Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.tree.2017.09.004 |
Genomic Quantitative Genetics to Study Evolution in the Wild | |
Gienapp, Phillip1; Fior, Simone2; Guillaume, Frereric3; Lasky, Jesse R.4; Sork, Victoria L.5; Csillery, Katalin3,6 | |
2017-12-01 | |
发表期刊 | TRENDS IN ECOLOGY & EVOLUTION |
ISSN | 0169-5347 |
EISSN | 1872-8383 |
出版年 | 2017 |
卷号 | 32期号:12 |
文章类型 | Review |
语种 | 英语 |
国家 | Netherlands; Switzerland; USA |
英文摘要 | Quantitative genetic theory provides a means of estimating the evolutionary potential of natural populations. However, this approach was previously only feasible in systems where the genetic relatedness between individuals could be inferred from pedigrees or experimental crosses. The genomic revolution opened up the possibility of obtaining the realized proportion of genome shared among individuals in natural populations of virtually any species, which could promise (more) accurate estimates of quantitative genetic parameters in virtually any species. Such a 'genomic' quantitative genetics approach relies on fewer assumptions, offers a greater methodological flexibility, and is thus expected to greatly enhance our understanding of evolution in natural populations, for example, in the context of adaptation to environmental change, eco-evolutionary dynamics, and biodiversity conservation. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000415306100010 |
WOS关键词 | ARABIDOPSIS-THALIANA ACCESSIONS ; CLIMATE-CHANGE ; RELATIONSHIP MATRIX ; LOCAL ADAPTATION ; WHITE SPRUCE ; POPULATION ; RELATEDNESS ; SELECTION ; HERITABILITY ; CONSERVATION |
WOS类目 | Ecology ; Evolutionary Biology ; Genetics & Heredity |
WOS研究方向 | Environmental Sciences & Ecology ; Evolutionary Biology ; Genetics & Heredity |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/28818 |
专题 | 资源环境科学 |
作者单位 | 1.Netherlands Inst Ecol NIOO KNAW, Dept Anim Ecol, Wageningen, Netherlands; 2.Swiss Fed Inst Technol, Plant Ecol Genet, Zurich, Switzerland; 3.Univ Zurich, Dept Evolutionary Biol & Environm Studies, Zurich, Switzerland; 4.Penn State Univ, Dept Biol, University Pk, PA 16802 USA; 5.Univ Calif Los Angeles, Dept Ecol & Evolutionary Biol, Los Angeles, CA USA; 6.WSL Swiss Fed Res Inst, Biodivers & Conservat Biol, Birmensdorf, Switzerland |
推荐引用方式 GB/T 7714 | Gienapp, Phillip,Fior, Simone,Guillaume, Frereric,et al. Genomic Quantitative Genetics to Study Evolution in the Wild[J]. TRENDS IN ECOLOGY & EVOLUTION,2017,32(12). |
APA | Gienapp, Phillip,Fior, Simone,Guillaume, Frereric,Lasky, Jesse R.,Sork, Victoria L.,&Csillery, Katalin.(2017).Genomic Quantitative Genetics to Study Evolution in the Wild.TRENDS IN ECOLOGY & EVOLUTION,32(12). |
MLA | Gienapp, Phillip,et al."Genomic Quantitative Genetics to Study Evolution in the Wild".TRENDS IN ECOLOGY & EVOLUTION 32.12(2017). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论