QTL-based analysis of genotype-by-environment interaction for grain yield of rice in stress and non-stress environments

被引:16
作者
Manneh, Baboucarr
Stam, Piet
Struik, Paul C.
Bruce-Oliver, Samuel
van Eeuwijk, Fred A.
机构
[1] Africa Rice Ctr, Biotechnol Unit, WARDA, ADRAO, Cotonou, Benin
[2] Univ Wageningen & Res Ctr, Lab Plant Breeding, Dept Plant Sci, NL-6700 AJ Wageningen, Netherlands
[3] Univ Wageningen & Res Ctr, Crop & Weed Ecol Grp, Dept Plant Sci, NL-6700 AK Wageningen, Netherlands
[4] Univ Wageningen & Res Ctr, Biometris Dept PlantSci, NL-6700 AC Wageningen, Netherlands
关键词
genotype-by-environment interaction; marker-assisted selection; Oryza sativa L; QTL; rice;
D O I
10.1007/s10681-007-9368-8
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Use of DNA-based markers can accelerate cultivar development in variable cultivation environments since, in contrast to phenotype, DNA markers are environment-independent. In an effort to elucidate the genetic basis of genotype-by-environment interaction (G x E) for yield of rice (Oryza sativa L.), the associations between 139 AFLP markers and grain yield were determined for rice grown in fresh water (EC of 0.65 dS m(-1) and saline conditions (EC of 4-8 dS m(-1)) with 0 kg ha(-1) or 100 kg ha(-1) nitrogen fertilizer in the years 2000 and 2001. A population of recombinant inbred lines of rice, developed from an IR29 x Pokkali cross, was used in the study. Both genotype x salinity and genotype x nitrogen level interactions were significant, with the genotype x salinity interaction being stronger. Through multiple regression analysis using a stepwise procedure for selecting markers, 36 markers were detected for grain yield in the four test conditions and of these 28 were detected in only one test condition implying strong environmental specificity for yield QTL expression. However, the fact that eight QTLs were detected in more than one test condition points to the existence of wide-adaptability genes in this cross. Markers with significant associations with yield explained between 37% and 48% of the yield variation in each test condition. Superior genotypes of rice were identified in all four test conditions based on their marker signatures. Furthermore, across N fertilizer regimes, yield predicted from summed additive effects of QTLs were significantly correlated with observed yield in the same year and across years. Thus marker-assisted selection can help breeders overcome the problem of low selection efficiency encountered during phenotypic selection for yield in stress environments.
引用
收藏
页码:213 / 226
页数:14
相关论文
共 31 条
[1]  
[Anonymous], 1982, Introduction to Linear Regression Analysis
[2]   THE SEMIDWARF GENE, SD-1, OF RICE (ORYZA-SATIVA L) .2. MOLECULAR MAPPING AND MARKER-ASSISTED SELECTION [J].
CHO, YG ;
EUN, MY ;
MCCOUCH, SR ;
CHAE, YA .
THEORETICAL AND APPLIED GENETICS, 1994, 89 (01) :54-59
[3]   THE EFFECTS OF SELECTION FOR SODIUM-TRANSPORT AND OF SELECTION FOR AGRONOMIC CHARACTERISTICS UPON SALT RESISTANCE IN RICE (ORYZA-SATIVA L) [J].
GARCIA, A ;
SENADHIRA, D ;
FLOWERS, TJ ;
YEO, AR .
THEORETICAL AND APPLIED GENETICS, 1995, 90 (7-8) :1106-1111
[4]  
*GENSTAT 6 1, 2002, GENST 6 REL 1
[5]  
Gomez K.A., 1984, Statistical Procedures for Agricultural Research
[6]  
Gregorio G.B., 1997, Tagging salinity tolerance gene in rice (Oryza sativa) using amplified fragment length polymorphism (AFLP)
[7]  
HAANSTRA JPW, 2000, THESIS WAGENINGEN AG
[8]   Comparison of molecular linkage maps and agronomic trait loci between DH and RIL populations derived from the same rice cross [J].
He, P ;
Li, JZ ;
Zheng, XW ;
Shen, LS ;
Lu, CF ;
Chen, Y ;
Zhu, LH .
CROP SCIENCE, 2001, 41 (04) :1240-1246
[9]   Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia [J].
Hittalmani, S ;
Huang, N ;
Courtois, B ;
Venuprasad, R ;
Shashidhar, HE ;
Zhuang, JY ;
Zheng, KL ;
Liu, GF ;
Wang, GC ;
Sidhu, JS ;
Srivantaneeyakul, S ;
Singh, VP ;
Bagali, PG ;
Prasanna, HC ;
McLaren, G ;
Khush, GS .
THEORETICAL AND APPLIED GENETICS, 2003, 107 (04) :679-690
[10]  
IRRI, 1996, STAND EV SYST RIC