1
|
Luo Y, Ye Y, Saibaidoula Y, Zhang Y, Chen Y. Multifaceted investigations of PSMB8 provides insights into prognostic prediction and immunological target in thyroid carcinoma. PLoS One 2025; 20:e0323013. [PMID: 40334200 PMCID: PMC12058196 DOI: 10.1371/journal.pone.0323013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2024] [Accepted: 04/01/2025] [Indexed: 05/09/2025] Open
Abstract
The Proteasome 20S subunit beta 8 (PSMB8) is an integral element of the immunoproteasome complex, playing a pivotal role in antigen processing. Despite its significance, the contributory role of PSMB8 in oncogenesis, particularly in thyroid carcinoma (THCA), has not been well-characterized. To address this gap in knowledge, our study endeavored to delineate the potential associations between PSMB8 and THCA. Transcriptomic profiles and clinical data of patients with THCA were retrieved from The Cancer Genome Atlas (TCGA) database to facilitate comprehensive analysis. Complementary resources from additional online databases were utilized to augment the study. Logistic regression analysis was employed to elucidate the relationship between PSMB8 and various clinicopathological parameters. Uni/multivariate Cox regression analyses were conducted to ascertain the independent prognostic factors for THCA patient outcomes. Quantitative polymerase chain reaction (qPCR) and western blot assays were employed to verify the expression level of PSMB8 in vitro. Our study demonstrated that PSMB8 was significantly upregulated in THCA, with its overexpression correlating with lymph node metastasis, extrathyroidal extension, and favorable prognosis. Immunohistochemistry substantiated a higher PSMB8 protein presence in THCA tissue compared to the normal, supporting its potential role as a moderately accurate diagnostic biomarker. Logistic regression analysis identified PSMB8 as a significant indicator of the N1 stage, classical histological subtype, and extrathyroidal extension. Age, T stage, and PSMB8 were further determined as independent prognostic factors for THCA. Functional investigations linked PSMB8 to immune processes, evidenced by its association with increased immune cell infiltration and higher stromal/immune scores, as well as a positive co-expression with several immune checkpoints. A constructed predicted competing endogenous RNA (ceRNA) network implicated PSMB8 in complex post-transcriptional regulation. Finally, in vitro assays confirmed the upregulation of PSMB8, underscoring its relevance in THCA and as a target for future research. Our work has preliminarily appraised PSMB8 as a biomarker with certain prognostic and diagnostic significance, and as a potential target for immunotherapy in THCA.
Collapse
Affiliation(s)
- Yulou Luo
- Department of Breast Surgery, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China
| | - Yinghui Ye
- Department of Laboratory Medicine, Xinhua Hospital, Shenzhen, Guangdong Province, China
| | - Yilina Saibaidoula
- Department of Breast Surgery, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China
| | - Yuting Zhang
- Department of Breast Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong Province, China
| | - Yan Chen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China
- Xinjiang Key Laboratory of Molecular Biology for Endemic Diseases, Urumqi, Xinjiang Uygur Autonomous Region, China
| |
Collapse
|
2
|
Zhang G, Song C, Yin M, Liu L, Zhang Y, Li Y, Zhang J, Guo M, Li C. TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data. Nat Commun 2025; 16:3611. [PMID: 40240358 PMCID: PMC12003887 DOI: 10.1038/s41467-025-58921-0] [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: 06/17/2024] [Accepted: 04/01/2025] [Indexed: 04/18/2025] Open
Abstract
It is challenging to identify regulatory transcriptional regulators (TRs), which control gene expression via regulatory elements and epigenomic signals, in context-specific studies on the onset and progression of diseases. The use of large-scale multi-omics epigenomic data enables the representation of the complex epigenomic patterns of control of the regulatory elements and the regulators. Herein, we propose Transcription Regulator Activity Prediction Tool (TRAPT), a multi-modality deep learning framework, which infers regulator activity by learning and integrating the regulatory potentials of target gene cis-regulatory elements and genome-wide binding sites. The results of experiments on 570 TR-related datasets show that TRAPT outperformed state-of-the-art methods in predicting the TRs, especially in terms of forecasting transcription co-factors and chromatin regulators. Moreover, we successfully identify key TRs associated with diseases, genetic variations, cell-fate decisions, and tissues. Our method provides an innovative perspective on identifying TRs by using epigenomic data.
Collapse
Affiliation(s)
- Guorui Zhang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Chao Song
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
- Key Laboratory of Rare Pediatric Diseases, Ministry of Education, University of South China, Hengyang, Hunan, 421001, China
| | - Mingxue Yin
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Liyuan Liu
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Yuexin Zhang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
| | - Ye Li
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Jianing Zhang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
| | - Maozu Guo
- School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China.
| | - Chunquan Li
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China.
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.
- School of Computer, University of South China, Hengyang, Hunan, 421001, China.
- Key Laboratory of Rare Pediatric Diseases, Ministry of Education, University of South China, Hengyang, Hunan, 421001, China.
| |
Collapse
|
3
|
Deng Z, Zhu H, Cheng Z, Li R, Peng H. Identification and validation of pyroptosis patterns in AML via comprehensive bioinformatics analysis. Discov Oncol 2025; 16:509. [PMID: 40208371 PMCID: PMC11985831 DOI: 10.1007/s12672-025-02298-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2024] [Accepted: 04/02/2025] [Indexed: 04/11/2025] Open
Abstract
Pyroptosis, a lytic inflammatory cell death mechanism, plays dual roles in tumorigenesis, but its clinical relevance in acute myeloid leukemia (AML) remains poorly understood. Through an integrative analysis of 40 pyroptosis-related genes in newly diagnosed AML patients (TCGA, n = 151) and healthy controls (GTEx, n = 386), we identified 32 genes with aberrant expression. Among these, 9 genes were found to be significant prognostic markers, including ELANE (protective), and CASP1, CHMP4B, BAK1, and CHMP2A (risk), which retained their prognostic significance after adjusting for age and gender. Using unsupervised nonnegative matrix factorization (NMF) on TCGA data, we classified AML into two pyroptosis patterns: the ELANEhigh subtype, associated with favorable survival, and the ELANElow subtype, which was enriched in poor karyotypes and adverse outcomes. This classification was validated in an independent cohort (GSE10358, n = 91). Single-cell RNA sequencing data (GSE116256, n = 15) revealed that the ELANElow subtype is characterized by an immunologically active microenvironment, marked by an expansion of cytotoxic T cells and naive CD4 + /CD8 + T cells. Factor analysis revealed associations between pyroptosis patterns and other forms of cell death, including ferroptosis, autophagy, and apoptosis, as well as with karyotype, leukemia stemness, and TP53/FLT3-ITD mutations. Prognostic immune gene sets enriched in the ELANElow subtype were associated with interferon signaling and ubiquitin-mediated degradation pathways. Furthermore, protein-protein interaction (PPI) network analysis identified three sub-networks and nine key hub genes. This study integrates gene expression data from newly diagnosed AML patients, revealing the heterogeneity of pyroptosis patterns within the population. It highlights the potential links between distinct pyroptosis patterns, the immune microenvironment, various cell death pathways, leukemia stemness, and genomic alterations, offering novel biomarkers and therapeutic targets for risk stratification and immunomodulatory interventions in AML.
Collapse
Affiliation(s)
- Zeyu Deng
- Department of Hematology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China
- Institute of Hematology, Central South University, Changsha, Hunan, People's Republic of China
- Hunan Engineering Research Center of Cell Immunotherapy for Hematopoietic Malignancies, Changsha, Hunan, People's Republic of China
| | - Hongkai Zhu
- Department of Hematology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China
- Institute of Hematology, Central South University, Changsha, Hunan, People's Republic of China
- Hunan Engineering Research Center of Cell Immunotherapy for Hematopoietic Malignancies, Changsha, Hunan, People's Republic of China
| | - Zhao Cheng
- Department of Hematology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China
- Institute of Hematology, Central South University, Changsha, Hunan, People's Republic of China
- Hunan Engineering Research Center of Cell Immunotherapy for Hematopoietic Malignancies, Changsha, Hunan, People's Republic of China
| | - Ruijuan Li
- Department of Hematology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
- Institute of Hematology, Central South University, Changsha, Hunan, People's Republic of China.
- Hunan Engineering Research Center of Cell Immunotherapy for Hematopoietic Malignancies, Changsha, Hunan, People's Republic of China.
| | - Hongling Peng
- Department of Hematology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People's Republic of China.
- Institute of Hematology, Central South University, Changsha, Hunan, People's Republic of China.
- Hunan Engineering Research Center of Cell Immunotherapy for Hematopoietic Malignancies, Changsha, Hunan, People's Republic of China.
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, Changsha, Hunan, People's Republic of China.
| |
Collapse
|
4
|
Sierant MC, Jin SC, Bilguvar K, Morton SU, Dong W, Jiang W, Lu Z, Li B, López-Giráldez F, Tikhonova I, Zeng X, Lu Q, Choi J, Zhang J, Nelson-Williams C, Knight JR, Zhao H, Cao J, Mane S, Sedore SC, Gruber PJ, Lek M, Goldmuntz E, Deanfield J, Giardini A, Mital S, Russell M, Gaynor JW, King E, Wagner M, Srivastava D, Shen Y, Bernstein D, Porter GA, Newburger JW, Seidman JG, Roberts AE, Yandell M, Yost HJ, Tristani-Firouzi M, Kim R, Chung WK, Gelb BD, Seidman CE, Brueckner M, Lifton RP. Genomic analysis of 11,555 probands identifies 60 dominant congenital heart disease genes. Proc Natl Acad Sci U S A 2025; 122:e2420343122. [PMID: 40127276 PMCID: PMC12002227 DOI: 10.1073/pnas.2420343122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Accepted: 02/18/2025] [Indexed: 03/26/2025] Open
Abstract
Congenital heart disease (CHD) is a leading cause of infant mortality. We analyzed de novo mutations (DNMs) and very rare transmitted/unphased damaging variants in 248 prespecified genes in 11,555 CHD probands. The results identified 60 genes with a significant burden of heterozygous damaging variants. Variants in these genes accounted for CHD in 10.1% of probands with similar contributions from de novo and transmitted variants in parent-offspring trios that showed incomplete penetrance. DNMs in these genes accounted for 58% of the signal from DNMs. Thirty-three genes were linked to a single CHD subtype while 12 genes were associated with 2 to 4 subtypes. Seven genes were only associated with isolated CHD, while 37 were associated with 1 or more extracardiac abnormalities. Genes selectively expressed in the cardiomyocyte lineage were associated with isolated CHD, while those widely expressed in the brain were also associated with neurodevelopmental delay (NDD). Missense variants introducing or removing cysteines in epidermal growth factor (EGF)-like domains of NOTCH1 were enriched in tetralogy of Fallot and conotruncal defects, unlike the broader CHD spectrum seen with loss of function variants. Transmitted damaging missense variants in MYH6 were enriched in multiple CHD phenotypes and account for ~1% of all probands. Probands with characteristic mutations causing syndromic CHD were frequently not diagnosed clinically, often due to missing cardinal phenotypes. CHD genes that were positively or negatively associated with development of NDD suggest clinical value of genetic testing. These findings expand the understanding of CHD genetics and support the use of molecular diagnostics in CHD.
Collapse
Grants
- U01 HL128711 NHLBI NIH HHS
- RM1HG011014 HHS | NIH | National Human Genome Research Institute (NHGRI)
- UO1 HL128711 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UO1 HL098147 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U01 HL098162 NHLBI NIH HHS
- UO1 HL153009 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UO1 HL098162 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U54 HG006504 NHGRI NIH HHS
- UL1 TR000003 NCATS NIH HHS
- R00HL143036-02 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UO1 HL131003 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- 1UG1HL135680-01 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- CDI-FR-2021-926 Children's Discovery Institute (CDI)
- NIH R03HD100883-A1 HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
- UG1 HL135680 NHLBI NIH HHS
- T32 HD007149 NICHD NIH HHS
- R03 HD100883 NICHD NIH HHS
- RM1 HG011014 NHGRI NIH HHS
- U01 HL098153 NHLBI NIH HHS
- U01 HL131003 NHLBI NIH HHS
- 5U54HG006504 HHS | NIH | National Human Genome Research Institute (NHGRI)
- HHMI HHMI (HHMI)
- U01 HL153009 NHLBI NIH HHS
- R00 HL143036 NHLBI NIH HHS
- HL157653 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UL1TR000003 HHS | NIH | National Center for Advancing Translational Sciences (NCATS)
- 19PRE3438084 American Heart Association (AHA)
- K08 HL157653 NHLBI NIH HHS
- U01 HL098147 NHLBI NIH HHS
Collapse
Affiliation(s)
- Michael C. Sierant
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY10065
| | - Sheng Chih Jin
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY10065
- Department of Genetics, Washington University School of Medicine, St. Louis, MO63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO63110
| | - Kaya Bilguvar
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Yale Center for Genome Analysis, Yale University, New Haven, CT06516
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT06510
- Yale Program on Neurogenetics, Yale School of Medicine, New Haven, CT06510
- Department of Medical Genetics, School of Medicine, Acibadem University, Istanbul34752, Türkiye
- Department of Translational Medicine, Health Sciences Institute, Acibadem University, Istanbul34752, Türkiye
| | - Sarah U. Morton
- Division of Newborn Medicine, Department of Pediatrics, Boston Children’s Hospital, Boston, MA02115
- Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA02115
- Broad Institute of Massachusetts Institute of Technology and Harvard, Boston, MA02142
| | - Weilai Dong
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY10065
| | - Wei Jiang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT06510
| | - Ziyu Lu
- Laboratory of Single-Cell Genomics and Population Dynamics, The Rockefeller University, New York, NY10065
| | - Boyang Li
- Department of Biostatistics, Yale School of Public Health, New Haven, CT06510
| | | | - Irina Tikhonova
- Yale Center for Genome Analysis, Yale University, New Haven, CT06516
| | - Xue Zeng
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY10065
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI53706
| | - Jungmin Choi
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY10065
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, South Korea
| | - Junhui Zhang
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
| | | | - James R. Knight
- Yale Center for Genome Analysis, Yale University, New Haven, CT06516
| | - Hongyu Zhao
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Department of Biostatistics, Yale School of Public Health, New Haven, CT06510
| | - Junyue Cao
- Laboratory of Single-Cell Genomics and Population Dynamics, The Rockefeller University, New York, NY10065
| | - Shrikant Mane
- Yale Center for Genome Analysis, Yale University, New Haven, CT06516
| | - Stanley C. Sedore
- Department of Pediatrics, Section of Cardiology, Yale School of Medicine, New Haven, CT06510
- Department of Pediatrics, Michigan State University College of Human Medicine, Grand Rapids, MI48824
| | - Peter J. Gruber
- Department of Surgery, Yale University School of Medicine, New Haven, CT06510
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
| | - Elizabeth Goldmuntz
- Division of Cardiology, Children’s Hospital of Philadelphia, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - John Deanfield
- Institute of Cardiovascular Science, University College London, LondonWC1E 6BT, United Kingdom
| | - Alessandro Giardini
- Pediatric Cardiology, Great Ormond Street Hospital, LondonWC1N 3JH, United Kingdom
| | - Seema Mital
- Division of Cardiology, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ONM5G1X8, Canada
| | - Mark Russell
- Department of Pediatrics and Communicable Diseases, University of Michigan, Ann Arbor, MI48109
| | - J. William Gaynor
- Division of Cardiothoracic Surgery, Children's Hospital of Philadelphia, Philadelphia, PA19104
| | - Eileen King
- Department of Pediatrics, University of Cincinnati, Cincinnati, OH45229
| | - Michael Wagner
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH45229
- Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH45229
| | - Deepak Srivastava
- Gladstone Institute of Cardiovascular Disease and University of California San Francisco, San Francisco, CA94158
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY10032
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY10032
| | - Daniel Bernstein
- Department of Pediatrics, Cardiology, Stanford University, Stanford, CA94304
| | - George A. Porter
- Department of Pediatrics, Section of Cardiology, Yale School of Medicine, New Haven, CT06510
- Department of Pediatrics, The School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY14642
| | - Jane W. Newburger
- Department of Cardiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA02115
- Department of Pediatrics, Harvard Medical School, Boston, MA02115
| | | | - Amy E. Roberts
- Department of Cardiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA02115
- Department of Pediatrics, Harvard Medical School, Boston, MA02115
| | - Mark Yandell
- Department of Human Genetics, University of Utah and School of Medicine, Salt Lake City, UT84112
| | - H. Joseph Yost
- Department of Human Genetics, University of Utah and School of Medicine, Salt Lake City, UT84112
- The Catholic University of America, Washington, DC20064
| | | | - Richard Kim
- Pediatric Cardiac Surgery, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA90048
| | - Wendy K. Chung
- Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA02115
- Department of Pediatrics and Medicine, Columbia University Medical Center, New York, NY10032
| | - Bruce D. Gelb
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY10029
| | - Christine E. Seidman
- Cardiovascular Division, Brigham and Women’s Hospital, Boston, MA02115
- HHMI, Chevy Chase, MD20815
| | - Martina Brueckner
- Department of Genetics, Yale School of Medicine, New Haven, CT06510
- Department of Pediatrics, Section of Cardiology, Yale School of Medicine, New Haven, CT06510
| | - Richard P. Lifton
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY10065
| |
Collapse
|
5
|
Tian X, Wang R, Liu Z, Lu S, Chen X, Zhang Z, Liu F, Li H, Zhang X, Wang M. Widespread impact of transposable elements on the evolution of post-transcriptional regulation in the cotton genus Gossypium. Genome Biol 2025; 26:60. [PMID: 40098207 PMCID: PMC11912738 DOI: 10.1186/s13059-025-03534-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Accepted: 03/07/2025] [Indexed: 03/19/2025] Open
Abstract
BACKGROUND Transposable element (TE) expansion has long been known to mediate genome evolution and phenotypic diversity in organisms, but its impact on the evolution of post-transcriptional regulation following species divergence remains unclear. RESULTS To address this issue, we perform long-read direct RNA sequencing, polysome profiling sequencing, and small RNA sequencing in the cotton genus Gossypium, the species of which range more than three folds in genome size. We find that TE expansion contributes to the turnover of transcription splicing sites and regulatory sequences, leading to changes in alternative splicing patterns and the expression levels of orthologous genes. We also find that TE-derived upstream open reading frames and microRNAs serve as regulatory elements mediating differences in the translation levels of orthologous genes. We further identify genes that exhibit lineage-specific divergence at the transcriptional, splicing, and translational levels, and showcase the high flexibility of gene expression regulation in the evolutionary process. CONCLUSIONS Our work highlights the significant role of TE in driving post-transcriptional regulation divergence in the cotton genus. It offers insights for deciphering the evolutionary mechanisms of cotton species and the formation of biological diversity.
