Are There Laws of Genome Evolution?

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.     

A statistical model for the genetic origin of allometric scaling laws in biology

Many biological processes, from cellular metabolism to population dynamics, are characterized by particular allometric scaling (power-law) relationships between size and rate. Although such allometric relationships may be under genetic determination, their precise genetic mechanisms have not been clearly understood due to a lack of a statistical analytical method. In this paper, we present a basic statistical framework for mapping quantitative genes (or quantitative trait loci, QTL) responsible for universal quarter-power scaling laws of organic structure and function with the entire body size. Our model framework allows the testing of whether a single QTL affects the allometric relationship of two traits or whether more than one linked QTL is segregating. Like traditional multi-trait mapping, this new model can increase the power to detect the underlying QTL and the precision of its localization on the genome. Beyond the traditional method, this model is integrated with pervasive scaling laws to take advantage of the mechanistic relationships of biological structures and processes. Simulation studies indicate that the estimation precision of the QTL position and effect can be improved when the scaling relationship of the two traits is considered. The application of our model in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship of third-year stem height with third-year stem biomass. The model proposed here has implications for genetic, evolutionary, biomedicinal and breeding research.     

Evolutionary analysis of glycosyl hydrolase family 28 (GH28) suggests lineage-specific expansions in necrotrophic fungal pathogens

Glycosyl hydrolase family 28 (GH28) is a set of structurally related enzymes that hydrolyze glycosidic bonds in pectin, and are important extracellular enzymes for both pathogenic and saprotrophic fungi. Yet, very little is understood about the evolutionary forces driving the diversification of GH28s in fungal genomes. We reconstructed the evolutionary history of family GH28 in fungi by examining the distribution of GH28 copy number across the phylogeny of fungi, and by reconstructing the phylogeny of GH28 genes. We also examined the relationship between lineage-specific GH28 expansions and fungal ecological strategy, testing the hypothesis that GH28 evolution in fungi is driven by ecological strategy (pathogenic vs. non-pathogenic) and pathogenic niche (necrotrophic vs. biotrophic). Our results showed that GH28 phylogeny of Ascomycota and Basidiomycota sequences was structured by specific biochemical function, with endo-polygalacturonases and endo-rhamnogalacturonases forming distinct, apparently ancient clades, while exo-polygalacturonases are more widely distributed. In contrast, Mucoromycotina and Stramenopile sequences formed taxonomically-distinct clades. Large, lineage-specific variation in GH28 copy number indicates that the evolution of this gene family is consistent with the birth-and-death model of gene family evolution, where diversity of GH28 loci within genomes was generated through multiple rounds of gene duplication followed by functional diversification and loss of some gene family members. Although GH28 copy number was correlated with genome size, our findings suggest that ecological strategy also plays an important role in determining the GH28 repertoire of fungi. Both necrotrophic and biotrophic fungi have larger genomes than non-pathogens, yet only necrotrophs possess more GH28 enzymes than non-pathogens. Hence, lineage-specific GH28 expansion is the result of both variation in genome size across fungal species and diversifying selection within the necrotrophic plant pathogen ecological niche. GH28 evolution among necrotrophs has likely been driven by a co-evolutionary arms race with plants, whereas the need to avoid plant immune responses has resulted in purifying selection within biotrophic fungi.     

The evolution of domain-content in bacterial genomes

Background  

Across all sequenced bacterial genomes, the number of domains n _c in different functional categories c scales as a power-law in the total number of domains n, i.e. , with exponents α _c that vary across functional categories. Here we investigate the implications of these scaling laws for the evolution of domain-content in bacterial genomes and derive the simplest evolutionary model consistent with these scaling laws.     

Evolutionary analysis of three gibberellin oxidase genes in rice, Arabidopsis, and soybean

GAs are plant hormones that play fundamental roles in plant growth and development. GA2ox, GA3ox, and GA20ox are three key enzymes in GA biosynthesis. These enzymes belong to the 2OG-Fe (II) oxygenase superfamily and are independently encoded by different gene families. To date, genome-wide comparative analyses of GA oxidases in plant species have not been thoroughly carried out. In the present work, 61 GA oxidase family genes from rice (Oryza sativa), Arabidopsis, and soybean (Glycine max) were identified and a full study of these genes including phylogenetic tree construction, gene structure, gene family expansion and analysis of functional motifs was performed. Based on phylogeny, most of the GA oxidases were divided into four subgroups that reflected functional classifications. Intron/intron average length of GA oxidase genes in rice analysis revealed that GA oxidase genes in rice experienced substantial evolutionary divergence. Segmental duplication events were mainly found in soybean genome. However, in rice and Arabidopsis, no single expansion pattern exhibited dominance, indicating that GA oxidase genes from these species might have been subjected to a more complex evolutionary mechanism. In addition, special functional motifs were discovered in GA20ox, GA3ox, and GA2ox, which suggested that different functional motifs are associated with differences in protein function. Taken together our results suggest that GA oxidase family genes have undergone divergent evolutionary routes, especially at the monocot-dicot split, with dynamic evolution occurring in Arabidopsis thaliana and soybean.     

Scaling laws in bacterial genomes: A side-effect of selection of mutational robustness?

