1
|
Čugalj Kern B, Kovač J, Šket R, Tesovnik T, Jenko Bizjan B, Galhardo J, Battelino T, Bratina N, Dovč K. Exploring early DNA methylation alterations in type 1 diabetes: implications of glycemic control. Front Endocrinol (Lausanne) 2024; 15:1416433. [PMID: 38904047 PMCID: PMC11188314 DOI: 10.3389/fendo.2024.1416433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 05/16/2024] [Indexed: 06/22/2024] Open
Abstract
Background Prolonged hyperglycemia causes diabetes-related micro- and macrovascular complications, which combined represent a significant burden for individuals living with diabetes. The growing scope of evidence indicates that hyperglycemia affects the development of vascular complications through DNA methylation. Methods A genome-wide differential DNA methylation analysis was performed on pooled peripheral blood DNA samples from individuals with type 1 diabetes (T1D) with direct DNA sequencing. Strict selection criteria were used to ensure two age- and sex-matched groups with no clinical signs of chronic complications according to persistent mean glycated hemoglobin (HbA1c) values over 5 years: HbA1c<7% (N=10) and HbA1c>8% (N=10). Results Between the two groups, 8385 differentially methylated CpG sites, annotated to 1802 genes, were identified. Genes annotated to hypomethylated CpG sites were enriched in 48 signaling pathways. Further analysis of key CpG sites revealed four specific regions, two of which were hypermethylated and two hypomethylated, associated with long non-coding RNA and processed pseudogenes. Conclusions Prolonged hyperglycemia in individuals with T1D, who have no clinical manifestation of diabetes-related complications, is associated with multiple differentially methylated CpG sites in crucial genes and pathways known to be linked to chronic complications in T1D.
Collapse
Affiliation(s)
- Barbara Čugalj Kern
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Jernej Kovač
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Robert Šket
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tine Tesovnik
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Barbara Jenko Bizjan
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Julia Galhardo
- Paediatric Endocrinology and Diabetes Unit, Hospital de Dona Estefânia - Central Lisbon University Hospital Center, Lisbon, Portugal
- Lisbon Academic and Clinical Center, NOVA Medical School, Lisbon, Portugal
| | - Tadej Battelino
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Nataša Bratina
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Klemen Dovč
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| |
Collapse
|
2
|
Lande K, Williams AE. PCBS: an R package for fast and accurate analysis of bisulfite sequencing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595620. [PMID: 38854090 PMCID: PMC11160565 DOI: 10.1101/2024.05.23.595620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Motivation Whole-genome bisulfite sequencing is a powerful tool for analyzing chromatin methylation genome-wide, but analysis of whole-genome bisulfite data is hampered by slow, inaccurate, and inflexible pipelines. Results We developed PCBS, a computationally efficient R package for Whole Genome Bisulfite Sequencing analysis that demonstrates remarkable accuracy and flexibility compared to current tools. PCBS identifies differentially methylated loci and differentially methylated regions and offers novel functionality that allows for more targeted methylation analyses. PCBS uses minimal computational resources; a complete pipeline in mouse can run on a local RStudio instance in a matter of minutes. Availability and Implementation PCBS is an R package available under a GNU GPLv3 license at: https://github.com/katlande/PCBS and from CRAN: https://CRAN.R-project.org/package=PCBS. Instructions for use are available at: https://katlande.github.io/PCBS/.