Collapse
Affiliation(s)
- Xuehan Tian
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
| | - Ruipeng Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhenping Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
| | - Sifan Lu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xinyuan Chen
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zeyu Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
- College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, 455000, China
| | - Hongbin Li
- College of Life Science, Shihezi University, Shihezi, 832003, China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China
| | - Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
- College of Life Science, Shihezi University, Shihezi, 832003, China.
| |
Collapse
|
6
|
Tennakoon R, Bily TM, Hasan F, Syal S, Voigt A, Balci TB, Hoffman KS, O’Donoghue P. Glutamine missense suppressor transfer RNAs inhibit polyglutamine aggregation. MOLECULAR THERAPY. NUCLEIC ACIDS 2025; 36:102442. [PMID: 39897579 PMCID: PMC11787650 DOI: 10.1016/j.omtn.2024.102442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 12/19/2024] [Indexed: 02/04/2025]
Abstract
Huntington's disease (HD) is caused by polyglutamine (polyQ) repeat expansions in the huntingtin gene. HD-causative polyQ alleles lead to protein aggregation, which is a prerequisite for disease. Translation fidelity modifies protein aggregation, and several studies suggest that mutating one or two glutamine (Gln) residues in polyQ reduces aggregation. Thus, we hypothesized that missense suppression of Gln codons with other amino acids will reduce polyQ aggregate formation in cells. In neuroblastoma cells, we assessed tRNA variants that misread Gln codons with serine (tRNASer C/UUG) or alanine (tRNAAla C/UUG). The tRNAs with the CUG anticodon were more effective at suppressing the CAG repeats in polyQ, and serine and alanine mis-incorporation had differential impacts on polyQ. The expression of tRNASer CUG reduced polyQ protein production as well as both soluble and insoluble aggregate formation. In contrast, cells expressing tRNAAla CUG selectively decreased insoluble polyQ aggregate formation by 2-fold. Mass spectrometry confirmed Ala mis-incorporation at an average level of ∼20% per Gln codon. Cells expressing the missense suppressor tRNAs showed no cytotoxic effects and no defects in growth or global protein synthesis levels. Our findings demonstrate that tRNA-dependent missense suppression of Gln codons is well tolerated in mammalian cells and significantly reduces polyQ levels and aggregates that cause HD.
Collapse
Affiliation(s)
- Rasangi Tennakoon
- Department of Biochemistry, The University of Western Ontario, London, ON N6A 5C1, Canada
| | - Teija M.I. Bily
- Department of Biochemistry, The University of Western Ontario, London, ON N6A 5C1, Canada
| | - Farah Hasan
- Department of Biochemistry, The University of Western Ontario, London, ON N6A 5C1, Canada
| | - Sunidhi Syal
- Department of Biochemistry, The University of Western Ontario, London, ON N6A 5C1, Canada
| | - Aaron Voigt
- Department of Neurology, RWTH Aachen, 52062 Aachen, Germany
| | - Tugce B. Balci
- Department of Paediatrics, The University of Western Ontario, London, ON N6A 5C1, Canada
| | | | - Patrick O’Donoghue
- Department of Biochemistry, The University of Western Ontario, London, ON N6A 5C1, Canada
- Department of Chemistry, The University of Western Ontario, London, ON N6A 5C1, Canada
| |
Collapse
|
7
|
Margalit S, Tulpová Z, Michaeli Y, Zur T, Deek J, Louzoun-Zada S, Nifker G, Grunwald A, Scher Y, Schütz L, Weinhold E, Gnatek Y, Omer D, Dekel B, Friedman E, Ebenstein Y. Optical genome and epigenome mapping of clear cell renal cell carcinoma. NAR Cancer 2025; 7:zcaf008. [PMID: 40061565 PMCID: PMC11886815 DOI: 10.1093/narcan/zcaf008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2024] [Revised: 02/18/2025] [Accepted: 03/05/2025] [Indexed: 04/02/2025] Open
Abstract
Cancer cells display complex genomic aberrations that include large-scale genetic rearrangements and epigenetic modulation that are not easily captured by short-read sequencing. This study presents a novel approach for simultaneous profiling of long-range genetic and epigenetic changes in matched cancer samples, focusing on clear cell renal cell carcinoma (ccRCC). ccRCC is a common kidney cancer subtype frequently characterized by a 3p deletion and the inactivation of the von Hippel-Lindau (VHL) gene. We performed integrated genetic, cytogenetic, and epigenetic analyses on paired tumor and adjacent nontumorous tissue samples. Optical genome mapping identified genomic aberrations as structural and copy number variations, complementing exome-sequencing findings. Single-molecule methylome and hydroxymethylome mapping revealed a significant global reduction in 5hmC level in both sample pairs, and a correlation between both epigenetic signals and gene expression was observed. The single-molecule epigenetic analysis identified numerous differentially modified regions, some implicated in ccRCC pathogenesis, including the genes VHL, PRCC, and PBRM1. Notably, pathways related to metabolism and cancer development were significantly enriched among these differential regions. This study demonstrates the feasibility of integrating optical genome and epigenome mapping for comprehensive characterization of matched tumor and adjacent tissue, uncovering both established and novel somatic aberrations.
Collapse
Affiliation(s)
- Sapir Margalit
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Zuzana Tulpová
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
- Institute of Experimental Botany of the Czech Academy of Sciences, 77900, Olomouc, Czech Republic
| | - Yael Michaeli
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Tahir Detinis Zur
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Jasline Deek
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Sivan Louzoun-Zada
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Gil Nifker
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Assaf Grunwald
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Yuval Scher
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
| | - Leonie Schütz
- Institute of Organic Chemistry, RWTH Aachen University, D-52056 Aachen, Germany
| | - Elmar Weinhold
- Institute of Organic Chemistry, RWTH Aachen University, D-52056 Aachen, Germany
| | - Yehudit Gnatek
- Pediatric Stem Cell Research Institute, Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, 52621 Ramat Gan, Israel
| | - Dorit Omer
- Pediatric Stem Cell Research Institute, Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, 52621 Ramat Gan, Israel
| | - Benjamin Dekel
- Pediatric Stem Cell Research Institute, Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, 52621 Ramat Gan, Israel
- Pediatric Nephrology Unit, The Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, 52621 Ramat Gan, Israel
- School of Medicine, Faculty of Medical and Health Sciences, Tel-Aviv University, 6997801 Tel Aviv, Israel
| | - Eitan Friedman
- School of Medicine, Faculty of Medical and Health Sciences, Tel-Aviv University, 6997801 Tel Aviv, Israel
- The Susanne Levy Gertner Oncogenetics Unit, The Danek Gertner Institute of Human Genetics, Sheba Medical Center, 52621 Ramat Gan, Israel
| | - Yuval Ebenstein
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel
- Department of Biomedical Engineering, Tel Aviv University, 6997801 Tel Aviv, Israel
| |
Collapse
|
8
|
Bozkurt-Yozgatli T, Lun MY, Bengtsson JD, Sezerman U, Chinn IK, Coban-Akdemir Z, Carvalho CMB. Investigation of a pathogenic inversion in UNC13D and comprehensive analysis of chromosomal inversions across diverse datasets. Eur J Hum Genet 2025:10.1038/s41431-025-01817-w. [PMID: 40021841 DOI: 10.1038/s41431-025-01817-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2024] [Revised: 12/19/2024] [Accepted: 02/12/2025] [Indexed: 03/03/2025] Open
Abstract
Inversions are known contributors to the pathogenesis of genetic diseases. Identifying inversions poses significant challenges, making it one of the most demanding structural variants (SVs) to detect and interpret. Recent advancements in sequencing technologies and the development of publicly available SV datasets have substantially enhanced our capability to explore inversions. However, a cross-comparison in those datasets remains unexplored. In this study, we reported a proband with familial hemophagocytic lymphohistiocytosis type-3 carrying a splicing variant (c.1389+1G>A) in trans with an inversion present in 0.006345% of individuals in gnomAD (v4.0) that disrupts UNC13D. Based on this result, we investigate the features of potentially pathogenic inversions in gnomAD which revealed 98.9% of them are rare and disrupt 5% of protein-coding genes associated with a phenotype in OMIM. We then conducted a comparative analysis of additional public datasets, including DGV, 1KGP, and two recent studies from the Human Genome Structural Variation Consortium which revealed common and dataset-specific inversion characteristics suggesting methodology detection biases. Next, we investigated the genetic features of inversions disrupting the protein-coding genes. Notably, we found that the majority of protein-coding genes in OMIM disrupted by inversions are associated with autosomal recessive phenotypes supporting the hypothesis that inversions in trans with other variants are potential hidden causes of monogenic diseases. This effort aims to fill the gap in our understanding of the molecular characteristics of inversions with low frequency in the population and highlight the importance of identifying them in rare disease studies.
Collapse
Affiliation(s)
- Tugce Bozkurt-Yozgatli
- Department of Biostatistics and Bioinformatics, Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ming Yin Lun
- Pacific Northwest Research Institute, Seattle, WA, USA
| | | | - Ugur Sezerman
- Department of Biostatistics and Bioinformatics, Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
- Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Ivan K Chinn
- Department of Pediatrics, Division of Immunology, Allergy, and Retrovirology, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA
- Center for Human Immunobiology of Texas Children's Hospital/Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Zeynep Coban-Akdemir
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
| | | |
Collapse
|
9
|
Kinnear E, Derbel H, Zhao Z, Liu Q. Deep5mC: Predicting 5-methylcytosine (5mC) methylation status using a deep learning transformer approach. Comput Struct Biotechnol J 2025; 27:631-638. [PMID: 40041569 PMCID: PMC11879672 DOI: 10.1016/j.csbj.2025.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2024] [Revised: 02/12/2025] [Accepted: 02/13/2025] [Indexed: 03/06/2025] Open
Abstract
DNA methylations, such as 5-methylcytosine (5mC), are crucial in biological processes, and aberrant methylations are strongly linked to various human diseases. Genomic 5mC is not randomly distributed but exhibits a strong association with genomic sequences. Thus, various computational methods were developed to predict 5mC status based on DNA sequences. These methods generated promising achievements and overcome the limitations of experimental approaches. However, few studies have comprehensively investigated the dependency of 5mC on genomic sequences, and most existing methods focus on specific genomic regions. In this work, we introduce Deep5mC, a deep learning transformer-based method designed to predict 5mC methylations. Deep5mC leverages long-range dependencies within genomic sequences to estimate the probability of cytosine methylations. Through cross-chromosome evaluation, Deep5mC achieves Matthew's correlation coefficient over 0.86 and F1-score over 0.93, substantially outperforming state-of-the-art methods. Deep5mC not only confirms the influence of long-range sequence context on 5mC prediction but also paves the way for further studying 5mC-sequence dependency across species and in human diseases.
Collapse
Affiliation(s)
- Evan Kinnear
- Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154, USA
| | - Houssemeddine Derbel
- Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154, USA
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Qian Liu
- Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154, USA
- School of Life Sciences, College of Sciences, University of Nevada, Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154, USA
| |
Collapse
|
10
|
Zhou X, Qin Y, Li J, Fan L, Zhang S, Zhang B, Wu L, Gao A, Yang Y, Lv X, Guo B, Sun L. LncPepAtlas: a comprehensive resource for exploring the translational landscape of long non-coding RNAs. Nucleic Acids Res 2025; 53:D468-D476. [PMID: 39435995 PMCID: PMC11701525 DOI: 10.1093/nar/gkae905] [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: 08/14/2024] [Revised: 09/20/2024] [Accepted: 10/07/2024] [Indexed: 10/23/2024] Open
Abstract
Long non-coding RNAs were commonly viewed as non-coding elements. However, they are increasingly recognized for their ability to be translated into proteins, thereby playing a significant role in various cellular processes and diseases. With developments in biotechnology and computational algorithms, a range of novel approaches are being applied to investigate the translation of long non-coding RNA (lncRNAs). Herein, we developed the LncPepAtlas database (http://www.cnitbiotool.net/LncPepAtlas/), which aims to compile multiple evidences for the translation of lncRNAs and annotations for the upstream regulation of lncRNAs across various species. LncPepAtlas integrated compelling evidence from nine distinct sources for the translation of lncRNAs. These include a dataset comprising 2631 publicly available Ribo-seq samples from nine species, which has been collected and analysed. LncPepAtlas offers extensive annotation for lncRNA upstream regulation and expression profiles across various cancers, tissues or cell lines at transcriptional and translational levels. Importantly, it enables novel antigen predictions for lncRNA-encoded peptides. By identifying numerous peptide candidates that could potentially bind to major histocompatibility complex class I and II molecules, this work may provide new insights into cancer immunotherapy. The function of peptides were inferred by aligning them with experimentally detected proteins. LncPepAtlas aims to become a convenient resource for exploring translatable lncRNAs.
Collapse
Affiliation(s)
- Xinyuan Zhou
- Binzhou People’s Hospital Affiliated to Shandong First Medical University/College of Medical Information and Artificial Intelligence, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Yanxia Qin
- Binzhou People’s Hospital Affiliated to Shandong First Medical University/College of Medical Information and Artificial Intelligence, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Jiangxue Li
- Binzhou People’s Hospital Affiliated to Shandong First Medical University/College of Medical Information and Artificial Intelligence, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Linyuan Fan
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, Shandong 250000, China
| | - Shun Zhang
- School of Information Science and Engineering, University of Jinan, Jinan, Shandong 250022, China
| | - Bing Zhang
- School of Mathematical Sciences, Harbin Normal University, Harbin, Heilongjiang 150025, China
| | - Luoxuan Wu
- College of Ophthalmology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Anwei Gao
- Binzhou People’s Hospital Affiliated to Shandong First Medical University/College of Medical Information and Artificial Intelligence, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Yongsan Yang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xueqin Lv
- School of Mathematical Sciences, Harbin Normal University, Harbin, Heilongjiang 150025, China
- College of Basic Science, Tianjin Sino-German University of Applied Sciences, Tianjin 300350, China
| | - Bingzhou Guo
- Binzhou People’s Hospital Affiliated to Shandong First Medical University/College of Medical Information and Artificial Intelligence, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Liang Sun
- Binzhou People’s Hospital Affiliated to Shandong First Medical University/College of Medical Information and Artificial Intelligence, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| |
Collapse
|
11
|
Gluckman J, Levy T, Friedman K, Garces F, Filip-Dhima R, Quinlan A, Iannotti I, Pekar M, Hernandez AL, Nava MT, Kravets E, Siegel A, Bernstein JA, Berry-Kravis E, Powell CM, Soorya LV, Thurm A, Srivastava S, Buxbaum JD, Sahin M, Kolevzon A, Gelb BD. Aortic Root Dilation and Genotype Associations in Phelan-McDermid Syndrome. Am J Med Genet A 2025; 197:e63872. [PMID: 39257296 PMCID: PMC11637948 DOI: 10.1002/ajmg.a.63872] [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: 07/05/2024] [Revised: 08/20/2024] [Accepted: 08/24/2024] [Indexed: 09/12/2024]
Abstract
Phelan-McDermid syndrome (PMS) is a rare genetic neurodevelopmental disorder that results from the loss of one functional copy of the SHANK3 gene. While many clinical features of PMS are well-understood, there is currently limited literature on cardiovascular abnormalities in PMS. This report aims to evaluate the prevalence of aortic root dilation (ARD) among individuals with PMS and to understand if underlying genetic variation relates to risk for ARD. We present findings from 59 participants collected from a multisite observational study evaluating the phenotype and natural history of PMS. Individual echocardiographic and genetic reports were analyzed for aortic root measurements and genetic variant data, respectively. Our a priori hypothesis was that participants with chromosome 22 deletions with hg19 start coordinates on or before 49,900,000 (larger deletions) would have more instances of ARD than participants with deletion start coordinates after 49,900,000 (smaller deletions). Eight participants (14%) had ARD, and its presence was statistically significantly associated with large deletions (p = 0.047). Relatedly, participants with ARD had significantly more genes deleted on chromosome 22 than participants without ARD (p = 0.013). These results could aid in the identification of individuals with PMS who are at higher risk for ARD.
