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Chapter 3. Multi-trait multi-environment QTL modelling for drought-stress adaptation in maize

By: Contributor(s): Material type: ArticleArticleLanguage: English Series: Wageningen UR Frontis Series ; No. 21Publication details: Dordrecht (Netherlands) : Springer, 2007.ISBN:
  • 978-1-4020-5904-9
  • 978-1-4020-5906-3 (Online)
Subject(s): In: Scale and complexity in plant systems research: gene-plant-crop relations p. 25-36Summary: Water shortage is a major cause of yield loss in maize. Thus, breeding for adaptation to waterstressed environments is an important task for breeders. The use of quantitative-trait loci (QTL) models in which the response of complex phenotypes under stressed environments is described in direct relation to molecular information can improve the understanding of the genetic causes underlying stress tolerance. Mixed QTL models are particularly useful for this type of modelling, especially when the data stem from multi-environment evaluations including stressed and non-stressed conditions. The study of complex phenotypic traits such as yield under water-limited conditions can benefit from the analysis of trait components (e.g., yield components) that can be exploited in indirect selection. Multi-trait multi-environment QTL models help to identify the genome regions responsible for genetic correlations, whether caused by pleiotropy or genetic linkage, and can show how genetic correlations depend on the environmental conditions. With the objective of identifying QTLs for adaptation to drought stress, we present the results of a multi-trait multi-environment QTL-modelling approach using data from the CIMMYT maize-breeding programme.
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Water shortage is a major cause of yield loss in maize. Thus, breeding for adaptation to waterstressed environments is an important task for breeders. The use of quantitative-trait loci (QTL) models in which the response of complex phenotypes under stressed environments is described in direct relation to molecular information can improve the understanding of the genetic causes underlying stress tolerance. Mixed QTL models are particularly useful for this type of modelling, especially when the data stem from multi-environment evaluations including stressed and non-stressed conditions. The study of complex phenotypic traits such as yield under water-limited conditions can benefit from the analysis of trait components (e.g., yield components) that can be exploited in indirect selection. Multi-trait multi-environment QTL models help to identify the genome regions responsible for genetic correlations, whether caused by pleiotropy or genetic linkage, and can show how genetic correlations depend on the environmental conditions. With the objective of identifying QTLs for adaptation to drought stress, we present the results of a multi-trait multi-environment QTL-modelling approach using data from the CIMMYT maize-breeding programme.

Generation Challenge Program|Genetic Resources Program

Text in English

INT1991|CCJL01

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