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Mujyambere V, Adomako K, Olympio OS. Effectiveness of DArTseq markers application in genetic diversity and population structure of indigenous chickens in Eastern Province of Rwanda. BMC Genomics 2024; 25:193. [PMID: 38373904 PMCID: PMC10875757 DOI: 10.1186/s12864-024-10089-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 02/04/2024] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND The application of biotechnologies which make use of genetic markers in chicken breeding is developing rapidly. Diversity Array Technology (DArT) is one of the current Genotyping-By-Sequencing techniques allowing the discovery of whole genome sequencing. In livestock, DArT has been applied in cattle, sheep, and horses. Currently, there is no study on the application of DArT markers in chickens. The aim was to study the effectiveness of DArTSeq markers in the genetic diversity and population structure of indigenous chickens (IC) and SASSO in the Eastern Province of Rwanda. METHODS In total 87 blood samples were randomly collected from 37 males and 40 females of indigenous chickens and 10 females of SASSO chickens purposively selected from 5 sites located in two districts of the Eastern Province of Rwanda. Genotyping by Sequencing (GBS) using DArTseq technology was employed. This involved the complexity reduction method through digestion of genomic DNA and ligation of barcoded adapters followed by PCR amplification of adapter-ligated fragments. RESULTS From 45,677 DArTseq SNPs and 25,444 SilicoDArTs generated, only 8,715 and 6,817 respectively remained for further analysis after quality control. The average call rates observed, 0.99 and 0.98 for DArTseq SNPs and SilicoDArTs respectively were quite similar. The polymorphic information content (PIC) from SilicoDArTs (0.33) was higher than that from DArTseq SNPs (0.22). DArTseq SNPs and SilicoDArTs had 34.4% and 34% of the loci respectively mapped on chromosome 1. DArTseq SNPs revealed distance averages of 0.17 and 0.15 within IC and SASSO chickens respectively while the respective averages observed with SilicoDArTs were 0.42 and 0.36. The average genetic distance between IC and SASSO chickens was moderate for SilicoDArTs (0.120) compared to that of DArTseq SNPs (0.048). The PCoA and population structure clustered the chicken samples into two subpopulations (1 and 2); 1 is composed of IC and 2 by SASSO chickens. An admixture was observed in subpopulation 2 with 12 chickens from subpopulation 1. CONCLUSIONS The application of DArTseq markers have been proven to be effective and efficient for genetic relationship between IC and separated IC from exotic breed used which indicate their suitability in genomic studies. However, further studies using all chicken genetic resources available and large big sample sizes are required.
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Affiliation(s)
- Valentin Mujyambere
- Department of Animal Production, School of Veterinary Medicine, University of Rwanda, Nyagatare, Rwanda.
- Department of Animal Production, University of Rwanda (UR), P.O. Box 57, Nyagatare, Rwanda.
- Department of Animal Science, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, AK-385-1973, Ghana.
| | - Kwaku Adomako
- Department of Animal Science, Faculty of Agriculture, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Oscar Simon Olympio
- Department of Animal Science, Faculty of Agriculture, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
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Küçüktopçu E, Cemek B, Simsek H. Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach. Animals (Basel) 2024; 14:501. [PMID: 38338144 PMCID: PMC10854819 DOI: 10.3390/ani14030501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/27/2024] [Accepted: 02/01/2024] [Indexed: 02/12/2024] Open
Abstract
In recent years, computational fluid dynamics (CFD) has become increasingly important and has proven to be an effective method for assessing environmental conditions in poultry houses. CFD offers simplicity, efficiency, and rapidity in assessing and optimizing poultry house environments, thereby fueling greater interest in its application. This article aims to facilitate researchers in their search for relevant CFD studies in poultry housing environmental conditions by providing an in-depth review of the latest advancements in this field. It has been found that CFD has been widely employed to study and analyze various aspects of poultry house ventilation and air quality under the following five main headings: inlet and fan configuration, ventilation system design, air temperature-humidity distribution, airflow distribution, and particle matter and gas emission. The most commonly used turbulence models in poultry buildings are the standard k-ε, renormalization group (RNG) k-ε, and realizable k-ε models. Additionally, this article presents key solutions with a summary and visualization of fundamental approaches employed in addressing path planning problems within the CFD process. Furthermore, potential challenges, such as data acquisition, validation, computational resource requirements, meshing, and the selection of a proper turbulence model, are discussed, and avenues for future research (the integration of machine learning, building information modeling, and feedback control systems with CFD) are explored.