Collapse
Affiliation(s)
- Jake Gluckman
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Tess Levy
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kate Friedman
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Francesca Garces
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Rajna Filip-Dhima
- Department of Neurology, Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, 02115, USA
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Aisling Quinlan
- Department of Neurology, Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, 02115, USA
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Isabelle Iannotti
- Department of Neurology, Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, 02115, USA
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Margaret Pekar
- Neurodevelopmental and Behavioral Phenotyping Service, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Alexandra Lopez Hernandez
- Department of Pediatrics, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Anatomy and Cell Biology, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Madison T Nava
- Department of Pediatrics, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Anatomy and Cell Biology, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Elijah Kravets
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - Abigail Siegel
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jonathan A. Bernstein
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - Elizabeth Berry-Kravis
- Department of Pediatrics, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
- Department of Anatomy and Cell Biology, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Craig M. Powell
- Department of Neurobiology, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, 35233, USA
- Civitan International Research Center, University of Alabama at Birmingham, Birmingham, AL, 352233, USA
| | - Latha Valluripalli Soorya
- Department of Psychiatry & Behavioral Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Audrey Thurm
- Neurodevelopmental and Behavioral Phenotyping Service, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Siddharth Srivastava
- Department of Neurology, Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Joseph D. Buxbaum
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Mustafa Sahin
- Department of Neurology, Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, 02115, USA
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Alexander Kolevzon
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Bruce D. Gelb
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| |
Collapse
|
12
|
Jia Y, Liu M, Liu H, Liang W, Zhu Q, Wang C, Chen Y, Gao Y, Liu Z, Cheng X. DSN1 may predict poor prognosis of lower-grade glioma patients and be a potential target for immunotherapy. Cancer Biol Ther 2024; 25:2425134. [PMID: 39555702 PMCID: PMC11581156 DOI: 10.1080/15384047.2024.2425134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 07/11/2023] [Accepted: 10/30/2024] [Indexed: 11/19/2024] Open
Abstract
DSN1 has been previously found to be positively correlated with various cancers. However, the effect of DSN1 or its methylation on the prognosis, molecular characteristics, and immune cell infiltration of low-grade glioma (LGG) has not yet been studied. We obtained 1046 LGG samples from the The Cancer Genome Atlas, The Chinese Glioma Genome Atlas (CGGA) microarray, and CGGA RNA-Seq databases. Bioinformatic methods (gene set enrichment analysis (GSEA), chi-square test, multivariate), and laboratory validation were used to investigate DSN1 in LGG. The expression levels of DSN1 mRNA and protein in LGG were substantially higher than those in normal brain tissue, and their expression was negatively regulated by methylation. The survival time of patients with low expression of DSN1 and cg12601032 hypermethylation was considerably prolonged. DSN1 was a risk factor, and of good diagnostic and prognostic value for LGG. Importantly, the expression of DSN1 is related to many types of tumor-infiltrating immune cells and has a positive correlation with PDL1. DSN1 promoted the activation of multiple cancer-related pathways, such as the cell cycle. Additionally, knockdown of DSN1 substantially inhibited the proliferation and invasion of LGG cells. To the best of our knowledge, this study is the first comprehensive analysis of the mechanism of DSN1 leading to poor prognosis of LGG, which provides a new perspective for revealing the pathogenesis of LGG. DSN1 or its methylation has diagnostic value for the prognosis of glioma, and may become a new biological target of anti-tumor immunotherapy.
Collapse
Affiliation(s)
- Yulong Jia
- Department of Neurosurgery, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, School of Clinical Medicine, Henan University, Zhengzhou, China
| | - Meiling Liu
- School of Clinical Medicine, Sanquan College of Xinxiang Medical University, Xinxiang, Henan, China
| | - Han Liu
- Department of Clinical Medicine, Medical College of Jinzhou Medical University. Taihe District, Jinzhou, Liaoning Province, China
| | - Wenjia Liang
- Henan Provincial People’s Hospital, People’s Hospital of Henan University, Zhengzhou, Henan Province, China
| | - Qingyun Zhu
- Henan Provincial People’s Hospital, People’s Hospital of Henan University, Zhengzhou, Henan Province, China
| | - Chao Wang
- Department of Neurobiology, School of Basic Medical Sciences, Harbin Medical University, Harbin, Heilongjiang, P. R. China
| | - Yake Chen
- School of Pharmacy, Xinxiang Medical University, Xinxiang, Henan, China
| | - Yanzheng Gao
- Department of Surgery of Spine and Spinal Cord, Henan Provincial People’s Hospital, Henan Province Intelligent orthopedic technology innovation and transformation International Joint Laboratory, Henan Key Laboratory for intelligent precision orthopedics, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, China
| | - Zhendong Liu
- Department of Surgery of Spine and Spinal Cord, Henan Provincial People’s Hospital, Henan Province Intelligent orthopedic technology innovation and transformation International Joint Laboratory, Henan Key Laboratory for intelligent precision orthopedics, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, China
| | - Xingbo Cheng
- Department of Surgery of Spine and Spinal Cord, Henan Provincial People’s Hospital, Henan Province Intelligent orthopedic technology innovation and transformation International Joint Laboratory, Henan Key Laboratory for intelligent precision orthopedics, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, China
| |
Collapse
|
13
|
Zou M, Feng Z, Hu K, Shu Y, Li T, Peng X, Chen L, Xiao L, Zhang S, Xiong T, Deng X, Peng J, Hao L. DCLRE1B as a novel prognostic biomarker associated with immune infiltration: a pancancer analysis. Sci Rep 2024; 14:31636. [PMID: 39738287 PMCID: PMC11685409 DOI: 10.1038/s41598-024-80603-y] [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: 05/18/2024] [Accepted: 11/19/2024] [Indexed: 01/01/2025] Open
Abstract
The DNA cross-link repair 1B (DCLRE1B) gene is involved in repairing cross-links between DNA strands, including those associated with Hoyeraal-Hreidarsson syndrome and congenital dyskeratosis. However, its role in tumours is not well understood. DCLRE1B expression profiles were examined in tumour tissues and normal tissues using TCGA, GTEx, and TARGET datasets. Additionally, we performed experiments with clinical melanoma samples to verify DCLRE1B expression patterns. We also performed pancancer analyses to investigate the diverse roles of DCLRE1B in the biological functions of various cancers. DCLRE1B exhibited distinct expression patterns and played crucial prognostic roles in most tumours. In particular, high expression of DCLRE1B in melanoma was significantly correlated with a poor prognosis and increased malignancy. DCLRE1B was also found to be associated with the immune landscape and various immune biomarkers and regulators. Furthermore, our analysis identified potential small molecules that could target DCLRE1B in different cancer types. The DCLRE1B gene may be involved in the development and occurrence of a variety of cancers. Additionally, DCLRE1B affects various tumour types not only by mediating DNA repair but also by shaping the differential immune microenvironment. In conclusion, our research offers fresh perspectives on the diagnosis and treatment of different types of cancers.
Collapse
Affiliation(s)
- Mi Zou
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Zuxi Feng
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Kaibo Hu
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Yuan Shu
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Ting Li
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Xiaogang Peng
- Jiangxi Province Key Laboratory of Molecular Medicine, the Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Leifeng Chen
- Department of General Surgery, Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Leyang Xiao
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Shouhua Zhang
- Department of General Surgery, Jiangxi Children's Hospital, Nanchang, 330006, Jiangxi Province, China
| | - Ting Xiong
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Xueqiang Deng
- Department of Rehabilitation, Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
| | - Jie Peng
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
- The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
| | - Liang Hao
- Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
- Institute of Orthopedics of Jiangxi Province, Nanchang, 330006, Jiangxi Province, China.
- Jiangxi Provincial Key Laboratory of Spine and Spinal Cord Disease, 330006, Nanchang, Jiangxi Province, China.
- Institute of Minimally Invasive Orthopedics, Nanchang University, 330006, Nanchang, Jiangxi Province, China.
| |
Collapse
|
14
|
Kim Y, Kim SW, Saul D, Neyazi M, Schmid M, Wakimoto H, Slaven N, Lee JH, Layton O, Wasson LK, Letendre JH, Xiao F, Ewoldt JK, Gkatzis K, Sommer P, Gobert B, Wiest-Daesslé N, McAfee Q, Singhal N, Lun M, Gorham JM, Arany Z, Sharma A, Toepfer CN, Oudit GY, Pu WT, Dickel DE, Pennacchio LA, Visel A, Chen CS, Seidman J, Seidman CE. Regulation of sarcomere formation and function in the healthy heart requires a titin intronic enhancer. J Clin Invest 2024; 135:e183353. [PMID: 39688912 PMCID: PMC11827849 DOI: 10.1172/jci183353] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 12/13/2024] [Indexed: 12/18/2024] Open
Abstract
Heterozygous truncating variants in the sarcomere protein titin (TTN) are the most common genetic cause of heart failure. To understand mechanisms that regulate abundant cardiomyocyte (CM) TTN expression, we characterized highly conserved intron 1 sequences that exhibited dynamic changes in chromatin accessibility during differentiation of human CMs from induced pluripotent stem cells (hiPSC-CMs). Homozygous deletion of these sequences in mice caused embryonic lethality, whereas heterozygous mice showed an allele-specific reduction in Ttn expression. A 296 bp fragment of this element, denoted E1, was sufficient to drive expression of a reporter gene in hiPSC-CMs. Deletion of E1 downregulated TTN expression, impaired sarcomerogenesis, and decreased contractility in hiPSC-CMs. Site-directed mutagenesis of predicted binding sites of NK2 homeobox 5 (NKX2-5) and myocyte enhancer factor 2 (MEF2) within E1 abolished its transcriptional activity. In embryonic mice expressing E1 reporter gene constructs, we validated in vivo cardiac-specific activity of E1 and the requirement for NKX2-5- and MEF2-binding sequences. Moreover, isogenic hiPSC-CMs containing a rare E1 variant in the predicted MEF2-binding motif that was identified in a patient with unexplained dilated cardiomyopathy (DCM) showed reduced TTN expression. Together, these discoveries define an essential, functional enhancer that regulates TTN expression. Manipulation of this element may advance therapeutic strategies to treat DCM caused by TTN haploinsufficiency.
Collapse
Affiliation(s)
- Yuri Kim
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Seong Won Kim
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - David Saul
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Meraj Neyazi
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Manuel Schmid
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
- German Heart Center, Technical University of Munich, Munich, Germany
| | - Hiroko Wakimoto
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Neil Slaven
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Joshua H. Lee
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Olivia Layton
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Lauren K. Wasson
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Justin H. Letendre
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Feng Xiao
- Department of Cardiology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Jourdan K. Ewoldt
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | | | | | | | | | - Quentin McAfee
- Cardiovascular Institute, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nandita Singhal
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Mingyue Lun
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Joshua M. Gorham
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Zolt Arany
- Cardiovascular Institute, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Arun Sharma
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Christopher N. Toepfer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine and
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Gavin Y. Oudit
- Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
- Mazankowski Alberta Heart Institute, Edmonton, Alberta, Canada
| | - William T. Pu
- Department of Cardiology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Harvard Stem Cell Institute, Cambridge, Pennsylvania, USA
| | - Diane E. Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Len A. Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
- US Department of Energy Joint Genome Institute, One Cyclotron Road, Berkeley, California, USA
- Comparative Biochemistry Program, UCB, Berkeley, California, USA
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
- US Department of Energy Joint Genome Institute, One Cyclotron Road, Berkeley, California, USA
- School of Natural Sciences, UCM, Merced, California, USA
| | - Christopher S. Chen
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - J.G. Seidman
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Christine E. Seidman
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
| |
Collapse
|
15
|
Zhou X, Zhou L, Qian F, Chen J, Zhang Y, Yu Z, Zhang J, Yang Y, Li Y, Song C, Wang Y, Shang D, Dong L, Zhu J, Li C, Wang Q. TFTG: A comprehensive database for human transcription factors and their targets. Comput Struct Biotechnol J 2024; 23:1877-1885. [PMID: 38707542 PMCID: PMC11068477 DOI: 10.1016/j.csbj.2024.04.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/15/2024] [Accepted: 04/15/2024] [Indexed: 05/07/2024] Open
Abstract
Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.
Collapse
Affiliation(s)
- Xinyuan Zhou
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- College of Artificial Intelligence and Big Data For Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Liwei Zhou
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Fengcui Qian
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Jiaxin Chen
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Yuexin Zhang
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Zhengmin Yu
- School of Computer, University of South China, Hengyang, Hunan 421001, China
| | - Jian Zhang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Yongsan Yang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Yanyu Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Chao Song
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Yuezhu Wang
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Desi Shang
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Longlong Dong
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Jiang Zhu
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China
| | - Chunquan Li
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Hunan Provincial Maternal and Child Health Care Hospital, National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Qiuyu Wang
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| |
Collapse
|
16
|
Ormond C, Ryan NM, Cap M, Byerley W, Corvin A, Heron EA. BICEP: Bayesian inference for rare genomic variant causality evaluation in pedigrees. Brief Bioinform 2024; 26:bbae624. [PMID: 39656772 PMCID: PMC11645550 DOI: 10.1093/bib/bbae624] [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: 06/18/2024] [Revised: 10/04/2024] [Accepted: 11/27/2024] [Indexed: 12/17/2024] Open
Abstract
Next-generation sequencing is widely applied to the investigation of pedigree data for gene discovery. However, identifying plausible disease-causing variants within a robust statistical framework is challenging. Here, we introduce BICEP: a Bayesian inference tool for rare variant causality evaluation in pedigree-based cohorts. BICEP calculates the posterior odds that a genomic variant is causal for a phenotype based on the variant cosegregation as well as a priori evidence such as deleteriousness and functional consequence. BICEP can correctly identify causal variants for phenotypes with both Mendelian and complex genetic architectures, outperforming existing methodologies. Additionally, BICEP can correctly down-weight common variants that are unlikely to be involved in phenotypic liability in the context of a pedigree, even if they have reasonable cosegregation patterns. The output metrics from BICEP allow for the quantitative comparison of variant causality within and across pedigrees, which is not possible with existing approaches.
Collapse
Affiliation(s)
- Cathal Ormond
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, St James’s Hospital, Dublin 8, Ireland
| | - Niamh M Ryan
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, St James’s Hospital, Dublin 8, Ireland
| | - Mathieu Cap
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, St James’s Hospital, Dublin 8, Ireland
| | - William Byerley
- Department of Psychiatry and Behavioral Sciences, University of California, 1550 Fourth Street, San Francisco, CA 94158, United States
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, St James’s Hospital, Dublin 8, Ireland
| | - Elizabeth A Heron
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, St James’s Hospital, Dublin 8, Ireland
| |
Collapse
|
17
|
Yu S, Ha H, Kim K. Integrated analysis of circRNA regulation with ADARB2 enrichment in inhibitory neurons. Comput Biol Med 2024; 182:109212. [PMID: 39341111 DOI: 10.1016/j.compbiomed.2024.109212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Revised: 08/28/2024] [Accepted: 09/24/2024] [Indexed: 09/30/2024]
Abstract
This study investigates the regulation of circular RNAs (circRNAs) with Adenosine Deaminase RNA Specific B2 (ADARB2) enrichment specifically in inhibitory neurons. Using an integrated analysis combining high-throughput sequencing and bioinformatics approaches, we identified a group of circRNAs that are potentially enhanced by ADARB2. Our findings highlight the pivotal role of ADARB2 in circRNA synthesis within inhibitory neurons, likely through its specific binding to precursor RNAs, which facilitates circRNA biogenesis.
