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Alenazi AS, Pereira L, Christin PA, Osborne CP, Dunning LT. Identifying genomic regions associated with C 4 photosynthetic activity and leaf anatomy in Alloteropsis semialata. THE NEW PHYTOLOGIST 2024; 243:1698-1710. [PMID: 38953386 DOI: 10.1111/nph.19933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/13/2024] [Indexed: 07/04/2024]
Abstract
C4 photosynthesis is a complex trait requiring multiple developmental and metabolic alterations. Despite this complexity, it has independently evolved over 60 times. However, our understanding of the transition to C4 is complicated by the fact that variation in photosynthetic type is usually segregated between species that diverged a long time ago. Here, we perform a genome-wide association study (GWAS) using the grass Alloteropsis semialata, the only known species to have C3, intermediate, and C4 accessions that recently diverged. We aimed to identify genomic regions associated with the strength of the C4 cycle (measured using δ13C), and the development of C4 leaf anatomy. Genomic regions correlated with δ13C include regulators of C4 decarboxylation enzymes (RIPK), nonphotochemical quenching (SOQ1), and the development of Kranz anatomy (SCARECROW-LIKE). Regions associated with the development of C4 leaf anatomy in the intermediate individuals contain additional leaf anatomy regulators, including those responsible for vein patterning (GSL8) and meristem determinacy (GIF1). The parallel recruitment of paralogous leaf anatomy regulators between A. semialata and other C4 lineages implies the co-option of these genes is context-dependent, which likely has implications for the engineering of the C4 trait into C3 species.
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Affiliation(s)
- Ahmed S Alenazi
- Department of Biological Sciences, College of Science, Northern Border University, Arar, 91431, Saudi Arabia
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Lara Pereira
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Pascal-Antoine Christin
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Colin P Osborne
- Plants, Photosynthesis and Soil, School of Biosciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Luke T Dunning
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
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2
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Arias KD, Fernández I, Gutiérrez JP, Álvarez I, Goyache F. Population dynamics of potentially harmful haplotypes: a pedigree analysis. BMC Genomics 2024; 25:487. [PMID: 38755557 PMCID: PMC11097446 DOI: 10.1186/s12864-024-10407-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 05/13/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND The identification of low-frequency haplotypes, never observed in homozygous state in a population, is considered informative on the presence of potentially harmful alleles (candidate alleles), putatively involved in inbreeding depression. Although identification of candidate alleles is challenging, studies analyzing the dynamics of potentially harmful alleles are lacking. A pedigree of the highly endangered Gochu Asturcelta pig breed, including 471 individuals belonging to 51 different families with at least 5 offspring each, was genotyped using the Axiom PigHDv1 Array (658,692 SNPs). Analyses were carried out on four different cohorts defined according to pedigree depth and at the whole population (WP) level. RESULTS The 4,470 Linkage Blocks (LB) identified in the Base Population (10 individuals), gathered a total of 16,981 alleles in the WP. Up to 5,466 (32%) haplotypes were statistically considered candidate alleles, 3,995 of them (73%) having one copy only. The number of alleles and candidate alleles varied across cohorts according to sample size. Up to 4,610 of the alleles identified in the WP (27% of the total) were present in one cohort only. Parentage analysis identified a total of 67,742 parent-offspring incompatibilities. The number of mismatches varied according to family size. Parent-offspring inconsistencies were identified in 98.2% of the candidate alleles and 100% of the LB in which they were located. Segregation analyses informed that most potential candidate alleles appeared de novo in the pedigree. Only 17 candidate alleles were identified in the boar, sow, and paternal and maternal grandparents and were considered segregants. CONCLUSIONS Our results suggest that neither mutation nor recombination are the major forces causing the apparition of candidate alleles. Their occurrence is more likely caused by Allele-Drop-In events due to SNP calling errors. New alleles appear when wrongly called SNPs are used to construct haplotypes. The presence of candidate alleles in either parents or grandparents of the carrier individuals does not ensure that they are true alleles. Minimum Allele Frequency thresholds may remove informative alleles. Only fully segregant candidate alleles should be considered potentially harmful alleles. A set of 16 candidate genes, potentially involved in inbreeding depression, is described.
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Affiliation(s)
- Katherine D Arias
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, Gijón, 33394, Spain
| | - Iván Fernández
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, Gijón, 33394, Spain
| | - Juan Pablo Gutiérrez
- Departamento de Producción Animal, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, Madrid, 28040, Spain
| | - Isabel Álvarez
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, Gijón, 33394, Spain
| | - Félix Goyache
- Área de Genética y Reproducción Animal, SERIDA-Deva, Camino de Rioseco 1225, Gijón, 33394, Spain.
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Dogantzis KA, Raffiudin R, Putra RE, Shaleh I, Conflitti IM, Pepinelli M, Roberts J, Holmes M, Oldroyd BP, Zayed A, Gloag R. Post-invasion selection acts on standing genetic variation despite a severe founding bottleneck. Curr Biol 2024; 34:1349-1356.e4. [PMID: 38428415 DOI: 10.1016/j.cub.2024.02.010] [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: 09/22/2023] [Revised: 12/12/2023] [Accepted: 02/06/2024] [Indexed: 03/03/2024]
Abstract
Invasive populations often have lower genetic diversity relative to the native-range populations from which they derive.1,2 Despite this, many biological invaders succeed in their new environments, in part due to rapid adaptation.3,4,5,6 Therefore, the role of genetic bottlenecks in constraining the adaptation of invaders is debated.7,8,9,10 Here, we use whole-genome resequencing of samples from a 10-year time-series dataset, representing the natural invasion of the Asian honey bee (Apis cerana) in Australia, to investigate natural selection occurring in the aftermath of a founding event. We find that Australia's A. cerana population was founded by as few as one colony, whose arrival was followed by a period of rapid population expansion associated with an increase of rare variants.11 The bottleneck resulted in a steep loss of overall genetic diversity, yet we nevertheless detected loci with signatures of positive selection during the first years post-invasion. When we investigated the origin of alleles under selection, we found that selection acted primarily on the variation introduced by founders and not on the variants that arose post-invasion by mutation. In all, our data highlight that selection on standing genetic variation can occur in the early years post-invasion, even where founding bottlenecks are severe.
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Affiliation(s)
- Kathleen A Dogantzis
- York University, Department of Biology, 4700 Keele Street, Toronto, ON M3J 1P3, Canada
| | - Rika Raffiudin
- IPB University, Department of Biology, Faculty of Mathematics and Natural Sciences, Bogor 16680, Indonesia
| | - Ramadhani Eka Putra
- Bandung Institute of Technology, School of Life Sciences and Technology, Bandung 40132, West Java, Indonesia
| | - Ismail Shaleh
- IPB University, Department of Biology, Faculty of Mathematics and Natural Sciences, Bogor 16680, Indonesia
| | - Ida M Conflitti
- York University, Department of Biology, 4700 Keele Street, Toronto, ON M3J 1P3, Canada
| | - Mateus Pepinelli
- York University, Department of Biology, 4700 Keele Street, Toronto, ON M3J 1P3, Canada
| | - John Roberts
- Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT 2601, Australia
| | - Michael Holmes
- University of Sydney, School of Life and Environmental Sciences, Sydney, NSW 2006, Australia
| | - Benjamin P Oldroyd
- University of Sydney, School of Life and Environmental Sciences, Sydney, NSW 2006, Australia
| | - Amro Zayed
- York University, Department of Biology, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.
| | - Rosalyn Gloag
- University of Sydney, School of Life and Environmental Sciences, Sydney, NSW 2006, Australia.
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Aw AJ, Spence JP, Song YS. A SIMPLE AND FLEXIBLE TEST OF SAMPLE EXCHANGEABILITY WITH APPLICATIONS TO STATISTICAL GENOMICS. Ann Appl Stat 2024; 18:858-881. [PMID: 38784669 PMCID: PMC11115382 DOI: 10.1214/23-aoas1817] [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] [Indexed: 05/25/2024]
Abstract
In scientific studies involving analyses of multivariate data, basic but important questions often arise for the researcher: Is the sample exchangeable, meaning that the joint distribution of the sample is invariant to the ordering of the units? Are the features independent of one another, or perhaps the features can be grouped so that the groups are mutually independent? In statistical genomics, these considerations are fundamental to downstream tasks such as demographic inference and the construction of polygenic risk scores. We propose a non-parametric approach, which we call the V test, to address these two questions, namely, a test of sample exchangeability given dependency structure of features, and a test of feature independence given sample exchangeability. Our test is conceptually simple, yet fast and flexible. It controls the Type I error across realistic scenarios, and handles data of arbitrary dimensions by leveraging large-sample asymptotics. Through extensive simulations and a comparison against unsupervised tests of stratification based on random matrix theory, we find that our test compares favorably in various scenarios of interest. We apply the test to data from the 1000 Genomes Project, demonstrating how it can be employed to assess exchangeability of the genetic sample, or find optimal linkage disequilibrium (LD) splits for downstream analysis. For exchangeability assessment, we find that removing rare variants can substantially increase the p -value of the test statistic. For optimal LD splitting, the V test reports different optimal splits than previous approaches not relying on hypothesis testing. Software for our methods is available in R (CRAN: flintyR) and Python (PyPI: flintyPy).
