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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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IV. Ecosmomics: An Independent, UniVersal, Source Code-Script of Generative Complex Network Systems

B. Our Own HumanVerse Genome Studies

Nussimov, Ruth, et al. Protein Ensembles Link Genotype to Phenotype. PLoS Computational Biology. June, 2019. National Cancer Institute researchers contribute a latest insight into how genetic phenomena proceeds to actively inform and array into evolving organisms. Rather than a prior one gene to one trait, now mostly set aside, it is “ensembles” of biochemical generative guidance which are the pathway by which life forms and vivifies itself. See also The Energy Landscapes of Biomolecular Function by Nussimov and Peter Wolynes in Physical Chemistry Chemical Physics (16/6321, 2014) for a setup piece.

Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods from genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene actually encodes ensembles of conformations. A dynamic ensemble view can better reveal the linkage between genetic change and observable physical or biochemical features. An ensemble view, rather than the genotype–phenotype paradigm, clarifies how even small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function. (Abstract excerpts)

The terms genotype and phenotype have been in use at least since the turn of the last century. Genotype has been defined as the genetic makeup of an organism or of a specific characteristic. Phenotype has been construed as the composite of the organism’s observable characteristics or traits, such as morphology, development, biochemical, and physiological properties. Classically, the genotype of an organism has been described as the inherited genetic material coding for all processes in the organism’s life. (1)

Oiwa, Nestor and James Glazier. The Fractal Structure of the Mitochondrial Genomes. Physica A. 311/1-2, 2002. An identical scale-free genetic pattern is discovered across a wide range of plants and animals from algae to sharks and homo sapiens, another sign of a universal recurrence.

The mitochondrial DNA genome has a definite multifractal structure. We show that loops, hairpins and inverted palindromes are responsible for this self-similarity. (221) We thus see true multifractality in all 35 mtDNAs analyzed showing that self-similarity is independent of level of evolutionary complexity. (229)

Olsen, Peter, et al, eds. Next Generation Systematics. Cambridge: Cambridge University Press, 2016. As the blurb notes, this volume 78 of the Systematics Association series considers how their phylogenetics endeavors (second quote) can be advanced by the latest sequencing abilities. Some chapters are Systematics in the Age of Genomics by Antonis Rojas, and The Role of NGS for Integrative Approaches in Evolutionary Biology by Ralf Sommer. The edition is another instance of nature’s every aspect gaining a genetic essence

We live in an age of ubiquitous genomics. Next generation sequencing (NGS) technology, both widely adopted and advancing at pace, has transformed the data landscape, opening up an enormous source of heritable characters to the comparative biologist. Its impact on systematics, like many other fields of biology, has been felt throughout its breadth: from defining species boundaries to estimating their evolutionary histories. This volume examines the broad range of ways in which NGS data are being used in systematics and in the fields that it underpins, from biodiversity prospecting to evo-devo. Experts in their fields draw on contemporary case studies to demonstrate state-of-the-art applications of NGS data. These, along with novel analyses, comprehensive reviews and lively perspectives, are combined to produce an authoritative account of contemporary issues in systematics that have been impacted by the adoption of NGS (Publisher).

Biological systematics is the study of the diversification of living forms, both past and present, and the relationships among living things through time. Relationships are visualized as evolutionary trees (synonyms: cladograms, phylogenetic trees, phylogenies). Phylogenies have two components, branching order (showing group relationships) and branch length (showing amount of evolution). (Wikipedia)

Pagel, Mark. Rise of the Digital Machine. Nature. 452/699, 2008. In this note, the University of Reading biologist cites a common affinity between genomes and language. Our speech might thus be genetic in kind, while the molecular code can appear as a written text. In each parallel case, the total number of words or DNA genes is not important but how they are ‘grammatically’ used or regulated in a complex adaptive system. From our vantage I add, this rise of evolutionary information might be seen to proceed from analogue to digital (alphabetic) and on a nascent bicameral synthesis of both modes. What kind of a Universe evolves its own Reader? Are ‘we the people’ in some way acting as ‘genes’ trying to learn and continue the cosmic genetic message?

