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作物学报

作物学报 ›› 2023, Vol. 49 ›› Issue (1): 140-152.doi: 10.3724/SP.J.1006.2023.23020

所属专题： 玉米：遗传育种·种质资源·分子遗传学

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

玉米籽粒淀粉含量全基因组关联分析和候选基因预测

王锐璞1(), 董振营1,2(), 高悦欣1, 鲍建喜1, 殷芳冰1, 李金萍2, 龙艳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:2023-01-12 网络出版日期:2022-05-24
  • 通讯作者: 龙艳,万向元
  • 作者简介:王锐璞, E-mail: 15903575520@163.com;
    董振营, E-mail: zydong@ustb.edu.cn第一联系人：**同等贡献
  • 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 gene prediction of kernel starch content in maize

WANG Rui-Pu1(), DONG Zhen-Ying1,2(), GAO Yue-Xin1, BAO Jian-Xi1, YIN Fang-Bing1, LI Jin-Ping2, LONG Yan1,2,*(), 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:2023-01-12 Published online:2022-05-24
  • Contact: LONG Yan,WAN Xiang-Yuan
  • About author:First author contact:**Contributed equally to this work
  • Supported by:
    National Key Research and Development Program of China(2021YFD1200700)

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摘要：

玉米是重要的粮食作物, 其籽粒重量的70%来自于淀粉。淀粉不仅是人类及其他动物的主要能量来源, 同时也是化工等行业的重要原料。本研究利用711份玉米自交系作为关联群体, 对2个环境下玉米籽粒湿基淀粉含量和干基淀粉含量进行统计分析, 结合覆盖玉米全基因组的2799个单核苷酸多态性(single nucleotide polymorphism, SNP)标记, 通过FarmCPU模型对玉米籽粒淀粉含量性状开展全基因组关联分析(genome-wide association study, GWAS), 共关联到67个显著SNP位点, 其中23个高可信度显著SNP位点可在多个环境重复检测到。3个高可信度SNP标记位点为本研究首次发现与玉米籽粒淀粉含量相关, 其余20个SNP标记位于前人已定位QTL (quantitative trait locus)置信区间或/和已报道与籽粒淀粉含量显著相关SNP标记1 Mb之内。进一步通过基因功能注释、基因本体论(gene ontology, GO)分析及籽粒胚乳基因表达分析, 在23个高可信度显著SNP位点上下游各200 kb候选区间共挖掘45个重要候选基因, 涉及淀粉生物合成与代谢、碳水化合物代谢、糖代谢、激素代谢等途径, 同时检测到2个已报道调控玉米籽粒淀粉含量的基因Ae1和Pin1。通过等位变异效应分析鉴定出9个主效SNP位点及其优异等位变异。本研究为深入解析玉米籽粒淀粉含量遗传机制提供了新的信息, 为加速培育高产、优质玉米新品种提供重要基因资源。

关键词: 玉米, 籽粒淀粉含量, 全基因组关联分析, 候选基因

Abstract:

Maize is an important food crop worldwide, and about 70% of its grain weight comes from starch. Starch is not only the main energy resource for human and other animals but also an important raw material for chemical industries. In this study, an association panel including 711 maize inbred lines was used for the examination of both wet-base starch content and dry-base starch content of maize kernel from two environments combined with 2799 single nucleotide polymorphism (SNP) markers spaning the whole genome of maize, genome-wide association study (GWAS) was carried out using FarmCPU model. 67 significant SNPs were identified, of which 23 highly reliable significant SNPs (HRS-SNPs) could be repeatedly associated in different environments. Three HRS-SNPs were reported for the first time by our study, and the remaining 20 HRS-SNPs were either located within the known quantitative trait loci (QTLs) or within 1 Mb of known SNPs associated with mazie kernel starch content. Through gene function annotation, gene ontology (GO) analysis and gene expression analysis, a total of 45 important candidate genes, involving starch biosynthesis, carbohydrate metabolism, sugar metabolism, hormone metabolism, and other pathways were identified within 200 kb regions around the HRS-SNPs. And two genes Ae1 and Pin1 which had been reported to regulate the maize kernel starch content were also detected. Furthermore, elite alles of the nine major SNPs was identified by allelic variation effect analysis. Our study provides new genetic information for further disecting the genetic mechanism of maize kernel starch content and provides important gene resources for accelerating the breeding of new maize varieties with high yield and quality.

Key words: maize, kernel starch content, genome-wide association study, candidate gene

表1

玉米籽粒淀粉含量数据统计分析"

性状及环境
Trait and environment		 变异范围
Range (%)		 平均值
Average (%)		 标准差
SD		 变异系数
CV (%)		 偏度
Skewness		 峰度
Kurtosis
WSYC2019 61.46-71.16 66.95 1.62 2.42 -0.40 -0.03
WSPG2020 59.66-68.94 64.55 1.57 2.43 -0.17 -0.29
DSYC2019 68.14-75.97 72.59 1.21 1.67 -0.49 0.64
DSPG2020 66.40-75.22 71.19 1.27 1.78 -0.25 0.14

附图1

玉米籽粒湿基(A)和干基(B)淀粉含量频率分布 WSYC2019: 2019年崖城玉米籽粒湿基淀粉含量; WSPG2020: 2020年平谷玉米籽粒湿基淀粉含量; DSYC2019: 2019年崖城玉米籽粒干基淀粉含量; DSPG2020: 2020年平谷玉米籽粒干基淀粉含量。"

