Analysis of population heterogeneity in CHO cells by genome-wide DNA methylation analysis and by multi-modal single-cell sequencing
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ABSTRACT:
ORGANISM(S): Cricetulus griseus
PROVIDER: GSE273685 | GEO | 2024/11/04
REPOSITORIES: GEO
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Project description:CHO cells are major hosts for the industrial production of therapeutic proteins and their production stability is of considerable economic significance. It is widely known that CHO cells can rapidly acquire genetic alterations, which affects their genetic homogeneity over time. However, the role of non-genetic mechanisms, including epigenetic mechanisms such as DNA methylation, remains poorly understood. We have now used whole-genome bisulfite sequencing to establish single-base methylation maps of eight independent CHO cell lines. Our results identify CpG islands and low-methylated regions as conserved elements with dynamic DNA methylation. Interestingly, methylation patterns were found to cluster clearly along the three main branches of CHO evolution, with no directional changes over short culture periods. Furthermore, multi-ome single-cell sequencing of 9,833 nuclei from three independent cultures revealed dynamic subpopulation structures characterized by robust expression differences in pathways related to protein production. Our findings thus provide novel insights into the epigenetic heterogeneity of CHO cells and support the development of epigenetic biomarkers that trace the emergence of subpopulations in CHO cultures.
2024-11-04 | GSE273851 | GEO
Project description:CHO cells are major hosts for the industrial production of therapeutic proteins and their production stability is of considerable economic significance. It is widely known that CHO cells can rapidly acquire genetic alterations, which affects their genetic homogeneity over time. However, the role of non-genetic mechanisms, including epigenetic mechanisms such as DNA methylation, remains poorly understood. We have now used whole-genome bisulfite sequencing to establish single-base methylation maps of eight independent CHO cell lines. Our results identify CpG islands and low-methylated regions as conserved elements with dynamic DNA methylation. Interestingly, methylation patterns were found to cluster clearly along the three main branches of CHO evolution, with no directional changes over short culture periods. Furthermore, multi-ome single-cell sequencing of 9,833 nuclei from three independent cultures revealed dynamic subpopulation structures characterized by robust expression differences in pathways related to protein production. Our findings thus provide novel insights into the epigenetic heterogeneity of CHO cells and support the development of epigenetic biomarkers that trace the emergence of subpopulations in CHO cultures.
2024-11-04 | GSE272869 | GEO
Project description:CHO cells are major hosts for the industrial production of therapeutic proteins and their production stability is of considerable economic significance. It is widely known that CHO cells can rapidly acquire genetic alterations, which affects their genetic homogeneity over time. However, the role of non-genetic mechanisms, including epigenetic mechanisms such as DNA methylation, remains poorly understood. We have now used whole-genome bisulfite sequencing to establish single-base methylation maps of eight independent CHO cell lines. Our results identify CpG islands and low-methylated regions as conserved elements with dynamic DNA methylation. Interestingly, methylation patterns were found to cluster clearly along the three main branches of CHO evolution, with no directional changes over short culture periods. Furthermore, multi-ome single-cell sequencing of 9,833 nuclei from three independent cultures revealed dynamic subpopulation structures characterized by robust expression differences in pathways related to protein production. Our findings thus provide novel insights into the epigenetic heterogeneity of CHO cells and support the development of epigenetic biomarkers that trace the emergence of subpopulations in CHO cultures.
2024-11-04 | GSE273684 | GEO
Project description:Analysis of population heterogeneity in CHO cells by genome-wide DNA methylation analysis and by multi-modal single-cell sequencing
| PRJNA1142613 | ENA
Project description:Analysis of population heterogeneity in CHO cells by genome-wide DNA methylation analysis and by multi-modal single-cell sequencing [WGBS]
| PRJNA1143486 | ENA
Project description:Analysis of population heterogeneity in CHO cells by genome-wide DNA methylation analysis and by multi-modal single-cell sequencing [multiome]
| PRJNA1139152 | ENA
Project description:Analysis of population heterogeneity in CHO cells by genome-wide DNA methylation analysis and by multi-modal single-cell sequencing [time series]
| PRJNA1142615 | ENA
Project description:BackgroundIn a heterogeneous population of cells, individual cells can behave differently and respond variably to the environment. This cellular diversity can be assessed by measuring DNA methylation patterns. The loci with variable methylation patterns are informative of cellular heterogeneity and may serve as biomarkers of diseases and developmental progression. Cell-to-cell methylation heterogeneity can be evaluated through single-cell methylomes or computational techniques for pooled cells. However, the feasibility and performance of these approaches to precisely estimate methylation heterogeneity require further assessment.ResultsHere, we proposed model-based methods adopted from a mathematical framework originally from biodiversity, to estimate genome-wide DNA methylation heterogeneity. We evaluated the performance of our models and the existing methods with feature comparison, and tested on both synthetic datasets and real data. Overall, our methods have demonstrated advantages over others because of their better correlation with the actual heterogeneity. We also demonstrated that methylation heterogeneity offers an additional layer of biological information distinct from the conventional methylation level. In the case studies, we showed that distinct profiles of methylation heterogeneity in CG and non-CG methylation can predict the regulatory roles between genomic elements in Arabidopsis. This opens up a new direction for plant epigenomics. Finally, we demonstrated that our score might be able to identify loci in human cancer samples as putative biomarkers for early cancer detection.ConclusionsWe adopted the mathematical framework from biodiversity into three model-based methods for analyzing genome-wide DNA methylation heterogeneity to monitor cellular heterogeneity. Our methods, namely MeH, have been implemented, evaluated with existing methods, and are open to the research community.