Collapse
Affiliation(s)
- Kathryn Lande
- The Razavi Newman Integrative Genomics and Bioinformatics Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, 92037, United States
| | - April E. Williams
- The Razavi Newman Integrative Genomics and Bioinformatics Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, 92037, United States
| |
Collapse
|
3
|
Li SJ, Gao X, Wang ZH, Li J, Zeng LT, Dang YM, Ma YQ, Zhang LQ, Wang QY, Zhang YM, Liu HL, Qi RM, Cai JP. Cell-free DNA methylation patterns in aging and their association with inflamm-aging. Epigenomics 2024:1-17. [PMID: 38869474 DOI: 10.1080/17501911.2024.2340958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 04/05/2024] [Indexed: 06/14/2024] Open
Abstract
Aim: Liquid biopsies analyzing cell-free DNA (cfDNA) methylation in plasma offer a noninvasive diagnostic for diseases, with the potential of aging biomarkers underexplored. Methods: Utilizing enzymatic methyl-seq (EM-seq), this study assessed cfDNA methylation patterns in aging with blood from 35 healthy individuals. Results: It found aging signatures, including higher cfDNA levels and variations in fragment sizes, plus approximately 2000 age-related differentially methylated CpG sites. A biological age predictive model based on 48 CpG sites showed a strong correlation with chronological age, verified by two datasets. Age-specific epigenetic shifts linked to inflammation were revealed through differentially methylated regions profiling and Olink proteomics. Conclusion: These findings suggest cfDNA methylation as a potential aging biomarker and might exacerbate immunoinflammatory reactivity in older individuals.
Collapse
Affiliation(s)
- Si-Jia Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
- Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, 100730, PR China
| | - Xin Gao
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
- Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, 100730, PR China
| | - Zi-Hui Wang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
- Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, 100730, PR China
| | - Jin Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Lv-Tao Zeng
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Ya-Min Dang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
- Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, 100730, PR China
| | - Ya-Qing Ma
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Li-Qun Zhang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Qing-Yu Wang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Ying-Min Zhang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Hong-Lei Liu
- School of Biomedical Engineering, Capital Medical University, 100730, PR China
| | - Ruo-Mei Qi
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Jian-Ping Cai
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
- Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, 100730, PR China
| |
Collapse
|
4
|
Ferro dos Santos MR, Giuili E, De Koker A, Everaert C, De Preter K. Computational deconvolution of DNA methylation data from mixed DNA samples. Brief Bioinform 2024; 25:bbae234. [PMID: 38762790 PMCID: PMC11102637 DOI: 10.1093/bib/bbae234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/30/2024] [Accepted: 04/30/2024] [Indexed: 05/20/2024] Open
Abstract
In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.
Collapse
Affiliation(s)
- Maísa R Ferro dos Santos
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Edoardo Giuili
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Andries De Koker
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Celine Everaert
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Katleen De Preter
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| |
Collapse
|
5
|
Wang J, Zhang C, Zhang L, Yao HJ, Liu X, Shi Y, Zhao J, Bo X, Chen H, Li L. Comparative study on genomic and epigenomic profiles of retinoblastoma or tuberous sclerosis complex via nanopore sequencing and a joint screening framework. Cancer Gene Ther 2024; 31:439-453. [PMID: 38146007 DOI: 10.1038/s41417-023-00714-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 12/27/2023]
Abstract
Recurrence and extraocular metastasis in advanced intraocular retinoblastoma (RB) are still major obstacles for successful treatment of Chinese children. Tuberous sclerosis complex (TSC) is a very rare, multisystemic genetic disorder characterized by hamartomatous growth. In this study, we aimed to compare genomic and epigenomic profiles with human RB or TSC using recently developed nanopore sequencing, and to identify disease-associated variations or genes. Peripheral blood samples were collected from either RB or RB/TSC patients plus their normal siblings, followed by nanopore sequencing and identification of disease-specific structural variations (SVs) and differentially methylated regions (DMRs) by a systematic biology strategy named as multiomics-based joint screening framework. In total, 316 RB- and 1295 TSC-unique SVs were identified, as well as 1072 RB- and 1114 TSC-associated DMRs, respectively. We eventually identified 6 key genes for RB for further functional validation. Knockdown of CDK19 with specific siRNAs significantly inhibited Y79 cellular proliferation and increased sensitivity to carboplatin, whereas downregulation of AHNAK2 promoted the cell growth as well as drug resistance. Those two genes might serve as potential diagnostic markers or therapeutic targets of RB. The systematic biology strategy combined with functional validation might be an effective approach for rare pediatric malignances with limited samples and challenging collection process.
