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Frontiers of Agriculture in China

ISSN 1673-7334

ISSN 1673-744X(Online)

CN 11-5729/S

Front Agric Chin    2009, Vol. 3 Issue (2) : 130-139    https://doi.org/10.1007/s11703-009-0033-y
RESEARCH ARTICLE
Correlation between allele sizes of microsatellites and phenotypic variations in rice landraces
Yawen ZENG1(), Shuming YANG1, Juan DU1, Xiaoying PU1, Hongliang ZHANG2, Zichao LI2(), Luxiang WANG3, Jiafu LIU3, Fenghui XIAO4
1. Biotechnology and Genetic Resources Institute, Yunnan Academy of Agricultural Sciences, Kunming 650205, China; 2. Key Lab of Crop Genomics and Genetic Improvement of Ministry of Agriculture, Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing 100094, China; 3. Supervision and Testing Center for Farm Products Quality, Ministry of Agriculture of the People’s Republic of China, Kunming 650223, China; 4. Yunnan Agricultural University, Kunming 650201, China
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Abstract

Yunnan is one of the largest centers of genetic diversity in the world. Allele size of microsatellites associated with phenotypic traits of rice landraces in Yunnan, Southwest China, was investigated based on 20 SSR markers and 23 phenotypic traits, as well as eight mineral elements in brown rice within the core collection of 629 accessions; and there was a significant correlation for 182 (r = 0.083*-0.438**) of 620 pairs among these markers and traits, as well as elements. Surprisingly, there was a significant correlation for 94 of 180 pairs between the allele size of microsatellites and grain traits, and 48 of 160 pairs between allele size of microsatellites and panicle traits. In these rice landraces, 309 alleles were detected, with an average of 15.5 alleles per marker, ranging from 5 (RM60) to 40 (RM257). There was a significant correlation between the allele size of 20 SSR markers and some phenotypic traits, such as the significant correlation of 17 (r = -0.085*--0.438**) pairs between the allele size of RM224 and 23 phenotypic traits, as well as eight elements. The allele size of microsatellites was more associated with grain or panicle traits than that of plant traits or element contents in brown rice. Grain length/width ratio and 1-2 internode length, as indica-japonica classification traits, in which two traits were closely associated with the allele size of 14 SSR markers ranging from 0.089* to -0.438**. Therefore, allele size of SSRs was associated with phenotypic traits (especially in grain traits), as well as elemental contents in brown rice.

Keywords allele size of microsatellite      phenotypic traits      mineral elements      correlation      rice landraces     
Corresponding Author(s): ZENG Yawen,Email:zengyw1967@126.com; LI Zichao,Email:lizichao@cau.edu.cn   
Issue Date: 05 June 2009
 Cite this article:   
Yawen ZENG,Shuming YANG,Juan DU, et al. Correlation between allele sizes of microsatellites and phenotypic variations in rice landraces[J]. Front Agric Chin, 2009, 3(2): 130-139.
