RNA processing in evolution. The logic of soft-wired genomes

The Intransitive Logic of Directed Cycles and Flipons Enhances the Evolution of Molecular Computers by Augmenting the Kolmogorov Complexity of Genomes

Cell responses are usually viewed as transitive events with fixed inputs and outputs that are regulated by feedback loops. In contrast, directed cycles (DCs) have all nodes connected, and the flow is in a single direction. Consequently, DCs can regenerate themselves and implement intransitive logic. DCs are able to couple unrelated chemical reactions to each edge. The output depends upon which node is used as input. DCs can also undergo selection to minimize the loss of thermodynamic entropy while maximizing the gain of information entropy. The intransitive logic underlying DCs enhances their programmability and impacts their evolution. The natural selection of DCs favors the persistence, adaptability, and self-awareness of living organisms and does not depend solely on changes to coding sequences. Rather, the process can be RNA-directed. I use flipons, nucleic acid sequences that change conformation under physiological conditions, as a simple example and then describe more complex DCs. Flipons are often encoded by repeats and greatly increase the Kolmogorov complexity of genomes by adopting alternative structures. Other DCs allow cells to regenerate, recalibrate, reset, repair, and rewrite themselves, going far beyond the capabilities of current computational devices. Unlike Turing machines, cells are not designed to halt but rather to regenerate.

Brain cell somatic gene recombination and its phylogenetic foundations

A new form of somatic gene recombination (SGR) has been identified in the human brain that affects the Alzheimer's disease gene, amyloid precursor protein (APP). SGR occurs when a gene sequence is cut and recombined within a single cell's genomic DNA, generally independent of DNA replication and the cell cycle. The newly identified brain SGR produces genomic complementary DNAs (gencDNAs) lacking introns, which integrate into locations distinct from germline loci. This brief review will present an overview of likely related recombination mechanisms and genomic cDNA-like sequences that implicate evolutionary origins for brain SGR. Similarities and differences exist between brain SGR and VDJ recombination in the immune system, the first identified SGR form that now has a well-defined enzymatic machinery. Both require gene transcription, but brain SGR uses an RNA intermediate and reverse transcriptase (RT) activity, which are characteristics shared with endogenous retrotransposons. The identified gencDNAs have similarities to other cDNA-like sequences existing throughout phylogeny, including intron-less genes and inactive germline processed pseudogenes, with likely overlapping biosynthetic processes. gencDNAs arise somatically in an individual to produce multiple copies; can be functional; appear most frequently within postmitotic cells; have diverse sequences; change with age; and can change with disease state. Normally occurring brain SGR may represent a mechanism for gene optimization and long-term cellular memory, whereas its dysregulation could underlie multiple brain disorders and, potentially, other diseases like cancer. The involvement of RT activity implicates already Food and Drug Administration-approved RT inhibitors as possible near-term interventions for managing SGR-associated diseases and suggest next-generation therapeutics targeting SGR elements.

Simple Repeats as Building Blocks for Genetic Computers

Processing of RNA involves heterogeneous nuclear ribonucleoproteins. The simple sequence repeats (SSRs) they bind can also adopt alternative DNA structures, like Z DNA, triplexes, G quadruplexes, and I motifs. Those SSRs capable of switching conformation under physiological conditions (called flipons) are genetic elements that can encode alternative RNA processing by their effects on RNA processivity, most likely as DNA:RNA hybrids. Flipons are elements of a binary, instructive genetic code directing how genomic sequences are compiled into transcripts. The combinatorial nature of this code provides a rich set of options for creating genetic computers able to reproduce themselves and use a heritable and evolvable code to optimize survival. The underlying computational logic potentiates a diverse set of genetic programs that modify cis-mediated heritability and disease risk.

The State of Long Non-Coding RNA Biology

Transcriptomic studies have demonstrated that the vast majority of the genomes of mammals and other complex organisms is expressed in highly dynamic and cell-specific patterns to produce large numbers of intergenic, antisense and intronic long non-protein-coding RNAs (lncRNAs). Despite well characterized examples, their scaling with developmental complexity, and many demonstrations of their association with cellular processes, development and diseases, lncRNAs are still to be widely accepted as major players in gene regulation. This may reflect an underappreciation of the extent and precision of the epigenetic control of differentiation and development, where lncRNAs appear to have a central role, likely as organizational and guide molecules: most lncRNAs are nuclear-localized and chromatin-associated, with some involved in the formation of specialized subcellular domains. I suggest that a reassessment of the conceptual framework of genetic information and gene expression in the 4-dimensional ontogeny of spatially organized multicellular organisms is required. Together with this and further studies on their biology, the key challenges now are to determine the structure–function relationships of lncRNAs, which may be aided by emerging evidence of their modular structure, the role of RNA editing and modification in enabling epigenetic plasticity, and the role of RNA signaling in transgenerational inheritance of experience.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs.

