The identification of genes underlying complex quantitative traits such as grain yield by means of conventional genetic analysis (positional cloning) requires the development of several large mapping populations. However, it is possible that phenotypically related, but more extreme, allelic variants generated by mutational studies could provide a means for more efficient cloning of QTLs (quantitative trait loci). In barley (Hordeum vulgare), with the development of high-throughput genome analysis tools, efficient genome-wide identification of genetic loci harbouring mutant alleles has recently become possible. Genotypic data from NILs (near-isogenic lines) that carry induced or natural variants of genes that control aspects of plant development can be compared with the location of QTLs to potentially identify candidate genes for development-related traits such as grain yield. As yield itself can be divided into a number of allometric component traits such as tillers per plant, kernels per spike and kernel size, mutant alleles that both affect these traits and are located within the confidence intervals for major yield QTLs may represent extreme variants of the underlying genes. In addition, the development of detailed comparative genomic models based on the alignment of a high-density barley gene map with the rice and sorghum physical maps, has enabled an informed prioritization of ‘known function’ genes as candidates for both QTLs and induced mutant genes.
Exploiting induced variation to dissect quantitative traits in barley
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Arnis Druka, Jerome Franckowiak, Udda Lundqvist, Nicola Bonar, Jill Alexander, Justyna Guzy-Wrobelska, Luke Ramsay, Ilze Druka, Iain Grant, Malcolm Macaulay, Vera Vendramin, Fahimeh Shahinnia, Slobodanka Radovic, Kelly Houston, David Harrap, Linda Cardle, David Marshall, Michele Morgante, Nils Stein, Robbie Waugh; Exploiting induced variation to dissect quantitative traits in barley. Biochem Soc Trans 1 April 2010; 38 (2): 683–688. doi: https://doi.org/10.1042/BST0380683
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