两种施氮条件下大豆农艺性状QTL分析
QTL Analysis of Agronomic Traits in Soybean under Two Nitrogen Application Conditions
DOI: 10.12677/HJAS.2021.119116, PDF,   
作者: 苏代群, 庄振涛, 孙中华, 张时轶：黑龙江省种业技术服务中心，黑龙江 哈尔滨；景 琦, 刘春青：全国农业技术推广服务中心，北京
关键词: 大豆；农艺性状；QTL分析；Soybean； Agronomic Traits； QTL Analysis
摘要: 大豆是全球范围内食用蛋白和食用油脂的主要来源。大豆的产量及形态等性状多属于数量性状，不但受微效多基因控制，还受环境影响。本研究利用杂交组合“东农L13 × 黑河36”、“东农L13 × 合农60”衍生的两个重组自交系群体RIL3613和RIL6013为材料，在哈尔滨、阿城和双城3个地点进行正常施用氮肥和不施用氮肥两种条件种植，对大豆形态、产量等性状进行加性和上位性QTL定位，并对各性状进行氮肥响应QTL定位和候选基因预测，旨在剖析不同氮肥水平下大豆农艺性状的遗传基础，发掘相关基因位点，在RIL3613和RIL6013群体中共检出9个株高加性QTL、6个主茎节数加性QTL、3个单株荚数加性QTL、5个单株粒数加性QTL、3个百粒重加性QTL、4个单株粒重加性QTL，单个加性QTL可解释2.04%~8.64%、1.13%~8.25%、5.97%~12.72%、0.02%~11.72%、1.34%~10.78%、5.51%~8.99%的表型变异。利用SoyBase在线程序获得的标记信息，在4个一致QTL区间中，利用GO和KEGG数据库对1215个候选基因进行了筛选和注释。KEGG通路中，Ko04075参与植物激素信号转导途径，包括赤霉素、生长素、脱落酸等激素，在调节茎生长、植物生长和种子发育方面起着重要作用。
Abstract: Soybean is the main source of edible protein and edible oil worldwide. The yield and morphological traits of soybean are mostly quantitative traits, which are not only controlled by micro-effect genes, but also affected by environment. In this study, two recombinant inbred lines (RIL3613 and RIL6013) derived from hybrid combinations “Dongnong L13 × Heihe 36” and “Dongnong L13 × Henong 60” were used, with two treatments of normal application of nitrogen fertilizer and no application of nitrogen fertilizer at three locations in Harbin, Acheng and Shuangcheng. Additive and epistatic QTLs were mapped for soybean morphological and yield traits, and QTLs for nitrogen response of each trait were mapped and candidate genes were predicted, aiming to analyze the genetic basis of agronomic traits of soybean under different nitrogen fertilizer levels and discover related gene loci. A total of 9 QTLs for plant height, 6 QTLs for main stem node number, 3 QTLs for pod number per plant, 5 QTLs for grain number per plant, 3 QTLs for 100 grain weight and 4 QTLs for grain weight per plant were detected in RIL3613 and RIL6013 populations. A single additive QTL could explain 2.04%~8.64%, 1.13%~8.25%, 5.97%~12.72%, 0.02%~11.72%, 1.34%~10.78%, and 5.51%~8.99% of phenotypic variation. Using the tagged information obtained by SoyBase online program, 1215 candidate genes were screened and annotated in four consistent QTL intervals using GO and KEGG databases. In the KEGG pathway, Ko04075 is involved in plant hormone signal transduction pathways, including gibberellins, auxin, abiotic acid and other hormones, and plays an important role in regulating stem growth, plant growth and seed development.
文章引用：苏代群, 庄振涛, 景琦, 刘春青, 孙中华, 张时轶. 两种施氮条件下大豆农艺性状QTL分析[J]. 农业科学, 2021, 11(9): 864-876. https://doi.org/10.12677/HJAS.2021.119116

参考文献

[1] 黄中文, 赵团结, 喻德跃, 陈受宜, 盖钧镒. 大豆产量有关性状QTL的检测[J]. 中国农业科学, 2009, 42(12): 4155-4165.
[2] Yang, Z., Xin, D., Liu, C., et al. (2013) Erratum to: Identification of QTL for Seed and Pod Traits in Soybean and Analysis for Additive Effects and Epistatic Effects of QTL among Multiple Environments. Molecular Ge-netics and Genomics, 288, 651. [Google Scholar] [CrossRef] [PubMed]
[3] Hu, et al. (2014) Association Mapping of Yield-Related Traits and SSR Markers in Wild Soybean (Glycine soja Sieb. and Zucc.). Breed Science, 63, 441-449. [Google Scholar] [CrossRef] [PubMed]
[4] Fang, et al. (2017) Genome-Wide Association Studies Dissect the Genetic Networks Underlying Agronomical Traits in Soybean. Genome Biology, 18, 161.
