Project description:Tree House Explorer (THEx) is a genome browser that integrates phylogenomic data and genomic annotations into a single interactive platform for combined analysis. THEx allows users to visualize genome-wide variation in evolutionary histories and genetic divergence on a chromosome-by-chromosome basis, with continuous sliding window comparisons to gene annotations (GFF/GTF), recombination rates, and other user-specified, highly customizable feature annotations. THEx provides a new platform for interactive phylogenomic data visualization to analyze and interpret the diverse evolutionary histories woven throughout genomes. Hosted on Conda, THEx integrates seamlessly into new or pre-existing workflows.
Project description:Plants and photovoltaics share the same purpose as harvesting sunlight. Therefore, botanical studies could lead to new breakthroughs in photovoltaics. However, the basic mechanism of photosynthesis is different to semiconductor-based photovoltaics and the gap between photosynthesis and solar cells must be bridged before we can apply the botanical principles to photovoltaics. In this study, we analysed the role of the fractal structures found in plants in light harvesting based on a simplified model, rotated the structures by 90° and applied them to fractal-structured photovoltaic Si solar cell arrays. Adoption of botanically inspired fractal structures can result in solar cell arrays with omnidirectional properties, and in this case, yielded a 25% enhancement in electric energy production. The fractal structure used in this study was two-dimensional and symmetric; investigating and optimizing three-dimensional asymmetric fractal structures would further enhance the performance of photovoltaics. Furthermore, this study represents only the first step towards the development of a new type of photovoltaics based on botanical principles, and points to further aspects of botanical knowledge that could be exploited, in addition to plant fractal structures. For example, leaf anatomy, phyllotaxis and chloroplastic mechanisms could be applied to the design of new types of photovoltaics.
Project description:Cytosine methylation is a conserved base modification, but explanations for its interspecific variation remain elusive. Only through taxonomic sampling of disparate groups can unifying explanations for interspecific variation be thoroughly tested. Here we leverage phylogenetic resolution of cytosine DNA methyltransferases (DNA MTases) and genome evolution to better understand widespread interspecific variation across 40 diverse fungal species. DNA MTase genotypes have diversified from the ancestral DNMT1+DNMT5 genotype through numerous loss events, and duplications, whereas, DIM-2 and RID-1 are more recently derived in fungi. Methylation is typically enriched at intergenic regions, which includes repeats and transposons. Unlike certain Insecta and Angiosperm species, Fungi lack canonical gene body methylation. Some fungi species possess large clusters of contiguous methylation encompassing many genes, repetitive DNA and transposons, and are not ancient in origin. Broadly, methylation is partially explained by DNA MTase genotype and repetitive DNA content. Basidiomycota on average have the highest level of methylation, and repeat content, compared to other phyla. However, exceptions exist across Fungi. Other traits, including DNA repair mechanisms, might contribute to interspecific methylation variation within Fungi. Our results show mechanism and genome evolution are unifying explanations for interspecific methylation variation across Fungi.
Project description:Data exploration is critical to the comprehension of large biological data sets generated by high-throughput assays such as sequencing. However, most existing tools for interactive visualisation are limited to specific assays or analyses. Here, we present the iSEE (Interactive SummarizedExperiment Explorer) software package, which provides a general visual interface for exploring data in a SummarizedExperiment object. iSEE is directly compatible with many existing R/Bioconductor packages for analysing high-throughput biological data, and provides useful features such as simultaneous examination of (meta)data and analysis results, dynamic linking between plots and code tracking for reproducibility. We demonstrate the utility and flexibility of iSEE by applying it to explore a range of real transcriptomics and proteomics data sets.
Project description:Identifying our most distant animal relatives has emerged as one of the most challenging problems in phylogenetics. This debate has major implications for our understanding of the origin of multicellular animals and of the earliest events in animal evolution, including the origin of the nervous system. Some analyses identify sponges as our most distant animal relatives (Porifera-sister hypothesis), and others identify comb jellies (Ctenophora-sister hypothesis). These analyses vary in many respects, making it difficult to interpret previous tests of these hypotheses. To gain insight into why different studies yield different results, an important next step in the ongoing debate, we systematically test these hypotheses by synthesizing 15 previous phylogenomic studies and performing new standardized analyses under consistent conditions with additional models. We find that Ctenophora-sister is recovered across the full range of examined conditions, and Porifera-sister is recovered in some analyses under narrow conditions when most outgroups are excluded and site-heterogeneous CAT models are used. We additionally find that the number of categories in site-heterogeneous models is sufficient to explain the Porifera-sister results. Furthermore, our cross-validation analyses show CAT models that recover Porifera-sister have hundreds of additional categories and fail to fit significantly better than site-heterogenuous models with far fewer categories. Systematic and standardized testing of diverse phylogenetic models suggests that we should be skeptical of Porifera-sister results both because they are recovered under such narrow conditions and because the models in these conditions fit the data no better than other models that recover Ctenophora-sister.