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Zhang Y, Liu P, Wang C, Zhang N, Zhu Y, Zou C, Yuan G, Yang C, Gao S, Pan G, Ma L, Shen Y. Genome-wide association study uncovers new genetic loci and candidate genes underlying seed chilling-germination in maize. PeerJ 2021; 9:e11707. [PMID: 34249517 PMCID: PMC8247712 DOI: 10.7717/peerj.11707] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/08/2021] [Indexed: 12/13/2022] Open
Abstract
As one of the major crops, maize (Zea mays L.) is mainly distributed in tropical and temperate regions. However, with the changes of the environments, chilling stress has become a significantly abiotic stress affecting seed germination and thus the reproductive and biomass accumulation of maize. Herein, we investigated five seed germination-related phenotypes among 300 inbred lines under low-temperature condition (10 °C). By combining 43,943 single nucleotide polymorphisms (SNPs), a total of 15 significant (P < 2.03 × 10-6) SNPs were identified to correlate with seed germination under cold stress based on the FarmCPU model in GWAS, among which three loci were repeatedly associated with multiple traits. Ten gene models were closely linked to these three variations, among which Zm00001d010454, Zm00001d010458, Zm00001d010459, and Zm00001d050021 were further verified by candidate gene association study and expression pattern analysis. Importantly, these candidate genes were previously reported to involve plant tolerance to chilling stress and other abiotic stress. Our findings contribute to the understanding of the genetic and molecular mechanisms underlying chilling germination in maize.
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Affiliation(s)
- Yinchao Zhang
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Peng Liu
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Chen Wang
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Na Zhang
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Yuxiao Zhu
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Chaoying Zou
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Guangsheng Yuan
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Cong Yang
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Shibin Gao
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Guangtang Pan
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Langlang Ma
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Yaou Shen
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
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Nie C, Qu L, Li X, Jiang Z, Wang K, Li H, Wang H, Qu C, Qu L, Ning Z. Genomic Regions Related to White/Black Tail Feather Color in Dwarf Chickens Identified Using a Genome-Wide Association Study. Front Genet 2021; 12:566047. [PMID: 33995468 PMCID: PMC8120320 DOI: 10.3389/fgene.2021.566047] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 01/21/2021] [Indexed: 11/13/2022] Open
Abstract
Although the genetic foundation of chicken body feather color has been extensively explored, that of tail feather color remains poorly understood. In the present study, we used a synthetic chicken dwarf line (DW), derived from hybrids bred between a black tail chicken breed, Rhode Island Red (RIR), and a white tail breed, dwarf layer (DL), to investigate the genetic rules associated white/black tail color. Even though the body feathers are predominantly red, the DW line still comprises individuals with black or white tails after more than 10 generations of self-crossing and selection for the body feather color. We first performed four crosses using the DW chickens, including black-tailed males to females, reciprocal crosses between the black and white, and white males to females to elucidate the inheritance pattern of the white/black tail. We also performed a genome-wide association (GWA) analysis to determine the candidate genomic regions underlying the tail feather color using black tail chickens from the RIR and DW lines and white individuals from the DW line. In the crossing experiment, we found that (i) the white/black tail feather color is independent of body feather color; (ii) the phenotype is a simple autosomal trait; and (iii) the white is dominant to the black in the DW line. The GWA results showed that seven single-nucleotide polymorphisms (SNPs) on chromosome 24 were significantly correlated with tail feather color. The significant region (3.97-4.26 Mb) comprises nine known genes (NECTIN1, THY1, gga-mir-1466, USP2, C1QTNF5, RNF26, MCAM, CBL, and CCDC153) and five anonymous genes. This study revealed that the white/black tail feather trait is autosome-linked in DW chickens. Fourteen genes were found in the significant ~0.29 Mb genomic region, and some, especially MCAM, are suggested to play critical roles in the determination of white/black tail feather color. Our research is the first study on the genetics underlying tail feather color and could help further the understanding of feather pigmentation in chickens.
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Affiliation(s)
- Changsheng Nie
- State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Liang Qu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, China
| | - Xinghua Li
- State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhihua Jiang
- Department of Animal Sciences, Washington State University, Pullman, WA, United States
| | - Kehua Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, China
| | - Haiying Li
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Huie Wang
- College of Animal Science, Tarim University, Xinjiang, China
- Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production and Construction Corps, Xinjiang, China
| | - Changqing Qu
- Engineering Technology Research Center of Anti-aging Chinese Herbal Medicine of Anhui Province, Fuyang Normal University, Fuyang, China
| | - Lujiang Qu
- State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhonghua Ning
- State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Li J, Antonecchia E, Camerlenghi M, Chiaravalloti A, Chu Q, Costanzo AD, Li Z, Wan L, Zhang X, D'Ascenzo N, Schillaci O, Xie Q. Correlation of [ 18F]florbetaben textural features and age of onset of Alzheimer's disease: a principal components analysis approach. EJNMMI Res 2021; 11:40. [PMID: 33881633 PMCID: PMC8060386 DOI: 10.1186/s13550-021-00774-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 03/15/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND When Alzheimer's disease (AD) is occurring at an early onset before 65 years old, its clinical course is generally more aggressive than in the case of a late onset. We aim at identifying [[Formula: see text]F]florbetaben PET biomarkers sensitive to differences between early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). We conducted [[Formula: see text]F]florbetaben PET/CT scans of 43 newly diagnosed AD subjects. We calculated 93 textural parameters for each of the 83 Hammers areas. We identified 41 independent principal components for each brain region, and we studied their Spearman correlation with the age of AD onset, by taking into account multiple comparison corrections. Finally, we calculated the probability that EOAD and LOAD patients have different amyloid-[Formula: see text] ([Formula: see text]) deposition by comparing the mean and the variance of the significant principal components obtained in the two groups with a 2-tailed Student's t-test. RESULTS We found that four principal components exhibit a significant correlation at a 95% confidence level with the age of onset in the left lateral part of the anterior temporal lobe, the right anterior orbital gyrus of the frontal lobe, the right lateral orbital gyrus of the frontal lobe and the left anterior part of the superior temporal gyrus. The data are consistent with the hypothesis that EOAD patients have a significantly different [[Formula: see text]F]florbetaben uptake than LOAD patients in those four brain regions. CONCLUSIONS Early-onset AD implies a very irregular pattern of [Formula: see text] deposition. The authors suggest that the identified textural features can be used as quantitative biomarkers for the diagnosis and characterization of EOAD patients.
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Affiliation(s)
- Jing Li
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China
| | - Emanuele Antonecchia
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China.,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy
| | - Marco Camerlenghi
- NIM Competence Center for Digital Healthcare GmbH, Potsdamerplatz, 10, 10785, Berlin, Germany
| | - Agostino Chiaravalloti
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy. .,Department of Biomedicine and Prevention, University of Tor Vergata, 86100, Rome, Italy.
| | - Qian Chu
- Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road, Wuhan, 430030, China.,Department of Oncology, Tongji Hospital, Jiefang Avenue, Wuhan, 430030, China
| | - Alfonso Di Costanzo
- Universita degli Studi del Molise, Via Francesco de Sanctis, 1, 10115, Campobasso, Italy
| | - Zhen Li
- Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road, Wuhan, 430030, China.,Department of Radiology, Tongji Hospital, Jiefang Avenue, Wuhan, 430030, China
| | - Lin Wan
- Department of Software Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China
| | - Xiangsong Zhang
- The First Affiliated Hospital, Sun Yat-sen University, Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Nicola D'Ascenzo
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China. .,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy.
| | - Orazio Schillaci
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy.,Department of Biomedicine and Prevention, University of Tor Vergata, 86100, Rome, Italy
| | - Qingguo Xie
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China. .,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy.
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Pinsach-Abuin M, del Olmo B, Pérez-Agustin A, Mates J, Allegue C, Iglesias A, Ma Q, Merkurjev D, Konovalov S, Zhang J, Sheikh F, Telenti A, Brugada J, Brugada R, Gymrek M, di Iulio J, Garcia-Bassets I, Pagans S. Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants. Cell Rep Med 2021; 2:100250. [PMID: 33948580 PMCID: PMC8080235 DOI: 10.1016/j.xcrm.2021.100250] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 01/07/2021] [Accepted: 03/23/2021] [Indexed: 11/30/2022]
Abstract
Genome-wide association studies (GWASs) are instrumental in identifying loci harboring common single-nucleotide variants (SNVs) that affect human traits and diseases. GWAS hits emerge in clusters, but the focus is often on the most significant hit in each trait- or disease-associated locus. The remaining hits represent SNVs in linkage disequilibrium (LD) and are considered redundant and thus frequently marginally reported or exploited. Here, we interrogate the value of integrating the full set of GWAS hits in a locus repeatedly associated with cardiac conduction traits and arrhythmia, SCN5A-SCN10A. Our analysis reveals 5 common 7-SNV haplotypes (Hap1-5) with 2 combinations associated with life-threatening arrhythmia-Brugada syndrome (the risk Hap1/1 and protective Hap2/3 genotypes). Hap1 and Hap2 share 3 SNVs; thus, this analysis suggests that assuming redundancy among clustered GWAS hits can lead to confounding disease-risk associations and supports the need to deconstruct GWAS data in the context of haplotype composition.
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Affiliation(s)
- Mel·lina Pinsach-Abuin
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Visiting Scholar Program, Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Bernat del Olmo
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Visiting Scholar Program, Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Adrian Pérez-Agustin
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Jesus Mates
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Catarina Allegue
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Visiting Scholar Program, Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Anna Iglesias
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Qi Ma
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Daria Merkurjev
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sergiy Konovalov
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jing Zhang
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Farah Sheikh
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Amalio Telenti
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
| | - Josep Brugada
- Arrhythmia Unit, Hospital Clinic de Barcelona, Universitat de Barcelona, Barcelona, Spain
| | - Ramon Brugada
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
- Cardiology Service, Hospital Universitari Dr. Josep Trueta, Girona, Spain
| | - Melissa Gymrek
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Julia di Iulio
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ivan Garcia-Bassets
- Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Sara Pagans
- Department of Medical Sciences, School of Medicine, Universitat de Girona, Girona, Spain
- Institut d’Investigació Biomèdica de Girona, Salt, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
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Tibbs Cortes L, Zhang Z, Yu J. Status and prospects of genome-wide association studies in plants. THE PLANT GENOME 2021; 14:e20077. [PMID: 33442955 DOI: 10.1002/tpg2.20077] [Citation(s) in RCA: 127] [Impact Index Per Article: 42.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 11/18/2020] [Indexed: 05/22/2023]
Abstract
Genome-wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome-wide genetic variants across diverse genetic materials. The development of the mixed model framework for GWAS dramatically reduced the number of false positives compared with naïve methods. Building on this foundation, many methods have since been developed to increase computational speed or improve statistical power in GWAS. These methods have allowed the detection of genomic variants associated with either traditional agronomic phenotypes or biochemical and molecular phenotypes. In turn, these associations enable applications in gene cloning and in accelerated crop breeding through marker assisted selection or genetic engineering. Current topics of investigation include rare-variant analysis, synthetic associations, optimizing the choice of GWAS model, and utilizing GWAS results to advance knowledge of biological processes. Ongoing research in these areas will facilitate further advances in GWAS methods and their applications.
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Affiliation(s)
| | - Zhiwu Zhang
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99164, USA
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA, 50010, USA
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56
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Wang M, Li R, Xu S. Deshrinking ridge regression for genome-wide association studies. Bioinformatics 2021; 36:4154-4162. [PMID: 32379866 DOI: 10.1093/bioinformatics/btaa345] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 04/21/2020] [Accepted: 04/29/2020] [Indexed: 11/15/2022] Open
Abstract
MOTIVATION Genome-wide association studies (GWAS) are still the primary steps toward gene discovery. The urgency is more obvious in the big data era when GWAS are conducted simultaneously for thousand traits, e.g. transcriptomic and metabolomic traits. Efficient mixed model association (EMMA) and genome-wide efficient mixed model association (GEMMA) are the widely used methods for GWAS. An algorithm with high computational efficiency is badly needed. It is interesting to note that the test statistics of the ordinary ridge regression (ORR) have the same patterns across the genome as those obtained from the EMMA method. However, ORR has never been used for GWAS due to its severe shrinkage on the estimated effects and the test statistics. RESULTS We introduce a degree of freedom for each marker effect obtained from ORR and use it to deshrink both the estimated effect and the standard error so that the Wald test of ORR is brought back to the same level as that of EMMA. The new method is called deshrinking ridge regression (DRR). By evaluating the methods under three different model sizes (small, medium and large), we demonstrate that DRR is more generalized for all model sizes than EMMA, which only works for medium and large models. Furthermore, DRR detect all markers in a simultaneous manner instead of scanning one marker at a time. As a result, the computational time complexity of DRR is much simpler than EMMA and about m (number of genetic variants) times simpler than that of GEMMA when the sample size is way smaller than the number of markers. CONTACT shizhong.xu@ucr.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Meiyue Wang
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Ruidong Li
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Shizhong Xu
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
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57
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Nordestgaard NV, Thach T, Sarup P, Rodriguez-Algaba J, Andersen JR, Hovmøller MS, Jahoor A, Jørgensen LN, Orabi J. Multi-Parental Populations Suitable for Identifying Sources of Resistance to Powdery Mildew in Winter Wheat. FRONTIERS IN PLANT SCIENCE 2021; 11:570863. [PMID: 33552092 PMCID: PMC7859110 DOI: 10.3389/fpls.2020.570863] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 12/02/2020] [Indexed: 06/12/2023]
Abstract
Wheat (Triticum aestivum L.) is one of the world's staple food crops and one of the most devastating foliar diseases attacking wheat is powdery mildew (PM). In Denmark only a few specific fungicides are available for controlling PM and the use of resistant cultivars is often recommended. In this study, two Chinese wheat landraces and two synthetic hexaploid wheat lines were used as donors for creating four multi-parental populations with a total of 717 individual lines to identify new PM resistance genetic variants. These lines and the nine parental lines (including the elite cultivars used to create the populations) were genotyped using a 20 K Illumina SNP chip, which resulted in 8,902 segregating single nucleotide polymorphisms for assessment of the population structure and whole genome association study. The largest genetic difference among the lines was between the donors and the elite cultivars, the second largest genetic difference was between the different donors; a difference that was also reflected in differences between the four multi-parental populations. The 726 lines were phenotyped for PM resistance in 2017 and 2018. A high PM disease pressure was observed in both seasons, with severities ranging from 0 to >50%. Whole genome association studies for genetic variation in PM resistance in the populations revealed significant markers mapped to either chromosome 2A, B, or D in each of the four populations. However, linkage disequilibrium between these putative quantitative trait loci (QTL) were all above 0.80, probably representing a single QTL. A combined analysis of all the populations confirmed this result and the most associated marker explained 42% of the variation in PM resistance. This study gives both knowledge about the resistance as well as molecular tools and plant material that can be utilised in marker-assisted selection. Additionally, the four populations produced in this study are highly suitable for association studies of other traits than PM resistance.
