Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.
Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.
复制标题
DOI：
10.1186/s13073-016-0352-6
复制
发表时间：
2016-09-30
期刊：
影响因子：
12.3
通讯作者：
Gauguier D
中科院分区：
文献类型：
--
作者：
Dumas ME;Domange C;Calderari S;Martínez AR;Ayala R;Wilder SP;Suárez-Zamorano N;Collins SC;Wallis RH;Gu Q;Wang Y;Hue C;Otto GW;Argoud K;Navratil V;Mitchell SC;Lindon JC;Holmes E;Cazier JB;Nicholson JK;Gauguier D
代谢表型的遗传调节（即，2型糖尿病中的代谢型（代谢型）通过复杂的器官特异性细胞机制和网络发生，导致胰岛素分泌受损和胰岛素抵抗。全基因组基因表达谱系统可以剖析基因对代谢组和转录组调控的贡献。多基因表达性状和代谢表型的综合分析（即，代谢型）连同其潜在的遗传调控仍然是一个挑战。在这里，我们介绍了一种系统遗传学方法，该方法基于对通过表达和代谢型数量性状基因座作图（即，eQTL和mQTL）来优先考虑候选基因和性状的生物学表征。我们使用了系统的代谢分型的1H NMR光谱和全基因组基因表达的白色脂肪组织映射分子表型的基因组块与肥胖和胰岛素分泌在一系列大鼠同源株来自自发性糖尿病Goto-Kakizaki（GK）和血糖正常的布朗挪威（BN）大鼠。我们实施了一种网络生物学策略方法来可视化与每个基因组块显著相关的代谢物和基因之间的最短路径。尽管同源物之间存在很强的基因组相似性（95- 99%），但每个菌株都表现出特定的基因表达和代谢型模式，反映了同源间隔中一系列连锁遗传多态性的代谢结果。随后，我们使用同源面板定位特定mQTL和全基因组eQTL的数量性状位点。葡萄糖、琥珀酸、乳酸或3-羟基丁酸等关键代谢物和肌醇等第二信使前体的变异与几个独立的基因组间隔相关，表明这些区域存在功能冗余。为了浏览这些关联网络的复杂性，我们将候选基因和代谢物映射到代谢途径上，并实施最短路径策略以突出代谢物和转录物之间在共定位mQTL和eQTL处的潜在机制联系。最小化最短路径长度驱动了通过基因沉默进行生物学验证的优先级。这些结果强调了基于网络的多级系统遗传学数据集的整合的重要性，以提高对代谢型和转录组调控的遗传结构的理解，并表征决定组织特异性代谢的基因的新功能作用。本文的在线版本（doi：10.1186/s13073-016-0352-6）包含补充材料，可供授权用户使用。
The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95–99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism. The online version of this article (doi:10.1186/s13073-016-0352-6) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子：
64.8
作者：
通讯作者：
--
环境：两分网络的主动模块 - 使用高通量转录组数据解剖代谢反应。
影响因子：
--
作者：
Bryant WA;Sternberg MJ;Pinney JW
通讯作者：
Pinney JW
影响因子：
30.8
作者：
通讯作者：
--
影响因子：
2.2
作者：
GOTO, Y;KAKIZAKI, M;MASAKI, N
通讯作者：
MASAKI, N
影响因子：
4.5
作者：
Ferrara CT;Wang P;Neto EC;Stevens RD;Bain JR;Wenner BR;Ilkayeva OR;Keller MP;Blasiole DA;Kendziorski C;Yandell BS;Newgard CB;Attie AD
通讯作者：
Attie AD