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Genetics of single-cell protein abundance variation in large yeast populations

机译:大酵母种群中单细胞蛋白质丰度变异的遗传

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摘要

Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or several genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL). Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power. Consequently, many eQTL are probably missed, especially those with smaller effects. Furthermore, most studies use messenger RNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics reported unexpected differences between eQTL and protein QTL (pQTL) for the same genes, but these studies have been even more limited in scope. Here we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyces cerevisiae. We measure single-cell protein abundance through the use of green fluorescent protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high versus low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci that we detected were clustered in 'hotspots' that influence multiple proteins, and some hotspots were found to influence more than half of the proteins that we examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.%很多DNA变体通过改变一个或几个基因的表达水平来影响表现型,因此人们目前对标绘这些"表达量化性状位点"(eQTL)很感兴趣。这篇论文介绍了一个新的eQTL标绘(mapping)方法,它设计用来克服现有方法的局限性(现有方法所关注的是RNA或蛋白丰度)。该新方法依靠GFP(绿色荧光蛋白)标记来测定酿酒酵母中的单细胞蛋白丰度。然后,混合测序(Pooled sequencing)方法被用来对数千个蛋白丰度高和蛋白丰度低的人的整个基因组中的等位基因频率进行比较。作者发现,对一个给定的基因来说,在影响mRNA和蛋白丰度的等位基因(位点)之间存在密切对应关系,同时他们也识别出了影响多个蛋白的热点位置-后者对基因调控网络有深远影响。
机译:个体之间的差异部分是由于DNA序列的差异引起的,但对大多数特征(包括常见疾病)变异的遗传基础仍然只有部分了解。许多DNA变体通过改变一个或几个基因的表达水平来影响表型。可以将此类变体的作用检测为表达定量性状基因座(eQTL)。传统的eQTL定位需要研究样本中每个个体的大规模基因型和基因表达数据,这将样本大小限制为人类和模型生物中的数百个个体,并降低了统计能力。因此,可能会错过许多eQTL,尤其是效果较小的eQTL。此外,大多数研究使用信使RNA而不是蛋白质丰度作为基因表达的量度。使用质谱蛋白质组学的研究报告了相同基因的eQTL和蛋白质QTL(pQTL)之间出乎意料的差异,但是这些研究的范围更加有限。在这里,我们介绍了一种强大的方法,用于识别影响酵母酿酒酵母中蛋白质表达的遗传基因座。我们通过在非常大量的遗传可变细胞群体中使用绿色荧光蛋白标签来测量单细胞蛋白的丰度,并使用汇总测序比较成千上万的具有高蛋白丰度和低蛋白丰度的个体在整个基因组中的等位基因频率。我们将这种方法应用于160个基因,并且每个基因检测到的基因座比以前的研究多得多。我们还观察到影响蛋白质丰度的基因座与影响给定基因的mRNA丰度的基因座之间的对应关系更紧密。我们检测到的大多数基因座都聚集在影响多种蛋白质的“热点”中,并且发现一些热点会影响我们检测的蛋白质的一半以上。这些热点的变异对基因调控网络产生了深远的影响,并为深入了解酵母菌株之间细胞生理学的遗传变异提供了见解。%DNA变异体通过改变一个或几个基因的表达水平来影响表现型,因此有人目前本文介绍了一个新的eQTL标绘(映射)方法,它设计克服了现有方法的局限性(现有方法所该新方法依靠GFP(绿色荧光蛋白)标记来测定酿酒酵母中的单细胞蛋白丰度。然后,混合选择(混合测序)方法被用于对大量个蛋白作者发现,对一个给定的基因而言,在影响mRNA和蛋白丰度的等位基因(位点)之上。丰度高和蛋白丰度低的人的整个基因组中的等位基因频率进行比较。间存在密切对应关系,同时他们也识别出了影响多个蛋白的斑点位置-另一对基因突变网络有深远影响。

著录项

  • 来源
    《Nature》 |2014年第7489期|494-497C3C5|共6页
  • 作者单位

    Department of Human Genetics, University of California, Los Angeles, California 90095, USA,Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA;

    Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA;

    Synthetic Genomics, 11149 North Torrey Pines Road, La Jolla, California 92037, USA;

    Department of Human Genetics, University of California, Los Angeles, California 90095, USA,Howard Hughes Medical Institute, University of California, Los Angeles, California 90095, USA Department of Biological Chemistry, University of California, Los Angeles, California 90095, USA;

    Howard Hughes Medical Institute, University of California, Los Angeles, California 90095, USA Department of Biological Chemistry, University of California, Los Angeles, California 90095, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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