Two red algal classes, the Florideophyceae (approximately 7,100 spp.) and Bangiophyceae (approximately 193 spp.), comprise 98% of red algal diversity in marine and freshwater habitats. These two classes form well-supported monophyletic groups in most phylogenetic analyses. Nonetheless, the interordinal relationships remain largely unresolved, in particular in the largest subclass Rhodymeniophycidae that includes 70% of all species. To elucidate red algal phylogenetic relationships and study organelle evolution, we determined the sequence of 11 mitochondrial genomes (mtDNA) from 5 florideophycean subclasses. These mtDNAs were combined with existing data, resulting in a database of 25 florideophytes and 12 bangiophytes (including cyanidiophycean species). A concatenated alignment of mt proteins was used to resolve ordinal relationships in the Rhodymeniophycidae. Red algal mtDNA genome comparisons showed 47 instances of gene rearrangement including 12 that distinguish Bangiophyceae from Hildenbrandiophycidae, and 5 that distinguish Hildenbrandiophycidae from Nemaliophycidae. These organelle data support a rapid radiation and surprisingly high conservation of mtDNA gene syntheny among the morphologically divergent multicellular lineages of Rhodymeniophycidae. In contrast, we find extensive mitochondrial gene rearrangements when comparing Bangiophyceae and Florideophyceae and multiple examples of gene loss among the different red algal lineages.

A software implementation of the algorithm and example output files are available at http://fcg.tamu.edu/C_Hunter/.

Cryptophytes are an ecologically important group of largely photosynthetic unicellular eukaryotes. This lineage is of great interest to evolutionary biologists because their plastids are of red algal secondary endosymbiotic origin and the host cell retains four different genomes (host nuclear, mitochondrial, plastid, and red algal nucleomorph). Here, we report a comparative analysis of plastid genomes from six representative cryptophyte genera. Four newly sequenced cryptophyte plastid genomes of Chroomonas mesostigmatica, Ch. placoidea, Cryptomonas curvata, and Storeatula sp. CCMP1868 share a number of features including synteny and gene content with the previously sequenced genomes of Cryptomonas paramecium, Rhodomonas salina, Teleaulax amphioxeia, and Guillardia theta. Our analysis of these plastid genomes reveals examples of gene loss and intron insertion. In particular, the chlB/chlL/chlN genes, which encode light-independent (dark active) protochlorophyllide oxidoreductase (LIPOR) proteins have undergone recent gene loss and pseudogenization in cryptophytes. Comparison of phylogenetic trees based on plastid and nuclear genome data sets show the introduction, via secondary endosymbiosis, of a red algal derived plastid in a lineage of chlorophyll-c containing algae. This event was followed by additional rounds of eukaryotic endosymbioses that spread the red lineage plastid to diverse groups such as haptophytes and stramenopiles.

Teleaulax amphioxeia is a photosynthetic unicellular cryptophyte alga that is distributed throughout marine habitats worldwide. This alga is an important plastid donor to the dinoflagellate Dinophysis caudata through the ciliate Mesodinium rubrum in the marine food web. To better understand the genomic characteristics of T. amphioxeia, we have sequenced and analyzed its plastid genome. The plastid genome sequence of T. amphioxeia is similar to that of Rhodomonas salina, and they share significant synteny. This sequence exhibits less similarity to that of Guillardia theta, the representative plastid genome of photosynthetic cryptophytes. The gene content and order of the three photosynthetic cryptomonad plastid genomes studied is highly conserved. The plastid genome of T. amphioxeia is composed of 129,772 bp and includes 143 protein-coding genes, 2 rRNA operons and 30 tRNA sequences. The DNA polymerase III gene (dnaX) was most likely acquired via lateral gene transfer (LGT) from a firmicute bacterium, identical to what occurred in R. salina. On the other hand, the psbN gene was independently encoded by the plastid genome without a reverse transcriptase gene as an intron. To clarify the phylogenetic relationships of the algae with red-algal derived plastids, phylogenetic analyses of 32 taxa were performed, including three previously sequenced cryptophyte plastid genomes containing 93 protein-coding genes. The stramenopiles were found to have branched out from the Chromista taxa (cryptophytes, haptophytes, and stramenopiles), while the cryptophytes and haptophytes were consistently grouped into sister relationships with high resolution.

Supplementary data are available at Bioinformatics online.

