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Ophiostomatoid fungi are vectored by their bark-beetle associates and colonize different host tree species. To survive and proliferate in the host, they have evolved mechanisms for detoxification and elimination of host defence compounds, efficient nutrient sequestration, and, in pathogenic species, virulence towards plants. Here, we assembled a draft genome of the spruce pathogen Ophiostoma bicolor. For our comparative and phylogenetic analyses, we mined the genomes of closely related species (Ophiostoma piceae, Ophiostoma ulmi, Ophiostoma novo-ulmi, and Grosmannia clavigera). Our aim was to acquire a genomic and evolutionary perspective of gene families important in host colonization. Genome comparisons showed that both the nuclear and mitochondrial genomes in our assembly were largely complete. Our O. bicolor 25.3 Mbp draft genome had 10 018 predicted genes, 6041 proteins with gene ontology (GO) annotation, 269 carbohydrate-active enzymes (CAZymes), 559 peptidases and inhibitors, and 1373 genes likely involved in pathogen-host interactions. Phylogenetic analyses of selected protein families revealed core sets of cytochrome P450 genes, ABC transporters and backbone genes involved in secondary metabolite (SM) biosynthesis (polyketide synthases (PKS) and non-ribosomal synthases), and species-specific gene losses and duplications. Phylogenetic analyses of protein families of interest provided insight into evolutionary adaptations to host biochemistry in ophiostomatoid fungi.
Motivation: Full-length DNA and protein sequences that span the entire length of a gene are ideally used for multiple sequence alignments (MSAs) and the subsequent inference of their relationships. Frequently, however, MSAs contain a substantial amount of missing data. For example, expressed sequence tags (ESTs), which are partial sequences of expressed genes, are the predominant source of sequence data for many organisms. The patterns of missing data typical for EST-derived alignments greatly compromise the accuracy of estimated phylogenies. Results: We present a statistical method for inferring phylogenetic trees from EST-based incomplete MSA data. We propose a class of hierarchical models for modeling pairwise distances between the sequences, and develop a fully Bayesian approach for estimation of the model parameters. Once the distance matrix is estimated, the phylogenetic tree may be constructed by applying neighbor-joining (or any other algorithm of choice). We also show that maximizing the marginal likelihood from the Bayesian approach yields similar results to a pro. le likelihood estimation. The proposed methods are illustrated using simulated protein families, for which the true phylogeny is known, and one real protein family.
The unusual mix of morphological traits displayed by extinct South American native ungulates (SANUs) confounded both Charles Darwin, who first discovered them, and Richard Owen, who tried to resolve their relationships. Here we report an almost complete mitochondrial genome for the litoptern Macrauchenia. Our dated phylogenetic tree places Macrauchenia as sister to Perissodactyla, but close to the radiation of major lineages within Laurasiatheria. This position is consistent with a divergence estimate of B66Ma (95% credibility interval, 56.64-77.83 Ma) obtained for the split between Macrauchenia and other Panperissodactyla. Combined with their morphological distinctiveness, this evidence supports the positioning of Litopterna (possibly in company with other SANU groups) as a separate order within Laurasiatheria. We also show that, when using strict criteria, extinct taxa marked by deep divergence times and a lack of close living relatives may still be amenable to palaeogenomic analysis through iterative mapping against more distant relatives.
The unusual mix of morphological traits displayed by extinct South American native ungulates (SANUs) confounded both Charles Darwin, who first discovered them, and Richard Owen, who tried to resolve their relationships. Here we report an almost complete mitochondrial genome for the litoptern Macrauchenia. Our dated phylogenetic tree places Macrauchenia as sister to Perissodactyla, but close to the radiation of major lineages within Laurasiatheria. This position is consistent with a divergence estimate of B66Ma (95% credibility interval, 56.64-77.83 Ma) obtained for the split between Macrauchenia and other Panperissodactyla. Combined with their morphological distinctiveness, this evidence supports the positioning of Litopterna (possibly in company with other SANU groups) as a separate order within Laurasiatheria. We also show that, when using strict criteria, extinct taxa marked by deep divergence times and a lack of close living relatives may still be amenable to palaeogenomic analysis through iterative mapping against more distant relatives.