表2

玉米籽粒淀粉含量数据相关性分析"

性状及环境
Trait and environment		 相关系数Correlation coefficient
WSYC2019 WSPG2020 DSYC2019 DSPG2020
WSYC2019 1
WSPG2020 0.627** 1
DSYC2019 0.804** 0.526** 1
DSPG2020 0.563** 0.844** 0.610** 1

附图2

玉米自交系系统进化树"

图1

玉米籽粒淀粉含量全基因组关联分析Manhattan图(A)和QQ图(B) WSBLUP和DSBLUP分别表示玉米籽粒湿基和干基淀粉含量最佳线性无偏预测值; Chr表示染色体。其他处理缩写同表1。"

附表1

本研究所鉴定67个玉米籽粒淀粉含量关联分析显著SNP信息"

关联位点
Associated SNP		 染色体
Chr.		 位置
Position (bp)		 P 值
P-value		 表型变异率
PVE (%)		 性状及环境
Trait and environment
SYN20034 1 13,864,423 4.83E-05 0.94 C*
PZE-101026314 1 16,041,430 1.16E-04 1.22 A
PZE-101058274 1 42,284,401 8.48E-04 2.56 D
PZE-101060842 1 44,730,532 4.27E-05 2.89 E, F
PZE-101099263 1 93,135,341 2.46E-05 0.13 B
PZE-101105385 1 109,861,210 3.43E-04 0.76 D
PZE-101107894 1 115,245,510 4.01E-07 2.86 A, C, D, F
PZE-101117618 1 144,859,179 9.63E-04 0.99 E
PZE-101182888 1 231,208,427 9.34E-05 5.05 B, C
PZE-101188800 1 237,883,989 5.74E-04 0.92 D
PZE-101224367 1 279,939,641 3.43E-04 1.09 A
PZE-101233856 1 286,821,902 2.85E-04 3.93 B, C
PZE-102000560 2 837,383 5.60E-04 0.11 B, C
SYN4735 2 9,618,618 1.02E-05 5.08 B, E
SYN19565 2 32,086,278 1.84E-04 3.23 A
PZE-102055831 2 35,216,627 4.31E-04 1.15 A
PZA02450.1 2 49,124,335 5.70E-04 2.50 F
PZE-102082146 2 69,751,058 8.97E-04 4.28 F
SYN33606 2 169,623,783 4.00E-06 0.21 F
PZE-102123716 2 176,643,239 9.36E-05 2.66 D, F
PZE-102131295 2 187,143,781 3.36E-04 1.68 B
PZA03527.1 3 5,148,837 7.57E-04 7.09 B, C
PZE-103024939 3 16,957,568 1.76E-04 1.30 A
PZE-103065358 3 105,359,736 9.15E-07 1.97 A
PZE-103112971 3 175,092,704 6.95E-05 0.19 F
PZE-103165581 3 218,640,885 2.34E-05 5.86 E, F
PZE-104044786 4 69,044,273 1.14E-04 0.47 A
PZE-104080388 4 158,252,821 3.53E-05 0.01 A
PZE-104092771 4 171,771,502 5.79E-06 3.12 E
PZE-104116111 4 196,212,782 2.20E-04 2.78 E
SYN37141 4 227,482,564 3.12E-04 1.17 E
PZE-105024985 5 12,912,185 4.13E-04 2.10 B, F
SYN27691 5 23,539,045 2.36E-05 0.13 F
PZE-105070840 5 77,119,846 4.46E-04 0.60 A
PZE-105111323 5 172,217,865 1.39E-04 2.36 B, E
PZE-105132778 5 194,317,312 1.53E-04 0.96 C, F
PZE-105158980 5 212,371,623 6.15E-07 0.11 C
SYN35254 5 218,593,404 1.48E-04 2.71 B
PZE-106041751 6 93,712,294 3.59E-06 6.34 B, D, F
PZE-106041753 6 93,713,273 5.79E-06 6.56 C, E
PZE-106049962 6 102,943,268 1.07E-04 3.99 A
PZE-106049961 6 102,943,378 1.70E-04 3.60 C
SYN4597 6 107,195,543 1.11E-04 3.71 F
PZE-106088503 6 150,161,584 5.29E-04 1.77 E
PZE-106104150 6 159,598,074 1.94E-04 0.25 B
SYN4194 6 162,814,863 2.76E-05 2.98 B, C
SYN10687 6 169,009,504 4.06E-05 0.56 E
SYN32203 7 8,799,859 2.50E-05 0.02 D
SYN34669 7 9,820,060 5.57E-05 5.43 D, E
PZE-107044349 7 91,690,556 6.53E-04 0.08 B
SYN17951 7 143,619,654 3.39E-06 5.55 D, E, F
PZE-107088998 7 148,971,333 3.54E-05 0.10 E, F
SYN34204 7 156,490,174 8.51E-04 0.96 B
PZE-108005623 8 5,939,105 8.88E-05 3.99 A, D
PZE-108038271 8 63,280,888 5.15E-04 0.31 C
PZE-108053763 8 97,541,328 1.09E-07 0.03 D, F
SYN21795 8 117,579,482 7.45E-05 5.59 B, C
PZE-108064353 8 117,743,973 1.29E-04 2.07 F
ZM012274-0351 8 120,522,562 8.98E-05 2.03 E
SYN14914 8 132,971,220 6.87E-05 0.48 D
PZE-108078728 8 138,559,450 9.03E-04 2.54 B
PZE-109003046 9 3,291,982 5.83E-04 1.73 B, C
PZA03595.2 9 96,808,133 7.94E-05 0.70 F
PZE-109054725 9 98,196,277 7.53E-04 0.97 B
PZE-109069969 9 117,528,657 1.98E-04 1.15 A
SYN12403 10 2,241,835 1.30E-06 2.31 F
PZE-110061626 10 117,865,752 9.07E-07 0.67 A, C

