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At least 127 records · Page 7Linked to original sources
PubMed2026

Multimodal risk assessment for oral potentially malignant disorders: Integrating patient-centered and specimen-derived data.

BACKGROUND: Oral potentially malignant disorders exhibit heterogeneous malignant transformation risk that clinical approaches fail to adequately predict. Histopathologic dysplasia grading, the reference standard of risk assessment, is associated with poor interobserver reliability and limited prognostic discrimination. It is necessary to define other potential patient- and tissue-associated risk modifiers to improve patient-specific disease prediction. TYPES OF STUDIES REVIEWED: PubMed was queried for patient- and specimen-derived factors as they relate to oral cancer and oral potentially malignant disorders, with preference for systematic review and meta-analysis articles published within the past 5 years. When not available, guidelines from the American Cancer Society, National Cancer Institute, or other national organizations or the most recent best articles were referenced to support the data presented. RESULTS: Within patient-associated factors, validated measures of tobacco and alcohol exposure, clinical lesion characteristics, systemic health factors including metabolic syndrome components, comorbidity risk, and dental health indexes were found. Within specimen-derived data, tissue-based analyses encompassing histopathology and advanced molecular profiling (genomic, epigenomic, transcriptomic, spatial approaches), blood-based germline and somatic mutation analysis, and saliva-based microbiome characterization and inflammatory biomarker assessment were addressed. PRACTICAL IMPLICATIONS: Malignant transformation reflects intersecting patient and specimen risk pathways that affect each patient differently; no single modality captures this complexity. Realizing precision prognostication in oral precancer will require coordinated expansion and standardization of data collection across research groups. This review is intended to guide covariate selection for prospective study design, improve reproducibility, and ultimately enable the development of validated multimodal risk prediction tools for clinical deployment.

Humans↗
PubMed2025

Multi-omics analyses reveal DjTcf4 critical for proper timing of differentiation in planarian regeneration.

The blastema is key to forming complete tissues in regenerating Dugesia japonica (D. japonica). However, the dynamic changes in cellular compositions and transcription landscapes in blastema during regeneration are understudied. Here, through genome reannotation, 3D spatial transcriptome construction, single-cell RNA sequencing (scRNA-seq), and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) analyses of changes in gene expression and chromatin structures, we delineate key transcription factors regulating the developmental trajectories of major cell clusters in the regenerating head. Importantly, we find that the T cell factor 4 (DjTcf4)-positive cells highly accumulate at wound areas, and its gene network is critical for the proper timing of development during regeneration in multiple progenitor cells. Depletion of DjTcf4 and its target genes leads to singular eye and/or dull tail phenotypes and delays regeneration. Taken together, we build multi-omics atlases in D. japonica and reveal the noncanonical function of the DjTcf4 network in developmental pattern formation, laying a foundation for studies of regeneration in D. japonica.

Animals↗
PubMed2004

Isolation and characterization of a novel rice gene encoding a putative insect-inducible protein homologous to wheat Wir1.

A full-length cDNA, designated BpHi008A, was cloned representing a rice (Oryza sativa) mRNA that accumulates after brown planthopper (BPH) Nilapar vata lugens Stål feeding. The cDNA encodes a putative 82 amino acid protein (BpHi008A) exhibiting about 37% amino acid sequence identity to Wir1 family of proteins that are encoded by pathogen-induced transcripts in wheat. Like Wir1 proteins, it consists of a hydrophobic N-terminal half and a hydrophilic C-terminal half relatively rich in glycine and proline. These proteins are predicted to be integrated into the membrane, with the C-terminus being extracytoplastic. Genomic Southern analysis indicated that the BpHi008A gene was present as a single-copy sequence in the rice genome. Temporal and spatial studies showed that BpHi008A were systemically induced in rice when 2nd and 3rd-instars were feeding. The BpHi008A transcripts level was also increased in seedlings damaged by mechanical wounding. These data indicated that BphHi008A was implicated in the response of rice plants to BPH feeding and wounding.

Amino Acid Sequence↗
PubMed1998

Isochore evolution in mammals: a human-like ancestral structure.

Codon usage in mammals is mainly determined by the spatial arrangement of genomic G + C-content, i.e., the isochore structure. Ancestral G + C-content at third codon positions of 27 nuclear protein-coding genes of eutherian mammals was estimated by maximum-likelihood analysis on the basis of a nonhomogeneous DNA substitution model, accounting for variable base compositions among present-day sequences. Data consistently supported a human-like ancestral pattern, i.e., highly variable G + C-content among genes. The mouse genomic structure-more narrow G + C-content distribution-would be a derived state. The circumstances of isochore evolution are discussed with respect to this result. A possible relationship between G + C-content homogenization in murid genomes and high mutation rate is proposed, consistent with the negative selection hypothesis for isochore maintenance in mammals.

