IV. Ecosmomics: Independent Complex Network Systems, Computational Programs, Genetic Ecode Scripts

C. Our Own HumanVerse (Epi) Genomic Heredity

Rzhetsky, Andrey and Shawn Gomez. Birth of Scale-Free Molecular Networks and the Number of Distinct DNA and Protein Domains per Genome. Bioinformatics. 17/10, 2001. The same invariance evident throughout the natural realm is equally present in dynamic genetic systems.

Salthe, Stan. The Natural Philosophy of Ecology. www.nbi.dk/~natphil/salthe/natphilecol.2001. An essay on the need to rediscover an original unity in nature in order to find an “intelligible picture of the world.” So conceived, evolution is most of all the “irreversible accumulation of historical information.”

Sandoval-Motta, Santiago, et al. The Human Microbiome and the Missing Heritability Problem. Frontiers in Genetics. Online June 13, 2017. Universidad Nacional Autónoma de México researchers contribute to this on-going concern since 2008 when it was realized that the copious Human Genome Project data results could not yet fully explain organisms. We cited an extended Abstract in regard. A Google of the MH thtle phrase will get more hits, this paper is another instance of expansive inputs much beyond nucleotides alone.

The “missing heritability” problem states that genetic variants in Genome-Wide Association Studies (GWAS) cannot completely explain the heritability of complex traits. Traditionally, the heritability of a phenotype is measured through familial studies using twins, siblings and other close relatives, making assumptions on the genetic similarities between them. When this heritability is compared to the one obtained through GWAS for the same traits, a substantial gap between both measurements arise with genome wide studies reporting significantly smaller values. Several mechanisms for this “missing heritability” have been proposed, such as epigenetics, epistasis, and sequencing depth. However, none of them are able to fully account for this gap in heritability. In this paper we provide evidence that suggests that in order for the phenotypic heritability of human traits to be broadly understood and accounted for, the compositional and functional diversity of the human microbiome must be taken into account.

This hypothesis is based on several observations: (A) The composition of the human microbiome is associated with many important traits, including obesity, cancer, and neurological disorders. (B) Our microbiome encodes a second genome with nearly a 100 times more genes than the human genome, and this second genome may act as a rich source of genetic variation and phenotypic plasticity. (C) Human genotypes interact with the composition and structure of our microbiome, but cannot by themselves explain microbial variation. (D) Microbial genetic composition can be strongly influenced by the host's behavior, its environment or by vertical and horizontal transmissions from other hosts. Therefore, genetic similarities assumed in familial studies may cause overestimations of heritability values. We also propose a method that allows the compositional and functional diversity of our microbiome to be incorporated to genome wide association studies. (Abstract)

Sansom, Roger. The Connectionist Framework for Gene Regulation. Biology & Philosophy. 23/4, 2008. The Texas A&M University philosopher finds a useful affinity to exist between this neuroscience approach, aka parallel distributed processing and neural networks, and molecular genomic systems. His own website cites an MIT Press forthcoming book: Ingenious Genes: How Gene Regulation Networks Evolve to Control Ontogeny. One more citation of nature’s consistent employ, under various terms and emphasis, of the same complex dynamics at each and every phase and instance.

Seringhaus, Michael and Mark Gerstein. Genomics Confounds Gene Classification. American Scientist. November-December, 2008. As noted herein, the intensive genome sequencing of human, primate, and other species have resulted in a total revision of what constitutes a gene. In this report, Yale University geneticists first review the last 70 years to illustrate a steady morphing from discrete molecules to a growing notice of systemic, repetitive networks, along with many epigenetic influences. In this bioinformatics age, how “genes” and their functions are defined, named, and classified is of much importance. But a leap of the author’s work is to perceive its deep affinity with the formative phase and current operative format of the World Wide Web. Common parallels occur by way of ontologies which gather distributed annotations and intelligence. One involves proteins, the other web pages. Might it then be imagined through an emergence from word to flesh to word that the globally collaborative Internet could be in some way genetic in kind?

