大豆种皮色泽的QTL定位

doi:10.13560/j.cnki.biotech.bull.1985.2026-0347

摘要/Abstract

摘要：

目的种皮色泽是大豆重要的品质性状，通过对大豆种皮色泽相关性状进行QTL定位，挖掘相关基因位点，解析种皮色泽遗传效应，筛选关键候选基因，为培育品质优良的大豆品种提供参考依据。方法以栽培大豆品种晋大53为母本、野生大豆平南为父本杂交衍生的重组自交系群体（RIL）为材料，以籽粒的色泽度（L^*）、红绿值（a^*）和蓝黄值（b^*）为种皮色泽指标，结合前期SLAF标记构建的遗传图谱，采用复合区间作图法检测QTL，并结合SoyBase数据库和SoyMD数据库筛选候选基因。结果共定位10个种皮色泽相关的QTL，获得第8染色体663 kb和第9染色体370 kb 2个候选区段，分别包含11和6个候选基因。经转录组数据表达分析，Glyma.08G103900、Glyma.08G104100、Glyma.09G191200和Glyma.09G191700在籽粒中高表达且与种皮色泽相关，且在晋大53中表达量高于平南，确定为关键候选基因。结论在大豆中检测到2个一因多效QTL位点和4个QTL新位点。

关键词: 大豆, 种皮色泽, 重组自交系, QTL, 候选基因

Abstract:

Objective Seed coat color is a key quality trait in soybean. Through QTL mapping for seed coat color-related traits, this study aims to identify associated genetic loci, clarify the genetic effects underlying seed coat color, screen for key candidate genes, and provide a reference for breeding high-quality soybean varieties. Method A recombinant inbred line (RIL) population derived from a cross between cultivated soybean Jinda 53 (female) and wild soybean Pingnan (male) was used. Seed coat color was evaluated using three parameters: lightness (L),red-green value(a*), and blue-yellow value (b*). A genetic map previously constructed with SLAF markers was employed, and QTL analysis was performed using composite interval mapping. Candidate genes were screened against the SoyBase and SoyMD databases. Result Ten QTLs associated with seed coat color were identified. Two candidate regions were obtained: a 663 kb interval on chromosome 8 and a 370 kb interval on chromosome 9, harboring 11 and 6 candidate genes, respectively. Transcriptome analysis revealed that Glyma.08G103900, Glyma.08G104100, Glyma.09G191200, and Glyma.09G191700 were highly expressed in seeds and were associated with seed coat color, showing higher expression levels in Jinda 53 than in Pingnan. These were thus identified as key candidate genes. Conclusion Two pleiotropic QTLs and four novel QTLs were identified in soybean.

Key words: soybean, seed coat color, recombinant inbred line, QTL, candidate gene

李雅迁, 冯龙哲, 孙楠, 张豪, 张艺杰, 杨雅琪, 张欣宇, 岳爱琴, 杜维俊, 王敏. 大豆种皮色泽的QTL定位[J]. 生物技术通报, doi: 10.13560/j.cnki.biotech.bull.1985.2026-0347.

LI Ya-qian, FENG Long-zhe, SUN Nan, ZHANG Hao, ZHANG Yi-jie, YANG Ya-qi, ZHANG Xin-yu, YUE Ai-qin, DU Wei-jun, WANG Min. QTL Mapping for Seed Coat Color in Soybean[J]. Biotechnology Bulletin, doi: 10.13560/j.cnki.biotech.bull.1985.2026-0347.