| S-EPMC10634068 | biostudies-literature
Project description:Smoking is a risk factor for many human diseases. DNA methylation has been related to smoking, but genome-wide methylation data for smoking in Chinese populations is limited.We aimed to investigate epigenome-wide methylation in relation to smoking in a Chinese population.We measured the methylation levels at > 485,000 CpG sites (CpGs) in DNA from leukocytes using a methylation array and conducted a genome-wide meta-analysis of DNA methylation and smoking in a total of 596 Chinese participants. We further evaluated the associations of smoking-related CpGs with internal polycyclic aromatic hydrocarbon (PAH) biomarkers and their correlations with the expression of corresponding genes.We identified 318 CpGs whose methylation levels were associated with smoking at a genome-wide significance level (false discovery rate < 0.05), among which 161 CpGs annotated to 123 genes were not associated with smoking in recent studies of Europeans and African Americans. Of these smoking-related CpGs, methylation levels at 80 CpGs showed significant correlations with the expression of corresponding genes (including RUNX3, IL6R, PTAFR, ANKRD11, CEP135 and CDH23), and methylation at 15 CpGs was significantly associated with urinary 2-hydroxynaphthalene, the most representative internal monohydroxy-PAH biomarker for smoking.We identified DNA methylation markers associated with smoking in a Chinese population, including some markers that were also correlated with gene expression. Exposure to naphthalene, a byproduct of tobacco smoke, may contribute to smoking-related methylation.Zhu X, Li J, Deng S, Yu K, Liu X, Deng Q, Sun H, Zhang X, He M, Guo H, Chen W, Yuan J, Zhang B, Kuang D, He X, Bai Y, Han X, Liu B, Li X, Yang L, Jiang H, Zhang Y, Hu J, Cheng L, Luo X, Mei W, Zhou Z, Sun S, Zhang L, Liu C, Guo Y, Zhang Z, Hu FB, Liang L, Wu T. 2016. Genome-wide analysis of DNA methylation and cigarette smoking in Chinese. Environ Health Perspect 124:966-973;?http://dx.doi.org/10.1289/ehp.1509834.
| S-EPMC4937856 | biostudies-other
Project description:Understanding how regulatory DNA elements shape gene expression across individual cells is a fundamental challenge in genomics. Joint RNA-seq and epigenomic profiling provides opportunities to build unifying models of gene regulation capturing sequence determinants across steps of gene expression. However, current models, developed primarily for bulk omics data, fail to capture the cellular heterogeneity and dynamic processes revealed by single-cell multi-modal technologies. Here, we introduce scooby, the first model to predict scRNA-seq coverage and scATAC-seq insertion profiles along the genome from sequence at single-cell resolution. For this, we leverage the pre-trained multi-omics profile predictor Borzoi as a foundation model, equip it with a cell-specific decoder, and fine-tune its sequence embeddings. Specifically, we condition the decoder on the cell position in a precomputed single-cell embedding resulting in strong generalization capability. Applied to a hematopoiesis dataset, scooby recapitulates cell-specific expression levels of held-out genes and cells, and identifies regulators and their putative target genes through in silico motif deletion. Moreover, accurate variant effect prediction with scooby allows for breaking down bulk eQTL effects into single-cell effects and delineating their impact on chromatin accessibility and gene expression. We anticipate scooby to aid unraveling the complexities of gene regulation at the resolution of individual cells.
| S-EPMC11429888 | biostudies-literature