Zhang Yuji
Division of Biostatistics and Bioinformatics, University of Maryland Greenebaum Cancer Center, Baltimore, USA ; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, USA.
BioData Min. 2015 Aug 28;8:26. doi: 10.1186/s13040-015-0057-1. eCollection 2015.
Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems.
In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development.
We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.
分子网络是细胞内分子活动的支柱,为更好地理解疾病机制提供了独特的契机。虽然网络数据通常仅构成静态网络图谱,但将它们与时间进程基因表达信息相结合,可以为这些网络的动态特征提供线索,并揭示表征细胞反应的机制驱动基因。时间进程基因表达数据使我们能够广泛地“观察”系统的动态变化。然而,分析此类数据的一个挑战是在生物过程或功能类别的背景下,建立并表征在不同时间点发生变化的基因之间的相互作用。对这些数据源进行综合分析将使我们更全面地了解生物实体(如基因和蛋白质)如何在生物系统中协调执行其生物学功能。
在本文中,我们引入了一种基于网络的新方法,利用斑马鱼胚胎发育过程中的时间进程mRNA测序数据,在系统水平上从时间依赖性生物过程中提取功能知识。所提出的方法被应用于研究斑马鱼胚胎发育中1α,25(OH)2D3改变的机制。我们将所提出的方法应用于一个公开的斑马鱼时间进程mRNA-Seq数据集,该数据集包含沿四个时间点的两种不同处理。我们在基因本体生物学过程类别之间构建了网络,这些类别在连续时间点和不同条件下的差异表达基因中富集。1α,25-二羟基维生素D3改变的转录变化的时间传播从早期最初改变的少数基因开始,到后期大量生物学相关基因。最显著的生物学过程包括神经元和视网膜发育以及全身性应激反应。此外,我们还研究了不同条件下共表达基因中富集的生物学过程之间的关系。富集的生物学过程包括翻译延伸、核小体组装和视网膜发育。这些网络动态为1α,25-二羟基维生素D3处理对骨骼和软骨发育的影响提供了新的见解。
我们开发了一种基于网络的方法,通过整合分子相互作用和基因本体信息来分析不同时间点的差异表达基因。这些结果表明,所提出的方法可以为用1α,25(OH)2D3处理后脊椎动物胚胎发育中发生的分子机制提供见解。我们的方法能够监测生物过程,可为生成新的可测试假设提供基础。这种基于网络的整合方法可以很容易地扩展到任何时间或条件依赖性基因组数据分析。