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Affiliation(s)
| | - Tine Thach
- Department of Agroecology, Aarhus University, Slagelse, Denmark
| | | | | | | | | | - Ahmed Jahoor
- Nordic Seed A/S, Odder, Denmark
- Department of Plant Breeding, The Swedish University of Agricultural Sciences, Alnarp, Sweden
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58
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Qu L, Shen MM, Dou TC, Ma M, Lu J, Wang XG, Guo J, Hu YP, Li YF, Wang KH. Genome-wide association studies for mottled eggs in chickens using a high-density single-nucleotide polymorphism array. Animal 2020; 15:100051. [PMID: 33516007 DOI: 10.1016/j.animal.2020.100051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 10/22/2022] Open
Abstract
Mottled eggs in layer chickens are gaining increasing attention because of the economic impact on the egg industry caused by the reduced sale value of commodity eggs. However, the genetic architecture underlying mottled eggs is not well understood. The genetic architecture underlying the mottled egg trait was investigated using genome-wide association studies (GWAS) by high-density arrays, using a total of 407 pink eggs and 799 blue eggs from an F2 resource population generated by crossing Dongxiang Blue-shelled and White Leghorn chickens. The mottled egg score in blue eggs was found to be higher than that in pink eggs. The single-nucleotide polymorphism heritability of mottled egg at laying day and storage for 7 days was 0.18 and 0.20, respectively. Bivariate GWAS provided 29 significant loci, mainly located on GGA2, GGA3, GGA8, GGA10, GGA15, GGA17, and GGA23, affecting mottled egg on laying day. Candidate genes RIMS2, SLC25A32, RIMBP2, VPS13B, and RGS3 were obtained for mottled eggshell by bivariate GWAS and gene annotation. Our findings provide new insights into the genetic architecture of mottled egg in hens, and demonstrate that a genomic selection method would be profitable for breeding out the mottled egg trait.
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Affiliation(s)
- L Qu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - M M Shen
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China; College of Biotechnology, Jiangsu University of Science and Technology, 212003 Zhenjiang, Jiangsu, China
| | - T C Dou
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - M Ma
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - J Lu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - X G Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - J Guo
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - Y P Hu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - Y F Li
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - K H Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China.
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59
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Sapkota S, Boatwright JL, Jordan K, Boyles R, Kresovich S. Identification of Novel Genomic Associations and Gene Candidates for Grain Starch Content in Sorghum. Genes (Basel) 2020; 11:E1448. [PMID: 33276449 PMCID: PMC7760202 DOI: 10.3390/genes11121448] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 11/10/2020] [Accepted: 11/27/2020] [Indexed: 01/15/2023] Open
Abstract
Starch accumulated in the endosperm of cereal grains as reserve energy for germination serves as a staple in human and animal nutrition. Unraveling genetic control for starch metabolism is important for breeding grains with high starch content. In this study, we used a sorghum association panel with 389 individuals and 141,557 single nucleotide polymorphisms (SNPs) to fit linear mixed models (LMM) for identifying genomic regions and potential candidate genes associated with starch content. Three associated genomic regions, one in chromosome (chr) 1 and two novel associations in chr-8, were identified using combination of LMM and Bayesian sparse LMM. All significant SNPs were located within protein coding genes, with SNPs ∼ 52 Mb of chr-8 encoding a Casperian strip membrane protein (CASP)-like protein (Sobic.008G111500) and a heat shock protein (HSP) 90 (Sobic.008G111600) that were highly expressed in reproductive tissues including within the embryo and endosperm. The HSP90 is a potential hub gene with gene network of 75 high-confidence first interactors that is enriched for five biochemical pathways including protein processing. The first interactors of HSP90 also showed high transcript abundance in reproductive tissues. The candidates of this study are likely involved in intricate metabolic pathways and represent candidate gene targets for source-sink activities and drought and heat stress tolerance during grain filling.
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Affiliation(s)
- Sirjan Sapkota
- Advanced Plant Technology Program, Clemson University, Clemson, SC 29634, USA; (J.L.B.); (K.J.); (S.K.)
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA;
| | - J. Lucas Boatwright
- Advanced Plant Technology Program, Clemson University, Clemson, SC 29634, USA; (J.L.B.); (K.J.); (S.K.)
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA;
| | - Kathleen Jordan
- Advanced Plant Technology Program, Clemson University, Clemson, SC 29634, USA; (J.L.B.); (K.J.); (S.K.)
| | - Richard Boyles
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA;
- Pee Dee Research and Education Center, Clemson University, Florence, SC 29506, USA
| | - Stephen Kresovich
- Advanced Plant Technology Program, Clemson University, Clemson, SC 29634, USA; (J.L.B.); (K.J.); (S.K.)
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA;
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Zhang Y, Hu Y, Guan Z, Liu P, He Y, Zou C, Li P, Gao S, Peng H, Yang C, Pan G, Shen Y, Ma L. Combined linkage mapping and association analysis reveals genetic control of maize kernel moisture content. PHYSIOLOGIA PLANTARUM 2020; 170:508-518. [PMID: 32754968 DOI: 10.1111/ppl.13180] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 07/27/2020] [Accepted: 07/30/2020] [Indexed: 06/11/2023]
Abstract
The free moisture in crop kernels after being naturally dried is referred to as kernel moisture content (KMC). Maize KMC reflects grain quality and influences transportation and storage of seeds. We used an IBM Syn10 DH maize population consisting of 249 lines and an association panel comprising 310 maize inbred lines to identify the genetic loci affecting maize KMC in three environments. Using the IBM population detected 13 QTL on seven chromosomes, which were clustered into nine common QTL. Genome-wide association analysis (GWAS) identified 16 significant SNPs across the 3 environments, which were linked to 158 genes across the three environments. Combined QTL mapping and GWAS found two SNPs that were located in two of the mapped QTL, respectively. Twenty-three genes were linked with the loci co-localized in both populations. Of these 181 genes, five have previously been reported to be associated with KMC or to regulate seed development. These associations were verified by candidate gene association analysis. Two superior alleles and one favorable haplotype for Zm00001d007774 and Zm00001d047868 were found to influence KMC. These findings provide insights into molecular mechanisms underlying maize KMC and contribute to the use of marker-assisted selection for breeding low-KMC maize.
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Affiliation(s)
- Yinchao Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yu Hu
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhongrong Guan
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Peng Liu
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yongcong He
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Chaoying Zou
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Peng Li
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Shibin Gao
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Hua Peng
- Sichuan Tourism College, Chengdu, 610100, China
| | - Cong Yang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Guangtang Pan
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yaou Shen
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Langlang Ma
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
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61
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Lin S, Wan Z, Zhang J, Xu L, Han B, Sun D. Genome-Wide Association Studies for the Concentration of Albumin in Colostrum and Serum in Chinese Holstein. Animals (Basel) 2020; 10:ani10122211. [PMID: 33255903 PMCID: PMC7759787 DOI: 10.3390/ani10122211] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 11/19/2020] [Accepted: 11/19/2020] [Indexed: 01/24/2023] Open
Abstract
Albumin can be of particular benefit in fighting infections for newborn calves due to its anti-inflammatory and anti-oxidative stress properties. To identify the candidate genes related to the concentration of albumin in colostrum and serum, we collected the colostrum and blood samples from 572 Chinese Holstein cows within 24 h after calving and measured the concentration of albumin in the colostrum and serum using the ELISA methods. The cows were genotyped with GeneSeek 150 K chips (containing 140,668 single nucleotide polymorphisms; SNPs). After quality control, we performed GWASs via GCTA software with 91,620 SNPs and 563 cows. Consequently, 9 and 7 genome-wide significant SNPs (false discovery rate (FDR) at 1%) were identified. Correspondingly, 42 and 206 functional genes that contained or were approximate to (±1 Mbp) the significant SNPs were acquired. Integrating the biological process of these genes and the reported QTLs for immune and inflammation traits in cattle, 3 and 12 genes were identified as candidates for the concentration of colostrum and serum albumin, respectively; these are RUNX1, CBR1, OTULIN,CDK6, SHARPIN, CYC1, EXOSC4, PARP10, NRBP2, GFUS, PYCR3, EEF1D, GSDMD, PYCR2 and CXCL12. Our findings provide important information for revealing the genetic mechanism behind albumin concentration and for molecular breeding of disease-resistance traits in dairy cattle.
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Affiliation(s)
- Shan Lin
- Key Laboratory of Animal Genetics and Breeding of the Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (S.L.); (J.Z.); (L.X.); (B.H.)
| | - Zihui Wan
- Stae Key Laboratory of Agriobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China;
| | - Junnan Zhang
- Key Laboratory of Animal Genetics and Breeding of the Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (S.L.); (J.Z.); (L.X.); (B.H.)
| | - Lingna Xu
- Key Laboratory of Animal Genetics and Breeding of the Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (S.L.); (J.Z.); (L.X.); (B.H.)
| | - Bo Han
- Key Laboratory of Animal Genetics and Breeding of the Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (S.L.); (J.Z.); (L.X.); (B.H.)
| | - Dongxiao Sun
- Key Laboratory of Animal Genetics and Breeding of the Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (S.L.); (J.Z.); (L.X.); (B.H.)
- Correspondence:
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Zamanpoor M, Ghaedi H, Omrani MD. The genetic basis for the inverse relationship between rheumatoid arthritis and schizophrenia. Mol Genet Genomic Med 2020; 8:e1483. [PMID: 32965087 PMCID: PMC7667353 DOI: 10.1002/mgg3.1483] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 06/30/2020] [Accepted: 07/10/2020] [Indexed: 12/13/2022] Open
Abstract
Introduction Rheumatoid arthritis is a common autoimmune disease and schizophrenia is a relatively common and debilitating neurological disorder. There are several common features between rheumatoid arthritis and schizophrenia. The inverse relationship between rheumatoid arthritis and schizophrenia has been replicated in several studies. Despite evidence for an inverse epidemiological relationship and negative correlations for risk between rheumatoid arthritis and schizophrenia, there are no biological data that directly support this inverse relationship. Materials and Methods’ We meta‐analyzed the genome‐wide association studies to investigate the shared association loci between rheumatoid arthritis and schizophrenia at the genome‐wide scale. Rheumatoid arthritis‐ and schizophrenia‐associated loci in most recent genome‐wide association studies of rheumatoid arthritis and schizophrenia were tested. Genetic risk score analysis was also conducted to investigate the collective contribution of schizophrenia risk loci to rheumatoid arthritis risk. Results Rheumatoid arthritis and schizophrenia meta‐genome‐wide association study showed a significant peak at the major histocompatibility complex locus on chromosome 6 in both rheumatoid arthritis‐schizophrenia meta‐genome‐wide association study and inverted meta‐genome‐wide association study datasets. Testing rheumatoid arthritis‐ and schizophrenia‐associated loci outside the human leukocyte antigen region showed no association with both rheumatoid arthritis and schizophrenia at a genome‐wide level of significance. Weighted genetic risk scores showed no evidence for a statistically significant association between rheumatoid arthritis and schizophrenia. Conclusion The finding of our study is consistent with the role of the major histocompatibility complex locus in the genetic correlation between rheumatoid arthritis and schizophrenia, and suggests that either schizophrenia has an autoimmune basis and/or rheumatoid arthritis has an active neurological component.
