Diversification of the C-TERMINALLY ENCODED PEPTIDE (CEP) gene family in angiosperms, and evolution of plant-family specific CEP genes

BACKGROUND Small, secreted signaling peptides work in parallel with phytohormones to control important aspects of plant growth and development. Genes from the C-TERMINALLY ENCODED PEPTIDE (CEP) family produce such peptides which negatively regulate plant growth, especially under stress, and affect other important developmental processes. To illuminate how the CEP gene family has evolved within the plant kingdom, including its emergence, diversification and variation between lineages, a comprehensive survey was undertaken to identify and characterize CEP genes in 106 plant genomes. RESULTS Using a motif-based system developed for this study to identify canonical CEP peptide domains, a total of 916 CEP genes and 1,223 CEP domains were found in angiosperms and for the first time in gymnosperms. This defines a narrow band for the emergence of CEP genes in plants, from the divergence of lycophytes to the angiosperm/gymnosperm split. Both CEP genes and domains were found to have diversified in angiosperms, particularly in the Poaceae and Solanaceae plant families. Multispecies orthologous relationships were determined for 22% of identified CEP genes, and further analysis of those groups found selective constraints upon residues within the CEP peptide and within the previously little-characterized variable region. An examination of public Oryza sativa RNA-Seq datasets revealed an expression pattern that links OsCEP5 and OsCEP6 to panicle development and flowering, and CEP gene trees reveal these emerged from a duplication event associated with the Poaceae plant family. CONCLUSIONS The characterization of the plant-family specific CEP genes OsCEP5 and OsCEP6, the association of CEP genes with angiosperm-specific development processes like panicle development, and the diversification of CEP genes in angiosperms provides further support for the hypothesis that CEP genes have been integral to the evolution of novel traits within the angiosperm lineage. Beyond these findings, the comprehensive set of CEP genes and their properties reported here will be a resource for future research on CEP genes and peptides.We thank Jason Bragg for his input and advice on inferring gene trees. This work was supported by an Australian Research Council Discovery Project grant (DP120101893). HAO received financial support (UHS10488) to conduct this study from the Grains Research and Development Council

StarBEAST2 Brings Faster Species Tree Inference and Accurate Estimates of Substitution Rates

Fully Bayesian multispecies coalescent (MSC) methods like *BEAST estimate species trees from multiple sequence alignments. Today thousands of genes can be sequenced for a given study, but using that many genes with *BEAST is intractably slow. An alternative is to use heuristic methods which compromise accuracy or completeness in return for speed. A common heuristic is concatenation, which assumes that the evolutionary history of each gene tree is identical to the species tree. This is an inconsistent estimator of species tree topology, a worse estimator of divergence times, and induces spurious substitution rate variation when incomplete lineage sorting is present. Another class of heuristics directly motivated by the MSC avoids many of the pitfalls of concatenation but cannot be used to estimate divergence times. To enable fuller use of available data and more accurate inference of species tree topologies, divergence times, and substitution rates, we have developed a new version of *BEAST called StarBEAST2. To improve convergence rates we add analytical integration of population sizes, novel MCMC operators and other optimizations. Computational performance improved by 13.5× and 13.8× respectively when analyzing two empirical data sets, and an average of 33.1× across 30 simulated data sets. To enable accurate estimates of per-species substitution rates, we introduce species tree relaxed clocks, and show that StarBEAST2 is a more powerful and robust estimator of rate variation than concatenation. StarBEAST2 is available through the BEAUTi package manager in BEAST 2.4 and above.This work was supported by a Rutherford Discovery Fellowship awarded to A.J.D. by the Royal Society of New Zealand. H.A.O. was supported by an Australian Laureate Fellowship awarded to Craig Moritz by the Australian Research Council (FL110100104)