图/表 9

参考文献 39

[1]	Qutob D, Ma FS, Peterson CA, et al. Structural and permeability properties of the soybean seed coat [J]. Botany, 2008, 86(3): 219-227.
[2]	Le BH, Wagmaister JA, Kawashima T, et al. Using genomics to study legume seed development [J]. Plant Physiol, 2007, 144(2): 562-574.
[3]	丁然. 基于随机森林大豆籽粒外观品质识别系统的设计与实现 [D]. 哈尔滨: 东北农业大学, 2015.
	Ding R. Design and implementation of soybean grain appearance quality distinguish system based on random forests [D]. Harbin: Northeast Agricultural University, 2015.
[4]	赵团结, 盖钧镒. 栽培大豆起源与演化研究进展 [J]. 中国农业科学, 2004, 37(7): 954-962.
	Zhao TJ, Gai JY. The origin and evolution of cultivated soybean [Glycine max (L.) merr. [J]. Sci Agric Sin, 2004, 37(7): 954-962.
[5]	吴谷丰, 张晓燕, 黄璐, 等. 不同种皮颜色大豆籽粒和芽菜营养品质与抗氧化活性分析 [J]. 江苏农业学报, 2026, 42(1): 186-198.
	Wu GF, Zhang XY, Huang L, et al. Analysis of nutritional quality and antioxidant activity in soybean seeds and sprouts with different seed coat colors [J]. Jiangsu J Agric Sci, 2026, 42(1): 186-198.
[6]	吴采玉, 文春雨, 黄丽萍, 等. 不同颜色大豆种皮成分及抗氧化性分析 [J]. 大豆科学, 2023, 42(5): 554-564.
	Wu CY, Wen CY, Huang LP, et al. Analysis of seed coat composition and antioxidant activity of soybean with different colors [J]. Soybean Sci, 2023, 42(5): 554-564.
[7]	邱红梅, 陈亮, 侯云龙, 等. 大豆种子颜色遗传调控机制研究进展 [J]. 作物学报, 2021, 47(12): 2299-2313.
	Qiu HM, Chen L, Hou YL, et al. Research progress on genetic regulatory mechanism of seed color in soybean (Glycine max) [J]. Acta Agron Sin, 2021, 47(12): 2299-2313.
[8]	Cho YB, Jones SI, Vodkin LO. Mutations in Argonaute5 illuminate epistatic interactions of the K1 and I loci leading to saddle seed color patterns in Glycine max [J]. Plant Cell, 2017, 29(4): 708-725.
[9]	Endrizzi J E, Turcotte E L, Kohel R J. Qualitative genetics, cytology, and cytogenetics [J]. Cotton Agronomy Monograph, 1984, 419(5): 137-214.
[10]	Bernard R L, Weiss M G. Qualitative genetics, in soybean: improvement, production and uses [J]. Plant Molecular Biology, 1973, 56(1): 117-149.
[11]	Dashiell K. SOYBEANS: improvement, production, and uses. third edition [J]. Agric Syst, 2005, 83(1): 110-111.
[12]	Nicholas CD, Lindstrom JT, Vodkin LO. Variation of proline rich cell wall proteins in soybean lines with anthocyanin mutations [J]. Plant Mol Biol, 1993, 21(1): 145-156.
[13]	Clough SJ, Tuteja JH, Li M, et al. Features of a 103-kb gene-rich region in soybean include an inverted perfect repeat cluster of CHS genes comprising the I locus [J]. Genome, 2004, 47(5): 819-831.
[14]	Tuteja JH, Clough SJ, Chan WC, et al. Tissue-specific gene silencing mediated by a naturally occurring Chalcone synthase gene cluster in Glycine max [J]. Plant Cell, 2004, 16(4): 819-835.
[15]	Toda K, Yang DJ, Yamanaka N, et al. A single-base deletion in soybean flavonoid 3′-hydroxylase gene is associated with gray pubescence color [J]. Plant Mol Biol, 2002, 50(2): 187-196.
[16]	Buzzell RI, Buttery BR, MacTavish DC. Biochemical genetics of black pigmentation of soybean seed [J]. J Hered, 1987, 78(1): 53-54.
[17]	Todd JJ, Vodkin LO. Pigmented soybean (Glycine max) seed coats accumulate proanthocyanidins during development [J]. Plant Physiol, 1993, 102(2): 663-670.
[18]	Lee JH, Kang NS, Shin SO, et al. Characterisation of anthocyanins in the black soybean (Glycine max L.) by HPLC-DAD-ESI/MS analysis [J]. Food Chem, 2009, 112(1): 226-231.
[19]	曹杰, 谷勇哲, 洪慧龙, 等. 大豆红色种皮的色素鉴定和基因定位 [J]. 中国农业科学, 2023, 56(14): 2643-2659.
	Cao J, Gu YZ, Hong HL, et al. Pigment identification and gene mapping in red seed coat of soybean [J]. Sci Agric Sin, 2023, 56(14): 2643-2659.
[20]	董全中, 蒋炳军, 张勇, 等. 大豆褐色种皮遗传分析及基因定位 [J]. 大豆科学, 2020, 39(3): 361-369.
	Dong QZ, Jiang BJ, Zhang Y, et al. Inheritance analysis and gene mapping of brown seed coat in soybean [J]. Soybean Sci, 2020, 39(3): 361-369.
[21]	Zhang DJ, Sun LJ, Li S, et al. Elevation of soybean seed oil content through selection for seed coat shininess [J]. Nat Plants, 2018, 4(1): 30-35.
