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Fernández-Barroso MÁ, García-Casco JM, Núñez Y, Ramírez-Hidalgo L, Matos G, Muñoz M. Understanding the role of myoglobin content in Iberian pigs fattened in an extensive system through analysis of the transcriptome profile. Anim Genet 2022; 53:352-367. [PMID: 35355298 PMCID: PMC9314091 DOI: 10.1111/age.13195] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 01/31/2022] [Accepted: 03/11/2022] [Indexed: 11/30/2022]
Abstract
Meat color is the first perceived sensory feature and one of the most important quality traits. Myoglobin is the main pigment in meat, giving meat its characteristic cherry‐red color, highly appreciated by the consumers. In the current study, we used the RNA‐seq technique to characterize the longissimus dorsi muscle transcriptome in two groups of Iberian pigs with divergent breeding values for myoglobin content. As a result, we identified 57 differentially expressed genes and transcripts (DEGs). Moreover, we have validated the RNA‐seq expression of a set of genes by quantitative PCR (qPCR). Functional analyses revealed an enrichment of DEGs in biological processes related to oxidation (HBA1), lipid metabolism (ECH1, PLA2G10, PLD2), inflammation (CHST1, CD209, PLA2G10), and immune system (CD209, MX2, LGALS3, LGALS9). The upstream analysis showed a total of five transcriptional regulatory factors and eight master regulators that could moderate the expression of some DEGs, highlighting SPI1 and MAPK1, since they regulate the expression of DEGs involved in immune defense and inflammatory processes. Iberian pigs with high myoglobin content also showed higher expression of the HBA1 gene and both molecules, myoglobin and hemoglobin, have been described as having a protective effect against oxidative and inflammatory processes. Therefore, the HBA1 gene is a very promising candidate gene to harbor polymorphisms underlying myoglobin content, whereby further studies should be carried out for its potential use in an Iberian pig selection program.
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Affiliation(s)
- Miguel Ángel Fernández-Barroso
- Centro Nacional de I+D del Cerdo Ibérico, INIA-CSIC, Zafra, Spain.,Departamento de Mejora Genética Animal, INIA-CSIC, Madrid, Spain
| | - Juan María García-Casco
- Centro Nacional de I+D del Cerdo Ibérico, INIA-CSIC, Zafra, Spain.,Departamento de Mejora Genética Animal, INIA-CSIC, Madrid, Spain
| | - Yolanda Núñez
- Departamento de Mejora Genética Animal, INIA-CSIC, Madrid, Spain
| | | | - Gema Matos
- Sánchez Romero Carvajal-Jabugo, SRC, Huelva, Spain
| | - María Muñoz
- Departamento de Mejora Genética Animal, INIA-CSIC, Madrid, Spain
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Li J, Peng S, Zhong L, Zhou L, Yan G, Xiao S, Ma J, Huang L. Identification and validation of a regulatory mutation upstream of the BMP2 gene associated with carcass length in pigs. Genet Sel Evol 2021; 53:94. [PMID: 34906088 PMCID: PMC8670072 DOI: 10.1186/s12711-021-00689-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 12/01/2021] [Indexed: 11/10/2022] Open
Abstract
Background Carcass length is very important for body size and meat production for swine, thus understanding the genetic mechanisms that underly this trait is of great significance in genetic improvement programs for pigs. Although many quantitative trait loci (QTL) have been detected in pigs, very few have been fine-mapped to the level of the causal mutations. The aim of this study was to identify potential causal single nucleotide polymorphisms (SNPs) for carcass length by integrating a genome-wide association study (GWAS) and functional assays. Results Here, we present a GWAS in a commercial Duroc × (Landrace × Yorkshire) (DLY) population that reveals a prominent association signal (P = 4.49E−07) on pig chromosome 17 for carcass length, which was further validated in two other DLY populations. Within the detected 1 Mb region, the BMP2 gene stood out as the most likely causal candidate because of its functions in bone growth and development. Whole-genome gene expression studies showed that the BMP2 gene was differentially expressed in the cartilage tissues of pigs with extreme carcass length. Then, we genotyped an additional 267 SNPs in 500 selected DLY pigs, followed by further whole-genome SNP imputation, combined with deep genome resequencing data on multiple pig breeds. Reassociation analyses using genotyped and imputed SNP data revealed that the rs320706814 SNP, located approximately 123 kb upstream of the BMP2 gene, was the strongest candidate causal mutation, with a large association with carcass length, with a ~ 4.2 cm difference in length across all three DLY populations (N = 1501; P = 3.66E−29). This SNP segregated in all parental lines of the DLY (Duroc, Large White and Landrace) and was also associated with a significant effect on body length in 299 pure Yorkshire pigs (P = 9.2E−4), which indicates that it has a major value for commercial breeding. Functional assays showed that this SNP is likely located within an enhancer and may affect the binding affinity of transcription factors, thereby regulating BMP2 gene expression. Conclusions Taken together, these results suggest that the rs320706814 SNP on pig chromosome 17 is a putative causal mutation for carcass length in the widely used DLY pigs and has great value in breeding for body size in pigs. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00689-0.
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Affiliation(s)
- Jing Li
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Song Peng
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Liepeng Zhong
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lisheng Zhou
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Guorong Yan
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Shijun Xiao
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Junwu Ma
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
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Jiang J, Cao Y, Shan H, Wu J, Song X, Jiang Y. The GWAS Analysis of Body Size and Population Verification of Related SNPs in Hu Sheep. Front Genet 2021; 12:642552. [PMID: 34093644 PMCID: PMC8173124 DOI: 10.3389/fgene.2021.642552] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 04/20/2021] [Indexed: 12/03/2022] Open
Abstract
Body size is an important indicator of growth and health in sheep. In the present study, we performed Genome-Wide Association Studies (GWAS) to detect significant single-nucleotide polymorphisms (SNPs) associated with Hu sheep's body size. After genotyping parental (G1) and offspring (G2) generation of the nucleus herd for meat production of Hu sheep and conducting GWAS on the body height, chest circumference, body length, tail length, and tail width of the two groups, 5 SNPs associated with body height and 4 SNPs correlated with chest circumference were identified at the chromosomal significance level. No SNPs were significantly correlated to body length, tail length, and width. Four out of the 9 SNPs were found to be located within the 4 genes. KITLG and CADM2 are considered as candidate functional genes related to body height; MCTP1 and COL4A6 are candidate functional genes related to chest circumference. The 9 SNPs found in GWAS were verified using the G3 generation of the nucleus herd for meat production. Nine products were amplified around the 9 sites, and 29 SNPs were found; 3 mutation sites, G > C mutation at 134 bp downstream of s554331, T > G mutation at 19 bp upstream of s26859.1, and A > G mutation at 81 bp downstream of s26859.1, were significantly correlated to the body height. Dual-luciferase reporter gene experiments showed that the 3 SNPs could significantly impact dual-luciferase and gene transcription activity.
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Affiliation(s)
- Junfang Jiang
- Institute of Animal Husbandry and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Yuhao Cao
- Zhejiang Key Laboratory of Pathophysiology, Department of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, China
| | - Huili Shan
- Institute of Animal Husbandry and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Jianliang Wu
- Institute of Animal Husbandry and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Xuemei Song
- Zhejiang Key Laboratory of Pathophysiology, Department of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, China
| | - Yongqing Jiang
- Institute of Animal Husbandry and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
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Genome-wide association study reveals the genetic determinism of growth traits in a Gushi-Anka F 2 chicken population. Heredity (Edinb) 2020; 126:293-307. [PMID: 32989280 PMCID: PMC8026619 DOI: 10.1038/s41437-020-00365-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 08/18/2020] [Accepted: 08/30/2020] [Indexed: 02/07/2023] Open
Abstract
Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F2 resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1-6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.
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Raymond B, Yengo L, Costilla R, Schrooten C, Bouwman AC, Hayes BJ, Veerkamp RF, Visscher PM. Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock. PLoS Genet 2020; 16:e1008780. [PMID: 32925905 PMCID: PMC7514049 DOI: 10.1371/journal.pgen.1008780] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 09/24/2020] [Accepted: 07/21/2020] [Indexed: 01/13/2023] Open
Abstract
Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.
