Complete Eukaryotic Genomes Research Articles

Complete Genome Sequence of the Model Oleaginous Alga Nannochloropsis gaditana CCMP1894.

ABSTRACTThe model oleaginous alga Nannochloropsis gaditana was completely sequenced using a combination of optical mapping and next-generation sequencing technologies to generate one of the most complete eukaryotic genomes published to date. The assembled genome is 30.7 Mb long.

NumtS colonization in mammalian genomes

The colonization of the nuclear genome by mitochondrial DNA is an ongoing process in eukaryotes and plays an important role in genomic variability. Notwithstanding the DNA sequence availability of about 100 complete eukaryotic genomes, up to now NumtS distribution has been fully reported for a small number of sequenced eukaryotic species. With the aim to clarify the time and way of NumtS evolution, we explored the genomic distribution of NumtS in 23 eukaryotic species using an intra/interspecies in silico approach based on a cross-species similarity search and deeply investigate the evolution of NumtS in mammals. The intra- and interspecies analysis underlined how some mitochondrial regions that populated nuclear genomes can be considered as hotspots. Considering the large amount of NumtS we found in platypus and opossum genomes, we hypothesized the occurrence of an earlier colonization that happened prior to the Prototherian/Therian mammal divergence, approximately 160–210 million years ago. These events are still detectable due to the species-specific dynamics that have affected these genomes. Phylogenetic analyses of NumtS derived from two different mitochondrial DNA loci allowed us to recognize the unusual NumtS evolution that acted differently on primate and non-primate species’ genomes.

Intracellular metabolic pathway distribution in diatoms and tools for genome-enabled experimental diatom research

Diatoms are important primary producers in the oceans and can also dominate other aquatic habitats. One reason for the success of this phylogenetically relatively young group of unicellular organisms could be the impressive redundancy and diversity of metabolic isoenzymes in diatoms. This redundancy is a result of the evolutionary origin of diatom plastids by a eukaryote-eukaryote endosymbiosis, a process that implies temporary redundancy of functionally complete eukaryotic genomes. During the establishment of the plastids, this redundancy was partially reduced via gene losses, and was partially retained via gene transfer to the nucleus of the respective host cell. These gene transfers required re-assignment of intracellular targeting signals, a process that simultaneously altered the intracellular distribution of metabolic enzymes compared with the ancestral cells. Genome annotation, the correct assignment of the gene products and the prediction of putative function, strongly depends on the correct prediction of the intracellular targeting of a gene product. Here again diatoms are very peculiar, because the targeting systems for organelle import are partially different to those in land plants. In this review, we describe methods of predicting intracellular enzyme locations, highlight findings of metabolic peculiarities in diatoms and present genome-enabled approaches to study their metabolism.This article is part of the themed issue 'The peculiar carbon metabolism in diatoms'.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies.

Circular code motifs in genomes of eukaryotes

A set X of 20 trinucleotides was identified in genes of bacteria, eukaryotes, plasmids and viruses, which has in average the highest occurrence in reading frame compared to its two shifted frames (Michel, 2015; Arquès and Michel, 1996). This set X has an interesting mathematical property as X is a circular code (Arquès and Michel, 1996). Thus, the motifs from this circular code X, called X motifs, have the property to always retrieve, synchronize and maintain the reading frame in genes. In this paper, we develop several statistical analyzes of X motifs in 138 available complete genomes of eukaryotes in which genes as well as non-gene regions are examined. Large X motifs (with lengths of at least 15 consecutive trinucleotides of X and compositions of at least 10 different trinucleotides of X among 20) have the highest occurrence in genomes of eukaryotes compared to its 23 large bijective motifs, its two large permuted motifs and large random motifs. The largest X motifs identified in eukaryotic genomes are presented, e.g. an X motif in a non-gene region of the genome Solanum pennellii with a length of 155 trinucleotides (465 nucleotides) and an expectation E=10−71. In the human genome, the largest X motif occurs in a non-gene region of the chromosome 13 with a length of 36 trinucleotides and an expectation E=10−11. X motifs in non-gene regions of genomes could be evolutionary relics of primitive genes using the circular code for translation. However, the proportion of X motifs (with lengths of at least 10 consecutive trinucleotides of X and compositions of at least 5 different trinucleotides of X among 20) in genes/non-genes of the 138 complete eukaryotic genomes is about 8. Thus, the X motifs occur preferentially in genes, as expected from the previous works of 20 years.