Collapse
Affiliation(s)
- Suwan Yu
- Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Hongseok Ha
- Institute of Endemic Disease, Seoul National University Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Kwangsoo Kim
- Department of Medicine, College of Medicine, Seoul National University, Seoul, Republic of Korea; Department of Transdisciplinary Medicine, Institute of Convergence Medicine with Innovative Technology, Seoul National University Hospital, Seoul, Republic of Korea.
| |
Collapse
|
18
|
Bui VNV, Daugaard TF, Sorensen BS, Nielsen AL. Expression of the non-coding RNA nc886 facilitates the development of tyrosine kinase inhibitor resistance in EGFR-mutated non-small-cell lung cancer cells. Biochem Biophys Res Commun 2024; 731:150395. [PMID: 39024976 DOI: 10.1016/j.bbrc.2024.150395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 07/03/2024] [Accepted: 07/11/2024] [Indexed: 07/20/2024]
Abstract
Treatment of non-small-cell lung cancer (NSCLC) patients possessing EGFR-activating mutations with tyrosine kinase inhibitors (TKIs) can confer an initial promising response. However, TKI resistance inevitably arises. Numerous TKI resistance mechanisms are identified including EGFR secondary mutations, bypass receptor tyrosine kinase (RTK) signaling, and cellular transition e.g. epithelial-mesenchymal transition (EMT). To increase the knowledge of TKI resistance we performed an epigenetic screen to identify small non-coding (nc) genes with DNA methylation alterations in HCC827 NSCLC EGFR-mutated cells with acquired TKI resistance. We analyzed Infinium Methylation EPIC 850K Array data for DNA methylation changes present in both TKI-resistant HCC827 cells with EMT and MET-amplification. Hereby, we identified that the polymorphic maternal imprinted gene nc886 (vtRNA2-1) has a decrease in promoter DNA methylation in TKI-resistant cells. This epigenetic change was associated with an increase in the expression of nc886. The induction of EMT did not affect nc886 expression. CRISPR/Cas9-mediated distortion of the nc886 sequence increased the sensitivity of HCC827 cells towards TKI. Finally, nc886 sequence distortion hindered MET RTK activation and instead was EMT the endpoint TKI resistance mechanism. In conclusion, the expression of nc886 contributes to TKI resistance in the HCC827 NSCLC cell line by supporting cell survival and selection of the endpoint TKI resistance mechanism. We propose DNA methylation and expression changes for nc886 to constitute a novel TKI resistance contributing mechanism in NSCLC.
Collapse
MESH Headings
- Humans
- Carcinoma, Non-Small-Cell Lung/genetics
- Carcinoma, Non-Small-Cell Lung/drug therapy
- Carcinoma, Non-Small-Cell Lung/pathology
- Carcinoma, Non-Small-Cell Lung/metabolism
- Cell Line, Tumor
- DNA Methylation
- Drug Resistance, Neoplasm/genetics
- Epigenesis, Genetic/drug effects
- Epithelial-Mesenchymal Transition/genetics
- Epithelial-Mesenchymal Transition/drug effects
- ErbB Receptors/genetics
- ErbB Receptors/metabolism
- Gene Expression Regulation, Neoplastic/drug effects
- Lung Neoplasms/genetics
- Lung Neoplasms/drug therapy
- Lung Neoplasms/pathology
- Lung Neoplasms/metabolism
- Mutation
- RNA, Untranslated/genetics
- RNA, Untranslated/metabolism
- Tyrosine Kinase Inhibitors/pharmacology
- Tyrosine Kinase Inhibitors/therapeutic use
Collapse
Affiliation(s)
- Vivian N V Bui
- Department of Biomedicine, Aarhus University, 8000, Aarhus, Denmark.
| | - Tina F Daugaard
- Department of Biomedicine, Aarhus University, 8000, Aarhus, Denmark.
| | - Boe S Sorensen
- Department of Clinical Biochemistry, Aarhus University Hospital, 8200, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, 8200, Aarhus, Denmark.
| | - Anders L Nielsen
- Department of Biomedicine, Aarhus University, 8000, Aarhus, Denmark.
| |
Collapse
|
19
|
Bozkurt-Yozgatli T, Lun MY, Bengtsson JD, Sezerman U, Chinn IK, Coban-Akdemir Z, Carvalho CMB. Investigation of a Pathogenic Inversion in UNC13D and Comprehensive Analysis of Chromosomal Inversions Across Diverse Datasets. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.10.28.24315942. [PMID: 39574843 PMCID: PMC11581086 DOI: 10.1101/2024.10.28.24315942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
Inversions are known contributors to the pathogenesis of genetic diseases. Identifying inversions poses significant challenges, making it one of the most demanding structural variants (SVs) to detect and interpret. Recent advancements in sequencing technologies and the development of publicly available SV datasets have substantially enhanced our capability to explore inversions. However, a cross-comparison in those datasets remains unexplored. In this study, we reported a proband with familial hemophagocytic lymphohistiocytosis type-3 carrying c.1389+1G>A in trans with NC_000017.11:75576992_75829587inv disrupting UNC13D , an inversion present in 0.006345% of individuals in gnomAD(v4.0). Based on this result, we investigate the features of potentially pathogenic inversions in public datasets. 98.9% of inversions are rare in gnomAD, and they disrupt 5% of protein-coding genes associated with a phenotype in OMIM. We then conducted a comparative analysis of the datasets, including gnomAD, DGV, and 1KGP, and two recent studies from the Human Genome Structural Variation Consortium revealed common and dataset-specific inversion characteristics suggesting methodology detection biases. Next, we investigated the genetic features of inversions disrupting the protein-coding genes by classifying the intersections between them into three categories. We found that most of the protein-coding genes in OMIM disrupted by inversions are associated with autosomal recessive phenotypes regardless of categories supporting the hypothesis that inversions in trans with other variants are hidden causes of monogenic diseases. This effort aims to fill the gap in our understanding of the molecular characteristics of inversions with low frequency in the population and highlight the importance of identifying them in rare disease studies.
Collapse
|
20
|
Burkert M, Blanc E, Thiessen N, Weber C, Toedling J, Monti R, Dombrowe VM, Stella de Biase M, Kaufmann TL, Haase K, Waszak SM, Eggert A, Beule D, Schulte JH, Ohler U, Schwarz RF. Copy-number dosage regulates telomere maintenance and disease-associated pathways in neuroblastoma. iScience 2024; 27:110918. [PMID: 39635126 PMCID: PMC11615189 DOI: 10.1016/j.isci.2024.110918] [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: 02/17/2024] [Revised: 07/12/2024] [Accepted: 09/06/2024] [Indexed: 12/07/2024] Open
Abstract
Telomere maintenance in neuroblastoma is linked to poor outcome and caused by either telomerase reverse transcriptase (TERT) activation or through alternative lengthening of telomeres (ALT). In contrast to TERT activation, commonly caused by genomic rearrangements or MYCN amplification, ALT is less well understood. Alterations at the ATRX locus are key drivers of ALT but only present in ∼50% of ALT tumors. To identify potential new pathways to telomere maintenance, we investigate allele-specific gene dosage effects from whole genomes and transcriptomes in 115 primary neuroblastomas. We show that copy-number dosage deregulates telomere maintenance, genomic stability, and neuronal pathways and identify upregulation of variants of histone H3 and H2A as a potential alternative pathway to ALT. We investigate the interplay between TERT activation, overexpression and copy-number dosage and reveal loss of imprinting at the RTL1 gene associated with poor clinical outcome. These results highlight the importance of gene dosage in key oncogenic mechanisms in neuroblastoma.
Collapse
Affiliation(s)
- Martin Burkert
- Department of Biology, Humboldt University, Berlin, Germany
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Eric Blanc
- Core Unit Bioinformatics, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, Berlin, Germany
| | - Nina Thiessen
- Core Unit Bioinformatics, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, Berlin, Germany
| | | | - Joern Toedling
- Department of Pediatric Oncology/Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Remo Monti
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Victoria M. Dombrowe
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Maria Stella de Biase
- Department of Biology, Humboldt University, Berlin, Germany
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Tom L. Kaufmann
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
- Department of Electrical Engineering & Computer Science, Technische Universität Berlin, Marchstr. 23, 10587 Berlin, Germany
| | - Kerstin Haase
- Department of Pediatric Oncology/Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Sebastian M. Waszak
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Pediatric Research, Division of Pediatric and Adolescent Medicine, Rikshospitalet, Oslo University Hospital, Oslo, Norway
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Angelika Eggert
- Department of Pediatric Oncology/Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Dieter Beule
- Core Unit Bioinformatics, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, Berlin, Germany
| | - Johannes H. Schulte
- Department of Pediatric Oncology/Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Uwe Ohler
- Department of Biology, Humboldt University, Berlin, Germany
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Roland F. Schwarz
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| |
Collapse
|
21
|
薛 恩, 陈 曦, 王 雪, 王 斯, 王 梦, 李 劲, 秦 雪, 武 轶, 李 楠, 李 静, 周 治, 朱 洪, 吴 涛, 陈 大, 胡 永. [Single nucleotide polymorphism heritability of non-syndromic cleft lip with or without cleft palate in Chinese population]. BEIJING DA XUE XUE BAO. YI XUE BAN = JOURNAL OF PEKING UNIVERSITY. HEALTH SCIENCES 2024; 56:775-780. [PMID: 39397453 PMCID: PMC11480541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Indexed: 10/15/2024]
Abstract
OBJECTIVE To delve into the intricate relationship between common genetic variations across the entire genome and the risk of non-syndromic cleft lip with or without cleft palate (NSCL/P). METHODS Utilizing summary statistics data from genome-wide association studies (GWAS), a thorough investigation to evaluate the impact of common variations on the genome were undertook. This involved assessing single nucleotide polymorphism (SNP) heritability across the entire genome, as well as within specific genomic regions. To ensure the robustness of our analysis, stringent quality control measures were applied to the GWAS summary statistics data. Criteria for inclusion encompassed the absence of missing values, a minor allele frequency ≥1%, P-values falling within the range of 0 to 1, and clear SNP strand orientation. SNP meeting these stringent criteria were then meticulously included in our analysis. The SNP heritability of NSCL/P was calculated using linkage disequilibrium score regression. Additionally, hierarchical linkage disequilibrium score regression to partition SNP heritability within coding regions, promoters, introns, enhancers, and super enhancers were employed, and the enrichment levels within different genomic regions using LDSC (v1.0.1) software were further elucidated. RESULTS Our study drew upon GWAS summary statistics data obtained from 806 NSCL/P trios, comprising a total of 2 418 individuals from the Chinese population. Following rigorous quality control procedures, 490 593 out of 492 993 SNP were deemed suitable for inclusion in SNP heritability calculations. The observed SNP heritability of NSCL/P was 0.55 (95%CI: 0.28-0.82). Adjusting for the elevated disease pre-valence within our sample, the SNP heritability scaled down to 0.37 (95%CI: 0.19-0.55) based on the prevalence observed in the general Chinese population. Notably, our enrichment analysis unveiled significant enrichment of SNP heritability within enhancer regions (15.70, P=0.04) and super enhancer regions (3.18, P=0.03). CONCLUSION Our study sheds light on the intricate interplay between common genetic variations and the risk of NSCL/P in the Chinese population. By elucidating the SNP heritability landscape across different genomic regions, we contribute valuable insights into the genetic basis of NSCL/P. The significant enrichment of SNP heritability within enhancer and super enhancer regions underscores the potential role of these regulatory elements in shaping the genetic susceptibility to NSCL/P. This paves the way for further research aimed at uncovering novel genetic pathogenic factors underlying NSCL/P pathogenesis.
Collapse
Affiliation(s)
- 恩慈 薛
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 曦 陈
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 雪珩 王
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 斯悦 王
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 梦莹 王
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 劲 李
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 雪英 秦
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 轶群 武
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 楠 李
- 北京大学口腔医学院口腔颌面外科,北京 100081Department of Oral and Maxillofacial Surgery, Peking University School of Stomatology, Beijing 100081, China
| | - 静 李
- 北京大学口腔医学院儿童口腔科,北京 100081Department of Pediatric Dentistry, Peking University School of Stomatology, Beijing 100081, China
| | - 治波 周
- 北京大学口腔医学院口腔颌面外科,北京 100081Department of Oral and Maxillofacial Surgery, Peking University School of Stomatology, Beijing 100081, China
| | - 洪平 朱
- 北京大学口腔医学院口腔颌面外科,北京 100081Department of Oral and Maxillofacial Surgery, Peking University School of Stomatology, Beijing 100081, China
| | - 涛 吴
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 大方 陈
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 永华 胡
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| |
Collapse
|
22
|
Treutlein J, Löhlein S, Einenkel KE, Picotin R, Diekhof EK, Gruber O. Association of Unc-51-like Kinase 4 ( ULK4) with the reactivity of the extended reward system in response to conditioned stimuli. World J Biol Psychiatry 2024; 25:443-450. [PMID: 39185807 DOI: 10.1080/15622975.2024.2393381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 08/05/2024] [Accepted: 08/13/2024] [Indexed: 08/27/2024]
Abstract
OBJECTIVES ULK4 is an established candidate gene for mental disorders and antipsychotic treatment response. We investigated the association of functional genetic variation at the ULK4 locus with the human extended dopaminergic reward system using fMRI during the performance of a well-established reward paradigm. METHODS Two hundred and thirty-four patients were included in this study. Association of genetic variation in the ULK4 gene with reward system functioning were determined using the Desire-Reason-Dilemma (DRD) paradigm which allows to assess brain activation in response to conditioned reward stimuli. RESULTS Variant prioritisation revealed the strongest functional signatures for the ULK4 variant rs17215589, coding for amino acid exchange Ala715Thr. For rs17215589 minor allele carriers, we detected increased activation responses to conditioned reward stimuli in the ventral tegmental area, nucleus accumbens and several cortical brain regions of the extended reward system. CONCLUSIONS Our findings provide further evidence in humans that genetic variation in ULK4 may increase the vulnerability to mental disorders, by modulating the extended reward system function. Future studies are needed to confirm the modulation of the extended reward system by ULK4 and to specify the role of this mechanism in the pathogenesis of psychiatric disorders.
Collapse
Affiliation(s)
- Jens Treutlein
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Simone Löhlein
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
- Institute of Flight Systems, University of the Bundeswehr Munich, Munich, Germany
| | - Karolin E Einenkel
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Rosanne Picotin
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Esther K Diekhof
- Institute for Cell- and Systemsbiology of Animals, Department of Biology, Neuroendocrinology Unit, Universität Hamburg, Hamburg, Germany
- Department of Psychiatry and Psychotherapy, Center for Translational Research in Systems Neuroscience and Clinical Psychiatry, Georg August University Göttingen, Göttingen, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| |
Collapse
|
23
|
Armstrong EE, Mooney JA, Solari KA, Kim BY, Barsh GS, Grant VB, Greenbaum G, Kaelin CB, Panchenko K, Pickrell JK, Rosenberg N, Ryder OA, Yokoyama T, Ramakrishnan U, Petrov DA, Hadly EA. Unraveling the genomic diversity and admixture history of captive tigers in the United States. Proc Natl Acad Sci U S A 2024; 121:e2402924121. [PMID: 39298482 PMCID: PMC11441546 DOI: 10.1073/pnas.2402924121] [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: 02/20/2024] [Accepted: 08/09/2024] [Indexed: 09/21/2024] Open
Abstract
Genomic studies of endangered species have primarily focused on describing diversity patterns and resolving phylogenetic relationships, with the overarching goal of informing conservation efforts. However, few studies have investigated genomic diversity housed in captive populations. For tigers (Panthera tigris), captive individuals vastly outnumber those in the wild, but their diversity remains largely unexplored. Privately owned captive tiger populations have remained an enigma in the conservation community, with some believing that these individuals are severely inbred, while others believe they may be a source of now-extinct diversity. Here, we present a large-scale genetic study of the private (non-zoo) captive tiger population in the United States, also known as "Generic" tigers. We find that the Generic tiger population has an admixture fingerprint comprising all six extant wild tiger subspecies. Of the 138 Generic individuals sequenced for the purpose of this study, no individual had ancestry from only one subspecies. We show that the Generic tiger population has a comparable amount of genetic diversity relative to most wild subspecies, few private variants, and fewer deleterious mutations. We observe inbreeding coefficients similar to wild populations, although there are some individuals within both the Generic and wild populations that are substantially inbred. Additionally, we develop a reference panel for tigers that can be used with imputation to accurately distinguish individuals and assign ancestry with ultralow coverage (0.25×) data. By providing a cost-effective alternative to whole-genome sequencing (WGS), the reference panel provides a resource to assist in tiger conservation efforts for both ex- and in situ populations.