表3

玉米籽粒淀粉含量显著相关SNP和候选基因功能注释"

关联位点
Associated SNP		 染色体
Chr.		 位置
Position (bp)		 P值
P-value		 表型变异率
PVE (%)		 性状及环境
Trait and environment		 候选基因
Candidate gene ID		 基因名
Gene name		 功能注释
Gene annotation		 GO术语
GO term ID
PZE-101060842 1 44,730,532 4.27E-05 2.89 E, F* Zm00001d028735 Imd1 Isopropylmalate dehydrogenase1
Zm00001d028737 Glucuronoxylan 4-O-methyltransferase 2 GO:0016051
GO:0034637
GO:0033692
PZE-101107894 1 115,245,510 4.01E-07 2.86 A, C, D, F Zm00001d030236 Gibberellin-regulated protein 12
PZE-101182888 1 231,208,427 9.34E-05 5.05 B, C Zm00001d032577 CESA4 CESA4 (CELLULOSE SYNTHASE A4) GO:0016051
GO:0034637
GO:0033692
Zm00001d032578 Dof13 C2C2-Dof-transcription factor 13
PZE-101233856 1 286,821,902 2.85E-04 3.93 B, C Zm00001d034212 Hb8 Homeobox-transcription factor 8
PZE-102000560 2 837,383 5.60E-04 0.11 B, C Zm00001d001785 C2 calcium/lipid-binding plant phosphoribosyltransferase family protein
Zm00001d001791 Glucan endo-1,3-beta-D-glucosidase
SYN4735 2 9,618,618 1.02E-05 5.08 B, E Zm00001d002285 NAC22 NAC-transcription factor 22
Zm00001d002288 bHLH148 bHLH-transcription factor 148
Zm00001d002292 Gpm461b NAD(P)-binding Rossmann-fold superfamily protein GO:0016051
GO:0034637
GO:0033692
PZE-102123716 2 176,643,239 9.36E-05 2.66 D, F Zm00001d005502 Protein SMG7
Zm00001d005506
PZA03527.1 3 5,148,837 7.57E-04 7.09 B, C Zm00001d039469 Traf21 TNF receptor-associated factor 21
Zm00001d039475 Mybr22 MYB-related-transcription factor 22
PZE-103165581 3 218,640,885 2.34E-05 5.86 E, F Zm00001d044081 Hb46 Homeobox-transcription factor 46
Zm00001d044083 Pin10 PIN-formed protein10
Zm00001d044086 Nucleic acid-binding OB-fold-like protein
PZE-105024985 5 12,912,185 4.13E-04 2.10 B, F Zm00001d013500 C2H2-type domain-containing protein
Zm00001d013507 Heat shock 70 kDa protein 6 chloroplastic
PZE-105111323 5 172,217,865 1.39E-04 2.36 B, E Zm00001d016674 HSF6 HSF-transcription factor 6
Zm00001d016675 CTR1 Constitutive triple response1
Zm00001d016684 Ae1 Amylose extender1 GO:0016051
GO:0034637
GO:0033692
PZE-105132778 5 194,317,312 1.53E-04 0.96 C, F Zm00001d017391 Axial regulator YABBY 1
PZE-106041751 6 93,712,294 3.59E-06 6.34 B, D, F Zm00001d036583 BEACH domain-containing protein C2
PZE-106041753 6 93,713,273 5.79E-06 6.56 C, E Zm00001d036583 BEACH domain-containing protein C2
SYN4194 6 162,814,863 2.76E-05 2.98 B, C Zm00001d038693 Dof10 C2C2-Dof-transcription factor 10
Zm00001d038699 O-methyltransferase ZRP4
SYN34669 7 9,820,060 5.57E-05 5.43 D, E Zm00001d018936 Ribose-5-phosphate isomerase GO:0016051
Zm00001d018937 MMS19 nucleotide excision repair protein
Zm00001d018941 HSF4 HSF-transcription factor 4
SYN17951 7 143,619,654 3.39E-06 5.55 D, E, F Zm00001d021129 Alpha-(14)-fucosyltransferase GO:0016051
GO:0034637
GO:0033692
Zm00001d021130
Zm00001d021135 Pebp24 Phosphatidylethanolamine-binding protein24
Zm00001d021136 PTI3 Like tyrosine-protein kinase 3
PZE-107088998 7 148,971,333 3.54E-05 0.10 E, F Zm00001d021325 L-Aspartase-like family protein
PZE-108005623 8 5,939,105 8.88E-05 3.99 A, D Zm00001d008338 Trps14 Trehalose-6-phosphate synthase14 GO:0016051
GO:0034637
Zm00001d008345 Importin subunit alpha
PZE-108053763 8 97,541,328 1.09E-07 0.03 D, F Zm00001d010056 Delta-1-pyrroline-5-carboxylate synthase
Zm00001d010059 KH domain-containing protein
SYN21795 8 117,579,482 7.45E-05 5.59 B, C Zm00001d010487 UDP-glycosyltransferase 88A1
Zm00001d010490 CW-type Zinc Finger
PZE-109003046 9 3,291,982 5.83E-04 1.73 B, C Zm00001d044812 Pin1 PIN-formed protein1
Zm00001d044813 Gpm441 Putative fructokinase-6 chloroplastic GO:0016051
GO:0034637
GO:0033692
PZE-110061626 10 117,865,752 9.07E-07 0.67 A, C Zm00001d025409 Ereb21 Putative AP2/EREBP transcription factor superfamily protein
Zm00001d025412 Nicotinate phosphoribosyltransferase

