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At least 271 records · Page 15

Inference of Chromosome-Length Haplotypes Using Genomic Data of Three or a Few More Single Gametes

Compared with genomic data of individual markers, haplotype data provide higher resolution for DNA variants, advancing our knowledge in genetics and evolution. Although many computational and experimental phasing methods have been developed for analyzing diploid genomes, it remains challenging to reconstruct chromosome-scale haplotypes at low cost, which constrains the utility of this valuable genetic resource. Gamete cells, the natural packaging of haploid complements, are ideal materials for phasing entire chromosomes because the majority of the haplotypic allele combinations has been preserved. Therefore, compared with the current diploid-based phasing methods, using haploid genomic data of single gametes may substantially reduce the complexity in inferring the donor’s chromosomal haplotypes. In this study, we developed the first easy-to-use R package, Hapi, for inferring chromosome-length haplotypes of individual diploid genomes with only a few gametes. Hapi outperformed other phasing methods when analyzing both simulated and real single gamete cell sequencing data sets. The results also suggested that chromosome-scale haplotypes may be inferred by using as few as three gametes, which has pushed the boundary to its possible limit. The single gamete cell sequencing technology allied with the cost-effective Hapi method will make large-scale haplotype-based genetic studies feasible and affordable, promoting the use of haplotype data in a wide range of research.

59 BASIC BIOLOGICAL SCIENCES↗

Opportunities to advance the synthesis of ecology and evolution

Despite decades of research on the interactions between ecology and evolution, opportunities still remain to further integrate the two disciplines, especially when considering multispecies systems. Here, we discuss two such opportunities. First, the traditional emphasis on the distinction between evolutionary and ecological processes should be further relaxed as it is particularly unhelpful in the study of microbial communities, where the very notion of species is hard to define. Second, key processes of evolutionary theory such as adaptation should be exported to hierarchical levels higher than populations to make sense of biodiversity dynamics. Together, we argue that broadening our perspective of eco-evolutionary dynamics to be more inclusive of all biodiversity, both phylogenetically and hierarchically, will open up fertile new research directions and help us to address one of the major scientific challenges of our time, that is, to understand and predict changes in biodiversity in the face of rapid environmental change.

54 ENVIRONMENTAL SCIENCES↗

Behavioral biology of mammalian reproduction and development for a space station

Space Station research includes two kinds of adaption to space: somatic (the adjustments made by an organism, within its lifetime, in response to local conditions), and transgenerational adaption (continuous exposure across sequential life cycles of genetic descendents). Transgenerational effects are akin to evolutionary process. Areas of a life Sciences Program in a space station address the questions of the behavioral biology of mammalian reproduction and development, using the Norway rat as the focus of experimentation.

Alberts, J. R.↗

Convergent evolution of aerobic fermentation through divergent mechanisms acting on the same key glycolytic genes

Expression profiling by high throughput sequencing The model yeast Saccharomyces cerevisiae has evolved aerobic fermentation in part through a whole genome duplication and subsequent retention of glycolytic genes. To identify independent yeast lineages with a high glycolytic rate phenotype we developed an assay measuring extracellular acidification rates (ECAR) to evaluate the glycolytic rates across diverse yeast species. This assay identified a novel group of yeasts in the genus Saturnispora with rapid glycolytic rates. Through comparative approaches, we found that several glycolytic genes encoding hexokinases and enzymes in lower glycolysis had higher expression and modifications in promoter sequences in rapid ECAR species. Intriguingly, many of the upregulated genes are the same genes that are duplicated in S. cerevisiae. When the transcription factor required for their activation was deleted, the mutants had a slow glycolytic rate and more respiratory phenotype. This work shows how the aerobic fermentation phenotype has convergently evolved in Saturnispora through transcriptional rewiring. This divergent mechanism nevertheless impacts the same glycolytic genes, which suggests that there are evolutionary constraints on how aerobic fermentation can arise.

