Complexity as the new evolutionary biology dimension

The post- genomic era brought us into a new dimension, and anyone started to believe that the most intimate secrets of biology were hiding in a flood of literal strings packed into fasta files. Although we can still believe this, many recent papers are telling us that this story is much more complicated, and a change of strategy may be needed. The growing effort to understand the regulatory networks, underlying  many biological processes, brought us the evidence that the interaction between genotype and phenotype displays a non- linear relation. Many phenotypes arise from the interaction of several genes, and the singular contribution of each gene is not immediately evaluable in a phenotype analysis, since not all the genes contribute to the phenotype in the same way. There are three aspects of gene regulation that we may have to re- consider: the logic of gene regulation, the evolution of genotypes, and the physical structure of genomes.

The logic of gene regulation: gene networks as complex dynamical systems.

We can consider the interacting genes as constituents of a system showing a complex behaviour. A complex system, whose intrinsic properties are given by the sum of any single gene’s characteristics, and the extrinsic properties arise from the interaction of the components of the system: the genes. Phenotype may thus be the expression of the extrinsic properties of this complex genetic system. Considering Von Bertalanffy’s definition, we cannot fully understand the emergent features of a given system from the mere analysis of its components. So, in a reverse genetics approach, we cannot properly forecast a phenotype if we don’t consider the whole gene network and its complex interactions in our analysis. Furthermore, these genetic systems undergo to a change over time, since gene expression changes in relation of the cell state, developmental stage or environmental conditions, and the genotype changes throughout generations in reason of the evolution. This means that gene networks show up as dynamic, and they can be considered as complex dynamical systems.

I suggest to have a look to a couple of amazing papers of recent publication. Just one week ago, Zhang and Ho at the University of Michigan published this paper, that describes the characteristics of gene networks controlling the complex traits in yeast and illustrates the high potential of genome- wide reverse genetics and its deep relationship with complex systems. In evo- devo, the analysis or modelling of complex gene networks to understand how developmental processes evolve, it is a well-known practice. In this amazing paper, for instance, researchers from Autonomous University of Barcelona (UAB) and University of Helsinki provide the first three-dimensional simulation of the evolution of morphology, by integrating the mechanisms of genetic regulation that take place during embryo development. Different genes shape a complex phenotype, that is the result of their interaction.

The evolution of genotypes: criticism toward neo-Darwinism scores one point

Neo-Darwinism claims that genetic and phenotypic variation are linked by simple relations, and complex traits are the result of the sum of single gene contribution. This has been contested in many morphological variation studies, where the evidences lead to consider the relations between genotype and phenotype as anything but simple. Another example could come from multifactorial genetic diseases, such as the Chron’s, where the contribution of the many genes found to be potentially involved in determining the pathological phenotype is not really clear. The feeling is that neo-Darwinian approaches cannot fully explain how  a complex phenotype is selected in evolution.

In fact, if we can consider the phenotype as the expression of the emergent properties of a complex dynamical gene system, we should expect that selection intervene on these properties, since the fitness is determined by the optimization of phenotype to environmental conditions. Evolution may occur at a higher complexity level as described in this paper about epistasis and its role in protein evolution.

The physical structure of genomes.

The spatial organization of eukaryotic genome is collecting a growing interest, since there are many proofs indicating a functional and regulatory meaning of three-dimensional chromatin structure. Classically, the role of chromatin has been limited to his structural function, as in protecting DNA from mechanical stress. Actually, a regulatory role of histones has been extensively studied regarding their acetylation effects in gene regulation is one of the fundamentals of epigenetics. But, a comprehension of the role of 3D chromatin structure is a pretty recent and is collecting a growing interest. To have an idea of how much this field is gaining the attention of scientific community, we can just have a quick look to Pubmed. If we search for “Chromatin structure gene regulation” and divide the results into 5 years long time windows, we note that between the 1998 and 2003, 1378 papers have been published about this topic. The number rises to 2651 during the 2003- 2008 span. Between 2008 and 2013, 3192 papers have been published. It’s a really bold statistics, but clear enough to explain how much the interest is growing in this field. At this very moment, the relation between chromatin structure and long non-coding RNA, the role of 3D chromatin structure in cell differentiation, and its meaning in diseases are the hottest topics. In a very recent paper published on April 30th, for instance, a group in Montreal uses chromatin three-dimensional structure to classify human leukemia, proving that the relation between three-dimensional structure and phenotype is really deep.

The physical organization of genomes represents a strong phenotype determinant and the evolution of chromatin organization it’s definitely crucial in matter of phenotype plasticity, cell differentiation and evolution of multicellularity.

Biological evolution as evolution of complex systems.

With a high approximation, we could consider two main kinds of complexity. A “logical” complexity, given by the interactions between genes in genomes and a “physical” or “topological” complexity, given by the spatial organization of genomes. Organisms are sets of different, interlinked and nested complex systems, and any dynamical process, from physiology to development, may be described by a mathematical system dynamics approach. Evolution in itself is a matter of how complex systems change over generations, and the most of evolutionary considerations should me made in the light of complexity.


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