MRC Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, The University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK.
Nucleic Acids Res. 2012 Oct;40(19):e153. doi: 10.1093/nar/gks663. Epub 2012 Jul 12.
A number of studies have shown that transcriptome analysis in terms of chromosomal location can reveal regions of non-random transcriptional activity within the genome. Genomic clusters of differentially expressed genes can identify genomic patterns of structural organization, underlying copy number variations or long-range epigenetic regulation such as X-chromosome inactivation. Here we apply an integrative bioinformatics analysis to a collection of 315 freely available mouse pluripotent stem cell samples to discover transcriptional clusters in the genome. We show that over half of the analysed samples (56.83%) carry whole or partial-chromosome spanning clusters which recur in genomic regions previously implicated in chromosomal imbalances. Strikingly, we found that the presence of such large-clusters is linked to the differential expression of a limited number of genes, common to all samples carrying clusters irrespectively of the chromosome where the cluster is found. We have used these genes to train and test classification models that can predict samples that carry large-scale clusters on any chromosome with over 90% accuracy. Our findings suggest that there is a common downstream activation in these cells that affects a limited number of nodes. We propose that this effect is linked to selective advantage and identify potential driver genes.
许多研究表明，从染色体位置上对转录组进行分析，可以揭示基因组中非随机转录活性的区域。差异表达基因的基因组簇可以识别结构组织的基因组模式，潜在的拷贝数变异或长距离表观遗传调控，如 X 染色体失活。在这里，我们对 315 个可自由获取的小鼠多能干细胞样本进行了综合生物信息学分析，以发现基因组中的转录簇。我们表明，超过一半的分析样本（56.83%）携带跨越整个或部分染色体的簇，这些簇在先前涉及染色体失衡的基因组区域中重现。引人注目的是，我们发现这些大型簇的存在与少数基因的差异表达有关，这些基因在所有携带簇的样本中都是共同的，而不论簇所在的染色体如何。我们使用这些基因来训练和测试分类模型，这些模型可以预测携带大规模簇的样本，在任何染色体上的准确率都超过 90%。我们的研究结果表明，这些细胞中存在一个共同的下游激活作用，影响了有限数量的节点。我们提出，这种效应与选择优势有关，并确定了潜在的驱动基因。