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Affiliation(s)
- Erdem Küçüktopçu
- Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Türkiye;
| | - Bilal Cemek
- Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Türkiye;
| | - Halis Simsek
- Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA;
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EL Nagar AG, Salem MMI, Amin AMS, Khalil MH, Ashour AF, Hegazy MM, Abdel-Shafy H. A Single-Step Genome-Wide Association Study for Semen Traits of Egyptian Buffalo Bulls. Animals (Basel) 2023; 13:3758. [PMID: 38136796 PMCID: PMC10740893 DOI: 10.3390/ani13243758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/17/2023] [Accepted: 11/24/2023] [Indexed: 12/24/2023] Open
Abstract
The present study aimed to contribute to the limited research on buffalo (Bubalus bubalis) semen traits by incorporating genomic data. A total of 8465 ejaculates were collected. The genotyping procedure was conducted using the Axiom® Buffalo Genotyping 90 K array designed by the Affymetrix Expert Design Program. After conducting a quality assessment, we utilized 67,282 SNPs genotyped in 192 animals. We identified several genomic loci explaining high genetic variance by employing single-step genomic evaluation. The aforementioned regions were located on buffalo chromosomes no. 3, 4, 6, 7, 14, 16, 20, 22, and the X-chromosome. The X-chromosome exhibited substantial influence, accounting for 4.18, 4.59, 5.16, 5.19, and 4.31% of the genomic variance for ejaculate volume, mass motility, livability, abnormality, and concentration, respectively. In the examined genomic regions, we identified five novel candidate genes linked to male fertility and spermatogenesis, four in the X-chromosome and one in chromosome no. 16. Additional extensive research with larger sample sizes and datasets is imperative to validate these findings and evaluate their applicability for genomic selection.
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Affiliation(s)
- Ayman G. EL Nagar
- Department of Animal Production, Faculty of Agriculture at Moshtohor, Benha University, Benha 13736, Egypt;
| | - Mohamed M. I. Salem
- Department of Animal and Fish Production, Faculty of Agriculture (El-Shatby), Alexandria University, Alexandria 21545, Egypt;
| | - Amin M. S. Amin
- Animal Production Research Institute, Agricultural Research Center, Dokki, Giza 12619, Egypt; (A.M.S.A.); (A.F.A.); (M.M.H.)
| | - Maher H. Khalil
- Department of Animal Production, Faculty of Agriculture at Moshtohor, Benha University, Benha 13736, Egypt;
| | - Ayman F. Ashour
- Animal Production Research Institute, Agricultural Research Center, Dokki, Giza 12619, Egypt; (A.M.S.A.); (A.F.A.); (M.M.H.)
| | - Mohammed M. Hegazy
- Animal Production Research Institute, Agricultural Research Center, Dokki, Giza 12619, Egypt; (A.M.S.A.); (A.F.A.); (M.M.H.)