Horianopoulos, Linda C. [Department of Food Scienc↗

Three-Function Logic Gate Controlled by Analog Voltage

The figure is a schematic diagram of a complementary metal oxide/semiconductor (CMOS) electronic circuit that performs one of three different logic functions, depending on the level of an externally applied control voltage, V(sub sel). Specifically, the circuit acts as A NAND gate at V(sub sel) = 0.0 V, A wire (the output equals one of the inputs) at V(sub sel) = 1.0 V, or An AND gate at V(sub sel) = -1.8 V. [The nominal power-supply potential (VDD) and logic "1" potential of this circuit is 1.8 V.] Like other multifunctional circuits described in several prior NASA Tech Briefs articles, this circuit was synthesized following an automated evolutionary approach that is so named because it is modeled partly after the repetitive trial-and-error process of biological evolution. An evolved circuit can be tested by computational simulation and/or tested in real hardware, and the results of the test can provide guidance for refining the design through further iteration. The evolutionary synthesis of electronic circuits can now be implemented by means of a software package Genetic Algorithms for Circuit Synthesis (GACS) that was developed specifically for this purpose. GACS was used to synthesize the present trifunctional circuit. As in the cases of other multifunctional circuits described in several prior NASA Tech Briefs articles, the multiple functionality of this circuit, the use of a single control voltage to select the function, and the automated evolutionary approach to synthesis all contribute synergistically to a combination of features that are potentially advantageous for the further development of robust, multiple-function logic circuits, including, especially, field-programmable gate arrays (FPGAs). These advantages include the following: This circuit contains only 9 transistors about half the number of transistors that would be needed to obtain equivalent NAND/wire/AND functionality by use of components from a standard digital design library. If multifunctional gates like this circuit were used in the place of the configurable logic blocks of present commercial FPGAs, it would be possible to change the functions of the resulting digital systems within shorter times. For example, by changing a single control voltage, one could change the function of thousands of FPGA cells within nanoseconds. In contrast, typically, the reconfiguration in a conventional FPGA by use of bits downloaded from look-up tables via a digital bus takes microseconds.

Zebulum, Ricardo↗

An Evolutionary System of Mineralogy. Part I: Stellar Mineralogy (>13 to 4.6 Ga)

Minerals preserve records of the physical, chemical, and biological histories of their origins and subsequent alteration, and thus provide a vivid narrative of the evolution of Earth and other worlds through billions of years of cosmic history. Mineral properties, including trace and minor elements, ratios of isotopes, solid and fluid inclusions, external morphologies, and other idiosyncratic attributes, represent information that points to specific modes of formation and subsequent environmental histories—information essential to understanding the co-evolving geosphere and biosphere. This perspective suggests an opportunity to amplify the existing system of mineral classification, by which minerals are defined solely on idealized end-member chemical compositions and crystal structures. Here we present the first in a series of contributions to explore a complementary evolutionary system of mineralogy—a classification scheme that links mineral species to their paragenetic modes. The earliest stage of mineral evolution commenced with the appearance of the first crystals in the universe at >13 Ga and continues today in the expanding, cooling atmospheres of countless evolved stars, which host the high-temperature (T > 1000 K), low-pressure (P < 10-2 atm) condensation of refractory minerals and amorphous phases. Most stardust is thought to originate in three distinct processes in carbon- and/or oxygen-rich mineral-forming stars: (1) condensation in the cooling, expanding atmospheres of asymptotic giant branch stars; (2) during the catastrophic explosions of supernovae, most commonly core collapse (Type II) supernovae; and (3) classical novae explosions, the consequence of runaway fusion reactions at the surface of a binary white dwarf star. Each stellar environment imparts distinctive isotopic and trace element signatures to the micro- and nanoscale stardust grains that are recovered from meteorites and micrometeorites collected on Earth’s surface, by atmospheric sampling, and from asteroids and comets. Although our understanding of the diverse mineral-forming environments of stars is as yet incomplete, we present a preliminary catalog of 41 distinct natural kinds of stellar minerals, representing 22 official International Mineralogical Association (IMA) mineral species, as well as 2 as yet unapproved crystalline phases and 3 kinds of non-crystalline condensed phases not codified by the IMA.

Robert M. Hazen↗

A compendium of human gene functions derived from evolutionary modelling

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms 1,2 . Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

Phytohormones in a universe of regulatory metabolites: lessons from jasmonate

Small-molecule phytohormones exert control over plant growth, development, and stress responses by coordinating the patterns of gene expression within and between cells. Increasing evidence indicates that currently recognized plant hormones are part of a larger group of regulatory metabolites that have acquired signaling properties during the evolution of land plants. This rich assortment of chemical signals reflects the tremendous diversity of plant secondary metabolism, which offers evolutionary solutions to the daunting challenges of sessility and other unique aspects of plant biology. A major gap in our current understanding of plant regulatory metabolites is the lack of insight into the direct targets of these compounds. Here, we illustrate the blurred distinction between classical phytohormones and other bioactive metabolites by highlighting the major scientific advances that transformed the view of jasmonate from an interesting floral scent to a potent transcriptional regulator. Lessons from jasmonate research generally apply to other phytohormones and thus may help provide a broad understanding of regulatory metabolite–protein interactions. In providing a framework that links small-molecule diversity to transcriptional plasticity, we hope to stimulate future research to explore the evolution, functions, and mechanisms of perception of a broad range of plant regulatory metabolites.

