DNA Energy Code: “Survival of the Fittest”

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DNA Energy Code: “Survival of the Fittest” Feb 16, 2021 3:24:09 GMT

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Post by Admin on Feb 16, 2021 3:24:09 GMT

Correlating trimeric duplex stability with amino acid coding properties
Inspection of the data in Table 1 and Scheme 1 reveals eight exceptionally stable all-GC codons, as defined by the relative stability of the trimeric duplex they each form with their antiparallel, complementary codon. By the same criteria, a second group of significantly stable codons of the form, GCX, CGX, GGX, and CCX, also can be identified, although less resolved, where X is either T or A. It is noteworthy that collectively the GCX, CGX, GGX, and CCX families of stable codons code for Ala, Arg, Gly, and Pro, which are among the most abundant amino acids, and, save for Arg, also are considered ancient amino acids (Trifonov, 2000). Furthermore, when X = A or T, the complementary codons to this second group are XCG, XGC, XCC, and XGG. Except for Trp, these codons code for the amino acids Cys, Ser, and Thr, which, like Ala, Gly, and Pro noted above all are defined as ancient amino acids (Trifonov, 2000). This empirical correspondence between the stabilities of codons and the abundance as well as age of the amino acids for which they code raises the intriguing possibility of a stability-modulated, evolutionary shaping of the code.

These stable codon groups, and their corresponding, antiparallel codons, each occupy three positions within each of the eight cubes that make up the hypercube scaffolding that interconnect all 64 codons. This set of 24 ‘high-stability’, codon groupings may have been energetically favored ‘prebiotically’. As such, it is intriguing to note that all the other 40 codons can be generated/“evolved” from these most stable codons by, at most, three transition mutations; again suggestive of a stability-modulated, evolutionary shaping of the code.

To test the robustness of our conclusions, we conducted the same analyses for a dataset in which we reversed the polarities of the codon–complementary codon interactions to yield parallel codon couplets. This assessment yielded an altered energy spectrum, as well as changes in the stability rank order for the complementary codon couplets; particularly for the RRR/YYY and the YYR/RRY families of trimeric duplexes (columns 1 and 3 in Scheme 1). Further comparison of the antiparallel and parallel datasets also revealed differences in the energy changes associated with the sequential transition and transversion mutations. In the aggregate, these differential outcomes underscore the robustness of the correlations noted here between the stabilities of the antiparallel couplets and the shaping of the genetic code.

Correlations between larger domain DNA energy profiles and higher-order biological functions
One long-term goal is to define correlations between functional domains of the genome and the energy profiles of such domains. Some initial trends, that require further validation, include the suggestion by Klump and coworkers that protein-coding sequences predominately consist of codon domains of relatively uniform stability (Klump and Maeder, 1991). By contrast, Klump proposes that signal sequences exhibit less uniform and less stable domains, while also being more sensitive to local changes in cellular and sequence/structural environments, thereby allowing them to amplify a perturbation in a localized sequence. This biophysical behavior is what one would expect for a biological signal transducer. Coding sequences, by contrast, are less sensitive to environmental conditions, also consistent with their biological function to faithfully code for a protein. Much more research is required to establish a robust biophysical map of genomes to test such hypotheses. However, these intriguing early correlations should motivate such efforts, including a parallel analysis for RNA.

Concluding remarks
We have reviewed, presented, and integrated evidence that the iconic chemical genetic code also can be viewed as a differential energy code that influences biological outcomes. This perspective includes implications for differential, energy-based, molecular contributions to classic Darwinian evolutionary theory. In short, evolutionary pressures may well derive from the optimization of fundamental biophysical properties, as well as from the classic perspective of being driven to yield a functionally adaptive advantage for either a biopolymer or an organism.

Darwinian evolution, when proceeding over sufficiently long timeframes, leaves only the evolutionary ‘winners’ behind. This reality makes it difficult, if not impossible, to deduce, with any certitude, the precursors or evolutionary pathways that ultimately culminated in the current, evolved ‘winners’. However, by evoking the laws of thermodynamics, it becomes possible via considerations of thermodynamic selection and linkages, as illustrated in the hypercube of Fig. 2, to speculate on what may have preceded these ‘left behind winners’. It is precisely the beauty of thermodynamics that follows universal laws, under all conditions and times, that allows one to extrapolate backward from the ‘left behind winners’ to make informed speculations as to how these winners may have evolved from earlier remnants (molecular fossils).

Consistent with this perspective is our hypothesis that the evolution of the genetic code was shaped and modulated by the differential stabilities of complementary codons; a feature reflective of ‘molecular Darwinism’. As thermodynamic fingerprints of such an evolutionary influence, we found correlations between the free energies of formation of antiparallel, complementary DNA trimers and their codon usage frequency. We also noted correlations between the stabilities of complementary codon couplets and those that code for ‘ancient’ amino acids. Collectively, our observations are consistent with a scenario in which the genetic code, driven by differential codon stabilities, evolved under the influence and regulation of a series of interlocking thermodynamic cycles. We proposed that these coupled energy cycles controlled the transition and transversion mutations of a group of the 24 most ancient (‘prebiotic’) and stable codon pairs, ultimately yielding the complete 64 codon code; via a form of ‘thermodynamic selection’. As such, we suggested that the evolution of the genetic code exhibits contributions from both stability-driven ‘molecular’/genotypic Darwinism as well as the more traditional, phenotypic Darwinism. As we stated in the Abstract, yet worth repeating, it is not surprising that evolution of the code was influenced by differential energetics, as thermodynamics is the most general and universal branch of science that operates over all time and length scales.

