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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An EarthWinian Genesis Synthesis

B. Systems Biology Unites: EvoDevo, Genomes, Cells, Networks, Symbiosis, Homology, Inherency

Nuno de la Rosa, Laura and Gerd Muller, eds.. Evolutionary Developmental Biology: A Reference Guide. International: Springer, 2021. The editors are biophilosophers at Complutense University of Madrid, and at the University of Vienna. Muller is also president of the Konrad Lorenz Institute. The 1260 page volume rates as the most comprehensive topical source to date. It is arranged into ten main aspects such as Philosophy of EvoDevo, Evo-Devo of Basic Mechanisms, Vertebrate Evo-Devo, EvoDevo and Population Genetics and Extensions of EvoDevo. Some 86 chapters inform about Developmental Homology, Convergence (G. McGhee), Evo-Devo Lessons Learned from Honeybees, Inherency (S. Newman), Evo-Devo’s Contributions to the Extended Evolutionary Synthesis (G. Muller), and Evo-Devo of Language and Cognition.

In regard then, as these many contributions now possible in the third 21st century decade proceed from conceptual views and basic biological features all the way to social behaviors and linguistic cognition, an impression occurs in broad survey that life’s long arduous emergence can well take on a developmental guise of a quickening gestation.

Nurse, Paul. Biology as an Organized System. www.guardian.co.uk/science/video/2010/nov/05/paul-nurse-life-information-networks. We note this 11 minute clip from November 12, 2010 by the Nobel Laureate biologist for several reasons. (Also access via keywords) This 21st century systems turn, it is said, now ought to put a greater emphasis to informational and self-organization qualities. In accord with its vernacular, DNA is a “digital storage device,” life is a “chemical machine,” cells are “logical computational machines” and so on, for mechanism rules. But then near its conclusion, Nurse suddenly avers that this is in fact a male, one particle at a time, myopia. Going forward, if to truly perceive and appreciate life’s viable networks, a “woman’s” integrative, systems, holistic vision is imperative. See also his 2008 article “Life, Logic and Information” in Nature (454/424).

O’Malley, Maureen and John Dupre. Fundamental Issues in Systems Biology. BioEssays. 27/12, 2005. University of Exeter philosophers consider a necessary conceptual basis for the transition from molecular reduction to an equal emphasis on global complexity and dynamic networks in genomes and cellular metabolism.

O’Malley, Maureen, et al. A Philosophical Perspective on Evolutionary Systems Biology. Biological Theory. 10/1, 2015. O,Malley, University of Sydney, Orkun Soyer, University of Warwick, and Mark Siegal, NYU, introduce a special issue on this expanded perspective. With a systems biology integration underway since circa 2000, a further phase would be to reconsider and embellish life’s long developmental course by a similar synthesis. See also Explanatory Integration Challenges in Evolutionary Systems Biology by Sara Green, et al, and The Comet Cometh: Evolving Developmental Systems by Jaeger, Johannes Jaeger, et al, search each name.

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB’s progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology. (Abstract)

Ochoa, Carlos and Diego Rasskin-Gutman. Evo-Devo Mechanisms Underlying the Continuum between Homology and Homoplasy. Journal of Experimental Zoology B. Online February, 2015. As years of research seem to be reaching a synthesis phase, in this journal edited by Gunter Wagner, National Autonomous University of Mexico, and University of Valencia evolutionary biologists proceed to join and clarify these terms, along with parallelism, convergence, and more. The paper opens with Richard Owen’s “archetype,” a later brush with a metaphysical “orthogenesis,” and so on as life’s evolution in the 21st century increasingly takes on the actual guise of a universal developmental gestation.

The different manifestations of equivalence and similarity in structure throughout evolution suggest a continuous and hierarchical process that starts out with the origin of a morphological novelty, unit, or homologue. Once a morphological unit has originated, its properties change subsequently into variants that differ, in magnitude, from the original properties found in the common ancestor. We will look into the nature of morphological units and their degrees of modification, which will provide the starting point for restructuring the concept of “homology,” keeping the use of homology as the identity of an anatomical part, and homogeny, as the specific variation of that anatomical part during evolution. Finally, we will propose a hierarchical model that places homology, homogeny, homoplasy, and parallelism, as distinct phenomena within an evolutionary continuum. (Abstract excerpts)

Ogura, Takehiko and Wolfgang Busch. Genotypes, Networks, Phenotypes: Moving Toward Plant Systems Genetics. Annual Review of Cell and Developmental Biology. 32/103, 2016. Vienna Biocenter, Gregor Mendel Institute, Austrian Academy of Sciences researchers scope out ways to perceive botanical flora by way of the latest complex network dynamics.

One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotype-to-phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. (Abstract)

Padilla, Dianna and Brian Tsukimura. A New Organismal Systems Biology: How Animals Walk the Tight Rope between Stability and Change. Integrative & Comparative Biology. 54/2, 2014. SUNY Stony Brook, and California State University naturalists introduce a special section of presentations from the ICB Society 2013 annual meeting on this “grand challenge” to their field. Typical papers are A System Approach to Integrative Biology, and Developmental Change in the Function of Movement Systems.

