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

C. Our Own HumanVerse (Epi) Genomic Heredity

Boel, Gregory, et al. Omnipresent Maxwell’s Demons Orchestrate Information Management in Living Cells. Microbial Biotechnology. 12/2, 2019. French and Italian biologists including Antoine Danchin seek better explanations for life’s vital interactive conversations as organisms survive and evolve, which are in opposition to entropic losses. By this approach, a biological complementarity between cellular discrimination and recognition modes is glimpsed, along with allusions of a natural self-organization.

Synthetic biology advances require understandings of the critical functions that allow the construction and operation of a living cell. Besides coding for ubiquitous structures, minimal genomes encode a wealth of functions that dissipate energy. Analysis of these functions shows that they manage information under noisy conditions when discrimination of substrates is preferred over a recognition process. We show that such functions, including transporters and the ribosome constructors, behave as an informational agent theorized by (James Clerk) Maxwell, circa 1870, and well known as Maxwell's demon. Altogether these features form the minimal genome required to allow the construction of an autonomous cell and allow them to perform computations in an energy‐efficient way. (Abstract)

Brixi, Garyk, et al. Genome modeling and design across all domains of life with Evo 2. biorxiv. February 21, 2025. Some fifty computational geneticists at the Arc Institute (Google); Stanford University, NVIDIA, Liquid AI, UC Berkeley, Columbia University and the University of California, San Francisco post a latest version of this their human person – AI planet initiative to expand and enhance a wider scope of (epi)genetic encodings. See also Semantic mining of functional de novo genes from a genomic language model by Aditi Merchant at bioRxiv (December 18, 2024). In early regard, the concept that some Turing-type, genomic-like, LLModel code script is indeed running as it programs and informs an ecosmic genesis becomes increasingly evident.

While the sequencing, synthesis, and editing of genomic codes have transformed biological research, intelligently composing new biological systems requires deeper understandings of their immense complexity. We introduce Evo 2, a foundation model trained on 9.3 trillion DNA base pairs from a genomic atlas spanning all domains of life. Evo 2 learns from DNA sequences to accurately predict the influences of genetic variation. Guiding Evo 2 via inference-time search also enables controllable generation of epigenomic structure, which we demonstrate for the first time. (Excerpt)

Our work shows that a generative model of genomic language enables a machine learning model to achieve generalist prediction and design capabilities across Metazoan life. By learning the statistical properties of DNA via a trillion tokens of genomic sequences, Evo 2 can predict mutational effects on protein function, ncRNA function, and organismal fitness. (17) Biological foundation models capable of composing novel systems to advance biomedical innovation, but also raise safety, security and ethical considerations. Aligned with Responsible AI Biodesign (Google), we assessed and mitigated concerns prior to open source publication. (18)

New AI breakthrough can model and design genetic code across all domains of life. A team of scientists from UC Berkeley, Arc Institute, UCSF, Stanford University and NVIDIA have developed a machine learning model trained on the DNA of over 100,000 species across the entire tree of life. The model, called Evo 2, can identify patterns in gene sequences across disparate organisms that would typically need years to uncover. In addition to identifying disease-causing mutations in human genes, Evo 2 can design new genomes that are as long as that of simple bacteria. (UC Berkeley Center for Computational Biology)

Caporale, Lynn, ed. The Implicit Genome. Oxford: Oxford University Press, 2006. An edited contribution to a paradigm revision of our understanding of genetic codes. With the recent sequencing of genomes the initial DNA phase of identifying all the molecular components is fulfilled. But the dogma of an inert passivity before random mutations is now being discarded. Via a novel systems approach, the genetic realm is becoming seen as a nonrandom, dynamically responsive source. By these convergent insights, gene variation is able to focus and favorably guide itself. Rather than a “bag of letters,” it is the relationships between sequences that are important. In an Epilogue a parallel between genotype biology and the global Internet is proposed. Along with strings of nucleotides, nodes and links, sites and connections, protocol “rules” create a robust viability in both cases. As such they are highly mutable within changing environments. But these attributes, not evident until first parts and later waves were found, imply a new evolution and indeed universe with an innate spontaneity as it develops into a self-similar nest of complexity and consciousness.

Carroll, Sean B., et al. Regulating Evolution. Scientific American. May, 2008. A popular survey of an historic reconception in process of the functional nature of genes and genomes, that many other references herein report. We are surely familiar with the one to one attribution of DNA with a soma, trait, or malady. Yet it has lately perplexed for after the human genome sequence and a growing number of other creatures, how is it that animals differ so if they have similar gene complements? The prime distinction appears to be regulatory stretches in the double-helix that control when and where genes are turned on and off. It is mutations in these segments that then result in evolutionary change. As others such as Matt Ridley and Mark Pagel note, one gets an impression we could just as well be describing language with grammar and syntax. The same words exist, it is just how they are used in a sentence and paragraph.