Collapse
Affiliation(s)
- Junting Wang
- State Key Laboratory of Respiratory Health and Multimorbidity, NHC Key Laboratory of Biotechnology for Microbial Drugs, Department of Oncology, Institute of Medicinal Biotechnology (IMB), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), NO.1 Tiantan Xili, Beijing, 100050, China
- Institute of Health Service and Transfusion Medicine, Beijing, 100850, P.R. China
| | - Chengyue Zhang
- Department of Ophthalmology, Beijing Children's Hospital affiliated with Capital Medical University, National Center for Children's Health, Beijing, 100045, China.
| | - Li Zhang
- State Key Laboratory of Respiratory Health and Multimorbidity, NHC Key Laboratory of Biotechnology for Microbial Drugs, Department of Oncology, Institute of Medicinal Biotechnology (IMB), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), NO.1 Tiantan Xili, Beijing, 100050, China
| | - Hong-Juan Yao
- State Key Laboratory of Respiratory Health and Multimorbidity, NHC Key Laboratory of Biotechnology for Microbial Drugs, Department of Oncology, Institute of Medicinal Biotechnology (IMB), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), NO.1 Tiantan Xili, Beijing, 100050, China
| | - Xiaohong Liu
- Guang'anmen Hospital, Chinese Academy of Chinese Medical Sciences, No.5 BeiXianGe St., Beijing, 100053, China
| | - Yuchen Shi
- Dongzhimen Hospital, Beijing University of Chinese Medicine, No.5 Haiyuncang, Beijing, 100700, China
| | - Junyang Zhao
- Department of Ophthalmology, Beijing Children's Hospital affiliated with Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Xiaochen Bo
- Institute of Health Service and Transfusion Medicine, Beijing, 100850, P.R. China
| | - Hebing Chen
- Institute of Health Service and Transfusion Medicine, Beijing, 100850, P.R. China.
| | - Liang Li
- State Key Laboratory of Respiratory Health and Multimorbidity, NHC Key Laboratory of Biotechnology for Microbial Drugs, Department of Oncology, Institute of Medicinal Biotechnology (IMB), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), NO.1 Tiantan Xili, Beijing, 100050, China.
| |
Collapse
|
6
|
Hossain MN, Gao Y, Hatfield MJ, de Avila JM, McClure MC, Du M. Cold exposure impacts DNA methylation patterns in cattle sperm. Front Genet 2024; 15:1346150. [PMID: 38444759 PMCID: PMC10912962 DOI: 10.3389/fgene.2024.1346150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 01/23/2024] [Indexed: 03/07/2024] Open
Abstract
DNA methylation is influenced by various exogenous factors such as nutrition, temperature, toxicants, and stress. Bulls from the Pacific Northwest region of the United States and other northern areas are exposed to extreme cold temperatures during winter. However, the effects of cold exposure on the methylation patterns of bovine sperm remain unclear. To address, DNA methylation profiles of sperm collected during late spring and winter from the same bulls were analyzed using whole genome bisulfite sequencing (WGBS). Bismark (0.22.3) were used for mapping the WGBS reads and R Bioconductor package DSS was used for differential methylation analysis. Cold exposure induced 3,163 differentially methylated cytosines (DMCs) with methylation difference ≥10% and a q-value < 0.05. We identified 438 differentially methylated regions (DMRs) with q-value < 0.05, which overlapped with 186 unique genes. We also identified eight unique differentially methylated genes (DMGs) (Pax6, Macf1, Mest, Ubqln1, Smg9, Ctnnb1, Lsm4, and Peg10) involved in embryonic development, and nine unique DMGs (Prmt6, Nipal1, C21h15orf40, Slc37a3, Fam210a, Raly, Rgs3, Lmbr1, and Gan) involved in osteogenesis. Peg10 and Mest, two paternally expressed imprinted genes, exhibited >50% higher methylation. The differential methylation patterns of six distinct DMRs: Peg10, Smg9 and Mest related to embryonic development and Lmbr1, C21h15orf40 and Prtm6 related to osteogenesis, were assessed by methylation-specific PCR (MS-PCR), which confirmed the existence of variable methylation patterns in those locations across the two seasons. In summary, cold exposure induces differential DNA methylation patterns in genes that appear to affect embryonic development and osteogenesis in the offspring. Our findings suggest the importance of replicating the results of the current study with a larger sample size and exploring the potential of these changes in affecting offspring development.
