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Chen H, Naseri A, Zhi D. FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts. PLoS Genet 2023; 19:e1011057. [PMID: 38039339 PMCID: PMC10718418 DOI: 10.1371/journal.pgen.1011057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 12/13/2023] [Accepted: 11/07/2023] [Indexed: 12/03/2023] Open
Abstract
Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. We used sparse linear algebra and random matrix algorithms to speed up the computation, and a genome-wide IBD mapping scan of more than 400,000 samples finished within a few hours. Simulation studies showed that our new method had well-controlled type I error rates under the null hypothesis of no genetic association in large biobank-scale cohorts, and outperformed traditional GWAS single-variant tests when the causal variants were untyped and rare, or in the presence of haplotype effects. We also applied our method to IBD mapping of six anthropometric traits using the UK Biobank data and identified a total of 3,442 associations, 2,131 (62%) of which remained significant after conditioning on suggestive tag variants in the ± 3 centimorgan flanking regions from GWAS.
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Affiliation(s)
- Han Chen
- Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Ardalan Naseri
- Center for Artificial Intelligence and Genome Informatics, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Degui Zhi
- Center for Artificial Intelligence and Genome Informatics, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
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2
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Yu Z, Abdel-Azim S, Duggal P, Vergara C. Identity by descent mapping of HCV spontaneous clearance in populations of diverse ancestry. RESEARCH SQUARE 2023:rs.3.rs-2433454. [PMID: 36712049 PMCID: PMC9882640 DOI: 10.21203/rs.3.rs-2433454/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background Acute infection with hepatitis C virus (HCV) affects millions of individuals worldwide. Host genetics plays a role in spontaneous clearance of the acute infection which occurs in approximately 30% of the individuals. Common variants in GPR158, genes in the interferon lambda (IFNL) cluster, and the MHC region have been associated with HCV clearance in populations of diverse ancestry. Fine mapping of those regions has identified some key variants and amino acids as potential causal variants but the role of rare variants in those regions and in the genome, in general, has not been explored. We aimed to detect haplotypes containing rare variants related to HCV clearance using identity-by-descent (IBD) haplotype sharing between unrelated cases/case pairs and case/controls pairs in 3,608 individuals with European and African ancestry. Results We detected 1,711,832 and 5,678,043 and individual pairs of IBD segments in the European and African ancestry individuals, respectively. As expected, individuals of African descent had more, and shorter segments compared to Europeans. We did not detect any significant IBD signals in the known associated gene regions. Conclusions IBD is based on sharing of haplotypes and is most powerful in populations with a shared founder or recent common ancestor. For the complex trait of HCV clearance, we used two outbred, global populations that limited our power to detect IBD associations. Overall, in this population-based sample we failed to detect rare variations associated with HCV clearance in individuals of European and African ancestry.
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Affiliation(s)
- Zixuan Yu
- Johns Hopkins University, Bloomberg School of Public Health
| | | | - Priya Duggal
- Johns Hopkins University, Bloomberg School of Public Health
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3
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Samuels DC, Below JE, Ness S, Yu H, Leng S, Guo Y. Alternative Applications of Genotyping Array Data Using Multivariant Methods. Trends Genet 2020; 36:857-867. [PMID: 32773169 PMCID: PMC7572808 DOI: 10.1016/j.tig.2020.07.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 07/08/2020] [Accepted: 07/09/2020] [Indexed: 10/23/2022]
Abstract
One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotyping array has gained lasting applications in genome-wide association studies (GWAS) and thus accumulated an enormous amount of data. Empowered by continuous manufactural upgrades and analytical innovation, unconventional applications of genotyping array data have emerged to address more diverse genetic problems, holding promise of boosting genetic research into human diseases through the re-mining of the rich accumulated data. Here, we review several unconventional genotyping array analysis techniques that have been built on the idea of large-scale multivariant analysis and provide empirical application examples. These unconventional outcomes of genotyping arrays include polygenic score, runs of homozygosity (ROH)/heterozygosity ratio, distant pedigree computation, and mitochondrial DNA (mtDNA) copy number inference.