Going forward
Given the correlative examples noted here, going forward it seems justified to create a comprehensive energy map of the human genome; or for that matter, the genome of any organism of interest. The differential energy domains so characterized may correlate with known functionalities; or may reveal and yield insights into regions of yet defined function. Such profiling to create an ‘energy genome’ would yield a thermodynamic bridge between sequence, structure, and biological function.

Postscript: Shortly after the beginning of the 20th century, Albert Einstein (Schilpp and Einstein, 1949) declared:

‘A theory is the more impressive the greater the simplicity of its premises, the more different kinds of things it relates, and the more extended its area of applicability. Therefore the deep impression that classical thermodynamics made upon me. It is the only physical theory of universal content which I am convinced will never be overthrown, within the framework of applicability of its basic concepts’.

As biophysical chemists, the authors consider the ultimate exemplar/test of this assertion to be the demonstration that the molecular language and complexities of biology embedded in the genetic code can be rationalized in terms of fundamental thermodynamic principles.

Financial support
This research was supported by grants from the NIH GM23509, GM34469, and CA47995 (to K.J.B.) and NRF (Pretoria, RSA) grant GUN 61103 to H.H.K.

Last Edit: Feb 16, 2021 3:26:44 GMT by Admin

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DNA Energy Code: “Survival of the Fittest” Feb 20, 2021 19:59:25 GMT

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Post by Admin on Feb 20, 2021 19:59:25 GMT

How many genetic changes create new species?
Patrik Nosil1,2, Jeffrey L. Feder3, Zachariah Gompert2

Science 19 Feb 2021:
Vol. 371, Issue 6531, pp. 777-779
DOI: 10.1126/science.abf6671

The formation of new species generates biodiversity and is often driven by evolution through natural selection. However, the number of genetic changes involved in speciation is largely unknown. Many theoretical models predict that if speciation occurs without geographic isolation, it will be driven by a small number of genes. The logic is that only the few genes that experience the strongest natural selection can overcome the homogenizing effect of genetic mixing (i.e., gene flow) to diverge between populations. However, empirical studies in plants and animals now suggest that speciation—even with gene flow—involves differentiation in surprisingly many genetic regions. This is thought possible because the effects of selection can become coupled across correlated genes such that the selection each gene experiences is much stronger than it would receive in isolation. Thus, the potential for genes to evolve collectively because of coupling may be a key to understanding speciation.

Over recent decades, major strides have been made in understanding the speciation process, which is characterized by the evolution of reproductive isolation (i.e., barriers to interbreeding) and eventually widespread differentiation across the genome. For example, it is now known that natural selection often drives speciation (1). Moreover, it has been shown that selection can stem from the ecological environment, as proposed by Darwin, or can occur within genomes through conflict and competition between genetic elements.

In contrast to improved knowledge of the role of selection in speciation, the genetic changes involved are less understood (1). Filling this gap in understanding is important because genetic details, such as the number of genes affected by selection and their genomic organization, can influence the dynamics by which new species form (2, 3). For example, if only a few genes that are found together on the same chromosome drive speciation, the process could be highly constrained. By contrast, if many different genes and types of genetic changes drive speciation, the process may be more flexible, but less predictable (3). Although specific forms of reproductive isolation are known to be controlled by many genes, the overall genome-wide architecture of differentiation during the active phases of speciation remains poorly understood (1).

A key consideration is whether geographic factors allow interbreeding between diverging populations (i.e., gene flow) (2–5). When divergence occurs with strong geographic isolation—for example between mountain ranges—independent populations can readily diverge in many genetic regions by the combination of natural selection and chance. The situation with gene flow is different. This is because gene flow acts as a homogenizing force that mixes genes between populations, keeping them similar and preventing them from diverging into separate species. For speciation to occur, natural selection must act in contrasting directions in different populations, to oppose this mixing effect and generate differences. Amounts of gene flow, and thus the selection required to counter them, form a continuum ranging from absent or low to high and can vary over time and space during the speciation process.

Theoretical models predict that speciation with high gene flow is promoted by concentrated genetic architectures comprising one or few genes of large effect (2–4). This allows these few genes to experience strong natural selection to overcome gene flow. That is, selection needs to be concentrated on a few regions, rather than being spread thin among many genes. For example, with a gene flow rate of 0.10 (10% of individuals are immigrants), divergence occurs more readily if two genes each experience a selection intensity of 0.20 each (20% difference in expected fitness, higher than the gene flow rate) than if 10 genes experience an intensity of 0.04 (weaker than gene flow). The total selection intensity of 0.40 is the same in these two cases, but per gene, selection is stronger than gene flow only in the former (5). Thus, models and some findings have led to the concept that speciation with gene flow is driven by a few, isolated genomic islands of divergence. The remainder of the genome is overwhelmed by gene flow and cannot diverge.