 URL:  
https://academic.hep.com.cn/fag/EN/10.1007/s11703-009-0033-y
https://academic.hep.com.cn/fag/EN/Y2009/V3/I2/130
markers629 accessionsrepeat motif*linking traits of microsatellites from http://www.shigen.nig.ac.jp/ rice/oryzabase/update/htmlmain references
no. allelesize of allele/bp
RM511103-121(GA)14yield-enhancing, grains per panicle, percent germination, head rice grain, grain length/width ratioXiao et al., 1996; Thomson et al., 2003; Liang et al., 2004
RM81A12101-120(TCT)10grain yield per plant, 1000-grain weight, plant heightCui et al., 2004
RM2118142-162(TC)4T3C3(TC)(CT)2yield-improving, grain width, days to headingMiyata et al., 2007
RM26317149-197(CT)34broken rice grain, crushed rice grain, 1000-grain weight, spotted leafSeptiningsih et al., 2003; Xu et al., 2004
RM605160-168(AATT)5AATCT(AATT)high-tillering dwarf 1, days to heading, shatteringThomson et al., 2003; Septiningsih et al., 2003
RM23215137-164(CT)241000-grain weight, panicles per plant, panicle length, grains per panicle, grain yield per plant, cracked grainTan et al., 2007;Yoshida et al., 2002
RM24121111-148(GA)31Panicles per plant, plant heightThomson et al., 2003; Cui et al., 2004
RM25515112-159(AGG)5(AG)2(GA)161000-grain weight, panicle size, panicles per plant, panicle neck diameterXu et al., 2004;Yoshida et al., 2002
RM24911121-166(AG)5A2(AG)14tillers per plant, panicles per plant, grains number per plant, grain thickness, 1000-grain weight, panicle lengthPradeep et al., 2005; Miyata et al., 2007;Abdelkhalik et al., 2005
RM22512124-151(CT)18nitrogen use efficiency, grain breadthhttp://www.cropscience.org.au/icsc2004/poster/3/4/1/1296_senthilvels.htm
RM2532298-187(GA)25percent head rice, amylase content, alkali spreading score, protein content, grain length, grain length /width ratio, days to maturity, heading date, awn lengthXiao et al., 1996; Linh et al., 2006
RM1812150-172(GA)4AA(GA)(AG)16frizzle panicle, grain yield, tillers per plant, grains per panicle, heading dateDuan et al., 2003
RM23417110-170(CT)25days to heading, days to maturity, maximum root lengthThomson et al., 2003; Miyata et al., 2007
RM22317137-170(CT)20panicle per plant, days to heading, panicle length;Pradeep et al., 2005; Miyata et al., 2007
RM25740123-210(CT)24cold resistance, heading dateMiyata et al., 2007
RM2449149-164(CT)4(CG)3C(CT)6fertility restorer genesJing et al., 2000
RM25813131-152(GA)21(GGA)3spikelet fertility, 1000-grain weight, tiller number, heading dateCui et al., 2004; Miyata et al., 2007
RM22418124-162(AAG)8(AG)13plant height, tillers per plant, panicle length, root-shoot ratioMiyata et al., 2007
RM2351895-137(CT)24panicles per plantThomson et al., 2003
RM24728124-184(CT)16phosphorus deficiency, plant heightThomson et al., 2003
Tab.1  Allele size of microsatellites in Yunnan rice landraces and its linking gene or traits
markersPKCaMgFeZnCuMn
RM5-0.0110.087*0.080-0.022-0.017-0.0010.036-0.013
RM81A-0.144**-0.086*-0.0140.0030.0030.076-0.129**0.033
RM211-0.0490.002-0.0430.015-0.0260.0080.0360.029
RM2630.0020.001-0.0580.0350.0010.0640.0760.042
RM600.012-0.0280.0460.0240.042-0.061-0.096*-0.091*