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Affiliation(s)
- David C Samuels
- Department of Molecular Physiology and Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA
| | - Jennifer E Below
- Devision of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Scott Ness
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA
| | - Hui Yu
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA
| | - Shuguang Leng
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA
| | - Yan Guo
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA.
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4
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Han Z, Hu Y, Tian Q, Cao Y, Si A, Si Z, Zang Y, Xu C, Shen W, Dai F, Liu X, Fang L, Chen H, Zhang T. Genomic signatures and candidate genes of lint yield and fibre quality improvement in Upland cotton in Xinjiang. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:2002-2014. [PMID: 32030869 PMCID: PMC7540456 DOI: 10.1111/pbi.13356] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 01/21/2020] [Indexed: 06/10/2023]
Abstract
Xinjiang has been the largest and highest yield cotton production region not only in China, but also in the world. Improvements in Upland cotton cultivars in Xinjiang have occurred via pedigree selection and/or crossing of elite alleles from the former Soviet Union and other cotton producing regions of China. But it is unclear how genomic constitutions from foundation parents have been selected and inherited. Here, we deep-sequenced seven historic foundation parents, comprising four cultivars introduced from the former Soviet Union (108Ф, C1470, 611Б and KK1543) and three from United States and Africa (DPL15, STV2B and UGDM), and re-sequenced sixty-nine Xinjiang modern cultivars. Phylogenetic analysis of more than 2 million high-quality single nucleotide polymorphisms allowed their classification two groups, suggesting that Xinjiang Upland cotton cultivars were not only spawned from 108Ф, C1470, 611Б and KK1543, but also had a close kinship with DPL15, STV2B and UGDM. Notably, identity-by-descent (IBD) tracking demonstrated that the former Soviet Union cultivars have made a huge contribution to modern cultivar improvement in Xinjiang. A total of 156 selective sweeps were identified. Among them, apoptosis-antagonizing transcription factor gene (GhAATF1) and mitochondrial transcription termination factor family protein gene (GhmTERF1) were highly involved in the determination of lint percentage. Additionally, the auxin response factor gene (GhARF3) located in inherited IBD segments from 108Ф and 611Б was highly correlated with fibre quality. These results provide an insight into the genomics of artificial selection for improving cotton production and facilitate next-generation precision breeding of cotton and other crops.
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Affiliation(s)
- Zegang Han
- State Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
| | - Yan Hu
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
| | - Qin Tian
- Key Laboratory of China Northwestern Inland RegionMinistry of AgricultureCotton Research InstituteXinjiang Academy of Agricultural and Reclamation ScienceShiheziChina
| | - Yiwen Cao
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
| | - Aijun Si
- Key Laboratory of China Northwestern Inland RegionMinistry of AgricultureCotton Research InstituteXinjiang Academy of Agricultural and Reclamation ScienceShiheziChina
| | - Zhanfeng Si
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
| | - Yihao Zang
- State Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina
| | - Chenyu Xu
- State Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina
| | - Weijuan Shen
- State Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina
| | - Fan Dai
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
| | - Xia Liu
- Esquel GroupWanchai, Hong KongChina
| | - Lei Fang
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
| | - Hong Chen
- Key Laboratory of China Northwestern Inland RegionMinistry of AgricultureCotton Research InstituteXinjiang Academy of Agricultural and Reclamation ScienceShiheziChina
| | - Tianzhen Zhang
- State Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina
- Zhejiang Provincial Key Laboratory of Crop Genetic ResourcesInstitute of Crop SciencePlant Precision Breeding AcademyCollege of Agriculture and BiotechnologyZhejiang UniversityHangzhouChina
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5
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Xu Z, Xie C, Xia L, Yuan Y, Zhu H, Huang X, Li C, Tao Y, Qu X, Zhang F, Zhang Z. Targeted exome sequencing identifies five novel loci at genome-wide significance for modulating antidepressant response in patients with major depressive disorder. Transl Psychiatry 2020; 10:30. [PMID: 32066657 PMCID: PMC7026085 DOI: 10.1038/s41398-020-0689-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 10/23/2019] [Accepted: 11/06/2019] [Indexed: 02/08/2023] Open
Abstract
In order to determine the role of single nucleotide variants (SNVs) in modulating antidepressant response, we conducted a study, consisting of 929 major depressive disorder (MDD) patients, who were treated with antidepressant drugs (drug-only) or in combination with a repetitive transcranial magnetic stimulation (plus-rTMS), followed by targeted exome sequencing analysis. We found that the "plus-rTMS" patients presented a more effective response to the treatment when compared to the 'drug-only' group. Our data firstly demonstrated that the SNV burden had a significant impact on the antidepressant response presented in the "drug-only" group, but was limited in the "plus-rTMS" group. Further, after controlling for overall SNV burden, seven single nucleotide polymorphisms (SNPs) at five loci, IL1A, GNA15, PPP2CB, PLA2G4C, and GBA, were identified as affecting the antidepressant response at genome-wide significance (P < 5 × 10-08). Additional multiple variants achieved a level of correction for multiple testing, including GNA11, also shown as a strong signal for MDD risk. Our study showed some promising evidence on genetic variants that could be used as individualized therapeutic guides for MDD patients.