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Affiliation(s)
- Mansour Zamanpoor
- Medical Genetics Department, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Hamid Ghaedi
- Medical Genetics Department, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mir Davood Omrani
- Medical Genetics Department, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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63
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Chen SY, Oliveira HR, Schenkel FS, Pedrosa VB, Melka MG, Brito LF. Using imputed whole-genome sequence variants to uncover candidate mutations and genes affecting milking speed and temperament in Holstein cattle. J Dairy Sci 2020; 103:10383-10398. [PMID: 32952011 DOI: 10.3168/jds.2020-18897] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 07/10/2020] [Indexed: 12/12/2022]
Abstract
Milking speed (MS) and temperament (MT) are 2 workability traits of great importance in dairy cattle production and breeding. This is mainly due to an increased intensification of the worldwide production systems and greater adoption of precision technologies with less human-cattle interaction. Both MS and MT are heritable traits and thus, genomic selection is a promising tool to expedite their genetic progress. However, the genetic architecture and biological mechanisms underlying the phenotypic expression of these traits remain underexplored. In this study, we investigated the association of >5.7 million imputed whole-genome sequence variants with MT and MS in 4,381 and 4,219 North American Holstein cattle, respectively. The statistical analyses were performed using a mixed linear model fitting a polygenic effect. We detected 40 and 35 significant SNPs independently associated with MT and MS, respectively, which were distributed across 26 chromosomes. Eight candidate genes (GRIN3A, KCNJ3, BOSTAUV1R417, BOSTAUV1R419, MAP2K5, KCTD3, GAP43, and LSAMP) were suggested to play an important role in MT as they are involved in biologically relevant pathways, such as glutamatergic synapse, vomeronasal receptor and oxytocin signaling. Within their coding and upstream sequences, we used an independent data set to further detect or validate significantly differentiated SNP between cattle breeds with known differences in MT. There were fewer candidate genes potentially implicated in MS, but immunity-related genes (e.g., BOLA-NC1 and LOC512672), also identified in other populations, were validated in this study. The significant SNP and novel candidate genes identified contribute to a better understanding of the biological mechanisms underlying both traits in dairy cattle. This information will also be useful for the optimization of prediction of genomic breeding values by giving greater weights to SNP located in the genomic regions identified.
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Affiliation(s)
- Shi-Yi Chen
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907; Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Victor B Pedrosa
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa, PR, 84030-900, Brazil
| | - Melkaye G Melka
- Department of Animal and Food Science, University of Wisconsin River Falls, 54022
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907.
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64
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Genome-Wide Association Study and Pathway Analysis for Heterophil/Lymphocyte (H/L) Ratio in Chicken. Genes (Basel) 2020; 11:genes11091005. [PMID: 32867375 PMCID: PMC7563235 DOI: 10.3390/genes11091005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 08/19/2020] [Accepted: 08/19/2020] [Indexed: 12/27/2022] Open
Abstract
Disease control and prevention have been critical factors in the dramatic growth of the poultry industry. Disease resistance in chickens can be improved through genetic selection for immunocompetence. The heterophil/lymphocyte ratio (H/L) in the blood reflects the immune system status of chickens. Our objective was to conduct a genome-wide association study (GWAS) and pathway analysis to identify possible biological mechanisms involved in H/L traits. In this study, GWAS for H/L was performed in 1317 Cobb broilers to identify significant single-nucleotide polymorphisms (SNPs) associated with H/L. Eight SNPs (p < 1/8068) reached a significant level of association. The significant SNP on GGA 19 (chicken chromosome 19) was in the gene for complement C1q binding protein (C1QBP). The wild-type and mutant individuals showed significant differences in H/L at five identified SNPs (p < 0.05). According to the results of pathway analysis, nine associated pathways (p < 0.05) were identified. By combining GWAS with pathway analysis, we found that all SNPs after QC explained 12.4% of the phenotypic variation in H/L, and 52 SNPs associated with H/L explained as much as 9.7% of the phenotypic variation in H/L. Our findings contribute to understanding of the genetic regulation of H/L and provide theoretical support.
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65
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Lin A, Kolossváry M, Yuvaraj J, Cadet S, McElhinney PA, Jiang C, Nerlekar N, Nicholls SJ, Slomka PJ, Maurovich-Horvat P, Wong DTL, Dey D. Myocardial Infarction Associates With a Distinct Pericoronary Adipose Tissue Radiomic Phenotype: A Prospective Case-Control Study. JACC Cardiovasc Imaging 2020; 13:2371-2383. [PMID: 32861654 DOI: 10.1016/j.jcmg.2020.06.033] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 05/04/2020] [Accepted: 06/03/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVES This study sought to determine whether coronary computed tomography angiography (CCTA)-based radiomic analysis of pericoronary adipose tissue (PCAT) could distinguish patients with acute myocardial infarction (MI) from patients with stable or no coronary artery disease (CAD). BACKGROUND Imaging of PCAT with CCTA enables detection of coronary inflammation. Radiomics involves extracting quantitative features from medical images to create big data and identify novel imaging biomarkers. METHODS In a prospective case-control study, 60 patients with acute MI underwent CCTA within 48 h of admission, before invasive angiography. These subjects were matched to patients with stable CAD (n = 60) and controls with no CAD (n = 60) by age, sex, risk factors, medications, and CT tube voltage. PCAT was segmented around the proximal right coronary artery (RCA) in all patients and around culprit and nonculprit lesions in patients with MI. PCAT segmentations were analyzed using Radiomics Image Analysis software. RESULTS Of 1,103 calculated radiomic parameters, 20.3% differed significantly between MI patients and controls, and 16.5% differed between patients with MI and stable CAD (critical p < 0.0006); whereas none differed between patients with stable CAD and controls. On cluster analysis, the most significant radiomic parameters were texture or geometry based. At 6 months post-MI, there was no significant change in the PCAT radiomic profile around the proximal RCA or nonculprit lesions. Using machine learning (XGBoost), a model integrating clinical features (risk factors, serum lipids, high-sensitivity C-reactive protein), PCAT attenuation, and radiomic parameters provided superior discrimination of acute MI (area under the receiver operator characteristic curve [AUC]: 0.87) compared with a model with clinical features and PCAT attenuation (AUC: 0.77; p = 0.001) or clinical features alone (AUC: 0.76; p < 0.001). CONCLUSIONS Patients with acute MI have a distinct PCAT radiomic phenotype compared with patients with stable or no CAD. Using machine learning, a radiomics-based model outperforms a PCAT attenuation-based model in accurately identifying patients with MI.
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Affiliation(s)
- Andrew Lin
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California; Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Clayton, Victoria, Australia
| | - Márton Kolossváry
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Jeremy Yuvaraj
- Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Clayton, Victoria, Australia
| | - Sebastien Cadet
- Artificial Intelligence in Medicine Program, Cedars-Sinai Medical Center, Los Angeles, California
| | - Priscilla A McElhinney
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Cathy Jiang
- Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Clayton, Victoria, Australia
| | - Nitesh Nerlekar
- Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Clayton, Victoria, Australia
| | - Stephen J Nicholls
- Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Clayton, Victoria, Australia
| | - Piotr J Slomka
- Artificial Intelligence in Medicine Program, Cedars-Sinai Medical Center, Los Angeles, California
| | | | - Dennis T L Wong
- Monash Cardiovascular Research Centre, Monash University and MonashHeart, Monash Health, Clayton, Victoria, Australia
| | - Damini Dey
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.
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Sliz E, Shin J, Syme C, Black S, Seshadri S, Paus T, Pausova Z. Thickness of the cerebral cortex shows positive association with blood levels of triacylglycerols carrying 18-carbon fatty acids. Commun Biol 2020; 3:456. [PMID: 32820227 PMCID: PMC7441395 DOI: 10.1038/s42003-020-01189-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 07/30/2020] [Indexed: 12/12/2022] Open
Abstract
Perturbations in fatty acid (FA) metabolism as well as thinning of the cerebral cortex have been associated with cognitive decline in the elderly. Predominant FAs in the brain are docosahexaenoic acid (DHA) and arachidonic acid (ARA). Approximately 2-8% of esterified DHA and 3-5% of esterified ARA in the brain are replaced daily. DHA and ARA are derivatives of 18-carbon essential FAs, α-linolenic acid and linoleic acid, that must be imported into the brain from the circulation. In blood, FAs are primarily transported in triacylglycerols (TAGs) from which they can be released at the blood-brain-barrier and transported inside the brain. We show that circulating levels of TAGs carrying 18-carbon FAs are positively associated with cortical thickness in middle-aged adults. These associations are stronger in cortical regions with higher expression of genes regulating long-chain FA metabolism and cellular membranes, and cortical thickness in the same regions may be related to cognitive performance.
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Affiliation(s)
- Eeva Sliz
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.,Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Jean Shin
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.,Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Catriona Syme
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.,Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Sandra Black
- Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada.,Toronto Dementia Research Alliance, Toronto, ON, Canada.,Sunnybrook Research Institute, Toronto, ON, Canada.,Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,LC Campbell Cognitive Neurology Research Unit, Toronto, ON, Canada
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Tomas Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada.,Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada. .,Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada.
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Ramzan F, Gültas M, Bertram H, Cavero D, Schmitt AO. Combining Random Forests and a Signal Detection Method Leads to the Robust Detection of Genotype-Phenotype Associations. Genes (Basel) 2020; 11:E892. [PMID: 32764260 PMCID: PMC7465705 DOI: 10.3390/genes11080892] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 07/28/2020] [Accepted: 08/03/2020] [Indexed: 12/21/2022] Open
Abstract
Genome wide association studies (GWAS) are a well established methodology to identify genomic variants and genes that are responsible for traits of interest in all branches of the life sciences. Despite the long time this methodology has had to mature the reliable detection of genotype-phenotype associations is still a challenge for many quantitative traits mainly because of the large number of genomic loci with weak individual effects on the trait under investigation. Thus, it can be hypothesized that many genomic variants that have a small, however real, effect remain unnoticed in many GWAS approaches. Here, we propose a two-step procedure to address this problem. In a first step, cubic splines are fitted to the test statistic values and genomic regions with spline-peaks that are higher than expected by chance are considered as quantitative trait loci (QTL). Then the SNPs in these QTLs are prioritized with respect to the strength of their association with the phenotype using a Random Forests approach. As a case study, we apply our procedure to real data sets and find trustworthy numbers of, partially novel, genomic variants and genes involved in various egg quality traits.
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Affiliation(s)
- Faisal Ramzan
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (M.G.); (H.B.)
- Department of Animal Breeding and Genetics, University of Agriculture Faisalabad, 38000 Faisalabad, Pakistan
| | - Mehmet Gültas
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (M.G.); (H.B.)
- Center for Integrated Breeding Research (CiBreed), Albrecht-Thaer-Weg 3, Georg-August University, 37075 Göttingen, Germany
| | - Hendrik Bertram
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (M.G.); (H.B.)
| | | | - Armin Otto Schmitt
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (M.G.); (H.B.)
- Center for Integrated Breeding Research (CiBreed), Albrecht-Thaer-Weg 3, Georg-August University, 37075 Göttingen, Germany
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Perng W, Aslibekyan S. Find the Needle in the Haystack, Then Find It Again: Replication and Validation in the 'Omics Era. Metabolites 2020; 10:metabo10070286. [PMID: 32664690 PMCID: PMC7408356 DOI: 10.3390/metabo10070286] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 07/01/2020] [Accepted: 07/10/2020] [Indexed: 01/25/2023] Open
Abstract
Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon balancing false-positive associations with generalizability. Given the foundational role of reproducibility in scientific inference, replication and validation of ‘omics findings are cornerstones of this effort. In this narrative review, we define key terms relevant to replication and validation, present issues surrounding each concept with historical and contemporary examples from genomics (the most well-established and upstream ‘omics), discuss special issues and unique considerations for replication and validation in metabolomics (an emerging field and most downstream ‘omics for which best practices remain yet to be established), and make suggestions for future research leveraging multiple ‘omics datasets.
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Affiliation(s)
- Wei Perng
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver Anschutz Medical Campus, Aurora, CO 80045, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Denver Anschutz Medical Campus, Aurora, CO 80045, USA
- Correspondence:
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA;
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Kang J, Coates JT, Strawderman RL, Rosenstein BS, Kerns SL. Genomics models in radiotherapy: From mechanistic to machine learning. Med Phys 2020; 47:e203-e217. [PMID: 32418335 PMCID: PMC8725063 DOI: 10.1002/mp.13751] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 06/28/2019] [Accepted: 07/17/2019] [Indexed: 12/28/2022] Open
Abstract
Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles to biological data toward questions of radiation biology. Here, we provide a review of radiogenomics modeling frameworks and efforts toward genomically guided radiotherapy. We first discuss medical oncology efforts to develop precision biomarkers. We next discuss similar efforts to create clinical assays for normal tissue or tumor radiosensitivity. We then discuss modeling frameworks for radiosensitivity and the evolution of ML to create predictive models for radiogenomics.
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Affiliation(s)
- John Kang
- Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - James T. Coates
- CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford OX3 7DQ, UK
| | - Robert L. Strawderman
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA
| | - Barry S. Rosenstein
- Department of Radiation Oncology and the Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sarah L. Kerns
- Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY 14642, USA
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Michno J, Liu J, Jeffers JR, Stupar RM, Myers CL. Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks. PLANT DIRECT 2020; 4:e00220. [PMID: 32426691 PMCID: PMC7229696 DOI: 10.1002/pld3.220] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 02/04/2020] [Accepted: 02/24/2020] [Indexed: 05/17/2023]
Abstract
Genome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.