Phylovar: toward scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data

Motivation: Single-nucleotide variants (SNVs) are the most common variations in the human genome. Recently developed methods for SNV detection from single-cell DNA sequencing data, such as SCI and scVILP, leverage the evolutionary history of the cells to overcome the technical errors associated with single-cell sequencing protocols. Despite being accurate, these methods are not scalable to the extensive genomic breadth of single-cell whole-genome (scWGS) and whole-exome sequencing (scWES) data. Results: Here, we report on a new scalable method, Phylovar, which extends the phylogeny-guided variant calling approach to sequencing datasets containing millions of loci. Through benchmarking on simulated datasets under different settings, we show that, Phylovar outperforms SCI in terms of running time while being more accurate than Monovar (which is not phylogeny-aware) in terms of SNV detection. Furthermore, we applied Phylovar to two real biological datasets: an scWES triple-negative breast cancer data consisting of 32 cells and 3375 loci as well as an scWGS data of neuron cells from a normal human brain containing 16 cells and approximately 2.5 million loci. For the cancer data, Phylovar detected somatic SNVs with high or moderate functional impact that were also supported by bulk sequencing dataset and for the neuron dataset, Phylovar identified 5745 SNVs with non-synonymous effects some of which were associated with neurodegenerative diseases. Availability and implementation: Phylovar is implemented in Python and is publicly available at https://github.com/NakhlehLab/Phylovar.National Science Foundation | Ref. IIS-1812822National Science Foundation | Ref. IIS-210683

Comparative (Meta)genomic Analysis and Ecological Profiling of Human Gut-Specific Bacteriophage φB124-14

Bacteriophage associated with the human gut microbiome are likely to have an important impact on community structure and function, and provide a wealth of biotechnological opportunities. Despite this, knowledge of the ecology and composition of bacteriophage in the gut bacterial community remains poor, with few well characterized gut-associated phage genomes currently available. Here we describe the identification and in-depth (meta)genomic, proteomic, and ecological analysis of a human gut-specific bacteriophage (designated φB124-14). In doing so we illuminate a fraction of the biological dark matter extant in this ecosystem and its surrounding eco-genomic landscape, identifying a novel and uncharted bacteriophage gene-space in this community. φB124-14 infects only a subset of closely related gut-associated Bacteroides fragilis strains, and the circular genome encodes functions previously found to be rare in viral genomes and human gut viral metagenome sequences, including those which potentially confer advantages upon phage and/or host bacteria. Comparative genomic analyses revealed φB124-14 is most closely related to φB40-8, the only other publically available Bacteroides sp. phage genome, whilst comparative metagenomic analysis of both phage failed to identify any homologous sequences in 136 non-human gut metagenomic datasets searched, supporting the human gut-specific nature of this phage. Moreover, a potential geographic variation in the carriage of these and related phage was revealed by analysis of their distribution and prevalence within 151 human gut microbiomes and viromes from Europe, America and Japan. Finally, ecological profiling of φB124-14 and φB40-8, using both gene-centric alignment-driven phylogenetic analyses, as well as alignment-free gene-independent approaches was undertaken. This not only verified the human gut-specific nature of both phage, but also indicated that these phage populate a distinct and unexplored ecological landscape within the human gut microbiome

BEAST 2.5:An advanced software platform for Bayesian evolutionary analysis

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release

The Inuit discovery of Europe? The Orkney Finnmen, preternatural objects and the re-enchantment of early-modern science.

The late-seventeenth century saw a peak in accounts of supposed encounters with ‘Finnmen’ in Orkney. These accounts have shaped the folklore of the Northern Isles. Scholars linked to the Royal Society suggested the accounts represented encounters with Inuit. Subsequent explanations included autonomous travel by Inuit groups and abduction and abandonment. These accounts should be understood as part of a European scientific tradition of preternatural philosophy, occupied with the deviations and errors of nature. Far from indicating the presence of Inuit individuals in Orkney waters, they provide evidence of the narrative instability of early-modern science and its habit of ‘thinking with things’. Captivated by Inuit artefacts, the natural philosophers and virtuosi of the Royal Society imagined Orkney as a site of reverse contact with the ‘primitive’. Nineteenth-century antiquarians and folklorists reliant on these texts failed to understand the extent to which objectivity was not an epistemic virtue in early-modern science

Annotation-free delineation of prokaryotic homology groups.

