作物学报 ›› 2021, Vol. 47 ›› Issue (5): 847-859.doi: 10.3724/SP.J.1006.2021.04176
王吴彬1, 童飞1,2, KHAN Mueen Alam1, 张雅轩1, 贺建波1, 郝晓帅1, 邢光南1, 赵团结1, 盖钧镒1,*()
WANG Wu-Bin1, TONG Fei1,2, KHAN Mueen-Alam1, ZHANG Ya-Xuan1, HE Jian-Bo1, HAO Xiao-Shuai1, XING Guang-Nan1, ZHAO Tuan-Jie1, GAI Jun-Yi1,*()
摘要:
大豆是重要的植物蛋白质和植物油脂来源, 干旱是影响大豆产量的重要环境因子之一。为解析大豆耐旱性的遗传基础, 本研究在PEG水压胁迫条件下, 对由409个家系组成的巢式关联作图群体(具有1个共同亲本的2个重组自交系群体组成)进行叶片脯氨酸含量测定, 通过限制性二阶段多位点全基因组关联分析(restrictive two-stage multilocus genome-wide association study, RTM-GWAS), 解析了大豆根部水压胁迫耐逆指数(root hydraulic stress tolerance index, RHSTI)的遗传体系。结果表明, 在春季和夏季环境下, 3个亲本蒙8260 (共同亲本)、通山薄皮黄豆甲和正阳白毛平顶在RHSTI上均存在显著差异, 其衍生群体RHSTI表型变异丰富, 变幅分别为0.11~2.94和0.03~1.93, 遗传力分别为97.7%和97.9%; 2个环境联合分析发现, 家系遗传力和家系与环境互作遗传力分别为37.9%和60.1%, 说明群体RHSTI的变异受遗传和环境共同控制。通过RTM-GWAS方法, 共检测到45个与RHSTI相关的QTL, 分布在大豆18条染色体上, 可以解释37.58%的表型变异, 其中7个QTL的表型贡献率超过1%, 为大贡献位点; 这些QTL中, 有34个位点与环境存在显著互作, 可以解释12.50%的表型变异。结合PEG胁迫下大豆转录组数据, 在定位区间500 kb范围内共筛选到38个差异表达基因, 可归为ABA响应因子、逆境响应因子、转录因子、发育因子、蛋白代谢因子、未知功能和其他等7类, 其中逆境响应因子、转录因子和发育因子是最大的3类; 其中位于主效位点的6个基因, 与ABA响应因子、逆境响应因子、转录因子相关, 应为主要候选基因。上述结果表明, 大豆耐旱性是一个由多位点、多基因控制的复杂数量性状, 且与环境存在互作, 遗传基础复杂。研究结果为大豆耐旱性分子育种提供了依据。
[1] | Reynolds J F, Smith D M S, Lambin E F, Turner B L, Mortimore M, Batterbury S P J, Downing T E, Dowlatabadi H, Fernández R J, Herrick J E, Huber-Sannwald E, Jiang H, Leemans R, Lynam T, Maestre F T, Ayarza M, Walker B. Global desertification: Building a science for dryland development. Science, 2007,316:847-851. |
[2] | Cook E R, Seager R, Cane M A, Stahle D W. North American drought: reconstructions, causes, and consequences. Earth Sci Rev, 2007,81:93-134. |
[3] | Frederick J R, Camp C R, Bauer P J. Drought-stress effects on branch and mainstem seed yield and yield components of determinate soybean. Crop Sci, 2001,41:759-763. |
[4] | Sadeghipour O, Abbasi S. Soybean response to drought and seed inoculation. World Appl Sci J, 2012,17:55-60. |
[5] | Sloane R J, Patterson R P, Carter T E. Field drought tolerance of a soybean plant introduction. Crop Sci, 1990,30:118-123. |
[6] | 刘莹, 盖钧镒, 吕慧能, 王永军, 陈受宜. 大豆耐旱种质鉴定和相关根系性状的遗传与QTL定位. 遗传学报, 2005,32:855-863. |
Liu Y, Gai J Y, Lyu H N, Wang Y J, Chen S Y. Identification of drought tolerant germplasm and inheritance and QTL mapping of related root traits in soybean (Glycine max(L.) Merr.). Acta Genet Sin, 2005,32:855-863 (in Chinese with English abstract). | |
[7] | Liu F, Andersen M N, Jacobsen S E, Jensen C R. Stomatal control and water use efficiency of soybean (Glycine max L. Merr.) during progressive soil drying. Environ Exp Bot, 2005,54:33-40. |