Animals↗
PubMed2025

Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning.

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pretrained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Selection, Genetic↗
PubMed2025

Efficient detection and characterization of targets of natural selection using transfer learning.

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pre-trained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Journal Article↗
PubMed1997

ORC-dependent and origin-specific initiation of DNA replication at defined foci in isolated yeast nuclei.

We describe an in vitro replication assay from yeast in which the addition of intact nuclei to an S-phase nuclear extract results in the incorporation of deoxynucleotides into genomic DNA at spatially discrete foci. When BrdUTP is substituted for dTTP, part of the newly synthesized DNA shifts to a density on CsCl gradients, indicative of semiconservative replication. Initiation occurs in an origin-specific manner and can be detected in G1- or S-phase nuclei, but not in G2-phase or mitotic nuclei. The S-phase extract contains a heat- and 6-DMAP-sensitive component necessary to promote replication in G1-phase nuclei. Replication of nuclear DNA is blocked at the restrictive temperature in an orc2-1 mutant, and the inactive Orc2p cannot be complemented in trans by an extract containing wild-type ORC. The initiation of DNA replication in cln-deficient nuclei blocked in G1 indicates that the ORC-dependent prereplication complex is formed before Start. This represents the first nonviral and nonembryonic replication system in which DNA replication initiates in an ORC-dependent and origin-specific manner in vitro.

Cell Cycle↗
PubMed2005

Epigenetic control of replication origins.

Efficient duplication of the eukaryotic genome requires the spatial and temporal coordination of numerous replication origins on each chromosome. Epigenetic factors, like chromatin environment, can have profound effects on origin site selection, utilization frequency, and cell cycle firing time. Precisely how chromatin contributes to origin site selection and timing is not completely understood. Recently, we reported on the cell cycle changes in chromatin structure at the plasmid replication origins of Epstein-Barr Virus (EBV) and Kaposi's Sarcoma-Associated Herpes virus (KSHV). These studies and others suggest that cell cycle changes in histone modification and nucleosome remodeling regulate prereplication factor assembly and initiation of DNA replication at origins. We discuss how these studies of viral origins may provide important insights into epigenetic control of cellular chromosome origins.

Epigenesis, Genetic↗
PubMed2025

Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.

SUMMARY: Uchimata is a toolkit for visualization of 3D structures of genomes. It consists of two packages: a Javascript library facilitating the rendering of 3D models of genomes, and a Python widget for visualization in Jupyter Notebooks. Main features include an expressive way to specify visual encodings, and filtering of 3D genome structures based on genomic semantics and spatial aspects. Uchimata is designed to be highly integratable with biological tooling available in Python. AVAILABILITY AND IMPLEMENTATION: Uchimata is released under the MIT License. The Javascript library is available on NPM, while the widget is available as a Python package hosted on PyPI. The source code for both is available publicly on Github (https://github.com/hms-dbmi/uchimata and https://github.com/hms-dbmi/uchimata-py). The documentation with examples is hosted at https://hms-dbmi.github.io/uchimata/. CONTACT: david_kouril@hms.harvard.edu or nils@hms.harvard.edu.

Journal Article↗
PubMed1991

Temporal analysis and spatial mapping of Lymantria dispar nuclear polyhedrosis virus transcripts and in vitro translation polypeptides.

Genomic expression of the Lymantria dispar multinucleocapsid nuclear polyhedrosis virus (LdMNPV) was studied. Viral specific transcripts expressed in cell culture at various times from 2 through 72 h postinfection were identified and their genomic origins mapped through Northern analysis. Sixty-five distinct transcripts were identified in this analysis. Most viral transcripts were expressed late in infection, and originated from throughout the viral genome. Viral polypeptides expressed in infected 652Y cells were labeled with [35S]methionine and identified by autoradiography after separation by SDS polyacrylamide gel electrophoresis. Viral protein synthesis was found to occur in a sequential manner. Four proteins were identified in the early phase of viral replication (4-12 h p.i.), 24 proteins in the intermediate phase (12-24 h p.i.), and 5 proteins during the late phase (greater than 24 h p.i.). Cytoplasmic RNAs were isolated from LdMNPV infected cells at 16, 24, and 48 h p.i., and used for hybrid selections with overlapping DNA fragments that covered the entire LdMNPV genome. The selected RNAs were translated in vitro, and 61 distinct viral polypeptides were identified and their genomic origins mapped. Temporal and spatial transcription and translation maps of the LdMNPV genome were generated with these data, and the expression pattern of the LdMNPV genome was compared to that of the Autographa californica nuclear polyhedrosis virus.