The rise of regulatory RNA

Discoveries over the past decade portend a paradigm shift in molecular biology. Evidence suggests that RNA is not only functional as a messenger between DNA and protein but also involved in the regulation of genome organization and gene expression, which is increasingly elaborate in complex organisms. Regulatory RNA seems to operate at many levels; in particular, it plays an important part in the epigenetic processes that control differentiation and development. These discoveries suggest a central role for RNA in human evolution and ontogeny. Here, we review the emergence of the previously unsuspected world of regulatory RNA from a historical perspective.

Next-generation sequencing: from understanding biology to personalized medicine

Within just a few years, the new methods for high-throughput next-generation sequencing have generated completely novel insights into the heritability and pathophysiology of human disease. In this review, we wish to highlight the benefits of the current state-of-the-art sequencing technologies for genetic and epigenetic research. We illustrate how these technologies help to constantly improve our understanding of genetic mechanisms in biological systems and summarize the progress made so far. This can be exemplified by the case of heritable heart muscle diseases, so-called cardiomyopathies. Here, next-generation sequencing is able to identify novel disease genes, and first clinical applications demonstrate the successful translation of this technology into personalized patient care.

Deconstructing the dogma: a new view of the evolution and genetic programming of complex organisms

Since the birth of molecular biology it has been generally assumed that most genetic information is transacted by proteins, and that RNA plays an intermediary role. This led to the subsidiary assumption that the vast tracts of noncoding sequences in the genomes of higher organisms are largely nonfunctional, despite the fact that they are transcribed. These assumptions have since become articles of faith, but they are not necessarily correct. I propose an alternative evolutionary history whereby developmental and cognitive complexity has arisen by constructing sophisticated RNA-based regulatory networks that interact with generic effector complexes to control gene expression patterns and the epigenetic trajectories of differentiation and development. Environmental information can also be conveyed into this regulatory system via RNA editing, especially in the brain. Moreover, the observations that RNA-directed epigenetic changes can be inherited raises the intriguing question: has evolution learnt how to learn?

Deletion of many yeast introns reveals a minority of genes that require splicing for function

Splicing regulates gene expression and contributes to proteomic diversity in higher eukaryotes. However, in yeast only 283 of the 6000 genes contain introns and their impact on cell function is not clear. To assess the contribution of introns to cell function, we initiated large-scale intron deletions in yeast with the ultimate goal of creating an intron-free model eukaryote. We show that about one-third of yeast introns are not essential for growth. Only three intron deletions caused severe growth defects, but normal growth was restored in all cases by expressing the intronless mRNA from a heterologous promoter. Twenty percent of the intron deletions caused minor phenotypes under different growth conditions. Strikingly, the combined deletion of all introns from the 15 cytoskeleton-related genes did not affect growth or strain fitness. Together, our results show that although the presence of introns may optimize gene expression and provide benefit under stress, a majority of introns could be removed with minor consequences on growth under laboratory conditions, supporting the view that many introns could be phased out of Saccharomyces cerevisiae without blocking cell growth.

A new paradigm for developmental biology

It is usually thought that the development of complex organisms is controlled by protein regulatory factors and morphogenetic signals exchanged between cells and differentiating tissues during ontogeny. However, it is now evident that the majority of all animal genomes is transcribed, apparently in a developmentally regulated manner, suggesting that these genomes largely encode RNA machines and that there may be a vast hidden layer of RNA regulatory transactions in the background. I propose that the epigenetic trajectories of differentiation and development are primarily programmed by feed-forward RNA regulatory networks and that most of the information required for multicellular development is embedded in these networks, with cell–cell signalling required to provide important positional information and to correct stochastic errors in the endogenous RNA-directed program.

Efficient inefficiency: biochemical "junk" may represent molecular bridesmaids awaiting emergent function as a buffer against environmental fluctuation

The biochemical function of many parts of the genome, transcriptome, proteome, and interactome remain largely unknown. We propose that portions of these fundamental building blocks of life have no current biochemical function per se. Rather, sections of these "omes" may contribute to an inventory of biochemical parts and circuits that participate in the development of emergent functions. Low fidelity deoxyribonucleic acid replication, transcription, translation, and post-translational modification all represent potential mechanisms to produce an inventory of parts. Stochastic processes that influence the conformations of ribonucleic acid molecules and proteins may also contribute to potential biochemical inventory. Some components of the biochemical inventory may enable future adaptations, some may produce disease, and some may remain useless. The function of many of these components await discovery, not by science, but by evolution. While carrying such purposeless biochemical units may appear to dilute fitness by exacting a thermodynamic cost, we argue that net fitness becomes enhanced when considering the value for potential future innovations. One can envision components that intermingle, interact, and act out mock pathways, but in most cases remain molecular bridesmaids. Given sufficiently low thermodynamic cost, such stochastic cycling may persist until a markedly advantageous or cataclysmically disadvantageous trait emerges. Maladaptive screening and utilization of inventory content can lead to disease phenotypes, a process buffered and regulated in part by the heat shock protein and stress response network. Whereas failure of the ubiquitin pathway to recycle misfolded proteins has become increasingly recognized as a source of disease, protein misfolding may itself represent one step in a process that maximizes functional innovation through increasing proteomic diversity. Fractal correlates of these processes occur at the organizational level of cells and organisms. That the abnormal accumulation of units induces local collapse may serve to limit the extension of damage to the greater system at large. The immune and cognitive systems that selectively sample and prune environmental content may serve as additional portals for innovation.

