Are there laws of genome evolution?

Cross-species gene-family fluctuations reveal the dynamics of horizontal transfers

Prokaryotes vary their protein repertoire mainly through horizontal transfer and gene loss. To elucidate the links between these processes and the cross-species gene-family statistics, we perform a large-scale data analysis of the cross-species variability of gene-family abundance (the number of members of the family found on a given genome). We find that abundance fluctuations are related to the rate of horizontal transfers. This is rationalized by a minimal theoretical model, which predicts this link. The families that are not captured by the model show abundance profiles that are markedly peaked around a mean value, possibly because of specific abundance selection. Based on these results, we define an abundance variability index that captures a family's evolutionary behavior (and thus some of its relevant functional properties) purely based on its cross-species abundance fluctuations. Analysis and model, combined, show a quantitative link between cross-species family abundance statistics and horizontal transfer dynamics, which can be used to analyze genome ‘flux’. Groups of families with different values of the abundance variability index correspond to genome sub-parts having different plasticity in terms of the level of horizontal exchange allowed by natural selection.

Rapid speciation with gene flow following the formation of Mt. Etna

Environmental or geological changes can create new niches that drive ecological species divergence without the immediate cessation of gene flow. However, few such cases have been characterized. On a recently formed volcano, Mt. Etna, Senecio aethnensis and S. chrysanthemifolius inhabit contrasting environments of high and low altitude, respectively. They have very distinct phenotypes, despite hybridizing promiscuously, and thus may represent an important example of ecological speciation “in action,” possibly as a response to the rapid geological changes that Mt. Etna has recently undergone. To elucidate the species’ evolutionary history, and help establish the species as a study system for speciation genomics, we sequenced the transcriptomes of the two Etnean species, and the outgroup, S. vernalis, using Illumina sequencing. Despite the species’ substantial phenotypic divergence, synonymous divergence between the high- and low-altitude species was low (dS = 0.016 ± 0.017 [SD]). A comparison of species divergence models with and without gene flow provided unequivocal support in favor of the former and demonstrated a recent time of species divergence (153,080 ya ± 11,470 [SE]) that coincides with the growth of Mt. Etna to the altitudes that separate the species today. Analysis of dN/dS revealed wide variation in selective constraint between genes, and evidence that highly expressed genes, more “multifunctional” genes, and those with more paralogs were under elevated purifying selection. Taken together, these results are consistent with a model of ecological speciation, potentially as a response to the emergence of a new, high-altitude niche as the volcano grew.

Modelling the yeast interactome

The topology behind biological interaction networks has been studied for over a decade. Yet, there is no definite agreement on the theoretical models which best describe protein-protein interaction (PPI) networks. Such models are critical to quantifying the significance of any empirical observation regarding those networks. Here, we perform a comprehensive analysis of yeast PPI networks in order to gain insights into their topology and its dependency on interaction-screening technology. We find that: (1) interaction-detection technology has little effect on the topology of PPI networks; (2) topology of these interaction networks differs in organisms with different cellular complexity (human and yeast); (3) clear topological difference is present between PPI networks, their functional sub-modules, and their inter-functional “linkers”; (4) high confidence PPI networks have more “geometrical” topology compared to predicted, incomplete, or noisy PPI networks; and (5) inter-functional “linker” proteins serve as mediators in signal transduction, transport, regulation and organisational cellular processes.

ComPlEx: conservation and divergence of co-expression networks in A. thaliana, Populus and O. sativa

Background

Divergence in gene regulation has emerged as a key mechanism underlying species differentiation. Comparative analysis of co-expression networks across species can reveal conservation and divergence in the regulation of genes.

Results

We inferred co-expression networks of A. thaliana, Populus spp. and O. sativa using state-of-the-art methods based on mutual information and context likelihood of relatedness, and conducted a comprehensive comparison of these networks across a range of co-expression thresholds. In addition to quantifying gene-gene link and network neighbourhood conservation, we also applied recent advancements in network analysis to do cross-species comparisons of network properties such as scale free characteristics and gene centrality as well as network motifs. We found that in all species the networks emerged as scale free only above a certain co-expression threshold, and that the high-centrality genes upholding this organization tended to be conserved. Network motifs, in particular the feed-forward loop, were found to be significantly enriched in specific functional subnetworks but where much less conserved across species than gene centrality. Although individual gene-gene co-expression had massively diverged, up to ~80% of the genes still had a significantly conserved network neighbourhood. For genes with multiple predicted orthologs, about half had one ortholog with conserved regulation and another ortholog with diverged or non-conserved regulation. Furthermore, the most sequence similar ortholog was not the one with the most conserved gene regulation in over half of the cases.

