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Acta Agronomica Sinica ›› 2020, Vol. 46 ›› Issue (01): 9-19.doi: 10.3724/SP.J.1006.2020.94056


Mapping of QTLs for leafstalk angle in soybean

WANG Cun-Hu,LIU Dong,XU Rui-Neng,YANG Yong-Qing(),LIAO Hong   

  1. College of Resources and Environment, Fujian Agriculture and Forestry University/Root Biology Center, Fuzhou 350002, Fujian, China
  • Received:2019-04-12 Accepted:2019-08-09 Online:2020-01-12 Published:2019-09-12
  • Contact: Yong-Qing YANG E-mail:yyq287346@163.com
  • Supported by:
    This study was supported by the National Natural Science Foundation of China(31830083);Science and Technology Innovation Fund of Fujian Agriculture and Forestry University(CXZX2018028)


Leafstalk angle is one of the most important elements for shoot architecture of soybean, affecting canopy architecture, photosynthetic efficiency and final grain yield. Exploring genetic basis of soybean leafstalk angle is significant to improve soybean yield. In this study, two soybean accessions BLA and SLA, contrasting in leafstalk angle, and their derived RIL population were used for high resolution genetic map construction and QTL detection for leafstalk angle, further the near-isogenic lines (NIL) were constructed to validate partial QTLs. Genetic analysis results showed that values of leafstalk angle performed serial and normal distribution which coincides with genetic characteristics of quantitative traits. Additionally, a high resolution genetic map consisting of 859 bin markers was constructed by using GBS method. The linkage map covered 2326.9 cM of genetic distance and the average distance between two markers was 2.763 cM. A total of 14 QTLs for regulating leafstalk angle were detected, with explained 6.9%-12.4% of genetic variation, and their LOD values varied from 2.58 to 4.80, and five of them were clustered together on Chromosome 12. The phenotype of the NILs for qLA12 and qLA18 revealed that leafstalk angle performed significant difference between same pair of NILs which strongly suggested that qLA12 and qLA18 are two believable QTLs. In summary, our results lay a foundation for cloning functional genes of regulating leafstalk angle and provide genetic resources for breeding elite soybean varieties with ideal shoot architecture.

Key words: soybean shoot architecture, leafstalk angle, QTL mapping, near-isogenic lines (NIL)

Fig. 1

Phenotypic differences in leafstalk angle between parents (A) and statistical analysis (B) BLA: big leafstalk angle; SLA: small leafstalk angle. ** indicate the significant differences of leaf petiole angle between SLA and BLA at the 1% probability level. LA-H, LA-M, and LA-L represent angles of high (H), middle (M), and low (L) leaves petiole, respectively."

Table 1

Phenotypic variation and genetic analysis of leafstalk angle traits in soybean RILs"

亲本Parents 重组自交系群体RILs 遗传力
BLA±SE SLA±SE 均值 Mean 标准差SD 变异系数
CV (%)
最小值Min. 最大值Max. 峰度
LA-H 36.60±1.36 36.60±2.72 37.25 6.57 17.64 20 75 0.78 2.29 0.70
LA-M 53.30±1.36 51.67±3.60 56.61 8.82 15.58 30 85 0.56 0.52 0.72
LA-L 95.00±2.36 73.30±2.72 74.83 12.17 16.26 20 110 -1.22 3.16 0.90

Table 2

Summary of bin marker characteristics of recombinant inbred line population"

Genetic distance (cM)
Physical length
Number of bin markers
Average coverage distance (cM)
Chr01 132.25 56,510,449 45 2.94
Chr02 149.48 47,706,575 39 3.83
Chr03 82.60 45,730,193 38 2.17
Chr04 125.97 51,405,255 50 2.52
Chr05 99.11 41,919,006 34 2.91
Chr06 128.98 50,892,625 44 2.93
Chr07 113.88 43,534,570 44 2.59
Chr08 166.04 47,709,553 45 3.69
Chr09 157.61 50,173,153 32 4.93
Chr10 85.61 51,542,279 25 3.42
Chr11 158.21 34,671,664 53 2.99
Chr12 123.75 40,030,102 47 2.63
Chr13 135.19 45,514,498 45 3.00
Chr14 87.35 47,841,279 44 1.99
Chr15 106.51 51,710,377 48 2.22
Chr16 74.30 37,192,783 46 1.62
Chr17 90.05 41,348,852 45 2.00
Chr18 113.71 57,961,359 46 2.47
Chr19 103.79 50,522,110 46 2.26
Chr20 92.53 47,868,276 43 2.15
合计Total 2326.90 941,784,958 859 55.26