Collapse
Affiliation(s)
- Md Nazmul Hossain
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, WA, United States
- Department of Livestock Production and Management, Faculty of Veterinary, Animal, and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh
| | - Yao Gao
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, WA, United States
| | - Michael J. Hatfield
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, WA, United States
| | - Jeanene M. de Avila
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, WA, United States
| | | | - Min Du
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, WA, United States
| |
Collapse
|
7
|
Ramirez P, Sun W, Kazempour Dehkordi S, Zare H, Fongang B, Bieniek KF, Frost B. Nanopore-based DNA long-read sequencing analysis of the aged human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578450. [PMID: 38370753 PMCID: PMC10871260 DOI: 10.1101/2024.02.01.578450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Aging disrupts cellular processes such as DNA repair and epigenetic control, leading to a gradual buildup of genomic alterations that can have detrimental effects in post-mitotic cells. Genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark loci," are difficult to resolve using traditional sequencing approaches. New long-read technologies offer promising avenues for exploration of previously inaccessible regions of the genome. Using nanopore-based long-read whole-genome sequencing of DNA extracted from aged 18 human brains, we identify previously unreported structural variants and methylation patterns within repetitive DNA, focusing on transposable elements ("jumping genes") as crucial sources of variation, particularly in dark loci. Our analyses reveal potential somatic insertion variants and provides DNA methylation frequencies for many retrotransposon families. We further demonstrate the utility of this technology for the study of these challenging genomic regions in brains affected by Alzheimer's disease and identify significant differences in DNA methylation in pathologically normal brains versus those affected by Alzheimer's disease. Highlighting the power of this approach, we discover specific polymorphic retrotransposons with altered DNA methylation patterns. These retrotransposon loci have the potential to contribute to pathology, warranting further investigation in Alzheimer's disease research. Taken together, our study provides the first long-read DNA sequencing-based analysis of retrotransposon sequences, structural variants, and DNA methylation in the aging brain affected with Alzheimer's disease neuropathology.
Collapse
Affiliation(s)
- Paulino Ramirez
- Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas
| | - Wenyan Sun
- Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas
- School of Pharmacy, University of Missouri-Kansas City, Kansas City, Missouri
| | - Shiva Kazempour Dehkordi
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas
| | - Habil Zare
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas
| | - Bernard Fongang
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Biochemistry & Structural Biology, University of Texas Health San Antonio, San Antonio, Texas
| | - Kevin F. Bieniek
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Pathology, University of Texas Health San Antonio, San Antonio, Texas
| | - Bess Frost
- Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, Texas
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas
| |
Collapse
|
8
|
Porter VL, O'Neill K, MacLennan S, Corbett RD, Ng M, Culibrk L, Hamadeh Z, Iden M, Schmidt R, Tsaih SW, Chang G, Fan J, Nip KM, Akbari V, Chan SK, Hopkins J, Moore RA, Chuah E, Mungall KL, Mungall AJ, Birol I, Jones SJM, Rader JS, Marra MA. Genomic structures and regulation patterns at HPV integration sites in cervical cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.04.564800. [PMID: 37961641 PMCID: PMC10635144 DOI: 10.1101/2023.11.04.564800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Human papillomavirus (HPV) integration has been implicated in transforming HPV infection into cancer, but its genomic consequences have been difficult to study using short-read technologies. To resolve the dysregulation associated with HPV integration, we performed long-read sequencing on 63 cervical cancer genomes. We identified six categories of integration events based on HPV-human genomic structures. Of all HPV integrants, defined as two HPV-human breakpoints bridged by an HPV sequence, 24% contained variable copies of HPV between the breakpoints, a phenomenon we termed heterologous integration. Analysis of DNA methylation within and in proximity to the HPV genome at individual integration events revealed relationships between methylation status of the integrant and its orientation and structure. Dysregulation of the human epigenome and neighboring gene expression in cis with the HPV-integrated allele was observed over megabase-ranges of the genome. By elucidating the structural, epigenetic, and allele-specific impacts of HPV integration, we provide insight into the role of integrated HPV in cervical cancer.
