Literature DB >> 17660575

Association of candidate genes with flowering time and water-soluble carbohydrate content in Lolium perenne (L.).

Leif Skøt1, Jan Humphreys, Mervyn O Humphreys, Danny Thorogood, Joe Gallagher, Ruth Sanderson, Ian P Armstead, Ian D Thomas.   

Abstract

We describe a candidate gene approach for associating SNPs with variation in flowering time and water-soluble carbohydrate (WSC) content and other quality traits in the temperate forage grass species Lolium perenne. Three analysis methods were used, which took the significant population structure into account. First, a linear mixed model was used enabling a structured association analysis to be incorporated with the nine populations identified in the structure analysis as random variables. Second, a within-population analysis of variance was performed. Third, a tree-scanning method was used, in which haplotype trees were associated with phenotypes on the basis of inferred haplotypes. Analysis of variance within populations identified several associations between WSC, nitrogen (N), and dry matter digestibility with allelic variants within an alkaline invertase candidate gene LpcAI. These associations were only detected in material harvested in one of the two years. By contrast, consistent associations between the L. perenne homolog (LpHD1) of the rice photoperiod control gene HD1 and flowering time were identified. One SNP, in the immediate upstream region of the LpHD1 coding sequence (C-4443-A), was significant in the linear mixed model. Within-population analysis of variance and tree-scanning analysis confirmed and extended this result to the 2118 polymorphisms in some of the populations. The merits of the tree-scanning method are compared to the single SNP analysis. The potential usefulness of the 4443 SNP in marker-assisted selection is currently being evaluated in test crosses of genotypes from this work with turf-grass varieties.

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Year:  2007        PMID: 17660575      PMCID: PMC2013705          DOI: 10.1534/genetics.107.071522

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


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