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Affiliation(s)
- Jean‐Michel Michno
- Bioinformatics and Computational BiologyUniversity of MinnesotaSt. PaulMinnesota
- Department of Agronomy and Plant GeneticsUniversity of MinnesotaSt. PaulMinnesota
| | - Junqi Liu
- Department of Agronomy and Plant GeneticsUniversity of MinnesotaSt. PaulMinnesota
| | - Joseph R. Jeffers
- Department of Computer Science and EngineeringUniversity of MinnesotaMinneapolisMinnesota
| | - Robert M. Stupar
- Bioinformatics and Computational BiologyUniversity of MinnesotaSt. PaulMinnesota
- Department of Agronomy and Plant GeneticsUniversity of MinnesotaSt. PaulMinnesota
| | - Chad L. Myers
- Bioinformatics and Computational BiologyUniversity of MinnesotaSt. PaulMinnesota
- Department of Computer Science and EngineeringUniversity of MinnesotaMinneapolisMinnesota
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Kofsky J, Zhang H, Song BH. Genetic Architecture of Early Vigor Traits in Wild Soybean. Int J Mol Sci 2020; 21:E3105. [PMID: 32354037 PMCID: PMC7247153 DOI: 10.3390/ijms21093105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 04/24/2020] [Indexed: 01/13/2023] Open
Abstract
A worldwide food shortage has been projected as a result of the current increase in global population and climate change. In order to provide sufficient food to feed more people, we must develop crops that can produce higher yields. Plant early vigor traits, early growth rate (EGR), early plant height (EPH), inter-node length, and node count are important traits that are related to crop yield. Glycine soja, the wild counterpart to cultivated soybean, Glycine max, harbors much higher genetic diversity and can grow in diverse environments. It can also cross easily with cultivated soybean. Thus, it holds a great potential in developing soybean cultivars with beneficial agronomic traits. In this study, we used 225 wild soybean accessions originally from diverse environments across its geographic distribution in East Asia. We quantified the natural variation of several early vigor traits, investigated the relationships among them, and dissected the genetic basis of these traits by applying a Genome-Wide Association Study (GWAS) with genome-wide single nucleotide polymorphism (SNP) data. Our results showed positive correlation between all early vigor traits studied. A total of 12 SNPs significantly associated with EPH were identified with 4 shared with EGR. We also identified two candidate genes, Glyma.07G055800.1 and Glyma.07G055900.1, playing important roles in influencing trait variation in both EGR and EPH in G. soja.
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Affiliation(s)
| | | | - Bao-Hua Song
- Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (J.K.); (H.Z.)
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Ramzan F, Klees S, Schmitt AO, Cavero D, Gültas M. Identification of Age-Specific and Common Key Regulatory Mechanisms Governing Eggshell Strength in Chicken Using Random Forests. Genes (Basel) 2020; 11:genes11040464. [PMID: 32344666 PMCID: PMC7230204 DOI: 10.3390/genes11040464] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/08/2020] [Accepted: 04/21/2020] [Indexed: 12/21/2022] Open
Abstract
In today's chicken egg industry, maintaining the strength of eggshells in longer laying cycles is pivotal for improving the persistency of egg laying. Eggshell development and mineralization underlie a complex regulatory interplay of various proteins and signaling cascades involving multiple organ systems. Understanding the regulatory mechanisms influencing this dynamic trait over time is imperative, yet scarce. To investigate the temporal changes in the signaling cascades, we considered eggshell strength at two different time points during the egg production cycle and studied the genotype-phenotype associations by employing the Random Forests algorithm on chicken genotypic data. For the analysis of corresponding genes, we adopted a well established systems biology approach to delineate gene regulatory pathways and master regulators underlying this important trait. Our results indicate that, while some of the master regulators (Slc22a1 and Sox11) and pathways are common at different laying stages of chicken, others (e.g., Scn11a, St8sia2, or the TGF- β pathway) represent age-specific functions. Overall, our results provide: (i) significant insights into age-specific and common molecular mechanisms underlying the regulation of eggshell strength; and (ii) new breeding targets to improve the eggshell quality during the later stages of the chicken production cycle.
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Affiliation(s)
- Faisal Ramzan
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (S.K.); (A.O.S.)
- Department of Animal Breeding and Genetics, University of Agriculture Faisalabad, 38000 Faisalabad, Pakistan
| | - Selina Klees
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (S.K.); (A.O.S.)
| | - Armin Otto Schmitt
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (S.K.); (A.O.S.)
- Center for Integrated Breeding Research (CiBreed), Albrecht-Thaer-Weg 3, Georg-August University, 37075 Göttingen, Germany
| | | | - Mehmet Gültas
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; (F.R.); (S.K.); (A.O.S.)
- Center for Integrated Breeding Research (CiBreed), Albrecht-Thaer-Weg 3, Georg-August University, 37075 Göttingen, Germany
- Correspondence:
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73
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Bandoy DJDR, Weimer BC. Biological Machine Learning Combined with Campylobacter Population Genomics Reveals Virulence Gene Allelic Variants Cause Disease. Microorganisms 2020; 8:E549. [PMID: 32290186 PMCID: PMC7232492 DOI: 10.3390/microorganisms8040549] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/07/2020] [Accepted: 04/08/2020] [Indexed: 01/17/2023] Open
Abstract
Highly dimensional data generated from bacterial whole-genome sequencing is providing an unprecedented scale of information that requires an appropriate statistical analysis framework to infer biological function from populations of genomes. The application of genome-wide association study (GWAS) methods is an appropriate framework for bacterial population genome analysis that yields a list of candidate genes associated with a phenotype, but it provides an unranked measure of importance. Here, we validated a novel framework to define infection mechanism using the combination of GWAS, machine learning, and bacterial population genomics that ranked allelic variants that accurately identified disease. This approach parsed a dataset of 1.2 million single nucleotide polymorphisms (SNPs) and indels that resulted in an importance ranked list of associated alleles of porA in Campylobacter jejuni using spatiotemporal analysis over 30 years. We validated this approach using previously proven laboratory experimental alleles from an in vivo guinea pig abortion model. This framework, termed µPathML, defined intestinal and extraintestinal groups that have differential allelic porA variants that cause abortion. Divergent variants containing indels that defeated automated annotation were rescued using biological context and knowledge that resulted in defining rare, divergent variants that were maintained in the population over two continents and 30 years. This study defines the capability of machine learning coupled with GWAS and population genomics to simultaneously identify and rank alleles to define their role in infectious disease mechanisms.
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Affiliation(s)
- DJ Darwin R. Bandoy
- 100 K Pathogen Genome Project, Department of Population Health and Reproduction, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, USA
- Department of Veterinary, Paraclinical Sciences, College of Veterinary Medicine, University of the Philippines Los Baños, Los Baños 4031, Philippines;
| | - Bart C. Weimer
- 100 K Pathogen Genome Project, Department of Population Health and Reproduction, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, USA
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Ma L, Qing C, Frei U, Shen Y, Lübberstedt T. Association mapping for root system architecture traits under two nitrogen conditions in germplasm enhancement of maize doubled haploid lines. ACTA ACUST UNITED AC 2020. [DOI: 10.1016/j.cj.2019.11.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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75
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Beesley LJ, Salvatore M, Fritsche LG, Pandit A, Rao A, Brummett C, Willer CJ, Lisabeth LD, Mukherjee B. The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities. Stat Med 2020; 39:773-800. [PMID: 31859414 PMCID: PMC7983809 DOI: 10.1002/sim.8445] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 09/10/2019] [Accepted: 11/16/2019] [Indexed: 01/03/2023]
Abstract
Biobanks linked to electronic health records provide rich resources for health-related research. With improvements in administrative and informatics infrastructure, the availability and utility of data from biobanks have dramatically increased. In this paper, we first aim to characterize the current landscape of available biobanks and to describe specific biobanks, including their place of origin, size, and data types. The development and accessibility of large-scale biorepositories provide the opportunity to accelerate agnostic searches, expedite discoveries, and conduct hypothesis-generating studies of disease-treatment, disease-exposure, and disease-gene associations. Rather than designing and implementing a single study focused on a few targeted hypotheses, researchers can potentially use biobanks' existing resources to answer an expanded selection of exploratory questions as quickly as they can analyze them. However, there are many obvious and subtle challenges with the design and analysis of biobank-based studies. Our second aim is to discuss statistical issues related to biobank research such as study design, sampling strategy, phenotype identification, and missing data. We focus our discussion on biobanks that are linked to electronic health records. Some of the analytic issues are illustrated using data from the Michigan Genomics Initiative and UK Biobank, two biobanks with two different recruitment mechanisms. We summarize the current body of literature for addressing these challenges and discuss some standing open problems. This work complements and extends recent reviews about biobank-based research and serves as a resource catalog with analytical and practical guidance for statisticians, epidemiologists, and other medical researchers pursuing research using biobanks.
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Affiliation(s)
| | | | | | - Anita Pandit
- University of Michigan, Department of Biostatistics
| | - Arvind Rao
- University of Michigan, Department of Computational Medicine and Bioinformatics
| | - Chad Brummett
- University of Michigan, Department of Anesthesiology
| | - Cristen J. Willer
- University of Michigan, Department of Computational Medicine and Bioinformatics
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Basak T, Nagashima K, Kajimoto S, Kawaguchi T, Tabara Y, Matsuda F, Yamada R. A Geometry-Based Multiple Testing Correction for Contingency Tables by Truncated Normal Distribution. STATISTICS IN BIOSCIENCES 2020. [DOI: 10.1007/s12561-020-09271-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
AbstractInference procedure is a critical step of experimental researches to draw scientific conclusions especially in multiple testing. The false positive rate increases unless the unadjusted marginal p-values are corrected. Therefore, a multiple testing correction is necessary to adjust the p-values based on the number of tests to control type I error. We propose a multiple testing correction of MAX-test for a contingency table, where multiple χ2-tests are applied based on a truncated normal distribution (TND) estimation method by Botev. The table and tests are defined geometrically by contour hyperplanes in the degrees of freedom (df) dimensional space. A linear algebraic method called spherization transforms the shape of the space, defined by the contour hyperplanes of the distribution of tables sharing the same marginal counts. So, the stochastic distributions of these tables are transformed into a standard multivariate normal distribution in df-dimensional space. Geometrically, the p-value is defined by a convex polytope consisted of truncating hyperplanes of test’s contour lines in df-dimensional space. The TND approach of the Botev method was used to estimate the corrected p. Finally, the features of our approach were extracted using a real GWAS data.
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77
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Cerván-Martín M, Castilla JA, Palomino-Morales RJ, Carmona FD. Genetic Landscape of Nonobstructive Azoospermia and New Perspectives for the Clinic. J Clin Med 2020; 9:jcm9020300. [PMID: 31973052 PMCID: PMC7074441 DOI: 10.3390/jcm9020300] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Revised: 01/15/2020] [Accepted: 01/16/2020] [Indexed: 02/07/2023] Open
Abstract
Nonobstructive azoospermia (NOA) represents the most severe expression of male infertility, involving around 1% of the male population and 10% of infertile men. This condition is characterised by the inability of the testis to produce sperm cells, and it is considered to have an important genetic component. During the last two decades, different genetic anomalies, including microdeletions of the Y chromosome, karyotype defects, and missense mutations in genes involved in the reproductive function, have been described as the primary cause of NOA in many infertile men. However, these alterations only explain around 25% of azoospermic cases, with the remaining patients showing an idiopathic origin. Recent studies clearly suggest that the so-called idiopathic NOA has a complex aetiology with a polygenic inheritance, which may alter the spermatogenic process. Although we are far from a complete understanding of the molecular mechanisms underlying NOA, the use of the new technologies for genetic analysis has enabled a considerable increase in knowledge during the last years. In this review, we will provide a comprehensive and updated overview of the genetic basis of NOA, with a special focus on the possible application of the recent insights in clinical practice.
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Affiliation(s)
- Miriam Cerván-Martín
- Departamento de Genética e Instituto de Biotecnología, Universidad de Granada, Centro de Investigación Biomédica (CIBM), Parque Tecnológico Ciencias de la Salud, Av. del Conocimiento, s/n, 18016 Granada, Spain;
- Instituto de Investigación Biosanitaria ibs.GRANADA, Av. de Madrid, 15, Pabellón de Consultas Externas 2, 2ª Planta, 18012 Granada, Spain; (J.A.C.); (R.J.P.-M.)
| | - José A. Castilla
- Instituto de Investigación Biosanitaria ibs.GRANADA, Av. de Madrid, 15, Pabellón de Consultas Externas 2, 2ª Planta, 18012 Granada, Spain; (J.A.C.); (R.J.P.-M.)
- Unidad de Reproducción, UGC Obstetricia y Ginecología, HU Virgen de las Nieves, Av. de las Fuerzas Armadas 2, 18014 Granada, Spain
- CEIFER Biobanco—NextClinics, Calle Maestro Bretón 1, 18004 Granada, Spain
| | - Rogelio J. Palomino-Morales
- Instituto de Investigación Biosanitaria ibs.GRANADA, Av. de Madrid, 15, Pabellón de Consultas Externas 2, 2ª Planta, 18012 Granada, Spain; (J.A.C.); (R.J.P.-M.)
- Departamento de Bioquímica y Biología Molecular I, Universidad de Granada, Facultad de Ciencias, Av. de Fuente Nueva s/n, 18071 Granada, Spain
| | - F. David Carmona
- Departamento de Genética e Instituto de Biotecnología, Universidad de Granada, Centro de Investigación Biomédica (CIBM), Parque Tecnológico Ciencias de la Salud, Av. del Conocimiento, s/n, 18016 Granada, Spain;
- Instituto de Investigación Biosanitaria ibs.GRANADA, Av. de Madrid, 15, Pabellón de Consultas Externas 2, 2ª Planta, 18012 Granada, Spain; (J.A.C.); (R.J.P.-M.)