59 BASIC BIOLOGICAL SCIENCES↗

Evolutionary Stability of Microbial Mutualism in Simulated Microgravity

Sustainable long-term space travel will require astronauts to live in built environments cohabited by microbes. Though much of space biology research has focused on microbial monocultures, microbes naturally live in multispecies communities in which they compete and cooperate. Understanding how communities experience spaceflight over generations can influence sanitation measures and the design of synthetic communities for applications in spaceflight. In this study, we investigated the evolutionary stability of mutualism in multispecies communities in microgravity using a model system of cooperating microbes. Our model consisted of bioengineered strains of mutually dependent E. coli and S. enterica. E. coli metabolized lactose and produced a carbon source for S. enterica, which secreted methionine for E. coli. By introducing a noncooperative ("cheater") strain of S. enterica, we tested the dynamic stability of mutualism. Using a rotating wall vessel, we simulated microgravity, specifically a low-shear, diffusion-limited environment where metabolite transfer is limited compared to 1g conditions. Fluorescent motile and non-motile strains were used to assess how motility affects the microbial experience of microgravity. We hypothesized that mutualism in non-motile cocultures would be favored in microgravity due to the diffusion-limited spatial structure, while motile strains would show less difference between simulated microgravity and other conditions. We cultured communities for approximately 20 generations and assessed community composition over time using flow cytometry. We compared simulated microgravity to cultures grown in agar plates as spatially structured controls, shaken flasks as well-mixed controls, and still flasks representing the convective mixing of 1g. A high, sustained cooperator-to-cheater ratio represented stable mutualism within the community. Our results show that microbial communities may better maintain mutualism in microgravity compared to their counterparts in 1g conditions and that the motility of a community’s constituents influences how the community experiences microgravity on generational timescales.

Nathan Moreno↗

A Structural and Molecular Approach for the Study Biomarkers

Investigation of the nucleation and growth of crystals in both abiotic and biotic systems is critical to seemingly diverse disciplines of geology, biology, environmental science, and astrobiology. While there are abundant studies devoted to the determination of the structure and composition of inorganic crystals, as well as to the development of thermodynamic and kinetic models, it is only recently that research efforts have been directed towards understanding mineralization in biological systems (i.e., biomineralization). Biomineralization refers to the processes by which living organisms form inorganic solids. Studies of the processes of biomineralization under low temperature aqueous conditions have focused primarily on magnetite forming bacteria and shell forming marine organisms. Many of the biological building materials consist of inorganic minerals (calcium carbonate, calcium phosphate, silica or iron oxide) intricately combined with organic polymers (like proteins). More recently, efforts have been undertaken to explore the nature of biological activities in ancient rocks. In the absence of well-preserved microorganisms or genetic material required for the polmerase chain reaction (PCR) method in molecular phylogenetic studies, using biominerals as biomarkers offers an alternative approach for the recognition of biogenic activity in both terrestrial and extraterrestrial environments. The primary driving force in biomineralization is the interaction between organic and inorganic phases. Thus, the investigation of the ultrastructure and the nature of reactions at the molecular level occurring at the interface between inorganic and organic phases is essential to understanding the processes leading to the nucleation and growth of crystals. It is recognized that crystal surfaces can serve as the substrate for the organization of organic molecules that lead to the formation of polymers and other complex organic molecules, and in discussions of the origins of life, is referred to as organic synthesis on mineral surfaces. Furthermore, it is suggested that the interaction between mineral surfaces and simple organic molecules resulted in the formation of amino acids, RNA, and perhaps other more complex molecules such as proteins. On the other hand, in natural systems, it is recognized that functional groups on cell walls or membranes of microorganisms serve as sites of nucleation and crystallization. The precise replication of biominerals with controlled structure, morphology, size and texture is not confined to higher organisms as it also occurs in primitive prokaryotic cells such as magnetotactic bacteria and cyanobacteria. This suggests that the principal strategies of biomineralization were established early on in the evolutionary history of organisms. It is critical, therefore, to search for common mechanisms within diverse biological systems. One such common factor is the capability for organization and self-assembly. Organic macromolecules such as proteins and lipids can aggregate and polymerize forming membranes or extracellular matrix. At the organic-inorganic interface, several factors such as lattice geometry, polarity, stereochemistry and topography may act in concert to control nucleation and growth of crystals. Although several models have been proposed that discuss the significance of these factors for biomineralization, no comprehensive experimental data are available. In contrast to crystallization in exclusively inorganic systems, the kinetics of reaction and structural relationships between organic and inorganic phases in biominerals or biomimetic material is poorly understood. For example, it is not clear if the concept of epitactic growth (geometrical matching of unit cells at the interface of a secondary crystal growing on a primary crystal) applies to organic-inorganic systems. In contrast to inorganic templates that often have a smooth and rigid surface that promotes epitactic growth, biological substrates are usually rough and result in a large degree of mismatch. It is apparent that factors controlling the reaction at the crystal-matrix interface are strongly dependent upon the nature of the substrate. Therefore, characterization of the assembled organic surface and surface structure of the inorganic phase is crucial to understanding the processes of biomineralization. The focus of our research is the investigation of the processes leading to the nucleation and growth of crystals on both natural and synthetic systems through an interdisciplinary approach that integrates molecular biology, morphology and mineralogy using advanced preparation and analytical techniques. We have studied run-products, particularly magnetite, siderite and other carbonates, that resulted from extracellular biomineralization by extremophiles isolated from a variety of extreme environments ranging from permafrost to hydrothermal vent systems. The results of this study are critical to recognizing biomarkers in terrestrial and extraterrestrial environments.

