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Heterozygosity: An expanding role in proteomics

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

The human genome sequence provides the framework for understanding the biology of human cell function. The next step is to intensify the investigation of protein function in the context of complex biological systems. Cellular functions are carried out by molecular complexes acting in concert rather than by single molecules or single reactions. Parallels have been drawn between scale-free non-biologic networks and functionally interconnected metabolic pathways in the cell. Modeling of metabolic networks, in which functional modules or subnetworks represent individual related pathways, will lead to the prediction of protein function in the larger context of a complex system. Depending on the robustness of these metabolic networks, single-gene defects alone or in combination with other gene defects and the environment have the potential for invoking a spectrum of alterations in the integrity of a given network. The overall purpose of this review is to highlight the importance of simple heterozygosity for one pathogenic mutation or combinatorial heterozygosity for two or more mutations within or between individual genes in altering the stability of metabolic networks. Several forms of heterozygosity are considered, e.g., intra- and interallelic heterozygosity and double heterozygosity. The concepts of synergistic heterozygosity, loss of heterozygosity, and mitochondrial DNA heteroplasmy also are discussed in relation to the quantitative effects of coexisting mutations on the phenotypic expression of disease.

Original languageEnglish
Pages (from-to)51-63
Number of pages13
JournalMolecular Genetics and Metabolism
Volume74
Issue number1-2
DOIs
StatePublished - 2001

Keywords

  • Carnitine palmitoyltransferase II deficiency
  • Complex phenotypes
  • Genotype-phenotype correlation
  • Heterozygosity
  • Metabolic networks
  • Myoadenylate deaminase deficiency
  • Myophosphorylase deficiency
  • Proteomics

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