Literature DB >> 16009935

Evolution through genetically controlled allometry space.

Nicolas B Langlade1, Xianzhong Feng, Tracy Dransfield, Lucy Copsey, Andrew I Hanna, Christophe Thébaud, Andrew Bangham, Andrew Hudson, Enrico Coen.   

Abstract

Understanding evolutionary change requires phenotypic differences between organisms to be placed in a genetic context. However, there are few cases where it has been possible to define an appropriate genotypic space for a range of species. Here we address this problem by defining a genetically controlled space that captures variation in shape and size between closely related species of Antirrhinum. The axes of the space are based on an allometric model of leaves from an F2 of an interspecific cross between Antirrhinum majus and Antirrhinum charidemi. Three principal components were found to capture most of the genetic variation in shape and size, allowing a three-dimensional allometric space to be defined. The contribution of individual genetic loci was determined from QTL analysis, allowing each locus to be represented as a vector in the allometric space. Leaf shapes and sizes of 18 different Antirrhinum taxa, encompassing a broad range of leaf morphologies, could be accurately represented as clouds within the space. Most taxa overlapped with, or were near to, at least one other species in the space, so that together they defined a largely interconnected domain of viable forms. It is likely that the pattern of evolution within this domain reflects a combination of directional selection and evolutionary tradeoffs within a high dimensional space.

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Year:  2005        PMID: 16009935      PMCID: PMC1177394          DOI: 10.1073/pnas.0504210102

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  21 in total

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Journal:  Plant Cell       Date:  2004-05-06       Impact factor: 11.277

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  53 in total

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3.  Climate and Developmental Plasticity: Interannual Variability in Grapevine Leaf Morphology.

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Journal:  Plant Physiol       Date:  2016-01-29       Impact factor: 8.340

4.  Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

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7.  Effects of genetic and environmental factors on trait network predictions from quantitative trait locus data.

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8.  A modern ampelography: a genetic basis for leaf shape and venation patterning in grape.

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9.  Evolution of allometry in antirrhinum.

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