Chromatin dynamics of plant telomeres and ribosomal genes

Telomeres i.e., termini of the eukaryotic chromosomes protect chromosomes during DNA replication. Shortening of telomeres, either due to stress or ageing is related to replicative cellular senescence. There is little information on the effect of biotechnological methods, such as tissue culture via somatic embryogenesis (SE) or cryopreservation on plant telomeres, even if these techniques are widely applied. The aim of the present study was to examine telomeres of Norway spruce (Picea abies (L.) Karst.) during SE initiation, proliferation, embryo maturation, and cryopreservation to reveal potential ageing or stress-related effects that could explain variation observed at SE process. Altogether, 33 genotypes from 25 families were studied. SE initiation containing several stress factors cause telomere shortening in Norway spruce. Following initiation, the telomere length of the embryogenic tissues (ETs) and embryos produced remains unchanged up to one year of culture, with remarkable genotypic variation. Being prolonged in vitro culture can, however, shorten the telomeres and should be avoided. This is achieved by successful cryopreservation treatment preserving telomere length. Somatic embryo production capacity of the ETs was observed to vary a lot not only among the genotypes, but also from one timepoint to another. No connection between embryo production and telomere length was found, so this variation remains unexplained.

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Cell Division: Chromatin Dynamics Shape Insect Holocentromeres

Current Biology ◽

10.1016/j.cub.2020.10.049 ◽

2021 ◽

Vol 31 (1) ◽

pp. R34-R37

Author(s):

Reto Gassmann

Keyword(s):

Cell Division ◽

Chromatin Dynamics

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Comparative study on the physical mapping of ribosomal genes and repetitive sequences in Friesella schrottkyi (Friese, 1900) (Hymenoptera: Apidae, Meliponini)

Zoologischer Anzeiger ◽

10.1016/j.jcz.2021.04.006 ◽

2021 ◽

Author(s):

Arthur Mayrink Elizeu ◽

Natalia Martins Travenzoli ◽

Riudo de Paiva Ferreira ◽

Denilce Meneses Lopes ◽

Mara Garcia Tavares

Keyword(s):

Comparative Study ◽

Physical Mapping ◽

Repetitive Sequences ◽

Ribosomal Genes ◽

Friesella Schrottkyi

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Histone Modifying Enzymes in Gynaecological Cancers

Cancers ◽

10.3390/cancers13040816 ◽

2021 ◽

Vol 13 (4) ◽

pp. 816

Author(s):

Priya Ramarao-Milne ◽

Olga Kondrashova ◽

Sinead Barry ◽

John D. Hooper ◽

Jason S. Lee ◽

...

Keyword(s):

Genome Instability ◽

Cpg Islands ◽

Gene Promoter ◽

Driver Mutations ◽

Promoter Regions ◽

Post Translational Modifications ◽

Chromatin Dynamics ◽

Cancer Types ◽

Histone Modifying Enzymes

Genetic and epigenetic factors contribute to the development of cancer. Epigenetic dysregulation is common in gynaecological cancers and includes altered methylation at CpG islands in gene promoter regions, global demethylation that leads to genome instability and histone modifications. Histones are a major determinant of chromosomal conformation and stability, and unlike DNA methylation, which is generally associated with gene silencing, are amenable to post-translational modifications that induce facultative chromatin regions, or condensed transcriptionally silent regions that decondense resulting in global alteration of gene expression. In comparison, other components, crucial to the manipulation of chromatin dynamics, such as histone modifying enzymes, are not as well-studied. Inhibitors targeting DNA modifying enzymes, particularly histone modifying enzymes represent a potential cancer treatment. Due to the ability of epigenetic therapies to target multiple pathways simultaneously, tumours with complex mutational landscapes affected by multiple driver mutations may be most amenable to this type of inhibitor. Interrogation of the actionable landscape of different gynaecological cancer types has revealed that some patients have biomarkers which indicate potential sensitivity to epigenetic inhibitors. In this review we describe the role of epigenetics in gynaecological cancers and highlight how it may exploited for treatment.

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Fast detection of differential chromatin domains with SCIDDO

Bioinformatics ◽

10.1093/bioinformatics/btaa960 ◽

2020 ◽

Author(s):

Peter Ebert ◽

Marcel H Schulz

Keyword(s):

Differentially Expressed Genes ◽

Differentially Expressed ◽

Chromatin State ◽

Supplementary Information ◽

Differential Analysis ◽

Chromatin Domains ◽

Chromatin Dynamics ◽

Histone Marks ◽

Chromatin Immunoprecipitation Sequencing ◽

Downstream Analysis

Abstract Motivation The generation of genome-wide maps of histone modifications using chromatin immunoprecipitation sequencing (ChIP-seq) is a standard approach to dissect the complexity of the epigenome. Interpretation and differential analysis of histone datasets remains challenging due to regulatory meaningful co-occurrences of histone marks and their difference in genomic spread. To ease interpretation, chromatin state segmentation maps are a commonly employed abstraction combining individual histone marks. We developed the tool SCIDDO as a fast, flexible, and statistically sound method for the differential analysis of chromatin state segmentation maps. Results We demonstrate the utility of SCIDDO in a comparative analysis that identifies differential chromatin domains (DCD) in various regulatory contexts and with only moderate computational resources. We show that the identified DCDs correlate well with observed changes in gene expression and can recover a substantial number of differentially expressed genes. We showcase SCIDDO’s ability to directly interrogate chromatin dynamics such as enhancer switches in downstream analysis, which simplifies exploring specific questions about regulatory changes in chromatin. By comparing SCIDDO to competing methods, we provide evidence that SCIDDO’s performance in identifying differentially expressed genes (DEG) via differential chromatin marking is more stable across a range of cell-type comparisons and parameter cut-offs. Availability The SCIDDO source code is openly available under github.com/ptrebert/sciddo Supplementary information Supplementary data are available at Bioinformatics online.

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