[22]	Kim SL, Chi HY, Son JR, et al. Physicochemical characteristics of soybean seed coat and their relationship to seed lustre. Korean J Crop Sci, 2005, 50(spe): 123-131.
[23]	Wang WB, Liu MF, Wang YF, et al. Characterizing two inter-specific Bin maps for the exploration of the QTLs/genes that confer three soybean evolutionary traits [J]. Front Plant Sci, 2016, 7: 1248.
[24]	de Oliveira VR, Souza NOS, da Silva Arantes M, et al. Artificial intelligence applied to the classification of greenish seeds and prediction of physiological quality in soybean [J]. Ciênc Agrotec, 2024, 48: e003624.
[25]	Sofi P, Khalid R, Shafi S, et al. A low cost and high throughput spectroscopic method for quantification of seed coat colour differences in plain seeded bean (Phaseolus vulgaris L.) germplasm from Western Himalayan Kashmir [M]. Durham:Research Square, 2022.
[26]	Sinnecker P, Gomes MSO, Arêas JAG, et al. Relationship between color (instrumental and visual) and chlorophyll contents in soybean seeds during ripening [J]. J Agric Food Chem, 2002, 50(14): 3961-3966.
[27]	王存虎, 许潇, 许锐能, 等. 基于CIELAB的大豆种皮颜色全基因组关联分析 [J]. 大豆科学, 2024, 43(6): 674-682.
	Wang CH, Xu X, Xu RN, et al. Genome-wide association study of soybean seed coat color based on CIELAB [J]. Soybean Sci, 2024, 43(6): 674-682.
[28]	Sun XW, Liu DY, Zhang XF, et al. SLAF-seq: an efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing [J]. PLoS One, 2013, 8(3): e58700.
[29]	Liu DY, Ma CX, Hong WG, et al. Construction and analysis of high-density linkage map using high-throughput sequencing data [J]. PLoS One, 2014, 9(6): e98855.
[30]	陈奕博, 杨万明, 岳爱琴, 等. 基于SLAF标记的大豆遗传图谱构建及苗期耐盐性QTL定位 [J]. 生物技术通报, 2023, 39(2): 70-79.
	Chen YB, Yang WM, Yue AQ, et al. Construction of soybean genetic map based on SLAF markers and QTL mapping analysis of salt tolerance at seedling stage [J]. Biotechnol Bull, 2023, 39(2): 70-79.
[31]	Cho MH, Park HL, Park JH, et al. Characterization of regiospecific flavonoid 3′/5′-O-methyltransferase from tomato and its application in flavonoid biotransformation [J]. J Korean Soc Appl Biol Chem, 2012, 55(6): 749-755.
[32]	白新祥, 胡可, 戴思兰, 等. 不同花色菊花品种花色素成分的初步分析 [J]. 北京林业大学学报, 2006, 28(5): 84-89.
	Bai XX, Hu K, Dai SL, et al. Components of flower pigments in the petals of different color Chrysanthemum morifolium Ramat.cultivars [J]. J Beijing For Univ, 2006, 28(5): 84-89.
[33]	宋健, 熊亚俊, 陈伊洁, 等. 大豆巢式关联作图(NAM)群体构建及花色和种皮色遗传分析 [J]. 作物学报, 2024, 50(3): 556-575.
	Song J, Xiong YJ, Chen YJ, et al. Genetic analysis of seed coat and flower color based on a soybean nested association mapping population [J]. Acta Agron Sin, 2024, 50(3): 556-575.
[34]	Song J, Xu RX, Guo QY, et al. An omics strategy increasingly improves the discovery of genetic loci and genes for seed-coat color formation in soybean [J]. Mol Breeding, 2023, 43(9): 71.
[35]	Yuhazu M, Higuchi Y, Kanazawa A, et al. Large deletions including inverted repeats of the pseudo CHS gene in seed-coat-pigmented mutants derived from Japanese yellow soybean cultivars [J]. Breed Sci, 2025, 75(4): 334-338.
[36]	Gillman JD, Tetlow A, Lee JD, et al. Loss-of-function mutations affecting a specific Glycine max R2R3 MYB transcription factor result in brown hilum and brown seed coats [J]. BMC Plant Biol, 2011, 11(1): 155.
[37]	Vuong TD, Sonah H, Meinhardt CG, et al. Genetic architecture of cyst nematode resistance revealed by genome-wide association study in soybean [J]. BMC Genom, 2015, 16: 593.
[38]	Zhou ZK, Jiang Y, Wang Z, et al. Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean [J]. Nat Biotechnol, 2015, 33(4): 408-414.
[39]	Wang C, Fu PC, Sun TT, et al. Identifying candidate genes related to soybean (Glycine max) seed coat color via RNA-seq and coexpression network analysis [J]. Genes, 2025, 16(1): 44.