Collapse
Affiliation(s)
| | - Jazlyn A. Mooney
- Department of Biology, Stanford University, Stanford, CA94305
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA90089
| | | | - Bernard Y. Kim
- Department of Biology, Stanford University, Stanford, CA94305
| | - Gregory S. Barsh
- HudsonAlpha Institute for Biotechnology, Huntsville, AL35806
- Department of Genetics, School of Medine, Stanford University, Stanford, CA94305
| | | | - Gili Greenbaum
- Department of Ecology, Evolution & Behavior, The Hebrew University of Jerusalem, Jerusalem9190500, Israel
| | | | - Katya Panchenko
- Department of Biology, Stanford University, Stanford, CA94305
| | | | - Noah Rosenberg
- Department of Biology, Stanford University, Stanford, CA94305
| | | | - Tsuya Yokoyama
- Department of Biology, Stanford University, Stanford, CA94305
| | - Uma Ramakrishnan
- National Centre for Biological Sciences, Tata Institute for Fundamental Research, Bangalore560065, India
| | - Dmitri A. Petrov
- Department of Biology, Stanford University, Stanford, CA94305
- Chan Zuckerberg BioHub, San Francisco, CA94158
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA94305
| | - Elizabeth A. Hadly
- Department of Biology, Stanford University, Stanford, CA94305
- Department of Earth System Science, Stanford University, Stanford, CA94305
- Woods Institute for the Environment, Stanford University, Stanford, CA94305
- Center for Innovation in Global Health, Stanford University, Stanford, CA94305
| |
Collapse
|
24
|
Whited AM, Jungreis I, Allen J, Cleveland CL, Mudge JM, Kellis M, Rinn JL, Hough LE. Biophysical characterization of high-confidence, small human proteins. BIOPHYSICAL REPORTS 2024; 4:100167. [PMID: 38909903 PMCID: PMC11305224 DOI: 10.1016/j.bpr.2024.100167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 04/09/2024] [Accepted: 06/20/2024] [Indexed: 06/25/2024]
Abstract
Significant efforts have been made to characterize the biophysical properties of proteins. Small proteins have received less attention because their annotation has historically been less reliable. However, recent improvements in sequencing, proteomics, and bioinformatics techniques have led to the high-confidence annotation of small open reading frames (smORFs) that encode for functional proteins, producing smORF-encoded proteins (SEPs). SEPs have been found to perform critical functions in several species, including humans. While significant efforts have been made to annotate SEPs, less attention has been given to the biophysical properties of these proteins. We characterized the distributions of predicted and curated biophysical properties, including sequence composition, structure, localization, function, and disease association of a conservative list of previously identified human SEPs. We found significant differences between SEPs and both larger proteins and control sets. In addition, we provide an example of how our characterization of biophysical properties can contribute to distinguishing protein-coding smORFs from noncoding ones in otherwise ambiguous cases.
Collapse
Affiliation(s)
- A M Whited
- BioFrontiers Institute, University of Colorado, Boulder, Colorado
| | - Irwin Jungreis
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts; MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts
| | - Jeffre Allen
- BioFrontiers Institute, University of Colorado, Boulder, Colorado; Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado
| | | | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts; MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts
| | - John L Rinn
- BioFrontiers Institute, University of Colorado, Boulder, Colorado; Department of Biochemistry, University of Colorado Boulder, Boulder, Colorado
| | - Loren E Hough
- BioFrontiers Institute, University of Colorado, Boulder, Colorado; Department of Physics, University of Colorado Boulder, Boulder, Colorado.
| |
Collapse
|
25
|
Cornish AJ, Gruber AJ, Kinnersley B, Chubb D, Frangou A, Caravagna G, Noyvert B, Lakatos E, Wood HM, Thorn S, Culliford R, Arnedo-Pac C, Househam J, Cross W, Sud A, Law P, Leathlobhair MN, Hawari A, Woolley C, Sherwood K, Feeley N, Gül G, Fernandez-Tajes J, Zapata L, Alexandrov LB, Murugaesu N, Sosinsky A, Mitchell J, Lopez-Bigas N, Quirke P, Church DN, Tomlinson IPM, Sottoriva A, Graham TA, Wedge DC, Houlston RS. The genomic landscape of 2,023 colorectal cancers. Nature 2024; 633:127-136. [PMID: 39112709 PMCID: PMC11374690 DOI: 10.1038/s41586-024-07747-9] [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: 11/14/2022] [Accepted: 06/24/2024] [Indexed: 08/17/2024]
Abstract
Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2-9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichia colipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11-13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care.
Collapse
Affiliation(s)
- Alex J Cornish
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Andreas J Gruber
- Department of Biology, University of Konstanz, Konstanz, Germany
- Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Ben Kinnersley
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
- University College London Cancer Institute, London, UK
| | - Daniel Chubb
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Anna Frangou
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany
| | - Giulio Caravagna
- Department of Mathematics and Geosciences, University of Trieste, Trieste, Italy
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Boris Noyvert
- Cancer Research UK Centre and Centre for Computational Biology, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Eszter Lakatos
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Henry M Wood
- Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - Steve Thorn
- Department of Oncology, University of Oxford, Oxford, UK
| | - Richard Culliford
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Claudia Arnedo-Pac
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Jacob Househam
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - William Cross
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
- Research Department of Pathology, University College London, UCL Cancer Institute, London, UK
| | - Amit Sud
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Philip Law
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | | | - Aliah Hawari
- Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Connor Woolley
- Department of Oncology, University of Oxford, Oxford, UK
| | - Kitty Sherwood
- Department of Oncology, University of Oxford, Oxford, UK
- Edinburgh Cancer Research, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Nathalie Feeley
- Department of Oncology, University of Oxford, Oxford, UK
- Edinburgh Cancer Research, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Güler Gül
- Edinburgh Cancer Research, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Luis Zapata
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Ludmil B Alexandrov
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA
- Department of Bioengineering, UC San Diego, La Jolla, CA, USA
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Nirupa Murugaesu
- Genomics England, William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Alona Sosinsky
- Genomics England, William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Jonathan Mitchell
- Genomics England, William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Philip Quirke
- Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - David N Church
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford NIHR Comprehensive Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Andrea Sottoriva
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Trevor A Graham
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - David C Wedge
- Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Richard S Houlston
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| |
Collapse
|
26
|
Kovacs AS, Portelli S, Silk M, Rodrigues CHM, Ascher DB. MTR3D-AF2: Expanding the coverage of spatially derived missense tolerance scores across the human proteome using AlphaFold2. Protein Sci 2024; 33:e5112. [PMID: 39031445 PMCID: PMC11258768 DOI: 10.1002/pro.5112] [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: 12/17/2023] [Revised: 06/24/2024] [Accepted: 06/26/2024] [Indexed: 07/22/2024]
Abstract
The missense tolerance ratio (MTR) was developed as a novel approach to assess the deleteriousness of variants. Its three-dimensional successor, MTR3D, was demonstrated powerful at discriminating pathogenic from benign variants. However, its reliance on experimental structures and homologs limited its coverage of the proteome. We have now utilized AlphaFold2 models to develop MTR3D-AF2, which covers 89.31% of proteins and 85.39% of residues across the human proteome. This work has improved MTR3D's ability to distinguish clinically established pathogenic from benign variants. MTR3D-AF2 is freely available as an interactive web server at https://biosig.lab.uq.edu.au/mtr3daf2/.
Collapse
Affiliation(s)
- Aaron S. Kovacs
- The Australian Center for Ecogenomics, School of Chemistry and Molecular BiosciencesThe University of QueenslandBrisbaneQueenslandAustralia
| | - Stephanie Portelli
- The Australian Center for Ecogenomics, School of Chemistry and Molecular BiosciencesThe University of QueenslandBrisbaneQueenslandAustralia
- Computational Biology and Clinical InformaticsBaker Heart and Diabetes InstituteMelbourneAustralia
| | - Michael Silk
- Centre for Population Genomics, Murdoch Children's Research InstituteMelbourneAustralia
- Systems and Computational BiologyBio21 Institute, The University of MelbourneMelbourneAustralia
| | - Carlos H. M. Rodrigues
- The Australian Center for Ecogenomics, School of Chemistry and Molecular BiosciencesThe University of QueenslandBrisbaneQueenslandAustralia
- Computational Biology and Clinical InformaticsBaker Heart and Diabetes InstituteMelbourneAustralia
| | - David B. Ascher
- The Australian Center for Ecogenomics, School of Chemistry and Molecular BiosciencesThe University of QueenslandBrisbaneQueenslandAustralia
- Computational Biology and Clinical InformaticsBaker Heart and Diabetes InstituteMelbourneAustralia
- Systems and Computational BiologyBio21 Institute, The University of MelbourneMelbourneAustralia
| |
Collapse
|
27
|
Ormond C, Ryan NM, Byerley W, Heron EA, Corvin A. Investigating copy number variants in schizophrenia pedigrees using a new consensus pipeline called PECAN. Sci Rep 2024; 14:17518. [PMID: 39080331 PMCID: PMC11289470 DOI: 10.1038/s41598-024-66021-0] [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: 12/19/2023] [Accepted: 06/26/2024] [Indexed: 08/02/2024] Open
Abstract
Copy number variants (CNVs) have been implicated in many human diseases, including psychiatric disorders. Whole genome sequencing offers advantages in CNV calling compared to previous array-based methods. Here we present a robust and transparent CNV calling pipeline, PECAN (PEdigree Copy number vAriaNt calling), for short-read, whole genome sequencing data, comprised of a novel combination of four calling methods and structural variant genotyping. This method is scalable and can incorporate pedigree information to retain lower-confidence CNVs that would otherwise be discarded. We have robustly benchmarked PECAN using gold-standard CNV calls for two well-established evaluation samples, NA12878 and HG002, showing that PECAN performs with high precision and recall on both datasets, outperforming another pedigree-based CNV calling pipeline. As part of this work, we provide a list of high-confidence gold standard CNVs for the NA12878 reference sample, curated from multiple studies. We applied PECAN to a collection of pedigrees multiply affected with schizophrenia and identified a rare deletion that perfectly co-segregates with schizophrenia in one of the pedigrees. The CNV overlaps the gene PITRM1, which has been implicated in a complex phenotype including ataxia, developmental delay, and schizophrenia-like episodes in affected adults.
Collapse
Affiliation(s)
- Cathal Ormond
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, James' Street, Dublin 8, Ireland
| | - Niamh M Ryan
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, James' Street, Dublin 8, Ireland
| | - William Byerley
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Elizabeth A Heron
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, James' Street, Dublin 8, Ireland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity Centre for Health Sciences, Trinity College Dublin, James' Street, Dublin 8, Ireland.
| |
Collapse
|
28
|
Bogdanov A, Sokolova M, Bakloushinskaya I. Specificity of Key Sex Determination Genes in a Mammal with Ovotestes: The European Mole Talpa europaea. Animals (Basel) 2024; 14:2180. [PMID: 39123706 PMCID: PMC11311037 DOI: 10.3390/ani14152180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/19/2024] [Accepted: 07/24/2024] [Indexed: 08/12/2024] Open
Abstract
Here, for the first time, the structure of genes involved in sex determination in mammals (full Sry and partial Rspo1, Eif2s3x, and Eif2s3y) was analyzed for the European mole Talpa europaea with ovotestes in females. We confirmed male-specificity for Eif2s3y and Sry. Five exons were revealed for Rspo1 and the deep similarity with the structure of this gene in T. occidentalis was proved. The most intriguing result was obtained for the Sry gene, which, in placental mammals, initiates male development. We described two exons for this canonically single-exon gene: the first (initial) exon is only 15 bp while the second exon includes 450 bp. The exons are divided by an extended intron of about 1894 bp, including the fragment of the LINE retroposon. Moreover, in chromatogram fragments, which correspond to intron and DNA areas, flanking both exons, we revealed double peaks, similar to heterozygous nucleotide sites of autosomal genes. This may indicate the existence of two or more copies of the Sry gene. Proof of copies requires an additional in-depth study. We hypothesize that unusual structure and possible supernumerary copies of Sry may be involved in ovotestes formation.
Collapse
Affiliation(s)
- Alexey Bogdanov
- Koltzov Institute of Developmental Biology, Russian Academy of Sciences, 119334 Moscow, Russia; (A.B.); (M.S.)
| | - Maria Sokolova
- Koltzov Institute of Developmental Biology, Russian Academy of Sciences, 119334 Moscow, Russia; (A.B.); (M.S.)
- Biological Department, Lomonosov State University, 119234 Moscow, Russia
| | - Irina Bakloushinskaya
- Koltzov Institute of Developmental Biology, Russian Academy of Sciences, 119334 Moscow, Russia; (A.B.); (M.S.)
| |
Collapse
|
29
|
Karagianni K, Dafou D, Xanthopoulos K, Sklaviadis T, Kanata E. RNA editing regulates glutamatergic synapses in the frontal cortex of a molecular subtype of Amyotrophic Lateral Sclerosis. Mol Med 2024; 30:101. [PMID: 38997636 PMCID: PMC11241978 DOI: 10.1186/s10020-024-00863-2] [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: 04/04/2024] [Accepted: 06/12/2024] [Indexed: 07/14/2024] Open
Abstract
BACKGROUND Amyotrophic Lateral Sclerosis (ALS) is a highly heterogenous neurodegenerative disorder that primarily affects upper and lower motor neurons, affecting additional cell types and brain regions. Underlying molecular mechanisms are still elusive, in part due to disease heterogeneity. Molecular disease subtyping through integrative analyses including RNA editing profiling is a novel approach for identification of molecular networks involved in pathogenesis. METHODS We aimed to highlight the role of RNA editing in ALS, focusing on the frontal cortex and the prevalent molecular disease subtype (ALS-Ox), previously determined by transcriptomic profile stratification. We established global RNA editing (editome) and gene expression (transcriptome) profiles in control and ALS-Ox cases, utilizing publicly available RNA-seq data (GSE153960) and an in-house analysis pipeline. Functional annotation and pathway analyses identified molecular processes affected by RNA editing alterations. Pearson correlation analyses assessed RNA editing effects on expression. Similar analyses on additional ALS-Ox and control samples (GSE124439) were performed for verification. Targeted re-sequencing and qRT-PCR analysis targeting CACNA1C, were performed using frontal cortex tissue from ALS and control samples (n = 3 samples/group). RESULTS We identified reduced global RNA editing in the frontal cortex of ALS-Ox cases. Differentially edited transcripts are enriched in synapses, particularly in the glutamatergic synapse pathway. Bioinformatic analyses on additional ALS-Ox and control RNA-seq data verified these findings. We identified increased recoding at the Q621R site in the GRIK2 transcript and determined positive correlations between RNA editing and gene expression alterations in ionotropic receptor subunits GRIA2, GRIA3 and the CACNA1C transcript, which encodes the pore forming subunit of a post-synaptic L-type calcium channel. Experimental data verified RNA editing alterations and editing-expression correlation in CACNA1C, highlighting CACNA1C as a target for further study. CONCLUSIONS We provide evidence on the involvement of RNA editing in the frontal cortex of an ALS molecular subtype, highlighting a modulatory role mediated though recoding and gene expression regulation on glutamatergic synapse related transcripts. We report RNA editing effects in disease-related transcripts and validated editing alterations in CACNA1C. Our study provides targets for further functional studies that could shed light in underlying disease mechanisms enabling novel therapeutic approaches.
Collapse
Affiliation(s)
- Korina Karagianni
- Department of Genetics, Development, and Molecular Biology, School of Biology, Aristotle University of Thessaloniki, 541 24, Thessaloniki, Greece
| | - Dimitra Dafou
- Department of Genetics, Development, and Molecular Biology, School of Biology, Aristotle University of Thessaloniki, 541 24, Thessaloniki, Greece
| | - Konstantinos Xanthopoulos
- Laboratory of Pharmacology, Department of Pharmacy, School of Health Sciences, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, 57001, Thermi, Greece
| | - Theodoros Sklaviadis
- Laboratory of Pharmacology, Department of Pharmacy, School of Health Sciences, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
| | - Eirini Kanata
- Laboratory of Pharmacology, Department of Pharmacy, School of Health Sciences, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
| |
Collapse
|
30
|
Sun K, Liu X, Lan X. A single-cell atlas of chromatin accessibility in mouse organogenesis. Nat Cell Biol 2024; 26:1200-1211. [PMID: 38977846 DOI: 10.1038/s41556-024-01435-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/29/2024] [Indexed: 07/10/2024]
Abstract
Organogenesis is a highly complex and precisely regulated process. Here we profiled the chromatin accessibility in >350,000 cells derived from 13 mouse embryos at four developmental stages from embryonic day (E) 10.5 to E13.5 by SPATAC-seq in a single experiment. The resulting atlas revealed the status of 830,873 candidate cis-regulatory elements in 43 major cell types. By integrating the chromatin accessibility atlas with the previous transcriptomic dataset, we characterized cis-regulatory sequences and transcription factors associated with cell fate commitment, such as Nr5a2 in the development of gastrointestinal tract, which was preliminarily supported by the in vivo experiment in zebrafish. Finally, we integrated this atlas with the previous single-cell chromatin accessibility dataset from 13 adult mouse tissues to delineate the developmental stage-specific gene regulatory programmes within and across different cell types and identify potential molecular switches throughout lineage development. This comprehensive dataset provides a foundation for exploring transcriptional regulation in organogenesis.
