Welcome to Acta Agronomica Sinica，

Acta Agronomica Sinica ›› 2022, Vol. 48 ›› Issue (6): 1333-1345.doi: 10.3724/SP.J.1006.2022.14102

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

Genome wide association analysis of petiole angle based on 783 soybean resources (Glycine max L.)

CHEN Ling-Ling1,2(), LI Zhan1, LIU Ting-Xuan1, GU Yong-Zhe2, SONG Jian1,*(), WANG Jun1,*(), QIU Li-Juan1,2,*()   

  1. 1Yangtze University, Jingzhou 434025, Hubei, China
    2National Key Facility for Gene Resources and Genetic Improvement / Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture and Rural Affairs / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2021-06-10 Accepted:2021-10-19 Online:2022-06-12 Published:2021-11-15
  • Contact: SONG Jian,WANG Jun,QIU Li-Juan E-mail:905540072@qq.com;songhanxi2013@163.com;wangjagri@yangtzeu.edu.cn;qiulijuan@caas.cn
  • Supported by:
    Preservation of Soybean Germplasm Resources(19211205);Jingzhou Science and Technology Plan Project(2020CB21-28)

RichHTML399

60

PDF

646

Abstract:

Petiole angle is one of the important factors that affects the high-efficiency light posture of plants. It is very important to improve soybean plant architecture by adjusting the leaf angle petioles. Soybean petiole angle is a quantitative trait, which is limited to QTLs mapping for most studies up to date. The reported gene GmILPA1controlling leaf petiole angle gene was cloned from mutants. Identification of more regulatory genes and elite alleles is urgent both for the clarification of genetic mechanism for petiole angle and its breeding utilization. In this study, 783 and 690 soybean germplasms were phenotypic for petiole angle in Hainan and Beijing in 2019 and 2020, respectively, and genome-wide associated study (GWAS) were performed using genome-wide distributed SNPs. Results showed that the petiole angle at different nodes (top, middle, and bottom nodes) were in normal distribution, suggesting that the trait of typical quantitative was inheritance. A total of 325 SNPs associated with petiole angle were identified by two-point GWAS analysis in two years, including 51, 230, 10, and 34 SNPs for petiole angles of the top, middle, bottom, and mean value of different nodes, respectively. Three candidate genes (Glyma.05G059700: auxin regulatory protein, Glyma.06G076900: AFR, and Glyma.06G076000: COP9) were obtained by LD block analysis. Transcriptional analysis revealed that all these three candidate genes had high expression level in shoot apical meristem (SAM), however, high expression level were also identified in leaf for Glyma.06G076900, leaf and stem for Glyma.06G076000.

Key words: soybean, leaf petiole angle, GWAS

Fig. 1

Distribution of 783 soybean resources"

Table 1

Basic data of the angle between the petioles of 690 materials in two years"

地点
Location		 节位
Node		 极大值
Max (°)		 极小值
Min (°)		 均值
Average (°)		 标准差
Standard deviation (°)		 变异系数
Coefficient of variation(%)
2019年海南
2019 Hainan		 顶部Top 110.6 17.0 41.0 12.0 29.3
中部Middle 109.9 14.6 39.8 10.7 26.9
底部Bottom 99.8 21.7 57.6 13.0 22.6
平均值Average 104.2 24.4 46.1 9.9 21.5
2020年北京
2020 Beijing		 顶部Top 111.9 22.0 48.4 14.1 29.1
中部Middle 119.5 22.0 49.5 10.3 20.8
底部Bottom 108.9 27.2 55.9 11.2 20.0
平均值Average 99.1 27.5 51.3 8.4 16.4

Fig. 2

Phenotypic distribution of petiole angle in natural population A, C, and E are the distribution frequency histograms of petiole angle at top, middle, and bottom nodes of Hainan in 2019, with three replicates per sample; B, D, and F are the distribution frequency histograms of petiole angle at top, middle, and bottom nodes of Beijing in 2020, with three replicates per sample."