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Affiliation(s)
- Alan J Aw
- Department of Statistics, University of California, Berkeley
| | | | - Yun S Song
- Department of Statistics and Computer Science Division, University of California, Berkeley
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Mo C, Ye Z, Pan Y, Zhang Y, Wu Q, Bi C, Liu S, Mitchell B, Kochunov P, Hong LE, Ma T, Chen S. An in-depth association analysis of genetic variants within nicotine-related loci: Meeting in middle of GWAS and genetic fine-mapping. Mol Cell Neurosci 2023; 127:103895. [PMID: 37634742 PMCID: PMC11128188 DOI: 10.1016/j.mcn.2023.103895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 08/21/2023] [Accepted: 08/24/2023] [Indexed: 08/29/2023] Open
Abstract
In the last two decades of Genome-wide association studies (GWAS), nicotine-dependence-related genetic loci (e.g., nicotinic acetylcholine receptor - nAChR subunit genes) are among the most replicable genetic findings. Although GWAS results have reported tens of thousands of SNPs within these loci, further analysis (e.g., fine-mapping) is required to identify the causal variants. However, it is computationally challenging for existing fine-mapping methods to reliably identify causal variants from thousands of candidate SNPs based on the posterior inclusion probability. To address this challenge, we propose a new method to select SNPs by jointly modeling the SNP-wise inference results and the underlying structured network patterns of the linkage disequilibrium (LD) matrix. We use adaptive dense subgraph extraction method to recognize the latent network patterns of the LD matrix and then apply group LASSO to select causal variant candidates. We applied this new method to the UK biobank data to identify the causal variant candidates for nicotine addiction. Eighty-one nicotine addiction-related SNPs (i.e.,-log(p) > 50) of nAChR were selected, which are highly correlated (average r2>0.8) although they are physically distant (e.g., >200 kilobase away) and from various genes. These findings revealed that distant SNPs from different genes can show higher LD r2 than their neighboring SNPs, and jointly contribute to a complex trait like nicotine addiction.
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Affiliation(s)
- Chen Mo
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - Yezhi Pan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - Yuan Zhang
- Department of Statistics, College of Arts and Sciences, Ohio State University, Columbus, Ohio, United States
| | - Qiong Wu
- Department of Mathematics, University of Maryland, College Park, Maryland, United States
| | - Chuan Bi
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China
| | - Braxton Mitchell
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, United States
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Nyangiri OA, Mulindwa J, Namulondo J, Kitibwa A, Nassuuna J, Elliott A, Kimuda MP, Boobo A, Nerima B, Adriko M, Dunton NJ, Madhan GK, Kristiansen M, Casacuberta-Partal M, Noyes H, Matovu E. Variants of IL6, IL10, FCN2, RNASE3, IL12B and IL17B loci are associated with Schistosoma mansoni worm burden in the Albert Nile region of Uganda. PLoS Negl Trop Dis 2023; 17:e0011796. [PMID: 38033168 PMCID: PMC10715658 DOI: 10.1371/journal.pntd.0011796] [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: 04/01/2023] [Revised: 12/12/2023] [Accepted: 11/14/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Individuals genetically susceptible to high schistosomiasis worm burden may contribute disproportionately to transmission and could be prioritized for control. Identifying genes involved may guide development of therapy. METHODOLOGY/PRINCIPAL FINDINGS A cohort of 606 children aged 10-15 years were recruited in the Albert Nile region of Uganda and assessed for Schistosoma mansoni worm burden using the Up-Converting Particle Lateral Flow (UCP-LF) test detecting circulating anodic antigen (CAA), point-of-care Circulating Cathodic Antigen (POC-CCA) and Kato-Katz tests. Whole genome genotyping was conducted on 326 children comprising the top and bottom 25% of worm burden. Linear models were fitted to identify variants associated with worm burden in preselected candidate genes. Expression quantitative trait locus (eQTL) analysis was conducted for candidate genes with UCP-LF worm burden included as a covariate. Single Nucleotide Polymorphism loci associated with UCP-LF CAA included IL6 rs2066992 (OR = 0.43, p = 0.0006) and rs7793163 (OR = 2.0, p = 0.0007); IL21 SNP kgp513476 (OR 1.79, p = 0.0025) and IL17B SNP kgp708159 (OR = 0.35, p = 0.0028). A haplotype in the IL10 locus was associated with lower worm burden (OR = 0.53, p = 0.015) and overlapped SNPs rs1800896, rs1800871 and rs1800872. Significant haplotypes (p<0.05, overlapping significant SNP) associated with worm burden were observed in IL6 and the Th17 pathway IL12B and IL17B genes. There were significant eQTL in the IL6, IL5, IL21, IL25 and IFNG regions. CONCLUSIONS Variants associated with S. mansoni worm burden were in IL6, FCN2, RNASE3, IL10, IL12B and IL17B gene loci. However only eQTL associations remained significant after Bonferroni correction. In summary, immune balance, pathogen recognition and Th17 pathways may play a role in modulating Schistosoma worm burden. Individuals carrying risk variants may be targeted first in allocation of control efforts to reduce the burden of schistosomiasis in the community.
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Affiliation(s)
- Oscar Asanya Nyangiri
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Julius Mulindwa
- Department of Biochemistry and Sports Sciences, College of Natural Sciences, Makerere University, Kampala, Uganda
| | - Joyce Namulondo
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Anna Kitibwa
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Jacent Nassuuna
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
| | - Alison Elliott
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
| | - Magambo Phillip Kimuda
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Alex Boobo
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Barbara Nerima
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
| | - Moses Adriko
- Vector Borne & NTD Control Division, Ministry of Health, Uganda
| | - Nathan J. Dunton
- UCL Genomics core facility, University College London, London, United Kingdom
| | | | - Mark Kristiansen
- UCL Genomics core facility, University College London, London, United Kingdom
| | | | - Harry Noyes
- Centre for Genomic Research, University of Liverpool, Liverpool, United Kingdom
| | - Enock Matovu
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda
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Khvorykh GV, Sapozhnikov NA, Limborska SA, Khrunin AV. Evaluation of Density-Based Spatial Clustering for Identifying Genomic Loci Associated with Ischemic Stroke in Genome-Wide Data. Int J Mol Sci 2023; 24:15355. [PMID: 37895035 PMCID: PMC10607504 DOI: 10.3390/ijms242015355] [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: 07/22/2023] [Revised: 09/19/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
The genetic architecture of ischemic stroke (IS), which is one of the leading causes of death worldwide, is complex and underexplored. The traditional approach for associative gene mapping is genome-wide association studies (GWASs), testing individual single-nucleotide polymorphisms (SNPs) across the genomes of case and control groups. The purpose of this research is to develop an alternative approach in which groups of SNPs are examined rather than individual ones. We proposed, validated and applied to real data a new workflow consisting of three key stages: grouping SNPs in clusters, inferring the haplotypes in the clusters and testing haplotypes for the association with phenotype. To group SNPs, we applied the clustering algorithms DBSCAN and HDBSCAN to linkage disequilibrium (LD) matrices, representing pairwise r2 values between all genotyped SNPs. These clustering algorithms have never before been applied to genotype data as part of the workflow of associative studies. In total, 883,908 SNPs and insertion/deletion polymorphisms from people of European ancestry (4929 cases and 652 controls) were processed. The subsequent testing for frequencies of haplotypes restored in the clusters of SNPs revealed dozens of genes associated with IS and suggested the complex role that protocadherin molecules play in IS. The developed workflow was validated with the use of a simulated dataset of similar ancestry and the same sample sizes. The results of classic GWASs are also provided and discussed. The considered clustering algorithms can be applied to genotypic data to identify the genomic loci associated with different qualitative traits, using the workflow presented in this research.
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Affiliation(s)
| | | | | | - Andrey V. Khrunin
- National Research Centre “Kurchatov Institute”, Kurchatov Sq. 2, Moscow 123182, Russia; (G.V.K.); (N.A.S.); (S.A.L.)