Animals↗
PubMed2004

Variations in substitution rate in human and mouse genomes.

We present a method to quantify spatial fluctuations of the substitution rate on different length scales throughout genomes of eukaryotes. The fluctuations on large length scales are found to be predominantly a consequence of a coarse-graining effect of fluctuations on shorter length scales. This is verified for both the mouse and the human genome. We also found that the relative standard deviation of fluctuations in substitution rate is about a factor three smaller in mouse than in human. The method allows furthermore to determine time-resolved substitution rate maps of the genomes, where the corresponding autocorrelation functions quantify the velocity of spatial chromosomal reorganization.

Animals↗
PubMed1999

The Embryonics Project: a machine made of artificial cells.

It is possible to trace the origins of biological inspiration in the design of electronic circuits to the very dawn of the field of computer engineering, with the work of John von Neumann in the 1940s. To his brilliance we owe not only the first methodical attempts to define the electronic equivalents of many fundamental biological process, but also the development of the first self-replicating computing machines. Unfortunately, the electronic technology of the time would not allow a physical realization of von Neumann's machines, and it was not until the introduction of new programmable circuits in the 1980s that the field of bio-inspired machines gained new momentum. In this article, we describe the Embryonics (embryonic electronics) Project, an attempt to draw inspiration from the ontogenetic processes that determine the growth of multicellular organisms in the design of new, massively parallel arrays of processors (the artificial cells). Our cells are simple processors, all based on an identical hardware structure and all containing the same program (our artificial genome), but executing different parts of the genome depending on their spatial coordinates within the array. As in living beings, the presence of the genome in every cell allows the introduction of features such as self-replication and self-repair (cicatrization). In addition, the cells are implemented using an array of programmable elements (the artificial molecules), which allows their structure to be adapted to a given application. Through the parallel operation of many of these simple processors, we hope to realize highly complex systems, the equivalent of multicellular organisms in the natural world.

Animals↗
PubMed2026

Life in sediments fosters 'sexual' speciation in the Shewanella baltica complex.

Understanding how intra- and interspecific differentiation arises in natural microbial populations is central to explaining the processes that drive bacterial evolution. Motivated by the co-occurrence of multiple putative genospecies closely related to Shewanella baltica in Baltic Sea sediments, we investigated the genomic structure of this species complex across fine spatial scales. We analyzed 112 genome sequences from strains collected across several sediment cores and depths (0-6 cm) at Vaxön (Stockholm archipelago, Sweden) as well as earlier isolates from this site and allopatric strains from surrounding locations obtained from both sediments and the water column. Using a reverse-ecology population genomics approach, we found unprecedented genomic diversification among sediment-associated strains, which form a species complex resolving into three cohesive evolutionary groups (G1, G2, and G3) with distinct signatures of metabolic specialization including sulfite respiration. While G1 consists predominantly of a single species (S. baltica) with high gene turnover, G2 and G3 comprise an array of divergent putative genospecies and previously reported species consistently recovered from sediments. Patterns of homologous recombination indicate that diversification of the lineages within G2 and G3 is primarily recombination-driven ('sexual') and is associated with specialization in sulfite reduction and utilization of certain carbon sources. The extent of diversity uncovered here far exceeds that reported for S. baltica from other environments, suggesting that a sediment-associated lifestyle promotes the emergence of novel genotypes. These findings expand the known limits of sympatric speciation in prokaryotes beyond subspecific ecotypes, demonstrating that bacterial species can diverge and persist as distinct lineages in the absence of spatial segregation and at microgeographic scales. Furthermore, our results suggest that collective interactions and ecological differentiation can structure sediment-associated bacterial populations strongly enough to drive divergence at the species level.

Journal Article↗
PubMed2026

jsPCA: fast, scalable, and interpretable identification of spatial domains and variable genes across multi-slice and multi-sample spatial transcriptomics data.

MOTIVATION: Spatial transcriptomics technologies record genome-wide measurements of gene expression with high spatial resolution. These technologies generate large and high-dimensional datasets requiring efficient automated methods for their analysis. We introduce joint spatial PCA (jsPCA), a novel, fast, scalable and interpretable method for the automatic identification of spatial domains and variable genes in multi-slice and multi-sample spatial transcriptomics data. RESULTS: jsPCA relies on a simple mathematical formulation of a spatial covariance defined as the product of the gene expression covariance with the spatial autocorrelation. The principal components of this spatial covariance yield a biologically meaningful low-dimensional representation. From this representation, spatial domains are derived by simple clustering and spatially variable genes are identified directly from the principal component coefficients. A joint representation of multiple slices and samples without spatial alignment is obtained by computing common principal components via joint diagonalization. By leveraging data sparsity and non-convex manifold optimization, jsPCA leads to computing time in the order of seconds to minutes, substantially outperforming state-of-the-art approaches. We benchmarked jsPCA against 10 state-of-the-art methods on two reference databases. Our approach demonstrated excellent performance, comparable or better than state-of-the-art methods, while being much faster, interpretable, and scalable to very large datasets.

