Fluidity of eukaryotic genomes

The understanding the different kinds of sequences that make up a genome, as well as their proportions in genomes (obtained by the sequencing of the complete genome), has considerably changed our idea of evolution at the genomic level. The former view of a slowly evolving genome has given way to the idea of a genome that can undergo many transformations, on a large or small scale, depending on the evolution of the different types of sequences constituting it. Here we summarise the evolution of these sequences and the impact it can have on the genome. We have focused on micro-transformations, and especially on the impact of transposable elements on genomes. To cite this article: E. Bonnivard, D. Higuet, C. R. Biologies 332 (2009).     

Predicting protein function with hierarchical phylogenetic profiles: the Gene3D Phylo-Tuner method applied to eukaryotic genomes

“Phylogenetic profiling” is based on the hypothesis that during evolution functionally or physically interacting genes are likely to be inherited or eliminated in a codependent manner. Creating presence–absence profiles of orthologous genes is now a common and powerful way of identifying functionally associated genes. In this approach, correctly determining orthology, as a means of identifying functional equivalence between two genes, is a critical and nontrivial step and largely explains why previous work in this area has mainly focused on using presence–absence profiles in prokaryotic species. Here, we demonstrate that eukaryotic genomes have a high proportion of multigene families whose phylogenetic profile distributions are poor in presence–absence information content. This feature makes them prone to orthology mis-assignment and unsuited to standard profile-based prediction methods. Using CATH structural domain assignments from the Gene3D database for 13 complete eukaryotic genomes, we have developed a novel modification of the phylogenetic profiling method that uses genome copy number of each domain superfamily to predict functional relationships. In our approach, superfamilies are subclustered at ten levels of sequence identity—from 30% to 100%—and phylogenetic profiles built at each level. All the profiles are compared using normalised Euclidean distances to identify those with correlated changes in their domain copy number. We demonstrate that two protein families will “auto-tune” with strong co-evolutionary signals when their profiles are compared at the similarity levels that capture their functional relationship. Our method finds functional relationships that are not detectable by the conventional presence–absence profile comparisons, and it does not require a priori any fixed criteria to define orthologous genes.     

The dynamic nature of eukaryotic genomes

Analyses of diverse eukaryotes reveal that genomes are dynamic, sometimes dramatically so. In numerous lineages across the eukaryotic tree of life, DNA content varies within individuals throughout life cycles and among individuals within species. Discovery of examples of genome dynamism is accelerating as genome sequences are completed from diverse eukaryotes. Though much is known about genomes in animals, fungi, and plants, these lineages represent only 3 of the 60-200 lineages of eukaryotes. Here, we discuss diverse genomic strategies in exemplar eukaryotic lineages, including numerous microbial eukaryotes, to reveal dramatic variation that challenges established views of genome evolution. For example, in the life cycle of some members of the "radiolaria," ploidy increases from haploid (N) to approximately 1,000N, whereas intrapopulation variability of the enteric parasite Entamoeba ranges from 4N to 40N. Variation has also been found within our own species, with substantial differences in both gene content and chromosome lengths between individuals. Data on the dynamic nature of genomes shift the perception of the genome from being fixed and characteristic of a species (typological) to plastic due to variation within and between species.     

Integrated functional visualization of eukaryotic genomes

Background  

Increasing amounts of data from large scale whole genome analysis efforts demands convenient tools for manipulation, visualization and investigation. Whole genome plots offer an intuitive window to the analysis. We describe two applications that enable users to easily plot and explore whole genome data from their own or other researchers' experiments.     

Isochore chromosome maps of eukaryotic genomes

Analytical DNA ultracentrifugation revealed that eukaryotic genomes are mosaics of isochores: long DNA segments (>300 kb on average) relatively homogeneous in G+C. Important genome features are dependent on this isochore structure, e.g. genes are found predominantly in the GC-richest isochore classes. However, no reliable method is available to rigorously partition the genome sequence into relatively homogeneous regions of different composition, thereby revealing the isochore structure of chromosomes at the sequence level. Homogeneous regions are currently ascertained by plain statistics on moving windows of arbitrary length, or simply by eye on G+C plots. On the contrary, the entropic segmentation method is able to divide a DNA sequence into relatively homogeneous, statistically significant domains. An early version of this algorithm only produced domains having an average length far below the typical isochore size. Here we show that an improved segmentation method, specifically intended to determine the most statistically significant partition of the sequence at each scale, is able to identify the boundaries between long homogeneous genome regions displaying the typical features of isochores. The algorithm precisely locates classes II and III of the human major histocompatibility complex region, two well-characterized isochores at the sequence level, the boundary between them being the first isochore boundary experimentally characterized at the sequence level. The analysis is then extended to a collection of human large contigs. The relatively homogeneous regions we find show many of the features (G+C range, relative proportion of isochore classes, size distribution, and relationship with gene density) of the isochores identified through DNA centrifugation. Isochore chromosome maps, with many potential applications in genomics, are then drawn for all the completely sequenced eukaryotic genomes available.     