Table 2

Correlation analysis of two different nodes in two years"

地点
Location		 节位
Node		 北京Beijing 海南Hainan
顶部Top 中部Middle 底部Bottom 顶部Top 中部Middle 底部Bottom
北京
Beijing		 顶部Top 1
中部Middle 0.203** 1
底部Bottom 0.142** 0.419** 1
海南
Hainan		 顶部Top 0.088* -0.068 -0.119* 1
中部Middle 0.042 -0.014 -0.048 0.601** 1
底部Bottom 0.004 -0.082* -0.068 0.426** 0.584** 1

Fig. 3

Analysis of phenotypic difference between two years A: the significance analysis of phenotypic differences at the same node in two years; B: the analysis of the proportion of different grade materials; C: the phenotypic difference between the two years was in the geographical distribution of 0°-20° materials; D: the analysis of the proportion of different grade materials; C: the phenotypic difference between the two years was in the geographical distribution of 21°-40°; E: the difference of phenotype in two years is more than 40° in material geographical distribution."

Fig. 4

Location of petiole angle GWAS at each node in two years A-D: the correlation analysis Q-Q plot and Manhattan plot of petiole angle at top, middle, and bottom nodes and average value of petiole angle at three nodes in Hainan; E-H: the correlation analysis Q-Q plot and Manhattan plot of petiole angle at top, middle, and bottom nodes and average value of petiole angle at three nodes in Beijing."

Table 3

SNPs were significantly associated with leaf petiole angle at each node"

地点
Location		 节位
Node		 染色体
Chr.		 SNP数目
SNP number		 区间位置
Position interval		 极显著SNP位置
Peak SNP position		 等位基因型
Alleles		 -log10 P值极大值
(-log10 Pmax)		 已报道区间
Reported interval
海南Hainan
顶部Top 6 34 20081726-29191958 24044918 A/G 9.08 —
顶部Top 18 2 33523827-33523832 33523832 G/T 6.91 —
中部Middle 4 4 5596149-15210458 15210440 C/A 7.42 —
中部Middle 9 3 17234567-17234585 17234573 T/A 6.23 —
底部Bottom 1 5 3190286-3193332 3190286 A/T 7.21 —
平均值Average 5 3 5476726-5488204 5476976 A/C 11.37 —
北京Beijing
顶部Top 3 2 10230350-10230362 10230350 A/T 7.72 —
顶部Top 3 6 17497236-17497310 17497236 C/T 8.41 —
顶部Top 7 2 21264942-26216740 21264942 G/A 8.08 —
顶部Top 11 3 17811042-17811056 17811042 C/T 7.45 [9]
顶部Top 17 2 37154449-39977197 37154449 C/A 12.11 [9]
中部Middle 6 131 5787577-5947566 5889343 A/G 8.33 —
中部Middle 6 5 20003640-20973899 20071106 A/G 11.92 —
中部Middle 13 49 37043663-37156881 37117542 A/G 8.71 —
中部Middle 14 5 15953346-19558649 15953346 A/G 9.23 [9]
中部Middle 14 6 24281424-25306741 24281424 A/G 9.35 [9]
中部Middle 14 3 27024699-27783925 27076700 C/T 9.35 [9]
中部Middle 14 5 29151458-30357161 29151458 A/G 9.96 [9]
中部Middle 14 19 32044124-41988610 32044124 A/G 9.35 [9]
中部Middle 19 2 37695290-37695805 37695805 G/T 7.13 —
中部Middle 19 3 46080617-46082050 46080617 C/G 10.25 —
底部Bottom 3 3 1997994-1998818 1997994 C/G 7.35 —
底部Bottom 19 2 41151600-41169499 41169499 C/T 7.27 —
平均值Average 6 31 5859032-5958396 5948057 A/G 8.06 —

Fig. 5

Analysis of significant loci A: peak SNP site Gm05_5476976 allele difference analysis, AA and CC represent the frequency of AA and CC homozygosity at this site, AC indicates the frequency of AC heterozygosity at this site; B: peak SNP site Gm05_5476976 LD block analysis, the red dot on the red threshold line indicates Gm05_ 5476976 LD block loci closely linked to petiole angle traits; C: peak SNP site Gm06_24044918 allele difference analysis, AA and GG represent the frequency of AA and GG homozygosity at this site, GA indicates the frequency of GA heterozygosity at this site; peak SNP site Gm06_5948057 LD block analysis, the red dot on the red threshold line indicates Gm06_5948057 LD block loci closely linked to petiole angle traits."