Our ability to predict which features of complex integrated systems provide the capacity to be robust in changing environments is poorly developed. A predictive organismal biology is needed, but will require more quantitative approaches than are typical in biology, including complex systems-modeling approaches common to engineering. This new organismal systems biology will have reciprocal benefits for biologists, engineers, and mathematicians who address similar questions, including those working on control theory and dynamical systems biology, and will develop the tools we need to address the grand challenge questions of the 21st century. (Abstract)

Palsson, Bernhard. Systems Biology. Cambridge: Cambridge University Press, 2006. An introduction to the encompassing shift from a 20th century reduction to a 21st century integrative approach. This new paradigm involves four steps – identify components parts, prepare “wiring diagrams” of their mainly genetic interactions, mathematically describe such reconstructed networks, and use these models to analyze, interpret and predict experimental outcomes.

Pang, Tin Yau and Sergei Maslov. Universal Distribution of Component Frequencies in Biological and Technological Systems. Proceedings of the National Academy of Sciences. 110/15, 2013. Brookhaven National Laboratory biologists contribute to the growing experimental and theoretical recognition that life’s evolution, each creaturely instance, and our civil society repeats and iterates the same dynamic fractal self-organization at every degree, time and place. See also in regard by the authors “Toolbox Model of Evolution of Metabolic Pathways on Networks of Arbitrary Topology” in PLoS Computational Biology, along with Jacopo Grilli, et al, “Joint Scaling Laws in Functional and Evolutionary Categories in Prokaryotic Genomes” in Nucleic Acids Research (40/2, 2011) and Marco Lagomarsino, et al “Universal Features in the Genome-Level Evolution of Protein Domains” in Genome Biology (10/R12, 2009). Maslov leads a “KBase” team based at BNL, Cold Spring Harbor Laboratory, and Yale University trying to “integrate everything we can learn about plants, microbes, and metagenomics from the genetic and molecular to the organism and systems level,” see second quote. And where do all these whole repetitive propensities come from, who are we to learn this, what great discovery might they bode?

Bacterial genomes and large-scale computer software projects both consist of a large number of components (genes or software packages) connected via a network of mutual dependencies. Components can be easily added or removed from individual systems, and their use frequencies vary over many orders of magnitude. We study this frequency distribution in genomes of ~500 bacterial species and in over 2 million Linux computers and find that in both cases it is described by the same scale-free power-law distribution with an additional peak near the tail of the distribution corresponding to nearly universal components. We argue that the existence of a power law distribution of frequencies of components is a general property of any modular system with a multilayered dependency network. (Abstract, this paper)

In prokaryotic genomes the number of transcriptional regulators is known to be proportional to the square of the total number of protein-coding genes. A toolbox model of evolution was recently proposed to explain this empirical scaling for metabolic enzymes and their regulators. According to its rules, the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger “universal” network formed by the union of all species-specific networks. (Abstract, PLoS article)

The Department of Energy Systems Biology Knowledgebase (KBase) is an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses on a scalable computing infrastructure, and model interactions in microbes, plants, and their communities. KBase provides an open, extensible framework for secure sharing of data, tools, and scientific conclusions in predictive and systems biology. (www.kbase.us)

Perrimon, Norbert and Naama Barkai. The Era of Systems Developmental Biology. Current Opinion in Genetics & Development. 21/6, 2011. An introduction to a special issue of the Genetics of System Biology by the Harvard Medical School researchers. A typical article might be “Scaling of Morphogen Gradients” by Danny Ben-Zvi, et al. In this issue and journal “development” often pertains to embryological stages, as the “systems” vista once more revitalizes and reunites this archetypal phase.

Developmental biology, fueled by advances in genomics, proteomics, imaging, and applications of physics and mathematical modeling, is yet undergoing another renaissance – entering the era of ‘Systems Developmental Biology’. The goal of ‘Systems Developmental Biology’ is to go beyond our current understanding of what a single gene, or a few connected parts, do in a biological context. The challenge is to become more systematic, unbiased and quantitative in the analysis of developmental questions. Thus, we now want to identify all the parts and pathways involved and quantify some of the key parameters to build mathematical and computational models that describe and predict the behavior of the systems. (681)

Peter, Isabelle and Eric Davidson. Genomic Control Process: Development and Evolution. Cambridge, MA: Academic Press, 2015. A CalTech biology professor and the geneticist (1937-2015, search) who was the founding theorist of gene regulatory networks provide a consummate volume to date of this major expansion of active genetic phenomena.

Chapter 1 explains different levels of control affecting developmental gene expression in animal cells, and an overview of the physical nature of the regulatory genome. The book goes on to provide in depth understandings of GRNs, how they generate the regulatory conditions, cis-regulatory functions operating at the network nodes, and the dynamics of transcriptional activity in development. The next Chapters apply network theory to embryonic development of all major kinds; development of adult body parts and organs; and to cell fate specification. Chapter 6 examines the conceptual richness that has derived from various approaches to predictive, quantitative models of GRNs and GRN circuits. In The final section the notes applications to bilaterian evolution, including the underlying explanation of hierarchical animal phylogeny, and more. (Publisher excerpt)

Priami, Corrado. Algorthmic Systems Biology. Communications of the ACM. May, 2009. The University of Trento computer scientist and Director of its Microsoft funded Centre for Computational and Systems Biology extols the shift from a prior object emphasis to lately engage life’s dynamical phenomena. But a mechanistic metaphor prevails such that a philosophical disconnect remains.

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