Application of proteomics to ecology and population biology

Research output: Contribution to journalShort surveypeer-review

59 Scopus citations

Abstract

Proteomics is a relatively new scientific discipline that merges protein biochemistry, genome biology and bioinformatics to determine the spatial and temporal expression of proteins in cells, tissues and whole organisms. There has been very little application of proteomics to the fields of behavioral genetics, evolution, ecology and population dynamics, and has only recently been effectively applied to the closely allied fields of molecular evolution and genetics. However, there exists considerable potential for proteomics to impact in areas related to functional ecology; this review will introduce the general concepts and methodologies that define the field of proteomics and compare and contrast the advantages and disadvantages with other methods. Examples of how proteomics can aid, complement and indeed extend the study of functional ecology will be discussed including the main tool of ecological studies, population genetics with an emphasis on metapopulation structure analysis. Because proteomic analyses provide a direct measure of gene expression, it obviates some of the limitations associated with other genomic approaches, such as microarray and EST analyses. Likewise, in conjunction with associated bioinformatics and molecular evolutionary tools, proteomics can provide the foundation of a systems-level integration approach that can enhance ecological studies. It can be envisioned that proteomics will provide important new information on issues specific to metapopulation biology and adaptive processes in nature. A specific example of the application of proteomics to sperm ageing is provided to illustrate the potential utility of the approach.

Original languageEnglish (US)
Pages (from-to)200-206
Number of pages7
JournalHeredity
Volume100
Issue number2
DOIs
StatePublished - Feb 2008

Keywords

  • Ecology
  • Population genetics
  • Proteomics

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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