Collapse
Affiliation(s)
- Keyong Sun
- School of Medicine, Tsinghua University, Beijing, China
- Peking-Tsinghua-NIBS Joint Graduate Program, Tsinghua University, Beijing, China
- Tsinghua-Peking Center for Life Sciences, Beijing, China
| | - Xin Liu
- Tsinghua-Peking Center for Life Sciences, Beijing, China
- School of Life Sciences, Tsinghua University, Beijing, China
| | - Xun Lan
- School of Medicine, Tsinghua University, Beijing, China.
- Peking-Tsinghua-NIBS Joint Graduate Program, Tsinghua University, Beijing, China.
- Tsinghua-Peking Center for Life Sciences, Beijing, China.
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China.
| |
Collapse
|
31
|
Puvvula J, Braun JM, DeFranco EA, Ho SM, Leung YK, Huang S, Zhang X, Vuong AM, Kim SS, Percy Z, Calafat AM, Botelho JC, Chen A. Gestational exposure to environmental chemicals and epigenetic alterations in the placenta and cord blood mononuclear cells. EPIGENETICS COMMUNICATIONS 2024; 4:4. [PMID: 38962689 PMCID: PMC11217138 DOI: 10.1186/s43682-024-00027-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 06/24/2024] [Indexed: 07/05/2024]
Abstract
Background Exposure to environmental chemicals such as phthalates, phenols, and polycyclic aromatic hydrocarbons (PAHs) during pregnancy can increase the risk of adverse newborn outcomes. We explored the associations between maternal exposure to select environmental chemicals and DNA methylation in cord blood mononuclear cells (CBMC) and placental tissue (maternal and fetal sides) to identify potential mechanisms underlying these associations. Method This study included 75 pregnant individuals who planned to give birth at the University of Cincinnati Hospital between 2014 and 2017. Maternal urine samples during the delivery visit were collected and analyzed for 37 biomarkers of phenols (12), phthalates (13), phthalate replacements (4), and PAHs (8). Cord blood and placenta tissue (maternal and fetal sides) were also collected to measure the DNA methylation intensities using the Infinium HumanMethylation450K BeadChip. We used linear regression, adjusting for potential confounders, to assess CpG-specific methylation changes in CBMC (n = 54) and placenta [fetal (n = 67) and maternal (n = 68) sides] associated with gestational chemical exposures (29 of 37 biomarkers measured in this study). To account for multiple testing, we used a false discovery rate q-values < 0.05 and presented results by limiting results with a genomic inflation factor of 1±0.5. Additionally, gene set enrichment analysis was conducted using the Kyoto Encyclopedia of Genes and Genomics pathways. Results Among the 29 chemical biomarkers assessed for differential methylation, maternal concentrations of PAH metabolites (1-hydroxynaphthalene, 2-hydroxyfluorene, 4-hydroxyphenanthrene, 1-hydroxypyrene), monocarboxyisononyl phthalate, mono-3-carboxypropyl phthalate, and bisphenol A were associated with altered methylation in placenta (maternal or fetal side). Among exposure biomarkers associated with epigenetic changes, 1-hydroxynaphthalene, and mono-3-carboxypropyl phthalate were consistently associated with differential CpG methylation in the placenta. Gene enrichment analysis indicated that maternal 1-hydroxynaphthalene was associated with lipid metabolism and cellular processes of the placenta. Additionally, mono-3-carboxypropyl phthalate was associated with organismal systems and genetic information processing of the placenta. Conclusion Among the 29 chemical biomarkers assessed during delivery, 1-hydroxynaphthalene and mono-3-carboxypropyl phthalate were associated with DNA methylation in the placenta. Supplementary Information The online version contains supplementary material available at 10.1186/s43682-024-00027-7.
Collapse
Affiliation(s)
- Jagadeesh Puvvula
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Joseph M. Braun
- Department of Epidemiology, Brown University, Providence, RI USA
| | - Emily A. DeFranco
- Department of Obstetrics and Gynecology, College of Medicine, University of Kentucky, Lexington, KY USA
| | - Shuk-Mei Ho
- Department of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR USA
| | - Yuet-Kin Leung
- Department of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR USA
| | - Shouxiong Huang
- Pathogen-Host Interaction Program, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Xiang Zhang
- Department of Environmental & Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH USA
| | - Ann M. Vuong
- Department of Epidemiology and Biostatistics, School of Public Health, University of Nevada Las Vegas, Las Vegas, NV USA
| | - Stephani S. Kim
- Health Research, Battelle Memorial Institute, Columbus, OH USA
| | - Zana Percy
- Department of Environmental & Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH USA
| | - Antonia M. Calafat
- National Center for Environmental Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA USA
| | - Julianne C. Botelho
- National Center for Environmental Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA USA
| | - Aimin Chen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| |
Collapse
|
32
|
Schuy J, Sæther KB, Lisfeld J, Ek M, Grochowski CM, Lun MY, Hastie A, Rudolph S, Fuchs S, Neveling K, Hempel M, Hoischen A, Pettersson M, Carvalho CM, Eisfeldt J, Lindstrand A. A combination of long- and short-read genomics reveals frequent p-arm breakpoints within chromosome 21 complex genomic rearrangements. GENETICS IN MEDICINE OPEN 2024; 2:101863. [PMID: 39669604 PMCID: PMC11613786 DOI: 10.1016/j.gimo.2024.101863] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 06/18/2024] [Accepted: 06/20/2024] [Indexed: 12/14/2024]
Abstract
Purpose Although chromosome 21 is the smallest human chromosome, it is highly relevant in the pathogenicity of both cancer and congenital diseases, including Alzheimer disease and trisomy 21 (Down syndrome). In addition, cases with rare structural variants (SVs) of chromosome 21 have been reported. These events vary in size and include large chromosomal events, such as ring chromosomes and small partial aneuploidies. The p-arm of the acrocentric chromosome 21 was devoid of reference genomic sequence in GRCh37 and GRCh38, which hampered our ability to solve genomic rearrangements and find the mechanism of formation of disease-causing SVs. We hypothesize that conserved satellite structures and segmental duplications located on the p-arm play an important role in the formation of complex SVs involving chromosome 21. Methods Three cases with complex chromosome 21 rearrangements were studied with a combination of short-read and long-read genome sequencing, as well as optical genome mapping. The data were aligned to the T2T-CHM13 assembly. Results We were able to resolve all 3 complex chromosome 21 rearrangements in which 15, 8, and 26 breakpoints were identified, respectively. By comparing the identified SV breakpoints, we were able to pinpoint a region between 21p13 and 21p12 that appears to be frequently involved in chromosome 21 rearrangements. Importantly, we observed acrocentric satellite DNA at several breakpoint junctions suggesting an important role for those elements in the formation of complex SVs. Conclusion Taken together, our results provide further insights into the architecture and underlying mechanisms of complex rearrangements on acrocentric chromosomes.
Collapse
Affiliation(s)
- Jakob Schuy
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kristine Bilgrav Sæther
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Jasmin Lisfeld
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marlene Ek
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Ming Yin Lun
- Pacific Northwest Research Institute, Seattle, WA
| | | | - Susanne Rudolph
- Gemeinschaftspraxis für Humangenetik und Genetische Labore, Hamburg, Germany
| | - Sigrid Fuchs
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kornelia Neveling
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maja Hempel
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- University Heidelberg, Institute of Human Genetics, Heidelberg, Germany
| | - Alexander Hoischen
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Internal Medicine, Radboud Expertise Center for Immunodeficiency and Autoinflammation and Radboud Center for Infectious Disease (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Genomic Medicine Center Karolinska, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Genomic Medicine Center Karolinska, Karolinska University Hospital, Stockholm, Sweden
| |
Collapse
|
33
|
Feng C, Tie R, Xin S, Chen Y, Li S, Chen Y, Hu X, Zhou Y, Liu Y, Hu Y, Hu Y, Pan H, Wu Z, Chao H, Zhang S, Ni Q, Huang J, Luo W, Huang H, Chen M. Systematic single-cell analysis reveals dynamic control of transposable element activity orchestrating the endothelial-to-hematopoietic transition. BMC Biol 2024; 22:143. [PMID: 38937802 PMCID: PMC11209969 DOI: 10.1186/s12915-024-01939-5] [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: 08/02/2023] [Accepted: 06/14/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND The endothelial-to-hematopoietic transition (EHT) process during definitive hematopoiesis is highly conserved in vertebrates. Stage-specific expression of transposable elements (TEs) has been detected during zebrafish EHT and may promote hematopoietic stem cell (HSC) formation by activating inflammatory signaling. However, little is known about how TEs contribute to the EHT process in human and mouse. RESULTS We reconstructed the single-cell EHT trajectories of human and mouse and resolved the dynamic expression patterns of TEs during EHT. Most TEs presented a transient co-upregulation pattern along the conserved EHT trajectories, coinciding with the temporal relaxation of epigenetic silencing systems. TE products can be sensed by multiple pattern recognition receptors, triggering inflammatory signaling to facilitate HSC emergence. Interestingly, we observed that hypoxia-related signals were enriched in cells with higher TE expression. Furthermore, we constructed the hematopoietic cis-regulatory network of accessible TEs and identified potential TE-derived enhancers that may boost the expression of specific EHT marker genes. CONCLUSIONS Our study provides a systematic vision of how TEs are dynamically controlled to promote the hematopoietic fate decisions through transcriptional and cis-regulatory networks, and pre-train the immunity of nascent HSCs.
Collapse
Affiliation(s)
- Cong Feng
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
- Bioinformatics Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Ruxiu Tie
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 310058, China
- Institute of Hematology, Zhejiang University, Hangzhou, 310058, China
- Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, 310058, China
- Department of Hematology, The Second Clinical Medical College of Shanxi Medical University, Shanxi Medical University, Taiyuan, 030000, China
- Department of Hematology-Oncology, Taizhou Hospital of Zhejiang Province, Linhai, 317000, China
| | - Saige Xin
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yuhao Chen
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Sida Li
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yifan Chen
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Xiaotian Hu
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yincong Zhou
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yongjing Liu
- Bioinformatics Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yueming Hu
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yanshi Hu
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Hang Pan
- Department of Veterinary Medicine, Zhejiang University College of Animal Sciences, Hangzhou, 310058, China
| | - Zexu Wu
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Haoyu Chao
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Shilong Zhang
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Qingyang Ni
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Jinyan Huang
- Bioinformatics Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Wenda Luo
- Department of Hematology-Oncology, Taizhou Hospital of Zhejiang Province, Linhai, 317000, China.
| | - He Huang
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310058, China.
- Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, 310058, China.
| | - Ming Chen
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
- Bioinformatics Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
| |
Collapse
|
34
|
Xi C, Zhang G, Sun N, Liu M, Ju N, Shen C, Song H, Luo Q, Qiu Z. Repurposing homoharringtonine for thyroid cancer treatment through TIMP1/FAK/PI3K/AKT signaling pathway. iScience 2024; 27:109829. [PMID: 38770133 PMCID: PMC11103377 DOI: 10.1016/j.isci.2024.109829] [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: 09/14/2023] [Revised: 03/12/2024] [Accepted: 04/24/2024] [Indexed: 05/22/2024] Open
Abstract
Homoharringtonine (HHT), an alkaloid isolated from Cephalotaxus, is an effective anti-leukemia agent and exhibits inhibitory effects in various solid tumors. However, the impacts of HHT treatment on thyroid cancer (TC) remain unclear. Our findings demonstrated that HHT exhibited remarkable anti-TC activity that involved inhibiting cell proliferation, invasion, and migration, as well as inducing apoptosis. Proteomics analysis revealed that the expression of the tissue inhibitor of metalloproteinase 1 (TIMP1) was downregulated in TC cells after HHT treatment. TIMP1 overexpression promoted TC progression and partially reversed the anti-TC effects of HHT, while TIMP1 downregulation inhibited TC progression and enhanced the anti-TC effects of HHT. Furthermore, TIMP1 re-expression attenuated the enhancement of anti-TC effects of HHT induced by TIMP1 knockdown. Mechanistically, HHT exerted anti-TC effects by downregulating TIMP1 expression and then inactivating the FAK/PI3K/AKT signaling pathway. Taken together, our study demonstrated that HHT could inhibit TC progression by inhibiting the TIMP1/FAK/PI3K/AKT signaling pathway.
Collapse
Affiliation(s)
- Chuang Xi
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Guoqiang Zhang
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Nan Sun
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Mengyue Liu
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Nianting Ju
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Chentian Shen
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Hongjun Song
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Quanyong Luo
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Zhongling Qiu
- Department of Nuclear Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| |
Collapse
|
35
|
Jia Y, Zhang F, Meng X, Andreev D, Lyu P, Zhang W, Lai C, Schett G, Bozec A. Osteocytes support bone metastasis of melanoma cells by CXCL5. Cancer Lett 2024; 590:216866. [PMID: 38589005 DOI: 10.1016/j.canlet.2024.216866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/18/2024] [Accepted: 04/03/2024] [Indexed: 04/10/2024]
Abstract
Bone metastasis is a common complication of certain cancers such as melanoma. The spreading of cancer cells into the bone is supported by changes in the bone marrow environment. The specific role of osteocytes in this process is yet to be defined. By RNA-seq and chemokines screening we show that osteocytes release the chemokine CXCL5 when they are exposed to melanoma cells. Osteocytes-mediated CXCL5 secretion enhanced the migratory and invasive behaviour of melanoma cells. When the expression of the CXCL5 receptor, CXCR2, was down-regulated in melanoma cells in vitro, we observed a significant decrease in melanoma cell migration in response to osteocytes. Furthermore, melanoma cells with down-regulated CXCR2 expression showed less bone metastasis and less bone loss in the bone metastasis model in vivo. Furthermore, when simultaneously down-regulating CXCL5 in osteocytes and CXCR2 in melanoma cells, melanoma progression was abrogated in vivo. In summary, these data suggest a significant role of osteocytes in bone metastasis of melanoma, which is mediated through the CXCL5-CXCR2 pathway.
Collapse
Affiliation(s)
- Yewei Jia
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Fulin Zhang
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Xianyi Meng
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Darja Andreev
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Pang Lyu
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Wenshuo Zhang
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Chaobo Lai
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Georg Schett
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Aline Bozec
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany; Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany.
| |
Collapse
|
36
|
Joosten SEP, Gregoricchio S, Stelloo S, Yapıcı E, Huang CCF, Yavuz K, Donaldson Collier M, Morova T, Altintaş UB, Kim Y, Canisius S, Moelans CB, van Diest PJ, Korkmaz G, Lack NA, Vermeulen M, Linn SC, Zwart W. Estrogen receptor 1 chromatin profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions. Genome Res 2024; 34:539-555. [PMID: 38719469 PMCID: PMC11146591 DOI: 10.1101/gr.278680.123] [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: 10/30/2023] [Accepted: 04/11/2024] [Indexed: 06/05/2024]
Abstract
Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1+ breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.
