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作物学报 ›› 2025, Vol. 51 ›› Issue (7): 1747-1756.doi: 10.3724/SP.J.1006.2025.44221

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

大豆分枝数QTL定位及候选基因筛选

胡蒙(), 沙丹, 张晟瑞, 谷勇哲, 张世碧, 李静, 孙君明(), 邱丽娟(), 李斌()   

  1. 作物基因资源与育种全国重点实验室 / 作物分子育种国家工程中心 / 农业农村部北京大豆生物学重点实验室 / 中国农业科学院作物科学研究所, 北京 100081
  • 收稿日期:2024-12-31 接受日期:2025-04-27 出版日期:2025-07-12 网络出版日期:2025-05-09
  • 通讯作者: *李斌, E-mail: libin02@caas.cn; 孙君明, E-mail: sunjunming@caas.cn; 邱丽娟, E-mail: qiulijuan@ caas.cn
  • 作者简介:E-mail: winnercook@163.com
  • 基金资助:
    农业生物育种国家科技重大专项(2023ZD0403701);中国农业科学院农业科技创新工程项目资助

QTL mapping and candidate gene screening for branch number in soybean

HU Meng(), SHA Dan, ZHANG Sheng-Rui, GU Yong-Zhe, ZHANG Shi-Bi, LI Jing, SUN Jun-Ming(), QIU Li-Juan(), LI Bin()   

  1. The State Key Laboratory of Crop Gene Resources and Breeding / National Engineering Research Center for Crop Molecular Breeding / Key Laboratory of Soybean Biology (Beijing), Ministry of Agriculture and Rural Affairs / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2024-12-31 Accepted:2025-04-27 Published:2025-07-12 Published online:2025-05-09
  • Contact: *E-mail: libin02@caas.cn; E-mail: sunjunming@caas.cn; E-mail: qiulijuan@ caas.cn
  • Supported by:
    Biological Breeding-National Science and Technology Major Project(2023ZD0403701);Agricultural Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences

摘要: 大豆是重要的粮饲兼用作物。分枝数是影响大豆产量的重要农艺性状之一。本研究以少分枝大豆品种中黄35与多分枝品种中黄13杂交衍生的RIL F2:7-8群体为材料, 结合重测序基因型数据构建的高密度遗传连锁图谱, 采用QTL IciMapping完备复合区间定位方法, 在5个种植环境下定位与分枝数相关的QTL。结果显示, 在2号、6号、18号和19号染色体上共定位到6个与分枝数相关的QTL。其中位于2号染色体的qVBN02-1在2个环境中均被检测到, 平均解释16.07%的表型变异, 为新发掘的分枝数稳定主效QTL。该位点区间遗传距离为0.3 cM, 物理距离为261.37 kb, 包含29个注释基因。经QTL区间内双亲错义SNP筛选, 发掘出22个分枝数潜在候选基因。GO注释分析显示, 这些基因编码的蛋白涉及多个影响植物生长发育的重要过程。本研究不仅为大豆株型改良提供了分子标记靶位点, 也为精细定位大豆分枝数关键基因奠定了基础。

关键词: 大豆, 分枝数, 重组自交系, QTL定位, 候选基因

Abstract:

Soybean (Glycine max L.) is a vital crop widely used in both the food and feed industries. Branch number is a key agronomic trait that significantly influences soybean yield. In this study, we employed a recombinant inbred line (RIL) F2:7-8 population derived from a cross between the low-branching cultivar Zhonghuang 35 and the high-branching cultivar Zhonghuang 13. A high-density genetic linkage map constructed from resequencing-based genotypic data was used to identify quantitative trait loci (QTL) associated with branch number across five different planting environments, using the inclusive composite interval mapping (ICIM) method implemented in QTL IciMapping software. A total of six QTLs related to branch number were detected on chromosomes 2, 6, 18, and 19. Among them, qVBN02-1, located on chromosome 2, was consistently identified in two environments and accounted for an average of 16.07% of the phenotypic variance, indicating that it is a novel, stable, and major QTL for branch number. This QTL spans a genetic interval of 0.3 cM, corresponding to a physical distance of 261.37 kb and encompassing 29 annotated genes. By analyzing missense single nucleotide polymorphisms (SNPs) between the two parental lines within this region, we identified 22 potential candidate genes. Gene Ontology (GO) annotation revealed that these genes are involved in various biological processes critical to plant growth and development. This study not only provides valuable molecular markers for improving soybean plant architecture but also lays a foundation for the fine mapping and functional characterization of genes regulating branch number in soybean.