Mutations in DNA “switches” that control body-shaping genes, rather than in the genes themselves, have been a significant source of evolving differences among animals. If humans want to understand what distinguishes animals, including ourselves, from one another, we have to look beyond genes. (61) If we really want to understand what makes the human form different from that of other apes or what makes an elephant distinct form a mouse, for that matter, much of that information lies not in our respective genes and proteins but in an entirely different realm of our genomes that remains to be explored. (67)

Cloud, John. Why Gene’s Aren’t Destiny. Time. January 18, 2010. A well written report on the historic, on-going revolution from decades of a DNA determinism to a radically expanded genomic view that is quite Lamarckian in kind. A persons diet, environment, lifestyle (e.g. smoker or non) is now seen to impact, over one or two generations, one’s offspring as they influence this epigenetic editor. While the Human Genome Project sequenced some 25,000 “genes,” the number of “epigenome” markers is in the millions. Read along with Karen Hopkin’s essay within.

At its most basic, epigenetics is the study of changes in gene activity that do not involve alternations to the genetic code but still get passed down to at least one successive generation. These patterns of gene expression are governed by the cellular material – the epigenome – that sits on top of the genome, just outside it. (50) Biologists offer this analogy as an explanation: if the genome is the hardware, then the epigenome is the software. (51)

Cobb, Matthew. Life’s Greatest Secret: The Race to Crack the Genetic Code. New York: Basic Books, 2015. The University of Manchester zoologist cogently conveys this grand story from physicist Erwin Schrodinger and 1940s glimpses to the 1950s Watson and Crick decade, onto intense global research to the 2001 human genome sequence and beyond. A theoretical and philosophical theme then runs through whereby life’s code-script is an informational essence and flow that evolves and emerges.

Cochrane, Wesley, et al. Cross-chiral exponential amplification of an RNA enzyme. PNAS. 121/44, 2024. Salk Institute, La Jolla, CA including Gerald Joyce contribute still more research results that attest to how basically important catalytic processes is to genome-wide nucleotide informative operations.

A special form of autocatalysis, rarely seen outside of biology, is active in self-replication with exponential growth. Life relies on metabolic components of the same chiral handedness, including nucleic acids that contain only D-sugars. For our laboratory study, a system of cross-replicating RNAs was devised based on a ribozyme that joins two RNA fragments of the opposite handedness to form its own enantiomer (mirror image), and then a new copy of the original ribozyme. The D- and L-ribozymes grow together and can be propagated, which demonstrates a form of autocatalytic self-replication that relies on an RNA enzyme. (Excerpt

Cohen, Irun and Henri Atlan. Genetics as Explanation: Limits to the Human Genome Project. www.els.net.. In this 2006 posting on the Encyclopedia of the Life Sciences. website, Immunologist Cohen collaborates with the philosopher physician and pioneer applier of systems principles Henri Atlan, with academic posts in Jerusalem and Paris, to contend that the molecular genetic code organizes itself by the same interactive dynamics at work everywhere else in nature from immune responses to a thinking brain.

Similarly, an organism is built and operates with the help of its genome; but the genome is only one element in a recursive process. The iterating cycle of genes that
form proteins that form genes is the self-organizing process from which the organism emerges. If there be a genetic program, then such a program writes itself collectively. The action, as it were, precedes the plan. But how can that be?

Emergence is not a mystical concept. A physical basis for the emergence of self-organization has been established in studies of nonequilibrium thermodynamics: open systems that exchange matter and energy with their surroundings can maintain themselves in steady states far from equilibrium. The decrease in internal entropy in such systems can be offset by increased entropy in the surroundings; this makes it possible for macroscopic organization to emerge from the coupling of multiple microscopic reactions.

Cole, Steven. Human Social Genomics. PLoS Genetics. 10/8, 2015. Just as animal groupings are found to influence the genomes of its members, the UCLA professor of medicine, psychiatry, and biobehavioral sciences shows how the genetic endowments of human individuals also become modified by public interactions. A “reciprocal recursion” by way of “social signal transduction” connects and traverses from genes to endocrines to neural and onto cultural domains. Here is still another instance of a personal and communal complementarity, a natural balance and guide we ought to emulate.

The spectacular adaptive success of Homo sapiens is attributable in large part to our capacity to self-organize into complex social systems or ‘‘metaorganisms.” Research in human social genomics has begun to clarify how these extraorganismic social systems reciprocally regulate our intraorganismic physiologic function by modulating tissue-specific programs of gene expression. Social regulation of gene expression has long been observed in animal models of morphological plasticity such as worker bee maturation into guards and scouts, cichlid sex switching, and status-dependent changes in body size, coloring, brain development, immune response, and reproductive capacity. However, scientists, policy makers, and the general public have long wondered how such animal dynamics might pertain to everyday human life. Studies of human social genomics are now
clarifying which specific types of human genes are subject to social regulation and mapping the social signal transduction pathways that mediate these effects. (1)

