Abstract
BackgroundIdentification of QTL with large phenotypic effects conserved across genetic backgrounds and environments is one of the prerequisites for crop improvement using marker assisted selection (MAS). The objectives of this study were to identify meta-QTL (mQTL) for grain yield (GY) and anthesis silking interval (ASI) across 18 bi-parental maize populations evaluated in the same conditions across 2-4 managed water stressed and 3-4 well watered environments.ResultsThe meta-analyses identified 68 mQTL (9 QTL specific to ASI, 15 specific to GY, and 44 for both GY and ASI). Mean phenotypic variance explained by each mQTL varied from 1.2 to 13.1% and the overall average was 6.5%. Few QTL were detected under both environmental treatments and/or multiple (>4 populations) genetic backgrounds. The number and 95% genetic and physical confidence intervals of the mQTL were highly reduced compared to the QTL identified in the original studies. Each physical interval of the mQTL consisted of 5 to 926 candidate genes.ConclusionsMeta-analyses reduced the number of QTL by 68% and narrowed the confidence intervals up to 12-fold. At least the 4 mQTL (mQTL2.2, mQTL6.1, mQTL7.5 and mQTL9.2) associated with GY under both water-stressed and well-watered environments and detected up to 6 populations may be considered for fine mapping and validation to confirm effects in different genetic backgrounds and pyramid them into new drought resistant breeding lines. This is the first extensive report on meta-analysis of data from over 3100 individuals genotyped using the same SNP platform and evaluated in the same conditions across a wide range of managed water-stressed and well-watered environments.
Highlights
Identification of QTL with large phenotypic effects conserved across genetic backgrounds and environments is one of the prerequisites for crop improvement using marker assisted selection (MAS)
In the dataset used for QTL mapping, broad sense heritability for grain yield (GY) and anthesis silking interval (ASI) varied from 0.13 to 0.40 under water stressed and from 0.21 to 0.58 under optimum conditions
Our study clearly demonstrated four times as many mQTL expressed under optimum conditions than under stressed environments
Summary
Identification of QTL with large phenotypic effects conserved across genetic backgrounds and environments is one of the prerequisites for crop improvement using marker assisted selection (MAS). Maize is a staple food in many of the SSA countries and is commonly grown by resource poor, small-scale farmers in rural areas. It covers drought stress without significant yield penalty under optimal rainfall conditions [3,4,5]. Physiologists and breeders have devoted significant efforts in identifying relevant secondary traits correlated to grain yield for indirect selection. These include anthesis silking interval (ASI) between male and female flowering and several other morpho-physiological traits [8,9]
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