RM2320.101*-0.0180.0070.042-0.0150.0060.001-0.002
RM2410.0010.006-0.047-0.012-0.0560.0070.0120.046
RM2550.0600.0740.091*0.047-0.0050.023-0.0230.051
RM249-0.0410.0360.018-0.022-0.051-0.037-0.062-0.066
RM225-0.075-0.087*-0.059-0.101*-0.083*0.037-0.027-0.093*
RM253-0.104*-0.092*-0.009-0.0630.0240.015-0.103*0.002
RM180.035-0.0210.0250.088*-0.0130.017-0.0130.033
RM2340.096*-0.0260.042-0.0200.007-0.006-0.0470.014
RM2230.0190.0520.0440.019-0.0090.0020.027-0.025
RM257-0.0020.037-0.052-0.010-0.0200.028-0.024-0.046
RM244-0.092*-0.085*0.016-0.091*-0.030-0.002-0.065-0.011
RM2580.076-0.036-0.0310.020-0.0120.0390.028-0.004
RM224-0.0340.006-0.024-0.0340.0090.0330.042-0.034
RM2350.0530.110**-0.0070.0580.0240.036-0.0420.047
RM2470.0290.0590.101*0.0470.0510.010-0.084*0.041
Tab.2  Correlation coefficients between allele size of microsatellites and mineral concentration contents
markerschromosomeplant heighttillers per plantpanicles per plantdays to headingflagleaf lengthflagleaf width
RM51-0.019-0.089*0.0370.0540.0370.064
RM81A10.0420.0590.0570.0130.137-0.047
RM2112-0.052-0.0230.012-0.019-0.0010.012
RM2632-0.085*-0.028-0.015-0.036-0.049-0.098*
RM603-0.109**-0.0020.022-0.084*0.058-0.020
RM23230.0570.0430.0660.143**0.070-0.043
RM24140.039-0.0700.0580.0780.0210.006
RM25540.0290.0700.0420.0710.0650.009
RM24950.0440.033-0.100*0.04230.0470.005
RM2256-0.140**-0.015-0.001-0.0275-0.0310.042
RM25360.012-0.0280.0770.06410.033-0.010
RM1870.0450.095*0.0550.02750.068-0.078
RM23470.022-0.022-0.077-0.01040.0370.043
RM22380.037-0.008-0.0680.2001**0.052-0.053
RM25790.0280.126**0.0060.04170.138**0.055
RM244100.0420.0760.0530.05010.0580.008
RM25810-0.039-0.026-0.108**0.0114-0.0430.008
RM22411-0.151**-0.085*-0.042-0.1134**-0.086*0.021
RM235120.023-0.0520.0440.0228-0.032-0.048
RM24712-0.0060.082*0.049-0.01400.047-0.012
Tab.3  Correlation coefficients between allele size of microsatellites and plant traits
markers1000-grainweightgrain lengthgrain widthgrain length/width ratiograin thicknessrice lengthricewidthrice thicknessshattering
RM5-0.089*0.273**-0.195**0.294**-0.130**0.148**-0.220**-0.133**-0.134**
RM81A0.0590.189**-0.186**0.233**-0.0290.010-0.194**-0.209**-0.187**
RM211-0.080-0.121**0.101*-0.134**0.025-0.134**0.079-0.0320.092*
RM263-0.183**-0.287**0.127**-0.246**0.077-0.224**0.194**0.0520.070
RM60-0.079-0.045-0.0680.0190.016-0.078-0.025-0.024-0.010
RM232-0.028-0.020-0.0530.027-0.0450.025-0.048-0.026-0.045
RM2410.0010.064-0.089*0.089*-0.0410.050-0.067-0.066-0.013
RM2550.0570.180**-0.162**0.212**-0.125**0.073-0.178**-0.134**-0.089*
RM249-0.0080.041-0.0560.0660.024-0.023-0.069-0.047-0.092*
RM225-0.141**-0.155**0.103*-0.174**0.025-0.126**0.124**0.028-0.011
RM253-0.069-0.056-0.001-0.0350.011-0.087*0.035-0.0190.030
RM180.0460.198**-0.148**0.221**-0.0790.148**-0.166**-0.028-0.051
RM234-0.073-0.0790.014-0.0600.074-0.0790.0680.0060.090*
RM2230.013-0.0320.037-0.026-0.0120.0120.0550.033-0.012
RM2570.0090.214**-0.239**0.291**-0.144**0.138**-0.241**-0.151**0.085*
RM2440.0370.210**-0.159**0.230**-0.142**0.116**-0.159**-0.109**-0.135**
RM258-0.151**-0.226**0.135**-0.216**-0.032-0.152**0.160**0.0490.067
RM224-0.190**-0.424**0.242**-0.420**0.173**-0.349**0.348**0.189**0.113**
