Identification of QTLs for some agronomic traits in rice using an introgression line from Oryza minuta.
Wild progenitor species provide potential gene sources for complex traits such as yield and multiple resistances to biotic and abiotic stresses, and thus are expected to contribute to sustainable food supplies. An introgression line 'IR71033-121-15' was derived from a wild species Oryza minuta (2n = 48, BBCC, Acc No. 101141) at IRRI. Introgression analysis using 530 SSR and STS markers revealed that at least 14 chromosomal segments distributed over 12 chromosomes had been introgressed from O. minuta. An F2:3 population from the cross between IR71033 and Junambyeo (a Korean japonica cultivar) consisting of 146 lines was used for quantitative trait loci (QTL) analysis of 16 agronomic traits. A total of 36 single-locus QTLs (S-QTLs) and 45 digenic epistasis (E-QTLs) were identified. In spite of it's inferiority of O. minuta for most of the traits studied, its alleles contributed positively to 57% of the QTLs. The other QTLs originated from either parent, IR71033 or Junambyeo. QTLs for phenotypically correlated traits were mostly detected on introgressed segments. Fourteen QTLs corresponded to QTLs reported earlier, indicating that these QTLs are stable across genetic backgrounds. Twenty-two QTLs controlling yield and its components had not been detected in previous QTL studies. Of these, thirteen consisted of potentially novel alleles from O. minuta. QTLs from O. minuta introgression could be new sources of natural variation for the genetic improvement of rice.
Rahman
Md Lutfor
ML
Department of Plant Science and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 151-921, Korea.
Chu
Sang Ho
SH
Choi
Min-Sun
MS
Qiao
Yong Li
YL
Jiang
Wenzhu
W
Piao
Rihua
R
Khanam
Sakina
S
Cho
Young-Il
YI
Jeung
Ji-Ung
JU
Jena
Kshirod
K
Koh
Hee-Jong
HJ
D003433:Crosses, Genetic; D004843:Epistasis, Genetic; D008040:Genetic Linkage; D012275:Oryza / Q000235:genetics* / Q000254:growth & development; D040641:Quantitative Trait Loci