[8] | Guo Y, Yu H, Yang M, Kong D, Zhang Y. Effect of drought stress on lipid peroxidation, osmotic adjustment and antioxidant enzyme activity of leaves and roots of Lycium ruthenicum Murr. seedling. Russ J Plant Physiol, 2018,65:244-250. |
[9] | 耶兴元, 何晖, 张燕, 朱献辉. 脯氨酸对高温胁迫下猕猴桃苗抗热性相关生理指标的影响. 山东农业科学, 2010, (5):44-46. |
Ye X Y, He H, Zhang Y, Zhu X H. Effects of proline on physiological indexes related to heat resistance of kiwifruit seedlings under high temperature stress. Shandong Agric Sci, 2010, (5):44-46 (in Chinese with English abstract). | |
[10] | 王涛, 田雪瑶, 谢寅峰, 张往祥. 植物耐热性研究进展. 云南农业大学学报(自然科学), 2013,28:719-726. |
Wang T, Tian X Y, Xie Y F, Zhang W X. Research advance on heat-stress tolerance in plants. J Yunnan Agric Univ (Nat Sci), 2013,28:719-726 (in Chinese with English abstract). | |
[11] | Abdel-Haleem H, Carter T E, Purcell L C, King C A, Ries L L, Chen P Y, Schapaugh W, Sinclair T R, Boerma H R Mapping of quantitative trait loci for canopy-wilting trait in soybean (Glycine max L. Merr.). Theor Appl Genet, 2012,125:837-846. |
[12] | Charlson D V, Bhatnagar S, King C A, Ray J D, Sneller C H, Carter T E, Purcell L C. Polygenic inheritance of canopy wilting in soybean [Glycine max (L.) Merr.]. Theor Appl Genet, 2009,119:587-594. |
[13] | Hwang S D, King C A, Ray J D, Cregan P B, Chen P, Carter T E, Li Z L, Abdel-Haleem H, Matson K W, Schapaugh W, Purcell L C. Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations. Theor Appl Genet, 2015,128:2047-2065. |
[14] | Du W J, Wang M, Fu S X, Yu D Y. Mapping QTLs for seed yield and drought susceptibility index in soybean (Glycine max L.) across different environments. J Genet Genomics, 2009,36:721-731. |
[15] | Carpentieri-Pipolo V, Pipolo A E, Abdel-Haleem H, Boerma H R, Sinclair T R. Identification of QTLs associated with limited leaf hydraulic conductance in soybean. Euphytica, 2012,186:679-686. |
[16] | Mian M A R, Ashley D A, Boerma H R. An additional QTL for water use efficiency in soybean. Crop Sci, 1998,38:390-393. |
[17] | Mian M A R, Bailey M A, Ashley D A, Wells R, Carter T E, Parrott W A, Boerma H R. Molecular markers associated with water use efficiency and leaf ash in soybean. Crop Sci, 1996,36:1252-1257. |
[18] | Hwang S, King C A, Chen P Y, Ray J D, Cregan P B, Carter T E, Li Z L, Abdel-Haleem H, Matson K W, Schapaugh W, Purcell L C. Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean. Mol Breed, 2016,36. |
