Scientia Agricultura Sinica ›› 2017, Vol. 50 ›› Issue (4): 599-611.doi: 10.3864/j.issn.0578-1752.2017.04.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS •     Next Articles

Association Analysis of Rice Cooking Quality Traits with Molecular Markers

GAO WeiWei, CHEN SiPing, WANG LiPing, CHEN LiKai, GUO Tao, WANG Hui, CHEN ZhiQiang   

  1. National Engineering Research Centre of Plant Space Breeding, South China Agricultural University, Guangzhou 510642
  • Received:2016-08-22 Online:2017-02-16 Published:2017-02-16

RichHTML

15

PDF

992

Abstract: 【Objective】 In this study, the variation of major grain-quality traits and RVA profiles of representative rice germplasm were investigated, molecular markers significantly associated with the traits were identified, aiming to provide an important foundation for improvement of grain quality of rice. 【Method】 Global grain-quality properties and their differences were surveyed with a rice panel consisted of 48 diverse germplasms collected from both China and abroad. Starch RVA profile was examined with a Rapid Visco Analyzer. The markers reported to be related to starch biosynthesizing genes and QTLs for development of rice grain were used for genotyping. Trait-marker association for grain-quality properties was detected using the general linear model with Tassel 3.0 software. Moreover, stepwise regression analysis was performed with these detected markers significantly associated with grain-quality traits. The phenotypic effects of the alleles and allelic combinations were estimated and both elite alleles and typical carrier genotypes were identified. 【Result】There were wide phenotypic variance and diversity in amylose content (AC), gel consistency (GC) and alkali spreading value (ASV), and the coefficient of variation (CV.) ranged from 26.5% to 36.3%. Based on inspection of RVA profile, significant differences were found in breakdown (BDV), setback (SBV) and consistence (CSV), and these parameters have preferably reflected the diverse starch paste properties among different rice varieties. Correlation analysis showed the AC was positively correlated with cool paste viscosity (CPV), SBV and CSV, while negatively correlated with peak viscosity (PKV) and BDV. The GC was negatively correlated with SBV and CSV. A total of 491 alleles were identified with 154 polymorphic markers, with an average gene diversity of 0.447 and an average polymorphic information content of 0.390. Based on the analysis of trait-marker association, a total of 22 markers were detected to associate with grain-quality traits, which explained the phenotypic variance ranged from 14.11% to 75.62%. The GBSSI gene majorly affected the properties of AC and GC, and the SNP marker of Wx-G/T explained up to 61.44% and 41.87% of the phenotypic variation for AC and GC, respectively. While the SSIIa was the major gene affecting ASV, and the phenotypic variation of ASV explained by the markers of alk-GC/TT and SSIIa-F was up to 75.62% and 74.46%. The model equations based on stepwise regression analysis of AC, GC and ASV were developed using the significant markers, whose determination coefficients were 85.30%, 40.62%, and 80.38%, respectively. 【Conclusion】The starch RVA profile wass closely related to AC, GC and ASV. The RVA profile can be used to evaluate rice quality traits more comprehensively. With trait-marker association analysis, 22 markers were detected to be associated with grain-quality traits, and five of these sites were associated with both AC and GC. Regression models showed allelic combination can produce different phenotypic effects.

Key words: rice, grain-quality traits, trait-marker association, allelic variation