Collapse
|
9
|
Gentien D, Saberi-Ansari E, Servant N, Jolly A, de la Grange P, Némati F, Liot G, Saule S, Teissandier A, Bourc'his D, Girard E, Wong J, Masliah-Planchon J, Narmanli E, Liu Y, Torun E, Goulancourt R, Rodrigues M, Gaudé LV, Reyes C, Bazire M, Chenegros T, Henry E, Rapinat A, Bohec M, Baulande S, M'kacher R, Jeandidier E, Nicolas A, Ciriello G, Margueron R, Decaudin D, Cassoux N, Piperno-Neumann S, Stern MH, Gibcus JH, Dekker J, Heard E, Roman-Roman S, Waterfall JJ. Multi-omics comparison of malignant and normal uveal melanocytes reveals molecular features of uveal melanoma. Cell Rep 2023; 42:113132. [PMID: 37708024 PMCID: PMC10598242 DOI: 10.1016/j.celrep.2023.113132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 07/10/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
Uveal melanoma (UM) is a rare cancer resulting from the transformation of melanocytes in the uveal tract. Integrative analysis has identified four molecular and clinical subsets of UM. To improve our molecular understanding of UM, we performed extensive multi-omics characterization comparing two aggressive UM patient-derived xenograft models with normal choroidal melanocytes, including DNA optical mapping, specific histone modifications, and DNA topology analysis using Hi-C. Our gene expression and cytogenetic analyses suggest that genomic instability is a hallmark of UM. We also identified a recurrent deletion in the BAP1 promoter resulting in loss of expression and associated with high risk of metastases in UM patients. Hi-C revealed chromatin topology changes associated with the upregulation of PRAME, an independent prognostic biomarker in UM, and a potential therapeutic target. Our findings illustrate how multi-omics approaches can improve our understanding of tumorigenesis and reveal two distinct mechanisms of gene expression dysregulation in UM.
Collapse
Affiliation(s)
- David Gentien
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France.
| | - Elnaz Saberi-Ansari
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; INSERM U830, Research Center, Institut Curie, PSL Research University, 75005 Paris, France
| | | | | | | | - Fariba Némati
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Laboratory of Preclinical Investigation, Translational Research Department, Institut Curie, PSL Research University, 75248 Paris, France
| | - Géraldine Liot
- Institut Curie, PSL Research University, CNRS, INSERM, UMR3347, U1021, Orsay, France
| | - Simon Saule
- Institut Curie, PSL Research University, CNRS, INSERM, UMR3347, U1021, Orsay, France; Université Paris-Saclay Centre National de La Recherche Scientifique, UMR 3347, Unité 1021, Orsay, France
| | - Aurélie Teissandier
- Institut Curie, PSL Research University, Sorbonne University, INSERM U934, CNRS UMR 3215, 75005 Paris, France
| | - Deborah Bourc'his
- Institut Curie, PSL Research University, Sorbonne University, INSERM U934, CNRS UMR 3215, 75005 Paris, France
| | | | - Jennifer Wong
- Department of Diagnostic and Theranostic Molecular Pathology, Unit of Somatic Genetic, Hospital, Institut Curie, Paris, France
| | - Julien Masliah-Planchon
- Department of Diagnostic and Theranostic Molecular Pathology, Unit of Somatic Genetic, Hospital, Institut Curie, Paris, France
| | - Erkan Narmanli
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; INSERM U830, Research Center, Institut Curie, PSL Research University, 75005 Paris, France
| | - Yuanlong Liu
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Emma Torun
- Institut Curie, PSL Research University, Sorbonne University, INSERM U934, CNRS UMR 3215, 75005 Paris, France
| | | | - Manuel Rodrigues
- Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France; INSERM U830, DNA Repair and Uveal Melanoma (D.R.U.M.), Equipe Labellisée par la Ligue Nationale Contre le Cancer, Department of Genetics, Institut Curie, PSL Research University, 75005 Paris, France
| | - Laure Villoing Gaudé
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France
| | - Cécile Reyes
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France
| | - Matéo Bazire
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France
| | - Thomas Chenegros
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France
| | - Emilie Henry
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France
| | - Audrey Rapinat
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Genomics Platform, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France