Fig. 6

Expression profile of candidate genes A: the relative expression profile of candidate genes in Gm05_5476976 LD block interval; B: the relative expression profile of candidate genes in Gm05_5476976 LD block interval."

[1] Gao J S, Yang S X, Cheng W, Fu Y F, Leng J T, Yuan X H, Jiang N, Ma J X, Feng X Z. GmILPA1, encoding an APC8-like protein, controls leaf petiole angle in soybean. Plant Physiol, 2017, 174: 1167-1176.
[2] Ning J, Zhang B C, Wang N L, Zhou Y H, Xiong L Z. Increased leaf angle1, a raf-like MAPKKK that interacts with a nuclear protein family, regulates mechanical tissue formation in the lamina joint of rice. Plant Cell, 2011, 23: 4334-4347.
doi: 10.1105/tpc.111.093419
[3] 廖慧敏, 张启军, 秦海龙, 夏士健, 宗寿余, 高艳红. 一个籼稻叶夹角新基因的激素敏感性分析和基因定位. 江苏农业学报, 2014, 30: 1198-1203.
Liao M H, Zhang Q J, Qin H L, Xia S J, Zong S Y, Gao Y H. Hormone sensitivity and genetic mapping of a new leaf angle gene in rice (Oryza sativa L.). Jiangsu J Agric Sci, 2014, 30: 1198-1203 (in Chinese with English abstract).
[4] 徐庆章, 王庆成, 牛玉贞, 王忠孝, 张军. 玉米株型与群体光合作用的关系研究. 作物学报, 1995, 21: 492-496.
Xu Q Z, Wang Q C, Niu Y Z, Wang Z X, Zhang J. Study on the relationship between plant type and population photosynthesis in maize. Acta Agron Sin, 1995, 21: 492-496 (in Chinese with English abstract).
[5] 李登海, 张永慧, 杨今胜, 柳京国. 育种与栽培相结合紧凑型玉米创高产. 玉米科学, 2004, 12(1):69-71.
Li D H, Zhang Y H, Yang J S, Liu J G. High yield of compact maize by combination of breeding and cultivation. J Maize Sci, 2004, 12(1):69-71 (in Chinese with English abstract).
[6] Stewart D W, Costa C, Dwyer L M, Smith D L, Hamilton R I, Ma B L. Canopy structure, light interception, and photosynthesis in maize. Agron J, 2003, 95: 1465-1474.
doi: 10.2134/agronj2003.1465
[7] Lu M, Zhou F, Xie C X, Li M S, Xu Y B, Marilyn W, Zhang S H. Construction of a SSR linkage map and mapping of quantitative trait loci (QTL) for leaf angle and leaf orientation with an elite maize hybrid. Hereditas, 2007, 29: 1131-1138.
[8] Liu S L, Zhang M, Feng F, Tian Z X. Toward a “green revolution” for soybean. Mol Plant, 2020, 13: 688-697.
doi: 10.1016/j.molp.2020.03.002
[9] 王存虎, 刘东, 许锐能, 杨永庆, 廖红. 大豆叶柄角的QTL定位分析. 作物学报, 2020, 46: 9-19.
doi: 10.3724/SP.J.1006.2020.94056
Wang C H, Liu D, Xu R N, Yang Y Q, Liao H. Mapping of QTLs for leafstalk angle in soybean. Acta Agron Sin, 2020, 46: 9-19 (in Chinese with English abstract).
[10] 王吴彬, 何庆元, 杨红燕, 向仕华, 赵团结, 邢光南, 盖钧镒. 大豆分枝数和叶柄夹角的相关野生片段分析. 中国农业科学, 2012, 45: 4749-4758.
Wang W B, He Q Y, Yang H Y, Xiang S H, Zhao T J, Xing G N, Gai J Y. Detection of wild segments associated with number of branches on main stem and leafstalk angle in soybean. Sci Agric Sin, 2012, 45: 4749-4758 (in Chinese with English abstract).
[11] 陈玲玲, 刘亭萱, 谷勇哲, 宋健, 王俊, 邱丽娟. 大豆叶柄夹角相关基因GmILPA1单倍型分析. 植物遗传资源学报, 2021, 22: 1693-1702.
