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Zhu C, Zhu B, Xu S, Li L, Song Y, Tang C. ARID1A: Multiple functions in human pregnancy. J Reprod Immunol 2025; 168:104448. [PMID: 39908786 DOI: 10.1016/j.jri.2025.104448] [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: 10/29/2024] [Revised: 01/05/2025] [Accepted: 02/01/2025] [Indexed: 02/07/2025]
Abstract
AT-rich interacting domain containing respectively protein 1 A (ARID1A), a key member of the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complex, has been shown to play an important role in various physiological processes and diseases including female reproductive tumors, such as ovarian cancer and breast cancer. In addition to the studies regarding ARID1A expression and function in cancer, recent findings elucidate its important role in maintaining normal tissue homeostasis and cell differentiation by controlling chromatin remodeling and transcription factors recruitment. In the context of human pregnancy, ARID1A has been implicated in several pregnancy-related complications, including gestational diabetes, preeclampsia, and intrauterine growth restriction. This review examines the current research on the role of ARID1A in pregnancy, highlighting its potential as a biomarker and therapeutic target for these complications. Understanding the involvement of ARID1A in placental function and pregnancy-related disorders may provide valuable insights for the development of novel diagnostic and therapeutic strategies.
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Affiliation(s)
- Chongying Zhu
- National Clinical Research Center for Child Health of Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China; The Department of Obstetrics and Gynecology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Bingquan Zhu
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Shouying Xu
- National Clinical Research Center for Child Health of Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China
| | - Lin Li
- Department of Urology, Third Affiliated Hospital, Naval Medical University, Shanghai, 201805, China
| | - Yanhua Song
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Chao Tang
- National Clinical Research Center for Child Health of Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China.
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Zhang X, Luan P, Cao D, Hu G. A High-Density Genetic Linkage Map and Fine Mapping of QTL For Feed Conversion Efficiency in Common Carp ( Cyprinus carpio). Front Genet 2021; 12:778487. [PMID: 34868267 PMCID: PMC8633483 DOI: 10.3389/fgene.2021.778487] [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: 09/17/2021] [Accepted: 10/22/2021] [Indexed: 12/02/2022] Open
Abstract
Feed conversion efficiency (FCE) is an economically crucial trait in fish, however, little progress has been made in genetics and genomics for this trait because phenotypes of the trait are difficult to measure. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,416 SNP markers for common carp (Cyprinus carpio) based on high throughput genotyping with the carp 250K single nucleotide polymorphism (SNP) array in a full-sib F1 family of mirror carp (Cyprinus carpio) consisting of 141 progenies. The linkage map contained 11,983 distinct loci and spanned 3,590.09 cM with an average locus interval of 0.33 cM. A total of 17 QTL for the FCE trait were detected on four LGs (LG9, LG20, LG28, and LG32), explaining 8.9-15.9% of the phenotypic variations. One major cluster containing eight QTL (qFCE1-28, qFCE2-28, qFCE3-28, qFCE4-28, qFCE5-28, qFCE6-28, qFCE7-28, and qFCE8-28) was detected on LG28. Two clusters consisting of four QTL (qFCE1-32, qFCE2-32, qFCE3-32, and qFCE4-32) and three QTL (qFCE1-20, qFCE2-20, and qFCE3-20) were detected on LG32 and LG20, respectively. Nine candidate genes (ACACA, SCAF4, SLC2A5, TNMD, PCDH1, FOXO, AGO1, FFAR3, and ARID1A) underlying the feed efficiency trait were also identified, the biological functions of which may be involved in lipid metabolism, carbohydrate metabolism, energy deposition, fat accumulation, digestion, growth regulation, and cell proliferation and differentiation according to GO (Gene Ontology). As an important tool, high-density and high-resolution genetic linkage maps play a crucial role in the QTL fine mapping of economically important traits. Our novel findings provided new insights that elucidate the genetic basis and molecular mechanism of feed efficiency and the subsequent marker-assisted selection breeding in common carp.
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Affiliation(s)
- Xiaofeng Zhang
- National and Local United Engineering Laboratory for Freshwater Fish Breeding, Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin, China
| | | | | | - Guo Hu
- National and Local United Engineering Laboratory for Freshwater Fish Breeding, Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin, China
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Giri AK, Prasad G, Bandesh K, Parekatt V, Mahajan A, Banerjee P, Kauser Y, Chakraborty S, Rajashekar D, Sharma A, Mathur SK, Basu A, McCarthy MI, Tandon N, Bharadwaj D. Multifaceted genome-wide study identifies novel regulatory loci in SLC22A11 and ZNF45 for body mass index in Indians. Mol Genet Genomics 2020; 295:1013-1026. [PMID: 32363570 DOI: 10.1007/s00438-020-01678-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 04/11/2020] [Indexed: 12/22/2022]
Abstract
Obesity, a risk factor for multiple diseases (e.g. diabetes, hypertension, cancers) originates through complex interactions between genes and prevailing environment (food habit and lifestyle) that varies across populations. Indians exhibit a unique obesity phenotype with high abdominal adiposity for a given body weight compared to matched white populations suggesting presence of population-specific genetic and environmental factors influencing obesity. However, Indian population-specific genetic contributors for obesity have not been explored yet. Therefore, to identify potential genetic contributors, we performed a two-staged genome-wide association study (GWAS) for body mass index (BMI), a common measure to evaluate obesity in 5973 Indian adults and the lead findings were further replicated in 1286 Indian adolescents. Our study revealed novel association of variants-rs6913677 in BAI3 gene (p = 1.08 × 10-8) and rs2078267 in SLC22A11 gene (p = 4.62 × 10-8) at GWAS significance, and of rs8100011 in ZNF45 gene (p = 1.04 × 10-7) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped genetic data of identified signals with their DNA methylation patterns in 236 Indian individuals and performed methylation quantitative trait loci (meth-QTL) analysis. Further, functional roles of discovered variants and underlying genes were speculated using publicly available gene regulatory databases (ENCODE, JASPAR, GeneHancer, GTEx). The identified variants in BAI3 and SLC22A11 genes were found to dictate methylation patterns at unique CpGs harboring critical cis-regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were located in repressive chromatin, active enhancer, and active chromatin regions, respectively, in human subcutaneous adipose tissue in ENCODE database. Additionally, these genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, GTEx portal identify rs8100011 as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue (p = 1.6 × 10-7), and ZNF45 gene expression in skeletal muscle of Indian subjects showed an inverse correlation with BMI indicating its possible role in obesity. In conclusion, our study discovered 3 novel population-specific functional genetic variants (rs6913677, rs2078267, rs8100011) in 2 novel (SLC22A11 and ZNF45) and 1 earlier reported gene (BAI3) for BMI in Indians. Our study decodes key genomic loci underlying obesity phenotype in Indians that may serve as prospective drug targets in future.
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Affiliation(s)
- Anil K Giri
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Gauri Prasad
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Khushdeep Bandesh
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Vaisak Parekatt
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Priyanka Banerjee
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Yasmeen Kauser
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Shraddha Chakraborty
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Donaka Rajashekar
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | | | - Abhay Sharma
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Sandeep Kumar Mathur
- Department of Endocrinology, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| | - Analabha Basu
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India.
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India. .,Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India.
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