Coal is a mixture of several chemicals, many of which have mutagenic and carcinogenic effects and are a key contributor to the global burden of mortality and disease. Previous studies suggest that coal is related to telomeric shortening in individuals occupationally exposed, however little is known about the effects of mining and burning coal on the telomeres of individuals living nearby. Therefore, the primary objective of this investigation was to assess the impact of proximity to coal power plants and coal mines on the genomic instability of individuals environmentally exposed, while also exploring potential associations with individual characteristics, oxidative stress, inflammatory responses, and the presence of inorganic elements. This study involved 80 men participants from three cities around a thermoelectric power plant and one city unexposed to coal and byproducts. DNA was extracted from peripheral blood samples obtained from each participant, and the telomeres length (TL) was assessed using quantitative real-time polymerase chain reaction (qPCR) methodology. No significant difference was observed between exposed individuals (6227 ± 2884 bp) when compared to the unexposed group (5638 ± 2452 bp). Nevertheless, TL decrease was associated with age and risk for cardiovascular disease; and longer TL was found to be linked with increased concentrations of silicon and phosphorus in blood samples. No correlations were observed between TL with comet assay (visual score), micronucleus test, oxidative stress, and inflammatory results. Additional research is required to ascertain the potential correlation between these changes and the onset of diseases and premature mortality.

The genus Rhinella corresponds to a group of anurans characterized by numerous taxonomic and systemic challenges, leading to their organization into species complexes. Cytogenetic data for this genus thus far are limited to the diploid number and chromosome morphology, which remain highly conserved among the species. In this study, we analyse the karyotypes of three species of the genus Rhinella (Rhinella granulosa, Rhinella margaritifera, and Rhinella marina) using both classical (conventional staining and C-banding) and molecular (FISH-fluorescence in situ hybridization with 18S rDNA, telomeric sequences, and microsatellite probes) cytogenetic approaches. The aim of this study is to provide data that can reveal variations in the distribution of repetitive sequences that can contribute to understanding karyotypic diversification in these species. The results revealed a conserved karyotype across the species, with 2n = 22 and FN = 44, with metacentric and submetacentric chromosomes. C-banding revealed heterochromatic blocks in the pericentromeric region for all species, with a proximal block on the long arms of pairs 3 and 6 in R. marina and on the short arms of pairs 4 and 6 in R. margaritifera. Additionally, 18S rDNA probes hybridized to pair 5 in R. granulosa, to pair 7 in R. marina, and to pair 10 in R. margaritifera. Telomeric sequence probes displayed signals exclusively in the distal region of the chromosomes, while microsatellite DNA probes showed species-specific patterns. These findings indicate that despite a conserved karyotypical macrostructure, chromosomal differences exist among the species due to the accumulation of repetitive sequences. This variation may be attributed to chromosome rearrangements or differential accumulation of these sequences, highlighting the dynamic role of repetitive sequences in the chromosomal evolution of Rhinella species. Ultimately, this study emphasizes the importance of the role of repetitive DNAs in chromosomal rearrangements to elucidate the evolutionary mechanisms leading to independent diversification in the distinct phylogenetic groups of Rhinella.

UNASSIGNED: Gliomas are the most prevalent primary brain tumors, and patients typically exhibit poor prognoses. Increasing evidence suggests that telomere maintenance mechanisms play a crucial role in glioma development. However, the prognostic value of telomere-related genes in glioma remains uncertain. This study aimed to construct a prognostic model of telomere-related genes and further elucidate the potential association between the two.
UNASSIGNED: We acquired RNA-seq data for low-grade glioma (LGG) and glioblastoma (GBM), along with corresponding clinical information from The Cancer Genome Atlas (TCGA) database, and normal brain tissue data from the Genotype-Tissue Expression (GTEX) database for differential analysis. Telomere-related genes were obtained from TelNet. Initially, we conducted a differential analysis on TCGA and GTEX data to identify differentially expressed telomere-related genes, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on these genes. Subsequently, univariate Cox analysis and log-rank tests were employed to obtain prognosis-related genes. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis were sequentially utilized to construct prognostic models. The model\'s robustness was demonstrated using receiver operating characteristic (ROC) curve analysis, and multivariate Cox regression of risk scores for clinical characteristics and prognostic models were calculated to assess independent prognostic factors. The aforementioned results were validated using the Chinese Glioma Genome Atlas (CGGA) dataset. Finally, the CIBERSORT algorithm analyzed differences in immune cell infiltration levels between high- and low-risk groups, and candidate genes were validated in the Human Protein Atlas (HPA) database.
UNASSIGNED: Differential analysis yielded 496 differentially expressed telomere-related genes. GO and KEGG pathway analyses indicated that these genes were primarily involved in telomere-related biological processes and pathways. Subsequently, a prognostic model comprising ten telomere-related genes was constructed through univariate Cox regression analysis, log-rank test, LASSO regression analysis, and multivariate Cox regression analysis. Patients were stratified into high-risk and low-risk groups based on risk scores. Kaplan-Meier (K-M) survival analysis revealed worse outcomes in the high-risk group compared to the low-risk group, and establishing that this prognostic model was a significant independent prognostic factor for glioma patients. Lastly, immune infiltration analysis was conducted, uncovering notable differences in the proportion of multiple immune cell infiltrations between high- and low-risk groups, and eight candidate genes were verified in the HPA database.
UNASSIGNED: This study successfully constructed a prognostic model of telomere-related genes, which can more accurately predict glioma patient prognosis, offer potential targets and a theoretical basis for glioma treatment, and serve as a reference for immunotherapy through immune infiltration analysis.

