Insights into the evolutionary features of human neurodegenerative diseases

PLoS One. 2012;7(10):e48336. doi: 10.1371/journal.pone.0048336. Epub 2012 Oct 30.

Abstract

Comparative analyses between human disease and non-disease genes are of great interest in understanding human disease gene evolution. However, the progression of neurodegenerative diseases (NDD) involving amyloid formation in specific brain regions is still unknown. Therefore, in this study, we mainly focused our analysis on the evolutionary features of human NDD genes with respect to non-disease genes. Here, we observed that human NDD genes are evolutionarily conserved relative to non-disease genes. To elucidate the conserved nature of NDD genes, we incorporated the evolutionary attributes like gene expression level, number of regulatory miRNAs, protein connectivity, intrinsic disorder content and relative aggregation propensity in our analysis. Our studies demonstrate that NDD genes have higher gene expression levels in favor of their lower evolutionary rates. Additionally, we observed that NDD genes have higher number of different regulatory miRNAs target sites and also have higher interaction partners than the non-disease genes. Moreover, miRNA targeted genes are known to have higher disorder content. In contrast, our analysis exclusively established that NDD genes have lower disorder content. In favor of our analysis, we found that NDD gene encoded proteins are enriched with multi interface hubs (party hubs) with lower disorder contents. Since, proteins with higher disorder content need to adapt special structure to reduce their aggregation propensity, NDD proteins found to have elevated relative aggregation propensity (RAP) in support of their lower disorder content. Finally, our categorical regression analysis confirmed the underlined relative dominance of protein connectivity, 3'UTR length, RAP, nature of hubs (singlish/multi interface) and disorder content for such evolutionary rates variation between human NDD genes and non-disease genes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • 3' Untranslated Regions / genetics
  • Computational Biology*
  • Evolution, Molecular*
  • Gene Expression Regulation
  • Humans
  • MicroRNAs / genetics
  • MicroRNAs / metabolism
  • Neurodegenerative Diseases / genetics*
  • Neurodegenerative Diseases / metabolism*
  • Proteins / genetics
  • Proteins / metabolism
  • Regression Analysis

Substances

  • 3' Untranslated Regions
  • MicroRNAs
  • Proteins

Grants and funding

This work was supported by the Department of Science & Technology. Government of India (www.dst.gov.in). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.