2015年5月26日，国际学术期刊《Scientific Reports》已正式发表了纪志梁教授课题组的研究论文“pattern Genes Suggest Functional Connectivity of Organs”。

人体器官是人体的基本结构和功能单位，执行着特定的生理功能，而不同的器官精密的组织在一起以完成复杂的机体功能。遗憾的是，现有实验技术的局限使得我们对器官功能确切的分子机制知之甚少。

在这项研究中，纪志梁教授课题组建立了一个计算分析思路，尝试去阐述基因在构建器官功能联系之间的作用。为此，他们从8个囊括了36个人类正常组织的转录组数据集中，挖掘出一致性的模式基因集(包括看家基因和选择性/特异性表达基因)，随后通过分析这些模式基因在器官功能的潜在角色，尝试从基因功能的角度阐述什么主导着器官功能，什么在介导器官之间的功能联系，以及不同器官是怎样协作以完成特定的机体生理学功能。

最重要的是，纪志梁教授课题组发现选择性基因可以稳定地表征器官之间的功能联系，暗示选择性基因或在器官功能对话之中扮演重要角色，因此，基于36个人体正常器官/组织，他们构建了一个器官功能联系图，展示了器官之间的功能联系。模式基因在探索器官功能的分子机制上起到了或起关键作用，同时也暗示它们可作为选择性生物标志物和治疗靶点。

该论文的第一作者为2013级硕士覃杨梅。

Human organ connectivity map

原文摘要：

pattern Genes Suggest Functional Connectivity of Organs

Human organ, as the basic structural and functional unit in human body, is made of a large community of different cell types that organically bound together. Each organ usually exerts highly specified physiological function; while several related organs work smartly together to perform complicated body functions. In this study, we present a computational effort to understand the roles of genes in building functional connection between organs. More specifically, we mined multiple transcriptome datasets sampled from 36 human organs and tissues, and quantitatively identified 3,149 genes whose expressions showed consensus modularly patterns: specific to one organ/tissue, selectively expressed in several functionally related tissues and ubiquitously expressed. These pattern genes imply intrinsic connections between organs. According to the expression abundance of the 766 selective genes, we consistently cluster the 36 human organs/tissues into seven functional groups: adipose & gland, brain, muscle, immune, metabolism, mucoid and nerve conduction. The organs and tissues in each group either work together to form organ systems or coordinate to perform particular body functions. The particular roles of specific genes and selective genes suggest that they could not only be used to mechanistically explore organ functions, but also be designed for selective biomarkers and therapeutic targets.