Key words: soybean (Glycine max L.), branch number, recombinant inbred line (RIL), QTL mapping, candidate gene

图1

大豆RIL群体的亲本植株表型"

表1

192个大豆RIL株系在5个环境下分枝数的描述性统计、方差分析和广义遗传力"

环境
Environ-
ment
数量
Number
亲本
Parent
最小值Min. 最大值Max. 平均值Mean 标准差
SD
变异系数
CV (%)
方差分析P
ANOVA P-value
广义
遗传力
H2
中黄35
ZH35
中黄13
ZH13
显著性
Sig.
环境
E
基因型
G
2020SY 192.00 0.80 5.00 0.00* 0.20 7.00 2.88 1.29 44.70 <0.01 <0.05 0.54
2021CP 184.00 0.00 2.25 0.02* 0.00 11.40 4.04 2.14 52.94
2020NK 150.00 2.00 2.80 0.74 0.00 8.67 2.63 1.61 61.24
2022BPC 180.00 5.40 8.33 0.02* 0.00 16.60 4.68 3.46 73.86
2023CP 177.00 0.51 1.15 0.07 0.00 8.20 1.95 1.43 73.32

图2

大豆RIL群体分枝数在5个环境中的频率分布图 缩写同表1。ZH35表示母本中黄35; ZH13表示父本中黄13; 黑色箭头示意亲本的分枝数。"

表2

大豆分枝数QTL定位结果"

QTL名称
QTL name
环境
Environment
染色体
Chromosome
位置
Position
左标记
Left marker
右标记
Right marker
LOD值
LOD score
贡献率
PVE (%)
加性效应
Add
qVBN02-1 2020SY 2 172.30 bin296 bin295 32.90 16.10 1.13
2021CP 2 172.40 bin296 bin295 20.93 16.04 1.44
qVBN02-2 2021CP 2 183.50 bin283 bin284 11.68 8.19 -1.03
qVBN06-1 2020SY 6 123.50 bin1433 bin1432 7.95 2.81 -0.47
qVBN06-2 2021CP 6 136.10 bin1411 bin1410 7.00 4.52 -0.76
qVBN18 2020SY 18 186.90 bin4543 bin4544 7.12 2.48 -0.44
qVBN19 2022BPC 19 138.30 bin4814 bin4815 4.23 10.39 -1.12

图3

大豆遗传连锁图谱中的分枝数QTL"

表3

大豆分枝数上位性QTL定位结果"

环境
Environment
染色体1
Chr.1
位置1
Pos.1
染色体2
Chr.2
位置2
Pos.2
LOD值
LOD score
贡献率
PVE (%)
加性效应1
Add 1
加性效应2
Add 2
加性互作
Add by Add
2022BPC 6 115.00 6 120.00 5.90 2.68 1.74 -2.00 -2.90
2022BPC 18 100.00 18 110.00 5.35 2.54 2.54 -2.65 -1.94

表4

大豆分枝数主效位点qVBN02-1基因组区段内双亲间存在错义变异的基因"