[5] 刘晓芬. 大豆栽培品种群体粒形性状及百粒重的关联分析[D]: [硕士学位论文]. 南京: 南京农业大学, 2010.
[6] 范虎, 文自翔, 王春娥, 等. 中国野生大豆群体农艺加工性状与SSR关联分析和特异材料的遗传构成[J]. 作物学报, 2013, 39(5): 775-788.
[7] 文自翔, 赵团结, 郑永战, 等. 中国栽培和野生大豆农艺及品质性状与SSR标记的关联分析II. 优异等位变异的发掘[J]. 作物学报, 2008, 34(8): 1339-1349.
[8] Zhang, J., Song, Q., Cregan, P.B., et al. (2015) Ge-nome-Wide Association Study, Genomic Prediction and Marker-Assisted Selection for Seed Weight in Soybean (Gly-cinemax). Theoretical & Applied Genetics, 129, 117-130. [Google Scholar] [CrossRef] [PubMed]
[9] Yan, L., Hofmann, N., Li, S.X., et al. (2017) Identification of QTL with Large Effect on Seed Weight in a Selective Population of Soybean with Genome-Wide Association and Fixa-tion Index Analyses. BMC Genomics, 18, 529-540. [Google Scholar] [CrossRef] [PubMed]
[10] Ning, H.L., Yuan, J.Q., Dong, Q.Z., et al. (2018) Identification of QTLs Related to the Vertical Distribution and Seed-Set of Pod Number in Soybean [Glycine max (L.) Merr]. PLoS ONE, 13, e0195830. [Google Scholar] [CrossRef] [PubMed]
[11] Zhu, J. (1995) Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics. Genetics, 141, 1633-1639. [Google Scholar] [CrossRef] [PubMed]
[12] Jiang, H., Li, Y., Qin, H., et al. (2018) Identification of Major QTLs Associated with First Pod Height and Candidate Gene Mining in Soybean. Frontiers in Plant Science, 9, Article No. 1280. [Google Scholar] [CrossRef] [PubMed]
[13] Belles-Boix, E., Babiychuk, E., Montagu, M.V., et al. (2000) CEF, a sec24 Homologue of Arabidopsis thaliana, Enhances the Survival of Yeast under Oxidative Stress Condi-tions. Journal of Experimental Botany, 51, 1761-1762. [Google Scholar] [CrossRef] [PubMed]
[14] Chevalier, D. and Walker, J.C. (2005) Functional Genomics of Protein Kinases in Plants. Briefings in Functional Genomics, 3, 362-371. [Google Scholar] [CrossRef] [PubMed]
[15] Dong, X.-F., et al. (2012) The SnRK Protein Kinase Family and the Function of SnRK1 Protein Kinase. International Journal of Agriculture and Biology, 14, 575-579.