[19] | Khan M A, Tong F, Wang W B, He J B, Zhao T J, Gai J Y. Using the RTM-GWAS procedure to detect the drought tolerance QTL-allele system at the seedling stage under sand culture in a half-sib population of soybean [Glycine max (L.) Merr.]. Can J Plant Sci, 2019,99:801-814. |
[20] | Khan M A, Tong F, Wang W B, He J B, Zhao T J, Gai J Y. Analysis of QTL-allele system conferring drought tolerance at seedling stage in a nested association mapping population of soybean [Glycine max (L.) Merr.] using a novel GWAS procedure. Planta, 2019,249:1653-1653. |
[21] | 张志良, 瞿伟菁. 植物生理学实验指导. 北京: 高等教育出版社, 2003. pp 258-260. |
Zhang Z L, Qu W J. Guide to Plant Physiology. Beijing: High Education Press, 2003. pp 258-260(in Chinese). | |
[22] | Sayed M A, Schumann H, Pillen K, Naz A A, Leon J. AB-QTL analysis reveals new alleles associated to proline accumulation and leaf wilting under drought stress conditions in barley (Hordeum vulgare L.). BMC Genetics, 2012,13:61. |
[23] | Andolfatto P, Davison D, Erezyilmaz D, Hu T T, Mast J, Sunayama-Morita T, Stern D L. Multiplexed shotgun genotyping for rapid and efficient genetic mapping. Genome Res, 2011,21:610-617. |
[24] | Li R Q, Yu C, Li Y R, Lam T W, Yiu S M, Kristiansen K, Wang J. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics, 2009,25:1966-1967. |
[25] | Yi X, Liang Y, Huerta-Sanchez E, Jin X, Cuo Z X P, Pool J E, Xu X, Jiang H, Vinckenbosch N, Korneliussen T S, Zheng H C, Liu T, He W M, Li K, Luo R B, Nie X F, Wu H L, Zhao M R, Cao H Z, Zou J, Shan Y, Li S Z, Yang Q, Asan, Ni P X, Tian G, Xu J M, Liu X A, Jiang T, Wu R H, Zhou G Y, Tang M F, Qin J J, Wang T, Feng S J, Li G H, Huasang,Luosang J B, Wang W, Chen F, Wang Y D, Zheng X G, Li Z, Bianba Z M, Yang G, Wang X P, Tang S H, Gao G Y, Chen Y, Luo Z, Gusang L, Cao Z, Zhang Q H, Ouyang W H, Ren X L, Liang H Q, Zheng H S, Huang Y B, Li J X, Bolund L, Kristiansen K, Li Y R, Zhang Y, Zhang X Q, Li R Q, Li S G, Yang H M, Nielsen R, Wang J, Wang J A. Sequencing of 50 human exomes reveals adaptation to high altitude. Science, 2010,329:75-78. |
[26] | Scheet P, Stephens M. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet, 2006,78:629-644. |
[27] | Barrett J, Fry B, Maller J, Daly M. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics, 2005,21:263-265. |
[28] | He J, Meng S, Zhao T, Xing G, Yang S, Li Y, Guan R, Lu J, Wang Y, Xia Q, Yang B, Gai J. An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding. Theor Appl Genet, 2017,130:2327-2343. |