Shapiro, James. Bacteria are Small but not Stupid: Cognition, Natural genetic Engineering and Socio-bacteriology. Studies in History and Philosophy of Biological and Biomedical Sciences. 38/4, 2007. Another article in the Towards a Philosophy of Microbiology section wherein the University of Chicago geneticist finds the newly appreciated relational network, communicative, and collaborative qualities of genomes and microbes to infer, in these simpler stages, a true cognitive sentience can indeed be seen at work. As Shapiro has often cited, and others increasingly, an historic change is now underway from centuries of a mechanistic scheme to an intrinsic developmental vitality that actively survives, evolves, and emerges on its own.

Forty years’ experience as a bacterial geneticist has taught me that bacteria possess many cognitive, computational and evolutionary capabilities unimaginable in the first six decades of the twentieth century. Analysis of cellular processes such as metabolism, regulation of protein synthesis, and DNA repair established that bacteria continually monitor their external and internal environments and compute functional outputs based on information provided by their sensory apparatus. (807)

The realization that most DNA changes in bacteria (and eukaryotes too) occur by the action of natural genetic engineering systems removes the source of variation in the genome from the category of stochastic events or unpredictable accidents, and places it in the context of cellular biochemistry. (814) Bacteria certainly can use their cognitive capacities to activate DNA change when it can be useful in overcoming selective challenges. (814) Thus, the DNA segments that move through the genome, the places they move, and the sequences they rearrange can have both flexibility and predictability. (814)

The only way I know how to make sense out of the last fifty years of molecular biology is to abandon the mechanistic and atomistic ideas of the pre-DNA era and embrace a more organic, cognitive and computational view of cells and genomes. (816)

Shapiro, James. Genome Organization and Reorganization in Evolution. Van Speybroeck, Linda, et al, eds. From Epigenesis to Epigenetics: The Genome in Context. Annals of the New York Academy of Sciences, 2002. The University of Chicago microbiologist contrasts the ‘20th century of the gene’ and its reductionist method with a ‘21st century of the genome’ based on complex systems. As a result, evolutionary processes are revised from only random mutations and incremental selection to ‘non-random, genome wide rearrangements leading to novel genome system architectures.’

Shapiro, James. Genome System Architecture and Natural Genetic Engineering. Landweber, Laura and Eric Winfree, eds. Evolution as Computation. Berlin: Springer, 2002. In a contribution to the total rethinking of the nature of gene and genome, the old Mendelian version is supplanted by malleable information processing systems capable of nonrandom change guided by dynamic cellular networks. Once again an evolutionary trajectory with a sense of direction is implied.

Collectively, these discoveries set the stage for thinking of genomes as hierarchically integrated systems capable of biologically controlled change rather than as collections of autonomous genetic units subject to individual evolution by random variation. (3)

Shapiro, James A. Mobile DNA and Evolution in the 21st Century. Mobile DNA. 1/4, 2010. As he has pioneered for many years, the University of Chicago geneticist reports with new veracity, backed by over 200 references, upon a whole scale reconception of genomic phenomena in complementary terms of its dynamic, network, and communicative propensities. Which then informs and portends a 21st century synthesis, a true “universal gestation,” akin to and fulfilling Charles Darwin’s actual 19th century conviction.

Mobile DNA is an online, peer-reviewed, open access journal that publishes articles providing novel insights into DNA rearrangements, ranging from transposition and other types of recombination mechanisms to patterns and processes of mobile element and host genome evolution.

Abstract. Scientific history has had a profound effect on the theories of evolution. At the beginning of the 21st century, molecular cell biology has revealed a dense structure of information-processing networks that use the genome as an interactive read-write memory system rather than an organism blueprint. Genome sequencing has documented the importance of mobile DNA activities and major genome restructuring events at key junctures in evolution: exon shuffling, changes in cis-regulatory sites, horizontal transfer, cell fusions and whole genome doublings. The natural genetic engineering functions that mediate genome restructuring are activated by multiple stimuli, in particular by events similar to those found in the DNA record: microbial infection and interspecific hybridization leading to the formation of allotetraploids. These molecular genetic discoveries, plus a consideration of how mobile DNA rearrangements increase the efficiency of generating functional genomic novelties, make it possible to formulate a 21st century view of interactive evolutionary processes. (1)