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Affiliation(s)
- Biaty Raymond
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Biometris, Wageningen University and Research, Wageningen, The Netherlands
- * E-mail:
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, St. Lucia, Australia
| | - Roy Costilla
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, Australia
| | | | - Aniek C. Bouwman
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Ben J. Hayes
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, Australia
| | - Roel F. Veerkamp
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Peter M. Visscher
- Institute for Molecular Bioscience, University of Queensland, St. Lucia, Australia
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Ghoreishifar SM, Eriksson S, Johansson AM, Khansefid M, Moghaddaszadeh-Ahrabi S, Parna N, Davoudi P, Javanmard A. Signatures of selection reveal candidate genes involved in economic traits and cold acclimation in five Swedish cattle breeds. Genet Sel Evol 2020; 52:52. [PMID: 32887549 PMCID: PMC7487911 DOI: 10.1186/s12711-020-00571-5] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 08/21/2020] [Indexed: 02/01/2023] Open
Abstract
Background Thousands of years of natural and artificial selection have resulted in indigenous cattle breeds that are well-adapted to the environmental challenges of their local habitat and thereby are considered as valuable genetic resources. Understanding the genetic background of such adaptation processes can help us design effective breeding objectives to preserve local breeds and improve commercial cattle. To identify regions under putative selection, GGP HD 150 K single nucleotide polymorphism (SNP) arrays were used to genotype 106 individuals representing five Swedish breeds i.e. native to different regions and covering areas with a subarctic cold climate in the north and mountainous west, to those with a continental climate in the more densely populated south regions. Results Five statistics were incorporated within a framework, known as de-correlated composite of multiple signals (DCMS) to detect signatures of selection. The obtained p-values were adjusted for multiple testing (FDR < 5%), and significant genomic regions were identified. Annotation of genes in these regions revealed various verified and novel candidate genes that are associated with a diverse range of traits, including e.g. high altitude adaptation and response to hypoxia (DCAF8, PPP1R12A, SLC16A3, UCP2, UCP3, TIGAR), cold acclimation (AQP3, AQP7, HSPB8), body size and stature (PLAG1, KCNA6, NDUFA9, AKAP3, C5H12orf4, RAD51AP1, FGF6, TIGAR, CCND2, CSMD3), resistance to disease and bacterial infection (CHI3L2, GBP6, PPFIBP1, REP15, CYP4F2, TIGD2, PYURF, SLC10A2, FCHSD2, ARHGEF17, RELT, PRDM2, KDM5B), reproduction (PPP1R12A, ZFP36L2, CSPP1), milk yield and components (NPC1L1, NUDCD3, ACSS1, FCHSD2), growth and feed efficiency (TMEM68, TGS1, LYN, XKR4, FOXA2, GBP2, GBP5, FGD6), and polled phenotype (URB1, EVA1C). Conclusions We identified genomic regions that may provide background knowledge to understand the mechanisms that are involved in economic traits and adaptation to cold climate in cattle. Incorporating p-values of different statistics in a single DCMS framework may help select and prioritize candidate genes for further analyses.
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Affiliation(s)
- Seyed Mohammad Ghoreishifar
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Susanne Eriksson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, SE-75007, Uppsala, Sweden.
| | - Anna M Johansson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, SE-75007, Uppsala, Sweden
| | - Majid Khansefid
- AgriBio Centre for AgriBioscience, Agriculture Victoria, Bundoora, VIC, 3083, Australia
| | - Sima Moghaddaszadeh-Ahrabi
- Department of Animal Science, Faculty of Agriculture and Natural Resources, Islamic Azad University, Tabriz Branch, Tabriz, Iran
| | - Nahid Parna
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N5E3, Canada
| | - Arash Javanmard
- Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
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Costilla R, Kemper KE, Byrne EM, Porto-Neto LR, Carvalheiro R, Purfield DC, Doyle JL, Berry DP, Moore SS, Wray NR, Hayes BJ. Genetic control of temperament traits across species: association of autism spectrum disorder risk genes with cattle temperament. Genet Sel Evol 2020; 52:51. [PMID: 32842956 PMCID: PMC7448488 DOI: 10.1186/s12711-020-00569-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 08/07/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Temperament traits are of high importance across species. In humans, temperament or personality traits correlate with psychological traits and psychiatric disorders. In cattle, they impact animal welfare, product quality and human safety, and are therefore of direct commercial importance. We hypothesized that genetic factors that contribute to variation in temperament among individuals within a species will be shared between humans and cattle. Using imputed whole-genome sequence data from 9223 beef cattle from three cohorts, a series of genome-wide association studies was undertaken on cattle flight time, a temperament phenotype measured as the time taken for an animal to cover a short-fixed distance after release from an enclosure. We also investigated the association of cattle temperament with polymorphisms in bovine orthologs of risk genes for neuroticism, schizophrenia, autism spectrum disorders (ASD), and developmental delay disorders in humans. RESULTS Variants with the strongest associations were located in the bovine orthologous region that is involved in several behavioural and cognitive disorders in humans. These variants were also partially validated in independent cattle cohorts. Genes in these regions (BARHL2, NDN, SNRPN, MAGEL2, ABCA12, KIFAP3, TOPAZ1, FZD3, UBE3A, and GABRA5) were enriched for the GO term neuron migration and were differentially expressed in brain and pituitary tissues in humans. Moreover, variants within 100 kb of ASD susceptibility genes were associated with cattle temperament and explained 6.5% of the total additive genetic variance in the largest cattle cohort. The ASD genes with the most significant associations were GABRB3 and CUL3. Using the same 100 kb window, a weak association was found with polymorphisms in schizophrenia risk genes and no association with polymorphisms in neuroticism and developmental delay disorders risk genes. CONCLUSIONS Our analysis showed that genes identified in a meta-analysis of cattle temperament contribute to neuron development functions and are differentially expressed in human brain tissues. Furthermore, some ASD susceptibility genes are associated with cattle temperament. These findings provide evidence that genetic control of temperament might be shared between humans and cattle and highlight the potential for future analyses to leverage results between species.
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Affiliation(s)
- Roy Costilla
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
| | - Kathryn E. Kemper
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Enda M. Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Laercio R. Porto-Neto
- Commonwealth Scientific and Industrial Research Organization (CSIRO), Agriculture and Food, Brisbane, Australia
| | - Roberto Carvalheiro
- School of Agricultural and Veterinarian Sciences, Sao Paulo State University, Sao Paolo, Brazil
| | | | - Jennifer L. Doyle
- Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork Ireland
| | - Donagh P. Berry
- Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork Ireland
| | - Stephen S. Moore
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Ben J. Hayes
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
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Senczuk G, Guerra L, Mastrangelo S, Campobasso C, Zoubeyda K, Imane M, Marletta D, Kusza S, Karsli T, Gaouar SBS, Pilla F, Ciani E. Fifteen Shades of Grey: Combined Analysis of Genome-Wide SNP Data in Steppe and Mediterranean Grey Cattle Sheds New Light on the Molecular Basis of Coat Color. Genes (Basel) 2020; 11:genes11080932. [PMID: 32823527 PMCID: PMC7464420 DOI: 10.3390/genes11080932] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/02/2020] [Accepted: 07/07/2020] [Indexed: 12/20/2022] Open
Abstract
Coat color is among the most distinctive phenotypes in cattle. Worldwide, several breeds share peculiar coat color features such as the presence of a fawn pigmentation of the calf at birth, turning over time to grey, and sexual dichromatism. The aim of this study was to search for polymorphisms under differential selection by contrasting grey cattle breeds displaying the above phenotype with non-grey cattle breeds, and to identify the underlying genes. Using medium-density SNP array genotype data, a multi-cohort FST-outlier approach was adopted for a total of 60 pair-wise comparisons of the 15 grey with 4 non-grey cattle breeds (Angus, Limousin, Charolais, and Holstein), with the latter selected as representative of solid and piebald phenotypes, respectively. Overall, more than 50 candidate genes were detected; almost all were either directly or indirectly involved in pigmentation, and some of them were already known for their role in phenotypes related with hair graying in mammals. Notably, 17 relevant genes, including SDR16C5, MOS, SDCBP, and NSMAF, were located in a signal on BTA14 convergently observed in all the four considered scenarios. Overall, the key stages of pigmentation (melanocyte development, melanogenesis, and pigment trafficking/transfer) were all represented among the pleiotropic functions of the candidate genes, suggesting the complex nature of the grey phenotype in cattle.