RM235-0.027-0.129**0.236**-0.239**0.143**-0.0520.209**0.167**0.086*
RM2470.0270.244**-0.188**0.265**-0.089*0.176**-0.190**-0.087*-0.068
Tab.4  Correlation coefficients between allele size of microsatellites and grains traits
markers1-2 internode lengthpanicle lengthawn lengthfilled grainsper panicleblighted grains per panicletotal grains per panicleseedsetting rategraindensity
RM5-0.251**-0.013-0.055-0.0390.022-0.035-0.013-0.029
RM81A-0.369**0.098*-0.130**0.0050.0450.055-0.0290.010
RM2110.156**-0.0210.041-0.114**0.129**0.019-0.120**0.010
RM2630.298**-0.0450.061-0.0350.088*0.050-0.0350.085*
RM60-0.016-0.0130.019-0.0570.016-0.075-0.047-0.019
RM2320.0170.039-0.020-0.0090.0700.015-0.0610.049
RM241-0.049-0.001-0.025-0.016-0.043-0.0030.042-0.057
RM255-0.262**0.036-0.093*0.029-0.0090.0220.0390.009
RM249-0.0740.0380.009-0.009-0.015-0.0100.054-0.025
RM2250.113**-0.0350.046-0.158**0.133**0.044-0.149**0.006
RM2530.0060.035-0.0390.0220.0450.042-0.0270.036
RM18-0.259**-0.011-0.0360.015-0.066-0.025-0.082*-0.057
RM2340.0520.0200.061-0.0360.0390.043-0.028-0.004
RM2230.094*0.100*0.059-0.0740.088*-0.005-0.110**-0.031
RM257-0.285**0.036-0.111**0.046-0.0420.0600.090*-0.023
RM244-0.293**0.032-0.0550.062-0.0410.0330.0460.023
RM2580.279**0.0030.130**-0.0540.099*-0.072-0.087*0.044
RM2240.438**-0.0570.090*-0.0400.098*0.071-0.0720.086*
RM2350.303**-0.0050.070-0.0800.135**0.055-0.134**0.030
RM247-0.257**0.083*-0.101*0.060-0.0340.0250.056-0.005
Tab.5  Correlation coefficients between allele size of microsatellites and panicle traits
1 Abdelkhalik A F, Shishido R, Nomura K, Ikehashi H (2005). QTL-based analysis of heterosis for grain shape traits and seedling characteristics in an indica-japonica hybrid in rice (Oryza sativa L.). Breeding Science , 55(1): 41-48
doi: 10.1270/jsbbs.55.41
2 Andersen J R, Lübberstedt T (2003). Functional markers in plants. Trends in Plant Science , 8(11): 554-560
doi: 10.1016/j.tplants.2003.09.010
3 Bassam B J, Caetano-Anolles G, Gresshoff P M (1991). Fast and sensitive silver staining of DNA in polyacrylamide gels. Analytical Biochemistry , 196(1):80-83
doi: 10.1016/0003-2697(91)90120-I
4 Chang T T (1976). The origin, evolution, cultivation, dissemination and diversification of Asian and African rices. Euphytica , 25(1): 425-441
doi: 10.1007/BF00041576
5 Cui K H, Peng S B, Ying Y Z, Yu S B, Xu C G (2004). Molecular dissection of the relationships among tiller number, plant height and heading date in rice. Plant Production Science , 7(3): 309-318
doi: 10.1626/pps.7.309
6 Doyle J J, Doyle J L (1990). Isolation of plant DNA from fresh tissue. Focus , 12(1): 13-15
7 Duan Y L, Li W M, Wu W R, Pan R S, Zhou Y C, Qi J M, Lin L H, Chen Z W, Mao D M, Liu H Q, Zhang D F, Xue Y B (2003). Genetic analysis and mapping of gene fzp(t) controlling spikelet differentiation in rice. Science in China (Series C) , 46(4): 328-334
8 Gao L Z, Ge S, Hong D Y, Lin R S, Tao G D, Xu Z F (2002). Allozyme variation and conservation genetics of common wild rice (Oryza rufipogon Griff.) in Yunnan, China. Euphytica , 124(4): 273-281
doi: 10.1023/A:1015740331079