Conclusions

We have provided a comprehensive analysis of gene regulation evolution in plants and built a web tool for Comparative analysis of Plant co-Expression networks (ComPlEx, http://complex.plantgenie.org/). The tool can be particularly useful for identifying the ortholog with the most conserved regulation among several sequence-similar alternatives and can thus be of practical importance in e.g. finding candidate genes for perturbation experiments.

Diminishing return for increased Mappability with longer sequencing reads: implications of the k-mer distributions in the human genome

Background

The amount of non-unique sequence (non-singletons) in a genome directly affects the difficulty of read alignment to a reference assembly for high throughput-sequencing data. Although a longer read is more likely to be uniquely mapped to the reference genome, a quantitative analysis of the influence of read lengths on mappability has been lacking. To address this question, we evaluate the k-mer distribution of the human reference genome. The k-mer frequency is determined for k ranging from 20 bp to 1000 bp.

Results

We observe that the proportion of non-singletons k-mers decreases slowly with increasing k, and can be fitted by piecewise power-law functions with different exponents at different ranges of k. A slower decay at greater values for k indicates more limited gains in mappability for read lengths between 200 bp and 1000 bp. The frequency distributions of k-mers exhibit long tails with a power-law-like trend, and rank frequency plots exhibit a concave Zipf’s curve. The most frequent 1000-mers comprise 172 regions, which include four large stretches on chromosomes 1 and X, containing genes of biomedical relevance. Comparison with other databases indicates that the 172 regions can be broadly classified into two types: those containing LINE transposable elements and those containing segmental duplications.

Conclusion

Read mappability as measured by the proportion of singletons increases steadily up to the length scale around 200 bp. When read length increases above 200 bp, smaller gains in mappability are expected. Moreover, the proportion of non-singletons decreases with read lengths much slower than linear. Even a read length of 1000 bp would not allow the unique alignment of reads for many coding regions of human genes. A mix of techniques will be needed for efficiently producing high-quality data that cover the complete human genome.

Flagellated algae protein evolution suggests the prevalence of lineage-specific rules governing evolutionary rates of eukaryotic proteins

Understanding the general rules governing the rate of protein evolution is fundamental to evolutionary biology. However, attempts to address this issue in yeasts and mammals have revealed considerable differences in the relative importance of determinants for protein evolutionary rates. This phenomenon was previously explained by the fact that yeasts and mammals are different in many cellular and genomic properties. Flagellated algae species have several cellular and genomic characteristics that are intermediate between yeasts and mammals. Using partial correlation analyses on the evolution of 6,921 orthologous proteins from Chlamydomonas reinhardtii and Volvox carteri, we examined factors influencing evolutionary rates of proteins in flagellated algae. Previous studies have shown that mRNA abundance and gene compactness are strong determinants for protein evolutionary rates in yeasts and mammals, respectively. We show that both factors also influence algae protein evolution with mRNA abundance having a larger impact than gene compactness on the rates of algae protein evolution. More importantly, among all the factors examined, coding sequence (CDS) length has the strongest (positive) correlation with protein evolutionary rates. This correlation between CDS length and the rates of protein evolution is not due to alignment-related issues or domain density. These results suggest no simple and universal rules governing protein evolutionary rates across different eukaryotic lineages. Instead, gene properties influence the rate of protein evolution in a lineage-specific manner.