Single-Molecule Real-Time Sequencing Combined with Optical Mapping Yields Completely Finished Fungal Genome.

ABSTRACTNext-generation sequencing (NGS) technologies have increased the scalability, speed, and resolution of genomic sequencing and, thus, have revolutionized genomic studies. However, eukaryotic genome sequencing initiatives typically yield considerably fragmented genome assemblies. Here, we assessed various state-of-the-art sequencing and assembly strategies in order to produce a contiguous and complete eukaryotic genome assembly, focusing on the filamentous fungus Verticillium dahliae. Compared with Illumina-based assemblies of the V. dahliae genome, hybrid assemblies that also include PacBio-generated long reads establish superior contiguity. Intriguingly, provided that sufficient sequence depth is reached, assemblies solely based on PacBio reads outperform hybrid assemblies and even result in fully assembled chromosomes. Furthermore, the addition of optical map data allowed us to produce a gapless and complete V. dahliae genome assembly of the expected eight chromosomes from telomere to telomere. Consequently, we can now study genomic regions that were previously not assembled or poorly assembled, including regions that are populated by repetitive sequences, such as transposons, allowing us to fully appreciate an organism’s biological complexity. Our data show that a combination of PacBio-generated long reads and optical mapping can be used to generate complete and gapless assemblies of fungal genomes.

Uncovering RNA Editing Sites in Long Non-Coding RNAs

RNA editing is an important co/post-transcriptional molecular process able to modify RNAs by nucleotide insertions/deletions or substitutions. In human, the most common RNA editing event involves the deamination of adenosine (A) into inosine (I) through the adenosine deaminase acting on RNA proteins. Although A-to-I editing can occur in both coding and non-coding RNAs, recent findings, based on RNA-seq experiments, have clearly demonstrated that a large fraction of RNA editing events alter non-coding RNAs sequences including untranslated regions of mRNAs, introns, long non-coding RNAs (lncRNAs), and low molecular weight RNAs (tRNA, miRNAs, and others). An accurate detection of A-to-I events occurring in non-coding RNAs is of utmost importance to clarify yet unknown functional roles of RNA editing in the context of gene expression regulation and maintenance of cell homeostasis. In the last few years, massive transcriptome sequencing has been employed to identify putative RNA editing changes at genome scale. Despite several efforts, the computational prediction of A-to-I sites in complete eukaryotic genomes is yet a challenging task. We have recently developed a software package, called REDItools, in order to simplify the detection of RNA editing events from deep sequencing data. In the present work, we show the potential of our tools in recovering A-to-I candidates from RNA-Seq experiments as well as guidelines to improve the RNA editing detection in non-coding RNAs, with specific attention to the lncRNAs.

Evolution of Bacterial-Like Phosphoprotein Phosphatases in Photosynthetic Eukaryotes Features Ancestral Mitochondrial or Archaeal Origin and Possible Lateral Gene Transfer

Protein phosphorylation is a reversible regulatory process catalyzed by the opposing reactions of protein kinases and phosphatases, which are central to the proper functioning of the cell. Dysfunction of members in either the protein kinase or phosphatase family can have wide-ranging deleterious effects in both metazoans and plants alike. Previously, three bacterial-like phosphoprotein phosphatase classes were uncovered in eukaryotes and named according to the bacterial sequences with which they have the greatest similarity: Shewanella-like (SLP), Rhizobiales-like (RLPH), and ApaH-like (ALPH) phosphatases. Utilizing the wealth of data resulting from recently sequenced complete eukaryotic genomes, we conducted database searching by hidden Markov models, multiple sequence alignment, and phylogenetic tree inference with Bayesian and maximum likelihood methods to elucidate the pattern of evolution of eukaryotic bacterial-like phosphoprotein phosphatase sequences, which are predominantly distributed in photosynthetic eukaryotes. We uncovered a pattern of ancestral mitochondrial (SLP and RLPH) or archaeal (ALPH) gene entry into eukaryotes, supplemented by possible instances of lateral gene transfer between bacteria and eukaryotes. In addition to the previously known green algal and plant SLP1 and SLP2 protein forms, a more ancestral third form (SLP3) was found in green algae. Data from in silico subcellular localization predictions revealed class-specific differences in plants likely to result in distinct functions, and for SLP sequences, distinctive and possibly functionally significant differences between plants and nonphotosynthetic eukaryotes. Conserved carboxyl-terminal sequence motifs with class-specific patterns of residue substitutions, most prominent in photosynthetic organisms, raise the possibility of complex interactions with regulatory proteins.