[1]    Cheng F, Zhong L, Shu Q. Studies on the cooking and eating quality properties in chalky milled grains of early indica rice. Acta Agronomica Sinica, 2002, 28(3): 363-368.
[2]    胡培松, 翟虎渠, 唐绍清, 万建民. 利用RVA快速鉴定稻米蒸煮及食味品质的研究. 作物学报, 2004, 30(6): 519-524.
HU P S, ZHAI H Q, TANG S Q, WAN J M. Rapid evaluation of rice cooking and palatability quality by RVA profile. Acta Agronomica Sinica, 2004, 30(6): 519-524. (in Chinese)
[3]    Zhao X, Zhou L, Ponce K, Ye G. The usefulness of known genes/Qtls for grain quality traits in an Indica population of diverse breeding lines tested using association analysis. Rice, 2015, 8(1): 1-13.
[4]    Kharabian-Masouleh A, Waters D L E, Reinke R F, Ward R, Henry R J. SNP in starch biosynthesis genes associated with nutritional and functional properties of rice. Scientific Reports, 2012, 2(8): 1-9.
[5]    邱先进, 袁志华, 陈凯, 杜斌, 何文静, 杨隆维, 徐建龙, 邢丹英, 吕文恺. 用全基因组关联分析解析籼稻垩白的遗传基础. 作物学报, 2015, 41(7): 1007-1016.
QIU X J, YUAN Z H, CHEN K, DU B, HE W J, YANG L W, XU J L, XING D Y, Lü W K. Genetic dissection of grain chalkiness in Indica mini-core germplasm using genome-wide association method. Acta Agronomica Sinica, 2015, 41(7): 1007-1016. (in Chinese)
[6]    Xu C, Liu Y, Li Y, Xu X, Xu C, Li X, Xiao J, Zhang Q. Differential expression of GS5 regulates grain size in rice. Journal of Experimental Botany, 2015, 66(9): 2611-2623.
[7]    Wang S, Li S, Liu Q, Wu K, Zhang J, Wang S, Wang Y, Chen X, Zhang Y, Gao C. The OsSPL16-GW7 regulatory module determines grain shape and simultaneously improves rice yield and grain quality. Nature genetics, 2015, 47(8): 949-954.
[8]    Li Y, Fan C, Xing Y, Yun P, Luo L, Yan B, Peng B, Xie W, Wang G, Li X. Chalk5 encodes a vacuolar H+-translocating pyrophosphatase influencing grain chalkiness in rice. Nature genetics, 2014, 46(4): 398-404.
[9]    Chen M, Bergman C, Pinson S, Fjellstrom R. Waxy gene haplotypes: Associations with apparent amylose content and the effect by the environment in an international rice germplasm collection. Journal of Cereal Science, 2008, 47(3): 536-545.
[10]   Su Y, Rao Y, Hu S, Yang Y, Gao Z, Zhang G, Liu J, Hu J, Yan M, Dong G. Map-based cloning proves qGC-6, a major QTL for gel consistency of japonica/indica cross, responds by Waxy in rice (Oryza sativa L.). Theoretical and applied genetics, 2011, 123(5): 859-867.
[11]   Gao Z, Zeng D, Cui X, Zhou Y, Yan M, Huang D, Li J, Qian Q. Map-based cloning of the ALK gene, which controls the gelatinization temperature of rice. Science in China Series C: Life Sciences, 2003, 46(6): 661-668.
[12]   池彦衡. 稻种资源稻米品质评价及可溶性淀粉合酶基因序列多态性和关联分析[D]. 南昌: 江西农业大学, 2011.
CHI Y H. The quality evaluation of rice resources and sequence polymorphism and association analysis of rice soluble starch synthase gene[D]. Nanchang: Jiangxi Agricultural University, 2011. (in Chinese)
[13]   林华. 水稻可溶性淀粉合酶基因SSIIa、SSIIIa等位变异及其与稻米品质的关联分析[D]. 南昌: 江西农业大学, 2011.
LIN H. The research of allelic diversification of soluble starch synthase gene SSIIa and SSIIIa and its association with rice quality[D]. Nanchang: Jiangxi Agricultural University, 2011. (in Chinese)
[14]   徐卫. 水稻可溶性淀粉合酶基因与产量和稻米品质性状的关联分析[D]. 南昌: 江西农业大学, 2013.