[16] Shukla, V. and Mattoo, A.K. (2008) Sucrose Non-Fermenting 1-Related Protein Kinase 2 (SnRK2): A Family of Protein Kinases Involved in Hyperosmotic Stress Signaling. Physiology and Molecular Biology of Plants, 14, 91. [Google Scholar] [CrossRef] [PubMed]
[17] Li, D., Pfeiffer, W.T., Cornelius, P.L., et al. (2008) Soybean QTL for Yield and Yield Components Associated with Glycine soja Alleles. Crop Science, 48, 571-581. [Google Scholar] [CrossRef] 
[18] Schmidt, R.C., Muller, A., Hain, R., et al. (1996) Transgenic Tobacco Plants Expressing the Arabidopsis thaliana Nitrilase II Enzyme. The Plant Journal, 9, 683-691. [Google Scholar] [CrossRef] 
[19] Lark, K.G., Chase, K., Adler, F., et al. (1995) Interac-tions between Quantitative Trait Loci in Soybean in Which Trait Variation at One Locus Is Conditional upon a Specific Allele at Another. PNAS USA, 92, 4656-4660. [Google Scholar] [CrossRef] [PubMed]
[20] Sebolt, A.M., Shoemaker, R.C., Diers, B.W., et al. (2000) Analysis of a Quantitative Trait Locus Allele from Wild Soybean That Increases Seed Protein Concentration in Soybean. Crop Science, 40, 1438-1444. [Google Scholar] [CrossRef] 
[21] Kabelka, E.A., Diers, B.W., Fehr, W.R., et al. (2004) Putative Alleles for Increased Yield from Soybean Plant Introductions. Crop Science, 44, 784-791. [Google Scholar] [CrossRef] 
[22] Sun, D., Li, W., Zhang, Z., et al. (2006) Quantitative Trait Loci Analysis for the Developmental Behavior of Soybean (Glycine max L. Merr.). Theoretical and Applied Genetics, 112, 665-673. [Google Scholar] [CrossRef] [PubMed]
[23] Guzma, P.S., Diers, B.W., Neece, D.J., et al. (2007) QTL Associated with Yield in Three Backcross-Derived Populations of Soybean. Crop Science, 47, 111-122. [Google Scholar] [CrossRef] 
[24] Chen, Q.S., Zhang, Z.C., Liu, C.Y., et al. (2007) QTL Analysis of Major Agronomic Traits in Soybean. Agricultural Sciences in China, 6, 399-405. [Google Scholar] [CrossRef] 
[25] Gai, J., Wang, Y., Wu, X., et al. (2016) A Comparative Study on Segregation Analysis and QTL Mapping of Quantitative Traits in Plants—With a Case in Soybean. Frontiers of Agriculture in China, 1, 1-7. [Google Scholar] [CrossRef] 
[26] 白玉哲, 马钰聪, 孟一泽, 等. 大豆籽粒蛋白与脂肪含量上位性QTLs分析[J]. 中国农业科技导报, 2019, 21(6): 36-42.
[27] Daniel-Vedele, F., Filleur, S. and Caboche, M. (1998) Nitrate Transport: A Key Step in Nitrate Assimilation. Current Opinion in Plant Biology, 1, 235-239. [Google Scholar] [CrossRef] 
[28] 姜璐, 宁海龙, 李文霞, 等. 氮肥施用量对超早熟大豆源库关系、产量和品质的影响[J]. 中国农学通报, 2013, 29(30): 105-111.
[29] Agrama, H.A.S., Zakaria, A.G., Said, F.B. and Thinstra, M. (1999) Identification of Quantitative Trait Loci for Nitrogen Use Efficiency in Maize. Molecular Breeding, 5, 187-195. [Google Scholar] [CrossRef] 
[30] Bertin, P. and Gallais, A. (2001) Genetic Variation for Nitrogen Use Efficiency in a Set of Recombinant Inbred Lines. 2: QTL Detection and Coincidences. Maydica, 46, 53-68.
[31] 刘宗华. 氮胁迫条件下玉米氮利用效率及相关性状的QTL分析[D]: [博士学位论文]. 郑州: 河南农业大学, 2007.
[32] Bateson, W. (1909) Mendel’s Principles of Heredity. Cambridge University Press, Cambridge. [Google Scholar] [CrossRef] 
[33] Fisher, R. (1918) The Correlations between Relatives on the Supposition of Mendelian Inheritance. Transactions of the Royal Society of Edinburgh, 52, 399-433. [Google Scholar] [CrossRef] 
[34] Karikari, B., Li, S., Bhat, J., et al. (2019) Genome-Wide Detec-tion of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean under Multiple Environments Us-ing High-Density Bin Map. International Journal of Molecular Sciences, 20, 979. [Google Scholar] [CrossRef] [PubMed]
[35] 艾丽娟, 陈强, 杨春燕, 等. 大豆籽粒硬实加性和上位性QTL定位[J]. 作物学报, 2018, 44(6): 852-858.
[36] 孙亚男, 仕相林, 蒋洪蔚, 等. 大豆百粒重QTL的上位效应和基因型×环境互作效应[J]. 中国油料作物学报, 2012, 34(6): 598-603.
[37] Teng, W., Zhang, B., Zhang, Q., et al. (2017) Identification of Quantitative Trait Loci Underlying Seed Oil Content of Soybean Including Main, Epistatic and QTL × Environment Effects in Different Regions of Northeast China. Crop and Pasture Science, 68, 625-631. [Google Scholar] [CrossRef] 
[38] Cao, Y., Li, S., Chen, G., et al. (2019) Deciphering the Genetic Architecture of Plant Height in Soybean Using Two RIL Populations Sharing a Common M8206 Parent. Plants, 8, 373. [Google Scholar] [CrossRef] [PubMed]

为你推荐