In the past few years, numerous research projects have focused on identifying and understanding scaling properties in the gene content of prokaryote genomes and the intricacy of their regulation networks. Yet, and despite the increasing amount of data available, the origins of these scalings remain an open question. The RAevol model, a digital genetics model, provides us with an insight into the mechanisms involved in an evolutionary process. The results we present here show that (i) our model reproduces qualitatively these scaling laws and that (ii) these laws are not due to differences in lifestyles but to differences in the spontaneous rates of mutations and rearrangements. We argue that this is due to an indirect selective pressure for robustness that constrains the genome size.     

The Footprint of Genome Architecture in the Largest Genome Expansion in RNA Viruses

The small size of RNA virus genomes (2-to-32 kb) has been attributed to high mutation rates during replication, which is thought to lack proof-reading. This paradigm is being revisited owing to the discovery of a 3′-to-5′ exoribonuclease (ExoN) in nidoviruses, a monophyletic group of positive-stranded RNA viruses with a conserved genome architecture. ExoN, a homolog of canonical DNA proof-reading enzymes, is exclusively encoded by nidoviruses with genomes larger than 20 kb. All other known non-segmented RNA viruses have smaller genomes. Here we use evolutionary analyses to show that the two- to three-fold expansion of the nidovirus genome was accompanied by a large number of replacements in conserved proteins at a scale comparable to that in the Tree of Life. To unravel common evolutionary patterns in such genetically diverse viruses, we established the relation between genomic regions in nidoviruses in a sequence alignment-free manner. We exploited the conservation of the genome architecture to partition each genome into five non-overlapping regions: 5′ untranslated region (UTR), open reading frame (ORF) 1a, ORF1b, 3′ORFs (encompassing the 3′-proximal ORFs), and 3′ UTR. Each region was analyzed for its contribution to genome size change under different models. The non-linear model statistically outperformed the linear one and captured >92% of data variation. Accordingly, nidovirus genomes were concluded to have reached different points on an expansion trajectory dominated by consecutive increases of ORF1b, ORF1a, and 3′ORFs. Our findings indicate a unidirectional hierarchical relation between these genome regions, which are distinguished by their expression mechanism. In contrast, these regions cooperate bi-directionally on a functional level in the virus life cycle, in which they predominantly control genome replication, genome expression, and virus dissemination, respectively. Collectively, our findings suggest that genome architecture and the associated region-specific division of labor leave a footprint on genome expansion and may limit RNA genome size.     

The evolutionary relationships between the two bacteria Escherichia coli and Haemophilus influenzae and their putative last common ancestor

We have tried to approach the nature of the last common ancestor to Haemophilus influenzae and Escherichia coli and to determine how each bacterium could have diverged from this putative organism. The approach used was exhaustive analysis of the homologous proteins coded by genes present in these bacteria, using as criteria for sequence relatedness an alignment of at least 80 amino acid residues and a PAM distance (number of accepted point mutations per 100 residues separating two sequences) below 250. Evolutionarily significant similarities were found between 1,345 H. influenzae proteins (85% of the total genome) and 3,058 E. coli. proteins (75% of the total genome), many of them belonging to families of various sizes (from 666 doublets to 35 large groups of more than 10 members). Nearly all the genes found by this approach to be duplicated in both bacteria were already duplicated in their last common ancestor. This was deduced from (1) the comparison of the respective distributions of evolutionary distances between orthologs (genes separated only by speciation events) and paralogs (genes duplicated in the same genome) and (2) the analysis of the phylogenetic trees reconstructed for each family of paralogs containing at least two members belonging to each bacterium. The distributions of the different categories of homologs show a significant loss of paralogous genes in H. influenzae (reduction proportional to the genome size), of many sequences which are still present in one copy in E. coli, and of some entire gene families. Phylogenetic trees also confirmed this recent loss of paralogous genes in H. influenzae. Thus, the genome size of the last common ancestor of these two bacteria would have been close to that of present-day E. coli, and the evolution of H. influenzae toward a parasitic life led to an important decrease in its genome size by some mechanism of streamlining. During this recent evolution, the memory of the gene order present in the last common ancestor has been blurred, but a few short conserved chromosomal fragments can still be detected in present-day E. coli and H. influenzae.      

The "domino theory" of gene death: gradual and mass gene extinction events in three lineages of obligate symbiotic bacterial pathogens

During the adaptation of an organism to a parasitic lifestyle, various gene functions may be rendered superfluous due to the fact that the host may supply these needs. As a consequence, obligate symbiotic bacterial pathogens tend to undergo reductive genomic evolution through gene death (nonfunctionalization or pseudogenization) and deletion. Here, we examine the evolutionary sequence of gene-death events during the process of genome miniaturization in three bacterial species that have experienced extensive genome reduction: Mycobacterium leprae, Shigella flexneri, and Salmonella typhi. We infer that in all three lineages, the distribution of functional categories is similar in pseudogenes and genes but different from that of absent genes. Based on an analysis of evolutionary distances, we propose a two-step "domino effect" model for reductive genome evolution. The process starts with a gradual gene-by-gene-death sequence of events. Eventually, a crucial gene within a complex pathway or network is rendered nonfunctional triggering a "mass gene extinction" of the dependent genes. In contrast to published reports according to which genes belonging to certain functional categories are prone to nonfunctionalization more frequently and earlier than genes belonging to other functional categories, we could discern no characteristic regularity in the temporal order of function loss.