Genome-wide identification of new Wnt/beta-catenin target genes in the human genome using CART method

Abstract

Background: The importance of in silico predictions for understanding cellular processes is now widely accepted, and a variety of algorithms useful for studying different biological features have been designed. In particular, the prediction of cis regulatory modules in non-coding human genome regions represents a major challenge for understanding gene regulation in several diseases. Recently, studies of the Wnt signaling pathway revealed a connection with neurodegenerative diseases such as Alzheimer's. In this article, we construct a classification tool that uses the transcription factor binding site motifs composition of some gene promoters to identify new Wnt/beta-catenin pathway target genes potentially involved in brain diseases.

Results: In this study, we propose 89 new Wnt/beta-catenin pathway target genes predicted in silico by using a method based on multiple Classification and Regression Tree (CART) analysis. We used as decision variables the presence of transcription factor binding site motifs in the upstream region of each gene. This prediction was validated by RT-qPCR in a sample of 9 genes. As expected, LEF1, a member of the T-cell factor/lymphoid enhancer-binding factor family (TCF/LEF1), was relevant for the classification algorithm and, remarkably, other factors related directly or indirectly to the inflammatory response and amyloidogenic processes also appeared to be relevant for the classification. Among the 89 new Wnt/beta-catenin pathway targets, we found a group expressed in brain tissue that could be involved in diverse responses to neurodegenerative diseases, like Alzheimer's disease (AD). These genes represent new candidates to protect cells against amyloid beta toxicity, in agreement with the proposed neuroprotective role of the Wnt signaling pathway.

Conclusions: Our multiple CART strategy proved to be an effective tool to identify new Wnt/beta-catenin pathway targets based on the study of their regulatory regions in the human genome. In particular, several of these genes represent a new group of transcriptional dependent targets of the canonical Wnt pathway. The functions of these genes indicate that they are involved in pathophysiology related to Alzheimer's disease or other brain disorders.

Figure 1

Number of CART trees that declare a gene to be a Wnt/β-catenin pathway target. Red points correspond to genes already known to be targets of the Wnt/β-catenin pathway, and black points represent genes not previously identified as Wnt/β-catenin pathway targets. The vertical axis denotes the "score" of each individual gene. Genes are ordered decreasingly with the score. The horizontal line represents the threshold value C associated to the highest percentile.

Figure 2

Gene Ontology enrichment for training and proposed Wnt/β-catenin pathway targets. Enriched nodes are colored in different intensities of green depending of adjusted p-values. Thus, more significant enrichment corresponds to the more intense green. First ratio corresponds to the proportion of GO terms in the human genome and the second ratio corresponds to the proportion of GO terms in the study group. A) GO terms enrichment for the known Wnt/β-catenin pathway target genes used as training group. B) GO terms enrichment in the same terms, for the proposed Wnt/β-catenin pathway target genes.

Figure 3

Classic structure of a CART tree. The first node of the tree is subdivided into two finer nodes depending on whether v1 is lower than c1. The resulting nodes are further subdivided to determine the assigned class.

Figure 4

General structure of the proposed method. We trained 1,500 CART trees using 66 known target genes marked as black dots and two groups of 8,000 randomly chosen genes from a list of 15,476 genes in the human genome. The first group is used to produce a first tree and the second to prune and evaluate it. The classification method is the consolidation of the results of the 1,500 CART trees.