UNASSIGNED: Colorectal cancer (CRC) is the third-most prevalent cancer globally. The biological significance of telomeres in CRC carcinogenesis and progression is underscored by accumulating data. Nevertheless, not much is known about how telomere-related genes (TRGs) affect CRC prognosis. Therefore, the aim of this study was to investigate the role of TRGs in CRC prognosis.
UNASSIGNED: We retrospectively obtained the expression profiles and clinical data of CRC patients from public databases. Utilizing least absolute shrinkage and selection operator (LASSO) regression analysis, we created a telomere-related risk model to predict survival outcomes, identifying ten telomere-related differentially expressed genes (TRDEGs). Based on TRDEGs, we stratified patients from The Cancer Genome Atlas (TCGA) into low- and high-risk subsets. Subsequently, we conducted comprehensive analyses, including survival assessment, immune cell infiltration, drug sensitivity, and prediction of molecular interactions using Kaplan-Meier curves, ESTIMATE, CIBERSORT, OncoPredict, and other approaches.
UNASSIGNED: The model showed exceptional predictive accuracy for survival. Significant differences in survival were observed between the two groups of participants grouped according to the model (P<0.001), and this difference was further confirmed in the external validation set (GSE39582) (P=0.004). Additionally, compared to the low-risk group, the high-risk group exhibited significantly advanced tumor node metastasis (TNM) stages, lower proportions of activated CD4+ T cells, effector memory CD4+ T cells, and memory B cells, but increased ratios of M2 macrophages and regulatory T cells (Tregs), elevated tumor immune dysfunction and exclusion (TIDE) scores, and diminished sensitivity to dabrafenib, lapatinib, camptothecin, docetaxel, and telomerase inhibitor IX, reflecting the signature\'s capacity to distinguish clinical pathological characteristics, immune environment, and drug efficacy. Finally, we validated the expression of the ten TRDEGs (ACACB, TPX2, SRPX, PPARGC1A, CD36, MMP3, NAT2, MMP10, HIGD1A, and MMP1) through quantitative real-time polymerase chain reaction (qRT-PCR) and found that compared to normal cells, the expression levels of ACACB, HIGD1A, NAT2, PPARGC1A, and TPX2 in CRC cells were elevated, whereas those of CD36, SRPX, MMP1, MMP3, and MMP10 were reduced.
UNASSIGNED: Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction.

Aging significantly impacts the hematopoietic system, reducing its regenerative capacity and ability to restore homeostasis after stress. Mouse models have been invaluable in studying this process due to their shorter lifespan and the ability to explore genetic, treatment, and environmental influences on aging. However, not all aspects of aging are mirrored between species. This review compares three key aging biomarkers in the hematopoietic systems of mice and humans: myeloid bias, telomere attrition, and epigenetic clocks. Myeloid bias, marked by an increased fraction of myeloid cells and decreased lymphoid cells, is a significant aging marker in mice but is scarcely observed in humans after childhood. Conversely, telomere length is a robust aging biomarker in humans, whereas mice exhibit significantly different telomere dynamics, making telomere length less reliable in the murine system. Epigenetic clocks, based on DNA methylation changes at specific genomic regions, provide precise estimates of chronological age in both mice and humans. Notably, age-associated regions in mice and humans occur at homologous genomic locations. Epigenetic clocks, depending on the epigenetic signatures used, also capture aspects of biological aging, offering powerful tools to assess genetic and environmental impacts on aging. Taken together, not all blood aging biomarkers are transferable between mice and humans. When using murine models to extrapolate human aging, it may be advantageous to focus on aging phenomena observed in both species. In conclusion, while mouse models offer significant insights, selecting appropriate biomarkers is crucial for translating findings to human aging.

