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Viewed As a Clock of Macro-Evolution Biology Direct BioMed Central Hypothesis Open Access Genome increase as a clock for the origin and evolution of life Alexei A Sharov* Address: Laboratory of Genetics, National Institute on Aging (NIA/NIH), 333 Cassell Dr., Baltimore, MD 21224, USA Email: Alexei A Sharov* - [email protected] * Corresponding author Published: 12 June 2006 Received: 30 May 2006 Accepted: 12 June 2006 Biology Direct 2006, 1:17 doi:10.1186/1745-6150-1-17 This article is available from: http://www.biology-direct.com/content/1/1/17 © 2006 Sharov; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: The size of non-redundant functional genome can be an indicator of biological complexity of living organisms. Several positive feedback mechanisms including gene cooperation and duplication with subsequent specialization may result in the exponential growth of biological complexity in macro-evolution. Results: I propose a hypothesis that biological complexity increased exponentially during evolution. Regression of the logarithm of functional non-redundant genome size versus time of origin in major groups of organisms showed a 7.8-fold increase per 1 billion years, and hence the increase of complexity can be viewed as a clock of macro-evolution. A strong version of the exponential hypothesis is that the rate of complexity increase in early (pre-prokaryotic) evolution of life was at most the same (or even slower) than observed in the evolution of prokaryotes and eukaryotes. Conclusion: The increase of functional non-redundant genome size in macro-evolution was consistent with the exponential hypothesis. If the strong exponential hypothesis is true, then the origin of life should be dated 10 billion years ago. Thus, the possibility of panspermia as a source of life on earth should be discussed on equal basis with alternative hypotheses of de-novo life origin. Panspermia may be proven if bacteria similar to terrestrial ones are found on other planets or satellites in the solar system. Reviewers: This article was reviewed by Eugene V. Koonin, Chris Adami and Arcady Mushegian. Open peer review minimum length of encoding algorithm, etc. [1]. How- Reviewed by Eugene V. Koonin, Chris Adami and Arcady ever little is known about the laws of evolution in com- Mushegian. For the full reviews, please go to the Review- plex systems. One of them is the Moore's law which states ers' comments section. that the complexity and performance of certain systems associated with human technology (e.g., volume of pub- Introduction lished scientific information, number of nodes in compu- The phenomenon of system complexity attracts attention ter networks, etc.) increases exponentially [3]. It is of scientists from different areas of expertise from biolo- interesting if this law can be applied to other complex sys- gists and economists to mathematicians and cyberneti- tems, e.g. to the large-scale evolution of living organisms. cians [1,2]. Numerous approaches has been implemented to quantify complexity using estimates of probability, Page 1 of 10 (page number not for citation purposes) Biology Direct 2006, 1:17 http://www.biology-direct.com/content/1/1/17 Although the global increase of genome sizes from bacte- number of genes [12]. Thus, a better interpretation of the ria to mammals is a well-known fact [4], no attempt has Lynch-Conery phenomenon is that large effective popula- been made to model this process. The total genome size tion size in prokaryotes was one of the constraints that appeared highly variable among organisms with the same slowed the increase of their genome size in evolution. level of morphological complexity, a phenomenon known as a C-value paradox [5]. These variations in The exponential pattern of genome increase can be genome size are caused mostly by gene duplication, poly- expected only in organisms that were most successful in ploidy, and accumulation/deletion of intergenic DNA [6]. overcoming organizational constraints. If all groups of Thus, genome size was mostly studied as an indicator of organisms were equally successful in overcoming con- insertion-deletion frequencies in different species [7] straints, there would be no small genomes left. The only rather than a measure of complexity. way to trace the increase of genome sizes is to compare groups of organisms that were most successful in over- Biological complexity was recently defined by Adami et al. coming organizational constraints, with most ancient [8] as a size of functional and non-redundant genome. groups, whose genomes did not increase due to con- This measure does not depend on duplications, inser- straints. tions, or deletions of non-functional or redundant sequences, and therefore it is more stable in evolution In this paper I address the problem of the rate of complex- than the total genome size. The dynamics