We map protein level QTLs in yeast by sorting tens of thousands of yeast meiotic progeny based on fluorescence, and bulk genotyping the populations. The deposited sequence data come from the sorted populations.. Yeast BYxRM cross segregant populations selected for high and low GFP values

The genetic basis of macroscopic heritable traits has been studied for decades. However, mapping the cellular traits that mediate the genotype signal beyond transcript abundance has been challenging due to a lack of appropriate assays. Here, we systematically analyze levels of 4,084 GFP-tagged yeast proteins in large clonal and segregating populations using flow cytometry and an automated imaging pipeline. We find that the genotype of trans variants contributed little to protein level variation in single cells, but explained over 50% of the variance in the population average protein abundance for half of the GFP-fusions tested. Genotype of the gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We mapped regions responsible for the heritable signal for twenty-five proteins, and found a median of five protein quantitative trait loci (pQTLs) per GFP-fusion. While transcript and protein abundance changes were largely independent, and several pQTLs did not affect transcript levels, over half of the expression QTLs (eQTLs) contributed to their protein level as well. We performed allele replacements of genes known to underlie trans eQTL hotspots, and confirmed that their genotype effects on mRNA and protein levels were correlated in magnitude. Our study represents the first genome-scale measurement of genetic contribution to protein abundance in single cells and populations, identifies over a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein levels.

宏观可遗传性状的遗传基础研究已开展数十年。然而，由于缺乏合适的检测手段，解析介导基因型信号且超出转录本丰度范畴的细胞性状仍颇具挑战。本研究借助流式细胞术与自动化成像分析流程，系统分析了大规模克隆种群与分离种群中4084个绿色荧光蛋白（green fluorescent protein, GFP）标记酵母蛋白的表达水平。研究发现，反式变异位点的基因型对单细胞内的蛋白水平变异贡献极小，但可解释半数待测GFP融合蛋白的种群平均蛋白丰度差异的50%以上。基因自身及其周边区域的基因型对蛋白水平的强影响频率是基因组其余区域总和的六倍。我们定位了25种蛋白的可遗传信号相关区域，并发现每个GFP融合蛋白对应的蛋白数量性状位点（protein quantitative trait loci, pQTLs）的中位数为5个。尽管转录本与蛋白丰度的变化整体上相互独立，且部分pQTLs并不影响转录本水平，但超过半数的表达数量性状位点（expression QTLs, eQTLs）同样会对蛋白水平产生影响。我们对已知作为反式表达数量性状位点热点的驱动基因进行了等位基因替换实验，并证实其基因型对mRNA与蛋白水平的影响幅度存在相关性。本研究首次实现了单细胞与种群水平上遗传因素对蛋白丰度影响的全基因组尺度测量，鉴定出超过100个反式蛋白数量性状位点，并验证了转录本变异相关效应可传递至蛋白水平。