Systematic analysis of compositional order of proteins reveals new characteristics of biological functions and a universal correlate of macroevolution

We present a novel analysis of compositional order (CO) based on the occurrence of Frequent amino-acid Triplets (FTs) that appear much more than random in protein sequences. The method captures all types of proteomic compositional order including single amino-acid runs, tandem repeats, periodic structure of motifs and otherwise low complexity amino-acid regions. We introduce new order measures, distinguishing between ‘regularity’, ‘periodicity’ and ‘vocabulary’, to quantify these phenomena and to facilitate the identification of evolutionary effects. Detailed analysis of representative species across the tree-of-life demonstrates that CO proteins exhibit numerous functional enrichments, including a wide repertoire of particular patterns of dependencies on regularity and periodicity. Comparison between human and mouse proteomes further reveals the interplay of CO with evolutionary trends, such as faster substitution rate in mouse leading to decrease of periodicity, while innovation along the human lineage leads to larger regularity. Large-scale analysis of 94 proteomes leads to systematic ordering of all major taxonomic groups according to FT-vocabulary size. This is measured by the count of Different Frequent Triplets (DFT) in proteomes. The latter provides a clear hierarchical delineation of vertebrates, invertebrates, plants, fungi and prokaryotes, with thermophiles showing the lowest level of FT-vocabulary. Among eukaryotes, this ordering correlates with phylogenetic proximity. Interestingly, in all kingdoms CO accumulation in the proteome has universal characteristics. We suggest that CO is a genomic-information correlate of both macroevolution and various protein functions. The results indicate a mechanism of genomic ‘innovation’ at the peptide level, involved in protein elongation, shaped in a universal manner by mutational and selective forces.

Variations in compositionally ordered (CO) sections of proteins, such as amino acid runs, tandem repeats and low complexity regions, are often considered as a third type of genomic variation along with SNP and CNV. At the microevolutionary scale, they are involved in the rapid evolution of numerous biological functions and the development of novel phenotypic complex traits, including disease in human, in particular neurodegeneration and cancer. At the macroevolutionary scale, the best discriminating proteomic factor between super-kingdoms is the prevalence of CO proteins in eukaryotes. The analysis of CO structures has so far been quite eclectic. Here we introduce a novel unifying methodology, accounting for all types of low-complexity regions and repetitive phenomena, including the existence of large periodic structures in protein sequences. We define new CO measures providing insights into the correlation of CO with protein function and with evolution. In particular, a large-scale analysis of 94 proteomes shows that the CO vocabulary of frequently appearing amino acid triplets serves as a measure of taxonomic ordering separating major clades from each other. It unravels a missing genomic correlate of macroevolution and serves as a novel phylogenetic tool. This suggests that major CO generation occurs during the creation of a completely new species, i.e. during macroevolutionary events.

Replicon-dependent bacterial genome evolution: the case of Sinorhizobium meliloti

Many bacterial species, such as the alphaproteobacterium Sinorhizobium meliloti, are characterized by open pangenomes and contain multipartite genomes consisting of a chromosome and other large-sized replicons, such as chromids, megaplasmids, and plasmids. The evolutionary forces in both functional and structural aspects that shape the pangenome of species with multipartite genomes are still poorly understood. Therefore, we sequenced the genomes of 10 new S. meliloti strains, analyzed with four publicly available additional genomic sequences. Results indicated that the three main replicons present in these strains (a chromosome, a chromid, and a megaplasmid) partly show replicon-specific behaviors related to strain differentiation. In particular, the pSymB chromid was shown to be a hot spot for positively selected genes, and, unexpectedly, genes resident in the pSymB chromid were also found to be more widespread in distant taxa than those located in the other replicons. Moreover, through the exploitation of a DNA proximity network, a series of conserved “DNA backbones” were found to shape the evolution of the genome structure, with the rest of the genome experiencing rearrangements. The presented data allow depicting a scenario where the pSymB chromid has a distinctive role in intraspecies differentiation and in evolution through positive selection, whereas the pSymA megaplasmid mostly contributes to structural fluidity and to the emergence of new functions, indicating a specific evolutionary role for each replicon in the pangenome evolution.

Increments and duplication events of enzymes and transcription factors influence metabolic and regulatory diversity in prokaryotes