附图3

连锁不平衡衰减分析 横坐标表示同一染色体上单核苷酸位点(SNP)之间的物理距离, 纵坐标表示连锁不平衡参数r2值。"

图2

玉米籽粒淀粉含量主效SNP位点等位变异效应分析 *和**分别表示P < 0.05和P < 0.01水平显著。n为样本量。其他处理缩写同表1。"

[1] Downs S M, Anne M T, Suparna G J, Leeder S R. Aligning food-processing policies to promote healthier fat consumption in India. Health Promot Int, 2015, 30: 595-605.
doi: 10.1093/heapro/dat094 pmid: 24399031
[2] 张海林, 高旺盛, 陈阜, 朱文珊. 保护性耕作研究现状, 发展趋势及对策. 中国农业大学学报, 2005, 10(1): 16-20.
Zhang H L, Gao W S, Chen F, Zhu W S. Prospects and present situation of conservation tillage. J Chin Agric Univ, 2005, 10(1): 16-20. (in Chinese with English abstract)
[3] 张岚, 胡春辉, 张龙, 李鑫宇, 朱赛岚, 刘真真, 高洁, 张桂芳, 李玉玲. 不同来源玉米自交系籽粒品质性状及其相关分析. 中国农学通报, 2018, 34(12): 23-29.
Zhang L, Hu C H, Zhang L, Li X Y, Zhu S L, Liu Z Z, Gao J, Zhang G F, Li Y L. Grain quality traits and their correlations of maize inbred lines with different resources. Chin Agric Sci Bull, 2018, 34(12): 23-29. (in Chinese with English abstract)
[4] 曹永国, 孔繁玲, 宋同明. 高油玉米基础群体选择效果的评价及选择方法. 中国农业大学学报, 1999, 4(1): 83-89.
Cao Y G, Kong F L, Song T M. Effects of population improvement of BHO for high oil content maize and selection method evaluation. J Chin Agric Univ, 1999, 4(1): 83-89. (in Chinese with English abstract)
[5] 兰海, 谭登峰, 高世斌, 唐祈林, 曹墨菊, 潘光堂, 荣廷昭. 普通玉米主要营养品质性状的遗传效应分析. 作物学报, 2006, 32: 716-722.
Lan H, Tan D F, Gao S B, Tang Q L, Cao M J, Pan G T, Rong T Z. Genetic analysis of main nutrient quality characters in normal maize. Acta Agron Sin, 2006, 32: 716-722. (in Chinese with English abstract)
[6] 刘新香, 库丽霞, 吴连成, 王付娟, 杨铭波, 陈彦惠. 玉米籽粒淀粉含量的遗传效应分析. 河南农业科学, 2008, (2): 25-28.
Liu X X, Ku L X, Wu L C, Wang F J, Yang M B, Chen Y H. Genetic analysis of seed starch content in maize. J Henan Agric Sci, 2008, (2): 25-28. (in Chinese with English abstract)
[7] 朱保侠, 裴玉贺, 郭新梅, 李玉冰, 宋希云. 玉米籽粒淀粉含量的遗传效应分析. 东北农业大学学报, 2012, 43(10): 115-119.
Zhu B X, Pei Y H, Guo X M, Li Y B, Song X Y. Genetic effect analysis of starch content on maize kernels. J Northeast Agric Univ, 2012, 43(10): 115-119. (in Chinese with English abstract)
[8] Zhang J, Lu X Q, Song X F, Yan J B, Song T M, Dai J R, Rocheford T, Li J S. Mapping quantitative trait loci for oil, starch, and protein concentrations in grain with high-oil maize by SSR markers. Euphytica, 2008, 162: 335-344.
doi: 10.1007/s10681-007-9500-9
[9] Zhang H D, Jin T T, Huang Y Q, Chen J T, Zhu L Y, Zhao Y F, Guo J J. Identification of quantitative trait loci underlying the protein, oil and starch contents of maize in multiple environments. Euphytica, 2015, 205: 169-183.
doi: 10.1007/s10681-015-1419-y
[10] Wang T T, Wang M, Hu S T, Xiao Y N, Tong H, Pan Q C, Xue J Q, Yan J B, Li J S, Yang X H. Genetic basis of maize kernel starch content revealed by high-density single nucleotide polymorphism markers in a recombinant inbred line population. BMC Plant Biol, 2015, 15: 288.
doi: 10.1186/s12870-015-0675-2 pmid: 26654531
[11] Wang M, Yan J B, Zhao J R, Song W, Zhang X B, Xiao Y N, Zheng Y L. Genome-wide association study (GWAS) of resistance to head smut in maize. Plant Sci, 2012, 196: 125-131.
doi: 10.1016/j.plantsci.2012.08.004 pmid: 23017907
[12] Li H, Peng Z Y, Yang X H, Wang W D, Fu J J, Wang J H, Han Y J, Chai Y C, Guo T T, Yang N, Liu J, Warburton M, Cheng Y B, Hao X M, Zhang P, Zhao J Y, Liu Y J, Wang G Y, Li J S, Yan J B. Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nat Genet, 2013, 45: 43-50.
doi: 10.1038/ng.2484 pmid: 23242369
[13] Xiao Y J, Liu H J, Wu L J, Warburton M, Yan J B. Genome-wide association studies in maize: praise and stargaze. Mol Plant, 2017, 10: 359-374.
doi: S1674-2052(16)30308-2 pmid: 28039028
[14] Cook J P, McMullen M D, Holland J B, Tian F, Bradbury P, Ross-Ibarra J, Buckler E S, Flint-Garcia S A. Genetic architecture of maize kernel composition in the nested association mapping and inbred association panels. Plant Physiol, 2012, 158: 824-834.