基因ID
Gene ID
亲本间变异
Inter-parental variation
变异类型
Type of mutation
功能注释
Functional description
Glyma.02G059500 SNP 非同义单核苷酸变异
Nonsynonymous SNV
PQ环重复序列家族蛋白
PQ ring repeat sequence family protein
Glyma.02G059700 SNP 非同义单核苷酸变异/提前终止
Nonsynonymous SNV/stopgain
受体样激酶
Receptor-like kinase
Glyma.02G059900 InDel 非移码缺失
Nonframeshift deletion
泛素结合蛋白家族
Ubiquitin-binding protein family
Glyma.02G060000 SNP/InDel 非同义单核苷酸变异/移码插入
Nonsynonymous SNV/frameshift insertion
BEL家族蛋白BLH4
BEL family protein BLH4
Glyma.02G060200 SNP/InDel 同义单核苷酸变异/移码插入
Synonymous SNV/frameshift insertion
BTB/POZ结构域的蛋白质
Protein with BTB/POZ structural domain
Glyma.02G060500 SNP/InDel 同义单核苷酸变异/非同义单核苷酸变异/移码缺失
Synonymous SNV/nonsynonymous SNV/frameshift deletion
SET结构域蛋白SUVR5
SET structural domain protein SUVR5
Glyma.02G060700 SNP/InDel 同义单核苷酸变异/非同义单核苷酸变异/移码插入
Synonymous SNV/nonsynonymous SNV/frameshift insertion
电子转运蛋白
Electron transport protein
Glyma.02G060800 SNP 同义单核苷酸变异/非同义单核苷酸变异
Synonymous SNV/nonsynonymous SNV
CAP超家族蛋白
CAP superfamily protein
Glyma.02G060900 SNP 同义单核苷酸变异/非同义单核苷酸变异Synonymous SNV/nonsynonymous SNV 未知蛋白
Unknown protein
Glyma.02G061000 SNP 同义单核苷酸变异/非同义单核苷酸变异Synonymous SNV/nonsynonymous SNV 未知蛋白
Unknown protein
Glyma.02G061500 SNP 非同义单核苷酸变异
Nonsynonymous SNV
未知蛋白
Unknown protein
Glyma.02G061700 SNP/InDel 非同义单核苷酸变异/移码缺失
Nonsynonymous SNV/frameshift deletion
蛋白激酶超家族蛋白
Protein kinase superfamily protein
Glyma.02G061800 SNP/InDel 非同义单核苷酸变异/提前终止
Nonsynonymous SNV/stopgain
未知蛋白
Unknown protein
Glyma.02G061900 SNP 同义单核苷酸变异/非同义单核苷酸变异Synonymous SNV/nonsynonymous SNV 液泡蛋白分选相关蛋白
Vesicle protein sorting related protein
Glyma.02G062000 SNP 非同义单核苷酸变异
Nonsynonymous SNV
未知蛋白
Unknown protein
Glyma.02G062100 SNP 同义单核苷酸变异
Synonymous SNV
未知蛋白
Unknown protein
Glyma.02G062200 SNP 非同义单核苷酸变异
Nonsynonymous SNV
磷酸吡哆醇依赖性转移酶超家族蛋白
Pyridoxal phosphate-dependent transferase superfamily protein
Glyma.02G062300 SNP 同义单核苷酸变异/非同义单核苷酸变异
Synonymous SNV/nonsynonymous SNV
G-α蛋白
G-α protein
Glyma.02G062400 SNP 非同义单核苷酸变异
Nonsynonymous SNV
脯氨酰寡肽酶家族蛋白
Prolyl oligopeptidase family protein
Glyma.02G062500 SNP 同义单核苷酸变异/非同义单核苷酸变异
Synonymous SNV/nonsynonymous SNV
磷酸吡哆醇依赖性转移酶超家族蛋白
Pyridoxal phosphate-dependent transferase superfamily protein
Glyma.02G062700 SNP 同义单核苷酸变异/非同义单核苷酸变异
Synonymous SNV/nonsynonymous SNV
锌指结构的OBP1|OBF结合蛋白
Zinc finger structure of OBP1|OBF binding protein
Glyma.02G063800 InDel 非移码插入
Nonframeshift insertion
MLO家族蛋白
MLO family protein
[1] Agyenim-Boateng K G, Zhang S R, Zhang S B, Khattak A N, Shaibu A, Abdelghany A M, Qi J, Azam M, Ma C Y, Feng Y, et al. The nutritional composition of the vegetable soybean (Maodou) and its potential in combatting malnutrition. Front Nutr, 2023, 9: 1034115.
[2] Liu K S. Soybeans: Chemistry, Technology, and Utilization. Boston: Springer, 1997. pp 381-383, 401-406, 499-504.
[3] Liu S L, Zhang M, Feng F, Tian Z X. Toward a “green revolution” for soybean. Mol Plant, 2020, 13: 688-697.
[4] Wang Y, Jiao Y L. Axillary meristem initiation-a way to branch out. Curr Opin Plant Biol, 2018, 41: 61-66.
doi: S1369-5266(17)30093-6 pmid: 28963901
[5] 巩鹏涛, 李迪. 植物分枝发育的遗传控制. 分子植物育种, 2005, 3: 151-162.
Gong P T, Li D. Genetic control of plant shoot branching. Mol Plant Breed, 2005, 3: 151-162 (in Chinese with English abstract).