In this work, the content of enzymes and DNA-binding transcription factors (TFs) in 794 non-redundant prokaryotic genomes was evaluated. The identification of enzymes was based on annotations deposited in the KEGG database as well as in databases of functional domains (COG and PFAM) and structural domains (Superfamily). For identifications of the TFs, hidden Markov profiles were constructed based on well-known transcriptional regulatory families. From these analyses, we obtained diverse and interesting results, such as the negative rate of incremental changes in the number of detected enzymes with respect to the genome size. On the contrary, for TFs the rate incremented as the complexity of genome increased. This inverse related performance shapes the diversity of metabolic and regulatory networks and impacts the availability of enzymes and TFs. Furthermore, the intersection of the derivatives between enzymes and TFs was identified at 9,659 genes, after this point, the regulatory complexity grows faster than metabolic complexity. In addition, TFs have a low number of duplications, in contrast to the apparent high number of duplications associated with enzymes. Despite the greater number of duplicated enzymes versus TFs, the increment by which duplicates appear is higher in TFs. A lower proportion of enzymes among archaeal genomes (22%) than in the bacterial ones (27%) was also found. This low proportion might be compensated by the interconnection between the metabolic pathways in Archaea. A similar proportion was also found for the archaeal TFs, for which the formation of regulatory complexes has been proposed. Finally, an enrichment of multifunctional enzymes in Bacteria, as a mechanism of ecological adaptation, was detected.

Gene frequency distributions reject a neutral model of genome evolution

Evolution of prokaryotes involves extensive loss and gain of genes, which lead to substantial differences in the gene repertoires even among closely related organisms. Through a wide range of phylogenetic depths, gene frequency distributions in prokaryotic pangenomes bear a characteristic, asymmetrical U-shape, with a core of (nearly) universal genes, a “shell” of moderately common genes, and a “cloud” of rare genes. We employ mathematical modeling to investigate evolutionary processes that might underlie this universal pattern. Gene frequency distributions for almost 400 groups of 10 bacterial or archaeal species each over a broad range of evolutionary distances were fit to steady-state, infinite allele models based on the distribution of gene replacement rates and the phylogenetic tree relating the species in each group. The fits of the theoretical frequency distributions to the empirical ones yield model parameters and estimates of the goodness of fit. Using the Akaike Information Criterion, we show that the neutral model of genome evolution, with the same replacement rate for all genes, can be confidently rejected. Of the three tested models with purifying selection, the one in which the distribution of replacement rates is derived from a stochastic population model with additive per-gene fitness yields the best fits to the data. The selection strength estimated from the fits declines with evolutionary divergence while staying well outside the neutral regime. These findings indicate that, unlike some other universal distributions of genomic variables, for example, the distribution of paralogous gene family membership, the gene frequency distribution is substantially affected by selection.

Selection is no more efficient in haploid than in diploid life stages of an angiosperm and a moss

The masking hypothesis predicts that selection is more efficient in haploids than in diploids, because dominant alleles can mask the deleterious effects of recessive alleles in diploids. However, gene expression breadth and noise can potentially counteract the effect of masking on the rate at which genes evolve. Land plants are ideal to ask whether masking, expression breadth, or expression noise dominate in their influence on the rate of molecular evolution, because they have a biphasic life cycle in which the duration and complexity of the haploid and diploid phase varies among organisms. Here, we generate and compile genome-wide gene expression, sequence divergence, and polymorphism data for Arabidopsis thaliana and for the moss Funaria hygrometrica to show that the evolutionary rates of haploid- and diploid-specific genes contradict the masking hypothesis. Haploid-specific genes do not evolve more slowly than diploid-specific genes in either organism. Our data suggest that gene expression breadth influence the evolutionary rate of phase-specific genes more strongly than masking. Our observations have implications for the role of haploid life stages in the purging of deleterious mutations, as well as for the evolution of ploidy.

Influence of homology and node age on the growth of protein-protein interaction networks

Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so the dynamics of the two objects are intrinsically linked. Here we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions through the definition of three different node wiring or divergence schemes. A comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition and topology observables.

The Combinatorial Nature of Osmosensing in Fishes

Organisms exposed to altered salinity must be able to perceive osmolality change because metabolism has evolved to function optimally at specific intracellular ionic strength and composition. Such osmosensing comprises a complex physiological process involving many elements at organismal and cellular levels of organization. Input from numerous osmosensors is integrated to encode magnitude, direction, and ionic basis of osmolality change. This combinatorial nature of osmosensing is discussed with emphasis on fishes.