doi: 10.1104/pp.111.185033 pmid: 22135431
[15] Liu N, Xue Y D, Guo Z Y, Li W, Tang J. Genome-wide association study identifies candidate genes for starch content regulation in maize kernels. Front Plant Sci, 2016, 7: 1046-1053.
doi: 10.3389/fpls.2016.01046 pmid: 27512395
[16] Zheng Y X, Yuan F, Huang Y Q, Zhao Y, Guo J. Genome‑wide association studies of grain quality traits in maize. Sci Rep, 2021, 11: 9797-9808.
doi: 10.1038/s41598-021-89276-3
[17] Rong W, Qi L, Wang A Y, Ye X G, Du L P, Liang H X, Xin Z Y, Zhang Z Y. The ERF transcription factor TaERF3 promotes tolerance to salt and drought stresses in wheat. Plant Biotechnol J, 2014, 12: 468-479.
doi: 10.1111/pbi.12153 pmid: 24393105
[18] 代立刚, 何煜, 王浩, 李昊, 刘景圣. 谷物中总淀粉含量的测定方法. 中国食物与营养, 2013, 19(6): 38-42.
Dai L G, He Y, Wang H, Li H, Liu J S. Determination methods of total starch content in grain. Food Nutr China, 2013, 19(6): 38-42. (in Chinese with English abstract)
[19] 严衍禄, 张录达, 陈斌, 周学秋, 朱大洲, 安冬, 闵顺耕. 近红外光谱分析在农业领域应用中的几个问题. 现代仪器, 2011, 17(5): 5-8.
Yan Y L, Zhang L D, Chen B, Zhou X Q, Zhu D Z, An D, Min S G. Several issues of NIR spectroscopy analysis in agriculture applications. Mod Instrum, 2011, 17(5): 5-8. (in Chinese with English abstract)
[20] 檀其梅, 周杰. 近红外光谱分析与传统方法检测玉米中营养成分的比较. 饲料工业, 2007, (23): 40-41.
Tan Q M, Zhou J. Comparison of near infrared spectroscopy and traditional methods in detecting nutritional components in maize. Feed Indus, 2007, (23): 40-41. (in Chinese)
[21] Saghai-Maroof M A, Soliman K M, Jorgensen R A, Allard R W. Ribosomal DNA spacer-length polymorphisms in barley: mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci USA, 1984, 81: 8014-8018.
doi: 10.1073/pnas.81.24.8014
[22] 赵久然, 李春辉, 宋伟, 王元东, 张如养, 王继东, 王凤格, 田红丽, 王蕊. 基于SNP芯片揭示中国玉米育种种质的遗传多样性与群体遗传结构. 中国农业科学, 2018, 51: 626-644.
Zhao J R, Li C H, Song W, Wang D Y, Zhang R Y, Wang J D, Wang F G, Tian H L, Wang R. Genetic diversity and population structure of important Chinese maize breeding germplasm revealed by SNP-chips. Sci Agric Sin, 2018, 51: 626-644. (in Chinese with English abstract)
[23] 贺建波, 刘方东, 邢光南, 王吴彬, 赵团结, 管荣展, 盖钧镒. 限制性两阶段多位点全基因组关联分析方法的特点与计算程序. 作物学报, 2018, 44: 1274-1289.
He J B, Liu F D, Xing G N, Wang W B, Zhao T J, Guan R Z, Gai J Y. Characterization and analytical programs of the restricted two-stage multi-locus genome-wide association analysis. Acta Agron Sin, 2018, 44: 1274-1289. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2018.01274
[24] 邱先进, 袁志华, 陈凯, 杜斌, 何文静, 杨隆维, 徐建龙, 邢丹英, 吕文恺. 用全基因组关联分析解析籼稻垩白的遗传基础. 作物学报, 2015, 41: 1007-1016.
doi: 10.3724/SP.J.1006.2015.01007
Qiu X J, Yuan Z H, Chen K, Du B, He W J, Yang L W, Xu J L, Xing D Y, Lyu W K. Genetic dissection of grain chalkiness in Indica mini-core germplasm using genome-wide association method. Acta Agron Sin, 2015, 41: 1007-1016. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2015.01007
[25] 翟俊鹏, 李海霞, 毕惠惠, 周思远, 罗肖艳, 陈树林, 程西永, 许海霞. 普通小麦主要农艺性状的全基因组关联分析. 作物学报, 2019, 45: 1488-1502.
Zhai J P, Li H X, Bi H H, Zhou S Y, Luo X Y, Chen S L, Cheng X Y, Xu H X. Genome-wide association study for main agronomic traits in common wheat. Acta Agron Sin, 2019, 45: 1488-1502. (in Chinese with English abstract)
[26] 徐运林, 房浩, 周柏宇, 易月明, 王长进, 程昕昕, 余海兵. 甜玉米种质资源种子性状全基因组关联分析. 江苏农业学报, 2021, 37: 289-295.
Xu Y L, Fang H, Zhou B Y, Yi Y M, Wang C J, Cheng X X, Yu H B. Genome-wide association study of grain traits of sweet maize germplasm resources. Jiangsu J Agric Sci, 2021, 37: 289-295. (in Chinese with English abstract)
[27] 谢磊, 任毅, 张新忠, 王继庆, 张志辉, 石书兵, 耿洪伟. 小麦穗发芽性状的全基因组关联分析. 作物学报, 2021, 47: 1891-1902.
doi: 10.3724/SP.J.1006.2021.01078
