Network analysis identifies ELF3 as a QTL for the shade avoidance response in Arabidopsis
| Autor: | Julin N. Maloof, José M. Jiménez-Gómez, Andreah D. Wallace |
|---|---|
| Přispěvatelé: | Maloof, Julin N, University of California Davis - Department of Plant Biology, University of California, Mendel Biotechnology, Inc., Partenaires INRAE, National Science Foundation (DBI-0227103, DBI-0820854), Mauricio, Rodney |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
0106 biological sciences
Cancer Research Candidate gene Time Factors Gene regulatory network Arabidopsis Candidate Gene Identification 01 natural sciences Genetics and Genomics/Plant Genetics and Gene Expression Family-based QTL mapping ELF3 QTL shade avoidance response Gene Regulatory Networks Inbreeding Genetics (clinical) Genetics 0303 health sciences education.field_of_study qtl food and beverages Physical Chromosome Mapping Adaptation Physiological Circadian Rhythm Phenotype Biotechnology Autre (Sciences du Vivant) Research Article [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] lcsh:QH426-470 Physiological Population Quantitative Trait Loci Crosses Quantitative trait locus Biology Genetics and Genomics/Complex Traits 03 medical and health sciences Shade avoidance Genetic Adaptation Genetics and Genomics/Genomics education Molecular Biology Ecology Evolution Behavior and Systematics Crosses Genetic 030304 developmental biology Arabidopsis Proteins Human Genome Genetic Complementation Test Reproducibility of Results 15. Life on land lcsh:Genetics Developmental Biology/Plant Growth and Development Expression quantitative trait loci Developmental Biology 010606 plant biology & botany Transcription Factors |
| Zdroj: | PLoS Genetics, Vol 6, Iss 9, p e1001100 (2010) PLoS Genetics Plos Genetics 9 (6), 1-13. (2010) PLoS genetics, vol 6, iss 9 PLoS Genetics, Public Library of Science, 2010, 6 (9), pp.1-13. ⟨10.1371/journal.pgen.1001100⟩ |
| ISSN: | 1553-7404 1553-7390 |
| Popis: | Quantitative Trait Loci (QTL) analyses in immortal populations are a powerful method for exploring the genetic mechanisms that control interactions of organisms with their environment. However, QTL analyses frequently do not culminate in the identification of a causal gene due to the large chromosomal regions often underlying QTLs. A reasonable approach to inform the process of causal gene identification is to incorporate additional genome-wide information, which is becoming increasingly accessible. In this work, we perform QTL analysis of the shade avoidance response in the Bayreuth-0 (Bay-0, CS954) x Shahdara (Sha, CS929) recombinant inbred line population of Arabidopsis. We take advantage of the complex pleiotropic nature of this trait to perform network analysis using co-expression, eQTL and functional classification from publicly available datasets to help us find good candidate genes for our strongest QTL, SAR2. This novel network analysis detected EARLY FLOWERING 3 (ELF3; AT2G25930) as the most likely candidate gene affecting the shade avoidance response in our population. Further genetic and transgenic experiments confirmed ELF3 as the causative gene for SAR2. The Bay-0 and Sha alleles of ELF3 differentially regulate developmental time and circadian clock period length in Arabidopsis, and the extent of this regulation is dependent on the light environment. This is the first time that ELF3 has been implicated in the shade avoidance response and that different natural alleles of this gene are shown to have phenotypic effects. In summary, we show that development of networks to inform candidate gene identification for QTLs is a promising technique that can significantly accelerate the process of QTL cloning. Author Summary A major interest in evolutionary biology is to understand the genetic mechanisms that underlie phenotypic variation in nature and how they interact with the environment. A good example of adaptive genetic variation in response to the environment is the shade avoidance response. Although some plant groups try to outgrow their competitors when shade cues are detected others do not, as they are adapted to live in constitutive shade, such as a forest canopy. We used a segregating population derived from two Arabidopsis ecotypes to investigate this variation and found a chromosomal region affecting the shade avoidance response. We developed a network analysis method that combines genomic information from publicly available databases to identify the causative gene in that interval as ELF3. Using genetic and transgenic methods we confirmed the effect of ELF3 in the shade avoidance response, and showed that different alleles of this gene in natural populations of Arabidopsis result in different developmental times and circadian periodicity depending on the environmental conditions. |
| Databáze: | OpenAIRE |
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