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Affiliation(s)
- Gabriele Senczuk
- Dipartimento di Agricoltura, Ambiente e Alimenti, University of Molise, 86100 Campobasso, Italy; (G.S.); (F.P.)
| | - Lorenzo Guerra
- Dipartimento di Bioscienze, Biotecnologie e Biofarmaceutica, University of Bari, 70125 Bari, Italy; (L.G.); (C.C.)
| | - Salvatore Mastrangelo
- Dipartimento di Scienze Agrarie, Alimentari e Forestali, University of Palermo, 90128 Palermo, Italy;
| | - Claudia Campobasso
- Dipartimento di Bioscienze, Biotecnologie e Biofarmaceutica, University of Bari, 70125 Bari, Italy; (L.G.); (C.C.)
| | - Kaouadji Zoubeyda
- Department of Biology, University Abou Bekr Bélkaid, Tlemcen 13000, Algeria; (K.Z.); (M.I.); (S.B.S.G.)
| | - Meghelli Imane
- Department of Biology, University Abou Bekr Bélkaid, Tlemcen 13000, Algeria; (K.Z.); (M.I.); (S.B.S.G.)
| | - Donata Marletta
- Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, 95123 Catania, Italy;
| | - Szilvia Kusza
- Animal Genetics Laboratory, University of Debrecen, 4032 Debrecen, Hungary;
| | - Taki Karsli
- Department of Animal Science, Akdeniz University, 07070 Antalya, Turkey;
| | | | - Fabio Pilla
- Dipartimento di Agricoltura, Ambiente e Alimenti, University of Molise, 86100 Campobasso, Italy; (G.S.); (F.P.)
| | - Elena Ciani
- Dipartimento di Bioscienze, Biotecnologie e Biofarmaceutica, University of Bari, 70125 Bari, Italy; (L.G.); (C.C.)
- Correspondence:
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Gagnon M, Yannic G, Boyer F, Côté SD. Adult survival in migratory caribou is negatively associated with MHC functional diversity. Heredity (Edinb) 2020; 125:290-303. [PMID: 32728043 DOI: 10.1038/s41437-020-0347-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 07/04/2020] [Accepted: 07/16/2020] [Indexed: 11/09/2022] Open
Abstract
Genes of the major histocompatibility complex (MHC) are involved in acquired immunity in vertebrates. Only a few studies have investigated the fitness consequences of MHC gene diversity in wild populations. Here, we looked at the association between annual survival and body mass and MHC-DRB exon 2 (MHC-DRB) genetic diversity, obtained from high-throughput sequencing, in two declining migratory caribou (Rangifer tarandus) herds. To disentangle the potential direct and general effects of MHC-DRB genetic diversity, we compared different indices of diversity that were either based on DNA-sequence variation or on physicochemical divergence of the translated peptides, thereby covering a gradient of allelic-to-functional diversity. We found that (1) body mass was not related to MHC-DRB diversity or genotype, and (2) adult survival probability was negatively associated with point accepted mutation distance, a corrected distance that considers the likelihood of each amino acid substitution to be accepted by natural selection. In addition, we found no evidence of fluctuating selection over time on MHC-DRB diversity. We concluded that direct effects were involved in the negative relationship between MHC functional diversity and survival, although the mechanism underlying this result remains unclear. A possible explanation could be that individuals with higher MHC diversity suffer higher costs of immunity (immunopathology). Our results suggest that genetic diversity is not always beneficial even in genes that are likely to be strongly shaped by balancing selection.
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Affiliation(s)
- Marianne Gagnon
- Département de Biologie, Caribou Ungava and Centre d'Études Nordiques, Université Laval, 1045 avenue de la Médecine, Quebec City, QC, G1V 0A6, Canada
| | - Glenn Yannic
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, 38000, Grenoble, France.
| | - Frédéric Boyer
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, 38000, Grenoble, France
| | - Steeve D Côté
- Département de Biologie, Caribou Ungava and Centre d'Études Nordiques, Université Laval, 1045 avenue de la Médecine, Quebec City, QC, G1V 0A6, Canada
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Liu S, Yu Y, Zhang S, Cole JB, Tenesa A, Wang T, McDaneld TG, Ma L, Liu GE, Fang L. Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human. BMC Biol 2020; 18:80. [PMID: 32620158 PMCID: PMC7334855 DOI: 10.1186/s12915-020-00792-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 05/12/2020] [Indexed: 02/01/2023] Open
Abstract
Background Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle. Results We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle. Conclusion Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.
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Affiliation(s)
- Shuli Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA.,College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ying Yu
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Shengli Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA
| | - Albert Tenesa
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,The Roslin Institute, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Tara G McDaneld
- US Meat Animal Research Center, Agricultural Research Service, USDA, Clay Center, NE, 68933, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA.
| | - Lingzhao Fang
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, BARC-East, Beltsville, MD, 20705, USA. .,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. .,Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
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11
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Chen Q, Samayoa LF, Yang CJ, Bradbury PJ, Olukolu BA, Neumeyer MA, Romay MC, Sun Q, Lorant A, Buckler ES, Ross-Ibarra J, Holland JB, Doebley JF. The genetic architecture of the maize progenitor, teosinte, and how it was altered during maize domestication. PLoS Genet 2020; 16:e1008791. [PMID: 32407310 PMCID: PMC7266358 DOI: 10.1371/journal.pgen.1008791] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 06/02/2020] [Accepted: 04/22/2020] [Indexed: 11/19/2022] Open
Abstract
The genetics of domestication has been extensively studied ever since the rediscovery of Mendel's law of inheritance and much has been learned about the genetic control of trait differences between crops and their ancestors. Here, we ask how domestication has altered genetic architecture by comparing the genetic architecture of 18 domestication traits in maize and its ancestor teosinte using matched populations. We observed a strongly reduced number of QTL for domestication traits in maize relative to teosinte, which is consistent with the previously reported depletion of additive variance by selection during domestication. We also observed more dominance in maize than teosinte, likely a consequence of selective removal of additive variants. We observed that large effect QTL have low minor allele frequency (MAF) in both maize and teosinte. Regions of the genome that are strongly differentiated between teosinte and maize (high FST) explain less quantitative variation in maize than teosinte, suggesting that, in these regions, allelic variants were brought to (or near) fixation during domestication. We also observed that genomic regions of high recombination explain a disproportionately large proportion of heritable variance both before and after domestication. Finally, we observed that about 75% of the additive variance in both teosinte and maize is "missing" in the sense that it cannot be ascribed to detectable QTL and only 25% of variance maps to specific QTL. This latter result suggests that morphological evolution during domestication is largely attributable to very large numbers of QTL of very small effect.
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Affiliation(s)
- Qiuyue Chen
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Luis Fernando Samayoa
- Department of Crop Science, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Chin Jian Yang
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Peter J. Bradbury
- US Department of Agriculture–Agricultural Research Service, Cornell University, Ithaca, New York, United States of America
| | - Bode A. Olukolu
- Department of Entomology and Plant Pathology, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Michael A. Neumeyer
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Maria Cinta Romay
- Genomic Diversity Facility, Cornell University, Ithaca, New York, United States of America
| | - Qi Sun
- Genomic Diversity Facility, Cornell University, Ithaca, New York, United States of America
| | - Anne Lorant
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
| | - Edward S. Buckler
- US Department of Agriculture–Agricultural Research Service, Cornell University, Ithaca, New York, United States of America
| | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
| | - James B. Holland
- Department of Crop Science, North Carolina State University, Raleigh, North Carolina, United States of America
- US Department of Agriculture–Agricultural Research Service Plant Science Research Unit, North Carolina State University, Raleigh, North Carolina, United States of America
| | - John F. Doebley
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
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12
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Saif R, Henkel J, Jagannathan V, Drögemüller C, Flury C, Leeb T. The LCORL Locus is under Selection in Large-Sized Pakistani Goat Breeds. Genes (Basel) 2020; 11:genes11020168. [PMID: 32033434 PMCID: PMC7074466 DOI: 10.3390/genes11020168] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 01/29/2020] [Accepted: 01/29/2020] [Indexed: 12/16/2022] Open
Abstract
Goat domestication and human selection for valued traits have formed diverse breeds with characteristic phenotypes. This process led to the fixation of causative genetic variants controlling breed-specific traits within regions of reduced genetic diversity-so-called "selection signatures". We previously reported an analysis of selection signatures based on pooled whole-genome sequencing data of 20 goat breeds and bezoar goats. In the present study, we reanalyzed the data and focused on a subset of eight Pakistani goat breeds (Angora, Barbari, Beetal, Dera Din Panah, Kamori, Nachi, Pahari, Teddy). We identified 749 selection signatures based on reduced heterozygosity in these breeds. A search for signatures that are shared across large-sized goat breeds revealed that five medium-to-large-sized Pakistani goat breeds had a common selection signature on chromosome 6 in a region harboring the LCORL gene, which has been shown to modulate height or body size in several mammalian species. Fine-mapping of the region confirmed that all five goat breeds with the selection signature were nearly fixed for the same haplotype in a ~191 kb region spanning positions 37,747,447-37,938,449. From the pool sequencing data, we identified a frame-shifting single base insertion into an isoform-specific exon of LCORL as a potential candidate causal variant mediating the size-increasing effect. If this preliminary result can be confirmed in independent replication studies, genotyping of this variant might be used to improve breeding programs and the selection for stature in goats.
