The relative ages of eukaryotes and akaryotes.

The Last Eukaryote Common Ancestor (LECA) appears to have the genetics required for meiosis, mitosis, nucleus and nuclear substructures, an exon/intron gene structure, spliceosomes, many centres of DNA replication, etc. (and including mitochondria). Most of these features are not generally explained by models for the origin of the Eukaryotic cell based on the fusion of an Archeon and a Bacterium. We find that the term 'prokaryote' is ambiguous and the non-phylogenetic term akaryote should be used in its place because we do not yet know the direction of evolution between eukaryotes and akaryotes. We use the term 'protoeukaryote' for the hypothetical stem group ancestral eukaryote that took up a bacterium as an endosymbiont that formed the mitochondrion. It is easier to make detailed models with a eukaryote to an akaryote transition, rather than vice versa. So we really are at a phylogenetic impasse in not being confident about the direction of change between eukaryotes and akaryotes.

Two new fern chloroplasts and decelerated evolution linked to the long generation time in tree ferns.

We report the chloroplast genomes of a tree fern (Dicksonia squarrosa) and a "fern ally" (Tmesipteris elongata), and show that the phylogeny of early land plants is basically as expected, and the estimates of divergence time are largely unaffected after removing the fastest evolving sites. The tree fern shows the major reduction in the rate of evolution, and there has been a major slowdown in the rate of mutation in both families of tree ferns. We suggest that this is related to a generation time effect; if there is a long time period between generations, then this is probably incompatible with a high mutation rate because otherwise nearly every propagule would probably have several lethal mutations. This effect will be especially strong in organisms that have large numbers of cell divisions between generations. This shows the necessity of going beyond phylogeny and integrating its study with other properties of organisms.

Mutational dynamics of aroid chloroplast genomes.

A characteristic feature of eukaryote and prokaryote genomes is the co-occurrence of nucleotide substitution and insertion/deletion (indel) mutations. Although similar observations have also been made for chloroplast DNA, genome-wide associations have not been reported. We determined the chloroplast genome sequences for two morphotypes of taro (Colocasia esculenta; family Araceae) and compared these with four publicly available aroid chloroplast genomes. Here, we report the extent of genome-wide association between direct and inverted repeats, indels, and substitutions in these aroid chloroplast genomes. We suggest that alternative but not mutually exclusive hypotheses explain the mutational dynamics of chloroplast genome evolution.

Reconstruction of Sugar Metabolic Pathways of Giardia lamblia.

Giardia lamblia is an "important" pathogen of humans, but as a diplomonad excavate it is evolutionarily distant from other eukaryotes and relatively little is known about its core metabolic pathways. KEGG, the widely referenced site for providing information of metabolism, does not yet include many enzymes from Giardia species. Here we identify Giardia's core sugar metabolism using standard bioinformatic approaches. By comparing Giardia proteomes with known enzymes from other species, we have identified enzymes in the glycolysis pathway, as well as some enzymes involved in the TCA cycle and oxidative phosphorylation. However, the majority of enzymes from the latter two pathways were not identifiable, indicating the likely absence of these functionalities. We have also found enzymes from the Giardia glycolysis pathway that appear more similar to those from bacteria. Because these enzymes are different from those found in mammals, the host organisms for Giardia, we raise the possibility that these bacteria-like enzymes could be novel drug targets for treating Giardia infections.

Characterization of RNase MRP RNA and novel snoRNAs from Giardia intestinalis and Trichomonas vaginalis.

BACKGROUND: Eukaryotic cells possess a complex network of RNA machineries which function in RNA-processing and cellular regulation which includes transcription, translation, silencing, editing and epigenetic control. Studies of model organisms have shown that many ncRNAs of the RNA-infrastructure are highly conserved, but little is known from non-model protists. In this study we have conducted a genome-scale survey of medium-length ncRNAs from the protozoan parasites Giardia intestinalis and Trichomonas vaginalis. RESULTS: We have identified the previously 'missing' Giardia RNase MRP RNA, which is a key ribozyme involved in pre-rRNA processing. We have also uncovered 18 new H/ACA box snoRNAs, expanding our knowledge of the H/ACA family of snoRNAs. CONCLUSIONS: Results indicate that Giardia intestinalis and Trichomonas vaginalis, like their distant multicellular relatives, contain a rich infrastructure of RNA-based processing. From here we can investigate the evolution of RNA processing networks in eukaryotes.