XU W. The association analysis of rice soluble starch synthase gene with yield and quality traits[D]. Nanchang: Jiangxi Agricultural University, 2013. (in Chinese)
[15]   Yang F, Chen Y, Tong C, Huang Y, Xu F, Li K, Corke H, Sun M, Bao J. Association mapping of starch physicochemical properties with starch synthesis-related gene markers in nonwaxy rice (Oryza sativa L.). Molecular Breeding, 2014, 34(4): 1747-1763.
[16]   中华人民共和国农业部部颁标准. NY147-88稻米品质评价方法. 北京: 中国标准出版社, 1988: 4-6.
Chinese Ministry of Agriculture. NY147-88, The Method of Rice Quality Evaluation. Beijing: Chinese Criteria Press, 1988: 4-6. (in Chinese)
[17]   包劲松. 应用RVA测定米粉淀粉成糊温度. 中国水稻科学, 2007, 21(5): 543-546.
BAO J S. Accurate measurement of pasting temperature of rice flour by a rapid Visco-Analyser. Chinese Journal of Rice Science, 2007, 21(5): 543-546. (in Chinese)
[18]   Lee C, Park J, Kim B, Seo J, Lee G, Jang S, Koh H. Influence of multi-gene allele combinations on grain size of rice and development of a regression equation model to predict grain parameters. Rice, 2015, 8(1). 1-10.
[19]   Breseghello F. Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics, 2005, 172(2): 1165-1177.
[20]   文自翔, 赵团结, 郑永战, 刘顺湖. 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. 作物学报, 2008, 34(8): 1339-1349.
WEN Z X, ZHAO T J, ZHENG Y Z, LIU S H. Association analysis of agronomic and quality traits with SSR markers in Glycine max and Glycine soja in China: II. Exploration of elite alleles. Acta Agronomica Sinica, 2008, 34(8): 1339-1349. (in Chinese)
[21]   Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology, 2005, 14(8): 2611-2620.
[22]   何秀英, 程永盛, 刘志霞. 国标优质籼稻的稻米品质与淀粉RVA谱特征研究. 华南农业大学学报, 2015, 36(3): 37-44.
HE X Y, CHENG Y S, LIU Z X. Studies on the rice quality and starch RVA profile characteristics ofindica rice varieties with national high-quality. Journal of South China Agricultural University, 2015, 36(3): 37-44. (in Chinese)
[23]   隋炯明, 李欣, 严松, 严长杰, 张蓉, 汤述翥, 陆驹飞, 陈宗祥, 顾铭洪. 稻米淀粉RVA谱特征与品质性状相关性研究. 中国农业科学, 2005, 38(4): 657-663.
SUI J M, LI X, YAN S, YAN C J, ZHANG R, TANG S Z, LU J F, CHEN Z X, GU M H. Studies on the rice RVA profile characteristics and its correlation with the quality. Scientia Agricultura Sinica, 2005, 38(4): 657-663. (in Chinese)
[24]   贾良, 丁雪云, 王平荣, 邓晓建. 稻米淀粉RVA谱特征及其与理化品质性状相关性的研究. 作物学报, 2008, 34(5): 790-794.
JIA L, DING X Y, WANG P R, DENG X J. Rice RVA profile characteristics and correlation with the physical/chemical quality. Acta Agronomica Sinica, 2008, 34(5): 790-794. (in Chinese)
[25]   Jin L, Lu Y, Xiao P, Sun M, Corke H, Bao J. Genetic diversity and population structure of a diverse set of rice germplasm for association mapping. Theoretical and Applied Genetics, 2010, 121(3): 475-487.
[26]   孙业盈, 彦吕, 董春林, 王平荣. 水稻Wx基因与稻米AC、GC和GT的遗传关系. 作物学报, 2005, 31(5): 535-539.
SUN Y Y, YAN L, DONG C L, WANG P R. Genetic relationship among Wx gene, AC, GC and GT of rice. Acta Agronomica Sinica, 2005, 31(5): 535-539. (in Chinese)
[27]   Tian Z, Qian Q, Liu Q, Yan M, Liu X, Yan C, Liu G, Gao Z, Tang S, Zeng D, Wang Y, Yu J, Gu M, Li J. Allelic diversities in rice starch biosynthesis lead to a diverse array of rice eating and cooking qualities. Proceedings of the National Academy of Science of the USA, 2009, 106(51): 21760-21765.