[6] Domagalska M A, Leyser O. Signal integration in the control of shoot branching. Nat Rev Mol Cell Biol, 2011, 12: 211-221.
[7] Teichmann T, Muhr M. Shaping plant architecture. Front Plant Sci, 2015, 6: 233.
doi: 10.3389/fpls.2015.00233 pmid: 25914710
[8] Bell E M, Lin W C, Husbands A Y, Yu L F, Jaganatha V, Jablonska B, Mangeon A, Neff M M, Girke T, Springer P S. Arabidopsis lateral organ boundaries negatively regulates brassinosteroid accumulation to limit growth in organ boundaries. Proc Natl Acad Sci USA, 2012, 109: 21146-21151.
[9] Finlayson S A. Arabidopsis Teosinte Branched1-like 1 regulates axillary bud outgrowth and is homologous to monocot Teosinte Branched1. Plant Cell Physiol, 2007, 48: 667-677.
doi: 10.1093/pcp/pcm044 pmid: 17452340
[10] Wang J, Tian C H, Zhang C, Shi B H, Cao X W, Zhang T Q, Zhao Z, Wang J W, Jiao Y L. Cytokinin signaling activates WUSCHEL expression during axillary meristem initiation. Plant Cell, 2017, 29: 1373-1387.
[11] Choi M S, Woo M O, Koh E B, Lee J, Ham T H, Seo H S, Koh H J. Teosinte Branched 1 modulates tillering in rice plants. Plant Cell Rep, 2012, 31: 57-65.
[12] Jiao Y Q, Wang Y H, Xue D W, Wang J, Yan M X, Liu G F, Dong G J, Zeng D L, Lu Z F, Zhu X D, et al. Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nat Genet, 2010, 42: 541-544.
[13] Li X, Qian Q, Fu Z, Wang Y, Xiong G, Zeng D, Wang X, Liu X, Teng S, Hiroshi F, et al. Control of tillering in rice. Nature, 2003, 422: 618-621.
[14] Lu Z F, Shao G N, Xiong J S, Jiao Y Q, Wang J, Liu G F, Meng X B, Liang Y, Xiong G S, Wang Y H, et al. MONOCULM 3, an ortholog of WUSCHEL in rice, is required for tiller bud formation. J Genet Genomics, 2015, 42: 71-78.
[15] Miura K, Ikeda M, Matsubara A, Song X J, Ito M, Asano K, Matsuoka M, Kitano H, Ashikari M. OsSPL14 promotes panicle branching and higher grain productivity in rice. Nat Genet, 2010, 42: 545-549.
[16] Tanaka W, Ohmori Y, Ushijima T, Matsusaka H, Matsushita T, Kumamaru T, Kawano S, Hirano H Y. Axillary meristem formation in rice requires the WUSCHEL ortholog TILLERS ABSENT1. Plant Cell, 2015, 27: 1173-1184.
[17] Zhang L, Yu H, Ma B, Liu G F, Wang J J, Wang J M, Gao R C, Li J J, Liu J Y, Xu J, et al. A natural tandem array alleviates epigenetic repression of IPA1 and leads to superior yielding rice. Nat Commun, 2017, 8: 14789.
doi: 10.1038/ncomms14789 pmid: 28317902
[18] Dong C H, Zhang L C, Zhang Q, Yang Y X, Li D P, Xie Z C, Cui G Q, Chen Y Y, Wu L F, Li Z, et al. Tiller Number1 encodes an ankyrin repeat protein that controls tillering in bread wheat. Nat Commun, 2023, 14: 836.
[19] Zhou F, Lin Q B, Zhu L H, Ren Y L, Zhou K N, Shabek N, Wu F Q, Mao H B, Dong W, Gan L, et al. D14-SCFD3-dependent degradation of D53 regulates strigolactone signalling. Nature, 2013, 504: 406-410.
[20] Liu Y T, Wu G X, Zhao Y P, Wang H H, Dai Z Y, Xue W C, Yang J, Wei H B, Shen R X, Wang H Y. DWARF53 interacts with transcription factors UB2/UB3/TSH4 to regulate maize tillering and tassel branching. Plant Physiol, 2021, 187: 947-962.
doi: 10.1093/plphys/kiab259 pmid: 34608948
[21] Yao D, Liu Z Z, Zhang J, Liu S Y, Qu J, Guan S Y, Pan L D, Wang D, Liu J W, Wang P W. Analysis of quantitative trait loci for main plant traits in soybean. Genet Mol Res, 2015, 14: 6101-6109.
doi: 10.4238/2015.June.8.8 pmid: 26125811
[22] Shim S, Kim M Y, Ha J, Lee Y H, Lee S H. Identification of QTLs for branching in soybean (Glycine max (L.) Merrill). Euphytica, 2017, 213: 225.
[23] Bao A L, Chen H F, Chen L M, Chen S L, Hao Q N, Guo W, Qiu D Z, Shan Z H, Yang Z L, Yuan S L, et al. CRISPR/Cas9- mediated targeted mutagenesis of GmSPL9 genes alters plant architecture in soybean. BMC Plant Biol, 2019, 19: 131.
[24] Sun Z X, Su C, Yun J X, Jiang Q, Wang L X, Wang Y N, Cao D, Zhao F, Zhao Q S, Zhang M C, et al. Genetic improvement of the shoot architecture and yield in soya bean plants via the manipulation of GmmiR156b. Plant Biotechnol J, 2019, 17: 50-62.
[25] Guo W, Chen L M, Chen H F, Yang H L, You Q B, Bao A L, Chen S L, Hao Q N, Huang Y, Qiu D Z, et al. Overexpression of GmWRI1b in soybean stably improves plant architecture and associated yield parameters, and increases total seed oil production under field conditions. Plant Biotechnol J, 2020, 18: 1639-1641.
[26] Liang Q J, Chen L Y, Yang X, Yang H, Liu S L, Kou K, Fan L, Zhang Z F, Duan Z B, Yuan Y Q, et al. Natural variation of Dt2 determines branching in soybean. Nat Commun, 2022, 13: 6429.
[27] 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
[28] 刘亭萱, 谷勇哲, 张之昊, 王俊, 孙君明, 邱丽娟. 基于高密度遗传图谱定位大豆蛋白质含量相关的QTL. 作物学报, 2023, 49: 1532-1541.
doi: 10.3724/SP.J.1006.2023.24121
Liu T X, Gu Y Z, Zhang Z H, Wang J, Sun J M, Qiu L J. Mapping soybean protein QTLs based on high-density genetic map. Acta Agron Sin, 2023, 49: 1532-1541 (in Chinese with English abstract).
[29] van Ooijen J W. JoinMap 4, Software for the Calculation of Genetic Linkage Maps in Experimental Populations. Wageningen, Netherlands: Kyazma, 2006.
[30] Li S S, Wang J K, Zhang L Y. Inclusive composite interval mapping of QTL by environment interactions in biparental populations. PLoS One, 2015, 10: e0132414.
[31] Li H H, Ye G Y, Wang J K. A modified algorithm for the improvement of composite interval mapping. Genetics, 2007, 175: 361-374.
doi: 10.1534/genetics.106.066811 pmid: 17110476
[32] Cingolani P, Platts A, Wang L L, Coon M, Nguyen T, Wang L, Land S J, Lu X Y, Ruden D M. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly, 2012, 6: 80-92.
doi: 10.4161/fly.19695 pmid: 22728672
[33] Sayama T, Hwang T, Yamazaki H, Yamaguchi N, Komatsu K, Takahashi M, Suzuki C, Miyoshi T, Tanaka Y, Xia Z J, et al. Mapping and comparison of quantitative trait loci for soybean branching phenotype in two locations. Breed Sci, 2010, 60: 380-389.
[34] Bernard R L. Two genes affecting stem termination in soybeans. Crop Sci, 1972, 12: 235-239.
[35] Tian Z X, Wang X B, Lee R A, Li Y H, Specht J E, Nelson R L, McClean P E, Qiu L J, Ma J X. Artificial selection for determinate growth habit in soybean. Proc Natl Acad Sci USA, 2010, 107: 8563-8568.
doi: 10.1073/pnas.1000088107 pmid: 20421496
[36] Ping J Q, Liu Y F, Sun L J, Zhao M X, Li Y H, She M Y, Sui Y, Lin F, Liu X D, Tang Z X, et al. Dt2 is a gain-of-function MADS-domain factor gene that specifies semideterminacy in soybean. Plant Cell, 2014, 26: 2831-2842.
[37] Zhang D J, Wang X T, Li S, Wang C F, Gosney M J, Mickelbart M V, Ma J X. A post-domestication mutation, Dt2, triggers systemic modification of divergent and convergent pathways modulating multiple agronomic traits in soybean. Mol Plant, 2019, 12: 1366-1382.
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