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Affiliation(s)
- Rashid Saif
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001 Bern, Switzerland; (R.S.); (J.H.); (V.J.); (C.D.)
- Institute of Biotechnology, Gulab Devi Educational Complex, Lahore 54000, Pakistan
| | - Jan Henkel
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001 Bern, Switzerland; (R.S.); (J.H.); (V.J.); (C.D.)
| | - Vidhya Jagannathan
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001 Bern, Switzerland; (R.S.); (J.H.); (V.J.); (C.D.)
| | - Cord Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001 Bern, Switzerland; (R.S.); (J.H.); (V.J.); (C.D.)
| | - Christine Flury
- School of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, 3052 Zollikofen, Switzerland;
| | - Tosso Leeb
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001 Bern, Switzerland; (R.S.); (J.H.); (V.J.); (C.D.)
- Correspondence: ; Tel.: +41-31-631-23-26
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13
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Diniz-Filho JAF, Jardim L, Rangel TF, Holden PB, Edwards NR, Hortal J, Santos AMC, Raia P. Quantitative genetics of body size evolution on islands: an individual-based simulation approach. Biol Lett 2019; 15:20190481. [PMID: 31594495 DOI: 10.1098/rsbl.2019.0481] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
According to the island rule, small-bodied vertebrates will tend to evolve larger body size on islands, whereas the opposite happens to large-bodied species. This controversial pattern has been studied at the macroecological and biogeographical scales, but new developments in quantitative evolutionary genetics now allow studying the island rule from a mechanistic perspective. Here, we develop a simulation approach based on an individual-based model to model body size change on islands as a progressive adaptation to a moving optimum, determined by density-dependent population dynamics. We applied the model to evaluate body size differentiation in the pigmy extinct hominin Homo floresiensis, showing that dwarfing may have occurred in only about 360 generations (95% CI ranging from 150 to 675 generations). This result agrees with reports suggesting rapid dwarfing of large mammals on islands, as well as with the recent discovery that small-sized hominins lived in Flores as early as 700 kyr ago. Our simulations illustrate the power of analysing ecological and evolutionary patterns from an explicit quantitative genetics perspective.
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Affiliation(s)
| | - Lucas Jardim
- INCT EECBio, DTI program, Earth and Ecosystem Sciences, The Open University, Milton Keynes, UK
| | - Thiago F Rangel
- Departamento de Ecologia, ICB, Universidade Federal de Goiás (UFG), Goiania, Brazil
| | - Phillip B Holden
- Environment, Earth and Ecosystem Sciences, The Open University, Milton Keynes, UK
| | - Neil R Edwards
- Environment, Earth and Ecosystem Sciences, The Open University, Milton Keynes, UK
| | - Joaquín Hortal
- Departamento de Ecologia, ICB, Universidade Federal de Goiás (UFG), Goiania, Brazil.,Department of Biogeography and Global Change, Museo Nacional de Ciencias Naturales (MNCN-CSIC), C/José Gutiérrez Abascal 2, 28006 Madrid, Spain.,cE3c-Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Edifício C2, Piso 5, 1749-016 Lisboa, Portugal
| | - Ana M C Santos
- GLOCEE-Global Change Ecology and Evolution Group, Departamento de Ciencias de la Vida, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, Spain.,cE3c-Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Edifício C2, Piso 5, 1749-016 Lisboa, Portugal
| | - Pasquale Raia
- Department DiSTAR, University of Naples Federico II, Via Cintia 21, 20126 Napoli, Italy
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14
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MacRae CA. Closing the 'phenotype gap' in precision medicine: improving what we measure to understand complex disease mechanisms. Mamm Genome 2019; 30:201-211. [PMID: 31428846 DOI: 10.1007/s00335-019-09810-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 06/30/2019] [Indexed: 10/26/2022]
Abstract
The central concept underlying precision medicine is a mechanistic understanding of each disease and its response to therapy sufficient to direct a specific intervention. To execute on this vision requires parsing incompletely defined disease syndromes into discrete mechanistic subsets and developing interventions to precisely address each of these etiologically distinct entities. This will require substantial adjustment of traditional paradigms which have tended to aggregate high-level phenotypes with very different etiologies. In the current environment, where diagnoses are not mechanistic, drug development has become so expensive that it is now impractical to imagine the cost-effective creation of new interventions for many prevalent chronic conditions. The vision of precision medicine also argues for a much more seamless integration of research and development with clinical care, where shared taxonomies will enable every clinical interaction to inform our collective understanding of disease mechanisms and drug responses. Ideally, this would be executed in ways that drive real-time and real-world discovery, innovation, translation, and implementation. Only in oncology, where at least some of the biology is accessible through surgical excision of the diseased tissue or liquid biopsy, has "co-clinical" modeling proven feasible. In most common germline disorders, while genetics often reveal the causal mutations, there still remain substantial barriers to efficient disease modeling. Aggregation of similar disorders under single diagnostic labels has directly contributed to the paucity of etiologic and mechanistic understanding by directly reducing the resolution of any subsequent studies. Existing clinical phenotypes are typically anatomic, physiologic, or histologic, and result in a substantial mismatch in information content between the phenomes in humans or in animal 'models' and the variation in the genome. This lack of one-to-one mapping of discrete mechanisms between disease and animal models causes a failure of translation and is one form of 'phenotype gap.' In this review, we will focus on the origins of the phenotyping deficit and approaches that may be considered to bridge the gap, creating shared taxonomies between human diseases and relevant models, using cardiovascular examples.
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Affiliation(s)
- Calum A MacRae
- Cardiovascular Medicine, Genetics and Network Medicine Divisions, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Hale 7016, 75 Francis Street, Boston, MA, 02115, USA.
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15
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Sun Y, Liu Y, Sun X, Lin Y, Yin D, Xu S, Yang G. Insights into body size variation in cetaceans from the evolution of body-size-related genes. BMC Evol Biol 2019; 19:157. [PMID: 31351448 PMCID: PMC6660953 DOI: 10.1186/s12862-019-1461-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 06/14/2019] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Cetaceans exhibit an exceptionally wide range of body size, yet in this regard, their genetic basis remains poorly explored. In this study, 20 body-size-related genes for which duplication, mutation, or deficiency can cause body size change in mammals were chosen to preliminarily investigate the evolutionary mechanisms underlying the dramatic body size variation in cetaceans. RESULTS We successfully sequenced 20 body-size-related genes in six representative species of cetaceans. A total of 46 codons from 10 genes were detected and determined to be under strong positive selection, 32 (69.6%) of which were further found to be under radical physiochemical changes; moreover, some of these sites were localized in or near important functional regions. Interestingly, positively selected genes were well matched with body size evolution: for small cetaceans, strong evidence of positive selection was detected at ACAN, OBSL1, and GRB10, within which mutations or duplications could cause short stature; positive selection was found in large cetaceans at CBS and EIF2AK3, which could promote growth, and at the PLOD1 gene, within which mutations could cause tall stature. Importantly, relationship analyses revealed that the evolutionary rate of CBS was positively related to body length and body mass with statistical significance. Additionally, we identified 32 cetacean-specific amino acid changes in 10 genes. CONCLUSIONS This is the first study to investigate the molecular basis of dramatic body size variation in cetaceans. Our results provide evidence of the positive selection of several body-size-related genes in cetaceans, as well as divergent selection between large or small cetaceans, which suggest cetacean body size variation possibly associated with these genes. In addition, cetacean-specific amino acid changes might have played key roles in body size evolution after the divergence of cetaceans from their terrestrial relatives. Overall, the evolutionary pattern of these body-size-related genes could provide new insights into genetic mechanisms for the body size variation in cetaceans.