| | - Hamdy Abdel-Shafy
- Department of Animal Production, Faculty of Agriculture, Cairo University, El-Gamma Street, Giza 12613, Egypt;
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Urgessa OE, Woldesemayat AA. OMICs approaches and technologies for understanding low-high feed efficiency traits in chicken: implication to breeding. Anim Biotechnol 2023; 34:4147-4166. [PMID: 36927292 DOI: 10.1080/10495398.2023.2187404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
In poultry production, there has been a trend of continuous increase in cost of feed ingredients which represents the major proportion of the production costs. Feed costs can be reduced by improving feed efficiency traits which increase the possibility of using various indigestible feed sources and decrease the environmental impact of the enhanced poultry production. Therefore, feed efficiency has been used as one of the most important economic traits of selection in the breeding program of chickens. Recently, many OMICs experimental studies have been designed to characterize biological differences between the high and low feed efficiency chicken phenotypes. Biological complexity cannot be fully captured by main individual OMICs such as genomics, transcriptomics, proteomics and metabolomics. Therefore, researchers have combined multiple assays from the same set of samples to create multi-OMICs datasets. OMICs findings are crucial in improving existing approaches to poultry breeding. The current review aimed to highlight the components of feed efficiency and general OMICs approaches and technologies. Besides, individual and multi-OMICs based understanding of chicken feed efficiency traits and the application of the acquired knowledge in the chicken breeding program were addressed.
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Affiliation(s)
- Olyad Erba Urgessa
- School of Biological Sciences and Biotechnology, College of Natural and Computational Sciences, Haramaya University, Dire Dawa, Ethiopia
- Department of Applied Biology, School of Applied Natural Science, Adama Science and Technology University, Adama, Ethiopia
| | - Adugna Abdi Woldesemayat
- College of Biological and Chemical Engineering, Department of Biotechnology, Genomics and Bioinformatics Research Unit, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia
- College of Agriculture & Environmental Sciences, University of South Africa, Florida Science Campus, 28 Pioneer Ave, Florida Park, Roodepoort, South Africa
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First large-scale genomic prediction in the honey bee. Heredity (Edinb) 2023; 130:320-328. [PMID: 36878945 PMCID: PMC10163272 DOI: 10.1038/s41437-023-00606-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 02/23/2023] [Accepted: 02/23/2023] [Indexed: 03/08/2023] Open
Abstract
Genomic selection has increased genetic gain in several livestock species, but due to the complicated genetics and reproduction biology not yet in honey bees. Recently, 2970 queens were genotyped to gather a reference population. For the application of genomic selection in honey bees, this study analyzes the accuracy and bias of pedigree-based and genomic breeding values for honey yield, three workability traits, and two traits for resistance against the parasite Varroa destructor. For breeding value estimation, we use a honey bee-specific model with maternal and direct effects, to account for the contributions of the workers and the queen of a colony to the phenotypes. We conducted a validation for the last generation and a five-fold cross-validation. In the validation for the last generation, the accuracy of pedigree-based estimated breeding values was 0.12 for honey yield, and ranged from 0.42 to 0.61 for the workability traits. The inclusion of genomic marker data improved these accuracies to 0.23 for honey yield, and a range from 0.44 to 0.65 for the workability traits. The inclusion of genomic data did not improve the accuracy of the disease-related traits. Traits with high heritability for maternal effects compared to the heritability for direct effects showed the most promising results. For all traits except the Varroa resistance traits, the bias with genomic methods was on a similar level compared to the bias with pedigree-based BLUP. The results show that genomic selection can successfully be applied to honey bees.
