The infinite sites model of genome evolution.
Ontology highlight
ABSTRACT:
SUBMITTER: Ma J
PROVIDER: S-EPMC2533685 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:A tree-structured multiplicative gamma process (TMGP) is developed, for inferring the depth of a tree-based factor-analysis model. This new model is coupled with the nested Chinese restaurant process, to nonparametrically infer the depth and width (structure) of the tree. In addition to developing the model, theoretical properties of the TMGP are addressed, and a novel MCMC sampler is developed. The structure of the inferred tree is used to learn relationships between high-dimensional data, and the model is also applied to compressive sensing and interpolation of incomplete images.
| S-EPMC4180059 | biostudies-literature
Project description:Many important applications in biochemistry, materials science, and catalysis sit squarely at the interface between quantum and statistical mechanics: Coherent evolution is interrupted by discrete events, such as binding of a substrate or isomerization. Theoretical models for such dynamics usually truncate the incorporation of these events to the linear response limit, thus requiring small step sizes. Here, we completely reassess the foundations of chemical exchange models and redesign a master equation treatment for exchange accurate to infinite order in perturbation theory. The net result is an astonishingly simple correction to the traditional picture, which vastly improves convergence with no increased computational cost. We demonstrate that this approach accurately and efficiently extracts physical parameters from complex experimental data, such as coherent hyperpolarization dynamics in magnetic resonance, and is applicable to a wide range of other systems.
| S-EPMC7413723 | biostudies-literature
Project description:Mutations and changes in a protein's environment are well known for their potential to induce misfolding and aggregation, including amyloid formation. Alternatively, such perturbations can trigger new interactions that lead to the polymerization of folded proteins. In contrast to aggregation, this process does not require misfolding and, to highlight this difference, we refer to it as agglomeration. This term encompasses the amorphous assembly of folded proteins as well as the polymerization in one, two, or three dimensions. We stress the remarkable potential of symmetric homo-oligomers to agglomerate even by single surface point mutations, and we review the double-edged nature of this potential: how aberrant assemblies resulting from agglomeration can lead to disease, but also how agglomeration can serve in cellular adaptation and be exploited for the rational design of novel biomaterials.
| S-EPMC6471489 | biostudies-literature
Project description:The recent observation of superconductivity in [Formula: see text] has raised fundamental questions about the hierarchy of the underlying electronic structure. Calculations suggest that this system falls in the Mott-Hubbard regime, rather than the charge-transfer configuration of other nickel oxides and the superconducting cuprates. Here, we use state-of-the-art, locally resolved electron energy-loss spectroscopy to directly probe the Mott-Hubbard character of [Formula: see text] Upon doping, we observe emergent hybridization reminiscent of the Zhang-Rice singlet via the oxygen-projected states, modification of the Nd 5d states, and the systematic evolution of Ni 3d hybridization and filling. These experimental data provide direct evidence for the multiband electronic structure of the superconducting infinite-layer nickelates, particularly via the effects of hole doping on not only the oxygen but also nickel and rare-earth bands.
| S-EPMC7812792 | biostudies-literature
Project description:The large size and complexity of most fern genomes have hampered efforts to elucidate fundamental aspects of fern biology and land plant evolution through genome-enabled research. Here we present a chromosomal genome assembly and associated methylome, transcriptome and metabolome analyses for the model fern species Ceratopteris richardii. The assembly reveals a history of remarkably dynamic genome evolution including rapid changes in genome content and structure following the most recent whole-genome duplication approximately 60 million years ago. These changes include massive gene loss, rampant tandem duplications and multiple horizontal gene transfers from bacteria, contributing to the diversification of defence-related gene families. The insertion of transposable elements into introns has led to the large size of the Ceratopteris genome and to exceptionally long genes relative to other plants. Gene family analyses indicate that genes directing seed development were co-opted from those controlling the development of fern sporangia, providing insights into seed plant evolution. Our findings and annotated genome assembly extend the utility of Ceratopteris as a model for investigating and teaching plant biology.
| S-EPMC9477723 | biostudies-literature
Project description:In order to identify and characterize novel human gene expression responses to glucocorticoids, we exposed the human lung adenocarcinoma cell line, A549, to the synthetic glucocorticoid dexamethasone for 1, 3, 5, 7, 9, and 11 hrs in duration as well as to a paired vehicle control, ethanol. We assayed gene expression with RNA-seq and clustered gene expression profiles using an infinite Gaussian process mixture model.