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Affiliation(s)
- Yingying Sun
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
| | - Yanzhi Liu
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
| | - Xiaohui Sun
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
| | - Yurui Lin
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
| | - Daiqing Yin
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
| | - Shixia Xu
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
| | - Guang Yang
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China
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16
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Murthy V, Tebaldi T, Yoshida T, Erdin S, Calzonetti T, Vijayvargia R, Tripathi T, Kerschbamer E, Seong IS, Quattrone A, Talkowski ME, Gusella JF, Georgopoulos K, MacDonald ME, Biagioli M. Hypomorphic mutation of the mouse Huntington's disease gene orthologue. PLoS Genet 2019; 15:e1007765. [PMID: 30897080 PMCID: PMC6445486 DOI: 10.1371/journal.pgen.1007765] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 04/02/2019] [Accepted: 02/07/2019] [Indexed: 01/08/2023] Open
Abstract
Rare individuals with inactivating mutations in the Huntington's disease gene (HTT) exhibit variable abnormalities that imply essential HTT roles during organ development. Here we report phenotypes produced when increasingly severe hypomorphic mutations in the murine HTT orthologue Htt, (HdhneoQ20, HdhneoQ50, HdhneoQ111), were placed over a null allele (Hdhex4/5). The most severe hypomorphic allele failed to rescue null lethality at gastrulation, while the intermediate, though still severe, alleles yielded recessive perinatal lethality and a variety of fetal abnormalities affecting body size, skin, skeletal and ear formation, and transient defects in hematopoiesis. Comparative molecular analysis of wild-type and Htt-null retinoic acid-differentiated cells revealed gene network dysregulation associated with organ development that nominate polycomb repressive complexes and miRNAs as molecular mediators. Together these findings demonstrate that Htt is required both pre- and post-gastrulation to support normal development.
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Affiliation(s)
- Vidya Murthy
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Toma Tebaldi
- Laboratory of Translational Genomics, Centre for Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Toshimi Yoshida
- Cutaneous Biology Research Center (CBRC), Mass General Hospital, Harvard Medical School, Charlestown, MA, United States of America
| | - Serkan Erdin
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Teresa Calzonetti
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Frederick Community College, Frederick MD, United States of America
| | - Ravi Vijayvargia
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Takshashila Tripathi
- NeuroEpigenetics Laboratory, Centre for Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Emanuela Kerschbamer
- NeuroEpigenetics Laboratory, Centre for Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Ihn Sik Seong
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Alessandro Quattrone
- Laboratory of Translational Genomics, Centre for Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Michael E. Talkowski
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Broad Institute of Harvard and MIT, Cambridge, MA, United States of America
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
| | - James F. Gusella
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Broad Institute of Harvard and MIT, Cambridge, MA, United States of America
- Department of Genetics, Harvard Medical School, Boston, MA, United States of America
| | - Katia Georgopoulos
- Cutaneous Biology Research Center (CBRC), Mass General Hospital, Harvard Medical School, Charlestown, MA, United States of America
| | - Marcy E. MacDonald
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Broad Institute of Harvard and MIT, Cambridge, MA, United States of America
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
| | - Marta Biagioli
- Molecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- NeuroEpigenetics Laboratory, Centre for Integrative Biology (CIBIO), University of Trento, Trento, Italy
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17
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Bouwman AC, Daetwyler HD, Chamberlain AJ, Ponce CH, Sargolzaei M, Schenkel FS, Sahana G, Govignon-Gion A, Boitard S, Dolezal M, Pausch H, Brøndum RF, Bowman PJ, Thomsen B, Guldbrandtsen B, Lund MS, Servin B, Garrick DJ, Reecy J, Vilkki J, Bagnato A, Wang M, Hoff JL, Schnabel RD, Taylor JF, Vinkhuyzen AAE, Panitz F, Bendixen C, Holm LE, Gredler B, Hozé C, Boussaha M, Sanchez MP, Rocha D, Capitan A, Tribout T, Barbat A, Croiseau P, Drögemüller C, Jagannathan V, Vander Jagt C, Crowley JJ, Bieber A, Purfield DC, Berry DP, Emmerling R, Götz KU, Frischknecht M, Russ I, Sölkner J, Van Tassell CP, Fries R, Stothard P, Veerkamp RF, Boichard D, Goddard ME, Hayes BJ. Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nat Genet 2018; 50:362-367. [PMID: 29459679 DOI: 10.1038/s41588-018-0056-5] [Citation(s) in RCA: 173] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/03/2018] [Indexed: 11/09/2022]
Abstract
Stature is affected by many polymorphisms of small effect in humans 1 . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10-8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.
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Affiliation(s)
- Aniek C Bouwman
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, the Netherlands
| | - Hans D Daetwyler
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, Australia
| | - Amanda J Chamberlain
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
| | - Carla Hurtado Ponce
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,Faculty of Land and Food Resources, University of Melbourne, Parkville, Victoria, Australia
| | - Mehdi Sargolzaei
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada.,The Semex Alliance, Guelph, Ontario, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | | | - Simon Boitard
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Marlies Dolezal
- Platform of Bioinformatics and Statistics, University of Veterinary Medicine, Vienna, Austria
| | - Hubert Pausch
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,Chair of Animal Breeding, Technische Universität München, Freising-Weihenstephan, Germany.,Animal Genomics, ETH Zurich, Zurich, Switzerland
| | - Rasmus F Brøndum
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Phil J Bowman
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
| | - Bo Thomsen
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Bernt Guldbrandtsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Mogens S Lund
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Bertrand Servin
- GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France
| | - Dorian J Garrick
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - James Reecy
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Johanna Vilkki
- Green Technology, Natural Resources Institute Finland (Luke), Jokioinen, Finland
| | | | - Min Wang
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, Australia
| | - Jesse L Hoff
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Anna A E Vinkhuyzen
- University of Queensland, Institute for Molecular Bioscience, St Lucia, Queensland, Australia.,University of Queensland, Queensland Brain Institute, St Lucia, Queensland, Australia
| | - Frank Panitz
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Christian Bendixen
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Lars-Erik Holm
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | | | - Chris Hozé
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France.,Allice, Paris, France
| | - Mekki Boussaha
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | | | - Dominique Rocha
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Aurelien Capitan
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France.,Allice, Paris, France
| | - Thierry Tribout
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Anne Barbat
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Pascal Croiseau
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | | | | | - Christy Vander Jagt
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
| | | | - Anna Bieber
- Research Institute of Organic Agriculture (FiBL), Frick, Switzerland
| | - Deirdre C Purfield
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Ireland
| | - Donagh P Berry
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Ireland
| | - Reiner Emmerling
- Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, Poing, Germany
| | - Kay-Uwe Götz
- Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, Poing, Germany
| | | | | | - Johann Sölkner
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, US Department of Agriculture, Beltsville, MD, USA
| | - Ruedi Fries
- Chair of Animal Breeding, Technische Universität München, Freising-Weihenstephan, Germany
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science/Livestock Gentec, University of Alberta, Edmonton, Alberta, Canada
| | - Roel F Veerkamp
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, the Netherlands
| | - Didier Boichard
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Mike E Goddard
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,Faculty of Land and Food Resources, University of Melbourne, Parkville, Victoria, Australia
| | - Ben J Hayes
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia. .,Queensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, University of Queensland, St Lucia, Queensland, Australia.