If we judge societies at least in part by the extent to which they help each of us realize our genomically endowed potential for well-being, then the molecularly quantified self could represent one of our own society’s most significant achievements. After all, each of our human genomes is fundamentally a system for converting environmental information into molecular resources according to the accumulated wisdom of 4 million years of hominid evolution, and those who stand to gain most from the insights they afford are we whose lives they create. (5)

Costanzo, Michael, et al. The Genetic Landscape of a Cell. Science. 327/425, 2010. A significant contribution by some fifty-three researchers across Canada and the United States, many at Charles Boone’s University of Toronto, Donnelly Centre for Cellular and Biomolecular Research, laboratory, to the conceptual revolution from a particulate DNA phase so as to include the real presence of complementary, genome-wide, dynamic networks. Along with recent postings for Pigliucci, Garfield & Wray, and others, our appreciation of genetic phenomena is in major revision and expansion that open to epigenetic, lateral gene transfer, linguistic, environmental, and other aspects. By so doing, circa 2010, the universal, independent, self-organizing complex system of a natural genesis begins to take on an intrinsic, parental, genomic identity. See also Dixon, Scott, et al “Systematic Mapping of Genetic Interaction Networks” in Annual Reviews of Genetics (Vol. 43/601, 2009) by the same group.

A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. (425)

Genes belonging to the same pathway or biological process tend to share similar profiles of genetic interactions. We exploited this property to construct a global network, grouping genes with similar interaction patterns together. Nodes in this network represent genes, and edges connect gene pairs that share common sets of genetic interaction or similar interaction profiles. This network highlights genetic relations between diverse biological processes and the inherent functional organization of the cell. (427)

Cowen, Lenore, et al. Network Propagation: A Universal Amplifier of Genetic Associations. Nature Review Genetics. 18/551, 2020. Tufts, Princeton, Tel Aviv University, and UC San Diego, systems geneticists including Trey Ideker contribute to growing realizations of how important these connective genomic phenomena are. In regard, they can be seen to have an equally evident, proactive role, maybe more so, than the discrete nucleotide biomolecules.

Biological networks are powerful resources for the discovery of genes and genetic modules that drive disease. Fundamental to network analysis is the concept that genes underlying the same phenotype tend to interact. This principle can be used to combine and amplify signals from individual genes. Recently, bioinformatic techniques have been proposed for genetic analysis using networks, based on random walks, information diffusion and electrical resistance. In fact, all these approaches are variations of a unifying mathematical basis — network propagation — suggesting that it is a powerful data transformation method of broad utility in genetic research. (Abstract)

Crespi, Bernard. Shared Sociogenetic Basis of Honey Bee Behavior and Human Risk for Autism. Proceedings of the National Academy of Sciences. 114/9502, 2017. The Simon Fraser University biologist commends the paper Deep Evolutionary Conservation of Autism-Related Genes by Hagai Shpigler, et al in this issue (9653) for quantifying how the same genetic suite is involved for similar behaviors for both insects and human beings. Crespi has long been of this mind (search) and finds a “universal sociogenetic circuitry” across this wide span to be robustly verified. See also, e.g., Hox Genes, Evo-Devo, and the Case of the ftz Gene by Leslie Pick in Chromosoma (125/3, 2016). We quoted this whole first paragraph for its content.

We humans are great apes, but share a surprisingly extensive suite of traits with social insects as well as with primates. These overlapping human–insectan phenotypes, which include divisions of labor, alloparental care, extensive food sharing, group–colony structures, collective decision making, and complex social cooperation, have indeed been considered responsible for the spectacular ecological and evolutionary successes of both social insects and humans, compared with other forms of animal life. Given the immense phylogenetic distance of humans from social insects, their common behavioral and life-history traits have thus far usually been ascribed to convergence, whereby shared selective pressures drive the evolution of social similarities despite highly divergent genetic and morphological substrates. In contrast, Shpigler et al. (2) demonstrate that a core, shared human–social insect phenotype, social responsiveness—as indicated by between-bee interactions and human diagnoses of autism—actually reflects shared genetic underpinnings. Shpigler et al.’s discovery provides novel insights into the genomic bases of both social adaptation and autism spectrum disorders, and implies a universality to social life with implications from philosophy to medicine. (9502)

Sociobiological theory proposed that similarities between human and animal societies reflect similar evolutionary origins. We used comparative genomics to test this controversial idea by determining whether superficial behavioral similarities between humans and honey bees reflect shared molecular mechanisms. We found unique and significant enrichment for autism spectrum disorder-related genes in the neurogenomic signatures of a high-level integration center of the insect brain in bees unresponsive to two different salient social stimuli. These results demonstrate deep conservation for genes implicated in autism spectrum disorder in humans and genes associated with social responsiveness in honey bees. Comparative genomics thus provides a means to test theory on the biology of social behavior. (Shpigler, et al Significance)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next  [More Pages]