant Cell, 2011,23:3944-3960.
[30]	Shi Y, Tian S, Hou L, Huang X, Zhang X, Guo H, Yang S. Ethylene signaling negatively regulates freezing tolerance by repressing expression of CBF and type-A ARR genes in Arabidopsis. Plant Cell, 2012,24:2578-2595.
[31]	Chen H, Xue L, Chintamanani S, Germain H, Lin H, Cui H, Cai R, Zuo J, Tang X, Li X. Guo H, Zhou J. ETHYLENE INSENSITIVE3 and ETHYLENE INSENSITIVE3-LIKE1 repress SALICYLIC ACID INDUCTION DEFICIENT2 expression to negatively regulate plant innate immunity in Arabidopsis. Plant Cell, 2009,21:2527-2540.
[32]	Silverstone A, Ciampaglio C, Sun T. The Arabidopsis RGA gene encodes a transcriptional regulator repressing the gibberellin signal transduction pathway. Plant Cell, 1998,10:155-169.
[33]	Bolle C, Koncz C, Chua N H. PAT1, a new member of the GRAS family, is involved in phytochrome a signal transduction. Gene Dev, 2000,14:1269-1278.
[34]	Greb T, Clarenz O, Schafer E, Muller D, Herrero R, Schmitz G, Theres K. Molecular analysis of the LATERAL SUPPRESSOR gene in Arabidopsis reveals a conserved control mechanism for axillary meristem formation. Gene Dev, 2003,17:1175-1187.
[35]	Stuurman J, Jaggi F, Kuhlemeier C. Shoot meristem maintenance is controlled by a GRAS-gene mediated signal from differentiating cells. Gene Dev, 2002,16:2213-2218.
[36]	Moon J, Skibbe D, Timofejeva L, Wang C J, Kelliher T, Kremling K, Walbot V, Cande W Z. Regulation of cell divisions and differentiation by MALE STERILITY32 is required for anther development in maize. Plant J, 2013,76:592-602.
[37]	Rademacher E H, Lokerse A S, Schlereth A, Llavata-Peris C I, Bayer M, Kientz M, Freire Rios A, Borst J W, Lukowitz W, Jurgens G, Weijers D. Different auxin response machineries control distinct cell fates in the early plant embryo. Dev Cell, 2012,22:211-222.
[38]	Smith D K, Jones D M, Lau J B R, Cruz E R, Brown E, Harper J F, Wallace I S. A putative protein O-Fucosyltransferase facilitates pollen tube penetration through the stigma-style interface. Plant Physiol, 2018,176:2804-2818.
[39]	Wang Y, He Y, Su C, Zentella R, Sun T P, Wang L. Nuclear localized O-Fucosyltransferase SPY facilitates PRR5 proteolysis to fine-tune the pace of Arabidopsis circadian clock. Mol Plant, 2020,13:446-458.
[40]	Su W, Liu Y, Xia Y, Hong Z, Li J. The Arabidopsis homolog of the mammalian OS-9 protein plays a key role in the endoplasmic reticulum-associated degradation of misfolded receptor-like kinases. Mol Plant, 2012,5:929-940.
[41]	van Nocker S, Ludwig P. The WD-repeat protein superfamily in Arabidopsis: conservation and divergence in structure and function. BMC Genome, 2003,4:50.
[42]	Malinova I, Kunz H H, Alseekh S, Herbst K, Fernie A R, Gierth M, Fettke J. Reduction of the cytosolic phosphoglucomutase in Arabidopsis reveals impact on plant growth, seed and root development, and carbohydrate partitioning. PLoS One, 2014,9:e112468.
[43]	Zhang X, Li M, Agrawal A, San K Y. Efficient free fatty acid production in Escherichia coli using plant acyl-ACP thioesterases. Metab Eng, 2011,13:713-722.
[44]	Piroux N, Saunders K, Page A, Stanley J. Geminivirus pathogenicity protein C₄ interacts with Arabidopsis thaliana shaggy- related protein kinase AtSKeta, a component of the brassinosteroid signalling pathway. Virology, 2007,362:428-440.
[45]	Perez-Perez J M, Ponce M R, Micol J L. The UCU1 Arabidopsis gene encodes a SHAGGY/GSK3-like kinase required for cell expansion along the proximodistal axis. Dev Biol, 2002,242:161-173.
[46]	Hust B, Gutensohn M. Deletion of core components of the plastid protein import machinery causes differential arrest of embryo development in Arabidopsis thaliana. Plant Biol, 2006,8:18-30.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