Lamarckian evolution of the giant Mimivirus in allopatric laboratory culture on amoebae

Acanthamoeba polyphaga Mimivirus has been subcultured 150 times on germ-free amoebae. This allopatric niche is very different from that found in the natural environment, where the virus is in competition with many other organisms. In this experiment, substantial gene variability and loss occurred concurrently with the emergence of phenotypically different viruses. We sought to quantify the respective roles of Lamarckian and Darwinian evolution during this experiment. We postulated that the Mimivirus genes that were down-regulated at the beginning of the allopatric laboratory culture and inactivated after 150 passages experienced Lamarckian evolution because phenotypic modifications preceded genotypic modifications, whereas we considered that genes that were highly transcribed in the new niche but were later inactivated obeyed Darwinian rules. We used the total transcript abundances and sequences described for the genes of Mimivirus at the beginning of its laboratory life and after 150 passages in allopatric culture on Acanthamoeba spp. We found a statistically significant positive correlation between the level of gene expression at the beginning of the culture and gene inactivation during the 150 passages. In particular, the mean transcript abundance at baseline was significantly lower for inactivated genes than for unchanged genes (165 ± 589 vs. 470 ± 1,625; p < 1e–3), and the mean transcript levels during the replication cycle of Mimivirus M1 were up to 8.5-fold lower for inactivated genes than for unchanged genes. In addition, proteins tended to be less frequently identified from purified virions in their early life in allopatric laboratory culture if they were encoded by variable genes than if they were encoded by conserved genes (9 vs. 15%; p = 0.062). Finally, Lamarckian evolution represented the evolutionary process encountered by 63% of the inactivated genes. Such observations may be explained by the lower level of DNA repair of useless genes.

The population genomics of a fast evolver: high levels of diversity, functional constraint, and molecular adaptation in the tunicate Ciona intestinalis

Phylogenomics has revealed the existence of fast-evolving animal phyla in which the amino acid substitution rate, averaged across many proteins, is consistently higher than in other lineages. The reasons for such differences in proteome-wide evolutionary rates are still unknown, largely because only a handful of species offer within-species genomic data from which molecular evolutionary processes can be deduced. In this study, we use next-generation sequencing technologies and individual whole-transcriptome sequencing to gather extensive polymorphism sequence data sets from Ciona intestinalis. Ciona is probably the best-characterized member of the fast-evolving Urochordata group (tunicates), which was recently identified as the sister group of the slow-evolving vertebrates. We introduce and validate a maximum-likelihood framework for single-nucleotide polymorphism and genotype calling, based on high-throughput short-read typing. We report that the C. intestinalis proteome is characterized by a high level of within-species diversity, efficient purifying selection, and a substantial percentage of adaptive amino acid substitutions. We conclude that the increased rate of amino acid sequence evolution in tunicates, when compared with vertebrates, is the consequence of both a 2–6 times higher per-year mutation rate and prevalent adaptive evolution.

A neutral theory of genome evolution and the frequency distribution of genes

Background

The gene composition of bacteria of the same species can differ significantly between isolates. Variability in gene composition can be summarized in terms of gene frequency distributions, in which individual genes are ranked according to the frequency of genomes in which they appear. Empirical gene frequency distributions possess a U-shape, such that there are many rare genes, some genes of intermediate occurrence, and many common genes. It would seem that U-shaped gene frequency distributions can be used to infer the essentiality and/or importance of a gene to a species. Here, we ask: can U-shaped gene frequency distributions, instead, arise generically via neutral processes of genome evolution?

Results

We introduce a neutral model of genome evolution which combines birth-death processes at the organismal level with gene uptake and loss at the genomic level. This model predicts that gene frequency distributions possess a characteristic U-shape even in the absence of selective forces driving genome and population structure. We compare the model predictions to empirical gene frequency distributions from 6 multiply sequenced species of bacterial pathogens. We fit the model with constant population size to data, matching U-shape distributions albeit without matching all quantitative features of the distribution. We find stronger model fits in the case where we consider exponentially growing populations. We also show that two alternative models which contain a "rigid" and "flexible" core component of genomes provide strong fits to gene frequency distributions.

Conclusions

The analysis of neutral models of genome evolution suggests that U-shaped gene frequency distributions provide less information than previously suggested regarding gene essentiality. We discuss the need for additional theory and genomic level information to disentangle the roles of evolutionary mechanisms operating within and amongst individuals in driving the dynamics of gene distributions.

Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis

Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.

Toward a theory of multilevel evolution: long-term information integration shapes the mutational landscape and enhances evolvability

Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical-chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. In any case, these results provide us with novel search images to tackle the wealth of biological data.