Xie L, Ren Y, Zhang X Z, Wang J Q, Zhang Z H, Shi S B, Geng H W. Genome-wide association study of pre-harvest sprouting traits in wheat. Acta Agron Sin, 2021, 47: 1891-1902. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2021.01078
[28] Pandis N. Linear regression. Am J Orthod Dentofacial Orthop, 2016, 149: 431-434.
doi: 10.1016/j.ajodo.2015.11.019
[29] 袁亮, 孟鑫, 汪亚龙, 廖长见, 李高科, 吕桂华, 宋军, 邱正高, 林海建. 镉胁迫下甜、糯玉米开花期性状的全基因组关联分析. 植物遗传资源学报, 2021, 22: 438-447.
Yuan L, Meng X, Wang Y L, Liao C J, Li G K, Lyu G H, Song J, Qiu Z G, Lin H J. Genome wide association analysis of flowering traits in sweet and waxy maize under cadmium stress. J Plant Genet Res, 2021, 22: 438-447. (in Chinese with English abstract)
[30] Ertiro BT, Labuschagne M, Olsen M, Das B, Prasanna BM, Gowda M. Genetic dissection of nitrogen use efficiency in tropical maize through genome-wide association and genomic prediction. Front Plant Sci, 2020, 11: 474.
doi: 10.3389/fpls.2020.00474 pmid: 32411159
[31] Zhu C, Gore M, Buckler E S, Yu J M. Status and prospects of association mapping in plants. Plant Genome, 2008, 1: 5-20.
[32] An Y X, Chen L, Li Y X, Li C H, Shi Y S, Zhang D F, Li Y, Wang T Y. Genome-wide association studies and whole-genome prediction reveal the genetic architecture of KRN in maize. BMC Plant Biol, 2020, 20: 490-511.
doi: 10.1186/s12870-020-02676-x pmid: 33109077
[33] Zhang Y, Wan J Y, He L, Lan H, Li L J. Genome-wide association analysis of plant height using the maize F1 population. Plants, 2019, 8: 432-441.
doi: 10.3390/plants8100432
[34] 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 Z, 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)
doi: 10.3724/SP.J.1006.2022.13002
[35] Pfister B, Zeeman S C. Formation of starch in plant cells. Cell Mol Life Sci, 2016, 73: 2781-2807.
doi: 10.1007/s00018-016-2250-x pmid: 27166931
[36] 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
[37] Glawischnig E, Gierl A, Tomas A, Bacher A, Eisenreich W. Starch biosynthesis and intermediary metabolism in maize kernels. Quantitative analysis of metabolite flux by nuclear magnetic resonance. Plant Physiol, 2002, 130: 1717-1727.
pmid: 12481054
[38] Beloff-Chain A, Pocchiari F. Carbohydrate metabolism. Ann Rev Biochem, 1960, 29: 295-346.
doi: 10.1146/annurev.bi.29.070160.001455
[39] Spielbauer G, Margl L, Hannah L C, Römisch W, Ettenhuber C, Bacher A, Gierl A, Eisenreich W, Genschel U. Robustness of central carbohydrate metabolism in developing maize kernels. Phytochemistry, 2006, 67: 1460-1475.
pmid: 16815503
[40] Zhang Z Y, Zheng X X, Yang J, Messing J, Wu Y R. Maize endosperm-specific transcription factors O2 and PBF network the regulation of protein and starch synthesis. Proc Natl Acad Sci USA, 2016, 113: 10842-10847.
doi: 10.1073/pnas.1613721113
[41] López-González C, Juárez-Colunga S, Morales-Elías N C, Tiessen A. Exploring regulatory networks in plants: transcription factors of starch metabolism. PeerJ, 2019, 7: e6841.
doi: 10.7717/peerj.6841
[42] Dai D W, Ma Z Y, Song R T. Maize kernel development. Mol Breed, 2021, 41: 2.
doi: 10.1007/s11032-020-01195-9
[43] Fisher D K, Gao M, Kim K N, Boyer C D, Guiltinan M J. Allelic analysis of the maize amylose-extender locus suggests that independent genes encode starch-branching enzymes IIa and IIb. Plant Physiol, 1996, 110: 611-619.
pmid: 12226207
[44] Kim K N, Fisher D K, Gao M, Guiltinan M J. Molecular cloning and characterization of the Amylose-Extender gene encoding starch branching enzyme IIB in maize. Plant Mol Biol, 1998, 38: 945-956.
doi: 10.1023/A:1006057609995
[45] Liu F S, Ahmed Z, Lee E A, Donner E, Liu Q, Ahmed R, Morell M K, Emes M J, Tetlow I J. Allelic variants of the amylose extender mutation of maize demonstrate phenotypic variation in starch structure resulting from modified protein-protein interactions. J Exp Bot, 2012, 63: 1167-1183.