Journal Article↗
PubMed2003

Expression imbalance map: a new visualization method for detection of mRNA expression imbalance regions.

We describe the development of a new visualization method, called the expression imbalance map (EIM), for detecting mRNA expression imbalance regions, reflecting genomic losses and gains at a much higher resolution than conventional technologies such as comparative genomic hybridization (CGH). Simple spatial mapping of the microarray expression profiles on chromosomal location provides little information about genomic structure, because mRNA expression levels do not completely reflect genomic copy number and some microarray probes would be of low quality. The EIM, which does not employ arbitrary selection of thresholds in conjunction with hypergeometric distribution-based algorithm, has a high tolerance of these complex factors. The EIM could detect regionally underexpressed or overexpressed genes (called, here, an expression imbalance region) in lung cancer specimens from their gene expression data of oligonucleotide microarray. Many known as well as potential loci with frequent genomic losses or gains were detected as expression imbalance regions by the EIM. Therefore, the EIM should provide the user with further insight into genomic structure through mRNA expression.

Allelic Imbalance↗
PubMed2000

Re-modelling of nuclear architecture in quiescent and senescent human fibroblasts.

Spatial organisation of the genome within the nucleus can play a role in maintaining the expressed or silent state of some genes [1]. There are distinct addresses for specific chromosomes, which have different functional characteristics, within the nuclei of dividing populations of human cells [2]. Here, we demonstrate that this level of nuclear architecture is altered in cells that have become either quiescent or senescent. Upon cell cycle exit, a gene-poor human chromosome moves from a location at the nuclear periphery to a more internal site in the nucleus, and changes its associations with nuclear substructures. The chromosome moves back toward the edge of the nucleus at a distinctive time after re-entry into the cell cycle. There is a 2-4 hour period at the beginning of G1 when the spatial organisation of these human chromosomes is established. Lastly, these experiments provide evidence that temporal control of DNA replication can be independent of spatial chromosome organisation. We conclude that the sub-nuclear organisation of chromosomes in quiescent or senescent mammalian somatic cells is fundamentally different from that in proliferating cells and that the spatial organisation of the genome is plastic.

Cell Division↗
PubMed1995

Specificity and functional significance of DNA interaction with the nuclear matrix: new approaches to clarify the old questions.

In this chapter the specificity of chromosomal DNA partitioning into topological loops is discussed. Different experimental approaches used for the analysis of the above problem are critically reviewed. This discussion is followed by presentation of a novel approach for mapping the DNA loop anchorage sites that we have developed. This approach, based on the excision of the whole DNA loops by topoisomerase II-mediated DNA cleavage at matrix attachment sites, seems to constitute a unique tool for the analysis of topological organization of chromosomal DNA in living cells. We also discuss experimental results indicating that the DNA-loop anchorage sites form "weak points" in chromosomes that are preferentially sensitive to cleavage with both endogenous and exogenous nucleases. In connection with this discussion, rationales for the supposition that DNA loops constitute basic units of eukaryotic genome organization and evolution are considered. The chapter concludes by suggesting a new model of spatial organization of eukaryotic genome within the cell nucleus that resolves apparent contradictions between different data on the specificity of DNA interaction with the nuclear matrix.

Animals↗
PubMed2006

Detection of gene copy number changes in CGH microarrays using a spatially correlated mixture model.

MOTIVATION: Comparative genomic hybridization array experiments that investigate gene copy number changes present new challenges for statistical analysis and call for methods that incorporate spatial dependence between sequences along the chromosome. For this purpose, we propose a novel method called CGHmix. It is based on a spatially structured mixture model with three states corresponding to genomic sequences that are either unmodified, deleted or amplified. Inference is performed in a Bayesian framework. From the output, posterior probabilities of belonging to each of the three states are estimated for each genomic sequence and used to classify them. RESULTS: Using simulated data, CGHmix is validated and compared with both a conventional unstructured mixture model and with a recently proposed data mining method. We demonstrate the good performance of CGHmix for classifying copy number changes. In addition, the method provides a good estimate of the false discovery rate. We also present the analysis of a cancer related dataset. SUPPLEMENTARY INFORMATION: http://www.bgx.org.uk/papers.html

Algorithms↗