Chen L L, Liu L X, Gu Y Z, Song J, Wang J, Qiu L Y. Haplotype analysis of petiole angle related gene GmILPA1 in soybean. J Plant Genet Resour, 2021, 22: 1693-1702.
[12] Murray M G, Thompson C L, Wendel J F. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res, 1980, 8: 4321-4325.
pmid: 7433111
[13] Lyu Y, Guo Z L, Li X K, Ye H Y, Li X H, Xiong L Z. New insights into the genetic basis of natural chilling and cold shock tolerance in rice by genome-wide association analysis. Plant Cell Environ, 2016, 39: 556-570.
doi: 10.1111/pce.12635
[14] 葛芳君, 赵磊, 刘俊, 周旻馨, 郭毅, 张庆军. 基于Pearson相关系数的老年人社会支持与心理健康相关性研究的Meta分析. 中国循证医学杂志, 2012, 12: 1320-1329.
Ge F J, Zhao L, Liu J, Zhou M X, Guo Y, Zhang Q J. Correlation between social support and mental health of the aged based on pearson correlation coefficient: a meta-analysis. Chin J Evidence-Based Med, 2012, 12: 1320-1329 (in Chinese with English abstract).
[15] 王五宏. 串番茄株型性状遗传及与耐弱光性关系的研究. 沈阳农业大学博士学位论文, 辽宁沈阳, 2008.
Wang W H. Inheritance of Plant Type Characteristics and the Relationship Between Plant Type and Low Light Density Tolerance in Truss Tomato. PhD Dissertation of Shenyang Agricultural University, Shenyang, Liaoning, China, 2008 (in Chinese with English abstract).
[16] 裴文东, 张仁和, 王国兴, 雷文妮, 雷格丽, 高敏, 张宏军. 玉米冠层结构和群体光合特性对增密的响应. 玉米科学, 2020, 28(3):92-98.
Pei W D, Zhang R H, Wang G X, Lei W N, Lei G L, Gao M, Zhang H J. Responses of canopy structure and population photosynthetic traits on increased planting density of different maize cultivars. J Maize Sci, 2020, 28(3):92-98 (in Chinese with English abstract).
[17] 徐梓乘, 杨恒山, 张玉芹. 玉米冠层结构对种植密度的响应. 内蒙古民族大学学报(自然科学版), 2016, 31: 298-301.
Xu Z C, Yang H S, Zhang Y Q. Response of different planting densities to corn canopy structure. J Inner Mongolia Univ Nat, 2016, 31: 298-301 (in Chinese with English abstract).
[18] 何佳宾, 李叶蓓, 聂言顺, 张萍, 郭正宇, 张中东, 陶洪斌, 王璞. 耐密性玉米冠层结构对密度的响应. 玉米科学, 2016, 24(3):69-77.
He J B, Li Y B, Nie Y S, Zhang P, Guo Z Y, Zhang Z D, Tao H B, Wang P. Canopy structure of density-resistant maize cultivars under different plant densities. J Maize Sci, 2016, 24(3):69-77 (in Chinese with English abstract)
[19] 王永学. 玉米抗倒伏有关性状遗传的初步研究. 河南农业大学硕士学位论文, 河南郑州, 2011.
Wang Y X. Primary Study of Inheritance on Lodging Resistance Traits in Maize. MS Thesis of Henan Agricultural University, Zhengzhou, Henan, China, 2011 (in Chinese with English abstract).
[20] Martin F, Lindsey A H, Allison E C, Nicholas R S, David E F, Elizabeth V V. Light interacts with auxin during leaf elongation and leaf angle development in young corn seedlings. Planta, 2003, 216: 366-376.
doi: 10.1007/s00425-002-0881-7
[21] 陈志娜. 光信号调控水稻叶片直立性的机制研究. 华中农业大学硕士学位论文, 湖北武汉, 2018.
Chen Z N. The Mechanism Research of the Regulation of Rice Leaf Erectness by Light Signaling. MS Thesis of Huazhong Agricultural University, Wuhan, Hubei, China, 2018 (in Chinese with English abstract).