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Vahedi SM, Salek Ardetani S, Brito LF, Karimi K, Pahlavan Afshari K, Banabazi MH. Expanding the application of haplotype-based genomic predictions to the wild: A case of antibody response against Teladorsagia circumcincta in Soay sheep. BMC Genomics 2023; 24:335. [PMID: 37330501 DOI: 10.1186/s12864-023-09407-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 05/24/2023] [Indexed: 06/19/2023] Open
Abstract
BACKGROUND Genomic prediction of breeding values (GP) has been adopted in evolutionary genomic studies to uncover microevolutionary processes of wild populations or improve captive breeding strategies. While recent evolutionary studies applied GP with individual single nucleotide polymorphism (SNP), haplotype-based GP could outperform individual SNP predictions through better capturing the linkage disequilibrium (LD) between the SNP and quantitative trait loci (QTL). This study aimed to evaluate the accuracy and bias of haplotype-based GP of immunoglobulin (Ig) A (IgA), IgE, and IgG against Teladorsagia circumcincta in lambs of an unmanaged sheep population (Soay breed) based on Genomic Best Linear Unbiased Prediction (GBLUP) and five Bayesian [BayesA, BayesB, BayesCπ, Bayesian Lasso (BayesL), and BayesR] methods. RESULTS The accuracy and bias of GPs using SNP, haplotypic pseudo-SNP from blocks with different LD thresholds (0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.00), or the combinations of pseudo-SNPs and non-LD clustered SNPs were obtained. Across methods and marker sets, higher ranges of genomic estimated breeding values (GEBV) accuracies were observed for IgA (0.20 to 0.49), followed by IgE (0.08 to 0.20) and IgG (0.05 to 0.14). Considering the methods evaluated, up to 8% gains in GP accuracy of IgG were achieved using pseudo-SNPs compared to SNPs. Up to 3% gain in GP accuracy for IgA was also obtained using the combinations of the pseudo-SNPs with non-clustered SNPs in comparison to fitting individual SNP. No improvement in GP accuracy of IgE was observed using haplotypic pseudo-SNPs or their combination with non-clustered SNPs compared to individual SNP. Bayesian methods outperformed GBLUP for all traits. Most scenarios yielded lower accuracies for all traits with an increased LD threshold. GP models using haplotypic pseudo-SNPs predicted less-biased GEBVs mainly for IgG. For this trait, lower bias was observed with higher LD thresholds, whereas no distinct trend was observed for other traits with changes in LD. CONCLUSIONS Haplotype information improves GP performance of anti-helminthic antibody traits of IgA and IgG compared to fitting individual SNP. The observed gains in the predictive performances indicate that haplotype-based methods could benefit GP of some traits in wild animal populations.
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Affiliation(s)
- Seyed Milad Vahedi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N5E3, Canada
| | | | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907, USA
| | - Karim Karimi
- Molecular Diagnostics Program, Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, ON, N6A 5W9, Canada
| | - Kian Pahlavan Afshari
- Department of Animal Sciences, Islamic Azad University, Varamin, Varamin-Pishva Branch3381774895, Iran
| | - Mohammad Hossein Banabazi
- Department of Animal Breeding and Genetics (HGEN), Centre for Veterinary Medicine and Animal Science (VHC), Swedish University of Agricultural Sciences (SLU), 75007, Uppsala, Sweden.
- Department of Biotechnology, Animal Science Research Institute of IRAN (ASRI), Agricultural Research, Education & Extension Organization (AREEO), Karaj, 3146618361, Iran.
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Mieno MN, Yamasaki M, Kuchiba A, Yamaji T, Ide K, Tanaka N, Sawada N, Inoue M, Tsugane S, Sawabe M, Iwasaki M. Lack of significant associations between single nucleotide polymorphisms in LPAL2-LPA genetic region and all cancer incidence and mortality in Japanese population: The Japan public health center-based prospective study. Cancer Epidemiol 2023; 85:102395. [PMID: 37321067 DOI: 10.1016/j.canep.2023.102395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 05/02/2023] [Accepted: 05/25/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND High lipoprotein (a) level is an established cardiovascular risk, but its association with non-cardiovascular diseases, especially cancer, is controversial. Serum lipoprotein (a) levels vary widely by genetic backgrounds and are largely determined by the genetic variations of apolipoprotein (a) gene, LPA. In this study, we investigate the association between SNPs in LPA region and cancer incidence and mortality in Japanese. METHODS A genetic cohort study was conducted utilizing the data from 9923 participants in the Japan Public Health Center-based Prospective Study (JPHC Study). Twenty-five SNPs in the LPAL2-LPA region were selected from the genome-wide genotyped data. Cox regression analysis adjusted for the covariates and competing risks of death from other causes, were used to estimate the relative risk (hazard ratios (HR) with 95% confidence intervals (CI)) of overall and site-specific cancer incidence and mortality, for each SNP. RESULTS No significant association was found between SNPs in the LPAL2-LPA region and cancer incidence or mortality (overall/site-specific cancer). In men, however, HRs for stomach cancer incidence of 18SNPs were estimated higher than 1.5 (e.g., 2.15 for rs13202636, model free, 95%CI: 1.28-3.62) and those for stomach cancer mortality of 2SNPs (rs9365171, rs1367211) were estimated 2.13 (recessive, 95%CI:1.04-4.37) and 1.61 (additive, 95%CI: 1.00-2.59). Additionally, the minor allele for SNP rs3798220 showed increased death risk from colorectal cancer (CRC) in men (HR: 3.29, 95% CI:1.59 - 6.81) and decreased CRC incidence risk in women (HR: 0.46, 95%CI: 0.22-0.94). Minor allele carrier of any of 4SNPs could have risk of prostate cancer incidence (e.g., rs9365171 dominant, HR: 1.71, 95%CI: 1.06-2.77). CONCLUSIONS None of the 25 SNPs in the LPAL2-LPA region was found to be significantly associated with cancer incidence or mortality. Considering the possible association between SNPs in LPAL2-LPA region and colorectal, prostate and stomach cancer incidence or mortality, further analysis using different cohorts is warranted.
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Affiliation(s)
- Makiko Naka Mieno
- Department of Medical Informatics, Center for Information, Jichi Medical University, Shimotsuke 329-0498, Japan; Health Data Science Research Section, Healthy Aging Innovation Center, Tokyo Metropolitan Geriatric Research Institute, Tokyo 173-0015, Japan
| | - Maria Yamasaki
- Health Data Science Research Section, Healthy Aging Innovation Center, Tokyo Metropolitan Geriatric Research Institute, Tokyo 173-0015, Japan
| | - Aya Kuchiba
- Biostatistics Division, Center for Research Administration and Support/Division of Biostatistical Research, Institute for Cancer Control, National Cancer Center, Tokyo 104-0045, Japan; Graduate School of Health Innovation, Kanagawa University of Human Services, Kanagawa, 210-0821, Japan
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan.
| | - Keigo Ide
- Health Data Science Research Section, Healthy Aging Innovation Center, Tokyo Metropolitan Geriatric Research Institute, Tokyo 173-0015, Japan; Department of Life Science and Medical Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, Tokyo 162-8480, Japan
| | - Noriko Tanaka
- Health Data Science Research Section, Healthy Aging Innovation Center, Tokyo Metropolitan Geriatric Research Institute, Tokyo 173-0015, Japan.
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan
| | - Manami Inoue
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan; Division of Prevention, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan; National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan
| | - Motoji Sawabe
- Department of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo 113-8519, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan; Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo 104-0045, Japan
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10
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Fu H, Zheng H, Chen X, Weirauch MT, Muglia LJ, Wang L, Liu Y. NOMe-HiC: joint profiling of genetic variant, DNA methylation, chromatin accessibility, and 3D genome in the same DNA molecule. Genome Biol 2023; 24:50. [PMID: 36927507 PMCID: PMC10018866 DOI: 10.1186/s13059-023-02889-x] [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: 12/03/2021] [Accepted: 03/03/2023] [Indexed: 03/18/2023] Open
Abstract
Cis-regulatory elements are coordinated to regulate the expression of their targeted genes. However, the joint measurement of cis-regulatory elements' activities and their interactions in spatial proximity is limited by the current sequencing approaches. We describe a method, NOMe-HiC, which simultaneously captures single-nucleotide polymorphisms, DNA methylation, chromatin accessibility (GpC methyltransferase footprints), and chromosome conformation changes from the same DNA molecule, together with the transcriptome, in a single assay. NOMe-HiC shows high concordance with state-of-the-art mono-omic assays across different molecular measurements and reveals coordinated chromatin accessibility at distal genomic segments in spatial proximity and novel types of long-range allele-specific chromatin accessibility.