Comprehensive analysis of the origin of eukaryotic genomes

There is currently no consensus on the evolutionary origin of eukaryotes. In the search of the ancestors of eukaryotes, we analyzed the phylogeny of 46 genomes, including those of 2 eukaryotes, 8 archaea, and 36 eubacteria. To avoid the effects of gene duplications, we used inparalog pairs of genes with orthologous relationships. First, we grouped these inparalogs into the functional categories of the nucleus, cytoplasm, and mitochondria. Next, we counted the sister groups of eukaryotes in prokaryotic phyla and plotted them on a standard phylogenetic tree. Finally, we used Pearson's chi-square test to estimate the origin of the genomes from specific prokaryotic ancestors. The results suggest the eukaryotic nuclear genome descends from an archaea that was neither euryarchaeota nor crenarchaeota and that the mitochondrial genome descends from alpha-proteobacteria. In contrast, genes related to the cytoplasm do not appear to originate from a specific group of prokaryotes.     

The frequency of two-base tracts in eukaryotic genomes

The frequency of two-base tracts is surveyed in a wide range of eukaryotic genomes using the special program TRACTS. All three two-base families are surveyed: R.Y (A,G.C,T), K.M (A,C.G,T), and S;W (A.T and G.C). Data for the human β-globin complex, for the tobacco chloroplast, and for 247 nt mammalian promoter regions are presented. All two-base tracts longer than three or four bases are overrepresented to an extent surpassing by far their occurrence in a randomized DNA population in the majority of the genomic regions analyzed; 20–30 long tracts are quite frequent, against the statistical odds. R.Y tracts are found at the largest excess, K.M tract to a slightly lesser extent, while S.W tracts are found at a moderate yet significant excess. The majority of the tracts manifest only a limited extent of tandem repeat structures. The idea that the two base tracts serve as unwinding elements is considered. Preseented at the NATO Advanced Research Workshop onGenome Organization and Evolution, Spetsai, Greece, 16–22 September 1992     

Supertrees disentangle the chimerical origin of eukaryotic genomes

Eukaryotes are traditionally considered to be one of the three natural divisions of the tree of life and the sister group of the Archaebacteria. However, eukaryotic genomes are replete with genes of eubacterial ancestry, and more than 20 mutually incompatible hypotheses have been proposed to account for eukaryote origins. Here we test the predictions of these hypotheses using a novel supertree-based phylogenetic signal-stripping method, and recover supertrees of life based on phylogenies for up to 5,741 single gene families distributed across 185 genomes. Using our signal-stripping method, we show that there are three distinct phylogenetic signals in eukaryotic genomes. In order of strength, these link eukaryotes with the Cyanobacteria, the Proteobacteria, and the Thermoplasmatales, an archaebacterial (euryarchaeotes) group. These signals correspond to distinct symbiotic partners involved in eukaryote evolution: plastids, mitochondria, and the elusive host lineage. According to our whole-genome data, eukaryotes are hardly the sister group of the Archaebacteria, because up to 83% of eukaryotic genes with a prokaryotic homolog have eubacterial, not archaebacterial, origins. The results reject all but two of the current hypotheses for the origin of eukaryotes: those assuming a sulfur-dependent or hydrogen-dependent syntrophy for the origin of mitochondria.     