| | - Mylene Bohec
- Institut Curie Genomics of Excellence (ICGex) Platform, Institut Curie Research Center, PSL Research University, Paris, France
| | - Sylvain Baulande
- Institut Curie Genomics of Excellence (ICGex) Platform, Institut Curie Research Center, PSL Research University, Paris, France
| | | | - Eric Jeandidier
- Laboratoire de Génétique, Groupe Hospitalier de la Région de Mulhouse Sud-Alsace, Mulhouse, France
| | - André Nicolas
- Pathex, Institut Curie, PSL Research University, Paris, France
| | - Giovanni Ciriello
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Raphael Margueron
- Institut Curie, PSL Research University, Sorbonne University, INSERM U934, CNRS UMR 3215, 75005 Paris, France
| | - Didier Decaudin
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; Laboratory of Preclinical Investigation, Translational Research Department, Institut Curie, PSL Research University, 75248 Paris, France
| | - Nathalie Cassoux
- Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France; Department of Ocular Oncology, Faculty of Medicine, Institut Curie, Université de Paris Descartes, 75005 Paris, France
| | - Sophie Piperno-Neumann
- Department of Medical Oncology, Institut Curie, PSL Research University, 75005 Paris, France
| | - Marc-Henri Stern
- INSERM U830, DNA Repair and Uveal Melanoma (D.R.U.M.), Equipe Labellisée par la Ligue Nationale Contre le Cancer, Department of Genetics, Institut Curie, PSL Research University, 75005 Paris, France
| | - Johan Harmen Gibcus
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Job Dekker
- Howard Hughes Medical Institute, Department of Systems Biology, Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Edith Heard
- Director's Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Sergio Roman-Roman
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France.
| | - Joshua J Waterfall
- Translational Research Department, Research Center, Institut Curie, Paris Sciences et Lettres (PSL) Research University, 75005 Paris, France; INSERM U830, Research Center, Institut Curie, PSL Research University, 75005 Paris, France.
| |
Collapse
|
10
|
Troyee AN, Peña-Ponton C, Medrano M, Verhoeven KJF, Alonso C. Herbivory induced methylation changes in the Lombardy poplar: A comparison of results obtained by epiGBS and WGBS. PLoS One 2023; 18:e0291202. [PMID: 37682835 PMCID: PMC10490839 DOI: 10.1371/journal.pone.0291202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023] Open
Abstract
DNA cytosine methylation is an epigenetic mechanism involved in regulation of plant responses to biotic and abiotic stress and its ability to change can vary with the sequence context in which a cytosine appears (CpG, CHG, CHH, where H = Adenine, Thymine, Cytosine). Quantification of DNA methylation in model plant species is frequently addressed by Whole Genome Bisulfite Sequencing (WGBS), which requires a good-quality reference genome. Reduced Representation Bisulfite Sequencing (RRBS) is a cost-effective potential alternative for ecological research with limited genomic resources and large experimental designs. In this study, we provide for the first time a comprehensive comparison between the outputs of RRBS and WGBS to characterize DNA methylation changes in response to a given environmental factor. In particular, we used epiGBS (recently optimized RRBS) and WGBS to assess global and sequence-specific differential methylation after insect and artificial herbivory in clones of Populus nigra cv. 'italica'. We found that, after any of the two herbivory treatments, global methylation percentage increased in CHH, and the shift was detected as statistically significant only by epiGBS. As regards to loci-specific differential methylation induced by herbivory (cytosines in epiGBS and regions in WGBS), both techniques indicated the specificity of the response elicited by insect and artificial herbivory, together with higher frequency of hypo-methylation in CpG and hyper-methylation in CHH. Methylation changes were mainly found in gene bodies and intergenic regions when present at CpG and CHG and in transposable elements and intergenic regions at CHH context. Thus, epiGBS succeeded to characterize global, genome-wide methylation changes in response to herbivory in the Lombardy poplar. Our results support that epiGBS could be particularly useful in large experimental designs aimed to explore epigenetic changes of non-model plant species in response to multiple environmental factors.
