| 项目编号: | 1542534
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| 项目名称: | Dimensions: Landscape Genomics of an Adaptive Radiation using Ultra-High Resolution Genetic, Morphometric, and Spatial Analysis |
| 作者: | Ian Wang
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| 承担单位: | University of California-Berkeley
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| 批准年: | 2016
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| 开始日期: | 2016-06-15
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| 结束日期: | 2021-05-31
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| 资助金额: | 1486078
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Biological Sciences - Environmental Biology
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| 英文关键词: | species
; adaptive radiation
; project
; researcher
; geospatial analysis
; anolis lizard
; evolution
; environment
; phylogenetic dimension
; functional dimension
; genetic datum
; genetic basis
; parallel genetic divergence
; genetic dimension
; genetic dataset
|
| 英文摘要: | During adaptive radiation, a group of organisms diversifies into a variety of forms specialized for different environments or ecological roles. Anolis lizards (anoles) on the Greater Antillean islands in the Caribbean have undergone repeated adaptive evolution, resulting in the formation of different species on different islands that have evolved similar traits for occupying similar parts of the forest habitat. This is a remarkable case of convergent evolution, in which separate species independently evolve similar traits, and ecological divergence, in which species diversify in response to the environment. Thus, anoles present opportunities to answer several important questions, including what are the factors that produce diversity in the important ecological traits of a species? What is the genetic basis for these traits, and are the same genes involved in the repeated evolution of particular traits in different species? When do the processes generating variation lead to speciation, in which one species diversifies into multiple, distinct species? This project will examine how spatial variation in the environment leads to variation in adaptive physical traits and variation across the genome both within and between species. The researchers will use advanced methods in genetic, morphology, and spatial statistics to analyze individual animals from a dozen species of anoles collected across different environments. By examining multiple species and many individual from each species, the researchers will be able to identify the factors that generate different levels of biodiversity during different stages of adaptive evolution. This project will also result in the training of two postdoctoral researchers and numerous graduate and undergraduate students, including students from traditionally underrepresented backgrounds. The researchers also plan to integrate the results of the project into classroom learning modules on the ecology and evolution of adaptive radiations for K-12 students.
Adaptive radiations, like the replicated diversification of Anolis lizards on the Greater Antilles into ecomorph classes through the evolution of novel traits, present excellent systems in which to study ecological divergence and parallel evolution. The overarching goal of the proposed research will be to examine how spatial environmental variation generates adaptive phenotypic diversity (Functional dimension), population genomic diversity (Genetic dimension), and ecomorphological species diversity (Phylogenetic dimension) in replicated adaptive radiations of Anolis lizards. Specifically, this project will test whether patterns of genetic and phenotypic variation depend upon the spatial structure of the environment or the ecology of the species; whether parallel phenotypic divergence involves parallel genetic divergence; whether environmental variation generates heterogeneous genomic divergence both within and between species; and whether the same regions of the genome are repeatedly involved in generating ecomorphological diversity. These questions will be answered by assembling ultra-high resolution environmental, morphological, and genetic datasets for 12 Anolis species from the Greater Antilles using cutting-edge data collection methods. This project will use terrestrial-LiDAR scans of structural habitats and geospatial analysis of bioclimatic layers in a GIS (Geographical Information System) to generate the environmental data, exon capture and whole exome sequencing to produce the genetic data, and micro-CT scanning to generate 3D reconstructions of field-collected specimens for the morphological data. Innovative analytical approaches will then be used to integrate these diverse datasets to understand the processes underlying diversification across different stages of adaptive radiation. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/92065
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Ian Wang. Dimensions: Landscape Genomics of an Adaptive Radiation using Ultra-High Resolution Genetic, Morphometric, and Spatial Analysis. 2016-01-01.
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