Thomas-Keprta, Kathie↗

Phoresy in animals: review and synthesis of a common but understudied mode of dispersal

Phoresy is a type of interaction in which one species, the phoront, uses another species, the dispersal host, for transportation to new habitats or resources. Despite being a widespread behaviour, little is known about the ecology and evolution of phoresy. Our goal is to provide a comprehensive review of phoretic dispersal in animals and to bring renewed attention to this subject. We surveyed literature published between 1900 and 2020 to understand the extent of known higher-level taxonomic diversity (phyla, classes, and orders) and functional aspects of animals that use phoretic dispersal. Species dispersing phoretically have been observed in at least 13 animal phyla, 25 classes, and 60 orders. The majority of known phoronts are arthropods (Phylum Euarthropoda) in terrestrial habitats, but phoronts also occur in freshwater and marine environments. Marine phoronts may be severely under-represented in the literature due to the relative difficulty of studying these systems. Phoronts are generally small with low mobility and use habitats or resources that are ephemeral and/or widely dispersed. Many phoronts are also parasites. In general, animals that engage in phoresy use a wide variety of morphological and behavioural traits for locating, attaching to, and detaching from dispersal hosts, but the exact mechanisms behind these activities are largely unknown. In addition to diversity, we discuss the evolution of phoresy including the long-standing idea that it can be a precursor to parasitism and other forms of symbioses. To conclude, we suggest several areas of future research to improve our understanding of phoresy and its ecological and evolutionary significance.

59 BASIC BIOLOGICAL SCIENCES↗

Delimiting the cryptic diversity and host preferences of Sycophila parasitoid wasps associated with oak galls using phylogenomic data

Abstract Cryptic species diversity is a major challenge regarding the species‐rich community of parasitoids attacking oak gall wasps due to a high degree of sexual dimorphism, morphological plasticity, small size and poorly known biology. As such, we know very little about the number of species present, nor the evolutionary forces responsible for generating this diversity. One hypothesis is that trait diversity in the gall wasps, including the morphology of the galls they induce, has evolved in response to selection imposed by the parasitoid community, with reciprocal selection driving diversification of the parasitoids. Using a rare, continental‐scale data set of Sycophila parasitoid wasps reared from 44 species of cynipid galls from 18 species of oak across the USA, we combined mitochondrial DNA barcodes, ultraconserved elements (UCEs), morphological and natural history data to delimit putative species. Using these results, we generate the first large‐scale assessment of ecological specialization and host association in this species‐rich group, with implications for evolutionary ecology and biocontrol. We find most Sycophila target specific subsets of available cynipid host galls with similar morphologies, and generally attack larger galls. Our results suggest that parasitoid wasps such as Sycophila have adaptations allowing them to exploit particular host trait combinations, while hosts with contrasting traits are resistant to attack. These findings support the tritrophic niche concept for the structuring of plant–herbivore–parasitoid communities.