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Affiliation(s)
- Zhi Xu
- grid.263826.b0000 0004 1761 0489The Department of Neurology and Psychiatry of Affiliated ZhongDa Hospital, and Medical School of Southeast University, 210009 Nanjing, Jiangsu China
| | - Chunming Xie
- grid.263826.b0000 0004 1761 0489The Department of Neurology and Psychiatry of Affiliated ZhongDa Hospital, and Medical School of Southeast University, 210009 Nanjing, Jiangsu China
| | - Lu Xia
- Global Clinical and Translational Research Institute, Bethesda, MD 20814 USA
| | - Yonggui Yuan
- grid.263826.b0000 0004 1761 0489The Department of Neurology and Psychiatry of Affiliated ZhongDa Hospital, and Medical School of Southeast University, 210009 Nanjing, Jiangsu China
| | - Hong Zhu
- grid.263826.b0000 0004 1761 0489The Department of Neurology and Psychiatry of Affiliated ZhongDa Hospital, and Medical School of Southeast University, 210009 Nanjing, Jiangsu China
| | - Xiaofa Huang
- grid.263826.b0000 0004 1761 0489The Department of Neurology and Psychiatry of Affiliated ZhongDa Hospital, and Medical School of Southeast University, 210009 Nanjing, Jiangsu China
| | - Caihua Li
- Center for Genetics and Genomics Analysis, Genesky Biotechnologies, Inc, 201203 Shanghai, China
| | - Yu Tao
- Center for Genetics and Genomics Analysis, Genesky Biotechnologies, Inc, 201203 Shanghai, China
| | - Xiaoxiao Qu
- Genesky Diagnostics, Inc., BioBay, SIP, 215123 Jiangsu, China
| | - Fengyu Zhang
- Global Clinical and Translational Research Institute, Bethesda, MD, 20814, USA.
| | - Zhijun Zhang
- The Department of Neurology and Psychiatry of Affiliated ZhongDa Hospital, and Medical School of Southeast University, 210009, Nanjing, Jiangsu, China. .,Global Clinical and Translational Research Institute, Bethesda, MD, 20814, USA. .,The Institute of Neuropsychiatry, the Key Laboratory of Development Genes and Human Diseases, the Ministry of Education and Institute of Life Sciences of Southeast University, 210096, Nanjing, Jiangsu, China.
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6
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Harold D, Connolly S, Riley BP, Kendler KS, McCarthy SE, McCombie WR, Richards A, Owen MJ, O'Donovan MC, Walters J, Donohoe G, Gill M, Corvin A, Morris DW. Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia. Am J Med Genet B Neuropsychiatr Genet 2019; 180:223-231. [PMID: 30801977 PMCID: PMC8863274 DOI: 10.1002/ajmg.b.32716] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 10/22/2018] [Accepted: 12/03/2018] [Indexed: 12/30/2022]
Abstract
Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.