Many deep evolutionary divergences still remain unresolved, such as those among major taxa of the Lophotrochozoa. As alternative phylogenetic markers, the intron-exon structure of eukaryotic genomes and the patterns of absence and presence of spliceosomal introns appear to be promising. However, given the potential homoplasy of intron presence, the phylogenetic analysis of this data using standard evolutionary approaches has remained a challenge. Here, we used Mutual Information (MI) to estimate the phylogeny of Protostomia using gene structure data, and we compared these results with those obtained with Dollo Parsimony. Using full genome sequences from nine Metazoa, we identified 447 groups of orthologous sequences with 21,732 introns in 4,870 unique intron positions. We determined the shared absence and presence of introns in the corresponding sequence alignments and have made this data available in "IntronBase", a web-accessible and downloadable SQLite database. Our results obtained using Dollo Parsimony are obviously misled through systematic errors that arise from multiple intron loss events, but extensive filtering of data improved the quality of the estimated phylogenies. Mutual Information, in contrast, performs better with larger datasets, but at the same time it requires a complete data set, which is difficult to obtain for orthologs from a large number of taxa. Nevertheless, Mutual Information-based distances proved to be useful in analyzing this kind of data, also because the estimation of MI-based distances is independent of evolutionary models and therefore no pre-definitions of ancestral and derived character states are necessary.
Xenikoudakis et al. report a partial mitochondrial genome of the extinct giant beaver Castoroides and estimate the origin of aquatic behavior in beavers to approximately 20 million years. This time estimate coincides with the extinction of terrestrial beavers and raises the question whether the two events had a common cause.
Objective
Plant carnivory is distributed across the tree of life and has evolved at least six times independently, but sequenced and annotated nuclear genomes of carnivorous plants are currently lacking. We have sequenced and structurally annotated the nuclear genome of the carnivorous Roridula gorgonias and that of a non-carnivorous relative, Madeira’s lily-of-the-valley-tree, Clethra arborea, both within the Ericales. This data adds an important resource to study the evolutionary genetics of plant carnivory across angiosperm lineages and also for functional and systematic aspects of plants within the Ericales.
Results
Our assemblies have total lengths of 284 Mbp (R. gorgonias) and 511 Mbp (C. arborea) and show high BUSCO scores of 84.2% and 89.5%, respectively. We used their predicted genes together with publicly available data from other Ericales’ genomes and transcriptomes to assemble a phylogenomic data set for the inference of a species tree. However, groups of orthologs showed a marked absence of species represented by a transcriptome. We discuss possible reasons and caution against combining predicted genes from genome- and transriptome-based assemblies.
Objective
Plant carnivory is distributed across the tree of life and has evolved at least six times independently, but sequenced and annotated nuclear genomes of carnivorous plants are currently lacking. We have sequenced and structurally annotated the nuclear genome of the carnivorous Roridula gorgonias and that of a non-carnivorous relative, Madeira’s lily-of-the-valley-tree, Clethra arborea, both within the Ericales. This data adds an important resource to study the evolutionary genetics of plant carnivory across angiosperm lineages and also for functional and systematic aspects of plants within the Ericales.
Results
Our assemblies have total lengths of 284 Mbp (R. gorgonias) and 511 Mbp (C. arborea) and show high BUSCO scores of 84.2% and 89.5%, respectively. We used their predicted genes together with publicly available data from other Ericales’ genomes and transcriptomes to assemble a phylogenomic data set for the inference of a species tree. However, groups of orthologs showed a marked absence of species represented by a transcriptome. We discuss possible reasons and caution against combining predicted genes from genome- and transriptome-based assemblies.
Background
The Amazon molly, Poecilia formosa (Teleostei: Poeciliinae) is an unisexual, all-female species. It evolved through the hybridisation of two closely related sexual species and exhibits clonal reproduction by sperm dependent parthenogenesis (or gynogenesis) where the sperm of a parental species is only used to activate embryogenesis of the apomictic, diploid eggs but does not contribute genetic material to the offspring.
Here we provide and describe the first de novo assembled transcriptome of the Amazon molly in comparison with its maternal ancestor, the Atlantic molly Poecilia mexicana. The transcriptome data were produced through sequencing of single end libraries (100 bp) with the Illumina sequencing technique.
Results
83,504,382 reads for the Amazon molly and 81,625,840 for the Atlantic molly were assembled into 127,283 and 78,961 contigs for the Amazon molly and the Atlantic molly, respectively. 63% resp. 57% of the contigs could be annotated with gene ontology terms after sequence similarity comparisons. Furthermore, we were able to identify genes normally involved in reproduction and especially in meiosis also in the transcriptome dataset of the apomictic reproducing Amazon molly.
Conclusions
We assembled and annotated the transcriptome of a non-model organism, the Amazon molly, without a reference genome (de novo). The obtained dataset is a fundamental resource for future research in functional and expression analysis. Also, the presence of 30 meiosis-specific genes within a species where no meiosis is known to take place is remarkable and raises new questions for future research.
Consensify
(2020)
A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes.