Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
Proc Natl Acad Sci U S A. 2010 Mar 30;107(13):5732-7. doi: 10.1073/pnas.0913635107. Epub 2010 Mar 15.
We present a method termed mining developmentally regulated genes (MiDReG) to predict genes whose expression is either activated or repressed as precursor cells differentiate. MiDReG does not require gene expression data from intermediate stages of development. MiDReG is based on the gene expression patterns between the initial and terminal stages of the differentiation pathway, coupled with "if-then" rules (Boolean implications) mined from large-scale microarray databases. MiDReG uses two gene expression-based seed conditions that mark the initial and the terminal stages of a given differentiation pathway and combines the statistically inferred Boolean implications from these seed conditions to identify the relevant genes. The method was validated by applying it to B-cell development. The algorithm predicted 62 genes that are expressed after the KIT+ progenitor cell stage and remain expressed through CD19+ and AICDA+ germinal center B cells. qRT-PCR of 14 of these genes on sorted B-cell progenitors confirmed that the expression of 10 genes is indeed stably established during B-cell differentiation. Review of the published literature of knockout mice revealed that of the predicted genes, 63.4% have defects in B-cell differentiation and function and 22% have a role in the B cell according to other experiments, and the remaining 14.6% are not characterized. Therefore, our method identified novel gene candidates for future examination of their role in B-cell development. These data demonstrate the power of MiDReG in predicting functionally important intermediate genes in a given developmental pathway that is defined by a mutually exclusive gene expression pattern.
我们提出了一种称为挖掘发育调控基因(MiDReG)的方法,用于预测前体细胞分化时表达被激活或抑制的基因。MiDReG 不需要发育中间阶段的基因表达数据。MiDReG 基于分化途径初始和终末阶段之间的基因表达模式,结合从大规模微阵列数据库中挖掘出的“如果-那么”规则(布尔蕴涵)。MiDReG 使用两个基于基因表达的种子条件,标记给定分化途径的初始和终末阶段,并结合这些种子条件的统计推断的布尔蕴涵来识别相关基因。该方法通过应用于 B 细胞发育进行了验证。该算法预测了 62 个在 KIT+祖细胞阶段后表达并在 CD19+和 AICDA+生发中心 B 细胞中持续表达的基因。对这些基因中的 14 个进行的分选 B 细胞前体的 qRT-PCR 证实,10 个基因的表达在 B 细胞分化过程中确实稳定建立。对敲除小鼠的已发表文献的综述表明,在所预测的基因中,63.4%的基因在 B 细胞分化和功能上存在缺陷,22%的基因根据其他实验在 B 细胞中有作用,其余 14.6%的基因尚未确定。因此,我们的方法确定了新的候选基因,以进一步研究它们在 B 细胞发育中的作用。这些数据表明 MiDReG 在预测给定发育途径中功能重要的中间基因方面具有强大的功能,该途径由相互排斥的基因表达模式定义。
Proc Natl Acad Sci U S A. 2010-3-15
Proc Natl Acad Sci U S A. 2010-3-15
IEEE/ACM Trans Comput Biol Bioinform. 2024-10-29
bioRxiv. 2024-1-28
Genes Chromosomes Cancer. 2023-6
Biomolecules. 2022-11-29
BMC Bioinformatics. 2022-9-16
Cancers (Basel). 2021-8-26
Neurochem Res. 2009-6
Genome Biol. 2008-10-30
Nat Genet. 2005-4