Genotype-phenotype mapping in a post-GWAS world

被引:47
|
作者
Nuzhdin, Sergey V. [1 ]
Friesen, Maren L. [1 ]
McIntyre, Lauren M. [2 ]
机构
[1] Univ So Calif, Program Mol & Computat Biol, Dept Biol, Los Angeles, CA 90089 USA
[2] Univ Florida, Dept Mol Genet & Microbiol, Gainesville, FL 32611 USA
基金
美国国家科学基金会;
关键词
FLOWERING TIME CONTROL; GENETIC-VARIATION; FIT INDEXES; NETWORK; EXPRESSION; INFERENCE; MODEL; TRANSCRIPTOME; CIS;
D O I
10.1016/j.tig.2012.06.003
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Understanding how metabolic reactions, cell signaling, and developmental pathways translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS) statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular biology approach directly ties gene function to phenotype through gene regulatory networks (GRNs). Using natural variation in allele-specific expression, GWAS and GRN approaches can be merged into a single framework via structural equation modeling (SEM). This approach leverages the myriad of polymorphisms in natural populations to elucidate and quantitate the molecular pathways that underlie phenotypic variation. The SEM framework can be used to quantitate a GRN, evaluate its consistency across environments or sexes, identify the differences in GRNs between species, and annotate GRNs de nova in non-model organisms.
引用
收藏
页码:421 / 426
页数:6
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