Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model

Origin of functional de novo genes in humans from "hopeful monsters"

For a long time, it was believed that new genes arise only from modifications of preexisting genes, but the discovery of de novo protein-coding genes that originated from noncoding DNA regions demonstrates the existence of a "motherless" origination process for new genes. However, the features, distributions, expression profiles, and origin modes of these genes in humans seem to support the notion that their origin is not a purely "motherless" process; rather, these genes arise preferentially from genomic regions encoding preexisting precursors with gene-like features. In such a case, the gene loci are typically not brand new. In this short review, we will summarize the definition and features of human de novo genes and clarify their process of origination from ancestral non-coding genomic regions. In addition, we define the favored precursors, or "hopeful monsters," for the origin of de novo genes and present a discussion of the functional significance of these young genes in brain development and tumorigenesis in humans. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.

Analyzing Apomorphine-Mediated Effects in a Cell Model for Parkinson's Disease with Partial Least Squares Structure Equation Modeling

Genome-wide gene expression data for cell model of Parkinson's disease (PD) have considerably improved our understanding of the underlying molecular mechanisms involved in cell death during PD neurodegeneration. Apomorphine (APOM), a nonselective dopamine agonist, has been used to treat patients with advanced PD showing no response to levodopa or other dopamine agonists. Although APOM plays a role as a free radical scavenger with neuroprotective effect, it has been reported that long-term use of APOM in PD treatment brings about side effects such as nausea and orthostatic hypotension. For safe use of APOM in PD treatment, it is crucial to understand the underlying molecular mechanisms of APOM in PD. In this study, two groups of microarray data including PD cell model and APOM added PD cell model were used to survey mediation effects of APOM in PD cell model. Mediation analysis between disease genes obtained from PD cell model and drug genes obtained from APOM added PD cell model was carried out with shortest path model on KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways and partial least squares structure equation modeling. Our results suggest that drug genes responding to APOM might contribute to negative regulation of disease genes by direct or indirect ways.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.