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18
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Deciphering signature of selection affecting beef quality traits in Angus cattle. Genes Genomics 2017; 40:63-75. [PMID: 29892901 DOI: 10.1007/s13258-017-0610-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 09/14/2017] [Indexed: 12/16/2022]
Abstract
Artificial selection towards a desired phenotype/trait has modified the genomes of livestock dramatically that generated breeds that greatly differ in morphology, production and environmental adaptation traits. Angus cattle are among the famous cattle breeds developed for superior beef quality. This paper aimed at exploring genomic regions under selection in Angus cattle that are associated with meat quality traits and other associated phenotypes. The whole genome of 10 Angus cattle was compared with 11 Hanwoo (A-H) and 9 Jersey (A-J) cattle breeds using a cross-population composite likelihood ratio (XP-CLR) statistical method. The top 1% of the empirical distribution was taken as significant and annotated using UMD3.1. As a result, 255 and 210 genes were revealed under selection from A-H and A-J comparisons, respectively. The WebGestalt gene ontology analysis resulted in sixteen (A-H) and five (A-J) significantly enriched KEGG pathways. Several pathways associated with meat quality traits (insulin signaling, type II diabetes mellitus pathway, focal adhesion pathway, and ECM-receptor interaction), and feeding efficiency (olfactory transduction, tight junction, and metabolic pathways) were enriched. Genes affecting beef quality traits (e.g., FABP3, FTO, DGAT2, ACS, ACAA2, CPE, TNNI1), stature and body size (e.g., PLAG1, LYN, CHCHD7, RPS20), fertility and dystocia (e.g., ESR1, RPS20, PPP2R1A, GHRL, PLAG1), feeding efficiency (e.g., PIK3CD, DNAJC28, DNAJC3, GHRL, PLAG1), coat color (e.g., MC1-R) and genetic disorders (e.g., ITGB6, PLAG1) were found to be under positive selection in Angus cattle. The study identified genes and pathways that are related to meat quality traits and other phenotypes of Angus cattle. The findings in this study, after validation using additional or independent dataset, will provide useful information for the study of Angus cattle in particular and beef cattle in general.
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19
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Komurai R, Fujisawa T, Okuzaki Y, Sota T. Genomic regions and genes related to inter-population differences in body size in the ground beetle Carabus japonicus. Sci Rep 2017; 7:7773. [PMID: 28798311 PMCID: PMC5552851 DOI: 10.1038/s41598-017-08362-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 07/11/2017] [Indexed: 11/14/2022] Open
Abstract
Body size is a key trait in diversification among animal species, and revealing the gene regions responsible for body size diversification among populations or related species is important in evolutionary biology. We explored the genomic regions associated with body size differences in Carabus japonicus ground beetle populations by quantitative trait locus (QTL) mapping of F2 hybrids from differently sized parents from two populations using restriction site-associated DNA sequencing and de novo assembly of the beetle whole genome. The assembled genome had a total length of 191 Mb with a scaffold N50 of 0.73 Mb; 14,929 protein-coding genes were predicted. Three QTLs on different linkage groups had major effects on the overall size, which is composed chiefly of elytral length. In addition, we found QTLs on autosomal and X chromosomal linkage groups that affected head length and width, thoracic width, and elytral width. We determined the gene loci potentially related to control of body size in scaffolds of the genome sequence, which contained the QTL regions. The genetic basis of body size variation based on a small number of major loci would promote differentiation in body size in response to selection pressures related to variations in environmental conditions and inter-specific interactions.
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Affiliation(s)
- Ryohei Komurai
- Department of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto, 606-8502, Japan
| | - Tomochika Fujisawa
- Department of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto, 606-8502, Japan
| | - Yutaka Okuzaki
- Field Science Center for Northern Biosphere, Hokkaido University, Tomakomai, 053-0035, Japan
| | - Teiji Sota
- Department of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto, 606-8502, Japan.
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20
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Zhang Q, Calus MPL, Guldbrandtsen B, Lund MS, Sahana G. Contribution of rare and low-frequency whole-genome sequence variants to complex traits variation in dairy cattle. Genet Sel Evol 2017; 49:60. [PMID: 28764638 PMCID: PMC5539983 DOI: 10.1186/s12711-017-0336-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 07/24/2017] [Indexed: 11/26/2022] Open
Abstract
Background Whole-genome sequencing and imputation methodologies have enabled the study of the effects of genomic variants with low to very low minor allele frequency (MAF) on variation in complex traits. Our objective was to estimate the proportion of variance explained by imputed sequence variants classified according to their MAF compared with the variance explained by the pedigree-based additive genetic relationship matrix for 17 traits in Nordic Holstein dairy cattle. Results Imputed sequence variants were grouped into seven classes according to their MAF (0.001–0.01, 0.01–0.05, 0.05–0.1, 0.1–0.2, 0.2–0.3, 0.3–0.4 and 0.4–0.5). The total contribution of all imputed sequence variants to variance in deregressed estimated breeding values or proofs (DRP) for different traits ranged from 0.41 [standard error (SE) = 0.026] for temperament to 0.87 (SE = 0.011) for milk yield. The contribution of rare variants (MAF < 0.01) to the total DRP variance explained by all imputed sequence variants was relatively small (a maximum of 12.5% for the health index). Rare and low-frequency variants (MAF < 0.05) contributed a larger proportion of the explained DRP variances (>13%) for health-related traits than for production traits (<11%). However, a substantial proportion of these variance estimates across different MAF classes had large SE, especially when the variance explained by a MAF class was small. The proportion of DRP variance that was explained by all imputed whole-genome sequence variants improved slightly compared with variance explained by the 50 k Illumina markers, which are routinely used in bovine genomic prediction. However, the proportion of DRP variance explained by imputed sequence variants was lower than that explained by pedigree relationships, ranging from 1.5% for milk yield to 37.9% for the health index. Conclusions Imputed sequence variants explained more of the variance in DRP than the 50 k markers for most traits, but explained less variance than that captured by pedigree-based relationships. Although in humans partitioning variants into groups based on MAF and linkage disequilibrium was used to estimate heritability without bias, many of our bovine estimates had a high SE. For a reliable estimate of the explained DRP variance for different MAF classes, larger sample sizes are needed. Electronic supplementary material The online version of this article (doi:10.1186/s12711-017-0336-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Qianqian Zhang
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830, Tjele, Denmark. .,Animal Breeding and Genomics, Wageningen University & Research, 6700AH, Wageningen, The Netherlands.
| | - Mario P L Calus
- Animal Breeding and Genomics, Wageningen University & Research, 6700AH, Wageningen, The Netherlands
| | - Bernt Guldbrandtsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830, Tjele, Denmark
| | - Mogens Sandø Lund
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830, Tjele, Denmark
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830, Tjele, Denmark.
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21
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Kominakis A, Hager-Theodorides AL, Zoidis E, Saridaki A, Antonakos G, Tsiamis G. Combined GWAS and 'guilt by association'-based prioritization analysis identifies functional candidate genes for body size in sheep. Genet Sel Evol 2017; 49:41. [PMID: 28454565 PMCID: PMC5408376 DOI: 10.1186/s12711-017-0316-3] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2016] [Accepted: 04/19/2017] [Indexed: 12/30/2022] Open
Abstract
Background Body size in sheep is an important indicator of productivity, growth and health as well as of environmental adaptation. It is a composite quantitative trait that has been studied with high-throughput genomic methods, i.e. genome-wide association studies (GWAS) in various mammalian species. Several genomic markers have been associated with body size traits and genes have been identified as causative candidates in humans, dog and cattle. A limited number of related GWAS have been performed in various sheep breeds and have identified genomic regions and candidate genes that partly account for body size variability. Here, we conducted a GWAS in Frizarta dairy sheep with phenotypic data from 10 body size measurements and genotypic data (from Illumina ovineSNP50 BeadChip) for 459 ewes. Results The 10 body size measurements were subjected to principal component analysis and three independent principal components (PC) were constructed, interpretable as width, height and length dimensions, respectively. The GWAS performed for each PC identified 11 significant SNPs, at the chromosome level, one on each of the chromosomes 3, 8, 9, 10, 11, 12, 19, 20, 23 and two on chromosome 25. Nine out of the 11 SNPs were located on previously identified quantitative trait loci for sheep meat, production or reproduction. One hundred and ninety-seven positional candidate genes within a 1-Mb distance from each significant SNP were found. A guilt-by-association-based (GBA) prioritization analysis (PA) was performed to identify the most plausible functional candidate genes. GBA-based PA identified 39 genes that were significantly associated with gene networks relevant to body size traits. Prioritized genes were identified in the vicinity of all significant SNPs except for those on chromosomes 10 and 12. The top five ranking genes were TP53, BMPR1A, PIK3R5, RPL26 and PRKDC. Conclusions The results of this GWAS provide evidence for 39 causative candidate genes across nine chromosomal regions for body size traits, some of which are novel and some are previously identified candidates from other studies (e.g. TP53, NTN1 and ZNF521). GBA-based PA has proved to be a useful tool to identify genes with increased biological relevance but it is subjected to certain limitations. Electronic supplementary material The online version of this article (doi:10.1186/s12711-017-0316-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Antonios Kominakis
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
| | - Ariadne L Hager-Theodorides
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece.