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Affiliation(s)
- Hailu Fu
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Haizi Zheng
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Xiaoting Chen
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Matthew T Weirauch
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA
| | - Louis J Muglia
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Present address: Burroughs Wellcome Fund, Research Triangle Park, NC, 27614, USA
| | - Li Wang
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA.
- Department of Biology, Xavier University, Cincinnati, OH, 45207, USA.
| | - Yaping Liu
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA.
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA.
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA.
- Department of Electrical Engineering and Computing Sciences, University of Cincinnati College of Engineering and Applied Science, Cincinnati, OH, 45229, USA.
- University of Cincinnati Cancer Center, Cincinnati, OH, 45219, USA.
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11
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Araujo AC, Carneiro PLS, Oliveira HR, Lewis RM, Brito LF. SNP- and haplotype-based single-step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep. J Anim Breed Genet 2023; 140:216-234. [PMID: 36408677 PMCID: PMC10099590 DOI: 10.1111/jbg.12748] [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: 05/01/2022] [Accepted: 10/23/2022] [Indexed: 11/22/2022]
Abstract
Rambouillet sheep are commonly raised in extensive grazing systems in the US, mainly for wool and meat production. Genomic evaluations in US sheep breeds, including Rambouillet, are still incipient. Therefore, we aimed to evaluate the feasibility of performing genomic prediction of breeding values for various traits in Rambouillet sheep based on single nucleotide polymorphisms (SNP) or haplotypes (fitted as pseudo-SNP) under a single-step GBLUP approach. A total of 28,834 records for birth weight (BWT), 23,306 for postweaning weight (PWT), 5,832 for yearling weight (YWT), 9,880 for yearling fibre diameter (YFD), 11,872 for yearling greasy fleece weight (YGFW), and 15,984 for number of lambs born (NLB) were used in this study. Seven hundred forty-one individuals were genotyped using a moderate (50 K; n = 677) or high (600 K; n = 64) density SNP panel, in which 32 K SNP in common between the two SNP panels (after genotypic quality control) were used for further analyses. Single-step genomic predictions using SNP (H-BLUP) or haplotypes (HAP-BLUP) from blocks with different linkage disequilibrium (LD) thresholds (0.15, 0.35, 0.50, 0.65, and 0.80) were evaluated. We also considered different blending parameters when constructing the genomic relationship matrix used to predict the genomic-enhanced estimated breeding values (GEBV), with alpha equal to 0.95 or 0.50. The GEBV were compared to the estimated breeding values (EBV) obtained from traditional pedigree-based evaluations (A-BLUP). The mean theoretical accuracy ranged from 0.499 (A-BLUP for PWT) to 0.795 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.35 and alpha equal to 0.95 for YFD). The prediction accuracies ranged from 0.143 (A-BLUP for PWT) to 0.330 (A-BLUP for YGFW) while the prediction bias ranged from -0.104 (H-BLUP for PWT) to 0.087 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.15 and alpha equal to 0.95 for YGFW). The GEBV dispersion ranged from 0.428 (A-BLUP for PWT) to 1.035 (A-BLUP for YGFW). Similar results were observed for H-BLUP or HAP-BLUP, independently of the LD threshold to create the haplotypes, alpha value, or trait analysed. Using genomic information (fitting individual SNP or haplotypes) provided similar or higher prediction and theoretical accuracies and reduced the dispersion of the GEBV for body weight, wool, and reproductive traits in Rambouillet sheep. However, there were no clear improvements in the prediction bias when compared to pedigree-based predictions. The next step will be to enlarge the training populations for this breed to increase the benefits of genomic predictions.
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Affiliation(s)
- Andre C. Araujo
- Graduate Program in Animal SciencesState University of Southwestern BahiaItapetingaBahiaBrazil
- Department of Animal SciencesPurdue UniversityWest LafayetteIndianaUSA
| | | | | | - Ronald M. Lewis
- Department of Animal SciencesUniversity of Nebraska‐LincolnLincolnNebraskaUSA
| | - Luiz F. Brito
- Department of Animal SciencesPurdue UniversityWest LafayetteIndianaUSA
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12
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Wang F, Moon W, Letsou W, Sapkota Y, Wang Z, Im C, Baedke JL, Robison L, Yasui Y. Genome-Wide Analysis of Rare Haplotypes Associated with Breast Cancer Risk. Cancer Res 2023; 83:332-345. [PMID: 36354368 PMCID: PMC9852031 DOI: 10.1158/0008-5472.can-22-1888] [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: 06/13/2022] [Revised: 09/09/2022] [Accepted: 11/08/2022] [Indexed: 11/12/2022]
Abstract
Numerous common genetic variants have been linked to breast cancer risk, but they only partially explain the total breast cancer heritability. Inference from Nordic population-based twin data indicates rare high-risk loci as the chief determinant of breast cancer risk. Here, we use haplotypes, rather than single variants, to identify rare high-risk loci for breast cancer. With computationally phased genotypes from 181,034 white British women in the UK Biobank, a genome-wide haplotype-breast cancer association analysis was conducted using sliding windows of 5 to 500 consecutive array-genotyped variants. In the discovery stage, haplotype-breast cancer associations were evaluated retrospectively in the prestudy-enrollment data including 5,487 breast cancer cases. Breast cancer hazard ratios (HR) for additive haplotypic effects were estimated using Cox regression. The replication analysis included a prospective cohort of women free of breast cancer at enrollment, of whom 3,524 later developed breast cancer. This two-stage analysis detected 13 rare loci (frequency <1%), each associated with an appreciable breast cancer-risk increase (discovery: HRs = 2.84-6.10, P < 5 × 10-8; replication: HRs = 2.08-5.61, P < 0.01). In contrast, the variants that formed these rare haplotypes individually exhibited much smaller effects. Functional annotation revealed extensive cis-regulatory DNA elements in breast cancer-related cells underlying the replicated rare haplotypes. Using phased, imputed genotypes from 30,064 cases and 25,282 controls in the DRIVE OncoArray case-control study, 6 of the 13 rare-loci associations were found generalizable (odds ratio estimates: 1.48-7.67, P < 0.05). This study demonstrates the complementary advantage of utilizing rare haplotypes to capture novel risk loci and suggests the potential for the discovery of more genetic elements contributing to cancer heritability as large data sets of germline whole-genome sequencing become available. SIGNIFICANCE A genome-wide two-stage haplotype analysis identifies rare haplotypes associated with breast cancer risk and suggests that the rare risk haplotypes represent long-range interactions with regulatory consequences influencing cancer risk.
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Affiliation(s)
- Fan Wang
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Wonjong Moon
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - William Letsou
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Yadav Sapkota
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Zhaoming Wang
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Cindy Im
- School of Public Health, University of Alberta, Edmonton, Alberta T6G 1C9, Canada
| | - Jessica L. Baedke
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Leslie Robison
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
- School of Public Health, University of Alberta, Edmonton, Alberta T6G 1C9, Canada
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13
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Prioritized candidate causal haplotype blocks in plant genome-wide association studies. PLoS Genet 2022; 18:e1010437. [PMID: 36251695 PMCID: PMC9612827 DOI: 10.1371/journal.pgen.1010437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 10/27/2022] [Accepted: 09/20/2022] [Indexed: 11/05/2022] Open
Abstract
Genome wide association studies (GWAS) can play an essential role in understanding genetic basis of complex traits in plants and animals. Conventional SNP-based linear mixed models (LMM) that marginally test single nucleotide polymorphisms (SNPs) have successfully identified many loci with major and minor effects in many GWAS. In plant, the relatively small population size in GWAS and the high genetic diversity found in many plant species can impede mapping efforts on complex traits. Here we present a novel haplotype-based trait fine-mapping framework, HapFM, to supplement current GWAS methods. HapFM uses genotype data to partition the genome into haplotype blocks, identifies haplotype clusters within each block, and then performs genome-wide haplotype fine-mapping to prioritize the candidate causal haplotype blocks of trait. We benchmarked HapFM, GEMMA, BSLMM, GMMAT, and BLINK in both simulated and real plant GWAS datasets. HapFM consistently resulted in higher mapping power than the other GWAS methods in high polygenicity simulation setting. Moreover, it resulted in smaller mapping intervals, especially in regions of high LD, achieved by prioritizing small candidate causal blocks in the larger haplotype blocks. In the Arabidopsis flowering time (FT10) datasets, HapFM identified four novel loci compared to GEMMA’s results, and the average mapping interval of HapFM was 9.6 times smaller than that of GEMMA. In conclusion, HapFM is tailored for plant GWAS to result in high mapping power on complex traits and improved on mapping resolution to facilitate crop improvement. Genome-wide association studies (GWAS) are commonly used in human and plant studies to identify genetic variants responsible for the phenotype of interest and provide foundations for studying disease mechanisms and crop improvement. Most GWAS models are developed and optimized using human datasets. However, the difference between human and plant datasets essentially limits their applications in plant studies, especially when mapping complex traits such as drought resistance and yield. In this study, we present a novel GWAS method, HapFM, tailored for plant datasets to overcome the difficulties of many conventional GWAS methods. HapFM resulted in higher statistical power than conventional GWAS methods for mapping complex traits in our simulation and real dataset analyses. In addition, HapFM reduced the mapping interval by prioritizing candidate causal regions in the genome, which benefits the downstream experimental studies. Last but not least, HapFM can incorporate biological annotations to increase statistical power further. Overall, HapFM balances statistical power, result interpretability, and downstream experimental verifiability.