性状 Trait	年份 Year	亲本 Parents			群体 Population
性状 Trait	年份 Year	晋大53 Jinda53	平南 Pingnan	显著性 Significance	均值±标准差 Mean±SD	变幅 Range	变异系数 CV（%）	峰度 Kurtosis	偏度 Skewness	广义遗传率 H²（%）
光泽度 L^*	2017	57.25±2.72	25.79±1.42	**	31.45±13.26	12.08-86.76	42	2.09	1.14	0.99
光泽度 L^*	2019	47.54±1.50	21.57±1.56	**	28.04±9.60	12.91-51.77	34	-0.72	0.25	0.99
红绿值 a^*	2017	10.07±0.83	1.38±0.278	**	5.93±5.74	-6.34-21.26	97	-0.40	0.46	0.98
红绿值 a^*	2019	10.02±0.50	3.06±0.50	**	6.12±4.56	-1.56-17.79	75	-0.81	0.39	0.98
黄蓝值 b^*	2017	29.67±2.52	6.4±0.82	**	15.80±10.07	0.85-34.27	64	-1.40	-0.05	0.99
黄蓝值 b^*	2019	27.85±1.52	3.43±0.50	**	14.07±9.71	-1.21-32.31	69	-1.36	-0.12	0.99

性状 Trait	年份 Year	亲本 Parents			群体 Population
性状 Trait	年份 Year	晋大53 Jinda53	平南 Pingnan	显著性 Significance	均值±标准差 Mean±SD	变幅 Range	变异系数 CV（%）	峰度 Kurtosis	偏度 Skewness	广义遗传率 H²（%）
光泽度 L^*	2017	57.25±2.72	25.79±1.42	**	31.45±13.26	12.08-86.76	42	2.09	1.14	0.99
光泽度 L^*	2019	47.54±1.50	21.57±1.56	**	28.04±9.60	12.91-51.77	34	-0.72	0.25	0.99
红绿值 a^*	2017	10.07±0.83	1.38±0.278	**	5.93±5.74	-6.34-21.26	97	-0.40	0.46	0.98
红绿值 a^*	2019	10.02±0.50	3.06±0.50	**	6.12±4.56	-1.56-17.79	75	-0.81	0.39	0.98
黄蓝值 b^*	2017	29.67±2.52	6.4±0.82	**	15.80±10.07	0.85-34.27	64	-1.40	-0.05	0.99
黄蓝值 b^*	2019	27.85±1.52	3.43±0.50	**	14.07±9.71	-1.21-32.31	69	-1.36	-0.12	0.99

年份 Year	性状 Trait	光泽度 L*	红绿值 a*
2017	红绿值 a*	0.383**
2017	蓝绿值 b*	0.778**	0.586**
2019	红绿值 a*	0.502**
2019	蓝绿值 b*	0.949**	0.629**

年份 Year	性状 Trait	光泽度 L*	红绿值 a*
2017	红绿值 a*	0.383**
2017	蓝绿值 b*	0.778**	0.586**
2019	红绿值 a*	0.502**
2019	蓝绿值 b*	0.949**	0.629**

性状 Trait	QTL	位置 Position （cM）	位置区间 Location interval （cM）	物理距离 Physical distance （bp）	2017			2019
性状 Trait	QTL	位置 Position （cM）	位置区间 Location interval （cM）	物理距离 Physical distance （bp）	LOD	PVE （%）	Add	LOD	PVE （%）	Add
光泽度 L^*	qL-8	50	47.824‒50.404	7 905 824‒8 568 851	10.827	30.529	-6.952	15.312	39.077	-5.719
	qL-9	123	118.478‒123.476	42 399 568‒42 769 224	4.611	10.739	-4.138	5.913	12.806	-3.284
	qL-19	71	61.93‒71.689	41 102 103‒45 900 855	2.926	6.580	-3.224
红绿值 a^*	qa-1	32	25.748‒32.014	53 380 571‒52 253 404	3.024	6.980	-1.548	5.933	13.106	-1.662
红绿值 a^*	qa-9	121	118.478‒121.095	42 399 568‒42 578 104	13.459	35.021	-3.490	12.192	30.376	-2.546
蓝黄值 b^*	qb-8-1	50	47.824‒50.404	7 905 824‒8 568 851	23.403	45.822	-6.574
	qb-8-2	51	50.404‒51.033	8 568 851‒8 621 026				13.087	31.555	-5.088
	qb-9	123	118.478‒123.476	42 399 568‒42 769 224	10.129	15.674	-3.860	9.585	22.246	-4.289
	qb-17	127	126.428‒127.29	33 704 484‒34 031 005	2.556	3.257	-1.747
	qb-19	51	50.841‒51.66	37 230 018‒37 398 935	3.244	4.201	-2.008