REPINs are facultative genomic symbionts of bacterial genomes

Relationships among organisms, in which one lives inside of another, with benefits accruing to both partners, are referred to as endosymbiotic. Such relationships are common in the biological world, yet descriptions are confined to organismal life. Here we argue that short sequence repeats known as REPINs - whose replication is dependent on a non-jumping RAYT transposase - form a similar facultative symbiotic relationship with the bacterial chromosome. Evidence stems from distribution patterns across the eubacteria: persistence times of many millions of years, exceedingly rare duplication rates, vertical transmission, and population biology typical of living organisms, including population size fluctuations that correlate with available genome space. Additional analysis of patterns of REPIN evolution conform with theoretical predictions of conflict (and resolution) arising from the effects of selection operating simultaneously on REPINs and host cells. A search for similar kinds of genomic symbionts suggests that the REPIN-RAYT system is not unique.

3D Genome Contributes to Protein-Protein Interactome

Numerous computational methods have been proposed to predict protein-protein interactions, none of which however, considers the original DNA loci of the interacting proteins in the perspective of 3D genome. Here we retrospect the DNA origins of the interacting proteins in the context of 3D genome and discovered that 1) if a gene pair is more proximate in 3D genome, their corresponding proteins are more likely to interact. 2) signal peptide involvement of PPI affects the corresponding gene-gene proximity in 3D genome space. 3) by incorporating 3D genome information, existing PPI prediction methods can be further improved in terms of accuracy. Combining our previous discoveries, we conjecture the existence of 3D genome driven cellular compartmentalization, meaning the co-localization of DNA elements lead to increased probability of the co-localization of RNA elements and protein elements.

Fast and memory efficient approach for mapping NGS reads to a reference genome

New generation sequencing machines: Illumina and Solexa can generate millions of short reads from a given genome sequence on a single run. Alignment of these reads to a reference genome is a core step in Next-generation sequencing data analysis such as genetic variation and genome re-sequencing etc. Therefore there is a need of a new approach, efficient with respect to memory as well as time to align these enormous reads with the reference genome. Existing techniques such as MAQ, Bowtie, BWA, BWBBLE, Subread, Kart, and Minimap2 require huge memory for whole reference genome indexing and reads alignment. Gapped alignment versions of these techniques are also 20–40% slower than their respective normal versions. In this paper, an efficient approach: WIT for reference genome indexing and reads alignment using Burrows–Wheeler Transform (BWT) and Wavelet Tree (WT) is proposed. Both exact and approximate alignments are possible by it. Experimental work shows that the proposed approach WIT performs the best in case of protein sequence indexing. For indexing, the reference genome space required by WIT is 0.6[Formula: see text]N (N is the size of reference genome) whereas existing techniques BWA, Subread, Kart, and Minimap2 require space in between 1.25[Formula: see text]N to 5[Formula: see text]N. Experimentally, it is also observed that even using such small index size alignment time of proposed approach is comparable in comparison to BWA, Subread, Kart, and Minimap2. Other alignment parameters accuracy and confidentiality are also experimentally shown to be better than Minimap2. The source code of the proposed approach WIT is available at http://www.algorithm-skg.com/wit/home.html .

The fog of genetics: Known unknowns and unknown unknowns in the genetics of complex traits and diseases

Associating genetic variants with phenotypes is not only important to understand the underlying biology but also to identify potential drug targets for treating diseases. It is widely accepted that for most complex traits many associations remain to be discovered, the so-called “missing heritability.” Yet missing heritability can be estimated, it is a known unknown, and we argue is only a fraction of the unknowns in genetics. The majority of possible genetic variants in the genome space are either too rare to be detected or even entirely absent from populations, and therefore do not contribute to estimates of phenotypic or genetic variability. We call these unknown unknowns in genetics the “fog of genetics.” Using data from the 1000 Genomes Project we then show that larger genes with greater genetic diversity are more likely to be associated with human traits, demonstrating that genetic associations are biased towards particular types of genes and that the genetic information we are lacking about traits and diseases is potentially immense. Our results and model have multiple implications for how genetic variability is perceived to influence complex traits, provide insights on molecular mechanisms of disease and for drug discovery efforts based on genetic information.

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity —the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity—essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution.

Sex and Ageing: The Role of Sexual Recombination in Longevity

I use a set of machines based on the concept of nested rule systems built on the a modified version of the Wolfram elemental cellular automata to investigate the role of recombination in providing resistance to ageing. Class III and class IV machines are observed to respond differently to recombination. Class IV machines show recombinational centring in their neutral networks whereas class III machines respond negatively to recombination. Rule 110 shows a unusual response to recombination. Recombination selects for resistance to recombination, the population moves to regions of genome space with high redundancy, this results in organisms with highly robust genomes, more likely to complete development and to be long lived. The increase in longevity may be sufficient to compensate for the costs of sex, including the two fold cost of sex, through increased reproductive potential in long lived organisms requiring long maturation times. Large complex species should therefore be resistant to invasion by asexual mutants whereas small simple organisms with early maturation should be vulnerable to invasion by asexual forms.

Epistasis can lead to fragmented neutral spaces and contingency in evolution

In evolution, the effects of a single deleterious mutation can sometimes be compensated for by a second mutation which recovers the original phenotype. Such epistatic interactions have implications for the structure of genome space—namely, that networks of genomes encoding the same phenotype may not be connected by single mutational moves. We use the folding of RNA sequences into secondary structures as a model genotype–phenotype map and explore the neutral spaces corresponding to networks of genotypes with the same phenotype. In most of these networks, we find that it is not possible to connect all genotypes to one another by single point mutations. Instead, a network for a phenotypic structure with n bonds typically fragments into at least 2 n neutral components, often of similar size. While components of the same network generate the same phenotype, they show important variations in their properties, most strikingly in their evolvability and mutational robustness. This heterogeneity implies contingency in the evolutionary process.