Chromosome Gene Orientation Inversion Networks (GOINs) of Plasmodium Proteome,Journal of Proteome Research

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Chromosome Gene Orientation Inversion Networks (GOINs) of Plasmodium Proteome
Journal of Proteome Research ( IF 3.8 ) Pub Date : 2018-02-05 00:00:00 , DOI: 10.1021/acs.jproteome.7b00861
Viviana F. Quevedo-Tumailli _{1,

2} , Bernabé Ortega-Tenezaca _{1,

2,

3} , Humbert González-Díaz _{4,

5}

Affiliation

The spatial distribution of genes in chromosomes seems not to be random. For instance, only 10% of genes are transcribed from bidirectional promoters in humans, and many more are organized into larger clusters. This raises intriguing questions previously asked by different authors. We would like to add a few more questions in this context, related to gene orientation inversions. Does gene orientation (inversion) follow a random pattern? Is it relevant to biological activity somehow? We define a new kind of network coined as the gene orientation inversion network (GOIN). GOIN’s complex network encodes short- and long-range patterns of inversion of the orientation of pairs of gene in the chromosome. We selected Plasmodium falciparum as a case of study due to the high relevance of this parasite to public health (causal agent of malaria). We constructed here for the first time all of the GOINs for the genome of this parasite. These networks have an average of 383 nodes (genes in one chromosome) and 1314 links (pairs of gene with inverse orientation). We calculated node centralities and other parameters of these networks. These numerical parameters were used to study different properties of gene inversion patterns, for example, distribution, local communities, similarity to Erdös-Rényi random networks, randomness, and so on. We find clues that seem to indicate that gene orientation inversion does not follow a random pattern. We noted that some gene communities in the GOINs tend to group genes encoding for RIFIN-related proteins in the proteome of the parasite. RIFIN-like proteins are a second family of clonally variant proteins expressed on the surface of red cells infected with Plasmodium falciparum. Consequently, we used these centralities as input of machine learning (ML) models to predict the RIFIN-like activity of 5365 proteins in the proteome of Plasmodium sp. The best linear ML model found discriminates RIFIN-like from other proteins with sensitivity and specificity 70–80% in training and external validation series. All of these results may point to a possible biological relevance of gene orientation inversion not directly dependent on genetic sequence information. This work opens the gate to the use of GOINs as a tool for the study of the structure of chromosomes and the study of protein function in proteome research.

中文翻译：

疟原虫蛋白质组的染色体基因定向倒置网络（GOIN）

染色体中基因的空间分布似乎不是随机的。例如，人类中双向启动子仅转录了10％的基因，而更多的则组织成更大的簇。这就提出了以前由不同作者提出的有趣问题。在这种情况下，我们想添加一些与基因方向倒置有关的问题。基因方向（倒位）是否遵循随机模式？它与生物活性有关吗？我们定义了一种新的网络，称为基因方向反转网络（GOIN）。GOIN的复杂网络编码染色体中基因对方向的反向的短距离和远距离模式。我们选择了恶性疟原虫由于这种寄生虫与公共卫生（疟疾的病原体）高度相关，因此作为研究案例。我们首次在这里构建了该寄生虫基因组的所有GOIN。这些网络平均有383个节点（一个染色体中的基因）和1314个链接（成对的具有反向方向的基因）。我们计算了这些网络的节点中心度和其他参数。这些数值参数用于研究基因倒置模式的不同属性，例如分布，局部社区，与Erdös-Rényi随机网络的相似性，随机性等。我们发现线索似乎表明基因方向倒置并不遵循随机模式。我们注意到，GOIN中的某些基因群落倾向于将寄生虫蛋白质组中编码RIFIN相关蛋白的基因分组。恶性疟原虫。因此，我们将这些中心点用作机器学习（ML）模型的输入，以预测疟原虫sp蛋白质组中5365蛋白的RIFIN样活性。在训练和外部验证系列中，发现的最佳线性ML模型将RIFIN样与其他蛋白区分开，灵敏性和特异性为70-80％。所有这些结果可能表明基因方向倒置可能具有生物学相关性，而不直接取决于遗传序列信息。这项工作为使用GOINs作为研究染色体结构和蛋白质组学研究中蛋白质功能的工具打开了大门。

更新日期：2018-02-06

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