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14
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SCN1A overexpression, associated with a genomic region marked by a risk variant for a common epilepsy, raises seizure susceptibility. Acta Neuropathol 2022; 144:107-127. [PMID: 35551471 PMCID: PMC9217876 DOI: 10.1007/s00401-022-02429-0] [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: 03/16/2022] [Revised: 04/29/2022] [Accepted: 04/30/2022] [Indexed: 11/01/2022]
Abstract
Mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures is associated with common variation at rs7587026, located in the promoter region of SCN1A. We sought to explore possible underlying mechanisms. SCN1A expression was analysed in hippocampal biopsy specimens of individuals with mesial temporal lobe epilepsy with hippocampal sclerosis who underwent surgical treatment, and hippocampal neuronal cell loss was quantitatively assessed using immunohistochemistry. In healthy individuals, hippocampal volume was measured using MRI. Analyses were performed stratified by rs7587026 type. To study the functional consequences of increased SCN1A expression, we generated, using transposon-mediated bacterial artificial chromosome transgenesis, a zebrafish line expressing exogenous scn1a, and performed EEG analysis on larval optic tecta at 4 day post-fertilization. Finally, we used an in vitro promoter analysis to study whether the genetic motif containing rs7587026 influences promoter activity. Hippocampal SCN1A expression differed by rs7587026 genotype (Kruskal-Wallis test P = 0.004). Individuals homozygous for the minor allele showed significantly increased expression compared to those homozygous for the major allele (Dunn's test P = 0.003), and to heterozygotes (Dunn's test P = 0.035). No statistically significant differences in hippocampal neuronal cell loss were observed between the three genotypes. Among 597 healthy participants, individuals homozygous for the minor allele at rs7587026 displayed significantly reduced mean hippocampal volume compared to major allele homozygotes (Cohen's D = - 0.28, P = 0.02), and to heterozygotes (Cohen's D = - 0.36, P = 0.009). Compared to wild type, scn1lab-overexpressing zebrafish larvae exhibited more frequent spontaneous seizures [one-way ANOVA F(4,54) = 6.95 (P < 0.001)]. The number of EEG discharges correlated with the level of scn1lab overexpression [one-way ANOVA F(4,15) = 10.75 (P < 0.001]. Finally, we showed that a 50 bp promoter motif containing rs7587026 exerts a strong regulatory role on SCN1A expression, though we could not directly link this to rs7587026 itself. Our results develop the mechanistic link between rs7587026 and mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures. Furthermore, we propose that quantitative precision may be important when increasing SCN1A expression in current strategies aiming to treat seizures in conditions involving SCN1A haploinsufficiency, such as Dravet syndrome.
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15
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Ollivier R, Glory I, Cloteau R, Le Gallic JF, Denis G, Morlière S, Miteul H, Rivière JP, Lesné A, Klein A, Aubert G, Kreplak J, Burstin J, Pilet-Nayel ML, Simon JC, Sugio A. A major-effect genetic locus, ApRVII, controlling resistance against both adapted and non-adapted aphid biotypes in pea. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:1511-1528. [PMID: 35192006 DOI: 10.1007/s00122-022-04050-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 01/28/2022] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE A genome-wide association study for pea resistance against a pea-adapted biotype and a non-adapted biotype of the aphid, Acyrthosiphon pisum, identified a genomic region conferring resistance to both biotypes. In a context of reduced insecticide use, the development of cultivars resistant to insect pests is crucial for an integrated pest management. Pea (Pisum sativum) is a crop of major importance among cultivated legumes, for the supply of dietary proteins and nitrogen in low-input cropping systems. However, yields of the pea crop have become unstable due to plant parasites. The pea aphid (Acyrthosiphon pisum) is an insect pest species forming a complex of biotypes, each one adapted to feed on one or a few related legume species. This study aimed to identify resistance to A. pisum and the underlying genetic determinism by examining a collection of 240 pea genotypes. The collection was screened against a pea-adapted biotype and a non-adapted biotype of A. pisum to characterize their resistant phenotype. Partial resistance was observed in some pea genotypes exposed to the pea-adapted biotype. Many pea genotypes were completely resistant to non-adapted biotype, but some exhibited partial susceptibility. A genome-wide association study, using pea exome-capture sequencing data, enabled the identification of the major-effect quantitative trait locus ApRVII on the chromosome 7. ApRVII includes linkage disequilibrium blocks significantly associated with resistance to one or both of the two aphid biotypes studied. Finally, we identified candidate genes underlying ApRVII that are potentially involved in plant-aphid interactions and marker haplotypes linked with aphid resistance. This study sets the ground for the functional characterization of molecular pathways involved in pea defence to the aphids but also is a step forward for breeding aphid-resistant cultivars.
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Affiliation(s)
- Rémi Ollivier
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
| | - Isabelle Glory
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
| | - Romuald Cloteau
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
| | | | - Gaëtan Denis
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
| | | | - Henri Miteul
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
| | | | - Angélique Lesné
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
| | - Anthony Klein
- Agroécologie, INRAE, AgroSup Dijon, Univ Bourgogne-Franche-Comté, 21065, Dijon, France
| | - Grégoire Aubert
- Agroécologie, INRAE, AgroSup Dijon, Univ Bourgogne-Franche-Comté, 21065, Dijon, France
| | - Jonathan Kreplak
- Agroécologie, INRAE, AgroSup Dijon, Univ Bourgogne-Franche-Comté, 21065, Dijon, France
| | - Judith Burstin
- Agroécologie, INRAE, AgroSup Dijon, Univ Bourgogne-Franche-Comté, 21065, Dijon, France
| | | | | | - Akiko Sugio
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France.
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16
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Balagué-Dobón L, Cáceres A, González JR. Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure. Brief Bioinform 2022; 23:6535682. [PMID: 35211719 PMCID: PMC8921734 DOI: 10.1093/bib/bbac043] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 01/25/2022] [Accepted: 01/28/2022] [Indexed: 12/12/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.
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17
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Araujo AC, Carneiro PLS, Alvarenga AB, Oliveira HR, Miller SP, Retallick K, Brito LF. Haplotype-Based Single-Step GWAS for Yearling Temperament in American Angus Cattle. Genes (Basel) 2021; 13:17. [PMID: 35052358 PMCID: PMC8775055 DOI: 10.3390/genes13010017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/14/2021] [Accepted: 12/18/2021] [Indexed: 01/23/2023] Open
Abstract
Behavior is a complex trait and, therefore, understanding its genetic architecture is paramount for the development of effective breeding strategies. The objective of this study was to perform traditional and weighted single-step genome-wide association studies (ssGWAS and WssGWAS, respectively) for yearling temperament (YT) in North American Angus cattle using haplotypes. Approximately 266 K YT records and 70 K animals genotyped using a 50 K single nucleotide polymorphisms (SNP) panel were used. Linkage disequilibrium thresholds (LD) of 0.15, 0.50, and 0.80 were used to create the haploblocks, and the inclusion of non-LD-clustered SNPs (NCSNP) with the haplotypes in the genomic models was also evaluated. WssGWAS did not perform better than ssGWAS. Cattle YT was found to be a highly polygenic trait, with genes and quantitative trait loci (QTL) broadly distributed across the whole genome. Association studies using LD-based haplotypes should include NCSNPs and different LD thresholds to increase the likelihood of finding the relevant genomic regions affecting the trait of interest. The main candidate genes identified, i.e., ATXN10, ADAM10, VAX2, ATP6V1B1, CRISPLD1, CAPRIN1, FA2H, SPEF2, PLXNA1, and CACNA2D3, are involved in important biological processes and metabolic pathways related to behavioral traits, social interactions, and aggressiveness in cattle. Future studies should further investigate the role of these candidate genes.