This Déjà Vu Feeling—Analysis of Multidomain Protein Evolution in Eukaryotic Genomes

Evolutionary innovation in eukaryotes and especially animals is at least partially driven by genome rearrangements and the resulting emergence of proteins with new domain combinations, and thus potentially novel functionality. Given the random nature of such rearrangements, one could expect that proteins with particularly useful multidomain combinations may have been rediscovered multiple times by parallel evolution. However, existing reports suggest a minimal role of this phenomenon in the overall evolution of eukaryotic proteomes. We assembled a collection of 172 complete eukaryotic genomes that is not only the largest, but also the most phylogenetically complete set of genomes analyzed so far. By employing a maximum parsimony approach to compare repertoires of Pfam domains and their combinations, we show that independent evolution of domain combinations is significantly more prevalent than previously thought. Our results indicate that about 25% of all currently observed domain combinations have evolved multiple times. Interestingly, this percentage is even higher for sets of domain combinations in individual species, with, for instance, 70% of the domain combinations found in the human genome having evolved independently at least once in other species. We also show that previous, much lower estimates of this rate are most likely due to the small number and biased phylogenetic distribution of the genomes analyzed. The process of independent emergence of identical domain combination is widespread, not limited to domains with specific functional categories. Besides data from large-scale analyses, we also present individual examples of independent domain combination evolution. The surprisingly large contribution of parallel evolution to the development of the domain combination repertoire in extant genomes has profound consequences for our understanding of the evolution of pathways and cellular processes in eukaryotes and for comparative functional genomics.

ANALYSIS OF EXPRESSED SEQUENCE TAGS FROM THE GREEN ALGA DUNALIELLA SALINA (CHLOROPHYTA)1

The unicellular green alga Dunaliella salina (Dunal) Teodor. is a novel model photosynthetic eukaryote for studying photosystems, high salinity acclimation, and carotenoid accumulation. In spite of such significance, there have been limited studies on the Dunaliella genome transcriptome and proteome. To further investigate D. salina, a cDNA library was constructed and sequenced. Here, we present the analysis of the 2,282 expressed sequence tags (ESTs) generated together with 3,990 ESTs from dbEST. A total of 4,148 unique sequences (UniSeqs) were identified, of which 56.1% had sequence similarity with Uniprot entries, suggesting that a large number of unique genes may be harbored by Dunaliella. Additionally, protein family domains were identified to further characterize these sequences. Then, we also compared EST sequences with different complete eukaryotic genomes from several animals, plants, and fungi. We observed notable differences between D. salina and other organisms. This EST collection and its annotation provided a significant resource for basic and applied research on D. salina and laid the foundation for a systematic analysis of the transcriptome basis of green algae development and diversification.

What can next generation sequencing do for you? Next generation sequencing as a valuable tool in plant research

Next generation sequencing (NGS) technologies have opened fascinating opportunities for the analysis of plants with and without a sequenced genome on a genomic scale. During the last few years, NGS methods have become widely available and cost effective. They can be applied to a wide variety of biological questions, from the sequencing of complete eukaryotic genomes and transcriptomes, to the genome-scale analysis of DNA-protein interactions. In this review, we focus on the use of NGS for plant transcriptomics, including gene discovery, transcript quantification and marker discovery for non-model plants, as well as transcript annotation and quantification, small RNA discovery and antisense transcription analysis for model plants. We discuss the experimental design for analysis of plants with and without a sequenced genome, including considerations on sampling, RNA preparation, sequencing platforms and bioinformatics tools for data analysis. NGS technologies offer exciting new opportunities for the plant sciences, especially for work on plants without a sequenced genome, since large sequence resources can be generated at moderate cost.