Reverse transcription in genome evolution

As reverse transcription is predominantly performed by retrotransposable elements, the process is often entirely associated with the propagation of these elements. However, as a unique tool for transmitting information from the dynamic RNA to the more inert DNA, reverse transcription has been instrumental in shaping extant genomes. This review aims at presenting the diversity by which reverse transcription has influenced modern genomic structures.

Prokaryote and eukaryote evolvability

The concept of evolvability covers a broad spectrum of, often contradictory, ideas. At one end of the spectrum it is equivalent to the statement that evolution is possible, at the other end are untestable post hoc explanations, such as the suggestion that current evolutionary theory cannot explain the evolution of evolvability. We examine similarities and differences in eukaryote and prokaryote evolvability, and look for explanations that are compatible with a wide range of observations. Differences in genome organisation between eukaryotes and prokaryotes meets this criterion. The single origin of replication in prokaryote chromosomes (versus multiple origins in eukaryotes) accounts for many differences because the time to replicate a prokaryote genome limits its size (and the accumulation of junk DNA). Both prokaryotes and eukaryotes appear to switch from genetic stability to genetic change in response to stress. We examine a range of stress responses, and discuss how these impact on evolvability, particularly in unicellular organisms versus complex multicellular ones. Evolvability is also limited by environmental interactions (including competition) and we describe a model that places limits on potential evolvability. Examples are given of its application to predator competition and limits to lateral gene transfer. We suggest that unicellular organisms evolve largely through a process of metabolic change, resulting in biochemical diversity. Multicellular organisms evolve largely through morphological changes, not through extensive changes to cellular biochemistry.

Non-coding RNAs: the architects of eukaryotic complexity

Around 98% of all transcriptional output in humans is non-coding RNA. RNA-mediated gene regulation is widespread in higher eukaryotes and complex genetic phenomena like RNA interference, co-suppression, transgene silencing, imprinting, methylation, and possibly position-effect variegation and transvection, all involve intersecting pathways based on or connected to RNA signaling. I suggest that the central dogma is incomplete, and that intronic and other non-coding RNAs have evolved to comprise a second tier of gene expression in eukaryotes, which enables the integration and networking of complex suites of gene activity. Although proteins are the fundamental effectors of cellular function, the basis of eukaryotic complexity and phenotypic variation may lie primarily in a control architecture composed of a highly parallel system of trans-acting RNAs that relay state information required for the coordination and modulation of gene expression, via chromatin remodeling, RNA-DNA, RNA-RNA and RNA-protein interactions. This system has interesting and perhaps informative analogies with small world networks and dataflow computing.

The evolution of controlled multitasked gene networks: the role of introns and other noncoding RNAs in the development of complex organisms

Eukaryotic phenotypic diversity arises from multitasking of a core proteome of limited size. Multitasking is routine in computers, as well as in other sophisticated information systems, and requires multiple inputs and outputs to control and integrate network activity. Higher eukaryotes have a mosaic gene structure with a dual output, mRNA (protein-coding) sequences and introns, which are released from the pre-mRNA by posttranscriptional processing. Introns have been enormously successful as a class of sequences and comprise up to 95% of the primary transcripts of protein-coding genes in mammals. In addition, many other transcripts (perhaps more than half) do not encode proteins at all, but appear both to be developmentally regulated and to have genetic function. We suggest that these RNAs (eRNAs) have evolved to function as endogenous network control molecules which enable direct gene-gene communication and multitasking of eukaryotic genomes. Analysis of a range of complex genetic phenomena in which RNA is involved or implicated, including co-suppression, transgene silencing, RNA interference, imprinting, methylation, and transvection, suggests that a higher-order regulatory system based on RNA signals operates in the higher eukaryotes and involves chromatin remodeling as well as other RNA-DNA, RNA-RNA, and RNA-protein interactions. The evolution of densely connected gene networks would be expected to result in a relatively stable core proteome due to the multiple reuse of components, implying that cellular differentiation and phenotypic variation in the higher eukaryotes results primarily from variation in the control architecture. Thus, network integration and multitasking using trans-acting RNA molecules produced in parallel with protein-coding sequences may underpin both the evolution of developmentally sophisticated multicellular organisms and the rapid expansion of phenotypic complexity into uncontested environments such as those initiated in the Cambrian radiation and those seen after major extinction events.