- Correspondence: ; Tel.: +34-958-241-000 (ext 20170)
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78
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Ferreira JP, Duarte K, Woehrle H, Cowie MR, Wegscheider K, Angermann C, d'Ortho MP, Erdmann E, Levy P, Simonds AK, Somers VK, Teschler H, Rossignol P, Koenig W, Zannad F. Biomarkers in patients with heart failure and central sleep apnoea: findings from the SERVE-HF trial. ESC Heart Fail 2020; 7:503-511. [PMID: 31951323 PMCID: PMC7160494 DOI: 10.1002/ehf2.12521] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 08/19/2019] [Accepted: 09/06/2019] [Indexed: 12/28/2022] Open
Abstract
Aims The Treatment of Sleep‐Disordered Breathing with Predominant Central Sleep Apnoea by Adaptive Servo Ventilation in Patients with Heart Failure trial investigated the effects of adaptive servo‐ventilation (ASV) (vs. control) on outcomes of 1325 patients with heart failure and reduced ejection fraction (HFrEF) and central sleep apnoea (CSA). The primary outcome (a composite of all‐cause death or unplanned HF hospitalization) did not differ between the two groups. However, all‐cause and cardiovascular (CV) mortality were higher in the ASV group. Circulating biomarkers may help in better ascertain patients' risk, and this is the first study applying a large set of circulating biomarkers in patients with both HFrEF and CSA. Methods and results Circulating protein‐biomarkers (n = 276) ontologically involved in CV pathways, were studied in 749 (57% of the trial population) patients (biomarker substudy), to investigate their association with the study outcomes (primary outcome, CV death and all‐cause death). The mean age was 69 ± 10 years, and > 90% were male. The groups (ASV vs. control and biomarker substudy vs. no biomarker) were well balanced. The “best” clinical prognostic model included male sex, systolic blood pressure < 120 mmHg, diabetes, loop diuretic, cardiac device, 6‐min walking test distance, and N‐terminal pro BNP as the strongest prognosticators. On top of the “best” clinical prognostic model, the biomarkers that significantly improved both the discrimination (c‐index) and the net reclassification index (NRI) of the model were soluble suppression of tumorigenicity 2 for the primary outcome; neurogenic locus notch homolog protein 3 (Notch‐3) for CV‐death and all‐cause death; and growth differentiation factor 15 (GDF‐15) for all‐cause death only. Conclusions We studied 276 circulating biomarkers in patients with HFrEF and central sleep apnoea; of these biomarkers, three added significant prognostic information on top of the best clinical model: soluble suppression of tumorigenicity 2 (primary outcome), Notch‐3 (CV and all‐cause death), and GDF‐15 (all‐cause death).
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Affiliation(s)
- João Pedro Ferreira
- Inserm CIC-P 1433, CHRU de Nancy, Inserm U1116, French Clinical Research Infrastructure Network Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Université de Lorraine, Nancy, France
| | - Kévin Duarte
- Inserm CIC-P 1433, CHRU de Nancy, Inserm U1116, French Clinical Research Infrastructure Network Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Université de Lorraine, Nancy, France
| | - Holger Woehrle
- ResMed Science Center, ResMed Germany Inc., Martinsried, Germany
| | - Martin R Cowie
- Faculty of Medicine, Imperial College London, London, UK
| | - Karl Wegscheider
- Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christiane Angermann
- Faculty of Medicine I and Comprehensive Heart Failure Center, University Hospital and University of Würzburg, Würzburg, Germany
| | - Marie-Pia d'Ortho
- Hôpital Bichat, Explorations Fonctionnelles, DHU FIRE, AP-HP, Paris, France.,UFR de Médicine, Sorbonne Paris Cité, Paris Diderot University, Paris, France
| | | | - Patrick Levy
- Inserm, HP2 lab. CHU Grenoble, Université de Grenoble Alpes, Alpes, France
| | | | - Virend K Somers
- Cardiovascular Facility and the Sleep Facility, Mayo Clinic and Mayo Foundation, Rochester, MN, USA
| | - Helmut Teschler
- Department of Pneumology, Ruhrlandklinik, Essen, Germany.,West German Lung Centre, Essen University Hospital, Essen, Germany.,University Duisburg-Essen, Department of Pneumology, Essen, Germany
| | - Patrick Rossignol
- Inserm CIC-P 1433, CHRU de Nancy, Inserm U1116, French Clinical Research Infrastructure Network Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Université de Lorraine, Nancy, France
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.,Munich Heart Alliance, German Centre for Cardiovascular Research, partner site Munich Heart Alliance, Munich, Germany
| | - Faiez Zannad
- Inserm CIC-P 1433, CHRU de Nancy, Inserm U1116, French Clinical Research Infrastructure Network Investigation Network Initiative-Cardiovascular and Renal Clinical Trialists, Université de Lorraine, Nancy, France
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79
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Liu M, Tan X, Yang Y, Liu P, Zhang X, Zhang Y, Wang L, Hu Y, Ma L, Li Z, Zhang Y, Zou C, Lin H, Gao S, Lee M, Lübberstedt T, Pan G, Shen Y. Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:207-221. [PMID: 31199064 PMCID: PMC6920160 DOI: 10.1111/pbi.13188] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 05/26/2019] [Accepted: 06/01/2019] [Indexed: 05/14/2023]
Abstract
Kernel size-related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10-6 ) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10-3 ) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable-effect SNPs and the co-localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co-localized SNPs, of which zma-miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma-miR164e resulted in the down-regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker-assisted selection (MAS) for high-yield breeding in maize.
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Affiliation(s)
- Min Liu
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Xiaolong Tan
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Yan Yang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Peng Liu
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Xiaoxiang Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Yinchao Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Lei Wang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Yu Hu
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Langlang Ma
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Zhaoling Li
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Yanling Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Chaoying Zou
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Haijian Lin
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Shibin Gao
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Michael Lee
- Department of AgronomyIowa State UniversityAmesIAUSA
| | | | - Guangtang Pan
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
| | - Yaou Shen
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest RegionMaize Research InstituteSichuan Agricultural UniversityChengduChina
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China (In preparation)ChengduChina
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80
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Diaz S, Ariza-Suarez D, Ramdeen R, Aparicio J, Arunachalam N, Hernandez C, Diaz H, Ruiz H, Piepho HP, Raatz B. Genetic Architecture and Genomic Prediction of Cooking Time in Common Bean ( Phaseolus vulgaris L.). FRONTIERS IN PLANT SCIENCE 2020; 11:622213. [PMID: 33643335 PMCID: PMC7905357 DOI: 10.3389/fpls.2020.622213] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 12/21/2020] [Indexed: 05/21/2023]
Abstract
Cooking time of the common bean is an important trait for consumer preference, with implications for nutrition, health, and environment. For efficient germplasm improvement, breeders need more information on the genetics to identify fast cooking sources with good agronomic properties and molecular breeding tools. In this study, we investigated a broad genetic variation among tropical germplasm from both Andean and Mesoamerican genepools. Four populations were evaluated for cooking time (CKT), water absorption capacity (WAC), and seed weight (SdW): a bi-parental RIL population (DxG), an eight-parental Mesoamerican MAGIC population, an Andean (VEF), and a Mesoamerican (MIP) breeding line panel. A total of 922 lines were evaluated in this study. Significant genetic variation was found in all populations with high heritabilities, ranging from 0.64 to 0.89 for CKT. CKT was related to the color of the seed coat, with the white colored seeds being the ones that cooked the fastest. Marker trait associations were investigated by QTL analysis and GWAS, resulting in the identification of 10 QTL. In populations with Andean germplasm, an inverse correlation of CKT and WAC, and also a QTL on Pv03 that inversely controls CKT and WAC (CKT3.2/WAC3.1) were observed. WAC7.1 was found in both Mesoamerican populations. QTL only explained a small part of the variance, and phenotypic distributions support a more quantitative mode of inheritance. For this reason, we evaluated how genomic prediction (GP) models can capture the genetic variation. GP accuracies for CKT varied, ranging from good results for the MAGIC population (0.55) to lower accuracies in the MIP panel (0.22). The phenotypic characterization of parental material will allow for the cooking time trait to be implemented in the active germplasm improvement programs. Molecular breeding tools can be developed to employ marker-assisted selection or genomic selection, which looks to be a promising tool in some populations to increase the efficiency of breeding activities.
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Affiliation(s)
- Santiago Diaz
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Daniel Ariza-Suarez
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Raisa Ramdeen
- Institute of Crop Science, University of Hohenheim, Hohenheim, Germany
| | - Johan Aparicio
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Nirmala Arunachalam
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
- Departamento de Agronomía, Facultad de Ciencias Agrarias, Universidad Nacional de Colombia, Bogotá, Colombia
| | | | - Harold Diaz
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Henry Ruiz
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Hans-Peter Piepho
- Institute of Crop Science, University of Hohenheim, Hohenheim, Germany
| | - Bodo Raatz
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
- *Correspondence: Bodo Raatz,
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81
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Mikkola L, Holopainen S, Pessa-Morikawa T, Lappalainen AK, Hytönen MK, Lohi H, Iivanainen A. Genetic dissection of canine hip dysplasia phenotypes and osteoarthritis reveals three novel loci. BMC Genomics 2019; 20:1027. [PMID: 31881848 PMCID: PMC6935090 DOI: 10.1186/s12864-019-6422-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 12/22/2019] [Indexed: 12/15/2022] Open
Abstract
Background Hip dysplasia and osteoarthritis continue to be prevalent problems in veterinary and human medicine. Canine hip dysplasia is particularly problematic as it massively affects several large-sized breeds and can cause a severe impairment of the quality of life. In Finland, the complex condition is categorized to five classes from normal to severe dysplasia, but the categorization includes several sub-traits: congruity of the joint, Norberg angle, subluxation degree of the joint, shape and depth of the acetabulum, and osteoarthritis. Hip dysplasia and osteoarthritis have been proposed to have separate genetic etiologies. Results Using Fédération Cynologique Internationale -standardized ventrodorsal radiographs, German shepherds were rigorously phenotyped for osteoarthritis, and for joint incongruity by Norberg angle and femoral head center position in relation to dorsal acetabular edge. The affected dogs were categorized into mild, moderate and severe dysplastic phenotypes using official hip scores. Three different genome-wide significant loci were uncovered. The strongest candidate genes for hip joint incongruity were noggin (NOG), a bone and joint developmental gene on chromosome 9, and nanos C2HC-type zinc finger 1 (NANOS1), a regulator of matrix metalloproteinase 14 (MMP14) on chromosome 28. Osteoarthritis mapped to a long intergenic region on chromosome 1, between genes encoding for NADPH oxidase 3 (NOX3), an intriguing candidate for articular cartilage degradation, and AT-rich interactive domain 1B (ARID1B) that has been previously linked to joint laxity. Conclusions Our findings highlight the complexity of canine hip dysplasia phenotypes. In particular, the results of this study point to the potential involvement of specific and partially distinct loci and genes or pathways in the development of incongruity, mild dysplasia, moderate-to-severe dysplasia and osteoarthritis of canine hip joints. Further studies should unravel the unique and common mechanisms for the various sub-traits.
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Affiliation(s)
- Lea Mikkola
- Department of Veterinary Biosciences, University of Helsinki, P.O. Box 66 (Mustialankatu 1), FI-00014, Helsinki, Finland.,Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland
| | - Saila Holopainen
- Department of Veterinary Biosciences, University of Helsinki, P.O. Box 66 (Mustialankatu 1), FI-00014, Helsinki, Finland.,Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland.,Department of Equine and Small Animal Medicine, University of Helsinki, Helsinki, Finland
| | - Tiina Pessa-Morikawa
- Department of Veterinary Biosciences, University of Helsinki, P.O. Box 66 (Mustialankatu 1), FI-00014, Helsinki, Finland
| | - Anu K Lappalainen
- Department of Equine and Small Animal Medicine, University of Helsinki, Helsinki, Finland
| | - Marjo K Hytönen
- Department of Veterinary Biosciences, University of Helsinki, P.O. Box 66 (Mustialankatu 1), FI-00014, Helsinki, Finland.,Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland
| | - Hannes Lohi
- Department of Veterinary Biosciences, University of Helsinki, P.O. Box 66 (Mustialankatu 1), FI-00014, Helsinki, Finland.,Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland
| | - Antti Iivanainen
- Department of Veterinary Biosciences, University of Helsinki, P.O. Box 66 (Mustialankatu 1), FI-00014, Helsinki, Finland.
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82
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Zhang J, Zhang Y, Gong H, Cui L, Ma J, Chen C, Ai H, Xiao S, Huang L, Yang B. Landscape of Loci and Candidate Genes for Muscle Fatty Acid Composition in Pigs Revealed by Multiple Population Association Analysis. Front Genet 2019; 10:1067. [PMID: 31708975 PMCID: PMC6824322 DOI: 10.3389/fgene.2019.01067] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Accepted: 10/04/2019] [Indexed: 01/19/2023] Open
Abstract
Genome wide association analyses in diverse populations can identify complex trait loci that are specifically present in one population or shared across multiple populations, which help to better understand the genetic architecture of complex traits in a broader genetic context. In this study, we conducted genome-wide association studies and meta-analysis for 38 fatty acid composition traits with 12–19 million imputed genome sequence SNPs in 2446 pigs from six populations, encompassing White Duroc × Erhualian F2, Sutai, Duroc-Landrace-Yorkshire (DLY) three-way cross, Laiwu, Erhualian, and Bamaxiang pigs that were originally genotyped with 60 K or 1.4 million single nucleotide polymorphism (SNP) chips. The analyses uncovered 285 lead SNPs (P < 5 × 10-8), among which 78 locate more than 1 Mb to the lead chip SNPs were considered as novel, largely augmented the landscape of loci for porcine muscle fatty acid composition. Meta-analysis enhanced the association significance at loci near FADS2, ABCD2, ELOVL5, ELOVL6, ELOVL7, SCD, and THRSP genes, suggesting possible existence of population shared mutations underlying these loci. Further haplotype analysis at SCD loci identified a shared 3.7 kb haplotype in F2, Sutai and DLY pigs showing consistent effects of decreasing C18:0 contents in the three populations. In contrast, at FASN loci, we found an Erhualian specific haplotype explaining the population specific association signals in Erhualian pigs. This study refines our understanding on landscape of loci and candidate genes for fatty acid composition traits of pigs.
