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In such a situation, one may cluster traits and analyze the clustered traits, using a multitrait approach (Chun and Keles 2009).
These results highlight the major influence of INDEL Ins883 in the possible role of VvTFL1A on phenology and cluster traits.
Moreover, how to cluster traits and to determine the number of clusters will have an impact on results.
Herein the identification of VvTFL1A sequence polymorphisms associated with flowering and cluster traits is reported, being the most relevant ones corresponding to several INDELs in two intron regions.
Nucleotide polymorphisms in VvTFL1A LD blocks that discriminate the three haplogroups displayed differential association with cluster traits under linear regression models.
Genetic association studies with cluster traits revealed the presence of major INDEL polymorphisms, explaining 16%, 13%and25%5% of flowering time, cluster width and berry weight, respectively, and also structuring the three haplogroups.
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Regarding the 17 polymorphisms found in intron regions, two INDEL (Ins422 and Ins883) showed significant association with flowering and cluster trait variation.
Clustering traits by their association with modules separated alpha diversity from the other variables.
Multiple-trait analysis of the clustered traits tended to work better than single-trait analysis of the principal component variables but seemed to be a compromise between single-trait analysis and multitrait analysis of all 16 traits.
In terms of statistical power for the e-trait data, analysis of clustered traits seemed to be somewhere between single-trait analysis and multitrait analysis of all the traits.
We analyzed clustered traits separately (CL), with clusters being defined by hierarchical clustering based on the correlations between the e-traits and by a cutoff of 0.75 (section 7 in File S1).
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