Genetic Regulatory Network Analysis for App Based on Genetical Genomics Approach.
Saved in:
| Title: | Genetic Regulatory Network Analysis for App Based on Genetical Genomics Approach. |
|---|---|
| Authors: | Wang, Xusheng (AUTHOR), Chen, Ying (AUTHOR), Wang, Xiaodong (AUTHOR), Lu, Lu (AUTHOR) |
| Source: | Experimental Aging Research. Jan-Mar2010, Vol. 36 Issue 1, p79-93. 15p. 1 Diagram, 3 Graphs. |
| Subjects: | Genomics, Genetic research, Protein precursors, Genetic regulation, Alzheimer's disease |
| Abstract: | A number of studies have shown that amyloid precursor protein (App) plays a critical role in Alzheimer's disease (AD); however, little is known about the genetic regulatory network. In this study, the authors combined array analysis and quantitative trait loci (QTL) mapping to characterize the genetic variation and genetic regulatory network for App using hippocampus of BXD recombinant inbred (RI) mice. The variation in expression level of App is conspicuous across the 78 BXD RI strains. Moreover, the expression level of App is significantly higher in DBA/2J than the level in C57BL/6J (p < .001). Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis has further confirmed the significant difference between the two parental strains C57BL/6J and DBA/2J. The authors performed an interval mapping for App gene expression and found that it is cis regulated with highly significant likelihood-ratio statistic (LRS) score (LRS = 19; p < .05). Four SNPs and two InDels (insertions or deletions) were identified in the promoter, and one of the SNPs is located in the pax2 motif. Genetic regulatory network analysis showed that App coregulated with many AD-related genes, including Gsk3b, Falz, Mef2a, Tlk2, Rtn, and Prkca. The genetical genomics approach demonstrates the importance and the potential power of the expression quantitative trait loci (eQTL) studies in identifying regulatory network that contribute to complex traits, such as AD. [ABSTRACT FROM AUTHOR] |
| Copyright of Experimental Aging Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | A number of studies have shown that amyloid precursor protein (App) plays a critical role in Alzheimer's disease (AD); however, little is known about the genetic regulatory network. In this study, the authors combined array analysis and quantitative trait loci (QTL) mapping to characterize the genetic variation and genetic regulatory network for App using hippocampus of BXD recombinant inbred (RI) mice. The variation in expression level of App is conspicuous across the 78 BXD RI strains. Moreover, the expression level of App is significantly higher in DBA/2J than the level in C57BL/6J (p < .001). Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis has further confirmed the significant difference between the two parental strains C57BL/6J and DBA/2J. The authors performed an interval mapping for App gene expression and found that it is cis regulated with highly significant likelihood-ratio statistic (LRS) score (LRS = 19; p < .05). Four SNPs and two InDels (insertions or deletions) were identified in the promoter, and one of the SNPs is located in the pax2 motif. Genetic regulatory network analysis showed that App coregulated with many AD-related genes, including Gsk3b, Falz, Mef2a, Tlk2, Rtn, and Prkca. The genetical genomics approach demonstrates the importance and the potential power of the expression quantitative trait loci (eQTL) studies in identifying regulatory network that contribute to complex traits, such as AD. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 0361073X |
| DOI: | 10.1080/03610730903418729 |