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Affiliation(s)
- Andre C. Araujo
- Graduate Program in Animal Sciences, State University of Southwestern Bahia, Itapetinga 45700-000, Brazil;
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
| | - Paulo L. S. Carneiro
- Department of Biology, State University of Southwest Bahia, Jequié 45205-490, Brazil;
| | - Amanda B. Alvarenga
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
| | - Hinayah R. Oliveira
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G2W1, Canada
| | - Stephen P. Miller
- American Angus Association, Angus Genetics Inc., 3201 Frederick Ave, St. Joseph, MO 64506, USA; (S.P.M.); (K.R.)
| | - Kelli Retallick
- American Angus Association, Angus Genetics Inc., 3201 Frederick Ave, St. Joseph, MO 64506, USA; (S.P.M.); (K.R.)
| | - Luiz F. Brito
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
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18
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Pagni S, Mills JD, Frankish A, Mudge JM, Sisodiya SM. Non-coding regulatory elements: Potential roles in disease and the case of epilepsy. Neuropathol Appl Neurobiol 2021; 48:e12775. [PMID: 34820881 DOI: 10.1111/nan.12775] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/04/2021] [Accepted: 11/16/2021] [Indexed: 12/27/2022]
Abstract
Non-coding DNA (ncDNA) refers to the portion of the genome that does not code for proteins and accounts for the greatest physical proportion of the human genome. ncDNA includes sequences that are transcribed into RNA molecules, such as ribosomal RNAs (rRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and un-transcribed sequences that have regulatory functions, including gene promoters and enhancers. Variation in non-coding regions of the genome have an established role in human disease, with growing evidence from many areas, including several cancers, Parkinson's disease and autism. Here, we review the features and functions of the regulatory elements that are present in the non-coding genome and the role that these regions have in human disease. We then review the existing research in epilepsy and emphasise the potential value of further exploring non-coding regulatory elements in epilepsy. In addition, we outline the most widely used techniques for recognising regulatory elements throughout the genome, current methodologies for investigating variation and the main challenges associated with research in the field of non-coding DNA.
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Affiliation(s)
- Susanna Pagni
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - James D Mills
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont St Peter, UK.,Amsterdam UMC, Department of (Neuro)Pathology, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, Netherlands
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont St Peter, UK
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19
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Araujo AC, Carneiro PLS, Oliveira HR, Schenkel FS, Veroneze R, Lourenco DAL, Brito LF. A Comprehensive Comparison of Haplotype-Based Single-Step Genomic Predictions in Livestock Populations With Different Genetic Diversity Levels: A Simulation Study. Front Genet 2021; 12:729867. [PMID: 34721524 PMCID: PMC8551834 DOI: 10.3389/fgene.2021.729867] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/07/2021] [Indexed: 11/13/2022] Open
Abstract
The level of genetic diversity in a population is inversely proportional to the linkage disequilibrium (LD) between individual single nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs), leading to lower predictive ability of genomic breeding values (GEBVs) in high genetically diverse populations. Haplotype-based predictions could outperform individual SNP predictions by better capturing the LD between SNP and QTL. Therefore, we aimed to evaluate the accuracy and bias of individual-SNP- and haplotype-based genomic predictions under the single-step-genomic best linear unbiased prediction (ssGBLUP) approach in genetically diverse populations. We simulated purebred and composite sheep populations using literature parameters for moderate and low heritability traits. The haplotypes were created based on LD thresholds of 0.1, 0.3, and 0.6. Pseudo-SNPs from unique haplotype alleles were used to create the genomic relationship matrix ( G ) in the ssGBLUP analyses. Alternative scenarios were compared in which the pseudo-SNPs were combined with non-LD clustered SNPs, only pseudo-SNPs, or haplotypes fitted in a second G (two relationship matrices). The GEBV accuracies for the moderate heritability-trait scenarios fitting individual SNPs ranged from 0.41 to 0.55 and with haplotypes from 0.17 to 0.54 in the most (Ne ≅ 450) and less (Ne < 200) genetically diverse populations, respectively, and the bias fitting individual SNPs or haplotypes ranged between -0.14 and -0.08 and from -0.62 to -0.08, respectively. For the low heritability-trait scenarios, the GEBV accuracies fitting individual SNPs ranged from 0.24 to 0.32, and for fitting haplotypes, it ranged from 0.11 to 0.32 in the more (Ne ≅ 250) and less (Ne ≅ 100) genetically diverse populations, respectively, and the bias ranged between -0.36 and -0.32 and from -0.78 to -0.33 fitting individual SNPs or haplotypes, respectively. The lowest accuracies and largest biases were observed fitting only pseudo-SNPs from blocks constructed with an LD threshold of 0.3 (p < 0.05), whereas the best results were obtained using only SNPs or the combination of independent SNPs and pseudo-SNPs in one or two G matrices, in both heritability levels and all populations regardless of the level of genetic diversity. In summary, haplotype-based models did not improve the performance of genomic predictions in genetically diverse populations.
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Affiliation(s)
- Andre C Araujo
- Postgraduate Program in Animal Sciences, State University of Southwestern Bahia, Itapetinga, Brazil.,Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Paulo L S Carneiro
- Department of Biology, State University of Southwestern Bahia, Jequié, Brazil
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States.,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Renata Veroneze
- Department of Animal Sciences, Federal University of Viçosa, Viçosa, Brazil
| | - Daniela A L Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
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20
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Miculan M, Nelissen H, Ben Hassen M, Marroni F, Inzé D, Pè ME, Dell’Acqua M. A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays). THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 107:1056-1071. [PMID: 34087008 PMCID: PMC8519057 DOI: 10.1111/tpj.15364] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 05/31/2021] [Indexed: 05/13/2023]
Abstract
The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript-trait correlations. Then, leaf traits were associated with SNPs in a genome-wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript-trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co-expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.
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Affiliation(s)
- Mara Miculan
- Institute of Life SciencesScuola Superiore Sant’AnnaPisa56127Italy
| | - Hilde Nelissen
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhent9052Belgium
- Center for Plant Systems Biology, VIBGhent9052Belgium
| | - Manel Ben Hassen
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhent9052Belgium
- Center for Plant Systems Biology, VIBGhent9052Belgium
| | - Fabio Marroni
- IGA Technology ServicesUdine33100Italy
- Department of Agricultural, FoodAT, Environmental and Animal Sciences (DI4A)University of UdineUdine33100Italy
| | - Dirk Inzé
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhent9052Belgium
- Center for Plant Systems Biology, VIBGhent9052Belgium
| | - Mario Enrico Pè
- Institute of Life SciencesScuola Superiore Sant’AnnaPisa56127Italy
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21
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Privé F. Optimal linkage disequilibrium splitting. Bioinformatics 2021; 38:255-256. [PMID: 34260708 PMCID: PMC8696101 DOI: 10.1093/bioinformatics/btab519] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 05/22/2021] [Accepted: 07/09/2021] [Indexed: 02/05/2023] Open
Abstract
MOTIVATION A few algorithms have been developed for splitting the genome in nearly independent blocks of linkage disequilibrium. Due to the complexity of this problem, these algorithms rely on heuristics, which makes them suboptimal. RESULTS Here, we develop an optimal solution for this problem using dynamic programming. AVAILABILITY This is now implemented as function snp_ldsplit as part of R package bigsnpr. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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22
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Al Bkhetan Z, Chana G, Soon Ong C, Goudey B, Ramamohanarao K. eQTLHap: a tool for comprehensive eQTL analysis considering haplotypic and genotypic effects. Brief Bioinform 2021; 22:6214641. [PMID: 33834181 DOI: 10.1093/bib/bbab093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION The high accuracy of recent haplotype phasing tools is enabling the integration of haplotype (or phase) information more widely in genetic investigations. One such possibility is phase-aware expression quantitative trait loci (eQTL) analysis, where haplotype-based analysis has the potential to detect associations that may otherwise be missed by standard SNP-based approaches. RESULTS We present eQTLHap, a novel method to investigate associations between gene expression and genetic variants, considering their haplotypic and genotypic effect. Using multiple simulations based on real data, we demonstrate that phase-aware eQTL analysis significantly outperforms typical SNP-based methods when the causal genetic architecture involves multiple SNPs. We show that phase-aware eQTL analysis is robust to phasing errors, showing only a minor impact ($<4\%$) on sensitivity. Applying eQTLHap to real GEUVADIS and GTEx datasets detects numerous novel eQTLs undetected by a single-SNP approach, with 22 eQTLs replicating across studies or tissue types, highlighting the utility of phase-aware eQTL analysis. AVAILABILITY AND IMPLEMENTATION https://github.com/ziadbkh/eQTLHap. CONTACT ziad.albkhetan@gmail.com. SUPPLEMENTARY INFORMATION Supplementary data are available at Briefings in Bioinformatics online.