Collapse
Affiliation(s)
- A. Niloya Troyee
- Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas (CSIC), Sevilla, Spain
| | - Cristian Peña-Ponton
- Department of Terrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands
| | - Mónica Medrano
- Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas (CSIC), Sevilla, Spain
| | - Koen J. F. Verhoeven
- Department of Terrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands
| | - Conchita Alonso
- Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas (CSIC), Sevilla, Spain
| |
Collapse
|
11
|
Russell SK, Harrison JK, Olson BS, Lee HJ, O'Brien VP, Xing X, Livny J, Yu L, Roberson EDO, Bomjan R, Fan C, Sha M, Estfanous S, Amer AO, Colonna M, Stappenbeck TS, Wang T, Hannan TJ, Hultgren SJ. Uropathogenic Escherichia coli infection-induced epithelial trained immunity impacts urinary tract disease outcome. Nat Microbiol 2023; 8:875-888. [PMID: 37037942 PMCID: PMC10159856 DOI: 10.1038/s41564-023-01346-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 02/20/2023] [Indexed: 04/12/2023]
Abstract
Previous urinary tract infections (UTIs) can predispose one to future infections; however, the underlying mechanisms affecting recurrence are poorly understood. We previously found that UTIs in mice cause differential bladder epithelial (urothelial) remodelling, depending on disease outcome, that impacts susceptibility to recurrent UTI. Here we compared urothelial stem cell (USC) lines isolated from mice with a history of either resolved or chronic uropathogenic Escherichia coli (UPEC) infection, elucidating evidence of molecular imprinting that involved epigenetic changes, including differences in chromatin accessibility, DNA methylation and histone modification. Epigenetic marks in USCs from chronically infected mice enhanced caspase-1-mediated cell death upon UPEC infection, promoting bacterial clearance. Increased Ptgs2os2 expression also occurred, potentially contributing to sustained cyclooxygenase-2 expression, bladder inflammation and mucosal wounding-responses associated with severe recurrent cystitis. Thus, UPEC infection acts as an epi-mutagen reprogramming the urothelial epigenome, leading to urothelial-intrinsic remodelling and training of the innate response to subsequent infection.
Collapse
Affiliation(s)
- Seongmi K Russell
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA
| | - Jessica K Harrison
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Benjamin S Olson
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA
| | - Hyung Joo Lee
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Valerie P O'Brien
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA
- Fred Hutchinson Cancer Center, Human Biology Division, Seattle, WA, USA
| | - Xiaoyun Xing
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Jonathan Livny
- Infectious Disease and Microbiome Program, The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Lu Yu
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA
| | - Elisha D O Roberson
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Department of Medicine, Division of Rheumatology, Washington University School of Medicine, St Louis, MO, USA
| | - Rajdeep Bomjan
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA
| | - Changxu Fan
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Marina Sha
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Shady Estfanous
- Department of Microbial Infection and Immunity, Infectious Diseases Institute, Ohio State University, Columbus, OH, USA
- Biochemistry and Molecular Biology Department, Faculty of Pharmacy Helwan University, Cairo, Egypt
| | - Amal O Amer
- Department of Microbial Infection and Immunity, Infectious Diseases Institute, Ohio State University, Columbus, OH, USA
| | - Marco Colonna
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA
| | - Thaddeus S Stappenbeck
- Department of Inflammation and Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA.
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St Louis, MO, USA.
| | - Thomas J Hannan
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA.