[22] Asahina M, Tamaki Y, Sakamoto T, Shibata K, Nomura T, Yokota T. Blue light-promoted rice leaf bending and unrolling are due to up-regulated brassinosteroid biosynthesis genes accompanied by accumulation of castasterone. Phytochemistry, 2014, 104: 21-29.
doi: 10.1016/j.phytochem.2014.04.017
[23] Zhang Z W, Ersoz E, Lai C Q, Todhunter R J, Tiwari H K, Gore M A, Bradbury P J, Yu J. M, Arnett D K, Ordovas J M, Buckler E S. Mixed linear model approach adapted for genome-wide association studies. Nat Genet, 2010, 42: 355-360.
doi: 10.1038/ng.546
[24] Cordell H J, Clayton D G. Genetic association studies. Lancet, 2005, 366: 1121-1131.
doi: 10.1016/S0140-6736(05)67424-7
[25] Nordborg M, Weigel D. Next-generation genetics in plants. Nature, 2008, 456: 720-723.
doi: 10.1038/nature07629
[26] Franke A, McGovern D P, Barrett J C, Wang K, Radford-Smith G L, Ahmad T, Lees C W, Balschun T, Lee J, Roberts R, Anderson C A, Bis J C, Bumpstead S, Ellinghaus D, Festen E M, Georges M, Green T, Haritunians T, Jostins L, Latiano A, Mathew C G, Montgomery G W, Prescott N J, Raychaudhuri S, Rotter J I, Schumm P, Sharma Y, Simms L A, Taylor K D, Whiteman D, Wijmenga C, Baldassano R N, Barclay M, Bayless T M, Brand S, Büning C, Cohen A, Colombel J F, Cottone M, Stronati L, Denson T, De Vos M, D’Inca R, Dubinsky M, Edwards C, Florin T, Franchimont D, Gearry R, Glas J, Van Gossum A, Guthery S L, Halfvarson J, Verspaget H W, Hugot J P, Karban A, Laukens D, Lawrance I, Lemann M, Levine A, Libioulle C, Louis E, Mowat C, Newman W, Panés J, Phillips A, Proctor D D, Regueiro M, Russell R, Rutgeerts P, Sanderson J, Sans M, Seibold F, Steinhart A H, Stokkers P C, Torkvist L, Kullak-Ublick G, Wilson D, Walters T, Targan S R, Brant S R, Rioux J D, D’Amato M, Weersma R K, Kugathasan S, Griffiths A M, Mansfield J C, Vermeire S, Duerr R H, Silverberg M S, Satsangi J, Schreiber S, Cho J H, Annese V, Hakonarson H, Daly M J, Parkes M. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet, 2010, 42: 1118-1125.
doi: 10.1038/ng.717 pmid: 21102463
[27] Chasman D I, Schürks M, Anttila V, de Vries B, Schminke U, Launer L J, Terwindt G M, van den Maagdenberg A M, Fendrich K, Völzke H, Ernst F, Griffiths L R, Buring J E, Kallela M, Freilinger T, Kubisch C, Ridker P M, Palotie A, Ferrari M D, Hoffmann W, Zee R Y, Kurth T. Genome-wide association study reveals three susceptibility loci for common migraine in the general population. Nat Genet, 2011, 43: 695-698.
doi: 10.1038/ng.856 pmid: 21666692
[28] Andreassen O A, Djurovic S, Thompson W K, Schork A J, Kendler K S, O’Donovan M C, Rujescu D, Werge T, van de Bunt M, Morris A P, McCarthy M I. Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. Am J Human Genet, 2013, 92: 197-209.
doi: 10.1016/j.ajhg.2013.01.001
[29] Evangelou E, Ioannidis J P A. Meta-analysis methods for genome-wide association studies and beyond. Nat Rev Genet, 2013, 14: 379-389.