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Affiliation(s)
- Denise Harold
- Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine and Discipline of Psychiatry, Trinity College Dublin, Dublin, Ireland
- School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Siobhan Connolly
- Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine and Discipline of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Brien P Riley
- Departments of Psychiatry and Human Genetics, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Kenneth S Kendler
- Departments of Psychiatry and Human Genetics, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Shane E McCarthy
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
| | - William R McCombie
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
| | - Alex Richards
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, United Kingdom
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, United Kingdom
| | - Michael C O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, United Kingdom
| | - James Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, United Kingdom
| | - Gary Donohoe
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition & Genomics (NICOG) Centre & NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine and Discipline of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine and Discipline of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Derek W Morris
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition & Genomics (NICOG) Centre & NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
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7
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Lifestyle and Environmental Factors in Multiple Sclerosis. Cold Spring Harb Perspect Med 2019; 9:cshperspect.a028944. [PMID: 29735578 DOI: 10.1101/cshperspect.a028944] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Lifestyle and environmental factors potently influence the risk of multiple sclerosis (MS), because genetic predisposition only explains a fraction of the risk increase. There is strong evidence for associations of Epstein-Barr virus (EBV) infection, smoking, sun exposure/vitamin D, and adolescent obesity to risk of MS. There is also circumstantial evidence on organic solvents and shift work, all associate with greater risk, although certain factors like nicotine, alcohol, and a high coffee consumption associate with a reduced risk. Certain factors, smoking, EBV infection, and obesity interact with human leukocyte antigen (HLA) risk genes, arguing for a pathogenic pathway involving adaptive immunity. There is a potential for prevention, in particular for people at greater risk such as relatives of individuals with MS. All of the described factors for MS may influence adaptive and/or innate immunity, as has been argued for MS risk gene variants.
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8
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Yang X, Wu W, Peng M, Shen Q, Feng J, Lai W, Zhu H, Tu C, Quan X, Chen Y, Qin L, Li D, He L, Zhang Y. Identity-by-Descent Analysis Reveals Susceptibility Loci for Severe Acne in Chinese Han Cohort. J Invest Dermatol 2019; 139:2049-2051.e20. [PMID: 30922884 DOI: 10.1016/j.jid.2019.03.1132] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 02/20/2019] [Accepted: 03/05/2019] [Indexed: 10/27/2022]
Affiliation(s)
- Xingyan Yang
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, China
| | - Wenjuan Wu
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Institute of Dermatology and Venereology of Yunnan Province, Kunming, China
| | - Minsheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; KIZ/CUHK Joint Laboratory of Bio-Resources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Quankuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Jiaqi Feng
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Institute of Dermatology and Venereology of Yunnan Province, Kunming, China
| | - Wei Lai
- Department of Dermatology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Huilan Zhu
- Guangzhou Institute of Dermatology, Guangzhou, China
| | - Caixia Tu
- Department of Dermatology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiaorong Quan
- Guilin Skin Disease Prevention and Treatment Hospital, Guilin, China
| | - Yihong Chen
- Department of Dermatology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China
| | - Lanying Qin
- Department of Dermatology, Cangzhou People's Hospital, Cangzhou, China
| | - Donglin Li
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Institute of Dermatology and Venereology of Yunnan Province, Kunming, China
| | - Li He
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Institute of Dermatology and Venereology of Yunnan Province, Kunming, China.
| | - Yaping Zhang
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, China; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; KIZ/CUHK Joint Laboratory of Bio-Resources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
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Abstract
PURPOSE OF REVIEW The area of multiple sclerosis (MS) epidemiology has expanded during the last few years. Established lifestyle and environmental factors influencing MS risk are Epstein-Barr virus infection, sun exposure/vitamin D, and smoking. We review these factors and a series of other potential candidates implicated in the pathogenesis of MS and how environmental factors interact with genetic susceptibility with regard to disease risk. RECENT FINDINGS On top of established MS-associated factors, there is now strong evidence for influence of adolescent obesity, exposure to organic solvents and shift work, all demonstrating increased risk of disease. Other factors, such as nicotine, alcohol, and high coffee consumption are associated with decreased MS risk. A number of lifestyle/environmental factors, including smoking and obesity, seem to interact with MS risk human leukocyte antigen genes, conferring much stronger effects on disease risk among those exposed to both factors. Furthermore, an interaction between two environmental factors, obesity and infectious mononucleosis, with regard to MS risk, has been demonstrated in two independent studies. SUMMARY MS is a complex disease for which both genetic susceptibility and lifestyle/environmental factors are important, and where the latter may be of great importance. Lifestyle and environmental factors can often be modified and may denote pathogenic pathways.
