THE HUMAN BRAINOME:genome, transcriptome and proteome interaction in human cortex

描述(由申请人提供)：我们的人类脑组项目旨在定义正常衰老的人脑和受神经退行性疾病影响的大脑皮质中的基因组-转裂组-蛋白质组-物候组的相互作用。我们假设，目前公认的通过查看单层信息(基因类型)来发现新的遗传风险基因座的方法是缺乏力量的，采取更全系统的方法可能会增加发现新靶点的成功率。我们打算将我们的基因信息(约180万个单核苷酸多态)和我们的表达信息(约46,000个转录本)与一个新的蛋白质组学数据集进行比较，该数据集是通过在线运行液相色谱和高质量精度质谱仪(LC-MS，提供~2000-3000个蛋白质的定量)生成的。我们将同时研究单个相关的顺式和反式关系(即DNA变化影响一个转录本或蛋白质的下游调控)，以及执行分析，以了解发生在转录组和蛋白质组水平的关系网络。我们处于很好的位置来完成这项工作。首先，我们收集了大量冷冻的人类大脑样本(n~1500个，~60%的迟发性阿尔茨海默病样本)，这些样本有可用的基因和表达数据。为了获得足够的能力来准确地评估人类基因组，以及克服转录组和蛋白质组学样本分析固有的一些噪声和其他问题，需要大样本容量。这些现有的基因型和基因表达数据集对于这笔赠款的成功至关重要。其次，为了完成蛋白质组分析，我们将利用太平洋西北国家实验室开发的精确质量和时间(AMT)标签方法，以避免传统方法的灵敏度限制，并提高测量的吞吐量，提供广泛的蛋白质组覆盖。在拥有相同的蛋白质组覆盖率的同时，AMT标签方法通常将每个样品分析的仪器时间减少1-2个数量级(例如，1小时与通常的24小时)。因此，AMT标签方法是提供对该项目至关重要的灵敏度和测量吞吐量的唯一合理选择。最后，我们希望使用我们的新型去噪算法将灵敏度额外提高10倍，这将允许对人类大脑皮层的完整蛋白质组进行更准确的评估。通过发展对人脑表达过程的更全面的看法，我们将能够将新的基因发现与其下游的神经病理生物学相关性联系起来。这将有助于神经退行性疾病的新的遗传和分子生物标记物的开发。识别可以进一步对临床前亚组进行分类并识别快速转化子亚类的生物标志物将有助于显著降低药物试验的成本。这些生物标记物将具有额外的好处，它们不仅是分子的，而且还具有绘制的基因图谱，这应该比分子标记物更容易检测。在这个项目中，我们试图定义DNA变异对人类皮质表达的影响，重点是DNA变异对与阿尔茨海默病发病机制相关的蛋白质组表达变化的影响。如果我们实现了我们的目标，我们将确切地知道哪一种或哪组变异正在改变蛋白质的表达水平。这些信息将帮助我们定义DNA风险变异在阿尔茨海默病中的下游意义，这可能有助于发现这种毁灭性疾病的新生物标记物和治疗方法。

Description (provided by applicant): Our Human Brainome project seeks to define the genome-transriptome-proteome- phenome interactions in the cortexes of normally aged human brains and brains affected by neurodegenerative disease. We hypothesize that the current accepted approach for discovering novel genetic risk loci by looking at a single layer of information (genotypes) is lacking power and taking a more systems-wide approach might increase the success of finding novel targets. We intend upon comparing our genotype information (~ 1.8 million single nucleotide polymorphisms) and our expression information (~ 46,000 transcripts) with a novel proteomics dataset generated by running Liquid Chromatography coupled online with high mass accuracy Mass Spectrometry (LC- MS, providing quantification of ~2000-3000 proteins). We will look at both single correlative cis and trans relationships (i.e. DNA change affects downstream regulation of one transcript or protein), as well as perform analyses to understand the networks of relationships occurring both at the transcriptome and proteome level. We are well situated to perform this work. First, we have an extensive collection of frozen human brain samples (n~1500, ~60% late onset Alzheimer's disease samples) for which there is genotype and expression data available. Large sample sizes are needed to obtain sufficient power to accurately assess the human genome as well as overcome some of the noise and other issues inherent to transcriptomics and proteomics sample analysis. These existing genotype and gene expression datasets are essential to success in this grant. Second, to accomplish the proteome analyses we will utilize the accurate mass and time (AMT) tag approach developed at the Pacific Northwest National Laboratories to avoid the sensitivity constraints of conventional approaches and improve the throughput of measurements providing broad proteome coverage. While having the same coverage of the proteome, the AMT tag approach typically reduces by 1-2 orders (e.g. 1 hour vs normally 24 hours) of magnitude the instrument time per sample analysis. Thus, the AMT tag approach is the only reasonable option to provide the sensitivity and measurement throughput essential to this project. Finally, we expect to achieve an additional 10-fold increase in sensitivity using our novel de-noising algorithm that will allow for a more accurate assessment of the complete proteome of the human brain cortex. By developing a more global view of the processes involved in human brain expression we will be able to relate new genetic findings to their downstream neuro-pathobiological relevance. This should aid in the development of novel genetic and molecular biomarkers of neurodegenerative disease. Identifying biomarkers that could further classify pre-clinical subgroups and identify sub-classes of rapid converters would help to significantly reduce the cost of drug trials. These biomarkers will have the added benefit that they are not only molecular, but in addition have mapped genotype profiles, which should be easier to assay than a molecular marker. In this project we seek to define the effects of DNA variation on human cortical expression with an emphasis on the DNA variation that is impinging on proteome expression changes relevant to the pathogenesis of Alzheimer's disease. If we achieve our aims we will know specifically which variant or group of variants are changing protein expression levels. This information will help us to define the downstream significance of DNA risk variation in Alzheimer's disease, which might aid in the discovery of novel biomarkers and therapies for this devastating illness.