The RNA infrastructure: an introduction to ncRNA networks.

The RNA infrastructure connects RNA-based functions. With transcription-to-translation processing forming the core of the network, we can visualise how RNA-based regulation, cleavage and modification are the backbone of cellular function. The key to interpreting the RNA-infrastructure is in understanding how core RNAs (tRNA, mRNA and rRNA) and other ncRNAs operate in a spatial-temporal manner, moving around the nucleus, cytoplasm and organelles during processing, or in response to environmental cues. This chapter summarises the concept of the RNA-infrastructure, and highlights examples of RNA-based networking within prokaryotes and eukaryotes. It describes how transcription-to-translation processes are tightly connected, and explores some similarities and differences between prokaryotic and eukaryotic RNA networking.

Spliceosomal RNA infrastructure: the network of splicing components and their regulation by miRNAs.

The RNA infrastructure model highlights the major roles played by RNA- based networks in cellular biology. One of the principle concepts behind the RNA-infrastructure is that proteins shared between RNP machineries network their processes in a temporal (over the cell cycle) and spatial (across the cell, or intercellular) manner. In order to dig deeper into the RNA-infrastructure we need to examine the networking aspects of RNPs in a more detailed manner. The eukaryotic spliceosome is an excellent example of an RNA machine that contains RNA-Protein and RNA-RNA interactions, as well as temporal and spatial networking to other processes. This chapter will examine some different types of spliceosomal networks that involve RNPs and illustrate how current networking tools can be used to dissect the many faces of the RNA-infrastructure.

RNA networks in prokaryotes I: CRISPRs and riboswitches.

As with eukaryotes, prokaryotes employ a variety of mechanisms to allow the various types of RNA to interact and perform complex functions as a network. This chapter will detail prokaryotic molecular systems, such as riboswitches and CRISPRs, to show how they perform unique functions within the cell. These systems can interact with each other to gain a higher level of control and here we highlight some examples of such interactions including the cleavage of certain riboswitches by RNaseP, and endoribonuclease cleavage of pre-crRNAs in the CRISPR system. Thanks to such insights, we are beginning to get a glimpse of the prokaryotic RNA infrastructure, just as we have done with eukaryotes.

RNA networks in prokaryotes II: tRNA processing and small RNAs.

It is becoming clear that in prokaryotes RNAs interact and perform complex functions as a network similar to what we have uncovered in eukaryotes. This chapter will continue the discussion of prokaryotic molecular systems, showing how these systems can interact with each other to gain a higher level of control within the cell. Our examples include RNase P, the tRNA cleaving molecule that, as well as performing other functions, also cleaves certain ribo switches; and the glmS gene under the control of both a ribozyme in its 5' untranslated region and two small RNAs. With further investigation of nonprotein coding RNA interactions (i.e., the RNA infrastructure), in bacteria and archaea, we gain greater understanding of the influence that small strands of RNA sequence can have over the entire cell.

The modern RNP world of eukaryotes.