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Affiliation(s)
- Ziad Al Bkhetan
- School of Computing and Information Systems, The University of Melbourne, Parkville, 3010, Australia
| | - Gursharan Chana
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, 3010, Australia
| | | | - Benjamin Goudey
- School of Computing and Information Systems, The University of Melbourne, Parkville, 3010, Australia.,IBM Australia Research, Southgate, Victoria, Australia
| | - Kotagiri Ramamohanarao
- School of Computing and Information Systems, The University of Melbourne, Parkville, 3010, Australia
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23
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Jiang N, Fu J, Zeng Q, Liang Y, Shi Y, Li Z, Xiao Y, He Z, Wu Y, Long Y, Wang K, Yang Y, Liu X, Peng J. Genome-wide association mapping for resistance to bacterial blight and bacterial leaf streak in rice. PLANTA 2021; 253:94. [PMID: 33830376 DOI: 10.1007/s00425-021-03612-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Accepted: 03/24/2021] [Indexed: 06/12/2023]
Abstract
Using genome-wide SNP association mapping, a total of 77 and 7 loci were identified for rice bacterial blight and bacterial leaf streak resistance, respectively, which may facilitate rice resistance improvement. Bacterial blight (BB) and bacterial leaf streak (BLS) caused by Gram-negative bacteria Xanthomonas oryzae pv. oryzae (Xoo) and X. oryzae pv. oryzicola (Xoc), respectively, are two economically important diseases negatively affecting rice production. To mine new sources of resistance, a set of rice germplasm collection consisting of 895 re-sequenced accessions from the 3000 Rice Genomes Project (3 K RGP) were screened for BB and BLS resistance under field conditions. Higher levels of BB resistance were observed in aus/boro subgroup, whereas the japonica, temperate japonica and tropical japonica subgroups possessed comparatively high levels of resistance to BLS. A genome-wide association study (GWAS) mined 77 genomic loci significantly associated with BB and 7 with BLS resistance. The phenotypic variance (R2) explained by these loci ranged from 0.4 to 30.2%. Among the loci, 7 for BB resistance were co-localized with known BB resistance genes and one for BLS resistance overlapped with a previously reported BLS resistance QTL. A search for the candidates in other novel loci revealed several defense-related genes that may be involved in resistance to BB and BLS. High levels of phenotypic resistance to BB or BLS could be attributed to the accumulation of the resistance (R) alleles at the associated loci, indicating their potential value in rice resistance breeding via gene pyramiding. The GWAS analysis validated the known genes underlying BB and BLS resistance and identified novel loci that could enrich the current resistance gene pool. The resources with strong resistance and significant SNPs identified in this study are potentially useful in breeding for BB and BLS resistance.
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Affiliation(s)
- Nan Jiang
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops and College of Agronomy, Hunan Agricultural University, Changsha, China
- Huazhi Bio-Tech Company Ltd., Changsha, China
- Key Laboratory of Southern Rice Innovation and Improvement, Ministry of Agriculture and Rural Affairs, Hunan Engineering Laboratory of Disease and Pest Resistant Rice Breeding, Yuan Longping High-Tech Agriculture Company Ltd., Changsha, China
| | - Jun Fu
- Key Laboratory of Southern Rice Innovation and Improvement, Ministry of Agriculture and Rural Affairs, Hunan Engineering Laboratory of Disease and Pest Resistant Rice Breeding, Yuan Longping High-Tech Agriculture Company Ltd., Changsha, China
| | - Qin Zeng
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Yi Liang
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops and College of Agronomy, Hunan Agricultural University, Changsha, China
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Yanlong Shi
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Zhouwei Li
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Youlun Xiao
- Institute of Plant Protection, Hunan Academy of Agricultural Sciences, Changsha, China
| | - Zhizhou He
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Yuntian Wu
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Yu Long
- Huazhi Bio-Tech Company Ltd., Changsha, China
| | - Kai Wang
- Key Laboratory of Southern Rice Innovation and Improvement, Ministry of Agriculture and Rural Affairs, Hunan Engineering Laboratory of Disease and Pest Resistant Rice Breeding, Yuan Longping High-Tech Agriculture Company Ltd., Changsha, China
| | - Yuanzhu Yang
- Key Laboratory of Southern Rice Innovation and Improvement, Ministry of Agriculture and Rural Affairs, Hunan Engineering Laboratory of Disease and Pest Resistant Rice Breeding, Yuan Longping High-Tech Agriculture Company Ltd., Changsha, China
| | - Xionglun Liu
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops and College of Agronomy, Hunan Agricultural University, Changsha, China.
| | - Junhua Peng
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops and College of Agronomy, Hunan Agricultural University, Changsha, China.
- Huazhi Bio-Tech Company Ltd., Changsha, China.
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24
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Novikova G, Kapoor M, Tcw J, Abud EM, Efthymiou AG, Chen SX, Cheng H, Fullard JF, Bendl J, Liu Y, Roussos P, Björkegren JL, Liu Y, Poon WW, Hao K, Marcora E, Goate AM. Integration of Alzheimer's disease genetics and myeloid genomics identifies disease risk regulatory elements and genes. Nat Commun 2021; 12:1610. [PMID: 33712570 PMCID: PMC7955030 DOI: 10.1038/s41467-021-21823-y] [Citation(s) in RCA: 107] [Impact Index Per Article: 35.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 02/10/2021] [Indexed: 02/07/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer's disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility.
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Affiliation(s)
- Gloriia Novikova
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manav Kapoor
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Julia Tcw
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edsel M Abud
- Department of Neurobiology & Behavior, University of California Irvine, Irvine, CA, USA
- Sue and Bill Gross Stem Cell Research Center, University of California Irvine, Irvine, CA, USA
| | - Anastasia G Efthymiou
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven X Chen
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yiyuan Liu
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan Lm Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Wayne W Poon
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edoardo Marcora
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Alison M Goate
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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25
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Wittenburg D, Doschoris M, Klosa J. Grouping of genomic markers in populations with family structure. BMC Bioinformatics 2021; 22:79. [PMID: 33607943 PMCID: PMC7893918 DOI: 10.1186/s12859-021-04010-0] [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: 08/05/2020] [Accepted: 02/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Linkage and linkage disequilibrium (LD) between genome regions cause dependencies among genomic markers. Due to family stratification in populations with non-random mating in livestock or crop, the standard measures of population LD such as [Formula: see text] may be biased. Grouping of markers according to their interdependence needs to account for the actual population structure in order to allow proper inference in genome-based evaluations. RESULTS Given a matrix reflecting the strength of association between markers, groups are built successively using a greedy algorithm; largest groups are built at first. As an option, a representative marker is selected for each group. We provide an implementation of the grouping approach as a new function to the R package hscovar. This package enables the calculation of the theoretical covariance between biallelic markers for half- or full-sib families and the derivation of representative markers. In case studies, we have shown that the number of groups comprising dependent markers was smaller and representative SNPs were spread more uniformly over the investigated chromosome region when the family stratification was respected compared to a population-LD approach. In a simulation study, we observed that sensitivity and specificity of a genome-based association study improved if selection of representative markers took family structure into account. CONCLUSIONS Chromosome segments which frequently recombine in the underlying population can be identified from the matrix of pairwise dependence between markers. Representative markers can be exploited, for instance, for dimension reduction prior to a genome-based association study or the grouping structure itself can be employed in a grouped penalization approach.
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Affiliation(s)
- Dörte Wittenburg
- Institute of Genetics and Biometry, Leibniz Institute for Farm Animal Biology, 18196 Dummerstorf, Germany
| | - Michael Doschoris
- Institute of Genetics and Biometry, Leibniz Institute for Farm Animal Biology, 18196 Dummerstorf, Germany
| | - Jan Klosa
- Institute of Genetics and Biometry, Leibniz Institute for Farm Animal Biology, 18196 Dummerstorf, Germany
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26
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Discovery of beneficial haplotypes for complex traits in maize landraces. Nat Commun 2020; 11:4954. [PMID: 33009396 PMCID: PMC7532167 DOI: 10.1038/s41467-020-18683-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 09/06/2020] [Indexed: 12/17/2022] Open
Abstract
Genetic variation is of crucial importance for crop improvement. Landraces are valuable sources of diversity, but for quantitative traits efficient strategies for their targeted utilization are lacking. Here, we map haplotype-trait associations at high resolution in ~1000 doubled-haploid lines derived from three maize landraces to make their native diversity for early development traits accessible for elite germplasm improvement. A comparative genomic analysis of the discovered haplotypes in the landrace-derived lines and a panel of 65 breeding lines, both genotyped with 600k SNPs, points to untapped beneficial variation for target traits in the landraces. The superior phenotypic performance of lines carrying favorable landrace haplotypes as compared to breeding lines with alternative haplotypes confirms these findings. Stability of haplotype effects across populations and environments as well as their limited effects on undesired traits indicate that our strategy has high potential for harnessing beneficial haplotype variation for quantitative traits from genetic resources. Genetic variations present in landraces are critical for crop genetic improvement. Here, the authors map haplotype-trait associations in ~1000 doubled haploid lines derived from three European maize landraces and identify beneficial haplotypes for quantitative traits that are not present in breeding lines.