Phylogenomic studies of prokaryotic taxa often assume conserved marker genes are homologous across their length. However, processes such as horizontal gene transfer or gene duplication and loss may disrupt this homology by recombining only parts of genes, causing gene fission or fusion. We show using simulation that it is necessary to delineate homology groups in a set of bacterial genomes without relying on gene annotations to define the boundaries of homologous regions. To solve this problem, we have developed a graph-based algorithm to partition a set of bacterial genomes into Maximal Homologous Groups of sequences (MHGs) where each MHG is a maximal set of maximum-length sequences which are homologous across the entire sequence alignment. We applied our algorithm to a dataset of 19 Enterobacteriaceae species and found that MHGs cover much greater proportions of genomes than markers and, relatedly, are less biased in terms of the functions of the genes they cover. We zoomed in on the correlation between each individual marker and their overlapping MHGs, and show that few phylogenetic splits supported by the markers are supported by the MHGs while many marker-supported splits are contradicted by the MHGs. A comparison of the species tree inferred from marker genes with the species tree inferred from MHGs suggests that the increased bias and lack of genome coverage by markers causes incorrect inferences as to the overall relationship between bacterial taxa

Diversification of the C-TERMINALLY ENCODED PEPTIDE (CEP) gene family in angiosperms, and evolution of plant-family specific CEP genes

Background: Small, secreted signaling peptides work in parallel with phytohormones to control important aspects of plant growth and development. Genes from the C-TERMINALLY ENCODED PEPTIDE (CEP) family produce such peptides which negatively regulate plant growth, especially under stress, and affect other important developmental processes. To illuminate how the CEP gene family has evolved within the plant kingdom, including its emergence, diversification and variation between lineages, a comprehensive survey was undertaken to identify and characterize CEP genes in 106 plant genomes.Results: Using a motif-based system developed for this study to identify canonical CEP peptide domains, a total of 916 CEP genes and 1,223 CEP domains were found in angiosperms and for the first time in gymnosperms. This defines a narrow band for the emergence of CEP genes in plants, from the divergence of lycophytes to the angiosperm/gymnosperm split. Both CEP genes and domains were found to have diversified in angiosperms, particularly in the Poaceae and Solanaceae plant families. Multispecies orthologous relationships were determined for 22% of identified CEP genes, and further analysis of those groups found selective constraints upon residues within the CEP peptide and within the previously little-characterized variable region. An examination of public Oryza sativa RNA-Seq datasets revealed an expression pattern that links OsCEP5 and OsCEP6 to panicle development and flowering, and CEP gene trees reveal these emerged from a duplication event associated with the Poaceae plant family.Conclusions: The characterization of the plant-family specific CEP genes OsCEP5 and OsCEP6, the association of CEP genes with angiosperm-specific development processes like panicle development, and the diversification of CEP genes in angiosperms provides further support for the hypothesis that CEP genes have been integral to the evolution of novel traits within the angiosperm lineage. Beyond these findings, the comprehensive set of CEP genes and their properties reported here will be a resource for future research on CEP genes and peptides

Data from: Computational performance and statistical accuracy of *BEAST and comparisons with other methods

Under the multispecies coalescent model of molecular evolution, gene trees have independent evolutionary histories within a shared species tree. In comparison, supermatrix concatenation methods assume that gene trees share a single common genealogical history, thereby equating gene coalescence with species divergence. The multispecies coalescent is supported by previous studies which found that its predicted distributions fit empirical data, and that concatenation is not a consistent estimator of the species tree. *BEAST, a fully Bayesian implementation of the multispecies coalescent, is popular but computationally intensive, so the increasing size of phylogenetic data sets is both a computational challenge and an opportunity for better systematics. Using simulation studies, we characterize the scaling behavior of *BEAST, and enable quantitative prediction of the impact increasing the number of loci has on both computational performance and statistical accuracy. Follow-up simulations over a wide range of parameters show that the statistical performance of *BEAST relative to concatenation improves both as branch length is reduced and as the number of loci is increased. Finally, using simulations based on estimated parameters from two phylogenomic data sets, we compare the performance of a range of species tree and concatenation methods to show that using *BEAST with tens of loci can be preferable to using concatenation with thousands of loci. Our results provide insight into the practicalities of Bayesian species tree estimation, the number of loci required to obtain a given level of accuracy and the situations in which supermatrix or summary methods will be outperformed by the fully Bayesian multispecies coalescent