Fig. 2

High resolution genetic map The left scale represents the genetic distance, and the different colors on the linkage group indicate the marker density."

Table 3

Putative QTLs for leafstalk angle traits in soybean RILs in the field"

QTL 染色体
Markers interval
Genetic position (cM)
LOD 加性效应Add 表型变异PVE (%)
qLA12a Gm12 Chr12.3021337-Chr12.4783251 20.466 3.55 1.76 9.3
qLA12b Gm12 Chr12.6175142-Chr12.6947560 32.213 3.43 1.61 9.0
qLA12c Gm12 Chr12.2086945-Chr12.2529118 7.231 2.70 1.46 7.2
qLA01 Gm01 Chr01.55523848-Chr01.56419281 131.054 3.85 -1.67 10.1
qLA11 Gm11 Chr11.10213098-Chr11.24373759 57.808 2.58 1.55 6.9
中位LA-M qLA09 Gm09 Chr09.4074635-Chr09.4606081 34.147 3.97 -2.36 10.4
qLA12d Gm12 Chr12.1868502-Chr12.2529118 6.231 3.86 2.30 10.1
qLA12a Gm12 Chr12.3021337-Chr12.4783251 17.466 3.19 2.33 8.4
qLA14 Gm14 Chr14.6976251-Chr14.43836321 60.580 2.70 -2.70 7.2
qLA17 Gm17 Chr17.37570037-Chr17.36696957 49.792 2.62 -1.87 7.0
下位LA-L qLA18 Gm18 Chr18.46032220-Chr18.47375074 63.343 4.80 3.98 12.4
qLA06 Gm06 Chr06.11495976-Chr06.15321801 70.098 4.21 -4.69 11.0
qLA15 Gm15 Chr15.11748320-Chr15.47611763 83.523 2.94 -3.20 7.8
qLA07 Gm07 Chr07.7016819-Chr07.8103486 29.912 2.71 3.02 7.2

Table 4

dCAPS markers used in this study"

Primer name
SNP loci
Primer sequence (5°-3°)
Expected product size (bp)
dCAPS-Chr12-1 3465298 Spe I F: AGTGCTAAAAACAATCCCCG 250/(226+24)
dCAPS-Chr12-2 3513670 Bsm I F: GCATAGCCTCTCCAATCCAT 229/(198+31)
dCAPS-Chr12-4 3593743 Acl I F: TGCCAACATTCCCTCATCAG 186/(160+26)
dCAPS-Chr12-7 4546007 Sma I F: ACTCCCTTCTTGTTGCCTTG 169/(141+28)
dCAPS-Chr18-1 45231954 Taq I F: CTCTCATCTCAAACAAGTCT 209/(181+28)
dCAPS-Chr18-2 46986384 Sna I F: GAAGTAACAACAGACTACGACGGTTGTAT 230/(205+25)
dCAPS-Chr18-3 47034338 Asu I F: GTAGACACCGGCGATCGGGGACTTTGGTC 204/(181+23)
Primer name
SNP loci
Primer sequence (5°-3°)
Expected product size (bp)
dCAPS-Chr18-5 48514645 Mnl I F: TGGTTGTTCTGTTTTTCTTTGTTCTACCT 244/(215+29)
dCAPS-Chr18-6 50618122 Xmn I F: CTATACTCGGTCACTTATTG 195/(167+28)
dCAPS-Chr18-7 51595218 Dpn I F: GGTCACGTTGTTTTGTAAGAATGTTCCGA 242/(213+29)

Fig. 3

Phenotypic differences in leafstalk angle between near isogenic lines qLA12 (A) and statistical analysis (B) The consistent yellow alphabet on the pots indicates a pair of isogenic line from the same F5:6 family. The red box and curved arrows indicate the observed location."

Fig. 4

Phenotypic differences in leafstalk angle between near isogenic lines qLA18 (A) and statistical analysis (B) The consistent yellow alphabet on the pots indicates a pair of isogenic line from the same F5:6 family. The red box and curved arrows indicate the observed location."

[1] Reinhardt D, Kuhlemeier C . Plant architecture. EMBO Rep, 2002,3:846-851.
doi: 10.1093/embo-reports/kvf177 pmid: 12223466
[2] Wilcox J R, Sediyama T . Interrelationships among height, lodging and yield in determinate and indeterminate soybeans. Euphytica, 1981,30:323-326.
doi: 10.1007/BF00033993
[3] Wang D, Graef G L, Procopiuk A M, Diers B W . Identification of putative QTL that underlie yield in interspecific soybean backcross populations. Theor Appl Genet, 2004,108:458-467.
doi: 10.1007/s00122-003-1449-z
[4] Gowda C L L, Upadhyaya H D, Dronavalli N, Singh S . Identification of large-seeded high-yielding stable Kabuli chickpea germplasm lines for use in crop improvement. Crop Sci, 2011,51:198-209.
doi: 10.2135/cropsci2010.01.0078
[5] 王昱, 范杰英, 王玮, 姜晓丽, 张世忠 . 不同密度对大豆生理特性的影响. 黑龙江农业科学, 2012, (8):38-40.
Wang Y, Fan J Y, Wang W, Jiang X L, Zhang S Z . Effect of different density on the soybean physiological characteristics. Heilongjiang Agric Sci, 2012, (8):38-40 (in Chinese).
[6] 刘岩, 周勋波, 陈雨海, 齐林, 崔兆韵, 杨荣光, 徐德力 . 底墒和种植方式对夏大豆光合特性及产量的影响. 生态学报, 2010,31:3478-3487.
Liu Y, Zhou X B, Chen Y H, Qin L, Cui Z Y, Yang R G, Xu D L . Effects of pre-sowing soil moisture and planting patterns on photosynthetic characteristics and yield of summer soybean. Acta Ecol Sin, 2011,31:3478-3487.
[7] 刘春全, 毕一立, 王孝忠 . 大豆农艺性状与籽粒产量关系研究进展. 现代农业科技, 2009, (23):39-40.
Liu C Q, Bi Y L, Wang X Z . Advances in the relationship between agronomic traits and grain yield of soybean. Modern Agric Sci Technol, 2009, (23):39-40 (in Chinese).
[8] 董丽华 . 大豆产量构成因素及其相互关系. 大豆科技, 1996, (1):15.
Dong L H . Factors affecting soybean yield and their relationships. Soybean Bull, 1996, (1):15 (in Chinese).
[9] 杜维广, 盖钧镒 . 大豆超高产育种研究进展的讨论. 土壤与作物, 2014,3(3):81-92.
Du W G, Gai J Y . A discussion on advances in breeding for super high-yielding soybean cultivars. Soil Crop, 2014,3(3):81-92 (in Chinese with English abstract).
[10] 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.
doi: 10.1360/yc-007-1131 pmid: 17855265
[11] 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
[12] 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 H M, 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. Jiangsu J Agric Sci, 2014,30:1198-1203 (in Chinese with English abstract).
[13] 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 . Combination of breeding and cultivation, compact corn, high yield. J Maize Sci, 2004,12(1):69-71 (in Chinese with English abstract).
[14] 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 maize plant type and population photosynthesis. Acta Agron Sin, 1995,21:492-496 (in Chinese with English abstract).
[15] 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.
doi: 10.3864/j.issn.0578-1752.2012.23.001
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).
doi: 10.3864/j.issn.0578-1752.2012.23.001
[16] 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.
doi: 10.1104/pp.16.00074 pmid: 28336772