Molecular cell biology has uncovered sophisticated networks in all organisms. They acquire information about external and internal conditions, transmit and process that information inside the cell, compute the appropriate biochemical or biomechanical response, and activate the molecules needed to execute that response. These information-processing networks are central to the systems biology perspective of the new century. Altogether, we have a radically different conceptual perspective on living organisms than our predecessors. As a result, we need to ask how this new perspective affects our 21st century understanding of the evolutionary process. (2)

This 21st century scenario assumes a major role for the kind of cellular sensitivities and genomic responses emphasized by McClintock in her 1984 Nobel Prize address (Science 226/792, 1984). Such a cognitive component is absent from conventional evolutionary theory because 19th and 20th century evolutionists were not sufficiently knowledgeable about cellular response and control networks. This 21st century view of evolution establishes a reasonable connection between ecological changes, cell and organism responses, widespread genome restructuring, and the rapid emergence of adaptive inventions. (10)

Shea, Nicholas. Inherited Representations are Read in Development. British Journal for the Philosophy of Science. Online June, 2012. In a series of articles over recent years, the Oxford University philosopher of biology has proposed that our understandings of genomic activity, broadly conceived, could benefit by viewing this as semantic representations. In regard, an affinity to cognitive memories is drawn upon as they “represent” or contain one’s corpus of lived and learned experience. (Quote 1) A companion paper might be “Developmental Systems Theory Formulated as a Claim about Inherited Representations” in Philosophy of Science (76/1, 2011) where epigenetic and environmental influences are factored in via the DST school. (Quote 2)

Recent theoretical work has identified a tightly constrained sense in which genes carry representational content. Representational properties of the genome are founded in the transmission of DNA over phylogenetic time and its role in natural selection. However, genetic representation is not just relevant to questions of selection and evolution. This article goes beyond existing treatments and argues for the heterodox view that information generated by a process of selection over phylogenetic time can be read in ontogenetic time, in the course of individual development. Recent results in evolutionary biology, drawn both from modelling work, and from experimental and observational data, support a role for genetic representation in explaining individual ontogeny: both genetic representations and environmental information are read by the mechanisms of development, in an individual, so as to lead to adaptive phenotypes. Furthermore, in some cases there appears to have been selection between individuals that rely to different degrees on the two sources of information. Thus, the theory of representation in inheritance systems like the genome is much more than just a coherent reconstruction of information talk in biology. Genetic representation is a property with considerable explanatory utility. (Abstract 1)

Developmental systems theory (DST) is often dismissed on the basis that the causal indispensability of nongenetic factors in evolution and development has long been appreciated. A reformulation makes a more substantive claim: that the special role played by genes is also played by some (but not all) nongenetic resources. That special role can be captured by Shea’s ‘inherited representation’. Formulating DST as the claim that there are nongenetic inherited representations turns it into a striking, empirically testable hypothesis. DST’s characteristic rejection of a gene versus environment dichotomy is preserved but without dissolving into an interactionist casual soup, as some have alleged. (Abstract 2)

Sherman, Rachel and Steven Salzberg. Pan-Genomics in the Human Genome Era. Nature Reviews Genetics. 21/243, 2020. Johns Hopkins University computational biologists describe an expansion of the multinational project to sequence all creaturely genomes so as to achieve an entire integrative pan-species genome database. Such an accomplishment just now possible can help preserve biodiversity and converse environments.

Since the early genome era, the scientific community has relied on a single “reference” genome for each species. As sequencing costs dropped, thousands of new genomes have been sequenced which led us to realize that a single reference genome is inadequate. By sampling a diverse set of individuals, one can begin to assemble a pan-genome: a collection of all the DNA sequences that occur in a species. Here we review efforts to create pan-genomes for an array of species from bacteria to humans, and consider computational methods that have been proposed to capture, interpret and compare pan-genome data. (Abstract excerpt)

Shou, Chong, et al. Measuring the Evolutionary Rewiring of Biological Networks. PLoS Computational Biology. January, 2011. As the Abstract details, a team of Yale University, University of Toronto, and Stanford University bioinformatic specialists including Mark Gerstein contribute another take on nature’s inherent penchant for genomes to employ dynamical organizations. In regard, could one say that by drawing on such mathematical propensities, a genome might know what it is doing?

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or “rewire”, at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. (Abstract)

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