Zhang, Yuanmeng M.↗

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics

We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pre-training on over 110 million prokaryotic gene sequences and fine-tuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole-genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.

Zvyagin, Maxim↗

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High Synteny and Sequence Identity between Genomes of Nitrosococcus oceani Strains Isolated from Different Oceanic Gyres Reveals Genome Economization and Autochthonous Clonal Evolution

The ammonia-oxidizing obligate aerobic chemolithoautotrophic gammaproteobacterium, Nitrosococcus oceani, is omnipresent in the world’s oceans and as such important to the global nitrogen cycle. We generated and compared high quality draft genome sequences of N. oceani strains isolated from the Northeast (AFC27) and Southeast (AFC132) Pacific Ocean and the coastal waters near Barbados at the interface between the Caribbean Sea and the North Atlantic Ocean (C-27) with the recently published Draft Genome Sequence of N. oceani Strain NS58 (West Pacific Ocean) and the complete genome sequence of N. oceani C-107, the type strain (ATCC 19707) isolated from the open North Atlantic, with the goal to identify indicators for the evolutionary origin of the species. The genomes of strains C–107, NS58, C-27, and AFC27 were highly conserved in content and synteny, and these four genomes contained one nearly sequence-identical plasmid. The genome of strain AFC132 revealed the presence of genetic inventory unknown from other marine ammonia-oxidizing bacteria such as genes encoding NiFe-hydrogenase and a non-ribosomal peptide synthetase (NRPS)-like siderophore biosynthesis module. Comparative genome analysis in context with the literature suggests that AFC132 represents a metabolically more diverse ancestral lineage to the other strains with C-107 and NS58 potentially being the youngest. The results suggest that the N. oceani species evolved by genome economization characterized by the loss of genes encoding catabolic diversity while acquiring a higher redundancy in inventory dedicated to nitrogen catabolism, both of which could have been facilitated by their rich complements of CRISPR/Cas and Restriction Modification systems.

59 BASIC BIOLOGICAL SCIENCES↗

High Accuracy Indicators of Androgen Suppression Therapy Failure for Prostate Cancer—A Modeling Study

Prostate cancer is a serious public health concern in the United States. The primary obstacle to effective long-term management for prostate cancer patients is the eventual development of treatment resistance. Due to the uniquely chaotic nature of the neoplastic genome, it is difficult to determine the evolution of tumor composition over the course of treatment. Hence, a drug is often applied continuously past the point of effectiveness, thereby losing any potential treatment combination with that drug permanently to resistance. If a clinician is aware of the timing of resistance to a particular drug, then they may have a crucial opportunity to adjust the treatment to retain the drug’s usefulness in a potential treatment combination or strategy. In this study, we investigate new methods of predicting treatment failure due to treatment resistance using a novel mechanistic model built on an evolutionary interpretation of Droop cell quota theory. We analyze our proposed methods using patient PSA and androgen data from a clinical trial of intermittent treatment with androgen deprivation therapy. Our results produce two indicators of treatment failure. The first indicator, proposed from the evolutionary nature of the cancer population, is calculated using our mathematical model with a predictive accuracy of 87.3% (sensitivity: 96.1%, specificity: 65%). The second indicator, conjectured from the implication of the first indicator, is calculated directly from serum androgen and PSA data with a predictive accuracy of 88.7% (sensitivity: 90.2%, specificity: 85%). Our results demonstrate the potential and feasibility of using an evolutionary tumor dynamics model in combination with the appropriate data to aid in the adaptive management of prostate cancer.

59 BASIC BIOLOGICAL SCIENCES↗

Searching for Organics, Fossils, and Biology on Mars

One of the goals of Astrobiology is to understand life on a fundamental level. All life on Earth is constructed from the same basic biochemical building blocks consisting of 20 amino acids with left handed symmetry, five nucleotides, a few sugars of right handed symmetry and some lipids. Using the metaphor of computers this is equivalent to saying that all life shares the same hardware. Beyond hardware similarity, it is now known that all life has fundamentally the same software. The genetic code of life is common to all organisms. Some have argued that the "hammer of evolution is heavy" and life anywhere is likely to be composed of identical biochemical and genetic patterns. However, in a system as complex as biochemistry it is likely that there are numerous local optima and the details of the optimum found by evolutionary selection on another world would likely depend on the initial conditions and random developments in the early biological history on that world. To address these fundamental questions in Astrobiology we need a second example of life: a second genesis.

McKay, Christopher P.↗