Genes and homology in nervous system evolution: comparing gene functions, expression patterns, and cell type molecular fingerprints

Theory Biosci. 2005 Nov;124(2):185-97. doi: 10.1007/BF02814483. Epub 2005 Sep 22.

Abstract

The evolution of the nervous system is one of the most fascinating, but also most nebulous fields of homology research. We do not know for example whether the last common ancestors of human, squid, and fly already possessed an elaborate brain and eyes, or rather had a simple, diffuse nervous system. Nevertheless, in the past decade molecular data has greatly advanced our understanding of bilaterian nervous system evolution. In this methodological review, I explain the four levels on which molecular genetic studies advance the quest for homologies between animal nervous systems. (I) Bioinformatic homology research elucidates the evolutionary history of gene families relevant for nervous system evolution such as the opsin superfamily. It tells us when and in what order genes and their functions have emerged. Based on this, we can (II) infer the organismal complexity of some remote ancestor from the functional diversity of its reconstructed proteome. (III) Most common in molecular homology research has been the comparison of expression patterns of developmental control genes. This approach matches and aligns embryonic regions along the body axes, between remote bilaterians. It does not tell us much, however, about the complexity of structures that developed from these regions in Urbilateria. (IV) This is overcome by a novel variant of molecular homology research, the comparison of cell types. Here, a similar "molecular fingerprint" of cells is taken as indication of cross-bilaterian homology. This approach makes it possible to reconstruct the cell-type repertoire of the urbilaterian nervous system.

MeSH terms

  • Animals
  • Biological Evolution*
  • Computational Biology
  • Gene Expression Regulation*
  • Humans
  • Nervous System / cytology*
  • Nervous System / metabolism*
  • Nucleotide Mapping