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10
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Yang X, Shen Q, Sulaiman X, Liu H, Peng M, Zhang Y. Identity-by-descent refines mapping of candidate regions for preaxial polydactyly II /III in a large Chinese pedigree. Hereditas 2017; 155:2. [PMID: 28690477 PMCID: PMC5496229 DOI: 10.1186/s41065-017-0040-6] [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: 03/26/2017] [Accepted: 06/22/2017] [Indexed: 11/10/2022] Open
Abstract
Preaxial polydactyly (PPD) is congenital hand malformation characterized by the duplication of digit. Herein, we scan the genome-wide SNPs for a large Chinese family with PPD-II/III. We employ the refined IBD algorithm to identify the identity-by-decent (IBD) segments and compare the frequency among the patients and normal relatives. A total of 72 markers of 0.01 percentile of the permutation are identified as the peak signals. Among of them, 57markers locate on chromosome 7q36 which is associated with PPD. Further analyses refine the mapping of candidate region in chromosome 7q36 into two 380 Kb fragments within LMBR1 and SHH respectively. IBD approach is a suitable method for mapping causal gene of human disease. Target-enrichment sequencing as well as functional experiments are required to illustrate the pathogenic mechanisms for PPD in the future.
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Affiliation(s)
- Xingyan Yang
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, China
| | - Quankuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,KIZ /CUHK Joint Laboratory of Bio-resources and Molecular Research in Common Diseases, Kunming, China
| | | | - Hequn Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Kunming, China
| | - Minsheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,KIZ /CUHK Joint Laboratory of Bio-resources and Molecular Research in Common Diseases, Kunming, China.,Kunming Institute of Zoology, Chinese Academy of Sciences, 32 Jiaochang Donglu, Kunming, 650223 China
| | - Yaping Zhang
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, Kunming, China.,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,KIZ /CUHK Joint Laboratory of Bio-resources and Molecular Research in Common Diseases, Kunming, China.,Kunming Institute of Zoology, Chinese Academy of Sciences, 32 Jiaochang Donglu, Kunming, 650223 China
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11
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Exploring Identity-By-Descent Segments and Putative Functions Using Different Foundation Parents in Maize. PLoS One 2016; 11:e0168374. [PMID: 27997600 PMCID: PMC5172581 DOI: 10.1371/journal.pone.0168374] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Accepted: 11/29/2016] [Indexed: 02/06/2023] Open
Abstract
Maize foundation parents (FPs) play no-alternative roles in hybrid breeding because they were widely used in the development of new lines and hybrids. The combination of different identity-by-descent (IBD) segments and genes could account for the formation patterns of different FPs, and knowledge of these IBD regions would provide an extensive foundation for the development of new candidate FP lines in future maize breeding. In this paper, a panel of 304 elite lines derived from FPs, i.e., B73, 207, Mo17, and Huangzaosi (HZS), was collected and analyzed using 43,252 single nucleotide polymorphism (SNP) markers. Most IBD segments specific to particular FP groups were identified, including 116 IBD segments in B73, 105 in Mo17, 111 in 207, and 190 in HZS. In these regions, 423 quantitative trait nucleotides (QTNs) associated with 15 agronomic traits and 804 candidate genes were identified. Some known adaptation-related genes, e.g., dwarf8 and vgt1 in HZS, zcn8 and epc in Mo17, and ZmCCT in 207, were validated as being tightly linked to particular IBD segments. In addition, numerous new candidate genes were also identified. For example, GRMZM2G154278 in HZS, which belongs to the cell cycle control family, was closely linked to a QTN of the ear height/plant height (EH/PH) trait; GRMZM2G051943 in 207, which encodes an endochitinase precursor (EP) chitinase, was closely linked to a QTN for kernel density; and GRMZM2G170586 in Mo17 was closely linked to a QTN for ear diameter. Complex correlations among these genes were also found. Many IBD segments and genes were included in the formation of FP lines, and complex regulatory networks exist among them. These results provide new insights on the genetic basis of complex traits and provide new candidate IBD regions or genes for the improvement of special traits in maize production.