Eleocharis dulcis (Burm. f.) Trin. ex Hensch., commonly known as Chinese water chestnut, is a traditional aquatic vegetable in China, and now is widely cultivated throughout the world because of its high nutritional value and unique tastes. Here, we report the assembly of a 493.24 Mb telomere-to-telomere (T2T) genome of E. dulcis accomplished by integrating ONT ultra-long reads, PacBio long reads and Hi-C data. The reference genome was anchored onto 111 gap-free chromosomes, containing 48.31% repeat elements and 33,493 predicted protein-coding genes. Whole genome duplication (WGD) and inter-genomic synteny analyses indicated that chromosome breakage and genome duplication in E. dulcis possibly occurred multiple times during genome evolution after its divergence from a common ancestor with Rhynchospora breviuscula at ca. 35.6 Mya. A comparative time-course transcriptome analysis of corm development revealed different patterns of gene expression between cultivated and wild accessions with the highest number of differentially expressed genes (DEGs, 15,870) at the middle swelling stage and some of the DEGs were significantly enriched for starch metabolic process.

During meiosis, transient associations between the nuclear envelope and telomeres transmit nuclear movements to chromosomes, enabling their pairing and recombination. Recent advances in the field of quantitative cell biology allow a large volume of information about the kinetics of these chromosome movements to be extracted and analyzed with the aim of identifying biologically relevant movement patterns. To this end, we have developed ChroMo, a freely available application for the unsupervised study of chromosome movements in fission yeast meiosis. ChroMo contains a set of time series algorithms to identify chromosome movement motifs that are not easily observable by direct human visualization and to establish causal relationships between phenotypes. In this chapter, we present a detailed protocol for the processing of raw live imaging data from fission yeast and its subsequent analysis in ChroMo.

Telomere-led rapid chromosome movements (RPMs) are a conserved characteristic of chromosome dynamics in meiosis. RPMs have been suggested to influence critical meiotic functions such as DNA repair and the association of the homologous chromosomes. Here, we describe a method using 3D time-lapse fluorescence imaging to monitor RPMs in Hoechst-stained mouse seminiferous tubules explants. We supplement visualization with customized quantitative motion analysis and in silico simulation. The ability to carry out live imaging, combined with quantitative image analysis, offers a sensitive tool to investigate the regulation of RPMs, chromosome reorganizations that precede dynamic mid-prophase events, and their contribution to faithful transmission of genetic information.

Understanding the complex dynamics of telomere biology is important in the strong link between aging and cancer. Telomeres, the protective caps at the end of chromosomes, are central players in this connection. While their gradual shortening due to replication limits tumors expansion by triggering DNA repair mechanisms, it also promotes oncogenic changes within chromosomes, thus sustaining tumorigenesis. The enzyme telomerase, responsible for maintaining telomere length, emerges as a central player in this context. Its expression in cancer cells facilitates the preservation of telomeres, allowing them to circumvent the growth-limiting effects of short telomeres. Interestingly, the influence of telomerase extends beyond telomere maintenance, as evidenced by its involvement in promoting cell growth through alternative pathways. In this context, inflammation accelerates telomere shortening, resulting in telomere dysfunction, while telomere elements also play a role in modulating the inflammatory response. The recognition of this interplay has promoted the development of novel therapeutic approaches centered around telomerase inhibition. This review provides a comprehensive overview of the field, emphasizing recent progress in knowledge and the implications in understanding of cancer biology.

Werner syndrome (WS) is an autosomal recessive disease caused by loss of function of WRN. WS is a segmental progeroid disease and shows early onset or increased frequency of many characteristics of normal aging. WRN possesses helicase, annealing, strand exchange, and exonuclease activities and acts on a variety of DNA substrates, even complex replication and recombination intermediates. Here, we review the genetics, biochemistry, and probably physiological functions of the WRN protein. Although its precise role is unclear, evidence suggests WRN plays a role in pathways that respond to replication stress and maintain genome stability particularly in telomeric regions.