doi: 10.1093/jxb/err341
[46] Forestan C, Farinati S, Varotto S. The maize PIN gene family of auxin transporters. Front Plant Sci, 2012, 3: 16.
[47] Doll N M, Just J, Brunaud V, Caïus J, Grimault A, Depège-Fargeix N, Esteban E, Pasha A, Provart N J, Ingram G C, Rogowsky P M, Widieza T. Transcriptomics at maize embryo/endosperm interfaces identifies a transcriptionally distinct endosperm subdomain adjacent to the embryo scutellum. Plant Cell, 2020, 32: 833-852.
doi: 10.1105/tpc.19.00756
[48] Hu S T, Wang M, Zhang X, Chen W K, Song X R, Fu X Y, Fang H, Xu J, Xiao Y N, Li Y R, Bai G H, Li G S, Yang X H. Genetic basis of kernel starch content decoded in a maize multi-parent population. Plant Biotechnol J, 2021, 19: 2192-2205.
doi: 10.1111/pbi.13645 pmid: 34077617
[49] Wassom J J, Wong J C, Martinez E, King J J, DeBaene J, Hotchkiss J R, Mikkilineni V, Bohn M O, Rocheford T R. QTL associated with maize kernel oil, protein, and starch concentrations; kernel mass; and grain yield in Illinois high oil × B73 backcross-derived lines. Crop Sci, 2008, 48: 243-252.
doi: 10.2135/cropsci2007.04.0205
[50] Wang Y Z, Li J Z, Li Y L, Wei M G, Li X H, Fu J F. QTL detection for grain oil and starch content and their associations in two connected F2:3 populations in high-oil maize. Euphytica, 2010, 174: 239-252.
doi: 10.1007/s10681-010-0123-1
[51] Wang H W, Han J, Sun W T, Chen S J. Genetic analysis and QTL mapping of stalk digestibility and kernel composition in a high-oil maize mutant (Zea mays L.). Plant Breed, 2009, 129: 318-326.
doi: 10.1111/j.1439-0523.2009.01685.x
[52] Yang G H, Dong Y B, Li Y L, Wang Q L, Shi Q L, Zhou Q. Verification of QTL for grain starch content and its genetic correlation with oil content using two connected RIL populations in high-oil maize. PLoS One, 2013, 8: e53770.
doi: 10.1371/journal.pone.0053770
[53] Guo Y Q, Yang X H, Chander S, Yan J B, Zhang J, Song T M, Li J S. Identification of unconditional and conditional QTL for oil, protein and starch content in maize. Crop J, 2013, 1: 34-42.
doi: 10.1016/j.cj.2013.07.010
[54] Dong Y B, Zhang Z W, Shi Q L, Wang Q L, Zhou Q, Li Y L. QTL identification and meta-analysis for kernel composition traits across three generations in popcorn. Euphytica, 2015, 204: 649-660.
doi: 10.1007/s10681-015-1360-0
[55] Wang Z Y, Liu N, Ku L X, Tian Z Q, Shi Y, Guo S L, Su H H, Zhang L K, Ren Z Z, Li G H, Wang X B, Zhu Y G, Qi J S, Zhang X, Chen Y H. Dissection of the genetic architecture for grain quality-related traits in three RIL populations of maize (Zea mays L.). Plant Breed, 2016, 135: 38-46.
doi: 10.1111/pbr.12322
[56] 李学慧, 申顺先, 李玉玲, 曹雯梅, 杜红. 利用种子性状QTL定位高油玉米淀粉含量QTL. 华北农学报, 2012, 27(2): 97-99.
doi: 10.3969/j.issn.1000-7091.2012.02.019
Li X H, Shen S X, Li Y L, Cao W M, Du H. QTL analysis of starch content in high-oil maize using seed trait QTL. Acta Agric Boreali-Sin, 2012, 27(2): 97-99. (in Chinese with English abstract)
[57] 兰天茹, 崔婷婷, 何坤辉, 常立国, 刘建超. 不同氮水平下玉米子粒品质性状的QTL定位. 玉米科学, 2017, 25(2): 6-11.
Lan T R, Cui T T, He K H, Chang L G, Liu J C. QTL mapping of kernel quality traits under different nitrogen treatments in maize. J Maize Sci, 2017, 25(2): 6-11. (in Chinese with English abstract)
[58] 赵志鑫, 崔婷婷, 何坤辉, 兰天茹, 常立国, 刘建超. 多环境下玉米籽粒品质性状的QTL定位. 农业生物技术学报, 2018, 26: 2027-2035.
Zhao Z X, Cui T T, He K H, Lan T R, Chang L G, Liu J C. Mapping QTL for grain quality traits in maize (Zea mays) under multi-environments. J Agric Biotech, 2018, 26: 2027-2035. (in Chinese with English abstract)
[59] 李雪莹, 吴晗, 张君, 韩笑, 贾恩吉, 关淑艳, 卢敏, 张大瑜. 玉米淀粉QTL定位分析. 玉米科学, 2019, 27(6): 46-51.