2017-10-08 | GSE104714 | GEO
Project description:We present a model that describes the structure in the responses of different brain areas to a set of stimuli in terms of stimulus categories (clusters of stimuli) and functional units (clusters of voxels). We assume that voxels within a unit respond similarly to all stimuli from the same category, and design a nonparametric hierarchical model to capture inter-subject variability among the units. The model explicitly encodes the relationship between brain activations and fMRI time courses. A variational inference algorithm derived based on the model learns categories, units, and a set of unit-category activation probabilities from data. When applied to data from an fMRI study of object recognition, the method finds meaningful and consistent clusterings of stimuli into categories and voxels into units.
| S-EPMC4022600 | biostudies-literature
Project description:MotivationMammalian genomes can contain thousands of enhancers but only a subset are actively driving gene expression in a given cellular context. Integrated genomic datasets can be harnessed to predict active enhancers. One challenge in integration of large genomic datasets is the increasing heterogeneity: continuous, binary and discrete features may all be relevant. Coupled with the typically small numbers of training examples, semi-supervised approaches for heterogeneous data are needed; however, current enhancer prediction methods are not designed to handle heterogeneous data in the semi-supervised paradigm.ResultsWe implemented a Dirichlet Process Heterogeneous Mixture model that infers Gaussian, Bernoulli and Poisson distributions over features. We derived a novel variational inference algorithm to handle semi-supervised learning tasks where certain observations are forced to cluster together. We applied this model to enhancer candidates in mouse heart tissues based on heterogeneous features. We constrained a small number of known active enhancers to appear in the same cluster, and 47 additional regions clustered with them. Many of these are located near heart-specific genes. The model also predicted 1176 active promoters, suggesting that it can discover new enhancers and promoters.Availability and implementationWe created the 'dphmix' Python package: https://pypi.org/project/dphmix/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6748727 | biostudies-literature
Project description:Changes in the physical interaction between cis-regulatory DNA sequences and proteins drive the evolution of gene expression. However, it has proven difficult to accurately quantify evolutionary rates of such binding change or to estimate the relative effects of selection and drift in shaping the binding evolution. Here we examine the genome-wide binding of CTCF in four species of Drosophila separated by between ?2.5 and 25 million years. CTCF is a highly conserved protein known to be associated with insulator sequences in the genomes of human and Drosophila. Although the binding preference for CTCF is highly conserved, we find that CTCF binding itself is highly evolutionarily dynamic and has adaptively evolved. Between species, binding divergence increased linearly with evolutionary distance, and CTCF binding profiles are diverging rapidly at the rate of 2.22% per million years (Myr). At least 89 new CTCF binding sites have originated in the Drosophila melanogaster genome since the most recent common ancestor with Drosophila simulans. Comparing these data to genome sequence data from 37 different strains of Drosophila melanogaster, we detected signatures of selection in both newly gained and evolutionarily conserved binding sites. Newly evolved CTCF binding sites show a significantly stronger signature for positive selection than older sites. Comparative gene expression profiling revealed that expression divergence of genes adjacent to CTCF binding site is significantly associated with the gain and loss of CTCF binding. Further, the birth of new genes is associated with the birth of new CTCF binding sites. Our data indicate that binding of Drosophila CTCF protein has evolved under natural selection, and CTCF binding evolution has shaped both the evolution of gene expression and genome evolution during the birth of new genes.
| S-EPMC3491045 | biostudies-literature
Project description:DpbCasX, also called Cas12e, is an RNA-guided DNA endonuclease isolated from Deltaproteobacteria. In this paper I characterized the CasX-compatible genome editing sites in the reference genomes of yeast (Saccharomyces cerevisiae), flatworms (Caenorhabditis elegans), flies (Drosophila melanogaster), zebrafish (Danio rerio), mouse (Mus musculus), rats (Rattus norvegicus), and humans (Homo sapiens). Across those genomes there were > 27,000 CasX sites per megabase on average. More than 90% of genes in each genome had at least one unique site overlapping an exon, with median unique sites per gene of 6-45. I also annotated sites in the GRCm38 reference and 15 additional mouse strain genomes. The presence of specific guide sequences varied amongst the strains, with CAST/EiJ and PWK/PhJ showing the greatest divergence from the reference strain. The high density of CasX sites and number of exon overlapping sites suggests that CasX has the potential to be used as a common genome editor.
| S-EPMC6598274 | biostudies-literature