of genome ity increase in evolving living systems using Adami's [8] increase in evolution can be modelled on the basis of definition. Regression of the log functional genome size known mechanisms which appear to act as positive feed- versus time of origin in major groups of organisms is con- backs. First, the theory of a hypercycle considers a genome sistent with the exponential hypothesis and indicates a as a community of mutually beneficial (i.e., cross-cata- 7.8-fold increase of complexity per 1 billion years. An lytic) self-replicating elements [9]. For example, a gene interesting question is whether this rate of complexity that improves proof-reading increases the replication increase can be extrapolated to the early (pre-prokaryotic) accuracy of all other genes. These benefits are applied not evolution of life, which I call a strong exponential hypoth- just to existing genes but also to genes that may appear in esis. If this strong hypothesis is true, then the origin of life the future. Thus, already existing genes can help new genes should be dated ca. 10 billion years ago, i.e., before the to become established, and as a result, bigger genomes formation of earth and solar system. I discuss potential will grow faster than small ones. Second, new genes usu- arguments against the strong exponential hypothesis and ally originate via duplication and recombination of show that they are not conclusive. already existing genes in the genome [4,10]. Thus, larger genomes provide more diverse initial material for the Results emergence of new genes. Third, large genomes support The size of functional non-redundant genome can be more diverse metabolic networks and morphological ele- quantified using the Shannon's information measure [8], ments (at various scales from cell components to tissues but currently this approach is not feasible because it and organs) than small genomes, which in turn may pro- would require unavailable information on fitness weight vide new functional niches for novel genes. These three of each nucleotide in the genomic DNA. A simpler mechanisms of positive feedback may be sufficient to method is to consider functional genome as the size of cause an exponential growth in the size of functional non- coding and regulatory regions as they are known today. redundant genome. The size of the functional and non-redundant fraction of In some groups of organisms, the increase of genome size genomes gradually increased in evolutionary time (Fig. may be limited by organisational constraints. For exam- 1). Mammals (mouse, rat, and human), which appeared ple, prokaryotes have a small genome most likely because just recently in earth history, have a genome of ca. 3.2 × they had never developed mechanisms for preserving the 109 bp, however only 5% of it is conserved between spe- integrity of a larger genome (e.g., better proofreading and cies [13]. Conserved regions are definitely functional but mitosis). Lynch and Conery [11] showed that the effective there may be additional functional regulatory regions that population size, Ne, is negatively related to the total are species-specific. These regions can be identified based genome size and number of genes, and explained this on the absence of transposons, because transposons that relationship by an increased genetic drift in small popula- are inserted in functional regions would interfere with tions. However it is hard to agree with their interpretation normal gene regulation and eventually disappear due to of these facts that genome complexity "emerged passively natural selection [14]. Transposon-free regions of 5 and in response to the long-term population-size reductions 10 kb account for 20%, and 12% genome size, respec- that accompanied increases in organism size". Positive tively [14]. If we take 15% as a rough estimate, then the selection may be equally important in the increase of the size of functional and non-redundant genome in mam- Page 2 of 10 (page number not for citation purposes) Biology Direct 2006, 1:17 http://www.biology-direct.com/content/1/1/17 eukaryotes indeed had genome size comparable to con- 10 temporary parasitic species. Comparison of protein Mammals sequences indicates that the divergence time of archaebac- Fish teria, eubacteria, and eukaryotes occurred from 3.1 to 3.8 Worms billion years ago [25]. Eukaryotes I have not included plants into this graph for the follow- ing two reasons. First, their genomes are often highly redundant due to polyploidy [4], which makes it difficult 5 Prokaryotes to estimate the size of the functional non-redundant frac- tion. Second, functional non-redundant genomes in plants did not increase as fast as in vertebrates, and our Total genome goal was to trace the genomes in best performing groups Log Genome Size, bp Size, Genome Log Functional non-redundant genome of organisms.
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