Li X Y, Wu H, Zhang J, Han X, Jia E J, Guan S Y, Lu M, Zhang D Y. Analysis of QTL mapping on maize starch. J Maize Sci, 2019, 27(6): 46-51. (in Chinese with English abstract)
[60] Lin F, Zhou L, He B, Zhang X L, Dai H X, Qian Y L, Ruan L, Zhao H. QTL mapping for maize starch content and candidate gene prediction combined with co-expression network analysis. Theor Appl Genet, 2019, 132: 1931-1941.
doi: 10.1007/s00122-019-03326-z pmid: 30887095
[61] 王锐璞, 董振营, 高悦欣, 龙艳, 万向元. 玉米籽粒淀粉含量遗传基础与调控机制. 中国生物工程杂志, 2021, 41(12): 47-60.
Wang R P, Dong Z Y, Gao Y X, Long Y, Wan X Y. Research progress on genetic structure and regulation mechanism on starch content in maize kernel. China Biotechnol, 2021, 41(12): 47-60. (in Chinese with English abstract)
[62] Yan H B, Pan X X, Jiang H W, Wu G J. Comparison of the starch synthesis genes between maize and rice: copies, chromosome location and expression divergence. Theor Appl Genet, 2009, 119: 815-825.
doi: 10.1007/s00122-009-1091-5
[63] Li J H, Guiltinan M J, Thompson D B. Mutation of the maize sbe1a and ae genes alters morphology and physical behavior of wx-type endosperm starch granules. Carbohydr Res, 2007, 342: 2619-2627.
doi: 10.1016/j.carres.2007.07.019
[64] Lappe R R, Baier J W, Boehlein S K, Huffman R, Lin Q H, Wattebled F, Settles A M, Hannah L C, Borisjuk L, Rolletschek H, Stewart J D, Scott M P, Hennen-Bierwagen T A, Myers A M. Functions of maize genes encoding pyruvate phosphate dikinase in developing endosperm. Proc Natl Acad Sci USA, 115: E24-E33.
[65] Noguero M, Atif R M, Ochatt S, Thompson R D. The role of the DNA-binding one zinc finger (DOF) transcription factor family in plants. Plant Sci, 2013, 209: 32-45.
doi: 10.1016/j.plantsci.2013.03.016 pmid: 23759101
[66] Qi X, Li S, Zhu Y, Zhao Q, Zhu D Y, Yu J J. ZmDof3, a maize endosperm-specific Dof protein gene, regulates starch accumulation and aleurone development in maize endosperm. Plant Mol Biol, 2017, 93: 7-20.
doi: 10.1007/s11103-016-0543-y
[67] Wu J D, Chen L, Chen M C, Zhou W, Dong Q, Jiang H Y, Cheng B J. The DOF-domain transcription factor ZmDOF36 positively regulates starch synthesis in transgenic maize. Front Plant Sci, 2019, 10: 465.
doi: 10.3389/fpls.2019.00465 pmid: 31031791
[68] Chen Y Z, Cao J. Comparative analysis of Dof transcription factor family in maize. Plant Mol Biol Rep, 2015, 33: 1245-1258.
doi: 10.1007/s11105-014-0835-9
[69] Fan K, Wang M, Miao Y, Ni M, Bibi N, Yuan S N, Li F, Wang X D. Molecular evolution and expansion analysis of the NAC transcription factor in Zea mays. PLoS One, 2014, 9: e111837.
doi: 10.1371/journal.pone.0111837
[70] Zhang J J, Chen J, Yi Q, Hu Y F, Liu H M, Liu Y H, Huang Y B. Novel role of ZmaNAC36 in co‑expression of starch synthetic genes in maize endosperm. Plant Mol Biol, 2014, 84: 359-369.
doi: 10.1007/s11103-013-0153-x
[71] Peng X J, Wang Q Q, Wang Y, Cheng B J, Zhao Y, Zhu S W. A maize NAC transcription factor, ZmNAC34, negatively regulates starch synthesis in rice. Plant Cell Rep, 2019, 38: 1473-1484.
doi: 10.1007/s00299-019-02458-2
[72] Zhang Z Y, Dong J Q, Ji C, Wu Y R, Messing J. NAC-type transcription factors regulate accumulation of starch and protein in maize seeds. Proc Natl Acad Sci USA, 2019, 116: 11223-11228.
doi: 10.1073/pnas.1904995116
[73] Kolbe A, Tiessen A, Schluepmann H, Paul M, Ulrich S, Geigenberger P. Trehalose 6-phosphate regulates starch synthesis via posttranslational redox activation of ADP-glucose pyrophosphorylase. Proc Natl Acad Sci USA, 2005, 102: 11118-11123.
doi: 10.1073/pnas.0503410102
[74] Sekhon R S, Lin H N, Childs K L, Hansey C N, Buell C R, Leon N D, Kaeppler S M. Genome-wide atlas of transcription during maize development. Plant J, 2011, 66: 553-563.
doi: 10.1111/j.1365-313X.2011.04527.x
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