globalchange  > 全球变化的国际研究计划
项目编号: 1556995
项目名称:
SG: Combining phylogenetic and network analyses for the study of symbiotic systems: a case study using lichens
作者: Francois Lutzoni
承担单位: Duke University
批准年: 2016
开始日期: 2016-03-01
结束日期: 2019-02-28
资助金额: 149943
资助来源: US-NSF
项目类别: Standard Grant
国家: US
语种: 英语
特色学科分类: Biological Sciences - Environmental Biology
英文关键词: lichen ; project ; previous study ; specificity ; network analysis ; lichen symbiosis ; symbiotic association ; eco-phylogenetic analysis ; species ; model system ; prior genetic analysis ; other fungal-photoautotrophic system ; ecological network theory
英文摘要: Symbioses, which are physically close associations of species including positive (mutualism) and negative (parasitism) interactions, are more the rule than the exception in nature. Virtually all species, including humans, have been and continue to be strongly influenced by symbioses. Ultimately, a comprehensive understanding of the history of life on Earth requires the detailed understanding of the evolutionary and ecological forces shaping species symbioses. The over-arching goal of this research project is to integrate evolutionary (genealogical) and ecological (species interactions) network analyses to test hypotheses about the origins and control of symbiotic associations. This work will focus on the evolution of specificity between symbiotic partners (generalists vs. specialists) using lichen symbioses as a model system. The project builds on a great deal of prior genetic analyses, which have been conducted on over 700 symbiotic associations between fungal and algal species, which give rise to lichens. This project will also provide opportunities for postdoc and undergraduate student training, and will develop non-technical web pages outlining the project to be made available to the public. There will also be professional symposia on the development of novel computational methods for studying symbioses. High school students will be invited to participate in this project based on their interest in a general workshop on lichen symbioses that will be organized.

The datasets and phylogenetic results generated by previous studies, provide a unique opportunity to address the following objectives of this study: (1) conduct a network analysis to reveal the association trends of the two mutualistic partners giving rise to lichens, and to infer the most important contributing factors to those associations; (2) compare these results from lichens with other fungal-photoautotrophic systems (e.g., mycorrhizae, endophytes); and (3) design new phylogenetic methods to study the evolution of specificity of interacting fungi and cyanobacteria or algae, and to identify factors correlated with shifts in specificity toward lower or higher specificity in species associations (generalists or specialists). This project is expected to advance the field by coupling the inferential power of phylogenetics with ecological network theory to study symbiotic associations among species within lichens. This new approach for what may be called eco-phylogenetic analysis will estimate, for the first time, the contribution of biotic and abiotic factors through time that best explain the patterns of symbiotic associations observed in nature. The methods developed will be applicable to other symbioses, beyond lichens.
资源类型: 项目
标识符: http://119.78.100.158/handle/2HF3EXSE/92830
Appears in Collections:全球变化的国际研究计划
科学计划与规划

Files in This Item:

There are no files associated with this item.


Recommended Citation:
Francois Lutzoni. SG: Combining phylogenetic and network analyses for the study of symbiotic systems: a case study using lichens. 2016-01-01.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Francois Lutzoni]'s Articles
百度学术
Similar articles in Baidu Scholar
[Francois Lutzoni]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Francois Lutzoni]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.