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Küçüktopcu E, Cemek B, Simsek H, Ni JQ. Computational Fluid Dynamics Modeling of a Broiler House Microclimate in Summer and Winter. Animals (Basel) 2022; 12:ani12070867. [PMID: 35405856 PMCID: PMC8997067 DOI: 10.3390/ani12070867] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/15/2022] [Accepted: 03/22/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary Microclimate conditions in broiler housing are significant for maximizing poultry production and ensuring the welfare of the birds. In the present study, we modeled summer and winter microclimates in a mechanically ventilated broiler house. Validation of the simulated values was accomplished through comparison to field measurements. In visual simulations, the results were used to reconstruct microclimate conditions such as stagnant and stress zones of broiler houses. In conclusion, simulation techniques can be used as an alternative method for analyzing poultry house indoor environments. Abstract Appropriate microclimate conditions in broiler housing are critical for optimizing poultry production and ensuring the health and welfare of the birds. In this study, spatial variabilities of the microclimate in summer and winter seasons in a mechanically ventilated broiler house were modeled using the computational fluid dynamics (CFD) technique. Field measurements of temperature, relative humidity, and airspeeds were conducted in the house to compare the simulated results. The study identified two problems of high temperature in summer, which could result in bird heat stress and stagnant zones in winter, and simulated possible alternative solutions. In summer, if an evaporative cooling pad system was used, a decrease in temperature of approximately 3 °C could be achieved when the mean air temperature rose above 25 °C in the house. In winter, adding four 500-mm circulation fans of 20-m spacing inside the house could eliminate the accumulation of hot and humid air in the stagnant zones in the house. This study demonstrated that CFD is a valuable tool for adequate heating, ventilation, and air conditioning system design in poultry buildings.
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Affiliation(s)
- Erdem Küçüktopcu
- Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Turkey;
- Correspondence:
| | - Bilal Cemek
- Department of Agricultural Structures and Irrigation, Ondokuz Mayıs University, Samsun 55139, Turkey;
| | - Halis Simsek
- Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA; (H.S.); (J.-Q.N.)
| | - Ji-Qin Ni
- Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA; (H.S.); (J.-Q.N.)
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Bernstein R, Du M, Hoppe A, Bienefeld K. Simulation studies to optimize genomic selection in honey bees. Genet Sel Evol 2021; 53:64. [PMID: 34325663 PMCID: PMC8323320 DOI: 10.1186/s12711-021-00654-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 07/07/2021] [Indexed: 12/04/2022] Open
Abstract
Background With the completion of a single nucleotide polymorphism (SNP) chip for honey bees, the technical basis of genomic selection is laid. However, for its application in practice, methods to estimate genomic breeding values need to be adapted to the specificities of the genetics and breeding infrastructure of this species. Drone-producing queens (DPQ) are used for mating control, and usually, they head non-phenotyped colonies that will be placed on mating stations. Breeding queens (BQ) head colonies that are intended to be phenotyped and used to produce new queens. Our aim was to evaluate different breeding program designs for the initiation of genomic selection in honey bees. Methods Stochastic simulations were conducted to evaluate the quality of the estimated breeding values. We developed a variation of the genomic relationship matrix to include genotypes of DPQ and tested different sizes of the reference population. The results were used to estimate genetic gain in the initial selection cycle of a genomic breeding program. This program was run over six years, and different numbers of genotyped queens per year were considered. Resources could be allocated to increase the reference population, or to perform genomic preselection of BQ and/or DPQ. Results Including the genotypes of 5000 phenotyped BQ increased the accuracy of predictions of breeding values by up to 173%, depending on the size of the reference population and the trait considered. To initiate a breeding program, genotyping a minimum number of 1000 queens per year is required. In this case, genetic gain was highest when genomic preselection of DPQ was coupled with the genotyping of 10–20% of the phenotyped BQ. For maximum genetic gain per used genotype, more than 2500 genotyped queens per year and preselection of all BQ and DPQ are required. Conclusions This study shows that the first priority in a breeding program is to genotype phenotyped BQ to obtain a sufficiently large reference population, which allows successful genomic preselection of queens. To maximize genetic gain, DPQ should be preselected, and their genotypes included in the genomic relationship matrix. We suggest, that the developed methods for genomic prediction are suitable for implementation in genomic honey bee breeding programs. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00654-x.
