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Multienvironment Quantitative Trait Loci Mapping and Consistency across Environments of Resistance Mechanisms to Ferrous Iron Toxicity in Rice
Author(s) -
Dufey I.,
Hiel M.P.,
Hakizimana P.,
Draye X.,
Lutts S.,
Koné B.,
Dramé K.N.,
Konaté K.A.,
Sie M.,
Bertin P.
Publication year - 2012
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2009.09.0544
Subject(s) - quantitative trait locus , biology , genetics , population , oryza sativa , trait , family based qtl mapping , gene , gene mapping , demography , sociology , computer science , chromosome , programming language
Lowland rice ( Oryza sativa L.) is often affected by iron toxicity, which may lead to yield losses. One important constraint in the study of the inheritance of resistance strategies to this stress is the inconsistency of gene expression across different environments. This study aimed to determine the stability of quantitative trait loci (QTL) across several environments. Quantitative trait loci mapping for traits related to resistance mechanisms had been previously performed using 164 recombinant inbred lines derived from ‘Azucena’ and ‘IR64’ screened in hydroponics in a phytotron. In the present study, this population was tested under excessive ferrous iron conditions in three additional environments: in hydroponics in a greenhouse, on washed sand, and in the field. Altogether, 44 putative QTL were identified in the four single QTL analyses for morphological, physiological, and agronomic traits. From these 44 QTL, 20 were found in overlapping regions for the same or related traits in different environments, identifying six genomic regions of great interest for the inheritance of resistance to iron toxicity. Quantitative trait loci stability across environments was also checked by performing a joint QTL analysis, which confirmed the position of nine QTL previously found in the same or adjacent regions by at least one single analysis. Combining both single and joint analyses helps in separating QTL specific to a particular environment from generally expressed ones thus is more suitable for marker‐assisted selection.