[29] | Barik S R, Pandit E, Mohanty S P, Nayak D K, Pradhan S K. Genetic mapping of physiological traits associated with terminal stage drought tolerance in rice. BMC Genetics, 2020,21:1-12. |
[30] | Ilyas N, Amjid M W, Saleem M A, Khan W, Wattoo F M, Rana R M, Maqsood, Rana H, Zahid A, Shah G A, Anwar A. Ahmad M Q, Shaheen M, Riaz H, Ansari M J. Quantitative trait loci (QTL) mapping for physiological and biochemical attributes in a Pasban 90/Frontana recombinant inbred lines (RILs) population of wheat ( Triticum aestivum) under salt stress condition. Saudi J Biol Sci, 2020,27:341-351. |
[31] | Zhang C, Jin F, Li S, Liu W, Ma X, Yang S, Li X. Fine mapping of major QTLs for alkaline tolerance at the seedling stage in maize (Zea mays L.) through genetic linkage analysis combined with high-throughput DNA sequencing. Euphytica, 2018,214:120. |
[1] | 陈玲玲, 李战, 刘亭萱, 谷勇哲, 宋健, 王俊, 邱丽娟. 基于783份大豆种质资源的叶柄夹角全基因组关联分析[J]. 作物学报, 2022, 48(6): 1333-1345. |
[2] | 杨欢, 周颖, 陈平, 杜青, 郑本川, 蒲甜, 温晶, 杨文钰, 雍太文. 玉米-豆科作物带状间套作对养分吸收利用及产量优势的影响[J]. 作物学报, 2022, 48(6): 1476-1487. |
[3] | 王炫栋, 杨孙玉悦, 高润杰, 余俊杰, 郑丹沛, 倪峰, 蒋冬花. 拮抗大豆斑疹病菌放线菌菌株的筛选和促生作用及防效研究[J]. 作物学报, 2022, 48(6): 1546-1557. |
[4] | 于春淼, 张勇, 王好让, 杨兴勇, 董全中, 薛红, 张明明, 李微微, 王磊, 胡凯凤, 谷勇哲, 邱丽娟. 栽培大豆×半野生大豆高密度遗传图谱构建及株高QTL定位[J]. 作物学报, 2022, 48(5): 1091-1102. |
[5] | 李阿立, 冯雅楠, 李萍, 张东升, 宗毓铮, 林文, 郝兴宇. 大豆叶片响应CO2浓度升高、干旱及其交互作用的转录组分析[J]. 作物学报, 2022, 48(5): 1103-1118. |
[6] | 彭西红, 陈平, 杜青, 杨雪丽, 任俊波, 郑本川, 罗凯, 谢琛, 雷鹿, 雍太文, 杨文钰. 减量施氮对带状套作大豆土壤通气环境及结瘤固氮的影响[J]. 作物学报, 2022, 48(5): 1199-1209. |
[7] | 王好让, 张勇, 于春淼, 董全中, 李微微, 胡凯凤, 张明明, 薛红, 杨梦平, 宋继玲, 王磊, 杨兴勇, 邱丽娟. 大豆突变体ygl2黄绿叶基因的精细定位[J]. 作物学报, 2022, 48(4): 791-800. |
[8] | 李瑞东, 尹阳阳, 宋雯雯, 武婷婷, 孙石, 韩天富, 徐彩龙, 吴存祥, 胡水秀. 增密对不同分枝类型大豆品种同化物积累和产量的影响[J]. 作物学报, 2022, 48(4): 942-951. |
[9] | 杜浩, 程玉汉, 李泰, 侯智红, 黎永力, 南海洋, 董利东, 刘宝辉, 程群. 利用Ln位点进行分子设计提高大豆单荚粒数[J]. 作物学报, 2022, 48(3): 565-571. |
[10] | 周悦, 赵志华, 张宏宁, 孔佑宾. 大豆紫色酸性磷酸酶基因GmPAP14启动子克隆与功能分析[J]. 作物学报, 2022, 48(3): 590-596. |
[11] | 王娟, 张彦威, 焦铸锦, 刘盼盼, 常玮. 利用PyBSASeq算法挖掘大豆百粒重相关位点与候选基因[J]. 作物学报, 2022, 48(3): 635-643. |
[12] | 董衍坤, 黄定全, 高震, 陈栩. 大豆PIN-Like (PILS)基因家族的鉴定、表达分析及在根瘤共生固氮过程中的功能[J]. 作物学报, 2022, 48(2): 353-366. |
[13] | 张国伟, 李凯, 李思嘉, 王晓婧, 杨长琴, 刘瑞显. 减库对大豆叶片碳代谢的影响[J]. 作物学报, 2022, 48(2): 529-537. |
[14] | 宋丽君, 聂晓玉, 何磊磊, 蒯婕, 杨华, 郭安国, 黄俊生, 傅廷栋, 汪波, 周广生. 饲用大豆品种耐荫性鉴定指标筛选及综合评价[J]. 作物学报, 2021, 47(9): 1741-1752. |
[15] | 曹亮, 杜昕, 于高波, 金喜军, 张明聪, 任春元, 王孟雪, 张玉先. 外源褪黑素对干旱胁迫下绥农26大豆鼓粒期叶片碳氮代谢调控的途径分析[J]. 作物学报, 2021, 47(9): 1779-1790. |
|