| | - Evangelos Zoidis
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
| | - Aggeliki Saridaki
- Department of Environmental and Natural Resources Management, University of Patras, Seferi 2, 30100, Agrinio, Greece
| | - George Antonakos
- Agricultural and Livestock Union of Western Greece, 13rd Km N.R. Agrinio-Ioannina, 30100, Lepenou, Greece
| | - George Tsiamis
- Department of Environmental and Natural Resources Management, University of Patras, Seferi 2, 30100, Agrinio, Greece
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22
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Fink T, Tiplady K, Lopdell T, Johnson T, Snell RG, Spelman RJ, Davis SR, Littlejohn MD. Functional confirmation of PLAG1 as the candidate causative gene underlying major pleiotropic effects on body weight and milk characteristics. Sci Rep 2017; 7:44793. [PMID: 28322319 PMCID: PMC5359603 DOI: 10.1038/srep44793] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 02/14/2017] [Indexed: 12/23/2022] Open
Abstract
A major pleiotropic quantitative trait locus (QTL) located at ~25 Mbp on bovine chromosome 14 affects a myriad of growth and developmental traits in Bos taurus and indicus breeds. These QTL have been attributed to two functional variants in the bidirectional promoter of PLAG1 and CHCHD7. Although PLAG1 is a good candidate for mediating these effects, its role remains uncertain given that these variants are also associated with expression of five additional genes at the broader locus. In the current study, we conducted expression QTL (eQTL) mapping of this region using a large, high depth mammary RNAseq dataset representing 375 lactating cows. Here we show that of the seven previously implicated genes, only PLAG1 and LYN are differentially expressed by QTL genotype, and only PLAG1 bears the same association signature of the growth and body weight QTLs. For the first time, we also report significant association of PLAG1 genotype with milk production traits, including milk fat, volume, and protein yield. Collectively, these data strongly suggest PLAG1 as the causative gene underlying this diverse range of traits, and demonstrate new effects for the locus on lactation phenotypes.
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Affiliation(s)
- Tania Fink
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | | | - Thomas Lopdell
- School of Biological Sciences, University of Auckland, Auckland, New Zealand.,Livestock Improvement Corporation, Hamilton, New Zealand
| | - Thomas Johnson
- Livestock Improvement Corporation, Hamilton, New Zealand
| | - Russell G Snell
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | | | | | - Mathew D Littlejohn
- School of Biological Sciences, University of Auckland, Auckland, New Zealand.,Livestock Improvement Corporation, Hamilton, New Zealand
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23
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Imputation-Based Fine-Mapping Suggests That Most QTL in an Outbred Chicken Advanced Intercross Body Weight Line Are Due to Multiple, Linked Loci. G3-GENES GENOMES GENETICS 2017; 7:119-128. [PMID: 27799342 PMCID: PMC5217102 DOI: 10.1534/g3.116.036012] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The Virginia chicken lines have been divergently selected for juvenile body weight for more than 50 generations. Today, the high- and low-weight lines show a >12-fold difference for the selected trait, 56-d body weight. These lines provide unique opportunities to study the genetic architecture of long-term, single-trait selection. Previously, several quantitative trait loci (QTL) contributing to weight differences between the lines were mapped in an F2-cross between them, and these were later replicated and fine-mapped in a nine-generation advanced intercross of them. Here, we explore the possibility to further increase the fine-mapping resolution of these QTL via a pedigree-based imputation strategy that aims to better capture the genetic diversity in the divergently selected, but outbred, founder lines. The founders of the intercross were high-density genotyped, and then pedigree-based imputation was used to assign genotypes throughout the pedigree. Imputation increased the marker density 20-fold in the selected QTL, providing 6911 markers for the subsequent analysis. Both single-marker association and multi-marker backward-elimination analyses were used to explore regions associated with 56-d body weight. The approach revealed several statistically and population structure independent associations and increased the mapping resolution. Further, most QTL were also found to contain multiple independent associations to markers that were not fixed in the founder populations, implying a complex underlying architecture due to the combined effects of multiple, linked loci perhaps located on independent haplotypes that still segregate in the selected lines.
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24
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Zhang Q, Guldbrandtsen B, Calus MPL, Lund MS, Sahana G. Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships. Genet Sel Evol 2016; 48:60. [PMID: 27534618 PMCID: PMC4989328 DOI: 10.1186/s12711-016-0238-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Accepted: 08/04/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. RESULTS We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. CONCLUSIONS We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.
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Affiliation(s)
- Qianqian Zhang
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark. .,Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, The Netherlands.
| | - Bernt Guldbrandtsen
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - Mario P L Calus
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, The Netherlands
| | - Mogens Sandø Lund
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - Goutam Sahana
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
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25
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Holmes MW, Hammond TT, Wogan GOU, Walsh RE, LaBarbera K, Wommack EA, Martins FM, Crawford JC, Mack KL, Bloch LM, Nachman MW. Natural history collections as windows on evolutionary processes. Mol Ecol 2016; 25:864-81. [PMID: 26757135 DOI: 10.1111/mec.13529] [Citation(s) in RCA: 139] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 11/30/2015] [Accepted: 12/27/2015] [Indexed: 12/14/2022]
Abstract
Natural history collections provide an immense record of biodiversity on Earth. These repositories have traditionally been used to address fundamental questions in biogeography, systematics and conservation. However, they also hold the potential for studying evolution directly. While some of the best direct observations of evolution have come from long-term field studies or from experimental studies in the laboratory, natural history collections are providing new insights into evolutionary change in natural populations. By comparing phenotypic and genotypic changes in populations through time, natural history collections provide a window into evolutionary processes. Recent studies utilizing this approach have revealed some dramatic instances of phenotypic change over short timescales in response to presumably strong selective pressures. In some instances, evolutionary change can be paired with environmental change, providing a context for potential selective forces. Moreover, in a few cases, the genetic basis of phenotypic change is well understood, allowing for insight into adaptive change at multiple levels. These kinds of studies open the door to a wide range of previously intractable questions by enabling the study of evolution through time, analogous to experimental studies in the laboratory, but amenable to a diversity of species over longer timescales in natural populations.
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Affiliation(s)
- Michael W Holmes
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA.,Department of Biology, Coastal Carolina University, Conway, SC, 29528, USA
| | - Talisin T Hammond
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Guinevere O U Wogan
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Rachel E Walsh
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Katie LaBarbera
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Elizabeth A Wommack
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA.,Department of Zoology and Physiology, University of Wyoming Museum of Vertebrates, Laramie, WY, 82071, USA
| | - Felipe M Martins
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Jeremy C Crawford
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Katya L Mack
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Luke M Bloch
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
| | - Michael W Nachman
- Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, CA, 97420-3140, USA
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26
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Gutiérrez-Gil B, Arranz JJ, Wiener P. An interpretive review of selective sweep studies in Bos taurus cattle populations: identification of unique and shared selection signals across breeds. Front Genet 2015; 6:167. [PMID: 26029239 PMCID: PMC4429627 DOI: 10.3389/fgene.2015.00167] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Accepted: 04/13/2015] [Indexed: 12/11/2022] Open
Abstract
This review compiles the results of 21 genomic studies of European Bos taurus breeds and thus provides a general picture of the selection signatures in taurine cattle identified by genome-wide selection-mapping scans. By performing a comprehensive summary of the results reported in the literature, we compiled a list of 1049 selection sweeps described across 37 cattle breeds (17 beef breeds, 14 dairy breeds, and 6 dual-purpose breeds), and four different beef-vs.-dairy comparisons, which we subsequently grouped into core selective sweep (CSS) regions, defined as consecutive signals within 1 Mb of each other. We defined a total of 409 CSSs across the 29 bovine autosomes, 232 (57%) of which were associated with a single-breed (Single-breed CSSs), 134 CSSs (33%) were associated with a limited number of breeds (Two-to-Four-breed CSSs) and 39 CSSs (9%) were associated with five or more breeds (Multi-breed CSSs). For each CSS, we performed a candidate gene survey that identified 291 genes within the CSS intervals (from the total list of 5183 BioMart-extracted genes) linked to dairy and meat production, stature, and coat color traits. A complementary functional enrichment analysis of the CSS positional candidates highlighted other genes related to pathways underlying behavior, immune response, and reproductive traits. The Single-breed CSSs revealed an over-representation of genes related to dairy and beef production, this was further supported by over-representation of production-related pathway terms in these regions based on a functional enrichment analysis. Overall, this review provides a comparative map of the selection sweeps reported in European cattle breeds and presents for the first time a characterization of the selection sweeps that are found in individual breeds. Based on their uniqueness, these breed-specific signals could be considered as “divergence signals,” which may be useful in characterizing and protecting livestock genetic diversity.