Eukaryote gene expression is mediated by a cascade of RNA functions that regulate, process, store, transport, and translate RNA transcripts. The RNA network that promotes this cascade depends on a large cohort of proteins that partner RNAs; thus, the modern RNA world of eukaryotes is really a ribonucleoprotein (RNP) world. Features of this "RNP infrastructure" can be related to the high cytosolic density of macromolecules and the large size of eukaryote cells. Because of the densely packed cytosol or nucleoplasm (with its severe restriction on diffusion of macromolecules), partitioning of the eukaryote cell into functionally specialized compartments is essential for efficiency. This necessitates the association of RNA and protein into large RNP complexes including ribosomes and spliceosomes. This is well illustrated by the ubiquitous spliceosome for which most components are conserved throughout eukaryotes and which interacts with other RNP-based machineries. The complexes involved in gene processing in modern eukaryotes have broad phylogenetic distributions suggesting that the common ancestor of extant eukaryotes had a fully evolved RNP network. Thus, the eukaryote genome may be uniquely informative about the transition from an earlier RNA genome world to the modern DNA genome world.

Ancestral RNA: the RNA biology of the eukaryotic ancestor.

Our knowledge of RNA biology within eukaryotes has exploded over the last five years. Within new research we see that some features that were once thought to be part of multicellular life have now been identified in several protist lineages. Hence, it is timely to ask which features of eukaryote RNA biology are ancestral to all eukaryotes. We focus on RNA-based regulation and epigenetic mechanisms that use small regulatory ncRNAs and long ncRNAs, to highlight some of the many questions surrounding eukaryotic ncRNA evolution.

The RNA infrastructure: dark matter of the eukaryotic cell?

Eukaryotes express many functional non-protein-coding RNAs (ncRNAs) that participate in the processing and regulation of other RNA molecules. By focusing on connections between RNA-based processes, common patterns emerge that form a network-like RNA infrastructure. Owing to the intracellular movement of RNA during its processing (both between nuclear compartments and between the nucleus and cytoplasm), the RNA infrastructure contains both spatial and temporal connections. As research moves away from being protein-centric and focuses more on genomics, it is timely to explore these often 'hidden' aspects of the eukaryotic cell. The general and ancestral nature of most basic RNA-processing steps places a new focus on the generality of the spatial and temporal steps in RNA processing.

High throughput genome-wide survey of small RNAs from the parasitic protists Giardia intestinalis and Trichomonas vaginalis.

RNA interference (RNAi) is a set of mechanisms which regulate gene expression in eukaryotes. Key elements of RNAi are small sense and antisense RNAs from 19 to 26 nt generated from double-stranded RNAs. MicroRNAs (miRNAs) are a major type of RNAi-associated small RNAs and are found in most eukaryotes studied to date. To investigate whether small RNAs associated with RNAi appear to be present in all eukaryotic lineages, and therefore present in the ancestral eukaryote, we studied two deep-branching protozoan parasites, Giardia intestinalis and Trichomonas vaginalis. Little is known about endogenous small RNAs involved in RNAi of these organisms. Using Illumina Solexa sequencing and genome-wide analysis of small RNAs from these distantly related deep-branching eukaryotes, we identified 10 strong miRNA candidates from Giardia and 11 from Trichomonas. We also found evidence of Giardia short-interfering RNAs potentially involved in the expression of variant-specific surface proteins. In addition, eight new small nucleolar RNAs from Trichomonas are identified. Our results indicate that miRNAs are likely to be general in ancestral eukaryotes and therefore are likely to be a universal feature of eukaryotes.

Computational identification of four spliceosomal snRNAs from the deep-branching eukaryote Giardia intestinalis.

RNAs processing other RNAs is very general in eukaryotes, but is not clear to what extent it is ancestral to eukaryotes. Here we focus on pre-mRNA splicing, one of the most important RNA-processing mechanisms in eukaryotes. In most eukaryotes splicing is predominantly catalysed by the major spliceosome complex, which consists of five uridine-rich small nuclear RNAs (U-snRNAs) and over 200 proteins in humans. Three major spliceosomal introns have been found experimentally in Giardia; one Giardia U-snRNA (U5) and a number of spliceosomal proteins have also been identified. However, because of the low sequence similarity between the Giardia ncRNAs and those of other eukaryotes, the other U-snRNAs of Giardia had not been found. Using two computational methods, candidates for Giardia U1, U2, U4 and U6 snRNAs were identified in this study and shown by RT-PCR to be expressed. We found that identifying a U2 candidate helped identify U6 and U4 based on interactions between them. Secondary structural modelling of the Giardia U-snRNA candidates revealed typical features of eukaryotic U-snRNAs. We demonstrate a successful approach to combine computational and experimental methods to identify expected ncRNAs in a highly divergent protist genome. Our findings reinforce the conclusion that spliceosomal small-nuclear RNAs existed in the last common ancestor of eukaryotes.