EXCLUSIVE SEQUENCES OF DIFFERENT GENOMES

We studied the distribution of 1-7 bp words in a dataset that includes 139 complete eukaryotic genomes, 33 masked eukaryotic genomes and coding regions from 35 genomes. We tested different statistical models to determine over- and under-represented words. The method described by Karlin et al. has the strongest predictive power compared to other methods. Using this method we identified over- and under-represented words consistent within a large array of taxonomic groups. Some of those words have not yet been described as exclusive. For example, CGCG is over-represented in CG-deficient organisms. We also describe exceptions for widely known exclusive words, such as CG and TA.

Location, location, (ChIP‐)location! Mapping chromatin landscapes one immunoprecipitation at a time

A small fraction of the typical animal genome (<5% in humans) codes for the organism's collection of proteins, yet the study of protein coding sequences dominated the early years of genomics research. In the decade since the sequencing of complete eukaryotic genomes, however, genomic techniques have shed a great deal of light on the non-coding DNA making up the remainder. A single molecular technique, Chromatin Immuno-Precipitation (ChIP) location analysis, has had a profound impact and has made possible the study of an incredible range of biology. This issue of The Journal of Cellular Biochemistry aims to put into context advancements made possible by the ChIP-location revolution, while at the same time highlighting some of the most important technical aspects and challenges along with some of the work yet to come.

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.

Dark matter in a deep‐sea vent and in human mouth

Summer used to be a slow time for genomics news. This year, even the summer heat failed to stem the influx of new completely sequenced microbial genomes. The latest list (Table 1) includes genomes from a number of environmental bacteria (Chen et al., 2007; Nakagawa et al., 2007), four methanogenic archaea, as well as the finished genome of the red alga Cyanidioschyzon merolae, the first 100% complete eukaryotic genome (Nozaki et al., 2007). However, this time the most striking news comes from an unfinished genome, the genome sequence of the first representative of the enigmatic TM7 phylum (Hugenholtz et al., 2001). So far, no member of this widespread phylum has been isolated in pure culture and the genome sequence, even an incomplete one, provides the first glimpse into the physiology of this biological ‘dark matter’ (Marcy et al., 2007).

Assembly rules for protein networks derived from phylogenetic-statistical analysis of whole genomes

BackgroundWe report an analysis of a protein network of functionally linked proteins, identified from a phylogenetic statistical analysis of complete eukaryotic genomes. Phylogenetic methods identify pairs of proteins that co-evolve on a phylogenetic tree, and have been shown to have a high probability of correctly identifying known functional links.ResultsThe eukaryotic correlated evolution network we derive displays the familiar power law scaling of connectivity. We introduce the use of explicit phylogenetic methods to reconstruct the ancestral presence or absence of proteins at the interior nodes of a phylogeny of eukaryote species. We find that the connectivity distribution of proteins at the point they arise on the tree and join the network follows a power law, as does the connectivity distribution of proteins at the time they are lost from the network. Proteins resident in the network acquire connections over time, but we find no evidence that 'preferential attachment' – the phenomenon of newly acquired connections in the network being more likely to be made to proteins with large numbers of connections – influences the network structure. We derive a 'variable rate of attachment' model in which proteins vary in their propensity to form network interactions independently of how many connections they have or of the total number of connections in the network, and show how this model can produce apparent power-law scaling without preferential attachment.ConclusionA few simple rules can explain the topological structure and evolutionary changes to protein-interaction networks: most change is concentrated in satellite proteins of low connectivity and small phenotypic effect, and proteins differ in their propensity to form attachments. Given these rules of assembly, power law scaled networks naturally emerge from simple principles of selection, yielding protein interaction networks that retain a high-degree of robustness on short time scales and evolvability on longer evolutionary time scales.

