Dataset Information

Meta-coexpression conservation analysis of microarray data: a "subset" approach provides insight into brain-derived neurotrophic factor regulation.

ABSTRACT:

Background

Alterations in brain-derived neurotrophic factor (BDNF) gene expression contribute to serious pathologies such as depression, epilepsy, cancer, Alzheimer's, Huntington and Parkinson's disease. Therefore, exploring the mechanisms of BDNF regulation represents a great clinical importance. Studying BDNF expression remains difficult due to its multiple neural activity-dependent and tissue-specific promoters. Thus, microarray data could provide insight into the regulation of this complex gene. Conventional microarray co-expression analysis is usually carried out by merging the datasets or by confirming the re-occurrence of significant correlations across datasets. However, co-expression patterns can be different under various conditions that are represented by subsets in a dataset. Therefore, assessing co-expression by measuring correlation coefficient across merged samples of a dataset or by merging datasets might not capture all correlation patterns.

Results

In our study, we performed meta-coexpression analysis of publicly available microarray data using BDNF as a "guide-gene" introducing a "subset" approach. The key steps of the analysis included: dividing datasets into subsets with biologically meaningful sample content (e.g. tissue, gender or disease state subsets); analyzing co-expression with the BDNF gene in each subset separately; and confirming co- expression links across subsets. Finally, we analyzed conservation in co-expression with BDNF between human, mouse and rat, and sought for conserved over-represented TFBSs in BDNF and BDNF-correlated genes. Correlated genes discovered in this study regulate nervous system development, and are associated with various types of cancer and neurological disorders. Also, several transcription factor identified here have been reported to regulate BDNF expression in vitro and in vivo.

Conclusion

The study demonstrates the potential of the "subset" approach in co-expression conservation analysis for studying the regulation of single genes and proposes novel regulators of BDNF gene expression.

SUBMITTER: Aid-Pavlidis T

PROVIDER: S-EPMC2748098 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:S10-spc-alpha is a 17.5 kb cluster of 32 genes encoding ribosomal proteins. This locus has an unusual composition and organization in Leptospira interrogans. We demonstrate the highly conserved nature of this region among diverse Leptospira and show its utility as a phylogenetically informative region. Comparative analyses were performed by PCR using primer sets covering the whole locus. Correctly sized fragments were obtained by PCR from all L. interrogans strains tested for each primer set indicating that this locus is well conserved in this species. Few differences were detected in amplification profiles between different pathogenic species, indicating that the S10-spc-alpha locus is conserved among pathogenic Leptospira. In contrast, PCR analysis of this locus using DNA from saprophytic Leptospira species and species with an intermediate pathogenic capacity generated varied results. Sequence alignment of the S10-spc-alpha locus from two pathogenic species, L. interrogans and L. borgpetersenii, with the corresponding locus from the saprophyte L. biflexa serovar Patoc showed that genetic organization of this locus is well conserved within Leptospira. Multilocus sequence typing (MLST) of four conserved regions resulted in the construction of well-defined phylogenetic trees that help resolve questions about the interrelationships of pathogenic Leptospira. Based on the results of secY sequence analysis, we found that reliable species identification of pathogenic Leptospira is possible by comparative analysis of a 245 bp region commonly used as a target for diagnostic PCR for leptospirosis. Comparative analysis of Leptospira strains revealed that strain H6 previously classified as L. inadai actually belongs to the pathogenic species L. interrogans and that L. meyeri strain ICF phylogenetically co-localized with the pathogenic clusters. These findings demonstrate that the S10-spc-alpha locus is highly conserved throughout the genus and may be more useful in comparing evolution of the genus than loci studied previously.