9 Jiang H, Guo L B, Qian Q (2007). Recent progress on rice genetics in China. Journal of Integrative Plant Biology , 49(6): 776-790
doi: 10.1111/j.1744-7909.2007.00492.x
10 Jing R C, Li X M, Yi P, Zhu Y G (2001). Mapping fertility-restoring genes of rice WA cytoplasmic male sterility using SSLP markers. Botanical Bulletin of Academia Sinica , 42(3): 167-171
11 Lawson M J, Zhang L Q (2006). Distinct patterns of SSR distribution in the Arabidopsis thaliana and comment rice genomes. Genome Biology , 7(2): R14
doi: 10.1186/gb-2006-7-2-r14
12 Li Y C, Korol A B, Fahima T, Nevo E (2004). Microsatellites within genes: structure, function and evolution. Molecular Biology and Evolution , 21(6): 991-1007
doi: 10.1093/molbev/msh073
13 Liang F S, Deng Q Y, Wang Y Q, Xiong Y D, Jin D M, Li J M, Wang B (2004). Molecular marker-assisted selection for yield-enhancing genes in the progeny of “9311×O. rufipogon” using SSR. Euphytica , 139(2): 159-165
doi: 10.1007/s10681-004-2560-1
14 Linh L H, Jin F X, Kang K H, Lee Y T, Kwon S J, Ahn S N (2006). Mapping quantitative trait loci for heading date and awn length using an advanced backcross line from a cross between Oryza sativa and O. minuta. Breeding Science , 56(4): 341-349
doi: 10.1270/jsbbs.56.341
15 Ma J F, Tamai K, Yamaji N, Mitani N, Konishi S, Katsuhara M, Murata Y, Yano M, Ishiguro M (2006). A silicon transporter in rice. Nature , 440(30): 688-691
doi: 10.1038/nature04590
16 McCouch S R, Teytelman L, Xu Y, Lobos K B, Clare K, Walton M, Fu B, Maghirang R, Li Z, Xing Y, Zhang Q F, Kono I, Yano M, Fjellstrom R, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L (2002). Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Research , 9(6): 199-207
doi: 10.1093/dnares/9.6.199
17 Miyata M, Yamamoto T, Komori T, Nitta N (2007). Marker-assisted selection and evaluation of the QTL for stigma exsertion under japonica rice genetic background. Theoretical and Applied Genetics , 114(3): 539-548
doi: 10.1007/s00122-006-0454-4
18 Panaud O, Chen X, McCouch S R (1996). Development of microsatellite markers and characterization of simple sequence length polymorphism (SSLP) in rice (Oryza sativa L.). Molecular General Genetics , 252(5): 597-607
19 Pradeep R M, Sarla N, Laminaratana V R, Siddiq E A (2005). Identification and mapping of yield and yield related QTLs from an Indian accession of Oryza rufipogon. BMC genetics , 6: 33
20 Ramakrishna W, Davierwala A P, Gupta V S, Ranjekar P K (1998). Expansion of a (GA) dinucleotide at a microsatellite locus associated with domestication in rice. Biochemical Genetics , 36(9-10): 323-327
doi: 10.1023/A:1018793328896
21 Septiningsih E M, Trijatmiko K R, Moeljopawiro S, McCouch S R (2003). Identification of quantitative trait loci for grain quality in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon. Theoretical and Applied Genetics , 107(8): 1433-1441
doi: 10.1007/s00122-003-1376-z
22 Shen Y J, Jiang H, Jin J P, Zhang Z B, Xi B, He Y Y, Wang G, Wang C, Qian L, Li X, Yu Q B, Liu H J, Chen D H, Gao J H, Huang H, Shi T L, Yang Z N (2004). Development of genome-wide DNA polymorphism database for map-based cloning of rice genes. Plant Physiology , 135(3): 1198-1205
