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Quantitative Trait Loci for Grain Yield in Pearl Millet under Variable Postflowering Moisture Conditions
Author(s) -
Bidinger F. R.,
Nepolean T.,
Hash C. T.,
Yadav R. S.,
Howarth C. J.
Publication year - 2007
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/cropsci2006.07.0465
Subject(s) - quantitative trait locus , biology , moisture stress , agronomy , trait , software maintainer , population , grain yield , moisture , drought tolerance , gene–environment interaction , yield (engineering) , adaptation (eye) , genetics , genotype , gene , materials science , neuroscience , demography , sociology , computer science , metallurgy , composite material , programming language
Pearl millet marker‐assisted selection (MAS) programs targeting adaptation to variable postflowering moisture environments would benefit from quantitative trait loci (QTLs) that improve grain yield across the full range of postflowering moisture conditions, rather than just in drought‐stressed environments. This research was undertaken to identify such QTLs from an extensive (12‐environment) phenotyping data set that included both stressed and unstressed postflowering environments. Genetic materials were test crosses of 79 F 2 –derived F 4 progenies from a mapping population based on a widely adapted maintainer line (ICMB 841) × a postflowering drought‐tolerant maintainer (863B). Three QTLs (on linkage group [LG] 2, LG 3, and LG 4) were identified as primary candidates for MAS for improved grain yield across variable postflowering moisture environments. The QTLs on LG 2 and LG 3 (the most promising) explained a useful proportion (13–25%) of phenotypic variance for grain yield across environments. They also co‐mapped with QTLs for harvest index across environments, and with QTLs for both grain number and individual grain mass under severe terminal stress. Neither had a significant QTL × environment interaction, indicating that their predicted effects should occur across a broad range of available moisture environments. We have estimated the benefits in grain yield and accompanying changes in yield components and partitioning indices that would be expected as a result of incorporating these QTLs into other genetic backgrounds by MAS.