In contrast to these theoretical predictions, emerging data suggest that speciation with gene flow can involve many genetic regions. For example, population differentiation and reproductive isolation based on numerous regions across the genome have now been reported in systems diverging with gene flow, including insects (e.g., Anopheles mosquitoes, Rhagoletis flies, Timema stick insects) (6–8), fish (cichlids and stickleback) (9, 10), and plants (sunflowers) (11), among others. Moreover, when divergence does occur in few genetic regions, this is often associated with discrete phenotypic morphs (as in mimetic butterflies) (12), rather than the strong reproductive isolation and genome-wide differentiation that characterize distinct species. In some cases, different outcomes have even been tied to variation in the genetic architecture of diverging traits. For example, differentiation in a genetic region controlling coloration generates morphs of Midas cichlid fish, but speciation and stable genome-wide differentiation involve traits controlled by a greater number of genes, such as jaw morphology and body shape (9). Thus, divergence in polygenic traits and multiple genetic regions seems key to progress toward speciation in some systems (see the figure).

Given that models predict that speciation with gene flow will involve few genes, can these recent empirical findings be reconciled with theory? The answer is yes, but this requires a look at a different body of theory, focused on geographic clines, which describes how allele frequencies change over space. This theory was largely developed in the 1980s by Nick Barton and colleagues to understand the dynamics of hybrid zones between species (13). The models show how statistical associations between different genetic regions (called “linkage disequilibrium”) can cause selection on one genetic region to be transferred to other correlated genetic regions. In essence, selection spills over, through association, from one genetic region to others. In this manner, the effects of selection can spread and become coupled across the genome, rather than being isolated to single genes (4, 13). Such coupling means that the total selection that each genetic region experiences is much stronger than the direct selection it experiences in isolation. Thus, numerous genetic regions can evolve collectively as a unit to overcome gene flow (4).

Notably, the geographic configuration of populations can change during the speciation process, as species ranges expand and contract over time. This means that gene flow itself can be dynamic and change over time. Rather than occurring entirely in the presence or absence of gene flow, speciation likely involves periods of each. In turn, this can result in episodic hybridization, with diverse implications for evolution. For example, periods of geographic isolation might allow a pool of standing genetic variation to build up, including in structural features such as chromosomal inversions, which kick-starts the coupling process and later aids divergence with gene flow (4, 14). Moreover, occasional bouts of gene flow can play a creative role in evolution by allowing for introgression of genes that facilitate adaptation, as reported in tropical butterflies (12), cichlids (14), sunflowers (11), and Darwin's finches (15). Thus, gene flow can have creative as well as homogenizing effects, and speciation likely reflects a balance between these effects.

Ideas concerning few versus many genes driving speciation are not in conflict. This is exemplified by Helianthus sunflowers (11) and Rhagoletis flies (7). In both systems, differentiation occurs genome-wide on many chromosomes but is accentuated in regions of reduced recombination, such as those harboring inversions. Thus, even with widespread genomic differentiation, by no means do all genetic regions always diverge equally; those under strong selection or experiencing low recombination may diverge more readily. Moreover, interactions between genes can amplify how strongly genes cause reproductive isolation, again making some genes more critical for speciation than others. Indeed, even speciation involving many genetic regions likely involves a finite number of building blocks, which can be combined in different ways to create diversity, as reported in sunflowers (11) and cichlids (14).

Despite this emerging evidence for the potential importance of genomic coupling in speciation, much work remains to be done. For example, almost all studies to date are purely correlational and often not highly replicated. Thus, experiments are needed to test causal effects of differentiated regions on reproductive isolation and coupling, as are larger studies examining numerous taxon pairs. Such experiments could comprise experimental evolution studies in the lab or field transplants in the wild. Moreover, natural history and molecular studies, including those using ancient DNA, are required to establish whether divergence really occurred with gene flow. This is critical because false inference of gene flow could lead to erroneous evidence for coupling, because numerous genetic regions diverge between isolated populations through other processes (5). Moreover, genome assembly errors, particularly in regions of low recombination, could lead to a single genetic region being falsely inferred as multiple regions of differentiation. Nonetheless, initial evidence points to coupling as a consideration for understanding speciation. In turn, this suggests that sets of genes might exhibit emergent properties not seen by individual genes, implying the potential for sudden tipping points in the ability for selection to overcome gene flow (4).

By combining theory and data, evolutionary biologists are now poised to better understand how new species are created. A large part of this understanding will involve discovering how the effects of genes and phenotypes become coupled to cause a transition from polymorphism or geographic variation within species to genome-wide differences between distinct species. A major outstanding question is the extent to which the microevolutionary process of coupling can explain broader macroevolutionary patterns of biodiversity, as observed in radiations such as those in cichlid fish (9, 14).