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Helal M, Sameh J, Gharib S, Merghany RM, Bozhilova-Sakova M, Ragab M. Candidate genes associated with reproductive traits in rabbits. Trop Anim Health Prod 2024; 56:94. [PMID: 38441694 PMCID: PMC10914644 DOI: 10.1007/s11250-024-03938-8] [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: 12/11/2023] [Accepted: 02/20/2024] [Indexed: 03/07/2024]
Abstract
In the era of scientific advances and genetic progress, opportunities in the livestock sector are constantly growing. The application of molecular-based methods and approaches in farm animal breeding would accelerate and improve the expected results. The current work aims to comprehensively review the most important causative mutations in candidate genes that affect prolificacy traits in rabbits. Rabbits are a source of excellent-tasting meat that is high in protein and low in fat. Their early maturity and intensive growth are highly valued all over the world. However, improving reproductive traits and prolificacy in rabbits could be very tricky with traditional selection. Therefore, traditional breeding programs need new methods based on contemporary discoveries in molecular biology and genetics because of the complexity of the selection process. The study and implementation of genetic markers related to production in rabbits will help to create populations with specific productive traits that will produce the desired results in an extremely short time. Many studies worldwide showed an association between different genes and productive traits in rabbits. The study of these polymorphisms and their effects could be useful for molecular-oriented breeding, particularly marker-assisted selection programs in rabbit breeding.
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Affiliation(s)
- Mostafa Helal
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt.
| | - Jana Sameh
- Biotechnology Program, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt
| | - Sama Gharib
- Biotechnology Program, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt
| | - Rana M Merghany
- Department of Pharmacognosy, National Research Centre, Giza, 12622, Egypt
| | | | - Mohamed Ragab
- Poultry Production Department, Faculty of Agriculture, Kafrelsheikh University, Kafrelsheikh, Egypt
- Animal Breeding and Genetics Department, National Institute for Agricultural and Food Research and Technology (INIA), Madrid, 28040, Spain
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Tsai SJ, Kao CF, Su TP, Li CT, Lin WC, Hong CJ, Bai YM, Tu PC, Chen MH. Cytokine- and Vascular Endothelial Growth Factor-Related Gene-Based Genome-Wide Association Study of Low-Dose Ketamine Infusion in Patients with Treatment-Resistant Depression. CNS Drugs 2023; 37:243-253. [PMID: 36763263 DOI: 10.1007/s40263-023-00989-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/15/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND AND OBJECTIVE Ketamine may work as an anti-inflammatory agent, and it increases the levels of vascular endothelial growth factor (VEGF) in patients with treatment-resistant depression. However, whether genes related to pro-inflammatory and anti-inflammatory cytokines and VEGF may predict the treatment response to ketamine remains unknown.Therefore the aim of this study was to analyze whether specific genes related to inflammatory processes and VEGF were associated with treatment response to low-dose ketamine in patients with treatment-resistant depression. METHODS Based on the genome data from our clinical trial, this study was a secondary analysis of candidate genes correlated with different timepoints of depressive symptoms. In total, 65 patients with treatment-resistant depression (n = 21 for ketamine 0.5 mg/kg, 20 for ketamine 0.2 mg/kg, and 24 for normal saline) were genotyped for 684,616 single nucleotide polymorphisms. Genes associated with 80 cytokines (i.e., interleukin [IL]-1, IL-6, tumor necrosis factor-α, and adiponectin) and VEGF (i.e., VEGF and VEGF receptors) were selected for the gene-based genome-wide association study on the antidepressant effect of a ketamine infusion. RESULTS Specific single nucleotide polymorphisms, including rs2540315 and rs75746675 in IL1R1 and rs79568085 in VEGFC, were related to the rapid (within 240 min) antidepressant effect of a ketamine infusion; specific single nucleotide polymorphisms, such as Affx-20131665 in PIGF and rs8179353, rs8179353, and rs8179353 in TNFRSF8, were associated with the sustained (up to 2 weeks) antidepressant effect of low-dose (combined 0.5 mg/kg and 0.2 mg/kg) ketamine. CONCLUSIONS Our findings further revealed that genes related to both anti-inflammatory and pro-inflammatory cytokines (i.e., IL-1, IL-2, IL-6, tumor necrosis factor-α, C-reactive protein, and adiponectin) and VEGF-FLK signaling predicted the treatment response to a ketamine infusion in patients with treatment-resistant depression. The synergic modulation of inflammatory and VEGF systems may contribute to the antidepressant effect of ketamine. CLINICAL TRIAL REGISTRATION University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) number: UMIN000016985.
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Affiliation(s)
- Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chung-Feng Kao
- Department of Agronomy, College of Agriculture and Natural Resources, National Chung Hsing University, Taichung, Taiwan
- Advanced Plant Biotechnology Center, National Chung Hsing University, Taichung, Taiwan
| | - Tung-Ping Su
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Cheng Hsin General Hospital, Taipei, Taiwan
| | - Cheng-Ta Li
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei-Chen Lin
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chen-Jee Hong
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ya-Mei Bai
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Pei-Chi Tu
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Mu-Hong Chen
- Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan.
- Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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Demetci P, Cheng W, Darnell G, Zhou X, Ramachandran S, Crawford L. Multi-scale inference of genetic trait architecture using biologically annotated neural networks. PLoS Genet 2021; 17:e1009754. [PMID: 34411094 PMCID: PMC8407593 DOI: 10.1371/journal.pgen.1009754] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 08/31/2021] [Accepted: 07/31/2021] [Indexed: 01/01/2023] Open
Abstract
In this article, we present Biologically Annotated Neural Networks (BANNs), a nonlinear probabilistic framework for association mapping in genome-wide association (GWA) studies. BANNs are feedforward models with partially connected architectures that are based on biological annotations. This setup yields a fully interpretable neural network where the input layer encodes SNP-level effects, and the hidden layer models the aggregated effects among SNP-sets. We treat the weights and connections of the network as random variables with prior distributions that reflect how genetic effects manifest at different genomic scales. The BANNs software uses variational inference to provide posterior summaries which allow researchers to simultaneously perform (i) mapping with SNPs and (ii) enrichment analyses with SNP-sets on complex traits. Through simulations, we show that our method improves upon state-of-the-art association mapping and enrichment approaches across a wide range of genetic architectures. We then further illustrate the benefits of BANNs by analyzing real GWA data assayed in approximately 2,000 heterogenous stock of mice from the Wellcome Trust Centre for Human Genetics and approximately 7,000 individuals from the Framingham Heart Study. Lastly, using a random subset of individuals of European ancestry from the UK Biobank, we show that BANNs is able to replicate known associations in high and low-density lipoprotein cholesterol content.
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Affiliation(s)
- Pinar Demetci
- Department of Computer Science, Brown University, Providence, Rhode Island, United States of America
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America
| | - Wei Cheng
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America
| | - Gregory Darnell
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sohini Ramachandran
- Department of Computer Science, Brown University, Providence, Rhode Island, United States of America
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America
| | - Lorin Crawford
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America
- Microsoft Research New England, Cambridge, Massachusetts, United States of America
- Department of Biostatistics, Brown University, Providence, Rhode Island, United States of America
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Abstract
Obesity represents a major health burden to both developed and developing countries. Furthermore, the incidence of obesity is increasing in children. Obesity contributes substantially to mortality in the United States by increasing the risk for type 2 diabetes, cardiovascular-related diseases, and other comorbidities. Despite environmental changes over past decades, including increases in high-calorie foods and sedentary lifestyles, there is very clear evidence of a genetic predisposition to obesity risk. Childhood obesity cases can be categorized in one of two ways: syndromic or non-syndromic. Syndromic obesity includes disorders such as Prader-Willi syndrome, Bardet-Biedl syndrome, and Alström syndrome. Non-syndromic cases of obesity can be further separated into rarer instances of monogenic obesity and much more common forms of polygenic obesity. The advent of genome-wide association studies (GWAS) and next-generation sequencing has driven significant advances in our understanding of the genetic contribution to childhood obesity. Many rare and common genetic variants have been shown to contribute to the heritability in obesity, although the molecular mechanisms underlying most of these variants remain unclear. An important caveat of GWAS efforts is that they do not strictly represent gene target discoveries, rather simply the uncovering of robust genetic signals. One clear example of this is with progress in understanding the key obesity signal harbored within an intronic region of the FTO gene. It has been shown that the non-coding region in which the variant actually resides in fact influences the expression of genes distal to FTO instead, specifically IRX3 and IRX5. Such discoveries suggest that associated non-coding variants can be embedded within or next to one gene, but commonly influence the expression of other, more distal effector genes. Advances in genetics and genomics are therefore contributing to a deeper understanding of childhood obesity, allowing for development of clinical tools and therapeutic agents.
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Engle SE, Bansal R, Antonellis PJ, Berbari NF. Cilia signaling and obesity. Semin Cell Dev Biol 2020; 110:43-50. [PMID: 32466971 DOI: 10.1016/j.semcdb.2020.05.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 05/08/2020] [Accepted: 05/10/2020] [Indexed: 12/11/2022]
Abstract
An emerging number of rare genetic disorders termed ciliopathies are associated with pediatric obesity. It is becoming clear that the mechanisms associated with cilia dysfunction and obesity in these syndromes are complex. In addition to ciliopathic syndromic forms of obesity, several cilia-associated signaling gene mutations also lead to morbid obesity. While cilia have critical and diverse functions in energy homeostasis including their roles in centrally mediated food intake as well as in peripheral tissues, many questions remain. Here, we briefly discuss the syndromic ciliopathies and monoallelic cilia signaling gene mutations associated with obesity. We also describe potential ways cilia may be involved in common obesity. We discuss how neuronal cilia impact food intake potentially through leptin signaling and changes in ciliary G protein-coupled receptor (GPCR) signaling. We highlight several recent studies that have implicated the potential for cilia in peripheral tissues such as adipose and the pancreas to contribute to metabolic dysfunction. Then we discuss the potential for cilia to impact energy homeostasis through their roles in both development and adult tissue homeostasis. The studies discussed in this review highlight how a comprehensive understanding of the requirement of cilia for the regulation of diverse biological functions will contribute to our understanding of common forms of obesity.
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Affiliation(s)
- Staci E Engle
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA
| | - Ruchi Bansal
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA
| | - Patrick J Antonellis
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA
| | - Nicolas F Berbari
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, USA; Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA.
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