, Volume 91, Issue 11, pp 505–518 | Cite as

The evolutionary processes of mitochondrial and chloroplast genomes differ from those of nuclear genomes

  • Helena KorpelainenEmail author


This paper first introduces our present knowledge of the origin of mitochondria and chloroplasts, and the organization and inheritance patterns of their genomes, and then carries on to review the evolutionary processes influencing mitochondrial and chloroplast genomes. The differences in evolutionary phenomena between the nuclear and cytoplasmic genomes are highlighted. It is emphasized that varying inheritance patterns and copy numbers among different types of genomes, and the potential advantage achieved through the transfer of many cytoplasmic genes to the nucleus, have important implications for the evolution of nuclear, mitochondrial and chloroplast genomes. Cytoplasmic genes transferred to the nucleus have joined the more strictly controlled genetic system of the nuclear genome, including also sexual recombination, while genes retained within the cytoplasmic organelles can be involved in selection and drift processes both within and among individuals. Within-individual processes can be either intra- or intercellular. In the case of heteroplasmy, which is attributed to mutations or biparental inheritance, within-individual selection on cytoplasmic DNA may provide a mechanism by which the organism can adapt rapidly. The inheritance of cytoplasmic genomes is not universally maternal. The presence of a range of inheritance patterns indicates that different strategies have been adopted by different organisms. On the other hand, the variability occasionally observed in the inheritance mechanisms of cytoplasmic genomes reduces heritability and increases environmental components in phenotypic features and, consequently, decreases the potential for adaptive evolution.


Mitochondrial Genome Chloroplast Genome Nuclear Genome Plastid Genome Inheritance Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I am grateful to the anonymous referees for fruitful comments, which have helped me to improve this article considerably.


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© Springer-Verlag 2004

Authors and Affiliations

  1. 1.Department of Applied BiologyUniversity of HelsinkiHelsinkiFinland

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