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Affiliation(s)
- Richard Bernstein
- Institute for Bee Research Hohen Neuendorf, Friedrich-Engels-Str. 32, 16540, Hohen Neuendorf, Germany. .,Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt University of Berlin, 10099, Berlin, Germany.
| | - Manuel Du
- Institute for Bee Research Hohen Neuendorf, Friedrich-Engels-Str. 32, 16540, Hohen Neuendorf, Germany
| | - Andreas Hoppe
- Institute for Bee Research Hohen Neuendorf, Friedrich-Engels-Str. 32, 16540, Hohen Neuendorf, Germany
| | - Kaspar Bienefeld
- Institute for Bee Research Hohen Neuendorf, Friedrich-Engels-Str. 32, 16540, Hohen Neuendorf, Germany.,Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt University of Berlin, 10099, Berlin, Germany
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8
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Goto T, Shimamoto S, Ohtsuka A, Ijiri D. Analyses of free amino acid and taste sensor traits in egg albumen and yolk revealed potential of value-added eggs in chickens. Anim Sci J 2021; 92:e13510. [PMID: 33417307 DOI: 10.1111/asj.13510] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 11/29/2020] [Accepted: 12/17/2020] [Indexed: 12/24/2022]
Abstract
To create high-quality eggs by using different breed and feed materials, we investigated free amino acid contents and taste sensor traits using two chicken breeds (Rhode Island Red; RIR and Australorp; AUS) fed two feeds (mixed and fermented feeds). Two-way ANOVA revealed significant breed and feed main and interaction effects on albumen bitterness and a significant interaction effect on yolk bitterness. Albumen from RIR fed mixed feed and AUS fed fermented feed was higher bitterness, whereas yolk from those groups was lower bitterness. Significant breed effects were detected in four albumen amino acid traits (His, Met, Ile, and Lys) and a yolk His, whereas significant feed effects were found in 15 albumen amino acid traits (Asp, Glu, Ser, His, Gly, Thr, Ala, Tyr, Val, Met, Trp, Ile, Leu, Lys, and Pro) and a yolk cystine trait. Compared to albumen amino acids, yolk amino acids had limited effects by breed and feed. The present results suggest that genetic and nutritional factors can alter not only amino acid contents but also sensor values of bitterness, indicating that selecting the combination of breed and feed enable us to make amino acids enriched and taste added designer eggs in future.
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Affiliation(s)
- Tatsuhiko Goto
- Research Center for Global Agromedicine, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan.,Department of Life and Food Science, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan
| | - Saki Shimamoto
- Department of Biochemical Science and Technology, Kagoshima University, Korimoto, Japan.,Graduate School of Science and Technology, Niigata University, Niigata, Japan
| | - Akira Ohtsuka
- Department of Biochemical Science and Technology, Kagoshima University, Korimoto, Japan
| | - Daichi Ijiri
- Department of Biochemical Science and Technology, Kagoshima University, Korimoto, Japan
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Mao H, Xu X, Cao H, Dong X, Zou X, Xu N, Yin Z. Comparative Transcriptome Profiling of mRNA and lncRNA of Ovaries in High and Low Egg Production Performance in Domestic Pigeons ( Columba livia). Front Genet 2021; 12:571325. [PMID: 33833772 PMCID: PMC8021926 DOI: 10.3389/fgene.2021.571325] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 03/01/2021] [Indexed: 12/22/2022] Open
Abstract
Egg production performance is one of the most important economic traits in pigeon industry. However, little is known regarding how egg production performance is regulated by long non-coding RNAs (lncRNAs) in pigeons. To evaluate the lncRNAs and mRNAs in ovaries associated with egg production performance in domestic pigeons, high-throughput RNA sequencing of ovaries between high and low egg production performance groups were performed and analyzed in this study. A total of 34,346 mRNAs and 24,601 lncRNAs were identified, including 14,525 known lncRNAs and 10,076 novel lncRNAs, of which 811 mRNAs and 148 lncRNAs (P < 0.05) were significantly differentially expressed (DE) between the groups of high and low egg production performance. GO and KEGG annotation analysis indicated that the target genes of DE lncRNAs and DE mRNAs were related to cell differentiation, ATP binding and methylation. Moreover, we found that FOXK2, a target gene of lncRNA MSTRG.7894.4, was involved in regulating estrogen receptors. Our study provided a catalog of lncRNAs and mRNAs associated with egg production performance, and they deserve further study to deepen the understanding of biological processes in the ovaries of pigeons.