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27
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Varshney RK, Sinha P, Singh VK, Kumar A, Zhang Q, Bennetzen JL. 5Gs for crop genetic improvement. CURRENT OPINION IN PLANT BIOLOGY 2020; 56:190-196. [PMID: 32005553 PMCID: PMC7450269 DOI: 10.1016/j.pbi.2019.12.004] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 11/22/2019] [Accepted: 12/03/2019] [Indexed: 05/20/2023]
Abstract
Here we propose a 5G breeding approach for bringing much-needed disruptive changes to crop improvement. These 5Gs are Genome assembly, Germplasm characterization, Gene function identification, Genomic breeding (GB), and Gene editing (GE). In our view, it is important to have genome assemblies available for each crop and a deep collection of germplasm characterized at sequencing and agronomic levels for identification of marker-trait associations and superior haplotypes. Systems biology and sequencing-based mapping approaches can be used to identify genes involved in pathways leading to the expression of a trait, thereby providing diagnostic markers for target traits. These genes, markers, haplotypes, and genome-wide sequencing data may be utilized in GB and GE methodologies in combination with a rapid cycle breeding strategy.
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Affiliation(s)
- Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
| | - Pallavi Sinha
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Vikas K Singh
- International Rice Research Institute, South Asia Hub, ICRISAT, Hyderabad, 502324, India
| | - Arvind Kumar
- IRRI South Asia Regional Center, NSRTC Campus, G.T. Road, Collectry Farm, P.O. Industrial Estate, Varanasi, 221006, India
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
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28
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Kim SA, Brossard M, Roshandel D, Paterson AD, Bull SB, Yoo YJ. gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks. Bioinformatics 2020; 35:4419-4421. [PMID: 31070701 PMCID: PMC6821423 DOI: 10.1093/bioinformatics/btz308] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 03/30/2019] [Accepted: 04/25/2019] [Indexed: 12/22/2022] Open
Abstract
Summary For the analysis of high-throughput genomic data produced by next-generation sequencing (NGS) technologies, researchers need to identify linkage disequilibrium (LD) structure in the genome. In this work, we developed an R package gpart which provides clustering algorithms to define LD blocks or analysis units consisting of SNPs. The visualization tool in gpart can display the LD structure and gene positions for up to 20 000 SNPs in one image. The gpart functions facilitate construction of LD blocks and SNP partitions for vast amounts of genome sequencing data within reasonable time and memory limits in personal computing environments. Availability and implementation The R package is available at https://bioconductor.org/packages/gpart. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Sun Ah Kim
- The Research Institute of Basic Sciences, Seoul National University, Seoul, South Korea
| | - Myriam Brossard
- Prosserman Centre for Health Research, The Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Delnaz Roshandel
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Andrew D Paterson
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.,Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Shelley B Bull
- Prosserman Centre for Health Research, The Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Yun Joo Yoo
- Department of Mathematics Education, Seoul National University, Seoul, South Korea.,Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
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29
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Pook T, Schlather M, de Los Campos G, Mayer M, Schoen CC, Simianer H. HaploBlocker: Creation of Subgroup-Specific Haplotype Blocks and Libraries. Genetics 2019; 212:1045-1061. [PMID: 31152070 PMCID: PMC6707469 DOI: 10.1534/genetics.119.302283] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 05/30/2019] [Indexed: 11/18/2022] Open
Abstract
The concept of haplotype blocks has been shown to be useful in genetics. Fields of application range from the detection of regions under positive selection to statistical methods that make use of dimension reduction. We propose a novel approach ("HaploBlocker") for defining and inferring haplotype blocks that focuses on linkage instead of the commonly used population-wide measures of linkage disequilibrium. We define a haplotype block as a sequence of genetic markers that has a predefined minimum frequency in the population, and only haplotypes with a similar sequence of markers are considered to carry that block, effectively screening a dataset for group-wise identity-by-descent. From these haplotype blocks, we construct a haplotype library that represents a large proportion of genetic variability with a limited number of blocks. Our method is implemented in the associated R-package HaploBlocker, and provides flexibility not only to optimize the structure of the obtained haplotype library for subsequent analyses, but also to handle datasets of different marker density and genetic diversity. By using haplotype blocks instead of single nucleotide polymorphisms (SNPs), local epistatic interactions can be naturally modeled, and the reduced number of parameters enables a wide variety of new methods for further genomic analyses such as genomic prediction and the detection of selection signatures. We illustrate our methodology with a dataset comprising 501 doubled haploid lines in a European maize landrace genotyped at 501,124 SNPs. With the suggested approach, we identified 2991 haplotype blocks with an average length of 2685 SNPs that together represent 94% of the dataset.
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Affiliation(s)
- Torsten Pook
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, 37075, Germany
- Center for Integrated Breeding Research, University of Goettingen, 37075, Germany
| | - Martin Schlather
- Center for Integrated Breeding Research, University of Goettingen, 37075, Germany
- Stochastics and Its Applications Group, University of Mannheim, 68159, Germany
| | - Gustavo de Los Campos
- Departments of Epidemiology and Biostatistics and Statistics and Probability, Institute for Quantitative Health Science and Engineering, Michigan State University, Michigan 48824
| | - Manfred Mayer
- Plant Breeding, Technical University of Munich School of Life Sciences Weihenstephan, 85354 Freising, Germany
| | - Chris Carolin Schoen
- Plant Breeding, Technical University of Munich School of Life Sciences Weihenstephan, 85354 Freising, Germany
| | - Henner Simianer
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, 37075, Germany
- Center for Integrated Breeding Research, University of Goettingen, 37075, Germany
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Kudinov AA, Dementieva NV, Mitrofanova OV, Stanishevskaya OI, Fedorova ES, Larkina TA, Mishina AI, Plemyashov KV, Griffin DK, Romanov MN. Genome-wide association studies targeting the yield of extraembryonic fluid and production traits in Russian White chickens. BMC Genomics 2019; 20:270. [PMID: 30947682 PMCID: PMC6449956 DOI: 10.1186/s12864-019-5605-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 03/13/2019] [Indexed: 01/09/2023] Open
Abstract
Background The Russian White is a gene pool breed, registered in 1953 after crossing White Leghorns with local populations and, for 50 years, selected for cold tolerance and high egg production (EL). The breed has great potential in meeting demands of local food producers, commercial farmers and biotechnology sector of specific pathogen-free (SPF) eggs, the former valuing the breed for its egg weight (EW), EL, age at first egg (AFE), body weight (BW), and the latter for its yield of extraembryonic fluid (YEF) in 12.5-day embryos, ratio of extraembryonic fluid to egg weight, and embryo mass. Moreover, its cold tolerance has been presumably associated with day-old chick down colour (DOCDC) – white rather than yellow, the genetic basis of these traits being however poorly understood. Results We undertook genome-wide association studies (GWASs) for eight performance traits using single nucleotide polymorphism (SNP) genotyping of 146 birds and an Illumina 60KBeadChip. Several suggestive associations (p < 5.16*10− 5) were found for YEF, AFE, BW and EW. Moreover, on chromosome 2, an association with the white DOCDC was found where there is an linkage disequilibrium block of SNPs including genes that are responsible not for colour, but for immune resistance. Conclusions The obtained GWAS data can be used to explore the genetics of immunity and carry out selection for increasing YEF for SPF eggs production. Electronic supplementary material The online version of this article (10.1186/s12864-019-5605-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrei A Kudinov
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia.,University of Helsinki, FI-00014, Helsinki, Finland
| | - Natalia V Dementieva
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Olga V Mitrofanova
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Olga I Stanishevskaya
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Elena S Fedorova
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Tatiana A Larkina
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Arina I Mishina
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Kirill V Plemyashov
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Darren K Griffin
- School of Biosciences, University of Kent, Canterbury, Kent, CT2 7NJ, UK.
| | - Michael N Romanov
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia.,School of Biosciences, University of Kent, Canterbury, Kent, CT2 7NJ, UK
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