Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)
Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)
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DOI：
10.1534/genetics.112.143354
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发表时间：
2013-02-01
期刊：
影响因子：
3.3
通讯作者：
Teupser, Daniel
中科院分区：
文献类型：
--
作者：
Holdt, Lesca M.;von Delft, Annette;Teupser, Daniel
全基因组研究时代的一个当前挑战是确定新发现的基因座的相关基因和机制。通过高通量质谱（MALDI-TOF MS）筛选血浆蛋白质组被认为是鉴定代谢和疾病过程的有前途的方法。因此，血浆蛋白质组筛选可能是特别有用的，以确定负责任的基因时，结合基因组中的变异分析。在这里，我们描述了一个蛋白质组数量性状基因座（pQTL）的研究，血浆蛋白质组筛选的F-2杂交的455只小鼠与177个遗传标记的基因组映射。176种肽中共有69种显示出显著的LOD评分（>= 5.35），证明了血浆蛋白质组的不同组分的强遗传调节。通过机理研究和MALDI-TOF/TOF、液相色谱-串联质谱（LC-MS/MS）分析证实了两个最强的pQTL的分析结果：一个质荷比（m/z）为3494的pQTL（LOD 24.9，D11 Mit 151）被鉴定为血红蛋白A亚基（Hba）N端35个氨基酸，由Hba的遗传变异引起。m/z 8713的另一个pQTL（LOD 36.4; D1 Mit 111）由载脂蛋白A2（Apoa 2）的变异引起，并与HDL胆固醇共分离。总之，我们表明，全基因组血浆蛋白质组分析与全基因组遗传筛查相结合，有助于识别影响血浆蛋白丰度的致病遗传变异。
A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F-2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (>= 5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.