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Abiotic stress strongly affects yield-related traits in durum wheat. In particular drought is one of the main environmental factors reducing grain yield. Hundreds of quantitative trait loci (QTL) have been identified for yield-related traits across different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for QTL detected in individual studies. MQTL analysis makes it possible to dissect the genetic architecture of complex traits, provide a higher mapping resolution and allow the identification of…mehr

Produktbeschreibung
Abiotic stress strongly affects yield-related traits in durum wheat. In particular drought is one of the main environmental factors reducing grain yield. Hundreds of quantitative trait loci (QTL) have been identified for yield-related traits across different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for QTL detected in individual studies. MQTL analysis makes it possible to dissect the genetic architecture of complex traits, provide a higher mapping resolution and allow the identification of putative molecular markers useful for marker assisted selection (MAS). This chapter provides an overview of the use of MQTL analysis in identification of genomic regions associated with grain-yield related traits in durum wheat under different water regimes.


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Autorenporträt
Ilaria Marcotuli and Agata Gadaleta, University of Bari Aldo Moro, Italy; Osvin Arriagada, Samantha Reveco and Andrés R. Schwember, Pontificia Universidad Católica de Chile, Chile; Marco Maccaferri, Matteo Campana and Roberto Tuberosa, University of Bologna, Italy; Christian Alfaro, Instituto de Investigaciones Agropecuarias (INIA), Chile; and Iván Matus, Instituto de Investigaciones Agropecuarias (INIA), Chile