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Affiliation(s)
| | - Juan J Arranz
- Departamento de Producción Animal, Universidad de León León, Spain
| | - Pamela Wiener
- Division of Genetics and Genomics, Roslin Institute and R(D)SVS, University of Edinburgh Midlothian, UK
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27
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Speed D, O'Brien TJ, Palotie A, Shkura K, Marson AG, Balding DJ, Johnson MR. Describing the genetic architecture of epilepsy through heritability analysis. ACTA ACUST UNITED AC 2014; 137:2680-9. [PMID: 25063994 PMCID: PMC4163034 DOI: 10.1093/brain/awu206] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Epilepsy is highly heritable, but its genetic architecture is poorly understood. Speed et al. estimate the number of susceptibility loci, show that common variants account for the majority of heritability, and demonstrate that epilepsy consists of genetically distinct subtypes. They conclude that gene-based prediction models may have clinical utility in first-seizure settings. Epilepsy is a disease with substantial missing heritability; despite its high genetic component, genetic association studies have had limited success detecting common variants which influence susceptibility. In this paper, we reassess the role of common variants on epilepsy using extensions of heritability analysis. Our data set consists of 1258 UK patients with epilepsy, of which 958 have focal epilepsy, and 5129 population control subjects, with genotypes recorded for over 4 million common single nucleotide polymorphisms. Firstly, we show that on the liability scale, common variants collectively explain at least 26% (standard deviation 5%) of phenotypic variation for all epilepsy and 27% (standard deviation 5%) for focal epilepsy. Secondly we provide a new method for estimating the number of causal variants for complex traits; when applied to epilepsy, our most optimistic estimate suggests that at least 400 variants influence disease susceptibility, with potentially many thousands. Thirdly, we use bivariate analysis to assess how similar the genetic architecture of focal epilepsy is to that of non-focal epilepsy; we demonstrate both significant differences (P = 0.004) and significant similarities (P = 0.01) between the two subtypes, indicating that although the clinical definition of focal epilepsy does identify a genetically distinct epilepsy subtype, there is also scope to improve the classification of epilepsy by incorporating genotypic information. Lastly, we investigate the potential value in using genetic data to diagnose epilepsy following a single epileptic seizure; we find that a prediction model explaining 10% of phenotypic variation could have clinical utility for deciding which single-seizure individuals are likely to benefit from immediate anti-epileptic drug therapy.
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Affiliation(s)
- Doug Speed
- 1 UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Terence J O'Brien
- 2 The Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Australia
| | - Aarno Palotie
- 3 Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland 4 The Broad Institute of MIT and Harvard, Cambridge, USA 5 Department of Medical Genetics, University of Helsinki, Finland 6 University Central Hospital, Helsinki, Finland
| | - Kirill Shkura
- 7 Division of Brain Sciences, Imperial College London, London W6 8RF, UK 8 Medical Research Council (MRC) Clinical Sciences Centre, Faculty of Medicine, Imperial College London, UK
| | - Anthony G Marson
- 9 Department of Molecular and Clinical Pharmacology, University of Liverpool, UK
| | - David J Balding
- 1 UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Michael R Johnson
- 7 Division of Brain Sciences, Imperial College London, London W6 8RF, UK
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Curik I, Druml T, Seltenhammer M, Sundström E, Pielberg GR, Andersson L, Sölkner J. Complex inheritance of melanoma and pigmentation of coat and skin in Grey horses. PLoS Genet 2013; 9:e1003248. [PMID: 23408897 PMCID: PMC3567150 DOI: 10.1371/journal.pgen.1003248] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Accepted: 12/02/2012] [Indexed: 11/19/2022] Open
Abstract
The dominant phenotype of greying with age in horses, caused by a 4.6-kb duplication in intron 6 of STX17, is associated with a high incidence of melanoma and vitiligo-like skin depigmentation. However, the progressive greying and the incidence of melanoma, vitiligo-like depigmentation, and amount of speckling in these horses do not follow a simple inheritance pattern. To understand their inheritance, we analysed the melanoma grade, grey level, vitiligo grade, and speckling grade of 1,119 Grey horses (7,146 measurements) measured in six countries over a 9-year period. We estimated narrow sense heritability (h2), and we decomposed this parameter into polygenic heritability (h2POLY), heritability due to the Grey (STX17) mutation (h2STX17), and heritability due to agouti (ASIP) locus (h2ASIP). A high heritability was found for greying (h2 = 0.79), vitiligo (h2 = 0.63), and speckling (h2 = 0.66), while a moderate heritability was estimated for melanoma (h2 = 0.37). The additive component of ASIP was significantly different from zero only for melanoma (h2ASIP = 0.02). STX17 controlled large proportions of phenotypic variance (h2STX17 = 0.18–0.55) and overall heritability (h2STX17/h2 = 0.28–0.83) for all traits. Genetic correlations among traits were estimated as moderate to high, primarily due to the effects of the STX17 locus. Nevertheless, the correlation between progressive greying and vitiligo-like depigmentation remained large even after taking into account the effects of STX17. We presented a model where four traits with complex inheritance patterns are strongly influenced by a single mutation. This is in line with evidence of recent studies in domestic animals indicating that some complex traits are, in addition to the large number of genes with small additive effects, influenced by genes of moderate-to-large effect. Furthermore, we demonstrated that the STX17 mutation explains to a large extent the moderate to high genetic correlations among traits, providing an example of strong pleiotropic effects caused by a single gene. Clarifying the genetic architecture of complex traits is a problem with profound implications for agriculture, biology, and medicine. Using data from Lipizzan horses with the grey coat phenotype, we present an example of a single mutation (intronic duplication in STX17) that explains 18%–55% of phenotypic variation in four complex traits, while polygenic background additive effects also explain 11%–57% of phenotypic variation. This study provides a prime example of complex traits being influenced by genes of moderate-to-large effect and supports further the evidence of recent studies in domestic animals that some complex traits are, in addition to the large number of genes with small additive effects, influenced by genes of moderate-to-large effect. We further show that the STX17 mutation accounts for a large proportion of the estimated genetic correlations between the traits. This case of strong pleiotropic effects of a single mutation on complex traits makes this work of significant general interest for biology and medicine.
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Affiliation(s)
- Ino Curik
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Zagreb, Croatia
- * E-mail: (IC); (JS)
| | - Thomas Druml
- Department of Sustainable Agricultural Systems, University of Natural Resources and Applied Life Sciences, Vienna, Austria
| | - Monika Seltenhammer
- Department of Vascular Biology and Thrombosis Research, Medical University of Vienna, Vienna, Austria
| | - Elisabeth Sundström
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Gerli Rosengren Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Leif Andersson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Johann Sölkner
- Department of Sustainable Agricultural Systems, University of Natural Resources and Applied Life Sciences, Vienna, Austria
- * E-mail: (IC); (JS)
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Abstract
Genome-wide association studies and comparative genomics have established major loci and specific polymorphisms affecting human skin, hair and eye color. Environmental changes have had an impact on selected pigmentation genes as populations have expanded into different regions of the globe.
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Affiliation(s)
- Richard A Sturm
- Institute for Molecular Bioscience, Melanogenix Group, The University of Queensland, Brisbane, Qld 4072, Australia.
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