doi: 10.1038/nrg3472
[30] Pickrell J K, Berisa T, Liu J Z, Ségurel L, Tung J Y, Hinds D A. Detection and interpretation of shared genetic influences on 42 human traits. Nat Genet, 2016, 48: 709-717.
doi: 10.1038/ng.3570 pmid: 27182965
[31] 万何平, 陈禅友, 陈高, 曹新华, 夏明. 全基因组关联分析在大豆遗传学上的研究进展. 江汉大学学报(自然科学版), 2019, 47(3):197-203.
Wan H P, Chen C Y, Chen G, Cao X H, Xia M. Research status of genome-wide association study in soybean. J Jianghan Univ (Nat Sci Edn), 2019, 47(3):197-203 (in Chinese with English abstract).
[32] 曹子林. 中国沙棘平茬萌蘖内源激素调控的分子机制. 北京林业大学博士学位论文, 北京, 2019.
Cao Z L. Molecular Mechanisms of Endogenous Hormone Regulation in Stump Sprouting of Hippophae rhamnoides subsp. Sinensis. PhD Dissertation of Beijing Forestry University, Beijing, China, 2019 (in Chinese with English abstract).
[33] 海日汗. OsARF6调控水稻叶夹角的分子机制研究. 内蒙古师范大学硕士学位论文, 内蒙古呼和浩特, 2015.
Hai R H. Study on the Mechanism of OsARF6 Controlling Leaf Angle in Rice (Oryza sativa L.). MS Thesis of Inner Mongolia Normal University, Hohhot, Inner Mongolia, China, 2015 (in Chinese with English abstract).
[34] 张赛娜. OsARF19调控水稻叶夹角的分子机制. 浙江大学博士学位论文, 浙江杭州, 2014.
Zhang S N. Molecular Mechanism of OsARF19 Controlling Leaf Angle in Rice (Oryza sativa). PhD Dissertation of Zhejiang University, Hangzhou, Zhejiang, China, 2014 (in Chinese with English abstract).
[1] Mao Jia-Qi, Huang Peng-Yu, Zhao Jia-Jia, Zheng Xing-Wei, Wu Bang-Bang, Hao Yu-Qiong, Qu Fei, Liu Cheng, Ma Peng-Tao, Zheng Jun. Evaluation of powdery mildew resistance in wheat cultivars and molecular detection of resistance genes in Shanxi province, China [J]. Acta Agronomica Sinica, 2026, 52(6): 1669-1681.
[2] Tang Kuan-Qiang, Li Gong-Yun, Song Mei-Yi, Zhao Xue, Chang Chun-Ling. Genome-wide association analysis and prediction model construction for soybean plant height [J]. Acta Agronomica Sinica, 2026, 52(6): 1743-1756.
[3] Yao Shu, Guo Kai-Yue, Zhai Hui-Hui, Yao Jia-Hui, Deng Wen-Qi, Yan Ling, Huang Chi, Gao Yang, Yu Yan-Ran, Zhao Zhen-Bang, Li Ying-Hui, Wang Xiao-Bo, Li Jia-Jia. Comprehensive evaluation of low-iron tolerance and screening of elite germplasm at the soybean seedling stage [J]. Acta Agronomica Sinica, 2026, 52(5): 1373-1387.
[4] Zhang Qing, Yang Yu, Guo Qian, Yue Pei-Yao, Yin Cong-Cong, Niu Jing-Ping, Zhao Jin-Zhong, Du Wei-Jun, Yue Ai-Qin. Cloning and functional analysis of the soybean GmARA6a gene in response to salt stress [J]. Acta Agronomica Sinica, 2026, 52(2): 480-493.
[5] Li Shi-Qing, Wang Qian, Wang Su-Hua, Zhang Yao-Wen, Wang Li-Xia. Evaluation of salt tolerance at the seedling stage and related gene mining in mung bean germplasm resources [J]. Acta Agronomica Sinica, 2026, 52(2): 376-388.
[6] WANG Ke-Jing, LI Xiang-Hua. Endangerment assessment of the perennial species G. tabacina and G. tomentella of the genus Glycine Willd. in China [J]. Acta Agronomica Sinica, 2025, 51(8): 2009-2019.