Are you my mother? Phylogenetic analysis reveals orphan hybrid stick insect genus is part of a monophyletic New Zealand clade.

The hybrid stick insect genus Acanthoxyla Uvarov 1944 is unusual for an obligate parthenogen, in the extreme morphological diversity it exhibits that has led to eight species being recognised. The New Zealand sexual species Clitarchus hookeri [White, A. 1846. The zoology of the Voyage of H.M.S. Erebus and Terror. In: 1 Insects of New Zealand. E.W. Janson, London.] is the putative parental species in the hybridization that gave rise to the hybrid lineage Acanthoxyla. In an effort to identify the maternal ancestor of Acanthoxyla we sequenced nuclear 28S rDNA and/or mtDNA COI & COII of all nine endemic New Zealand stick insect genera, representing 17 of the 22 described species. We also sequenced 28S from eight non-New Zealand stick insects to supplement published 28S sequence data that provided a taxonomically and geographically broad sampling of the phasmids. We applied a novel search algorithm (SeqSSi=Sequence Similarity Sieve) to assist in selection of outgroup taxa for phylogenetic analysis prior to alignment. Phylogenetic reconstructions resolved an exclusively New Zealand clade to which the maternal lineage of Acanthoxyla belonged, but did not support existing higher level taxonomy of stick insects. We did not find a sexual maternal species for Acanthoxyla but phylogenetic relationships indicate that this species lived in New Zealand and could be classified among the New Zealand Phasmatinae. Among the available taxa, the nearest evolutionary neighbours to the New Zealand phasmid fauna as a whole were predominantly from the New Zealand region (Fiji, Australia, New Guinea, New Caledonia and South America). As it appears to be an orphan, it is interesting to speculate that a combination of parthenogenetic reproduction and/or hybrid vigour in Acanthoxyla may have contributed to the extinction of its mother.

An approach to transcriptome analysis of non-model organisms using short-read sequences.

Transcriptome analysis using high-throughput short-read sequencing technology is straightforward when the sequenced genome is the same species or extremely similar to the reference genome. We present an analysis approach for when the sequenced organism does not have an already sequenced genome that can be used for a reference, as will be the case of many non-model organisms. As proof of concept, data from Solexa sequencing of the polyploid plant Pachycladon enysii was analysed using our approach with its nearest model reference genome being the diploid plant Arabidopsis thaliana. By using a combination of mapping and de novo assembly tools we could determine duplicate genes belonging to one or other of the genome copies. Our approach demonstrates that transcriptome analysis using high-throughput short-read sequencing need not be restricted to the genomes of model organisms.

A fragmented aflatoxin-like gene cluster in the forest pathogen Dothistroma septosporum.

The polyketide toxin dothistromin is very similar in structure to the aflatoxin precursor, versicolorin B. Dothistromin is made by a pine needle pathogen, Dothistroma septosporum, both in culture and in planta. Orthologs of aflatoxin biosynthetic genes have been identified that are required for dothistromin biosynthesis in D. septosporum. In contrast to the situation in aflatoxin-producing fungi where 25 aflatoxin biosynthetic and regulatory genes are tightly clustered in one region of the genome, the dothistromin gene cluster is fragmented. Three mini-clusters of dothistromin genes have been identified, each located on a 1.3-Mb chromosome and each grouped with non-dothistromin genes. There are no obvious patterns of repeated sequences or transposon relics to suggest recent recombination events. Most dothistromin genes within the mini-clusters are co-regulated, suggesting that coordinate control of gene expression is achieved despite this unusual arrangement of secondary metabolite biosynthetic genes.