Human societies and multicellular organisms share a puzzling feature. They seem to be under-specified. Our societies depend on many more interactions among group members than there are members. Multicellular organisms have many more parts, and connections among those parts, that they have genes. This points to a principle of regulation in the evolution of such complex adaptive systems: complexity areses not from the number of genes or actors but from how those elements are expressed or deployed. (699) Deep down, language may be just the latest form of gene regulation – the voice of our genes. Information management, not lats of parts, is the key to complexity. (699)

Pah, Adam, et al. Use of a Global Metabolic Network to Curate Organismal Metabolic Network. Nature Scientific Reports. 3/1695, 2013. Via Google, the word Curate has dual meanings – “a person invested with the care or cure of souls,” or “to organize, sort, arrange, such as a museum.” A “Curator” is an overseer or caretaker. As the quotes explain, with Roger Guimera, A. M. Mustoe, and Luis Amaral, Northwestern University systems biologists propose a novel sophistication to further limn and parse complex genomes. As scientists proceed with this literacy project, as if “cosmic curators,” we seem to fulfill a phenomenal role as an intended agency by which a genesis uniVerse tries to consciously read its own genetic code.

The difficulty in annotating the vast amounts of biological information poses one of the greatest current challenges in biological research. The number of genomic, proteomic, and metabolomic datasets has increased dramatically over the last two decades, far outstripping the pace of curation efforts. Here, we tackle the challenge of curating metabolic network reconstructions. We predict organismal metabolic networks using sequence homology and a global metabolic network constructed from all available organismal networks. While sequence homology has been a standard to annotate metabolic networks it has been faulted for its lack of predictive power. We show, however, that when homology is used with a global metabolic network one is able to predict organismal metabolic networks that have enhanced network connectivity. Additionally, we compare the annotation behavior of current database curation efforts with our predictions and find that curation efforts are biased towards adding (rather than removing) reactions to organismal networks. (Abstract)

Because data reliability is such a pressing problem for experimental and computational researchers alike, there has been a push in research to consider the analysis of metabolic networks from novel perspectives. A promising new framework is to consider metabolism in the context of a global network. This framework has been successfully applied in assessing the emergence of biological carbon fixation in phylometabolism and, more generally, to understand the regulation of metabolism. A global network has also been recently used in conjunction with probabilistic methods to predict metabolic networks on a small scale with experimental verification. While the motivation for the global network approach has been mostly pragmatic, it is reminiscent of the ‘‘Res Potentia’’ framework proposed by (Alfred North) Whitehead. Wherein he proposes that which does exist—termed the Res Extenta or in the case of metabolism the set of organismal metabolic network—are specific realizations of a ‘‘universal’’ framework—the Res Potentia or the global network in our analysis—that defines what is possible. (1)

Pearson, Helen. What is a Gene? Nature. 441/399, 2006. The burst of genome sequencing is causing a major revision in the definition of what a gene is. No longer beads on a string, it is more like a DNA information package, which involves RNA, and whose protein codes have no clear beginning or end.

Piatogorsky, Joram. Gene Sharing and Evolution. Cambridge: Harvard University Press, 2007. The Chief of the Laboratory of Molecular and Developmental Biology, National Eye Institute, National Institutes of Health, quite engaged at the forefront of genetic research, discusses the on-going revision and redefinition of the nature of genes and their many activities. As an example of original multitasking, one gene can produce a polypeptide (a protein string of amino acids) with several optional biochemical functions. These novel insights and properties contribute to the systems biology project to articulate such contextual dynamic networks that discrete genes are contained within.

Although gene sharing refers specifically to multiple molecular uses of an individual polypeptide, the modern “gene” in gene sharing is an interactive, differentially expressed gene that challenges the investigator to see in how many ways it can enlarged through the functions of its polypeptide rather that how it might be subdivided into an elementary unit, as was the goal of investigators in the classical and neoclassical concepts of the gene. (53) Networks transform molecular biology to “modular” biology and link the rules of biology to many different disciplines, including statistical physics, engineering, the Internet, ecosystems, and social interactions. (196)

Pigliucci, Massimo. Genotype-Phenotype Mapping and the End of the ‘Genes as Blueprint’ Metaphor. Philosophical Transactions of the Royal Society B. 365/557, 2010. A paper in a dedicated issue on “Phenotypic Plasticity in Development and Evolution.” As long as an evolutionary burden remains that nothing beyond accident and selection is going on, a grand revision, here actually added to by one of the main players, (see Pigliucci & Muller, eds. Evolution – the Extended Synthesis, May 2010 from MIT Press) can not yet be appreciated. We are advised once more that the textbook stage of “bean-bag genetics” is over, superseded by nonlinear developmental encodings between information and individual in the guise of robust modular networks with “computational” activities.