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Affiliation(s)
- Junjie Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Yifeng Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Huanfa Gong
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Leilei Cui
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Junwu Ma
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Congying Chen
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Huashui Ai
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Bin Yang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
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83
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Tanimoto K, Muramatsu T, Inazawa J. Massive computational identification of somatic variants in exonic splicing enhancers using The Cancer Genome Atlas. Cancer Med 2019; 8:7372-7384. [PMID: 31631560 PMCID: PMC6885893 DOI: 10.1002/cam4.2619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 10/01/2019] [Accepted: 10/02/2019] [Indexed: 12/26/2022] Open
Abstract
Owing to the development of next-generation sequencing (NGS) technologies, a large number of somatic variants have been identified in various types of cancer. However, the functional significance of most somatic variants remains unknown. Somatic variants that occur in exonic splicing enhancer (ESE) regions are thought to prevent serine and arginine-rich (SR) proteins from binding to ESE sequence motifs, which leads to exon skipping. We computationally identified somatic variants in ESEs by compiling numerous open-access datasets from The Cancer Genome Atlas (TCGA). Using somatic variants and RNA-seq data from 9635 patients across 32 TCGA projects, we identified 646 ESE-disrupting variants. The false positive rate of our method, estimated using a permutation test, was approximately 1%. Of these ESE-disrupting variants, approximately 71% were located in the binding motifs of four classical SR proteins. ESE-disrupting variants occurred in proportion to the number of somatic variants, but not necessarily in the specific genes associated with the biological processes of cancer. Existing bioinformatics tools could not predict the pathogenicity of ESE-disrupting variants identified in this study, although these variants could cause exon skipping. We demonstrated that ESE-disrupting nonsense variants tended to escape nonsense-mediated decay surveillance. Using integrated analyses of open access data, we could specifically identify ESE-disrupting variants. We have generated a powerful tool, which can handle datasets without normal samples or raw data, and thus contribute to reducing variants of uncertain significance because our statistical approach only uses the exon-junction read counts from the tumor samples.
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Affiliation(s)
- Kousuke Tanimoto
- Genome Laboratory, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Genomics Research Support Unit, Research Core, Tokyo Medical and Dental University (TMDU), Japan, Tokyo, Japan
| | - Tomoki Muramatsu
- Department of Molecular Cytogenetics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Johji Inazawa
- Department of Molecular Cytogenetics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Bioresource Research Center, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
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84
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Rojano E, Seoane P, Ranea JAG, Perkins JR. Regulatory variants: from detection to predicting impact. Brief Bioinform 2019; 20:1639-1654. [PMID: 29893792 PMCID: PMC6917219 DOI: 10.1093/bib/bby039] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 04/18/2018] [Indexed: 02/01/2023] Open
Abstract
Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin-chromatin and chromatin-protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution. We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms.
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Affiliation(s)
- Elena Rojano
- Department of Molecular Biology and Biochemistry, University of Malaga (UMA), 29010 Malaga, Spain
| | - Pedro Seoane
- Department of Molecular Biology and Biochemistry, University of Malaga (UMA), 29010 Malaga, Spain
| | - Juan A G Ranea
- CIBER de Enfermedades Raras, ISCIII, Madrid, Spain and Department of Molecular Biology and Biochemistry, University of Malaga (UMA), 29010 Malaga, Spain
| | - James R Perkins
- Research laboratory, IBIMA-Regional University Hospital of Malaga, UMA, Malaga 29009, Spain
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85
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Weighill D, Tschaplinski TJ, Tuskan GA, Jacobson D. Data Integration in Poplar: 'Omics Layers and Integration Strategies. Front Genet 2019; 10:874. [PMID: 31608114 PMCID: PMC6773870 DOI: 10.3389/fgene.2019.00874] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Accepted: 08/20/2019] [Indexed: 12/20/2022] Open
Abstract
Populus trichocarpa is an important biofuel feedstock that has been the target of extensive research and is emerging as a model organism for plants, especially woody perennials. This research has generated several large ‘omics datasets. However, only few studies in Populus have attempted to integrate various data types. This review will summarize various ‘omics data layers, focusing on their application in Populus species. Subsequently, network and signal processing techniques for the integration and analysis of these data types will be discussed, with particular reference to examples in Populus.
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Affiliation(s)
- Deborah Weighill
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Knoxville, TN, United States.,Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Timothy J Tschaplinski
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Knoxville, TN, United States.,Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Gerald A Tuskan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Daniel Jacobson
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Knoxville, TN, United States.,Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
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86
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Xu W, Chen D, Yan G, Xiao S, Huang T, Zhang Z, Huang L. Rediscover and Refine QTLs for Pig Scrotal Hernia by Increasing a Specially Designed F 3 Population and Using Whole-Genome Sequence Imputation Technology. Front Genet 2019; 10:890. [PMID: 31608119 PMCID: PMC6768097 DOI: 10.3389/fgene.2019.00890] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 08/23/2019] [Indexed: 11/14/2022] Open
Abstract
Pig scrotal hernia is one of the most common congenital defects triggered by both genetic and environmental factors, leading to severe economic loss as well as poor animal welfare in the pig industry. Identification and implementation of genomic regions controlling scrotal hernia in breeding is of great appeal to reduce incidences of hernia in pig production. The aim of this study was to identify such regions or molecular markers affecting scrotal hernia in pigs. First of all, we summarized and analyzed the results of some international teams on scrotal hernia and designed a specially population which contains 246 male individuals. We then performed genome-wide association study (GWAS) in this specially designed population using two scenarios, i.e., the target panel data before and after imputation, which contain 42,365 SNPs and 18,756,672 SNPs, respectively. In addition, a series of methods including genetic differentiation analysis, linkage disequilibrium and linkage analysis (LDLA), and haplotype sharing analysis were appropriate to provide for further analysis to identify the potential gene underlying the QTL. The GWAS in this report detected a highly significant region affecting scrotal hernia within a 24.8Mb region (114.1-138.9Mb) on SSC8. And the result of genetic differentiation analysis also showed a strong genetic differentiation signal between 116.1 and 132.7Mb on SSC8. In addition, the QTL interval was refined to 2.99Mb by combining LDLA and genetic differentiation analysis. Finally, two susceptibility haplotypes were identified through haplotype sharing analysis, with one potential causal gene in it. Our study provided deeper insights into the genetic architecture of pig scrotal hernia and contributed to further fine-mapping and characterize haplotype and gene that influence scrotal hernia in pigs.
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Affiliation(s)
| | | | | | | | | | - Zhiyan Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
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87
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Kyriakis D, Kanterakis A, Manousaki T, Tsakogiannis A, Tsagris M, Tsamardinos I, Papaharisis L, Chatziplis D, Potamias G, Tsigenopoulos CS. Scanning of Genetic Variants and Genetic Mapping of Phenotypic Traits in Gilthead Sea Bream Through ddRAD Sequencing. Front Genet 2019; 10:675. [PMID: 31447879 PMCID: PMC6691846 DOI: 10.3389/fgene.2019.00675] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 06/27/2019] [Indexed: 12/31/2022] Open
Abstract
Gilthead sea bream (Sparus aurata) is a teleost of considerable economic importance in Southern European aquaculture. The aquaculture industry shows a growing interest in the application of genetic methods that can locate phenotype-genotype associations with high economic impact. Through selective breeding, the aquaculture industry can exploit this information to maximize the financial yield. Here, we present a Genome Wide Association Study (GWAS) of 112 samples belonging to seven different sea bream families collected from a Greek commercial aquaculture company. Through double digest Random Amplified DNA (ddRAD) Sequencing, we generated a per-sample genetic profile consisting of 2,258 high-quality Single Nucleotide Polymorphisms (SNPs). These profiles were tested for association with four phenotypes of major financial importance: Fat, Weight, Tag Weight, and the Length to Width ratio. We applied two methods of association analysis. The first is the typical single-SNP to phenotype test, and the second is a feature selection (FS) method through two novel algorithms that are employed for the first time in aquaculture genomics and produce groups with multiple SNPs associated to a phenotype. In total, we identified 9 single SNPs and 6 groups of SNPs associated with weight-related phenotypes (Weight and Tag Weight), 2 groups associated with Fat, and 16 groups associated with the Length to Width ratio. Six identified loci (Chr4:23265532, Chr6:12617755, Chr:8:11613979, Chr13:1098152, Chr15:3260819, and Chr22:14483563) were present in genes associated with growth in other teleosts or even mammals, such as semaphorin-3A and neurotrophin-3. These loci are strong candidates for future studies that will help us unveil the genetic mechanisms underlying growth and improve the sea bream aquaculture productivity by providing genomic anchors for selection programs.
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Affiliation(s)
- Dimitrios Kyriakis
- School of Medicine, University of Crete, Heraklion, Greece
- Foundation for Research and Technology–Hellas (FORTH), Heraklion, Greece
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece
| | | | - Tereza Manousaki
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece
| | - Alexandros Tsakogiannis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece
| | - Michalis Tsagris
- Deparment of Economics, University of Crete, Gallos Campus, Rethymnon, Greece
| | - Ioannis Tsamardinos
- Department of Computer Science, University of Crete, Voutes Campus, Heraklion, Greece
| | | | - Dimitris Chatziplis
- Department of Agriculture Technology, Alexander Technological Education Institute of Thessaloniki, Thessaloniki, Greece
| | - George Potamias
- Foundation for Research and Technology–Hellas (FORTH), Heraklion, Greece
| | - Costas S. Tsigenopoulos
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece
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88
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Wu P, Wang K, Yang Q, Zhou J, Chen D, Liu Y, Ma J, Tang Q, Jin L, Xiao W, Lou P, Jiang A, Jiang Y, Zhu L, Li M, Li X, Tang G. Whole-genome re-sequencing association study for direct genetic effects and social genetic effects of six growth traits in Large White pigs. Sci Rep 2019; 9:9667. [PMID: 31273229 PMCID: PMC6609718 DOI: 10.1038/s41598-019-45919-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 06/20/2019] [Indexed: 12/23/2022] Open
Abstract
Socially affected traits are affected by direct genetic effects (DGE) and social genetic effects (SGE). DGE and SGE of an individual directly quantify the genetic influence of its own phenotypes and the phenotypes of other individuals, respectively. In the current study, a total of 3,276 Large White pigs from different pens were used, and each pen contained 10 piglets. DGE and SGE were estimated for six socially affected traits, and then a GWAS was conducted to identify SNPs associated with DGE and SGE. Based on the whole-genome re-sequencing, 40 Large White pigs were genotyped and 10,501,384 high quality SNPs were retained for single-locus and multi-locus GWAS. For single-locus GWAS, a total of 54 SNPs associated with DGE and 33 SNPs with SGE exceeded the threshold (P < 5.00E-07) were detected for six growth traits. Of these, 22 SNPs with pleiotropic effects were shared by DGE and SGE. For multi-locus GWAS, a total of 72 and 110 putative QTNs were detected for DGE and SGE, respectively. Of these, 5 SNPs with pleiotropic effects were shared by DGE and SGE. It is noteworthy that 2 SNPs (SSC8: 16438396 for DGE and SSC17: 9697454 for SGE) were detected in single-locus and multi-locus GWAS. Furthermore, 15 positional candidate genes shared by SGE and DGE were identified because of their roles in behaviour, health and disease. Identification of genetic variants and candidate genes for DGE and SGE for socially affected traits will provide a new insight to understand the genetic architecture of socially affected traits in pigs.