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Affiliation(s)
- Haiguang Mao
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
- School of Biological and Chemical Engineering, Ningbo Tech University, Ningbo, Zhejiang, China
| | - Xiuli Xu
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
| | - Haiyue Cao
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xinyang Dong
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaoting Zou
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
| | - Ningying Xu
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhaozheng Yin
- Animal Science College, Zhejiang University, Hangzhou, Zhejiang, China
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Genome-wide association mapping and accuracy of predictions for amoebic gill disease in Atlantic salmon (Salmo salar). Sci Rep 2020; 10:6435. [PMID: 32296114 PMCID: PMC7160127 DOI: 10.1038/s41598-020-63423-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 03/30/2020] [Indexed: 11/09/2022] Open
Abstract
Amoebic gill disease (AGD) is a parasitic disease caused by the amoeba Paramoeba perurans, which colonizes the gill tissues and causes distress for the host. AGD can cause high morbidity and mortalities in salmonid and non-salmonid fish species. To understand the genetic basis of AGD and improve health status of farmed A. salmon, a population of ~ 6,100 individuals belonging to 150 full-sib families was monitored for development of AGD in the sea of Ireland. The population was followed for two rounds of AGD infections, and fish were gill scored to identify severity of disease in first (N = 3,663) and the second (N = 3,511) infection with freshwater treatment after the first gill-scoring. A subset of this gill-scored population (N = 1,141) from 119 full-sib families were genotyped with 57,184 SNPs using custom-made Affymetrix SNP-chip. GWAS analyses were performed which resulted in five significantly associated SNP variants distributed over chromosome 1, 2 and 5. Three candidate genes; c4, tnxb and slc44a4 were found within QTL region of chromosome 2. The tnxb and c4 genes are known to be a part of innate immune system, and may play a role in resistance to AGD. The gain in prediction accuracy obtained by involving genomic information was 9–17% higher than using traditional pedigree information.
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12
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Rowland K, Wolc A, Gallardo RA, Kelly T, Zhou H, Dekkers JCM, Lamont SJ. Genetic Analysis of a Commercial Egg Laying Line Challenged With Newcastle Disease Virus. Front Genet 2018; 9:326. [PMID: 30177951 PMCID: PMC6110172 DOI: 10.3389/fgene.2018.00326] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 07/30/2018] [Indexed: 01/17/2023] Open
Abstract
In low income countries, chickens play a vital role in daily life. They provide a critical source of protein through egg production and meat. Newcastle disease, caused by avian paramyxovirus type 1, has been ranked as the most devastating disease for scavenging chickens in Africa and Asia. High mortality among flocks infected with velogenic strains leads to a devastating loss of dietary protein and buying power for rural households. Improving the genetic resistance of chickens to Newcastle Disease virus (NDV), in addition to vaccination, is a practical target for improvement of poultry production in low income countries. Because response to NDV has a component of genetic control, it can be influenced through selective breeding. Adding genomic information to a breeding program can increase the amount of genetic progress per generation. In this study, we challenged a commercial egg-laying line with a lentogenic strain of NDV, measured phenotypic responses, collected genotypes, and associated genotypes with phenotypes. Collected phenotypes included viral load at 2 and 6 days post-infection (dpi), antibody levels pre-challenge and 10 dpi, and growth rates pre- and post-challenge. Six suggestive QTL associated with response to NDV and/or growth were identified, including novel and known QTL confirming previously reported associations with related traits. Additionally, previous RNA-seq analysis provided support for several of the genes located in or near the identified QTL. Considering the trend of negative genetic correlation between antibody and Newcastle Disease tolerance (growth under disease) and estimates of moderate to high heritability, we provide evidence that these NDV response traits can be influenced through selective breeding. Producing chickens that perform favorably in challenging environments will ultimately increase the supply of quality protein for human consumption.