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA.
| | - Scott J Hultgren
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St Louis, MO, USA.
| |
Collapse
|
12
|
Computational challenges in detection of cancer using cell-free DNA methylation. Comput Struct Biotechnol J 2022; 20:26-39. [PMID: 34976309 PMCID: PMC8669313 DOI: 10.1016/j.csbj.2021.12.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 12/02/2021] [Accepted: 12/02/2021] [Indexed: 12/18/2022] Open
Abstract
Cell-free DNA(cfDNA) methylation profiling is considered promising and potentially reliable for liquid biopsy to study progress of diseases and develop reliable and consistent diagnostic and prognostic biomarkers. There are several different mechanisms responsible for the release of cfDNA in blood plasma, and henceforth it can provide information regarding dynamic changes in the human body. Due to the fragmented nature, low concentration of cfDNA, and high background noise, there are several challenges in its analysis for regular use in diagnosis of cancer. Such challenges in the analysis of the methylation profile of cfDNA are further aggravated due to heterogeneity, biomarker sensitivity, platform biases, and batch effects. This review delineates the origin of cfDNA methylation, its profiling, and associated computational problems in analysis for diagnosis. Here we also contemplate upon the multi-marker approach to handle the scenario of cancer heterogeneity and explore the utility of markers for 5hmC based cfDNA methylation pattern. Further, we provide a critical overview of deconvolution and machine learning methods for cfDNA methylation analysis. Our review of current methods reveals the potential for further improvement in analysis strategies for detecting early cancer using cfDNA methylation.
Collapse
Key Words
- Cancer heterogeneity
- Cell free DNA
- Computation
- DMP, Differentially methylated base position
- DMR, Differentially methylated regions
- Diagnosis
- HELP-seq, HpaII-tiny fragment Enrichment by Ligation-mediated PCR sequencing
- MBD-seq, Methyl-CpG Binding Domain Protein Capture Sequencing
- MCTA-seq, Methylated CpG tandems amplification and sequencing
- MSCC, Methylation Sensitive Cut Counting
- MSRE, methylation sensitive restriction enzymes
- MeDIP-seq, Methylated DNA Immunoprecipitation Sequencing
- RRBS, Reduced-Representation Bisulfite Sequencing
- WGBS, Whole Genome Bisulfite Sequencing
- cfDNA, cell free DNA
- ctDNA, circulating tumor DNA
- dPCR, digital polymerase chain reaction
- ddMCP, droplet digital methylation-specific PCR
- ddPCR, droplet digital polymerase chain reaction
- scCGI, methylated CGIs at single cell level
Collapse
|
13
|
Zhang W, Xu H, Qiao R, Zhong B, Zhang X, Gu J, Zhang X, Wei L, Wang X. ARIC: accurate and robust inference of cell type proportions from bulk gene expression or DNA methylation data. Brief Bioinform 2021; 23:6361035. [PMID: 34472588 DOI: 10.1093/bib/bbab362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 08/13/2021] [Accepted: 08/16/2021] [Indexed: 11/12/2022] Open
Abstract
Quantifying cell proportions, especially for rare cell types in some scenarios, is of great value in tracking signals associated with certain phenotypes or diseases. Although some methods have been proposed to infer cell proportions from multicomponent bulk data, they are substantially less effective for estimating the proportions of rare cell types which are highly sensitive to feature outliers and collinearity. Here we proposed a new deconvolution algorithm named ARIC to estimate cell type proportions from gene expression or DNA methylation data. ARIC employs a novel two-step marker selection strategy, including collinear feature elimination based on the component-wise condition number and adaptive removal of outlier markers. This strategy can systematically obtain effective markers for weighted $\upsilon$-support vector regression to ensure a robust and precise rare proportion prediction. We showed that ARIC can accurately estimate fractions in both DNA methylation and gene expression data from different experiments. We further applied ARIC to the survival prediction of ovarian cancer and the condition monitoring of chronic kidney disease, and the results demonstrate the high accuracy and robustness as well as clinical potentials of ARIC. Taken together, ARIC is a promising tool to solve the deconvolution problem of bulk data where rare components are of vital importance.
Collapse
Affiliation(s)
- Wei Zhang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Hanwen Xu
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Rong Qiao
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Bixi Zhong
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xianglin Zhang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Jin Gu
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xuegong Zhang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Lei Wei
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xiaowo Wang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing 100084, China
| |
Collapse
|
14
|
The progress on the estimation of DNA methylation level and the detection of abnormal methylation. QUANTITATIVE BIOLOGY 2021. [DOI: 10.15302/j-qb-022-0289] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|