Evolutionary diversification of DNA methyltransferases in eukaryotic genomes

In eukaryotes, C5-cytosine methylation is a common mechanism associated with a variety of functions such as gene regulation or control of genomic stability. Different subfamilies of eukaryotic methyltransferases (MTases) have been identified, mainly in metazoa, plants, and fungi. In this paper, we used hidden Markov models to detect MTases in completed or almost completed eukaryotic genomes, including different species of Protozoa. A phylogenetic analysis of MTases enabled us to define six subfamilies of MTases, including two new subfamilies. The dnmt1 subfamily that includes all the known MTases with a maintenance activity seems to be absent in the Protozoa. The dnmt2 subfamily seems to be the most widespread, being present even in the nonmethylated Dictyostelium discoideum. We also found two dnmt2 members in the bacterial genus Geobacter, suggesting that horizontal transfers of MTases occurred between eukaryotes and prokaryotes. Even if the direction of transfer cannot be determined, this relationship might be useful for understanding the function of this enigmatic subfamily of MTases. Globally, our analysis reveals a great diversity of MTases in eukaryotes, suggesting the existence of different methylation systems. Our results also suggest acquisitions and losses of different MTases in every eukaryotic lineage studied and that some eukaryotes appear to be devoid of methylation.     

Efficient capture of unique sequences from eukaryotic genomes

Cot-based cloning and sequencing (CBCS), a synthesis of Cot analysis, DNA cloning and high-throughput sequencing, promises to accelerate the study of eukaryotic genomes. In particular, CBCS will (1) permit efficient gene discovery in species with substantial quantities of repetitive DNA, (2) allow the sequence complexity (i.e. all the unique sequence information) of large genomes to be elucidated at a fraction of the cost of shotgun sequencing, and (3) enhance genome sequencing efforts by facilitating capture of low-copy sequences not secured by EST sequencing. CBCS should accelerate comparative genomics research, especially in large genomes such as those of many crops.     

CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes

MOTIVATION: The numbers of finished and ongoing genome projects are increasing at a rapid rate, and providing the catalog of genes for these new genomes is a key challenge. Obtaining a set of well-characterized genes is a basic requirement in the initial steps of any genome annotation process. An accurate set of genes is needed in order to learn about species-specific properties, to train gene-finding programs, and to validate automatic predictions. Unfortunately, many new genome projects lack comprehensive experimental data to derive a reliable initial set of genes. RESULTS: In this study, we report a computational method, CEGMA (Core Eukaryotic Genes Mapping Approach), for building a highly reliable set of gene annotations in the absence of experimental data. We define a set of conserved protein families that occur in a wide range of eukaryotes, and present a mapping procedure that accurately identifies their exon-intron structures in a novel genomic sequence. CEGMA includes the use of profile-hidden Markov models to ensure the reliability of the gene structures. Our procedure allows one to build an initial set of reliable gene annotations in potentially any eukaryotic genome, even those in draft stages. AVAILABILITY: Software and data sets are available online at http://korflab.ucdavis.edu/Datasets.     

Simple sequences are ubiquitous repetitive components of eukaryotic genomes

Simple sequences are stretches of DNA which consist of only one, or a few tandemly repeated nucleotides, for example poly (dA) X poly (dT) or poly (dG-dT) X poly (dC-dA). These two types of simple sequence have been shown to be repetitive and interspersed in many eukaryotic genomes. Several other types have been found by sequencing eukaryotic DNA. In this report we have undertaken a systematical survey for simple sequences. We hybridized synthetical simple sequence DNA to genome blots of phylogenetically different organisms. We found that many, probably even all possible types of simple sequence are repetitive components of eukaryotic genomes. We propose therefore that they arise by common mechanisms namely slippage replication and unequal crossover and that they might have no general function with regards to gene expression. This latter inference is supported by the fact that we have detected simple sequences only in the metabolically inactive micronucleus of the protozoan Stylonychia, but not in the metabolically active macronucleus which is derived from the micronucleus by chromosome diminution.     

An approach of orthology detection from homologous sequences under minimum evolution

In the field of phylogenetics and comparative genomics, it is important to establish orthologous relationships when comparing homologous sequences. Due to the slight sequence dissimilarity between orthologs and paralogs, it is prone to regarding paralogs as orthologs. For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision. Depending on their algorithmic implementations, each of these methods sometimes has increased false negative or false positive rates. Here, we developed a novel algorithm for orthology detection that uses a distance method based on the phylogenetic criterion of minimum evolution. Our algorithm assumes that sets of sequences exhibiting orthologous relationships are evolutionarily less costly than sets that include one or more paralogous relationships. Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree. Unlike tree reconciliation, our algorithm appears free from the problem of incorrect topologies of species and gene trees. The reliability of the algorithm was tested in a comparative analysis with two other orthology detection methods using 95 manually curated KOG datasets and 21 experimentally verified EXProt datasets. Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.