| 项目编号: | 1546049
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| 项目名称: | EAGER: Developing a High Resolution Method for Mapping Regulatory QTLs |
| 作者: | Robert Reed
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| 承担单位: | Cornell University
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| 批准年: | 2016
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| 开始日期: | 2016-03-01
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| 结束日期: | 2019-02-28
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| 资助金额: | 299995
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| 资助来源: | US-NSF
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| 项目类别: | Continuing 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: | creqtl
; regulatory element
; method
; resolution
; variation
; new method
; project
; approach
; trait variation
; high-resolution approach
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| 英文摘要: | A major of focus of many research groups is to characterize specific genomic elements that control variation in quantitative traits (traits that are determined by many genes and their interactions with the environment). Some trait variation can be easily mapped to particular genes due to clear associations with variation in encoded proteins. Much trait variation, however, is difficult to characterize with precision because it is caused by differences in DNA sequences that control gene expression. Variation in these so-called regulatory elements has traditionally been much more difficult to characterize than variation in protein-coding regions for technical reasons. The purpose of this project is to develop new methods and computational resources to allow biologists to identify regulatory elements that control quantitative variation in natural and emerging model systems. The development of these methods will transform the manner in which biologists link phenotype with genotype and thus how they study the functional basis of evolutionary change. The methods will be broadly used and likely impact fields as disparate as agriculture and bioengineering.
Nucleotide polymorphism association studies, sometimes coupled with transcript abundance data, have become a favorite approach for identifying genomic loci underlying trait variation. This commonly adopted approach, however, often fails to characterize specific causal genomic elements. Instead, it often settles for neutral markers indicative of selection across regions spanning tens to hundreds of thousands of nucleotides. In some cases this may be sufficient to identify causal genes, especially when association intervals contain obvious changes in protein coding regions. In many cases, however, it is difficult to improve resolution because important functional changes in regulatory elements are difficult to identify. For this project the investigators are working to develop a novel, high-resolution approach to precisely map cis-regulatory quantitative trait loci (creQTLs). Specifically, they aim to characterize creQTLs by combining standard genotyping analysis with assays for chromatin structure and active transcription. This approach would allow association studies to consider both regulatory activity and nucleotide sequences, and could lead to resolution of <150bp for QTLs mapping to regulatory elements. The overarching goal of this project is to optimize this approach for use in emerging model systems and to develop bioinformatic tools for annotation and statistical inference of creQTLs, with an emphasis on utilizing readily available draft-quality genomes. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/92809
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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: | |
Robert Reed. EAGER: Developing a High Resolution Method for Mapping Regulatory QTLs. 2016-01-01.
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