性状 Trait	年份 Year	平均值 Average (mm)	标准差 SD	变异范围 Range (mm)	变异系数 CV	峰度 Kurt.	偏度 Skew.	遗传力 H²(%)	相关系数 Correlation coefficient
性状 Trait	年份 Year	平均值 Average (mm)	标准差 SD	变异范围 Range (mm)	变异系数 CV	峰度 Kurt.	偏度 Skew.	遗传力 H²(%)	粒长KL (mm)	粒宽KW (mm)	粒厚KT (mm)
粒长 KL (mm)	2018	10.89	1.04	8.52-13.47	0.10	-0.50	0.19	55.12	1.00	0.09	-0.22^**
	2019	8.96	0.73	6.39-11.87	0.10	0.77	0.04		1.00	0.31^**	0.04
	BLUP	9.95	0.42	8.74-11.19	0.05	0.10	0.18		1.00	0.22^**	0.03
粒宽 KW (mm)	2018	7.86	0.87	6.22-9.95	0.09	-0.14	0.33	80.76	0.09	1.00	0.24^**
	2019	7.45	0.66	6.13-9.32	0.09	-0.13	0.35		0.31^**	1.00	0.43^**
	BLUP	7.62	0.44	6.69-8.99	0.06	-0.09	0.30		0.22^**	1.00	0.36^**
粒厚 KT (mm)	2018	4.61	0.45	3.60-5.80	0.09	-0.16	0.40	55.52	-0.22^**	0.24^**	1.00
	2019	4.59	0.47	3.41-5.80	0.10	-0.34	0.37		0.04	0.43^**	1.00
	BLUP	4.60	0.19	4.10-5.14	0.04	-0.22	0.25		0.03	0.36^**	1.00

Dissecting the genetic architecture of maize kernel size based on genome-wide association study

RichHTML394

PDF

Abstract

Cite this article

share this article

Figures/Tables 13

References 46

Related Articles 15

Metrics

Comments

Recommended 0

[1]	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.
[2]	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.
[3]	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.
[4]	LI Hai-Fen, WEI Hao, WEN Shi-Jie, LU Qing, LIU Hao, LI Shao-Xiong, HONG Yan-Bin, CHEN Xiao-Ping, LIANG Xuan-Qiang. Cloning and expression analysis of voltage dependent anion channel (AhVDAC) gene in the geotropism response of the peanut gynophores [J]. Acta Agronomica Sinica, 2022, 48(6): 1558-1565.
[5]	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.
[6]	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.
[7]	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.
[8]	YAN Yu-Ting, SONG Qiu-Lai, YAN Chao, LIU Shuang, ZHANG Yu-Hui, TIAN Jing-Fen, DENG Yu-Xuan, MA Chun-Mei. Nitrogen accumulation and nitrogen substitution effect of maize under straw returning with continuous cropping [J]. Acta Agronomica Sinica, 2022, 48(4): 962-974.
[9]	XU Ning-Kun, LI Bing, CHEN Xiao-Yan, WEI Ya-Kang, LIU Zi-Long, XUE Yong-Kang, CHEN Hong-Yu, WANG Gui-Feng. Genetic analysis and molecular characterization of a novel maize Bt2 gene mutant [J]. Acta Agronomica Sinica, 2022, 48(3): 572-579.
[10]	JIN Rong, JIANG Wei, LIU Ming, ZHAO Peng, ZHANG Qiang-Qiang, LI Tie-Xin, WANG Dan-Feng, FAN Wen-Jing, ZHANG Ai-Jun, TANG Zhong-Hou. Genome-wide characterization and expression analysis of Dof family genes in sweetpotato [J]. Acta Agronomica Sinica, 2022, 48(3): 608-623.
[11]	SONG Shi-Qin, YANG Qing-Long, WANG Dan, LYU Yan-Jie, XU Wen-Hua, WEI Wen-Wen, LIU Xiao-Dan, YAO Fan-Yun, CAO Yu-Jun, WANG Yong-Jun, WANG Li-Chun. Relationship between seed morphology, storage substance and chilling tolerance during germination of dominant maize hybrids in Northeast China [J]. Acta Agronomica Sinica, 2022, 48(3): 726-738.
[12]	YAN Yan, ZHANG Yu-Shi, LIU Chu-Rong, REN Dan-Yang, LIU Hong-Run, LIU Xue-Qing, ZHANG Ming-Cai, LI Zhao-Hu. Variety matching and resource use efficiency of the winter wheat-summer maize “double late” cropping system [J]. Acta Agronomica Sinica, 2022, 48(2): 423-436.
[13]	CHEN Xin-Yi, SONG Yu-Hang, ZHANG Meng-Han, LI Xiao-Yan, LI Hua, WANG Yue-Xia, QI Xue-Li. Effects of water deficit on physiology and biochemistry of seedlings of different wheat varieties and the alleviation effect of exogenous application of 5-aminolevulinic acid [J]. Acta Agronomica Sinica, 2022, 48(2): 478-487.
[14]	ZHANG Qian, HAN Ben-Gao, ZHANG Bo, SHENG Kai, LI Lan-Tao, WANG Yi-Lun. Reduced application and different combined applications of loss-control urea on summer maize yield and fertilizer efficiency improvement [J]. Acta Agronomica Sinica, 2022, 48(1): 180-192.
[15]	YU Rui-Su, TIAN Xiao-Kang, LIU Bin-Bin, DUAN Ying-Xin, LI Ting, ZHANG Xiu-Ying, ZHANG Xing-Hua, HAO Yin-Chuan, LI Qin, XUE Ji-Quan, XU Shu-Tu. Dissecting the genetic architecture of lodging related traits by genome-wide association study and linkage analysis in maize [J]. Acta Agronomica Sinica, 2022, 48(1): 138-150.