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PubMed2025

Chromatin Landscape Is Associated With Sex-Biased Expression and Drosophila-Like Dosage Compensation of the Z Chromosome in Artemia franciscana.

The males and females of the brine shrimp Artemia franciscana are highly dimorphic, and this dimorphism is associated with substantial sex-biased gene expression in heads and gonads. How these sex-specific patterns of expression are regulated at the molecular level is unknown. A. franciscana also has differentiated ZW sex chromosomes, with complete dosage compensation, but the molecular mechanism through which compensation is achieved is unknown. Here, we conducted CUT&TAG assays targeting 7 post-translational histone modifications (H3K27me3, H3K9me2, H3K9me3, H3K36me3, H3K27ac, H3K4me3, and H4K16ac) in heads and gonads of A. franciscana, allowing us to divide the genome into 12 chromatin states. We further defined functional chromatin signatures for all genes, which were correlated with transcript level abundances. Differences in the occupancy of the profiled epigenetic marks between sexes were associated with differential gene expression between males and females. Finally, we found a significant enrichment of the permissive H4K16ac histone mark in the Z-specific region in both tissues of females but not males, supporting the role of this histone mark in mediating dosage compensation of the Z chromosome.

Animals↗
PubMed1984

Cross-linked proteins associated with a specific mRNA in the cytoplasm of HeLa cells.

Cytoplasmic messenger RNAs of eukaryotic cells are distributed between polysomal and post-polysomal fractions (free) as protein-bound complexes. These studies were designed to determine whether a specific mRNA isolated from different subcellular compartments is complexed with the same family of polypeptides. As a first approach we have examined the proteins associated with mRNA which codes for histone H4. To perform these experiments HeLa cells were exposed to ultraviolet light to cross-link in vivo polypeptides which are closely associated with nucleic acid. To identify the polypeptides associated with mRNA specific for histones a genomic probe for histone H4 mRNA was immobilized on epoxy-cellulose. By hybrid selection specific mRNPs containing histone mRNA were isolated. Our results reveal the existence of a number of polypeptides associated with both polysomal and post-polysomal histone mRNAs. In polysomal histone mRNA two polypeptides of Mr = 49 000 and 52 500 were the major components. In contrast polypeptides of Mr = 43 000 and 57 000 were the major polypeptide components of post-polysomal (or free) histone mRNA. Furthermore, these results also suggest that the polypeptides associated with either polysomal or free H4 histone mRNA represent a subset of proteins found in poly(A)-free fractions or poly(A)-rich mRNA fractions.

Centrifugation, Density Gradient↗
PubMed1967

Cell synchrony.

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Cell Division↗
PubMed2025

Post-translational modifications of the nucleoid protein H-NS: sites, mechanisms, and regulatory cues.

Histone-like nucleoid structuring protein H-NS plays a pivotal role in orchestrating bacterial chromatin and regulating horizontal gene transfer (HGT) elements. In response to environmental signals, H-NS undergoes dynamic post-translational modifications (PTMs) that resemble the epigenetic codes of eukaryotic histones. This review explores how environmental cues regulate PTMs at specific sites within distinct domains of H-NS, thereby modulating its oligomerization and DNA-binding capabilities to reprogram bacterial responses. Notably, HGT elements commonly encode counter-silencing factors, including PTM-modifying enzymes, that counteract H-NS repression. We propose that combinatorial PTM patterns on H-NS form the bacterial histone-like epigenetic code, regulating the expression of HGT elements. Collectively, these interactions establish a sophisticated network of silencing and counter-silencing mechanisms that drive bacterial genome evolution.

Protein Processing, Post-Translational↗
PubMed2025

Prediction of gene expression using histone modification patterns extracted by Particle Swarm Optimization.

MOTIVATION: Histone modifications play an important role in transcription regulation. Although the general importance of some histone modifications for transcription regulation has been previously established, the relevance of others and their interaction is subject to ongoing research. By training Machine Learning models to predict a gene's expression and explaining their decision making process, we can get hints on how histone modifications affect transcription. In previous studies, trained models were either hardly explainable or the models were trained solely on the abundance of histone modifications. Based on other studies, which used histone modification patterns, rather than their abundance, to identify potential regulatory elements, we hypothesize the histone modification pattern in a gene's promoter to be more predictive for gene expression. We used an optimization algorithm to extract predictive histone modification profiles. RESULTS: Our algorithm called PatternChrome achieved an average area under curve (AUC) score of 0.9029 over 56 samples for binary classification, outperforming all previous algorithms for the same task. We explained the models decisions to deduce the effect of specific features, certain histone modifications or promoter positions on transcription regulation. Although the predictive histone modification patterns were extracted for each sample separately, they can be used to predict gene expression in other samples, implying that the created patterns are largely generalizable. Interestingly, the impact of histone modifications on gene regulation appears predominantly indifferent to cellular specificity. Through explanation of the classifier's decisions, we substantiate established literature knowledge while concurrently revealing novel insights into the intricate landscape of transcriptional regulation via histone modification. AVAILABILITY AND IMPLEMENTATION: The code for the PatternChrome algorithm, the scripts for the analyses and the required data can be found at (https://gitlab.gwdg.de/MedBioinf/generegulation/patternchrome).

Humans↗