Portin, Petter. The Elusive Concept of the Gene. Hereditas. 146/3, 2009. In a paper noted by the journal as the most cited, a University of Turku, Finland geneticist provides a succinct summary, as the three quotes aver, of the 21st century revolution from molecular determinations to “interlaced networks” across nested scales stretching in a reciprocal way from genome to organism and environment. A “gene” is no longer a separate, fixed entity, rather entire genotypes are complicated webworks of complex, heritable components. Nucleotide sequences thus become “quantitative collections of binary information” applied in a variety of instances, depending on the organismic context. And to add, while reading about such genes and genomes, one is struck by their similarity to words in a sentence and paragraph, with a meaning dependent on the message being conveyed.

In recent years geneticists have witnessed many significant observations which have seriously shaken the traditional concept of the gene. These specifically include the facts that (1) the boundaries of transcriptional units are far from clear; in fact, whole chromosomes if not the whole genome seem to be continuums of genetic transcription, (2) many examples of gene fusion are known, (3) likewise many examples of so-called encrypted genes are known in the organelle genomes of microbial eukaryotes and in prokaryotes, and (4) in addition to the structure of the gene, its functional status can also be inheritable, and, further, (5) epigenetic extra-genomic modes of inheritance, called genetic restoration, seem to be a rather common phenomenon, meaning that organisms can sometimes rewrite their DNA on the basis of RNA messages inherited from generations past. (Abstract)

I will briefly review these observations and discuss the difficulties of defining the gene, and then formulate a new view, which is called the relational or systemic concept of the gene. It has to be noted that genes assume their information content characteristics in the Shannonian sense as nucleotide sequences of DNA (or RNA). However, on the basis of this we cannot say anything about their information content in the semantic sense. The semantic information content of genes is context-dependent. Genes namely assume their biochemical characteristics usually only within living cells, their developmental characteristics only within living organisms, and their evolutionary characteristics only within populations of living organisms. (Abstract, 112)

Accordingly, it can be said that the science of genetics is gradually moving away from a reductionistic way of thinking towards a more holistic – or better said – systemic way of thinking, which takes the whole of the organism and its parts into consideration at the same time. In fact, it is not possible to really understand a given whole without understanding its constituent parts nor really understand the parts of a given biological system – be it a gene, cell, individual, population or ecosystem – without understanding it as a total integrated whole. (115)

Portin, Petter and Adam Wilkins. The Evolving Definition of the Term “Gene.”. Genetics. 205/4, 2017. University of Turku, Finland and Humboldt University, Germany biologists (search each) first survey past takes on this “unit of inheritance” from before and after the 1950s molecular DNA helix and through to major 21st century revisions. In this current phase which gives equal import to “gene regulatory networks (GRN),” a new sense of nodal nucleotide and interlinked reciprocities, aka genome-wide association studies (GWAS), has come forth. As the quote alludes, we may view one more exemplary presence of a universal complementarity of particulate and integrative modes.

The conceptual consequences of viewing individual genes not as autonomous actors, but as interactive elements or outputs of networks are profound. For one thing, it becomes relatively easy to think about the nature of genetic background effects in terms of the structure of gene regulatory nets. While much of the thinking of the 20th century about genes was based on the premise that the route from gene to phenotype was fairly direct, and often deducible form the nature of the gene product, the network perspective envisages far more complexity and indirectness of effects. In general, the path from particular genes to specific phenes is long, and the role of many gene products seems to be the activation or repression of the activities of other genes. (1360)

Qui, Jane. Unfinished Symphony. Nature. 441/143, 2006. The codons in our now sequenced genome are orchestrated by an overlaying “epigenetic” code, which researchers are just tuning in to.

Rando, Oliver and Kevin Verstrepen. Timescales of Genetic and Epigenetic Inheritance. Cell. 128/4, 2007. One cannot underestimate the scope of this revolution in our understanding of heredity and evolution. While classic theory says phenotypic variety arises from random mutations independent of selective pressures, the latest research finds that organisms have evolved mechanisms to influence the timing or genomic location of heritable variation. In a revival of “directed mutagenesis” from the 1980’s, cells seem to exhibit a biased behavior in favor of successful variants to changing environmental stresses. By these lights, the views of Darwin, and especially of Lamarck, that life evolves in a self-guiding manner so as to maximize its survivability are said to deserve new notice. (See also Bernstein, Bradley, et al. The Mammalian Epigenome in the same issue)

We now finally turn to the idea that organisms may orchestrate specific, nonrandom heritable changes in themselves in response to appropriate conditions. (665)

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