Sudarsanam Priya, Cohen Barak A
Department of Genetics and Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.
PLoS Genet. 2014 May 1;10(5):e1004325. doi: 10.1371/journal.pgen.1004325. eCollection 2014 May.
Mapping the polymorphisms responsible for variation in gene expression, known as Expression Quantitative Trait Loci (eQTL), is a common strategy for investigating the molecular basis of disease. Despite numerous eQTL studies, the relationship between the explanatory power of variants on gene expression versus their power to explain ultimate phenotypes remains to be clarified. We addressed this question using four naturally occurring Quantitative Trait Nucleotides (QTN) in three transcription factors that affect sporulation efficiency in wild strains of the yeast, Saccharomyces cerevisiae. We compared the ability of these QTN to explain the variation in both gene expression and sporulation efficiency. We find that the amount of gene expression variation explained by the sporulation QTN is not predictive of the amount of phenotypic variation explained. The QTN are responsible for 98% of the phenotypic variation in our strains but the median gene expression variation explained is only 49%. The alleles that are responsible for most of the variation in sporulation efficiency do not explain most of the variation in gene expression. The balance between the main effects and gene-gene interactions on gene expression variation is not the same as on sporulation efficiency. Finally, we show that nucleotide variants in the same transcription factor explain the expression variation of different sets of target genes depending on whether the variant alters the level or activity of the transcription factor. Our results suggest that a subset of gene expression changes may be more predictive of ultimate phenotypes than the number of genes affected or the total fraction of variation in gene expression variation explained by causative variants, and that the downstream phenotype is buffered against variation in the gene expression network.
绘制导致基因表达变异的多态性图谱，即表达数量性状位点（eQTL），是研究疾病分子基础的常用策略。尽管有大量的eQTL研究，但变异对基因表达的解释力与其解释最终表型的能力之间的关系仍有待阐明。我们利用影响酿酒酵母野生菌株孢子形成效率的三种转录因子中的四个天然存在的数量性状核苷酸（QTN）解决了这个问题。我们比较了这些QTN解释基因表达变异和孢子形成效率变异的能力。我们发现，孢子形成QTN所解释的基因表达变异量并不能预测所解释的表型变异量。QTN在我们的菌株中导致了98%的表型变异，但所解释的基因表达变异中位数仅为49%。导致孢子形成效率大部分变异的等位基因并不能解释基因表达的大部分变异。基因表达变异中主效应和基因-基因相互作用之间的平衡与孢子形成效率的情况不同。最后，我们表明，同一转录因子中的核苷酸变异根据其是否改变转录因子的水平或活性，解释不同组靶基因的表达变异。我们的结果表明，基因表达变化的一个子集可能比受影响的基因数量或致病变异所解释的基因表达变异的总比例更能预测最终表型，并且下游表型对基因表达网络中的变异具有缓冲作用。
