Genetic variation shapes protein networks mainly through non-transcriptional mechanisms.
Genetic variation shapes protein networks mainly through non-transcriptional mechanisms.
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DOI：
10.1371/journal.pbio.1001144
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发表时间：
2011-09
期刊：
影响因子：
9.8
通讯作者：
Bedalov A
中科院分区：
文献类型：
--
作者：
Foss EJ;Radulovic D;Shaffer SA;Goodlett DR;Kruglyak L;Bedalov A
在远交酵母群体中在网络内起作用的共调节蛋白的水平的变化不是由相应转录物的变化驱动的。遗传多样性群体中的共调节转录物网络已被广泛研究，但对这些网络在蛋白质水平上引起类似共变异的程度知之甚少。我们量化了354个蛋白质在遗传多样性的酵母分离群体，这使得第一次构建一个连贯的蛋白质共变异矩阵。我们确定了36个和93个蛋白质的紧密共调控组，这些蛋白质分别主要由参与核糖体生物合成和氨基酸代谢的基因组成。尽管核糖体基因在蛋白质和转录水平上都受到严格的共调控，但蛋白质的遗传调控与转录的遗传调控完全不同，并且在这个网络中几乎没有基因显示出蛋白质和转录水平之间的显著相关性。这一结果质疑了广泛持有的信念，即在酵母中，与高等真核生物相反，核糖体蛋白水平主要通过调节转录水平来调节。此外，虽然蛋白质和转录物的氨基酸网络的遗传调控更相似，但回归分析表明，即使在这里，蛋白质的变化主要是由于非转录变异。我们还发现，转录组中常见的顺式调节在蛋白质组水平上很少见。我们的结论是，在这个遗传多样性的人口中，这些特定的高丰度蛋白质的水平的个体间的变化是不是由其潜在的转录本的变化。每个基因产生的蛋白质水平大致对应于该基因产生的mRNA转录物水平：因此，高丰度蛋白质，如参与蛋白质合成的蛋白质，由高丰度转录物表示，而低丰度蛋白质，如参与信号传导途径的蛋白质，由低丰度转录物表示。此外，遗传变异可以导致不同个体之间相同基因的转录水平的变化。这两个观察结果导致了这样的假设，即任何特定基因的转录水平的个体间差异会导致蛋白质水平的相应变化。然而，情况并非如此，因为蛋白质水平不仅可以通过调节转录水平来控制，还可以通过调节蛋白质翻译和稳定性来控制。由于任何特定基因的转录物水平的个体间差异通常小于3倍，而不是数量级，因此任何特定蛋白质水平的个体间差异的主要原因可能是蛋白质水平的转录非依赖性调节。在这里，我们在95个酵母菌株的遗传多样性群体中观察遗传变异，这些遗传变异反过来导致在共调节网络中起作用的354种蛋白质水平的变化。我们发现，应变之间的变化主要反映转录独立的机制。如果这一结果是典型的蛋白质组作为一个整体，它表明，蛋白质水平在遗传多样性的人口不能准确地推断出其基础转录水平。
Variation in the levels of co-regulated proteins that function within networks in an outbred yeast population is not driven by variation in the corresponding transcripts. Networks of co-regulated transcripts in genetically diverse populations have been studied extensively, but little is known about the degree to which these networks cause similar co-variation at the protein level. We quantified 354 proteins in a genetically diverse population of yeast segregants, which allowed for the first time construction of a coherent protein co-variation matrix. We identified tightly co-regulated groups of 36 and 93 proteins that were made up predominantly of genes involved in ribosome biogenesis and amino acid metabolism, respectively. Even though the ribosomal genes were tightly co-regulated at both the protein and transcript levels, genetic regulation of proteins was entirely distinct from that of transcripts, and almost no genes in this network showed a significant correlation between protein and transcript levels. This result calls into question the widely held belief that in yeast, as opposed to higher eukaryotes, ribosomal protein levels are regulated primarily by regulating transcript levels. Furthermore, although genetic regulation of the amino acid network was more similar for proteins and transcripts, regression analysis demonstrated that even here, proteins vary predominantly as a result of non-transcriptional variation. We also found that cis regulation, which is common in the transcriptome, is rare at the level of the proteome. We conclude that most inter-individual variation in levels of these particular high abundance proteins in this genetically diverse population is not caused by variation of their underlying transcripts. The level of protein produced by each gene corresponds approximately to the level of mRNA transcript produced by that gene: so high-abundance proteins, like those involved in protein synthesis, are represented by high-abundance transcripts, whereas low-abundance proteins, like those involved in signaling pathways, are represented by low-abundance transcripts. Furthermore, genetic variation can cause variation in transcript levels for the same gene between different individuals. These two observations have led to the assumption that inter-individual variation in transcript levels for any particular gene causes corresponding variation in protein levels. However, this need not be the case, because protein levels could be controlled not only by regulating transcript levels but also by regulating protein translation and stability. Because inter-individual variation in the levels of the transcript for any particular gene is typically less than 3-fold, rather than orders of magnitude, it is possible that the predominant cause of inter-individual variation in levels of any particular protein is transcription-independent regulation of protein levels. Here, we look in a genetically diverse population of 95 yeast strains at the genetic variation that leads in turn to variation in levels of 354 proteins that function within co-regulated networks. We find that the between-strain variation predominantly reflects transcription-independent mechanisms. If this result is typical of the proteome as a whole, it suggests that protein levels in genetically diverse populations cannot be accurately inferred from levels of their underlying transcripts.
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