[17] Elshire R J, Glaubitz J C, Sun Q . A Robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One, 2011,6:e19379.
doi: 10.1371/journal.pone.0019379 pmid: 21573248
[18] Huang X, Feng Q, Qian Q . High-throughput genotyping by whole-genome resequencing. Genome Res, 2009,19:1068-1076.
doi: 10.1101/gr.089516.108 pmid: 19420380
[19] Meng L, Li H H, Zhang L Y, Wang J K . QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J, 2015,3:269-283.
doi: 10.1016/j.cj.2015.01.001
[20] Van Ooijen J W . Map QTL 6, software for the mapping of quantitative trait loci in experimental populations of diploid species. Wageningen, Netherlands: Kyazma B V, 2009.
[21] McCouch S R, Cho Y G, Yano M, Paul E, Blinstrub M . Report on QTL nomenclature. Rice Genet Newsl, 1997,14:11-13.
doi: 10.1007/s10142-013-0328-1 pmid: 23813016
[22] Chang J H, Lee W S . A sliding window method for finding recently frequent itemsets over online data streams. J Inf Sci Eng, 2004,20:753-762.
[23] 蔡星星, 张盛, 王欢, 吕锐玲, 李兴华, 周强 . 水稻株型基因的研究现状及应用前景. 分子植物育种, 2017,15:2809-2814.
Cai X X, Zhang S, Wang H, Lyu R L, Li X H, Zhou Q . The present research situation and application prospect of rice plant type genes. Mol Plant Breed, 2017,15:2809-2814 (in Chinese with English abstract).
[24] 李灿东, 赵建有, 郭泰, 王志新, 郑伟, 张振宇, 郭美玲, 刘忠堂 . 不同密度下主茎亚有限型大豆株型及产量的变化规律. 中国农学通报, 2014,30(30):164-167.
Li C D, Zhao J Y, Guo T, Wang Z X, Zheng W, Zhang Z Y, Guo M L, Liu Z T . Effects of planting density on plant type and yield of main emi-determinate soybean. Chin Agric Sci Bull, 2014,30(30):164-167 (in Chinese with English abstract).
[25] 胡霞 . 利用回交导入系剖析水稻产量与品质QTL及其表达的遗传背景效应. 中国农业科学院博士学位论文, 北京, 2011.
Hu X . Dissection of QTLs for Yield and Grain Quality and Genetic Background Effect on Their Expression Using Backcross Introgression Lines of Rice. PhD Dissertation of Chinese Academy of Agricultural Sciences, Beijing, China, 2011 (in Chinese with English abstract).
[26] Cao Y L, Ding X H, Cai M, Zhao J, Lin Y J, Li X H, Xu C G, Wang S P . The expression pattern of a rice disease resistance genexa3/xa26 is differentially regulated by the genetic backgrounds and developmental stages that influence its function. Genetics, 2007,177:523-533.
doi: 10.1534/genetics.107.075176 pmid: 17720929
[27] Li Z K, Yu S B, Lafitte H R, Huang N, Courtois B, Hittalmani S, Vijayakumar C H M, Liu G F, Wang G C, Shashidhar H E, Zhuang J Y, Zheng K L, Singh V P, Sidhu J S, Srivantaneeyakul S, Khush G S . QTL × environment interactions in rice: I. Heading date and plant height. Theor Appl Genet, 2003,108:141-153.
doi: 10.1007/s00122-003-1401-2
[28] Zhuang J Y, Lin H X, Qian G R, Hittalmani S, Huang N, Zheng K L . Analysis of QTL × environment interaction for yield components and plant height in rice. Thero Appl Genet, 1997,95:799-808.
[29] Shen X H, Cao L Y, Shao G S, Zhan X D, Chen S G, Wu W M, Cheng S H . QTL Mapping for the content of five trace elements in brown rice. Mol Plant Breed, 2008,6:1061-1067.
[30] 张坤普, 徐宪斌, 田纪春 . 小麦籽粒产量及穗部相关性状的QTL定位. 作物学报, 2009,35:270-278.
doi: 10.3724/SP.J.1006.2009.00270
Zhang K P, Xu X B, Tian J C . QTL mapping for grain yield and spike related traits in common wheat. Acta Agron Sin, 2009,35:270-278 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2009.00270
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