doi: 10.1104/pp.103.038463
23 Tan L B, Liu F X, Xue W, Wang G J, Ye S, Zhu Z F, Fu Y C, Wang X K, Sun C Q (2007). Development of Oryza rufipogon and O. sativa introgression lines and assessment for yield-related quantitative trait loci. Journal of Integrative Plant Biology , 49(6): 871-884
doi: 10.1111/j.1744-7909.2007.00497.x
24 Thomson M J, Tai T H, McClung A M, Lai X H, Hinga M E, Lobos K B, Xu Y, Martinez C P, McCouch S R (2003). Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson. Theoretical and Applied Genetics , 107(3): 479-493
doi: 10.1007/s00122-003-1270-8
25 Xiao J, Grandillo S, Ahn S A, McCouch S R, Tanksley S D, Li J, Yuan L (1996). Genes from wild rice improve yield. Nature , 384: 223-224
doi: 10.1038/384223a0
26 Xu J L, Yu S B, Luo L J, Zhong D B, Mei H W, Li Z K (2004). Molecular dissection of the primary sink size and its related traits in rice. Plant Breeding , 123(1): 43-50
doi: 10.1046/j.1439-0523.2003.00936.x
27 Xue W Y, Xing Y Z, Weng X Y, Zhao Y, Tang W J, Wang L, Zhou H J, Yu S B, Xu C G, Li X H, Zhang Q F (2008). Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nature Genetics , 40: 761-767
doi: 10.1038/ng.143
28 Yoshida S, Ikegami M, Kuze J, Sawada K, Hashimoto Z, Ishii T, Nakamura C, Kamijima O (2002). QTL analysis for plant and grain characters of sake-brewing rice using a doubled haploid population. Breeding Science , 52(4): 309-317
doi: 10.1270/jsbbs.52.309
29 Zeng Y W, Liu J F, Wang L X, Du J, Pu X Y, Yang S M, Zhang H L (2006). Ecogeographic difference and variation pattern of mineral contents for Yunnan rice landraces. Acta Agronomica Sinica , 32(8): 1166-1173
30 Zeng Y W, Shen S Q, Li Z C, Yang Z Y, Wang X K, Zhang H L, Wen G S (2003). Ecogeographic and genetic diversity based on morphological characters of indigenous rice (Oryza sativa L.) in Yunnan, China. Genetic Resources and Crop Evolution , 50(6): 566-577
31 Zeng Y W, Shen S Q, Wang L X, Liu J F, Pu X Y, Du J, Gui M (2005). Correlation of plant morphological and grain quality traits with mineral element contents in Yunnan rice. Rice Science , 12(2): 101-106
32 Zeng Y W, Wang L X, Sun Z H, Yang S M, Du J, Li Q W, Pu X Y, Du W, Xiao F H (2008). Determination of mineral elements of brown rice in near-isogenic lines poputation for japonica rice by ICP-AES. Spectroscopy and Spectral Analysis , 28(12): 2966-2969 (in Chinese)
33 Zeng Y W, Xu F R, Shen S Q, Deng J Y (2000). Correlation of indica-japonica classification and morphological character of Yunnan nuda rice cultivars. Chinese Journal of Rice Science , 14(2): 115-118 (in Chinese)
34 Zeng Y W, Zhang H L, Li Z C, Shen S Q, Sun J L, Wang M X, Liao D Q, Liu X, Wang X K, Xiao F H, Wen G S (2007). Evaluation of genetic diversity in the rice landraces (Oryza sativa L.) in Yunnan, China. Breeding Science , 57(2): 91-99
doi: 10.1270/jsbbs.57.91
35 Zhang H L, Sun J L, Wang M X, Liao D Q, Zeng Y W, Shen S Q, Yu P, Mu P, Wang X K, Li Z C (2006). Genetic structure and phylogeography of rice landraces in Yunnan, China, revealed by SSR. Genome , 50(1): 72-83
doi: 10.1139/G06-130
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