[7] MENG Ran, LI Zhao-Jia, FENG Wei, CHEN Yue, LIU Lu-Ping, YANG Chun-Yan, LU Xue-Lin, WANG Xiu-Ping. Comprehensive evaluation of salt tolerance at different growth stages of soybean and screening of salt-tolerant germplasm [J]. Acta Agronomica Sinica, 2025, 51(8): 1991-2008.
[8] LI Yi-Qian, XU Shou-Zhen, LIU Ping, MA Qi, XIE Bin, CHEN Hong. Genome-wide association study of yield components using a 40K SNP array and identification of a stable locus for boll weight in upland cotton (Gossypium hirsutum L.) [J]. Acta Agronomica Sinica, 2025, 51(8): 2128-2138.
[9] HE Hong-Li, ZHANG Yu-Han, YANG Jing, CHENG Yun-Qing, ZHAO Yang, LI Xing-Nuo, SI Hong-Liang, ZHANG Xing-Zheng, YANG Xiang-Dong. Creation and physiological analysis of an e1-as gene mutant in soybean [J]. Acta Agronomica Sinica, 2025, 51(8): 2228-2239.
[10] GAO Meng-Juan, ZHAO He-Ying, CHEN Jia-Hui, CHEN Xiao-Qian, NIU Meng-Kang, QIAN Qi-Run, CUI Lu-Fei, XING Jiang-Min, YIN Qing-Miao, GUO Wen, ZHANG Ning, SUN Cong-Wei, YANG Xia, PEI Dan, JIA Ao-Lin, CHEN Feng, YU Xiao-Dong, REN Yan. Mapping and identification of a novel sharp eyespot resistance locus Qse.hnau-5AS and its candidate genes in wheat [J]. Acta Agronomica Sinica, 2025, 51(8): 2240-2250.
[11] HU Meng, SHA Dan, ZHANG Sheng-Rui, GU Yong-Zhe, ZHANG Shi-Bi, LI Jing, SUN Jun-Ming, QIU Li-Juan, LI Bin. QTL mapping and candidate gene screening for branch number in soybean [J]. Acta Agronomica Sinica, 2025, 51(7): 1747-1756.
[12] WANG Qiong, ZOU Dan-Xia, CHEN Xing-Yun, ZHANG Wei, ZHANG Hong-Mei, LIU Xiao-Qing, JIA Qian-Ru, WEI Li-Bin, CUI Xiao-Yan, CHEN Xin, WANG Xue-Jun, CHEN Hua-Tao. Genome-wide association analysis and candidate genes prediction of flowering time and maturity date traits in soybean (Glycine max L.) [J]. Acta Agronomica Sinica, 2025, 51(6): 1558-1568.
[13] YIN Cong-Cong, LI Rui-Qi, YUE Pei-Yao, LI Chen, NIU Jing-Ping, ZHAO Jin-Zhong, DU Wei-Jun, YUE Ai-Qin. Establishment and application of a visual detection method for soybean mosaic virus SC15 based on closed dumbbell mediated isothermal amplification [J]. Acta Agronomica Sinica, 2025, 51(5): 1248-1260.
[14] XU Jian-Xia, DING Yan-Qing, CAO Ning, CHENG Bin, GAO Xu, LI Wen-Zhen, ZHANG Li-Yi. Genome-wide association analysis and prediction of candidate genes for plant height and internode number in Chinese sorghum [J]. Acta Agronomica Sinica, 2025, 51(3): 568-585.
[15] ZHAO Fei-Fei, LI Shao-Xiong, LIU Hao, LI Hai-Fen, WANG Run-Feng, HUANG Lu, YU Qian-Xia, HONG Yan-Bin, CHEN Xiao-Ping, LU Qing, CAO Yu-Man. Association mapping of internode and lateral branch internode length of peanut main stem and analysis of candidate genes [J]. Acta Agronomica Sinica, 2025, 51(2): 548-556.
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