Collapse
Affiliation(s)
- Stacey E P Joosten
- Division of Oncogenomics, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Oncode Institute, The Netherlands
| | - Sebastian Gregoricchio
- Division of Oncogenomics, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Oncode Institute, The Netherlands
| | - Suzan Stelloo
- Oncode Institute, The Netherlands
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University Nijmegen, 6500HB Nijmegen, The Netherlands
| | - Elif Yapıcı
- Koç University School of Medicine, 34450 Istanbul, Turkey
- Koç University Research Center for Translational Medicine (KUTTAM), 34450 Istanbul, Turkey
| | - Chia-Chi Flora Huang
- Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, V6H 3Z6 Canada
| | - Kerim Yavuz
- Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, V6H 3Z6 Canada
| | - Maria Donaldson Collier
- Division of Oncogenomics, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Oncode Institute, The Netherlands
| | - Tunç Morova
- Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, V6H 3Z6 Canada
| | - Umut Berkay Altintaş
- Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, V6H 3Z6 Canada
| | - Yongsoo Kim
- Department of Pathology, Amsterdam University Medical Center, Cancer Center Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Sander Canisius
- Division of Molecular Pathology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Cathy B Moelans
- Department of Pathology, Utrecht University Medical Centre, 3584 CX Utrecht, The Netherlands
| | - Paul J van Diest
- Department of Pathology, Utrecht University Medical Centre, 3584 CX Utrecht, The Netherlands
| | - Gozde Korkmaz
- Koç University School of Medicine, 34450 Istanbul, Turkey
- Koç University Research Center for Translational Medicine (KUTTAM), 34450 Istanbul, Turkey
| | - Nathan A Lack
- Koç University School of Medicine, 34450 Istanbul, Turkey
- Koç University Research Center for Translational Medicine (KUTTAM), 34450 Istanbul, Turkey
- Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, V6H 3Z6 Canada
| | - Michiel Vermeulen
- Oncode Institute, The Netherlands
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University Nijmegen, 6500HB Nijmegen, The Netherlands
- Division of Molecular Genetics, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Sabine C Linn
- Division of Molecular Pathology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Department of Pathology, Utrecht University Medical Centre, 3584 CX Utrecht, The Netherlands
- Department of Medical Oncology, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Wilbert Zwart
- Division of Oncogenomics, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands;
- Oncode Institute, The Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
| |
Collapse
|
37
|
Le Clercq LS, Kotzé A, Grobler JP, Dalton DL. Methylation-based markers for the estimation of age in African cheetah, Acinonyx jubatus. Mol Ecol Resour 2024; 24:e13940. [PMID: 38390700 DOI: 10.1111/1755-0998.13940] [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: 11/20/2023] [Revised: 02/05/2024] [Accepted: 02/09/2024] [Indexed: 02/24/2024]
Abstract
Age is a key demographic in conservation where age classes show differences in important population metrics such as morbidity and mortality. Several traits, including reproductive potential, also show senescence with ageing. Thus, the ability to estimate age of individuals in a population is critical in understanding the current structure as well as their future fitness. Many methods exist to determine age in wildlife, with most using morphological features that show inherent variability with age. These methods require significant expertise and become less accurate in adult age classes, often the most critical groups to model. Molecular methods have been applied to measuring key population attributes, and more recently epigenetic attributes such as methylation have been explored as biomarkers for age. There are, however, several factors such as permits, sample sovereignty, and costs that may preclude the use of extant methods in a conservation context. This study explored the utility of measuring age-related changes in methylation in candidate genes using mass array technology. Novel methods are described for using gene orthologues to identify and assay regions for differential methylation. To illustrate the potential application, African cheetah was used as a case study. Correlation analyses identified six methylation sites with an age relationship, used to develop a model with sufficient predictive power for most conservation contexts. This model was more accurate than previous attempts using PCR and performed similarly to candidate gene studies in other mammal species. Mass array presents an accurate and cost-effective method for age estimation in wildlife of conservation concern.
Collapse
Affiliation(s)
- Louis-Stéphane Le Clercq
- South African National Biodiversity Institute, Pretoria, South Africa
- Department of Genetics, University of the Free State, Bloemfontein, South Africa
| | - Antoinette Kotzé
- South African National Biodiversity Institute, Pretoria, South Africa
- Department of Genetics, University of the Free State, Bloemfontein, South Africa
| | - J Paul Grobler
- Department of Genetics, University of the Free State, Bloemfontein, South Africa
| | - Desiré L Dalton
- School of Health and Life Sciences, Teesside University, Middlesbrough, UK
| |
Collapse
|
38
|
Wang M, Liu L, Li X, Jiang W, Xiao J, Hao Q, Wang J, Reddy AV, Talbot A, Ikuta S, Tian D, Ren L. Solute carrier family 16 member 1 as a potential prognostic factor for pancreatic ductal adenocarcinoma and its influence on tumor immunity. J Gastrointest Oncol 2024; 15:730-746. [PMID: 38756638 PMCID: PMC11094506 DOI: 10.21037/jgo-24-147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 04/11/2024] [Indexed: 05/18/2024] Open
Abstract
Background Solute carrier family 16 member 1 (SLC16A1) serves as a biomarker in numerous types of cancer. Tumor immune infiltration has drawn increasing attention in cancer progression and treatment. The objective of our study was to explore the association between SLC16A1 and the tumor immune microenvironment in pancreatic ductal adenocarcinoma (PDAC). Methods Data were obtained from The Cancer Genome Atlas. The xCell web tool was used to calculate the proportion of immune cells according to SLC16A1 expression. To further explore the mechanism of SLC16A1, immunity-related genes were screened from differentially expressed genes through weighted gene coexpression network analysis, examined via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, and filtrated using univariate Cox regression and least absolute shrinkage and selection operator regression model combined correlation analysis (P<0.05). Next, CIBERSORT was used to analyze the correlation between immune cells and five important genes. SLC16A1 expression and its clinical role in pancreatic cancer was clarified via immunohistochemical staining experiments. Finally, the effects of SLC16A1 on the results of cancer immunity were evaluated by in vitro experiments. Results SLC16A1 was overexpressed in PDAC tissues and could be an independent prognostic factor. SLC16A1 was significantly negatively correlated with overall survival and suppressed the tumor immunity of PDAC. In clinic, SLC16A1 expression was significantly positively correlated with tumor progression and poor prognosis. We also found that SLC16A1 could suppress the antitumor ability of CD8+ T cells. Conclusions SLC16A1 is a biomarker for the prognosis of PDAC and can influence the immune environment of PDAC. These findings provide new insights into the treatment of PDAC.
Collapse
Affiliation(s)
- Meng Wang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
- Department of Clinical Laboratory Diagnostics, Tianjin Medical University, Tianjin, China
| | - Lin Liu
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Xinze Li
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Wenna Jiang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jiawei Xiao
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Qianhui Hao
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jiayi Wang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | | | - Alice Talbot
- Department of Oncology, St. John of God Hospital, Subiaco, WA, Australia
| | - Shinichi Ikuta
- Department of Surgery, Meiwa Hospital, Nishinomiya, Hyogo, Japan
| | - Derun Tian
- Department of Clinical Laboratory Diagnostics, Tianjin Medical University, Tianjin, China
- Department of Human Anatomy and Histology, Tianjin Medical University, Tianjin, China
| | - Li Ren
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| |
Collapse
|
39
|
Lee HS, Kim B, Park T. Genome- and epigenome-wide association studies identify susceptibility of CpG sites and regions for metabolic syndrome in a Korean population. Clin Epigenetics 2024; 16:60. [PMID: 38685121 PMCID: PMC11059751 DOI: 10.1186/s13148-024-01671-5] [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: 11/14/2023] [Accepted: 04/13/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND While multiple studies have investigated the relationship between metabolic syndrome (MetS) and its related traits (fasting glucose, triglyceride, HDL cholesterol, blood pressure, waist circumference) and DNA methylation, our understanding of the epigenetic mechanisms in MetS remains limited. Therefore, we performed an epigenome-wide meta-analysis of blood DNA methylation to identify differentially methylated probes (DMPs) and differentially methylated regions (DMRs) associated with MetS and its components using two independent cohorts comprising a total of 2,334 participants. We also investigated the specific genetic effects on DNA methylation, identified methylation quantitative trait loci (meQTLs) through genome-wide association studies and further utilized Mendelian randomization (MR) to assess how these meQTLs subsequently influence MetS status. RESULTS We identified 40 DMPs and 27 DMRs that are significantly associated with MetS. In addition, we identified many novel DMPs and DMRs underlying inflammatory and steroid hormonal processes. The most significant associations were observed in 3 DMPs (cg19693031, cg26974062, cg02988288) and a DMR (chr1:145440444-145441553) at the TXNIP, which are involved in lipid metabolism. These CpG sites were identified as coregulators of DNA methylation in MetS, TG and FAG levels. We identified a total of 144 cis-meQTLs, out of which only 13 were found to be associated with DMPs for MetS. Among these, we confirmed the identified causal mediators of genetic effects at CpG sites cg01881899 at ABCG1 and cg00021659 at the TANK genes for MetS. CONCLUSIONS This study observed whether specific CpGs and methylated regions act independently or are influenced by genetic effects for MetS and its components in the Korean population. These associations between the identified DNA methylation and MetS, along with its individual components, may serve as promising targets for the development of preventive interventions for MetS.
Collapse
Affiliation(s)
- Ho-Sun Lee
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea.
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
| | - Boram Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea
| | - Taesung Park
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea
- Department of Statistics, Seoul National University, Seoul, 08826, Korea
| |
Collapse
|
40
|
Moreno-Oñate M, Gallardo-Fuentes L, Martínez-García PM, Naranjo S, Jiménez-Gancedo S, Tena JJ, Santos-Pereira JM. Rewiring of the epigenome and chromatin architecture by exogenously induced retinoic acid signaling during zebrafish embryonic development. Nucleic Acids Res 2024; 52:3682-3701. [PMID: 38321954 PMCID: PMC11040003 DOI: 10.1093/nar/gkae065] [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: 06/27/2023] [Revised: 01/15/2024] [Accepted: 01/24/2024] [Indexed: 02/08/2024] Open
Abstract
Retinoic acid (RA) is the ligand of RA receptors (RARs), transcription factors that bind to RA response elements. RA signaling is required for multiple processes during embryonic development, including body axis extension, hindbrain antero-posterior patterning and forelimb bud initiation. Although some RA target genes have been identified, little is known about the genome-wide effects of RA signaling during in vivo embryonic development. Here, we stimulate the RA pathway by treating zebrafish embryos with all-trans-RA (atRA) and use a combination of RNA-seq, ATAC-seq, ChIP-seq and HiChIP to gain insight into the molecular mechanisms by which exogenously induced RA signaling controls gene expression. We find that RA signaling is involved in anterior/posterior patterning, central nervous system development, and the transition from pluripotency to differentiation. AtRA treatment also alters chromatin accessibility during early development and promotes chromatin binding of RARαa and the RA targets Hoxb1b, Meis2b and Sox3, which cooperate in central nervous system development. Finally, we show that exogenous RA induces a rewiring of chromatin architecture, with alterations in chromatin 3D interactions involving target genes. Altogether, our findings identify genome-wide targets of RA signaling and provide a molecular mechanism by which developmental signaling pathways regulate target gene expression by altering chromatin topology.
Collapse
Affiliation(s)
- Marta Moreno-Oñate
- Centro Andaluz de Biología del Desarrollo (CABD), Consejo Superior de Investigaciones Científicas/Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - Lourdes Gallardo-Fuentes
- Centro Andaluz de Biología del Desarrollo (CABD), Consejo Superior de Investigaciones Científicas/Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - Pedro M Martínez-García
- Centro Andaluz de Biología del Desarrollo (CABD), Consejo Superior de Investigaciones Científicas/Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - Silvia Naranjo
- Centro Andaluz de Biología del Desarrollo (CABD), Consejo Superior de Investigaciones Científicas/Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - Sandra Jiménez-Gancedo
- Centro Andaluz de Biología del Desarrollo (CABD), Consejo Superior de Investigaciones Científicas/Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - Juan J Tena
- Centro Andaluz de Biología del Desarrollo (CABD), Consejo Superior de Investigaciones Científicas/Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - José M Santos-Pereira
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41012 Sevilla, Spain
| |
Collapse
|
41
|
Fadra N, Schultz-Rogers LE, Chanana P, Cousin MA, Macke EL, Ferrer A, Pinto E Vairo F, Olson RJ, Oliver GR, Mulvihill LA, Jenkinson G, Klee EW. Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic disease. BMC Genomics 2024; 25:371. [PMID: 38627676 PMCID: PMC11020449 DOI: 10.1186/s12864-024-10240-2] [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: 08/09/2023] [Accepted: 03/18/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND X-chromosome inactivation (XCI) is an epigenetic process that occurs during early development in mammalian females by randomly silencing one of two copies of the X chromosome in each cell. The preferential inactivation of either the maternal or paternal copy of the X chromosome in a majority of cells results in a skewed or non-random pattern of X inactivation and is observed in over 25% of adult females. Identifying skewed X inactivation is of clinical significance in patients with suspected rare genetic diseases due to the possibility of biased expression of disease-causing genes present on the active X chromosome. The current clinical test for the detection of skewed XCI relies on the methylation status of the methylation-sensitive restriction enzyme (Hpall) binding site present in proximity of short tandem polymorphic repeats on the androgen receptor (AR) gene. This approach using one locus results in uninformative or inconclusive data for 10-20% of tests. Further, recent studies have shown inconsistency between methylation of the AR locus and the state of inactivation of the X chromosome. Herein, we develop a method for estimating X inactivation status, using exome and transcriptome sequencing data derived from blood in 227 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium. We tested and validated the model on 11 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique. RESULTS In comparison to the AR clinical test for identification of X inactivation, our method was concordant with the AR method in 9 samples, discordant in 1, and provided a measure of X inactivation in 1 sample with uninformative clinical results. We applied this method on an additional 81 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis. CONCLUSIONS This study presents the use of transcriptome and exome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in a cohort of female patients with different types of suspected rare genetic disease.
Collapse
Affiliation(s)
- Numrah Fadra
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Laura E Schultz-Rogers
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Pritha Chanana
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Margot A Cousin
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Erica L Macke
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Alejandro Ferrer
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Filippo Pinto E Vairo
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Rory J Olson
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Gavin R Oliver
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Lindsay A Mulvihill
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Garrett Jenkinson
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA
| | - Eric W Klee
- Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA.
| |
Collapse
|
42
|
Whited AM, Jungreis I, Allen J, Cleveland CL, Mudge JM, Kellis M, Rinn JL, Hough LE. Biophysical characterization of high-confidence, small human proteins. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.12.589296. [PMID: 38659920 PMCID: PMC11042228 DOI: 10.1101/2024.04.12.589296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Significant efforts have been made to characterize the biophysical properties of proteins. Small proteins have received less attention because their annotation has historically been less reliable. However, recent improvements in sequencing, proteomics, and bioinformatics techniques have led to the high-confidence annotation of small open reading frames (smORFs) that encode for functional proteins, producing smORF-encoded proteins (SEPs). SEPs have been found to perform critical functions in several species, including humans. While significant efforts have been made to annotate SEPs, less attention has been given to the biophysical properties of these proteins. We characterized the distributions of predicted and curated biophysical properties, including sequence composition, structure, localization, function, and disease association of a conservative list of previously identified human SEPs. We found significant differences between SEPs and both larger proteins and control sets. Additionally, we provide an example of how our characterization of biophysical properties can contribute to distinguishing protein-coding smORFs from non-coding ones in otherwise ambiguous cases.
Collapse
Affiliation(s)
- A M Whited
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Irwin Jungreis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
| | - Jeffre Allen
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
- Department of Biochemistry, University of Colorado Boulder, CO, USA
| | | | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
| | - John L Rinn
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
- Department of Biochemistry, University of Colorado Boulder, CO, USA
| | - Loren E Hough
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
- Department of Physics, University of Colorado Boulder, CO, USA
| |
Collapse
|
43
|
Shi HH, Mugaanyi J, Lu C, Li Y, Huang J, Dai L. A paradigm shift in cancer research based on integrative multi-omics approaches: glutaminase serves as a pioneering cuproptosis-related gene in pan-cancer. BMC Womens Health 2024; 24:213. [PMID: 38566121 PMCID: PMC10988933 DOI: 10.1186/s12905-024-03061-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 03/28/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Cuproptosis is a newly identified form of unprogrammed cell death. As a pivotal metabolic regulator, glutaminase (GLS) has recently been discovered to be linked to cuproptosis. Despite this discovery, the oncogenic functions and mechanisms of GLS in various cancers are still not fully understood. METHODS In this study, a comprehensive omics analysis was performed to investigate the differential expression levels, diagnostic and prognostic potential, correlation with tumor immune infiltration, genetic alterations, and drug sensitivity of GLS across multiple malignancies. RESULTS Our findings revealed unique expression patterns of GLS across various cancer types and molecular subtypes of carcinomas, underscoring its pivotal role primarily in energy and nutrition metabolism. Additionally, GLS showed remarkable diagnostic and prognostic performance in specific cancers, suggesting its potential as a promising biomarker for cancer detection and prognosis. Furthermore, we focused on uterine corpus endometrial carcinoma (UCEC) and developed a novel prognostic model associated with GLS, indicating a close correlation between GLS and UCEC. Moreover, our exploration into immune infiltration, genetic heterogeneity, tumor stemness, and drug sensitivity provided novel insights and directions for future research and laid the foundation for high-quality verification. CONCLUSION Collectively, our study is the first comprehensive investigation of the biological and clinical significance of GLS in pan-cancer. In our study, GLS was identified as a promising biomarker for UCEC, providing valuable evidence and a potential target for anti-tumor therapy. Overall, our findings shed light on the multifaceted functions of GLS in cancer and offer new avenues for further research.