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Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nat Rev Neurol 2016; 13:25-36. [PMID: 27934854 DOI: 10.1038/nrneurol.2016.187] [Citation(s) in RCA: 633] [Impact Index Per Article: 79.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Genetic predisposition to multiple sclerosis (MS) only explains a fraction of the disease risk; lifestyle and environmental factors are key contributors to the risk of MS. Importantly, these nongenetic factors can influence pathogenetic pathways, and some of them can be modified. Besides established MS-associated risk factors - high latitude, female sex, smoking, low vitamin D levels caused by insufficient sun exposure and/or dietary intake, and Epstein-Barr virus (EBV) infection - strong evidence now supports obesity during adolescence as a factor increasing MS risk. Organic solvents and shift work have also been reported to confer increased risk of the disease, whereas factors such as use of nicotine or alcohol, cytomegalovirus infection and a high coffee consumption are associated with a reduced risk. Certain factors - smoking, EBV infection and obesity - interact with HLA risk genes, pointing at a pathogenetic pathway involving adaptive immunity. All of the described risk factors for MS can influence adaptive and/or innate immunity, which is thought to be the main pathway modulated by MS risk alleles. Unlike genetic risk factors, many environmental and lifestyle factors can be modified, with potential for prevention, particularly for people at the greatest risk, such as relatives of individuals with MS. Here, we review recent data on environmental and lifestyle factors, with a focus on gene-environment interactions.
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Myhr KM, Grytten N, Torkildsen Ø, Wergeland S, Bø L, Aarseth JH. The Norwegian Multiple Sclerosis Registry and Biobank. Acta Neurol Scand 2016; 132:24-8. [PMID: 26046555 DOI: 10.1111/ane.12427] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/04/2015] [Indexed: 02/01/2023]
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system with unknown cause and various benefits from disease modifying therapies. Systematic recording of data into national MS registries is therefore needed to optimize treatment and define the pathogenesis of the disease. The Norwegian MS Registry and Biobank was established for systematic collection of clinical and epidemiological data, as well as biological samples. Data collection is based on informed consent from the individual patients and recordings by treating neurologists. All researchers have, by application, access to data and biological samples from the Norwegian Multiple Sclerosis Registry and Biobank. By this combined effort from both patients and healthcare personnel, the Registry and Biobank aims to facilitate research for improved understanding of disease mechanisms and improved health care in MS.
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Affiliation(s)
- K.-M. Myhr
- Norwegian Multiple Sclerosis Registry and Biobank; Department of Neurology; Haukeland University Hospital; Bergen Norway
- KG Jebsen MS Research Centre; Department of Clinical Medicine; University of Bergen; Bergen Norway
| | - N. Grytten
- KG Jebsen MS Research Centre; Department of Clinical Medicine; University of Bergen; Bergen Norway
- Norwegian Multiple Sclerosis Competence Centre; Department of Neurology; Haukeland University Hospital; Bergen Norway
| | - Ø. Torkildsen
- KG Jebsen MS Research Centre; Department of Clinical Medicine; University of Bergen; Bergen Norway
- Norwegian Multiple Sclerosis Competence Centre; Department of Neurology; Haukeland University Hospital; Bergen Norway
| | - S. Wergeland
- KG Jebsen MS Research Centre; Department of Clinical Medicine; University of Bergen; Bergen Norway
- Norwegian Multiple Sclerosis Competence Centre; Department of Neurology; Haukeland University Hospital; Bergen Norway
| | - L. Bø
- KG Jebsen MS Research Centre; Department of Clinical Medicine; University of Bergen; Bergen Norway
- Norwegian Multiple Sclerosis Competence Centre; Department of Neurology; Haukeland University Hospital; Bergen Norway
| | - J. H. Aarseth
- Norwegian Multiple Sclerosis Registry and Biobank; Department of Neurology; Haukeland University Hospital; Bergen Norway
- KG Jebsen MS Research Centre; Department of Clinical Medicine; University of Bergen; Bergen Norway
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