Biomedical Informatics, Stanford University, Stanford, California, United States of America.
PLoS Genet. 2009 Dec;5(12):e1000776. doi: 10.1371/journal.pgen.1000776. Epub 2009 Dec 18.
In this work we present a method for the differential analysis of gene co-expression networks and apply this method to look for large-scale transcriptional changes in aging. We derived synonymous gene co-expression networks from AGEMAP expression data for 16-month-old and 24-month-old mice. We identified a number of functional gene groups that change co-expression with age. Among these changing groups we found a trend towards declining correlation with age. In particular, we identified a modular (as opposed to uniform) decline in general correlation with age. We identified potential transcriptional mechanisms that may aid in modular correlation decline. We found that computationally identified targets of the NF-KappaB transcription factor decrease expression correlation with age. Finally, we found that genes that are prone to declining co-expression tend to be co-located on the chromosome. Our results conclude that there is a modular decline in co-expression with age in mice. They also indicate that factors relating to both chromosome domains and specific transcription factors may contribute to the decline.
在这项工作中,我们提出了一种用于基因共表达网络差异分析的方法,并将该方法应用于寻找衰老过程中的大规模转录变化。我们从 16 个月大和 24 个月大的小鼠的 AGEMAP 表达数据中推导出同义基因共表达网络。我们确定了许多随年龄变化的功能基因群。在这些变化的群体中,我们发现与年龄的相关性呈下降趋势。特别是,我们发现与年龄的一般相关性呈模块化(而非均匀)下降。我们确定了可能有助于模块化相关性下降的潜在转录机制。我们发现,计算鉴定的 NF-KappaB 转录因子的靶基因表达与年龄的相关性降低。最后,我们发现易于发生共表达下降的基因往往在染色体上共定位。我们的研究结果表明,在小鼠中,共表达随年龄呈模块化下降。它们还表明,与染色体结构域和特定转录因子相关的因素可能导致共表达下降。