[28]   Tran N A, Daygon V D, Resurreccion A P, Cuevas R P, Corpuz H M, Fitzgerald M A. A single nucleotide polymorphism in the Waxy gene explains a significant component of gel consistency. Theoretical and applied genetics, 2011, 123(4): 519-525.
[29]   Bao J S, Corke H, Sun M. Nucleotide diversity in starch synthase IIa and validation of single nucleotide polymorphisms in relation to starch gelatinization temperature and other physicochemical properties in rice (Oryza sativa L.). Theoretical and Applied Genetics, 2006, 113(7): 1171-1183.
[30]   Cuevas R P, Daygon V D, Corpuz H M, Nora L, Reinke R F, Waters D L, Fitzgerald M A. Melting the secrets of gelatinisation temperature in rice. Functional Plant Biology, 2010, 37(5): 439-447.
[31]   Lin J, Shi C, Wu M, Wu J. Analysis of genetic effects for cooking quality traits of japonica rice across environments. Plant Science, 2005, 168(6): 1501-1506.
[32]   Su Y, Rao Y, Hu S, Yang Y, Gao Z, Zhang G, Liu J, Hu J, Yan M, Dong G, Zhu L, Guo L, Qian Q, Zeng D. Map-based cloning proves qGC-6, a major QTL for gel consistency of japonica/indica cross, responds by Waxy in rice (Oryza sativa L.). Theoretical and Applied Genetics, 2011, 123(5): 859-867.
[33]   GAO Z, ZENG D, CHENG F, TIAN Z. ALK, the key gene for gelatinization temperature, is a modifier gene for gel consistency in rice. Journal of Integrative Plant Biology, 2011, 53(9): 756-765.
[34]   Nakamura Y, Francisco P B, Hosaka Y, Sato A, Sawada T, Kubo A, Fujita N. Essential amino acids of starch synthase IIa differentiate amylopectin structure and starch quality between japonica and indica rice varieties. Plant molecular biology, 2005, 58(2): 213-227.
[35]   Lestari P, Jiang W, Chu S, REFLINUR, SUTRISNO, Kusbiantoro B, Kim B, Piao R, Cho Y, Luo Z, Chin J, Koh H. DNA markers for eating quality of indica rice in Indonesia. Plant Breeding, 2015, 134(1): 40-48.
[1] PENG TingShen, LU JiuYan, WU MeiLin, YAN YuXin, LIU HongZhou, NAN WenBin, QIN XiaoJian, LI Ming, GONG JunYi, LIANG YongShu. QTL Analysis of Yield-Related Traits in Both Huangnuo2# and Changbai7# of Perennial Chinese Rice [J]. Scientia Agricultura Sinica, 2026, 59(7): 1361-1379.
[2] CUI JieHao, ZHANG Meng, WANG Qin, YU JiaYan, LIN Kun, LI ShangZe, LAN Heng, GENG YanQiu, ZHANG Qiang, GUO LiYing, SHAO XiWen. Evaluation of Lodging Resistance and Its Physiological Mechanisms in Japonica Rice Resources [J]. Scientia Agricultura Sinica, 2026, 59(7): 1420-1438.
[3] YUAN HaoLiang, NIE Jun, LI Peng, LU YanHong, LIAO YuLin, XU ChangXu, LI ZhongYi, CAO WeiDong, ZHANG JiangLin. Effects of Co-Utilization of Chinese Milk Vetch and Rice Straw on Soil Phosphorus Composition and Phosphorus Activation of Paddy Field in Southern China [J]. Scientia Agricultura Sinica, 2026, 59(7): 1480-1491.
[4] XU YangHaoJun, CHEN LiMing, YANG ShiQi, TANG YiFan, TAN XueMing, ZENG YongJun, PAN XiaoHua, ZENG YanHua. Effects of Long-Term Different Straw Returning Methods on Soil Organic Carbon, Nutrients and Aggregate Formation in Different Soil Layers of Double Cropping Rice Field [J]. Scientia Agricultura Sinica, 2026, 59(7): 1492-1506.