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Affiliation(s)
- Pingxian Wu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Kai Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Qiang Yang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Jie Zhou
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Dejuan Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Yihui Liu
- Sichuan Animal Husbandry Station, Chengdu, 610041, Sichuan, China
| | - Jideng Ma
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Qianzi Tang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Long Jin
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Weihang Xiao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Pinger Lou
- Zhejiang Tianpeng Group Co., Ltd., Jiangshan, 324111, Zhejiang, China
| | - Anan Jiang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Yanzhi Jiang
- College of Life Science, Sichuan Agricultural University, Yaan, 625014, Sichuan, China
| | - Li Zhu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Mingzhou Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Xuewei Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China
| | - Guoqing Tang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
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89
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Mikkola LI, Holopainen S, Lappalainen AK, Pessa-Morikawa T, Augustine TJP, Arumilli M, Hytönen MK, Hakosalo O, Lohi H, Iivanainen A. Novel protective and risk loci in hip dysplasia in German Shepherds. PLoS Genet 2019; 15:e1008197. [PMID: 31323019 PMCID: PMC6668854 DOI: 10.1371/journal.pgen.1008197] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 07/31/2019] [Accepted: 05/14/2019] [Indexed: 12/15/2022] Open
Abstract
Canine hip dysplasia is a common, non-congenital, complex and hereditary disorder. It can inflict severe pain via secondary osteoarthritis and lead to euthanasia. An analogous disorder exists in humans. The genetic background of hip dysplasia in both species has remained ambiguous despite rigorous studies. We aimed to investigate the genetic causes of this disorder in one of the high-risk breeds, the German Shepherd. We performed genetic analyses with carefully phenotyped case-control cohorts comprising 525 German Shepherds. In our genome-wide association studies we identified four suggestive loci on chromosomes 1 and 9. Targeted resequencing of the two loci on chromosome 9 from 24 affected and 24 control German Shepherds revealed deletions of variable sizes in a putative enhancer element of the NOG gene. NOG encodes for noggin, a well-described bone morphogenetic protein inhibitor affecting multiple developmental processes, including joint development. The deletion was associated with the healthy controls and mildly dysplastic dogs suggesting a protective role against canine hip dysplasia. Two enhancer variants displayed a decreased activity in a dual luciferase reporter assay. Our study identifies novel loci and candidate genes for canine hip dysplasia, with potential regulatory variants in the NOG gene. Further research is warranted to elucidate how the identified variants affect the expression of noggin in canine hips, and what the potential effects of the other identified loci are.
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Affiliation(s)
- Lea I. Mikkola
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Department of Molecular Genetics, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland
| | - Saila Holopainen
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Department of Molecular Genetics, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland
- Department of Equine and Small Animal Medicine, University of Helsinki, Helsinki, Finland
| | - Anu K. Lappalainen
- Department of Equine and Small Animal Medicine, University of Helsinki, Helsinki, Finland
| | | | | | - Meharji Arumilli
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Department of Molecular Genetics, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland
| | - Marjo K. Hytönen
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Department of Molecular Genetics, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland
| | - Osmo Hakosalo
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Department of Molecular Genetics, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland
| | - Hannes Lohi
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Department of Molecular Genetics, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Programs Unit, Molecular Neurology, University of Helsinki, Helsinki, Finland
| | - Antti Iivanainen
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
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90
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Al Kalaldeh M, Gibson J, Duijvesteijn N, Daetwyler HD, MacLeod I, Moghaddar N, Lee SH, van der Werf JHJ. Using imputed whole-genome sequence data to improve the accuracy of genomic prediction for parasite resistance in Australian sheep. Genet Sel Evol 2019; 51:32. [PMID: 31242855 PMCID: PMC6595562 DOI: 10.1186/s12711-019-0476-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 06/18/2019] [Indexed: 01/16/2023] Open
Abstract
Background This study aimed at (1) comparing the accuracies of genomic prediction for parasite resistance in sheep based on whole-genome sequence (WGS) data to those based on 50k and high-density (HD) single nucleotide polymorphism (SNP) panels; (2) investigating whether the use of variants within quantitative trait loci (QTL) regions that were selected from regional heritability mapping (RHM) in an independent dataset improved the accuracy more than variants selected from genome-wide association studies (GWAS); and (3) comparing the prediction accuracies between variants selected from WGS data to variants selected from the HD SNP panel. Results The accuracy of genomic prediction improved marginally from 0.16 ± 0.02 and 0.18 ± 0.01 when using all the variants from 50k and HD genotypes, respectively, to 0.19 ± 0.01 when using all the variants from WGS data. Fitting a GRM from the selected variants alongside a GRM from the 50k SNP genotypes improved the prediction accuracy substantially compared to fitting the 50k SNP genotypes alone. The gain in prediction accuracy was slightly more pronounced when variants were selected from WGS data compared to when variants were selected from the HD panel. When sequence variants that passed the GWAS \documentclass[12pt]{minimal}
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\begin{document}$$- log_{10} (p\,value)$$\end{document}-log10(pvalue) threshold of 3 across the entire genome were selected, the prediction accuracy improved by 5% (up to 0.21 ± 0.01), whereas when selection was limited to sequence variants that passed the same GWAS \documentclass[12pt]{minimal}
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\begin{document}$$- log_{10} (p\,value)$$\end{document}-log10(pvalue) threshold of 3 in regions identified by RHM, the accuracy improved by 9% (up to 0.25 ± 0.01). Conclusions Our results show that through careful selection of sequence variants from the QTL regions, the accuracy of genomic prediction for parasite resistance in sheep can be improved. These findings have important implications for genomic prediction in sheep.
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Affiliation(s)
- Mohammad Al Kalaldeh
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia. .,School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
| | - John Gibson
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.,School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Naomi Duijvesteijn
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.,School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Hans D Daetwyler
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.,Centre for AgriBioscience, Agriculture Victoria, Bundoora, VIC, 3083, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | - Iona MacLeod
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.,Centre for AgriBioscience, Agriculture Victoria, Bundoora, VIC, 3083, Australia
| | - Nasir Moghaddar
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.,School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Sang Hong Lee
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia
| | - Julius H J van der Werf
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.,School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
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91
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Brennan RS, Garrett AD, Huber KE, Hargarten H, Pespeni MH. Rare genetic variation and balanced polymorphisms are important for survival in global change conditions. Proc Biol Sci 2019; 286:20190943. [PMID: 31185858 PMCID: PMC6571474 DOI: 10.1098/rspb.2019.0943] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 05/17/2019] [Indexed: 12/14/2022] Open
Abstract
Standing genetic variation is important for population persistence in extreme environmental conditions. While some species may have the capacity to adapt to predicted average future global change conditions, the ability to survive extreme events is largely unknown. We used single-generation selection experiments on hundreds of thousands of Strongylocentrotus purpuratus sea urchin larvae generated from wild-caught adults to identify adaptive genetic variation responsive to moderate (pH 8.0) and extreme (pH 7.5) low-pH conditions. Sequencing genomic DNA from pools of larvae, we identified consistent changes in allele frequencies across replicate cultures for each pH condition and observed increased linkage disequilibrium around selected loci, revealing selection on recombined standing genetic variation. We found that loci responding uniquely to either selection regime were at low starting allele frequencies while variants that responded to both pH conditions (11.6% of selected variants) started at high frequencies. Loci under selection performed functions related to energetics, pH tolerance, cell growth and actin/cytoskeleton dynamics. These results highlight that persistence in future conditions will require two classes of genetic variation: common, pH-responsive variants maintained by balancing selection in a heterogeneous environment, and rare variants, particularly for extreme conditions, that must be maintained by large population sizes.
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92
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Guo H, Wang Y, Zhang B, Li D, Chen J, Zong J, Li J, Liu J, Jiang Y. Association of candidate genes with drought tolerance traits in zoysiagrass germplasm. JOURNAL OF PLANT PHYSIOLOGY 2019; 237:61-71. [PMID: 31026777 DOI: 10.1016/j.jplph.2019.04.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 04/09/2019] [Accepted: 04/10/2019] [Indexed: 06/09/2023]
Abstract
Drought stress negatively influences the growth and physiology of perennial grasses. The objective of this study was to identify associations of candidate genes with drought tolerance traits in 96 zoysiagrass (Zoysia Willd.) accessions. Germplasm varied largely in leaf wilting, canopy and air temperature difference (CAD), leaf water content (LWC), chlorophyll fluorescence (Fv/Fm), leaf dry weight (LDW), stolon dry weight (SDW), rhizome dry weight (RZW), and root dry weight (RDW) under drought stress across the two experiments in 2014 and 2015 in a greenhouse. The population exhibited three subgroups based on molecular marker analysis and had minimum relative kinship. Associations between single nucleotide polymorphisms (SNPs) in BADH encoding betaine aldehyde dehydrogenase, DREB1 encoding DREB-like protein 1, Ndhf encoding NADH dehydrogenase subunit F, CAT encoding catalase, and VP1 encoding H+-pyrophosphatase were analyzed with trait under drought stress (D) and relative values compared to the control (R). Twenty-seven mark and trait associations were detected in year 2014, 2015, and a two-year combination across four genes, including 13 associations in 7 SNP loci in BADH, 9 associations in 5 SNP loci in DREB1, 3 associations in one SNP locus in Ndhf, and 2 associations in one SNP locus in CAT. Of them, one SNP in BADH was associated with D-RDW or D-SDW, three SNPs in DREB1 were associated with D-RZW, D-RDW, R-LWC, and D-CAD, and one SNP in CAT was associated with D-SDW. Nucleotide changes in these SNP loci caused non-synonymous amino acid substitutions. The results indicated that allelic diversity in genes involved in antioxidant metabolism, osmotic homeostasis, and dehydration responsive transcription factor could contribute to growth and physiological variations in zoysiagrass under drought stress.
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Affiliation(s)
- Hailin Guo
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Yi Wang
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Bing Zhang
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Dandan Li
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Jingbo Chen
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Junqing Zong
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Jianjian Li
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
| | - Jianxiu Liu
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China.
| | - Yiwei Jiang
- Department of Agronomy, Purdue University, West Lafayette, IN, 47907, USA.
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93
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Zhang Y, Zhang J, Gong H, Cui L, Zhang W, Ma J, Chen C, Ai H, Xiao S, Huang L, Yang B. Genetic correlation of fatty acid composition with growth, carcass, fat deposition and meat quality traits based on GWAS data in six pig populations. Meat Sci 2019; 150:47-55. [DOI: 10.1016/j.meatsci.2018.12.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Revised: 12/08/2018] [Accepted: 12/16/2018] [Indexed: 10/27/2022]
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94
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Wallace HJ, Cadby G, Melton PE, Wood FM, Falder S, Crowe MM, Martin LJ, Marlow K, Ward SV, Fear MW. Genetic influence on scar height and pliability after burn injury in individuals of European ancestry: A prospective cohort study. Burns 2018; 45:567-578. [PMID: 30595539 DOI: 10.1016/j.burns.2018.10.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 08/15/2018] [Accepted: 10/04/2018] [Indexed: 12/26/2022]
Abstract
After similar extent of injury there is considerable variability in scarring between individuals, in part due to genetic factors. This study aimed to identify genetic variants associated with scar height and pliability after burn injury. An exome-wide array association study and gene pathway analysis were performed on a prospective cohort of 665 patients treated for burn injury. Outcomes were scar height (SH) and scar pliability (SP) sub-scores of the modified Vancouver Scar Scale (mVSS). DNA was genotyped using the Infinium® HumanCoreExome-24 BeadChip. Associations between genetic variants (single nucleotide polymorphisms) and SH and SP were estimated using an additive genetic model adjusting for age, sex, number of surgical procedures and % total body surface area of burn in subjects of European ancestry. No individual genetic variants achieved the cut-off threshold of significance. Gene regions were analysed for spatially correlated single nucleotide polymorphisms and significant regions identified using comb-p software. This gene list was subject to gene pathway analysis to find which biological process terms were over-represented. Using this approach biological processes related to the nervous system and cell adhesion were the predominant gene pathways associated with both SH and SP. This study suggests genes associated with innervation may be important in scar fibrosis. Further studies using similar and larger datasets will be essential to validate these findings.
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Affiliation(s)
- Hilary J Wallace
- Burn Injury Research Unit, School of Biomedical Sciences, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia; School of Medicine, The University of Notre Dame Australia, Fremantle, Australia.
| | - Gemma Cadby
- Centre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia and Faculty of Health Science, Curtin University, Perth, Australia
| | - Phillip E Melton
- Centre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia and Faculty of Health Science, Curtin University, Perth, Australia; School of Pharmacy and Biomedical Sciences, Faculty of Health Science, Curtin University, Perth, Australia
| | - Fiona M Wood
- Burn Injury Research Unit, School of Biomedical Sciences, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia; Burns Service of Western Australia, Princess Margaret Hospital for Children and Fiona Stanley Hospital, Perth, Australia
| | - Sian Falder
- Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Margaret M Crowe
- Burns Service of Western Australia, Princess Margaret Hospital for Children and Fiona Stanley Hospital, Perth, Australia
| | - Lisa J Martin
- Burns Service of Western Australia, Princess Margaret Hospital for Children and Fiona Stanley Hospital, Perth, Australia
| | - Karen Marlow
- Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Sarah V Ward
- Centre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia and Faculty of Health Science, Curtin University, Perth, Australia
| | - Mark W Fear
- Burn Injury Research Unit, School of Biomedical Sciences, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia
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95
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Lehnert H, Serfling A, Friedt W, Ordon F. Genome-Wide Association Studies Reveal Genomic Regions Associated With the Response of Wheat ( Triticum aestivum L.) to Mycorrhizae Under Drought Stress Conditions. FRONTIERS IN PLANT SCIENCE 2018; 9:1728. [PMID: 30568663 PMCID: PMC6290350 DOI: 10.3389/fpls.2018.01728] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 11/07/2018] [Indexed: 05/06/2023]
Abstract
In the majority of wheat growing areas worldwide, the incidence of drought stress has increased significantly resulting in a negative impact on plant development and grain yield. Arbuscular mycorrhizal symbiosis is known to improve drought stress tolerance of wheat. However, quantitative trait loci (QTL) involved in the response to drought stress conditions in the presence of mycorrhizae are largely unknown. Therefore, a diverse set consisting of 94 bread wheat genotypes was phenotyped under drought stress and well watered conditions in the presence and absence of mycorrhizae. Grain yield and yield components, drought stress related traits as well as response to mycorrhizae were assessed. In parallel, wheat accessions were genotyped by using the 90k iSelect chip, resulting in a set of 15511 polymorphic and mapped SNP markers, which were used for genome-wide association studies (GWAS). In general, drought stress tolerance of wheat was significantly increased in the presence of mycorrhizae compared to drought stress tolerance in the absence of mycorrhizae. However, genotypes differed in their response to mycorrhizae under drought stress conditions. Several QTL regions on different chromosomes were detected associated with grain yield and yield components under drought stress conditions. Furthermore, two genome regions on chromosomes 3D and 7D were found to be significantly associated with the response to mycorrhizae under drought stress conditions. Overall, the results reveal that inoculation of wheat with mycorrhizal fungi significantly improves drought stress tolerance and that QTL regions associated with the response to mycorrhizae under drought stress conditions exist in wheat. Further research is necessary to validate detected QTL regions. However, this study may be the starting point for the identification of candidate genes associated with drought stress tolerance and response to mycorrhizae under drought stress conditions. Maybe in future, these initial results will help to contribute to use mycorrhizal fungi effectively in agriculture and combine new approaches i.e., use of genotypic variation in response to mycorrhizae under drought stress conditions with existing drought tolerance breeding programs to develop new drought stress tolerant genotypes.