Collapse
Affiliation(s)
- Hai-Hong Shi
- Department of Hepato-Pancreato-Biliary Surgery, Ningbo Medical Center Li Huili Hospital, The Affiliated Hospital of Ningbo University, Ningbo, 315040, China
| | - Joseph Mugaanyi
- Health Science Center, Ningbo University, Ningbo, 315211, China
| | - Changjiang Lu
- Department of Hepato-Pancreato-Biliary Surgery, Ningbo Medical Center Li Huili Hospital, The Affiliated Hospital of Ningbo University, Ningbo, 315040, China
| | - Yang Li
- Department of Emergency, Ningbo Medical Center Li Huili Hospital, The Affiliated Hospital of Ningbo University, Ningbo, 315040, China
| | - Jing Huang
- Department of Hepato-Pancreato-Biliary Surgery, Ningbo Medical Center Li Huili Hospital, The Affiliated Hospital of Ningbo University, Ningbo, 315040, China.
| | - Lei Dai
- Department of Hepato-Pancreato-Biliary Surgery, Ningbo Medical Center Li Huili Hospital, The Affiliated Hospital of Ningbo University, Ningbo, 315040, China.
| |
Collapse
|
44
|
Ding Z, Ding Q, Li H. The prognostic biomarker TPGS2 is correlated with immune infiltrates in pan-cancer: a bioinformatics analysis. Transl Cancer Res 2024; 13:1458-1478. [PMID: 38617524 PMCID: PMC11009813 DOI: 10.21037/tcr-23-113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 10/20/2023] [Indexed: 04/16/2024]
Abstract
Background Tubulin polyglutamylase complex subunit 2 (TPGS2) is an element of the neuronal polyglutamylase complex that plays a role in the post-translational addition of glutamate residues to C-terminal tubulin tails. Recent research has shown that TPGS2 is associated with some tumors, but the roles of TPGS2 in tumor immunity remain unclear. Methods The research data were mainly sourced from The Cancer Genome Atlas. The data were analyzed to identify potential correlations between TPGS2 expression and survival, gene alterations, the tumor mutational burden (TMB), microsatellite instability (MSI), immune infiltration, and various immune-related genes across various cancers. The Wilcoxon rank-sum test was used to identify the significance. A log-rank test and univariate Cox regression analysis were performed to assess the survival state of the patients. Spearman's correlation coefficients were used to show the correlations. Results TPGS2 exhibited abnormal expression patterns in most types of cancers, and has promising prognostic potential in adrenocortical carcinoma and liver hepatocellular carcinoma. Further, TPGS2 expression was significantly correlated with molecular and immune subtypes. Moreover, the single-cell analyses showed that the expression of TPGS2 was associated with the cell cycle, metastasis, invasion, inflammation, and DNA damage. In addition, the immune cell infiltration analysis and gene-set enrichment analysis demonstrated that a variety of immune cells and immune processes were associated with TPGS2 expression in various cancers. Further, immune regulators, including immunoinhibitors, immunostimulators, the major histocompatibility complex, chemokines, and chemokine receptors, were correlated with TPGS2 expression in different cancer types. Finally, the TMB and MSI, which have been identified as powerful predictors of immunotherapy, were shown to be correlated with the expression of TPGS2 across human cancers. Conclusions TPGS2 is aberrantly expressed in most cancer tissues and might be associated with immune cell infiltration in the tumor microenvironment. TPGS2 could serve not only as a biomarker for predicting clinical outcomes, but also as a promising biomarker for evaluating and developing new approaches to immunotherapy in many types of cancers, especially colon adenocarcinoma and stomach adenocarcinoma.
Collapse
Affiliation(s)
- Zujun Ding
- Department of General Surgery, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Qing Ding
- Department of Pharmacy, Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hang Li
- Department of General Surgery, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| |
Collapse
|
45
|
Kim M, Wang P, Clow PA, Chien I(E, Wang X, Peng J, Chai H, Liu X, Lee B, Ngan CY, Yue F, Milenkovic O, Chuang JH, Wei CL, Casellas R, Cheng AW, Ruan Y. Multifaceted roles of cohesin in regulating transcriptional loops. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.25.586715. [PMID: 38585764 PMCID: PMC10996690 DOI: 10.1101/2024.03.25.586715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Cohesin is required for chromatin loop formation. However, its precise role in regulating gene transcription remains largely unknown. We investigated the relationship between cohesin and RNA Polymerase II (RNAPII) using single-molecule mapping and live-cell imaging methods in human cells. Cohesin-mediated transcriptional loops were highly correlated with those of RNAPII and followed the direction of gene transcription. Depleting RAD21, a subunit of cohesin, resulted in the loss of long-range (>100 kb) loops between distal (super-)enhancers and promoters of cell-type-specific genes. By contrast, the short-range (<50 kb) loops were insensitive to RAD21 depletion and connected genes that are mostly housekeeping. This result explains why only a small fraction of genes are affected by the loss of long-range chromatin interactions due to cohesin depletion. Remarkably, RAD21 depletion appeared to up-regulate genes located in early initiation zones (EIZ) of DNA replication, and the EIZ signals were amplified drastically without RAD21. Our results revealed new mechanistic insights of cohesin's multifaceted roles in establishing transcriptional loops, preserving long-range chromatin interactions for cell-specific genes, and maintaining timely order of DNA replication.
Collapse
Affiliation(s)
- Minji Kim
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Present address: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Equal contributions
| | - Ping Wang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Evanston, IL, 60201, USA
- Equal contributions
| | - Patricia A. Clow
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Equal contributions
| | - I (Eli) Chien
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Xiaotao Wang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Reproduction and Development, Shanghai, China
| | - Jianhao Peng
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Haoxi Chai
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Xiyuan Liu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, P.R. China
| | - Byoungkoo Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Chew Yee Ngan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Feng Yue
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Evanston, IL, 60201, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Olgica Milenkovic
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Jeffrey H. Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, 06030, USA
| | - Chia-Lin Wei
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Rafael Casellas
- Hematopoietic Biology and Malignancy, MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Albert W. Cheng
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA
| | - Yijun Ruan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang Province, 310058, P.R. China
| |
Collapse
|
46
|
Chen K, Zhou Y, Ding M, Wang Y, Ren Z, Yang Y. Self-supervised learning on millions of primary RNA sequences from 72 vertebrates improves sequence-based RNA splicing prediction. Brief Bioinform 2024; 25:bbae163. [PMID: 38605640 PMCID: PMC11009468 DOI: 10.1093/bib/bbae163] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/22/2024] [Accepted: 03/19/2024] [Indexed: 04/13/2024] Open
Abstract
Language models pretrained by self-supervised learning (SSL) have been widely utilized to study protein sequences, while few models were developed for genomic sequences and were limited to single species. Due to the lack of genomes from different species, these models cannot effectively leverage evolutionary information. In this study, we have developed SpliceBERT, a language model pretrained on primary ribonucleic acids (RNA) sequences from 72 vertebrates by masked language modeling, and applied it to sequence-based modeling of RNA splicing. Pretraining SpliceBERT on diverse species enables effective identification of evolutionarily conserved elements. Meanwhile, the learned hidden states and attention weights can characterize the biological properties of splice sites. As a result, SpliceBERT was shown effective on several downstream tasks: zero-shot prediction of variant effects on splicing, prediction of branchpoints in humans, and cross-species prediction of splice sites. Our study highlighted the importance of pretraining genomic language models on a diverse range of species and suggested that SSL is a promising approach to enhance our understanding of the regulatory logic underlying genomic sequences.
Collapse
Affiliation(s)
- Ken Chen
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
| | - Yue Zhou
- Peng Cheng Laboratory, Shenzhen, China
| | - Maolin Ding
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
| | - Yu Wang
- Peng Cheng Laboratory, Shenzhen, China
| | | | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-sen University), Ministry of Education, China
| |
Collapse
|
47
|
Chowdhury HMAM, Boult T, Oluwadare O. Comparative study on chromatin loop callers using Hi-C data reveals their effectiveness. BMC Bioinformatics 2024; 25:123. [PMID: 38515011 PMCID: PMC10958853 DOI: 10.1186/s12859-024-05713-w] [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: 12/15/2023] [Accepted: 02/19/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Chromosome is one of the most fundamental part of cell biology where DNA holds the hierarchical information. DNA compacts its size by forming loops, and these regions house various protein particles, including CTCF, SMC3, H3 histone. Numerous sequencing methods, such as Hi-C, ChIP-seq, and Micro-C, have been developed to investigate these properties. Utilizing these data, scientists have developed a variety of loop prediction techniques that have greatly improved their methods for characterizing loop prediction and related aspects. RESULTS In this study, we categorized 22 loop calling methods and conducted a comprehensive study of 11 of them. Additionally, we have provided detailed insights into the methodologies underlying these algorithms for loop detection, categorizing them into five distinct groups based on their fundamental approaches. Furthermore, we have included critical information such as resolution, input and output formats, and parameters. For this analysis, we utilized the GM12878 Hi-C datasets at 5 KB, 10 KB, 100 KB and 250 KB resolutions. Our evaluation criteria encompassed various factors, including memory usages, running time, sequencing depth, and recovery of protein-specific sites such as CTCF, H3K27ac, and RNAPII. CONCLUSION This analysis offers insights into the loop detection processes of each method, along with the strengths and weaknesses of each, enabling readers to effectively choose suitable methods for their datasets. We evaluate the capabilities of these tools and introduce a novel Biological, Consistency, and Computational robustness score ( B C C score ) to measure their overall robustness ensuring a comprehensive evaluation of their performance.
Collapse
Affiliation(s)
- H M A Mohit Chowdhury
- Department of Computer Science, University of Colorado at Colorado Springs, 1420 Austin Bluffs Pkwy, Colorado Springs, CO, 80918, USA
| | - Terrance Boult
- Department of Computer Science, University of Colorado at Colorado Springs, 1420 Austin Bluffs Pkwy, Colorado Springs, CO, 80918, USA
| | - Oluwatosin Oluwadare
- Department of Computer Science, University of Colorado at Colorado Springs, 1420 Austin Bluffs Pkwy, Colorado Springs, CO, 80918, USA.
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| |
Collapse
|
48
|
Li H, Liu J, Wang S, Xu Y, Tang Q, Ying G. 4-Hydroxyphenylpyruvate Dioxygenase-Like predicts the prognosis and the immunotherapy response of cancers: a pan-cancer analysis. Aging (Albany NY) 2024; 16:4327-4347. [PMID: 38451188 PMCID: PMC10968709 DOI: 10.18632/aging.205591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 12/01/2023] [Indexed: 03/08/2024]
Abstract
The 4-Hydroxyphenylpyruvate Dioxygenase-Like (HPDL) protein plays a crucial role in safeguarding cells from oxidative stress by orchestrating metabolic reprogramming. New research suggests that HPDL is considerably increased in pancreatic ductal adenocarcinoma, although its impact on cancer immunotherapy is still unclear. Pancancer transcriptional data were obtained from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression datasets. The cBioPortal webtool was utilized to examine genomic changes in different cancer types. The prognostic significance of HPDL in pancancer was evaluated using univariate Cox regression analysis. Extensive utilization of the CTRP and PRISM databases was performed to forecast potential medications that specifically target HPDL in LUAD. In summary, studies were conducted to evaluate the impact of HPDL on the proliferation and movement of LUAD cells using loss-of-function experiments. HPDL is expressed excessively in a wide variety of cancer types, indicating its prognostic and predictive value. Moreover, we emphasized the strong correlation between HPDL and indicators of immune stimulation, infiltration of immune cells, and expression of immunoregulators. The remarkable finding of the HPDL was its capacity to precisely anticipate responses to cancer therapies using anti-PDL1 and anti-PD1 antibodies among individuals. Moreover, HPDL can function as a predictive marker for specific inhibitors in instances of cancer. Suppression of HPDL resulted in reduced growth and movement of LUAD cells. To summarize, our results suggest that HPDL acts as a prospective predictor of outcomes and a positive indication of response to immunotherapy in patients undergoing treatment with immune checkpoint inhibitors (ICIs).
Collapse
Affiliation(s)
- Huimin Li
- Laboratory of Cancer Cell Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
| | - Junzhi Liu
- Department of Otorhinolaryngology, Tianjin Medical University General Hospital, Tianjin 300070, China
| | - Shurui Wang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yue Xu
- Laboratory of Cancer Cell Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
| | - Qiang Tang
- The Second Affiliated Hospital of Zhejiang University School Medicine, Hang Zhou 310000, China
| | - Guoguang Ying
- Laboratory of Cancer Cell Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
| |
Collapse
|
49
|
McCoy MD, Sarasua SM, DeLuca JM, Davis S, Rogers RC, Phelan K, Boccuto L. Genetics of kidney disorders in Phelan-McDermid syndrome: evidence from 357 registry participants. Pediatr Nephrol 2024; 39:749-760. [PMID: 37733098 DOI: 10.1007/s00467-023-06146-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 08/07/2023] [Accepted: 08/22/2023] [Indexed: 09/22/2023]
Abstract
BACKGROUND Phelan-McDermid syndrome (PMS) is a rare genetic disorder caused by SHANK3 pathogenic variants or chromosomal rearrangements affecting the chromosome 22q13 region. Previous research found that kidney disorders, primarily congenital anomalies of the kidney and urinary tract, are common in people with PMS, yet research into candidate genes has been hampered by small study sizes and lack of attention to these problems. METHODS We used a cohort of 357 people from the Phelan-McDermid Syndrome Foundation International Registry to investigate the prevalence of kidney disorders in PMS using a cross-sectional design and to identify 22q13 genes contributing to these disorders. RESULTS Kidney disorders reported included vesicoureteral reflux (n = 37), hydronephrosis (n = 36), dysplastic kidneys (n = 19), increased kidney size (n = 19), polycystic kidneys (15 cases), and kidney stones (n = 4). Out of 315 subjects with a 22q13 deletion, 101 (32%) had at least one kidney disorder, while only one out of 42 (2%) individuals with a SHANK3 pathogenic variant had a kidney disorder (increased kidney size). We identified two genomic regions that were significantly associated with having a kidney disorder with the peak associations observed near positions approximately 5 Mb and 400 Kb from the telomere. CONCLUSIONS The candidate genes for kidney disorders include FBLN1, WNT7B, UPK3A, CELSR1, and PLXNB2. This study demonstrates the utility of patient registries for uncovering genetic contributions to rare diseases. Future work should focus on functional studies for these genes to assess their potential pathogenic contribution to the different subsets of kidney disorders.
Collapse
Affiliation(s)
- Megan D McCoy
- School of Nursing, Healthcare Genetics Program, Clemson University, Clemson, SC, 29634, USA
| | - Sara M Sarasua
- School of Nursing, Healthcare Genetics Program, Clemson University, Clemson, SC, 29634, USA.
| | - Jane M DeLuca
- School of Nursing, Healthcare Genetics Program, Clemson University, Clemson, SC, 29634, USA
| | - Stephanie Davis
- School of Nursing, Healthcare Genetics Program, Clemson University, Clemson, SC, 29634, USA
| | | | - Katy Phelan
- Genetics Laboratory, Florida Cancer Specialists and Research Institute, Fort Myers, FL, 33916, USA
| | - Luigi Boccuto
- School of Nursing, Healthcare Genetics Program, Clemson University, Clemson, SC, 29634, USA
| |
Collapse
|
50
|
Dong P, Voloudakis G, Fullard JF, Hoffman GE, Roussos P. Convergence of the dysregulated regulome in schizophrenia with polygenic risk and evolutionarily constrained enhancers. Mol Psychiatry 2024; 29:782-792. [PMID: 38145985 PMCID: PMC11153027 DOI: 10.1038/s41380-023-02370-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 12/06/2023] [Accepted: 12/07/2023] [Indexed: 12/27/2023]
Abstract
Enhancers play an essential role in the etiology of schizophrenia; however, the dysregulation of enhancer activity and its impact on the regulome in schizophrenia remains understudied. To address this gap in our knowledge, we assessed enhancer and gene expression in 1,382 brain samples comprising cases with schizophrenia and unaffected controls. Dysregulation of enhancer expression was concordant with changes in gene expression, and was more closely associated with schizophrenia polygenic risk, suggesting that enhancer dysregulation is proximal to the genetic etiology of the disease. Modeling the shared variance of cis-coordinated genes and enhancers revealed a gene regulatory program that was highly associated with genetic vulnerability to schizophrenia. By integrating coordinated factors with evolutionary constraints, we found that enhancers acquired during human evolution are more likely to regulate genes that are implicated in neuropsychiatric disorders and, thus, hold potential as therapeutic targets. Our analysis provides a systematic view of regulome dysregulation in schizophrenia and highlights its convergence with schizophrenia polygenic risk and human-gained enhancers.
Collapse
Affiliation(s)
- Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, 10468, USA.
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA.
| |
Collapse
|