Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels
Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels
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DOI：
10.1371/journal.pgen.1008686
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发表时间：
2020-03-01
期刊：
影响因子：
4.5
通讯作者：
Marioni, John C.
中科院分区：
文献类型：
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作者：
Morgan, Michael D.;Patin, Etienne;Marioni, John C.
作者摘要遗传变异可以改变同一类型组织或细胞群中基因开启或关闭的程度。然而，细胞群表达水平的这种平均掩盖了基因表达调控的一个重要方面，即其变异性。最近对人类的研究表明，附近的（顺式）遗传因素对这种变异性的影响最小。我们将遗传测量与流式细胞术单细胞蛋白质水平相结合，以解决人类免疫细胞中基因表达变异性的遗传控制。重要的是，我们已经证明，虽然目标基因（顺式）附近的遗传变异很少影响变异性，但远处的遗传位点或单独的染色体（反式）上的遗传位点仍然具有广泛的遗传贡献。此外，我们已经解决了这些转基因效应调节其他附近基因的表达，从而导致我们的目标蛋白的基因表达变异性的变化。我们的研究结果可以通过基因表达水平的顺式调节与基因表达变异性的下游后果之间的进化平衡来解释。确定复杂多细胞生物中影响蛋白质表达变异性的因素主要集中在顺式单细胞表达的启动子结构和调节上。然而，这种有针对性的方法迄今为止还无法识别人类细胞间基因表达变异的主要调节因子。为了解决这个问题，我们将使用流式细胞术的人类免疫系统中的单细胞蛋白质表达测量与定量遗传学分析相结合。对于表达变异具有可遗传成分的大多数蛋白质，我们发现遗传变异以反式作用，而以顺式作用的变异明显较少。此外，我们强调使用孟德尔随机化，这些变异性数量性状基因座可能是由上游基因的顺式调控驱动的。这表明自然选择可以平衡顺式基因调控的影响与反式表达变异的下游影响。
Author summaryGenetic variation can change how much a gene is turned on or off in a tissue or a population of cells of the same type. However, this averaging of expression levels across a cell population masks an important aspect of gene expression regulation, namely its variability. Recent work in humans has indicated that nearby (cis) genetic factors minimally influence this variability. We have combined genetic measurements with flow cytometry single-cell protein levels to resolve the genetic control of gene expression variability in human immune cells. Importantly, we have demonstrated that whilst genetic variants near the target genes (cis) rarely influence variability, there is still an extensive genetic contribution from genetic loci faraway, or on a separate chromosome (trans). Furthermore, we have resolved that these trans genetic effects regulate the expression of other nearby genes, which leads to changes in gene expression variability of our target proteins. Our findings can be explained by an evolutionary balance between the cis regulation of gene expression levels, and the downstream consequences on gene expression variability.Identifying the factors that shape protein expression variability in complex multi-cellular organisms has primarily focused on promoter architecture and regulation of single-cell expression in cis. However, this targeted approach has to date been unable to identify major regulators of cell-to-cell gene expression variability in humans. To address this, we have combined single-cell protein expression measurements in the human immune system using flow cytometry with a quantitative genetics analysis. For the majority of proteins whose variability in expression has a heritable component, we find that genetic variants act in trans, with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Randomization that these variability-Quantitative Trait Loci might be driven by the cis regulation of upstream genes. This indicates that natural selection may balance the impact of gene regulation in cis with downstream impacts on expression variability in trans.