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Affiliation(s)
- Heike Lehnert
- Institute of Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Julius Kühn-Institute (JKI), Quedlinburg, Germany
| | - Albrecht Serfling
- Institute of Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Julius Kühn-Institute (JKI), Quedlinburg, Germany
| | - Wolfgang Friedt
- IFZ Research Centre for Biosystems, Land Use and Nutrition, Plant Breeding Department, Justus Liebig University, Gießen, Germany
| | - Frank Ordon
- Institute of Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Julius Kühn-Institute (JKI), Quedlinburg, Germany
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96
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Wang J, Yuan X, Ye S, Huang S, He Y, Zhang H, Li J, Zhang X, Zhang Z. Genome wide association study on feed conversion ratio using imputed sequence data in chickens. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2018; 32:494-500. [PMID: 30381748 PMCID: PMC6409457 DOI: 10.5713/ajas.18.0319] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 09/20/2018] [Indexed: 01/11/2023]
Abstract
Objective Feed consumption contributes a large percentage for total production costs in the poultry industry. Detecting genes associated with feeding traits will be of benefit to improve our understanding of the molecular determinants for feed efficiency. The objective of this study was to identify candidate genes associated with feed conversion ratio (FCR) via genome-wide association study (GWAS) using sequence data imputed from single nucleotide polymorphism (SNP) panel in a Chinese indigenous chicken population. Methods A total of 435 Chinese indigenous chickens were phenotyped for FCR and were genotyped using a 600K SNP genotyping array. Twenty-four birds were selected for sequencing, and the 600K SNP panel data were imputed to whole sequence data with the 24 birds as the reference. The GWAS were performed with GEMMA software. Results After quality control, 8,626,020 SNPs were used for sequence based GWAS, in which ten significant genomic regions were detected to be associated with FCR. Ten candidate genes, ubiquitin specific peptidase 44, leukotriene A4 hydrolase, ETS transcription factor, R-spondin 2, inhibitor of apoptosis protein 3, sosondowah ankyrin repeat domain family member D, calmodulin regulated spectrin associated protein family member 2, zinc finger and BTB domain containing 41, potassium sodium-activated channel subfamily T member 2, and member of RAS oncogene family were annotated. Several of them were within or near the reported FCR quantitative trait loci, and others were newly reported. Conclusion Results from this study provide valuable prior information on chicken genomic breeding programs, and potentially improve our understanding of the molecular mechanism for feeding traits.
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Affiliation(s)
- Jiaying Wang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Xiaolong Yuan
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Shaopan Ye
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Shuwen Huang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yingting He
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Hao Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jiaqi Li
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Xiquan Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
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97
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Yan G, Guo T, Xiao S, Zhang F, Xin W, Huang T, Xu W, Li Y, Zhang Z, Huang L. Imputation-Based Whole-Genome Sequence Association Study Reveals Constant and Novel Loci for Hematological Traits in a Large-Scale Swine F 2 Resource Population. Front Genet 2018; 9:401. [PMID: 30405681 PMCID: PMC6204663 DOI: 10.3389/fgene.2018.00401] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Accepted: 09/03/2018] [Indexed: 11/13/2022] Open
Abstract
The whole-genome sequences of progenies with low-density single-nucleotide polymorphism (SNP) genotypes can be imputed with high accuracy based on the deep-coverage sequences of key ancestors. With this imputation technology, a more powerful genome-wide association study (GWAS) can be carried out using imputed whole-genome variants and the phenotypes of interest to overcome the shortcomings of low-power detection and the large confidence interval derived from low-density SNP markers in classic association studies. In this study, 19 ancestors of a large-scale swine F2 White Duroc × Erhualian population were deeply sequenced for their genome with an average coverage of 25×. Considering 98 pigs from 10 different breeds with high-quality deep sequenced genomes, we imputed the whole genomic variants of 1020 F2 pigs genotyped by the PorcineSNP60 BeadChip with high accuracy and obtained 14,851,440 sequence variants after quality control. Based on this, 87 novel quantitative traits loci (QTLs) for 18 hematological traits at three different physiological stages of the F2 pigs were identified, among which most of the novel QTLs have been repeated in two of the three stages. Literature mining pinpointed that the FGF14 and LCLAT1 genes at SSC11 and SSC3 may affect the MCH at day 240 and MCV at day 18, respectively. The present study shows that combining high-quality imputed genomic variants and correlated phenomic traits into GWAS can improve the capability to detect QTL considerably. The large number of different QTLs for hematological traits identified at multiple growth stages implies the complexity and time specificity of these traits.
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Affiliation(s)
- Guorong Yan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Tianfu Guo
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Feng Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Wenshui Xin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Tao Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Wenwu Xu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Yiping Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Zhiyan Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China
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98
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Cui Z, Xia A, Zhang A, Luo J, Yang X, Zhang L, Ruan Y, He Y. Linkage mapping combined with association analysis reveals QTL and candidate genes for three husk traits in maize. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:2131-2144. [PMID: 30043259 DOI: 10.1007/s00122-018-3142-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Accepted: 06/28/2018] [Indexed: 06/08/2023]
Abstract
Key message Combined linkage and association mapping analyses facilitate the emphasis on the candidate genes putatively involved in maize husk growth. The maize (Zea mays L.) husk consists of multiple leafy layers and plays important roles in protecting the ear from pathogen infection and in preventing grain dehydration. Although husk morphology varies widely among different maize inbred lines, the genetic basis of such variation is poorly understood. In this study, we used three maize recombinant inbred line (RIL) populations to dissect the genetic basis of three husk traits: i.e., husk length (HL), husk width (HW), and the number of husk layers (HN). Three husk traits in all three RIL populations showed wide phenotypic variation and high heritability. The HL showed stronger correlations with ear traits than did HW and HN. A total of 21 quantitative trait loci (QTL) were identified for the three traits in three RIL populations, and some of them were commonly observed for the same trait in different populations. The proportions of total phenotypic variation explained by QTL in three RIL populations were 31.8, 35.3, and 44.5% for HL, HW, and HN, respectively. The highest proportions of phenotypic variation explained by a single QTL were 14.7% for HL in the By815/K22 RIL population (BYK), 13.5% for HW in the By815/DE3 RIL population (BYD), and 19.4% for HN in the BYD population. A combined analysis of linkage mapping with a previous genome-wide association study revealed five candidate genes related to husk morphology situated within three QTL loci. These five genes were related to metabolism, gene expression regulation, and signal transduction.
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Affiliation(s)
- Zhenhai Cui
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Aiai Xia
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Ao Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Jinhong Luo
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Xiaohong Yang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Lijun Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Yanye Ruan
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
| | - Yan He
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China.
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99
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Zhou Z, Chen L, Dong C, Peng W, Kong S, Sun J, Pu F, Chen B, Feng J, Xu P. Genome-Scale Association Study of Abnormal Scale Pattern in Yellow River Carp Identified Previously Known Causative Gene in European Mirror Carp. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2018; 20:573-583. [PMID: 29882019 DOI: 10.1007/s10126-018-9827-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2017] [Accepted: 04/04/2018] [Indexed: 06/08/2023]
Abstract
Common carp (Cyprinus carpio) is one of the most widely studied fish species due to its great economic value and strong environmental adaptability. Scattered scale, a typical phenotype of the mirror carp that is derived from Europe, has never been observed in the Yellow River carp previously. We recently identified approximately one fourth of the F1 progenies displaying scattered scale in a full-sib Yellow River carp family in our breeding program, despite both parents that showed wild type with normal scale patterns. This family provides us unique materials to investigate the genetic basis underlying the abnormal scale mutant in Yellow River carp population. Genome-wide association study (GWAS) and association mapping were performed based on genome-wide single nucleotide polymorphisms (SNP) genotyped with common carp 250 K SNP genotyping array in 82 samples of the Yellow River carp family. We identified a 1.4 Mb genome region that was significantly associated with abnormal scattered scale patterns. We further identified a deletion mutation in fibroblast growth factor receptor 1 a1 (fgfr1a1) gene within this genome region. Amplification and sequencing analysis of this gene revealed a 311-bp deletion in intron 10 and exon 11, which proved that fgfr1a1 could be the causal gene responsible for abnormal scattered scale in the Yellow River carp family. Since similar fragment mutation with 306-bp and 310-bp deletions had been previously reported as causal mutation of scattered scale patterns in the mirror carp, we speculate that either the deletion mutation was introduced from Europe-derived mirror carp or the deletion independently occurred in the mutation hotspot in fgfr1a1 gene. The results provided insights into the genetic basis of scale pattern mutant in Yellow River carp population, which would help us to eliminate the recessive allele of the abnormal scale patterns in Yellow River carp population by molecular marker-assisted breeding.
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Affiliation(s)
- Zhixiong Zhou
- College of Life Sciences, Tianjin Normal University, Tianjin, 300387, China
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China
| | - Lin Chen
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China
- College of Fishery, Henan Normal University, Xinxiang, 453007, Henan, China
| | - Chuanju Dong
- College of Fishery, Henan Normal University, Xinxiang, 453007, Henan, China
| | - Wenzhu Peng
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China
| | - Shengnan Kong
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China
- College of Fishery, Henan Normal University, Xinxiang, 453007, Henan, China
| | - Jinsheng Sun
- College of Life Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Fei Pu
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China
| | - Baohua Chen
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China
- CAFS Key Laboratory of Aquatic Genomics and Beijing Key Laboratory of Fishery Biotechnology, Centre for Applied Aquatic Genomics, Chinese Academy of Fishery Sciences, Beijing, 100141, China
| | - Jianxin Feng
- Henan Academy of Fishery Science, Zhengzhou, 450044, China
| | - Peng Xu
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China.
- CAFS Key Laboratory of Aquatic Genomics and Beijing Key Laboratory of Fishery Biotechnology, Centre for Applied Aquatic Genomics, Chinese Academy of Fishery Sciences, Beijing, 100141, China.
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266071, China.
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100
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Pearce E, Wlodarski R, Machin A, Dunbar RIM. The Influence of Genetic Variation on Social Disposition, Romantic Relationships and Social Networks: a Replication Study. ADAPTIVE HUMAN BEHAVIOR AND PHYSIOLOGY 2018; 4:400-422. [PMID: 30393594 PMCID: PMC6190642 DOI: 10.1007/s40750-018-0101-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 08/02/2018] [Accepted: 08/06/2018] [Indexed: 12/31/2022]
Abstract
OBJECTIVES Sociality is underpinned by a variety of neurochemicals. We previously showed, in a large healthy Caucasian sample, that genes for different neurochemicals are typically associated with differing social domains (disposition, romantic relationships and networks). Here we seek to confirm the validity of these findings by asking whether they replicate in other population samples. METHODS We test for associations between the same 24 Single Nucleotide Polymorphisms (SNPs) and measures of sociality as previously, in two smaller independent samples: Caucasian individuals with histories of mental illness (subclinical sample) (N = 140), and non-Caucasian individuals (N = 66). We also combined the relevant SNPs and social measures into 18 distinct neurochemical/social domain categories to examine the distribution of significant associations across these. RESULTS In the subclinical Caucasian sample, we confirm previous associations between (i) specific oxytocin and dopamine receptor gene SNPs and sexual attitudes and behavior, and (ii) two SNPs associated with dopamine receptor 2 and feelings of inclusion in the local community. In the non-Caucasian sample, we replicate the previous association between an oxytocin receptor SNP and anxious attachment. More generally, chi-squared tests indicated that the distribution of significant associations for each neurochemical across the three social domains did not differ significantly between the original sample and either of the new samples, except for oxytocin in the non-Caucasian sample. CONCLUSIONS These results corroborate both the SNP-specific and broader neurochemical associations with particular facets of sociality in two new populations, thereby confirming the validity of the previous findings.
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Affiliation(s)
- Eiluned Pearce
- Social & Evolutionary Neuroscience Research Group, Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory, Woodstock Rd, Quarter, Oxford, OX2 6GG UK
| | - Rafael Wlodarski
- Social & Evolutionary Neuroscience Research Group, Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory, Woodstock Rd, Quarter, Oxford, OX2 6GG UK
| | - Anna Machin
- Social & Evolutionary Neuroscience Research Group, Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory, Woodstock Rd, Quarter, Oxford, OX2 6GG UK
| | - Robin I. M. Dunbar
- Social & Evolutionary Neuroscience Research Group, Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory, Woodstock Rd, Quarter, Oxford, OX2 6GG UK
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