BackgroundCryptophytes are an ecologically important group of algae comprised of phototrophic, heterotrophic and osmotrophic species. This lineage is of great interest to evolutionary biologists because their plastids are of red algal secondary endosymbiotic origin. Cryptophytes have a clear phylogenetic affinity to heterotrophic eukaryotes and possess four genomes: host-derived nuclear and mitochondrial genomes, and plastid and nucleomorph genomes of endosymbiotic origin.ResultsTo gain insight into cryptophyte mitochondrial genome evolution, we sequenced the mitochondrial DNAs of five species and performed a comparative analysis of seven genomes from the following cryptophyte genera: Chroomonas, Cryptomonas, Hemiselmis, Proteomonas, Rhodomonas, Storeatula and Teleaulax. The mitochondrial genomes were similar in terms of their general architecture, gene content and presence of a large repeat region. However, gene order was poorly conserved. Characteristic features of cryptophyte mtDNAs included large syntenic clusters resembling α-proteobacterial operons that encode bacteria-like rRNAs, tRNAs, and ribosomal protein genes. The cryptophyte mitochondrial genomes retain almost all genes found in many other eukaryotes including the nad, sdh, cox, cob, and atp genes, with the exception of sdh2 and atp3. In addition, gene cluster analysis showed that cryptophytes possess a gene order closely resembling the jakobid flagellates Jakoba and Reclinomonas. Interestingly, the cox1 gene of R. salina, T. amphioxeia, and Storeatula species was found to contain group II introns encoding a reverse transcriptase protein, as did the cob gene of Storeatula species CCMP1868.ConclusionsThese newly sequenced genomes increase the breadth of data available from algae and will aid in the identification of general trends in mitochondrial genome evolution. While most of the genomes were highly conserved, extensive gene arrangements have shuffled gene order, perhaps due to genome rearrangements associated with hairpin-containing mobile genetic elements, tRNAs with palindromic sequences, and tandem repeat sequences. The cox1 and cob gene sequences suggest that introns have recently been acquired during cryptophyte evolution. Comparison of phylogenetic trees based on plastid and mitochondrial genome data sets underscore the different evolutionary histories of the host and endosymbiont components of present-day cryptophytes.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4626-9) contains supplementary material, which is available to authorized users.

BackgroundAutomated protein function prediction methods are the only practical approach for assigning functions to genes obtained from model organisms. Many of the previously reported function annotation methods are of limited utility for fungal protein annotation. They are often trained only to one species, are not available for high-volume data processing, or require the use of data derived by experiments such as microarray analysis. To meet the increasing need for high throughput, automated annotation of fungal genomes, we have developed a tool for annotating fungal protein sequences with terms from the Gene Ontology.ResultsWe describe a classifier called PoGO (Prediction of Gene Ontology terms) that uses statistical pattern recognition methods to assign Gene Ontology (GO) terms to proteins from filamentous fungi. PoGO is organized as a meta-classifier in which each evidence source (sequence similarity, protein domains, protein structure and biochemical properties) is used to train independent base-level classifiers. The outputs of the base classifiers are used to train a meta-classifier, which provides the final assignment of GO terms. An independent classifier is trained for each GO term, making the system amenable to updating, without having to re-train the whole system. The resulting system is robust. It provides better accuracy and can assign GO terms to a higher percentage of unannotated protein sequences than other methods that we tested.ConclusionsOur annotation system overcomes many of the shortcomings that we found in other methods. We also provide a web server where users can submit protein sequences to be annotated.

Technologies for next-generation sequencing (NGS) have stimulated an exponential rise in high-throughput sequencing projects and resulted in the development of new read-assembly algorithms. A drastic reduction in the costs of generating short reads on the genomes of new organisms is attributable to recent advances in NGS technologies such as Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for several organisms, and de novo assembly is a key initiative that has facilitated gene discovery and other studies. More powerful analytical algorithms are needed to work on the increasing amount of sequence data. We make a thorough comparison of the de novo assembly algorithms to allow new users to clearly understand the assembly algorithms: overlap-layout-consensus and de-Bruijn-graph, string-graph based assembly, and hybrid approach. We also address the computational efficacy of each algorithm’s performance, challenges faced by the assem- bly tools used, and the impact of repeats. Our results compare the relative performance of the different assemblers and other related assembly differences with and without the reference genome. We hope that this analysis will contribute to further the application of de novo sequences and help the future growth of assembly algorithms.