Codon Signature Extremes In Eukaryote genomes

Twenty-one complete eukaryotic genomes are compared for codon signature biases. The codon signature refers to the dinucleotide relative abundance values at codon sites {1, 2}, {2, 3}, and {3, 4} (4 = 1 of the next codon site). The genomes under study include human, mouse, chicken, three invertebrates, one plant species, eight fungi, and six protists. The dinucleotide CpG is significantly underrepresented at all contiguous codon sites and drastically suppressed in noncoding regions in mammalian species, in yeast-like genomes, in the dicotArabidopsis thaliana, but not in the filamentous fungiNeurospora crassaandAsperigillus fumigatus, and in the protistEntamoeba histolytica.The dinucleotide TpA, probably due to DNA structural weaknesses, is underrepresented genome-wide and significantly underrepresented in the codon signature for all contiguous codon sites in mammals, inverterbrates, plants, and fungi, but somewhat restricted to codon sites {1, 2} among protists helping in avoidance of stop codons. The amino acid Ser, not of abundance in bacterial genomes, generally ranks among the two most used amino acids among eukaryotes ostensibly resulting from greater activity in the nucleus. The observed differences are linked to specifics of methylation, context-dependent mutation, DNA repair, and replication. For example, the amino acid Leu is broadly abundant in all life domains generally resulting from extra occurrences of the codon TTR, R purine. The malarial protistPlasmodium falciparumshows many codon signature extremes.

OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups.

The OrthoMCL database () houses ortholog group predictions for 55 species, including 16 bacterial and 4 archaeal genomes representing phylogenetically diverse lineages, and most currently available complete eukaryotic genomes: 24 unikonts (12 animals, 9 fungi, microsporidium, Dictyostelium, Entamoeba), 4 plants/algae and 7 apicomplexan parasites. OrthoMCL software was used to cluster proteins based on sequence similarity, using an all-against-all BLAST search of each species' proteome, followed by normalization of inter-species differences, and Markov clustering. A total of 511 797 proteins (81.6% of the total dataset) were clustered into 70 388 ortholog groups. The ortholog database may be queried based on protein or group accession numbers, keyword descriptions or BLAST similarity. Ortholog groups exhibiting specific phyletic patterns may also be identified, using either a graphical interface or a text-based Phyletic Pattern Expression grammar. Information for ortholog groups includes the phyletic profile, the list of member proteins and a multiple sequence alignment, a statistical summary and graphical view of similarities, and a graphical representation of domain architecture. OrthoMCL software, the entire FASTA dataset employed and clustering results are available for download. OrthoMCL-DB provides a centralized warehouse for orthology prediction among multiple species, and will be updated and expanded as additional genome sequence data become available.

Expansion of GAA trinucleotide repeats in mammals

We have previously shown that GAA trinucleotide repeats have undergone significant expansion in the human genome. Here we present the analysis of the length distribution of all 10 nonredundant trinucleotide repeat motifs in 20 complete eukaryotic genomes (6 mammalian, 2 nonmammalian vertebrates, 4 arthropods, 4 fungi, and 1 each of nematode, amoebozoa, alveolate, and plant), which showed that the abundance of large expansions of GAA trinucleotide repeats is specific to mammals. Analysis of human–chimpanzee–gorilla orthologs revealed that loci with large expansions are species-specific and have occurred after divergence from the common ancestor. PCR analysis of human controls revealed large expansions at multiple human (GAA) 30+ loci; nine loci showed expanded alleles containing >65 triplets, analogous to disease-causing expansions in Friedreich ataxia, including two that are in introns of genes of unknown function. The abundance of long GAA trinucleotide repeat tracts in mammalian genomes represents a significant mutation potential and source of interindividual variability.

Modeling gene and genome duplications in eukaryotes.

Recent analysis of complete eukaryotic genome sequences has revealed that gene duplication has been rampant. Moreover, next to a continuous mode of gene duplication, in many eukaryotic organisms the complete genome has been duplicated in their evolutionary past. Such large-scale gene duplication events have been associated with important evolutionary transitions or major leaps in development and adaptive radiations of species. Here, we present an evolutionary model that simulates the duplication dynamics of genes, considering genome-wide duplication events and a continuous mode of gene duplication. Modeling the evolution of the different functional categories of genes assesses the importance of different duplication events for gene families involved in specific functions or processes. By applying our model to the Arabidopsis genome, for which there is compelling evidence for three whole-genome duplications, we show that gene loss is strikingly different for large-scale and small-scale duplication events and highly biased toward certain functional classes. We provide evidence that some categories of genes were almost exclusively expanded through large-scale gene duplication events. In particular, we show that the three whole-genome duplications in Arabidopsis have been directly responsible for >90% of the increase in transcription factors, signal transducers, and developmental genes in the last 350 million years. Our evolutionary model is widely applicable and can be used to evaluate different assumptions regarding small- or large-scale gene duplication events in eukaryotic genomes.