[5] LI XingYu, HUANG Rong, XIAN YiMing, TIAN JiaoJiao, MA XiaoJin, YANG QiaoXi, LI Bing, WANG ChangQuan. Characteristics of Organic Carbon Fractions and Carbon Dioxide Emissions of Different Size Aggregates in Rice Field Soils in Response to Long-Term Fertilization [J]. Scientia Agricultura Sinica, 2026, 59(6): 1255-1271.
[6] MA ZhaoHui, QUAN ChengZhe, CHENG HaiTao, YANG KanJie, LI XinRui, LÜ WenYan. The Breeding Goals and Strategies of Northeast Japonica Rice Under the Background of Zhongke Fa No.5 [J]. Scientia Agricultura Sinica, 2026, 59(5): 927-936.
[7] ZHANG WeiJian, YAN ShengJi, SHANG ZiYin, TANG ZhiWei, WU LiuGe, LI JiaRui, CHEN HaoTian, DENG AiXing, ZHANG Jun, ZHANG Xin, ZHENG ChengYan, SONG ZhenWei. Methane Emissions from Paddy Fields: Not Entirely Attributable to Rice Cultivation [J]. Scientia Agricultura Sinica, 2026, 59(4): 824-833.
[8] CHEN Min, JIAO ZiLan, QIAO ChengBin, XU Hao, ZHANG Bi, MA DongHua, KONG WeiRu, WANG JingWen, SONG JiaWei, LUO ChengKe, LI PeiFu, TIAN Lei. Morpho-Physiological Responses and Adaptive Strategies of Rice Germplasm Accessions from Different Subspecies Under Salt Stress [J]. Scientia Agricultura Sinica, 2026, 59(4): 705-722.
[9] GUO FuCheng, TANG HaiJiang, HAO XinYi, MA GuoLin, YANG JiuJu, HUANG LinFeng, TIAN Lei, WANG Bin, LUO ChengKe. Effects of Different Irrigation Methods on Water-Salt Transport, Rice Yield, and Water Use Efficiency in Saline Soil in Ningxia [J]. Scientia Agricultura Sinica, 2026, 59(4): 750-764.
[10] LUO Wei, YU Hong, YUAN LiXin, WANG LingLing, ZHAO JinPeng, YIN Wei, WANG MingTian, WANG RuLin. Change of Geographic Distributions of Ratoon Rice in Sichuan- Chongqing Under Global Climate Change [J]. Scientia Agricultura Sinica, 2026, 59(4): 765-780.
[11] ZHU Shu, GUO ZhiPeng, SUN Ying. Functional Analysis of Rice Target of Rapamycin OsTOR in Regulating Root Elongation [J]. Scientia Agricultura Sinica, 2026, 59(3): 475-485.
[12] LÜ WenYan, CHENG HaiTao, MA ZhaoHui, TIAN ShuHua. Discussion on Hybridization Breeding Technology and Strategy of Rice in the New Era of Breeding [J]. Scientia Agricultura Sinica, 2026, 59(2): 233-238.
[13] LIAO TingLu, SHI YaFei, XIAO DongHao, SHE YangMengFei, GUO FuCheng, YANG JiuJu, TANG HaiJiang, LUO ChengKe. The Effect of Exogenous Nitroprusside on Sugar Metabolism in Rice Seedlings Under Alkaline Stress [J]. Scientia Agricultura Sinica, 2026, 59(2): 265-277.
[14] LIU TianSheng, LIU GengYuan, ZHAO AnQi, YANG Xu, CAI MingXue, YANG AiWen, LOU MingXuan, LI MuKai, WANG Han, ZHANG YaLing. Pathogenic Population of Rice Bakanae Disease in Heilongjiang Province [J]. Scientia Agricultura Sinica, 2026, 59(2): 305-321.
[15] WANG ZhongNi, LEI Yue, LI JiaLi, GONG YanLong, ZHU SuSong. Functions of ABC Transporter OsARG1 in Rice Heading Date Regulation [J]. Scientia Agricultura Sinica, 2026, 59(1): 1-16.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备09089781号-30
Copyright 2018 © Editorial office of Scientia Agricultura Sinica
Tel: 86-010-82106279    E-mail: zgnykx@mail.caas.net.cn
Supported by Beijing Magtech Co.Ltd