Dataset Information

Sequence locally, think globally: The Darwin Tree of Life Project.

ABSTRACT: The goals of the Earth Biogenome Project-to sequence the genomes of all eukaryotic life on earth-are as daunting as they are ambitious. The Darwin Tree of Life Project was founded to demonstrate the credibility of these goals and to deliver at-scale genome sequences of unprecedented quality for a biogeographic region: the archipelago of islands that constitute Britain and Ireland. The Darwin Tree of Life Project is a collaboration between biodiversity organizations (museums, botanical gardens, and biodiversity institutes) and genomics institutes. Together, we have built a workflow that collects specimens from the field, robustly identifies them, performs sequencing, generates high-quality, curated assemblies, and releases these openly for the global community to use to build future science and conservation efforts.

SUBMITTER: Darwin Tree of Life Project Consortium

PROVIDER: S-EPMC8797607 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sequence locally, think globally: The Darwin Tree of Life Project.

Proceedings of the National Academy of Sciences of the United States of America 20220101 4

The goals of the Earth Biogenome Project-to sequence the genomes of all eukaryotic life on earth-are as daunting as they are ambitious. The Darwin Tree of Life Project was founded to demonstrate the credibility of these goals and to deliver at-scale genome sequences of unprecedented quality for a biogeographic region: the archipelago of islands that constitute Britain and Ireland. The Darwin Tree of Life Project is a collaboration between biodiversity organizations (museums, botanical gardens, a ...[more]

PMID: 35042805

Similar Datasets

Project description:The precise placement of nucleosomes has large regulatory effects on gene expression. Recent work suggests that nucleosome placement is regulated in part by the affinity of the underlying DNA sequence for the histone octamer. Nucleosome locations are also regulated by several different ATP-dependent chromatin remodeling enzymes. This raises the question of whether DNA sequence influences the activity of chromatin remodeling enzymes. DNA sequence could most simply regulate nucleosome remodeling through its effect on nucleosome stability. In such a model, unstable nucleosomes would be remodeled faster than stable nucleosomes. It is also possible that certain DNA elements could regulate remodeling by inhibiting the interaction of nucleosomes with the remodeling enzyme. A third possibility is that DNA sequence could regulate the outcome of remodeling by influencing how reaction intermediates collapse into a particular set of stable nucleosomal positions. Here we dissect the contribution from these potential mechanisms to the activities of yeast RSC and human ACF, which are representative members of two major classes of remodeling complexes. We find that varying the histone-DNA affinity over 3 orders of magnitude has negligible effects on the rates of nucleosome remodeling and ATP hydrolysis by these two enzymes. This suggests that the rate-limiting step for nucleosome remodeling may not involve the disruption of histone-DNA contacts. We further find that a specific curved DNA element previously hypothesized to inhibit ACF activity does not inhibit substrate binding or remodeling by ACF. The element, however, does influence the distribution of nucleosome positions generated by ACF. Our data support a model in which remodeling enzymes move nucleosomes to new locations by a general sequence-independent mechanism. However, consequent to the rate-limiting remodeling step, the local DNA sequence promotes a collapse of remodeling intermediates into highly resolved positions that are dictated by thermodynamic differences between adjacent positions.

Project description:Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.

Project description:BackgroundNetwork-based learning algorithms for automated function prediction (AFP) are negatively affected by the limited coverage of experimental data and limited a priori known functional annotations. As a consequence their application to model organisms is often restricted to well characterized biological processes and pathways, and their effectiveness with poorly annotated species is relatively limited. A possible solution to this problem might consist in the construction of big networks including multiple species, but this in turn poses challenging computational problems, due to the scalability limitations of existing algorithms and the main memory requirements induced by the construction of big networks. Distributed computation or the usage of big computers could in principle respond to these issues, but raises further algorithmic problems and require resources not satisfiable with simple off-the-shelf computers.ResultsWe propose a novel framework for scalable network-based learning of multi-species protein functions based on both a local implementation of existing algorithms and the adoption of innovative technologies: we solve "locally" the AFP problem, by designing "vertex-centric" implementations of network-based algorithms, but we do not give up thinking "globally" by exploiting the overall topology of the network. This is made possible by the adoption of secondary memory-based technologies that allow the efficient use of the large memory available on disks, thus overcoming the main memory limitations of modern off-the-shelf computers. This approach has been applied to the analysis of a large multi-species network including more than 300 species of bacteria and to a network with more than 200,000 proteins belonging to 13 Eukaryotic species. To our knowledge this is the first work where secondary-memory based network analysis has been applied to multi-species function prediction using biological networks with hundreds of thousands of proteins.ConclusionsThe combination of these algorithmic and technological approaches makes feasible the analysis of large multi-species networks using ordinary computers with limited speed and primary memory, and in perspective could enable the analysis of huge networks (e.g. the whole proteomes available in SwissProt), using well-equipped stand-alone machines.

Project description:The evolution of cetaceans, from their early transition to an aquatic lifestyle to their subsequent diversification, has been the subject of numerous studies. However, although the higher-level relationships among cetacean families have been largely settled, several aspects of the systematics within these groups remain unresolved. Problematic clades include the oceanic dolphins (37 spp.), which have experienced a recent rapid radiation, and the beaked whales (22 spp.), which have not been investigated in detail using nuclear loci. The combined application of high-throughput sequencing with techniques that target specific genomic sequences provide a powerful means of rapidly generating large volumes of orthologous sequence data for use in phylogenomic studies. To elucidate the phylogenetic relationships within the Cetacea, we combined sequence capture with Illumina sequencing to generate data for $\sim $3200 protein-coding genes for 68 cetacean species and their close relatives including the pygmy hippopotamus. By combining data from $>$38,000 exons with existing sequences from 11 cetaceans and seven outgroup taxa, we produced the first comprehensive comparative genomic data set for cetaceans, spanning 6,527,596 aligned base pairs (bp) and 89 taxa. Phylogenetic trees reconstructed with maximum likelihood and Bayesian inference of concatenated loci, as well as with coalescence analyses of individual gene trees, produced mostly concordant and well-supported trees. Our results completely resolve the relationships among beaked whales as well as the contentious relationships among oceanic dolphins, especially the problematic subfamily Delphinidae. We carried out Bayesian estimation of species divergence times using MCMCTree and compared our complete data set to a subset of clocklike genes. Analyses using the complete data set consistently showed less variance in divergence times than the reduced data set. In addition, integration of new fossils (e.g., Mystacodon selenensis) indicates that the diversification of Crown Cetacea began before the Late Eocene and the divergence of Crown Delphinidae as early as the Middle Miocene. [Cetaceans; phylogenomics; Delphinidae; Ziphiidae; dolphins; whales.].

Dataset Information

Sequence locally, think globally: The Darwin Tree of Life Project.

Publications

Sequence locally, think globally: The Darwin Tree of Life Project.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets