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Shade Avoidance Components and Pathways in Adult Plants Revealed by Phenotypic Profiling


Because plants depend on light for photosynthesis, neighboring plant shade can be detrimental to survival. Many plants sense and respond to neighbor shade to compete for light. Although shade causes responses throughout the plant (collectively known as the shade avoidance syndrome or SAS), most SAS studies have been limited to single-gene analyses in seedlings. Here we move beyond these analyses by taking a multi-gene, multi-trait study of SAS across developmental stages. Recently, whole-genome studies examining large mutant collections have been exploited to determine the pathways and their interactions that combine to determine complex phenotypes. This type of analysis (phenotypic profiling) typically uses thousands of mutants and robotic phenotyping for assaying many characters in the multitude of mutant lines. In this paper, we develop a directed alternative that allows us to take a similar approach to understanding SAS. To reduce the number of mutants required for such an approach, we used a logical selection procedure to define mutants of interest by over-representation analysis of shade-responsive genes. We found at least three different subgroups of shade responses, and that each subgroup had both shared and separate pathways. Also, we found eighteen novel genes involved in SAS. Therefore, our method is useful for multi-dimensional phenotypic profiling without expensive robots.


Vyšlo v časopise: Shade Avoidance Components and Pathways in Adult Plants Revealed by Phenotypic Profiling. PLoS Genet 11(4): e32767. doi:10.1371/journal.pgen.1004953
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004953

Souhrn

Because plants depend on light for photosynthesis, neighboring plant shade can be detrimental to survival. Many plants sense and respond to neighbor shade to compete for light. Although shade causes responses throughout the plant (collectively known as the shade avoidance syndrome or SAS), most SAS studies have been limited to single-gene analyses in seedlings. Here we move beyond these analyses by taking a multi-gene, multi-trait study of SAS across developmental stages. Recently, whole-genome studies examining large mutant collections have been exploited to determine the pathways and their interactions that combine to determine complex phenotypes. This type of analysis (phenotypic profiling) typically uses thousands of mutants and robotic phenotyping for assaying many characters in the multitude of mutant lines. In this paper, we develop a directed alternative that allows us to take a similar approach to understanding SAS. To reduce the number of mutants required for such an approach, we used a logical selection procedure to define mutants of interest by over-representation analysis of shade-responsive genes. We found at least three different subgroups of shade responses, and that each subgroup had both shared and separate pathways. Also, we found eighteen novel genes involved in SAS. Therefore, our method is useful for multi-dimensional phenotypic profiling without expensive robots.


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