Combined experimental and computational approach to identify non-protein-coding RNAs in the deep-branching eukaryote Giardia intestinalis.

Non-protein-coding RNAs represent a large proportion of transcribed sequences in eukaryotes. These RNAs often function in large RNA-protein complexes, which are catalysts in various RNA-processing pathways. As RNA processing has become an increasingly important area of research, numerous non-messenger RNAs have been uncovered in all the model eukaryotic organisms. However, knowledge on RNA processing in deep-branching eukaryotes is still limited. This study focuses on the identification of non-protein-coding RNAs from the diplomonad parasite Giardia intestinalis, showing that a combined experimental and computational search strategy is a fast method of screening reduced or compact genomes. The analysis of our Giardia cDNA library has uncovered 31 novel candidates, including C/D-box and H/ACA box snoRNAs, as well as an unusual transcript of RNase P, and double-stranded RNAs. Subsequent computational analysis has revealed additional putative C/D-box snoRNAs. Our results will lead towards a future understanding of RNA metabolism in the deep-branching eukaryote Giardia, as more ncRNAs are characterized.

RNase MRP and the RNA processing cascade in the eukaryotic ancestor.

BACKGROUND: Within eukaryotes there is a complex cascade of RNA-based macromolecules that process other RNA molecules, especially mRNA, tRNA and rRNA. An example is RNase MRP processing ribosomal RNA (rRNA) in ribosome biogenesis. One hypothesis is that this complexity was present early in eukaryotic evolution; an alternative is that an initial simpler network later gained complexity by gene duplication in lineages that led to animals, fungi and plants. Recently there has been a rapid increase in support for the complexity-early theory because the vast majority of these RNA-processing reactions are found throughout eukaryotes, and thus were likely to be present in the last common ancestor of living eukaryotes, herein called the Eukaryotic Ancestor. RESULTS: We present an overview of the RNA processing cascade in the Eukaryotic Ancestor and investigate in particular, RNase MRP which was previously thought to have evolved later in eukaryotes due to its apparent limited distribution in fungi and animals and plants. Recent publications, as well as our own genomic searches, find previously unknown RNase MRP RNAs, indicating that RNase MRP has a wide distribution in eukaryotes. Combining secondary structure and promoter region analysis of RNAs for RNase MRP, along with analysis of the target substrate (rRNA), allows us to discuss this distribution in the light of eukaryotic evolution. CONCLUSION: We conclude that RNase MRP can now be placed in the RNA-processing cascade of the Eukaryotic Ancestor, highlighting the complexity of RNA-processing in early eukaryotes. Promoter analyses of MRP-RNA suggest that regulation of the critical processes of rRNA cleavage can vary, showing that even these key cellular processes (for which we expect high conservation) show some species-specific variability. We present our consensus MRP-RNA secondary structure as a useful model for further searches.

Using ancestral sequences to uncover potential gene homologues.

Gene homologues between distantly related species can be difficult to identify. We test the idea that inferred ancestral sequences could aid in finding gene homologues. Ancestral sequences are inferred by aligning gene homologues on a known tree and estimating the most likely amino acid for each position at each node in that tree. BLAST(R) and HMMER are used separately and together with ancestral sequences to search the genome sequence databases of Encephalitozoon cuniculi, Entamoeba histolytica and Giardia lamblia for RNase P protein homologues. RNase P proteins (Pop4, Pop1, Pop5 and Rpp21) have been reported in humans and at least two other eukaryotic species but have yet to be identified in the above genomes. Using ancestral sequences reconstruction (ASR) for these proteins, we successfully identified putative homologues from E. cuniculi, Ent. histolytica and G. lamblia. In some cases, the use of ASR outperformed BLAST and HMMER. Overall, including ancestral sequences in searches with BLAST and/or HMMER was the most successful approach in the recovery of potential RNase P protein gene homologues, making this a useful technique in early homologue identification.