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Morphobiological indicators and selection index are helpful tools to obtain promising genotypes and selecting multiple traits for genetic improvement of the predator, Cryptolaemus montrouzieri (Mulsant) (Coleoptera: Coccinellidae).
Many potentially novel QTLs were also identified which could be of great value for further elucidating the molecular genetic control of the traits investigated, as well as to provide recombined lines with multiple traits for breeding programs.
A recent study by Studer and Doebley (2011) detailed the dissection of a single QTL in maize that had demonstrated phenotypic effects on multiple traits for plant architecture and ear morphology, and also contained a 12 kb regulatory region for the teosinte branched1 (tb1) gene.
This mapping population was chosen for the first map due to the diverse genetic backgrounds of the parents: one is a small red lentil and the other a large green lentil and the population segregates for multiple traits for which this map will be used in the future to elucidate genetic control of these traits.
Many of the most recent models have expanded this further by focusing on the evolution of multiple traits (for example growth, PMRNs, and reproductive investment and on less studied traits such as migration (Jørgensen et al. 2008a; Thériault et al. 2008; Miethe et al. 2009) and sex allocation in hermaphrodites (Sattar et al. 2006).
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The variety of visible phenotypes observed in the mutant population is a good indicator of the depth of the genetic lesions, strongly suggesting that the mutant population is altered for multiple traits of agronomic importance.
They will also enable marker-assisted selection for multiple traits or for specific genome regions.
Currently, the single-step method can be more readily applied to multiple traits, especially for traits with low heritability and reliability.
Most of the significant markers were identified for multiple traits with different genotypic effects; for example, PtoCesA4_1914 is associated with seven traits, and PtoGA20ox_632 with six (Supplementary Table S9).
This QTL is added to the model as a random effect for multiple traits or two random effects for multiple environments; a main effect is added in the multienvironment situation to allow for a possible common set of QTL sizes.
This can occur if the same genes influence multiple traits, if genes for different traits are closely linked on chromosomes, or if environmental effects (e.g., temperature or diet) simultaneously influence multiple traits.
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