Association mapping of yield and its components in rice cultivars

被引:291
作者
Agrama, H. A. [1 ]
Eizenga, G. C.
Yan, W.
机构
[1] Univ Arkansas, Rice Res & Extens Ctr, Stuttgart, AR 72160 USA
[2] US Dept Agr, Dale Bumpers Natl Rice Res Ctr, Agr Res Serv, Stuttgart, AR 72160 USA
关键词
linkage disequilibrium; unified mixed-model method; population structure; kinship coefficient; relatedness;
D O I
10.1007/s11032-006-9066-6
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
To make advances in rice breeding it is important to understand the relatedness and ancestry of introduced rice accessions, and identify SSR markers associated with agronomically important phenotypic traits, for example yield. Ninety-two rice germplasm accessions recently introduced from seven geographic regions of Africa, Asia, and Latin America, and eleven US cultivars, included as checks, were evaluated for yield and kernel characteristics, and genotyped with 123 SSR markers. The SSR markers were highly polymorphic across all accessions. Population structure analysis identified eight main clusters for the accessions which corresponded to the major geographic regions, indicating agreement between genetic and predefined populations. Linkage disequilibrium (LD) patterns and distributions are of fundamental importance for genome-wide mapping association. LD between linked markers decreased with distance and with a substantial drop in LD decay values between 20 and 30 cM, suggesting it should be possible to achieve resolution down to the 25 cM level. For the 103 cultivars, the complex traits yield, kernel width, kernel length, kernel width/length ratio, and 1000-kernel weight, were estimated by analysis of variety trial data. The mixed linear model method was used to disclose marker-trait associations. Many of the associated markers were located in regions where QTL had previously been identified. In conclusion, association mapping in rice is a viable alternative to QTL mapping based on crosses between different lines.
引用
收藏
页码:341 / 356
页数:16
相关论文
共 82 条
  • [11] EAVES IA, 1998, AM J HUM GEN A, V221
  • [12] Identifying novel resistance genes in newly introduced blast resistant rice germplasm
    Eizenga, G. C.
    Agrama, H. A.
    Lee, F. N.
    Yan, W.
    Jia, Y.
    [J]. CROP SCIENCE, 2006, 46 (05) : 1870 - 1878
  • [13] ESTOUP A, 1995, MOL BIOL EVOL, V12, P1074
  • [14] Arlequin (version 3.0): An integrated software package for population genetics data analysis
    Excoffier, Laurent
    Laval, Guillaume
    Schneider, Stefan
    [J]. EVOLUTIONARY BIOINFORMATICS, 2005, 1 : 47 - 50
  • [15] Falush D, 2003, GENETICS, V164, P1567
  • [16] Extensive genome-wide linkage disequilibrium in cattle
    Farnir, F
    Coppieters, W
    Arranz, JJ
    Berzi, P
    Cambisano, N
    Grisart, B
    Karim, L
    Marcq, F
    Moreau, L
    Mni, M
    Nezer, C
    Simon, P
    Vanmanshoven, P
    Wagenaar, D
    Georges, M
    [J]. GENOME RESEARCH, 2000, 10 (02) : 220 - 227
  • [17] Development of DNA markers suitable for marker assisted selection of three Pi genes conferring resistance to multiple Pyricularia grisea pathotypes
    Fjellstrom, R
    Conaway-Bormans, CA
    McClung, AM
    Marchetti, MA
    Shank, AR
    Park, WD
    [J]. CROP SCIENCE, 2004, 44 (05) : 1790 - 1798
  • [18] Maize association population: a high-resolution platform for quantitative trait locus dissection
    Flint-Garcia, SA
    Thuillet, AC
    Yu, JM
    Pressoir, G
    Romero, SM
    Mitchell, SE
    Doebley, J
    Kresovich, S
    Goodman, MM
    Buckler, ES
    [J]. PLANT JOURNAL, 2005, 44 (06) : 1054 - 1064
  • [19] Race, ethnicity, and genomics: Social classifications as proxies of biological heterogeneity
    Foster, MW
    Sharp, RR
    [J]. GENOME RESEARCH, 2002, 12 (06) : 844 - 850
  • [20] Low levels of genetic diversity within populations and high differentiation among populations of a wild rice, Oryza granulata Nees et Arn. ex Watt., from China
    Gao, LZ
    Ge, S
    Hong, DY
    [J]. INTERNATIONAL JOURNAL OF PLANT SCIENCES, 2000, 161 (04) : 691 - 697