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Affiliation(s)
- Kaylee Rowland
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Anna Wolc
- Department of Animal Science, Iowa State University, Ames, IA, United States.,Hy-Line International, Dallas Center, IA, United States
| | - Rodrigo A Gallardo
- School of Veterinary Medicine, University of California, Davis, Davis, CA, United States
| | - Terra Kelly
- School of Veterinary Medicine, University of California, Davis, Davis, CA, United States.,Department of Animal Science, University of California, Davis, Davis, CA, United States
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, Davis, CA, United States
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Susan J Lamont
- Department of Animal Science, Iowa State University, Ames, IA, United States
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Kulibaba RA. The Genetic Structure Specificities of the Population of the Rhode-Island Red Chicken Breed by Quantitative Trait Loci. CYTOL GENET+ 2018. [DOI: 10.3103/s009545271803009x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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14
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Liu JJ, Liang AX, Campanile G, Plastow G, Zhang C, Wang Z, Salzano A, Gasparrini B, Cassandro M, Yang LG. Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo. J Dairy Sci 2017; 101:433-444. [PMID: 29128211 DOI: 10.3168/jds.2017-13246] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2017] [Accepted: 09/13/2017] [Indexed: 01/03/2023]
Abstract
Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.
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Affiliation(s)
- J J Liu
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan, Hubei, China 430070; Hubei Province's Engineering Research Center in Buffalo Breeding and Products, Wuhan, Hubei, China 430070
| | - A X Liang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan, Hubei, China 430070; Hubei Province's Engineering Research Center in Buffalo Breeding and Products, Wuhan, Hubei, China 430070
| | - G Campanile
- Department of Veterinary Medicine and Animal Productions, University of Naples "Federico II", Naples, Italy 80137
| | - G Plastow
- Department of Agricultural, Food, and Nutritional Sciences, University of Alberta, Edmonton, AB, Canada T6G 2C8
| | - C Zhang
- Department of Agricultural, Food, and Nutritional Sciences, University of Alberta, Edmonton, AB, Canada T6G 2C8
| | - Z Wang
- Department of Agricultural, Food, and Nutritional Sciences, University of Alberta, Edmonton, AB, Canada T6G 2C8
| | - A Salzano
- Department of Veterinary Medicine and Animal Productions, University of Naples "Federico II", Naples, Italy 80137
| | - B Gasparrini
- Department of Veterinary Medicine and Animal Productions, University of Naples "Federico II", Naples, Italy 80137
| | - M Cassandro
- Department of Agronomy, Food, Natural Resources, Animal, and Environment, University of Padova, Agripolis, Legnaro, Italy 35020
| | - L G Yang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan, Hubei, China 430070; Hubei Province's Engineering Research Center in Buffalo Breeding and Products, Wuhan, Hubei, China 430070.
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15
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Sell-Kubiak E, Wimmers K, Reyer H, Szwaczkowski T. Genetic aspects of feed efficiency and reduction of environmental footprint in broilers: a review. J Appl Genet 2017; 58:487-498. [PMID: 28342159 PMCID: PMC5655602 DOI: 10.1007/s13353-017-0392-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 01/18/2017] [Accepted: 03/08/2017] [Indexed: 11/28/2022]
Abstract
Currently, optimization of feed efficiency is one of the main challenges in improvement programs of livestock and poultry genetics. The objective of this review is to present the genetic aspects of feed efficiency related traits in meat-type chicken and possible ways to reduce the environmental impact of poultry meat production with effective breeding. Basic measures of feed efficiency are defined and the genetic background of these traits, including a review of heritabilities is described. Moreover, a number of genomic regions and candidate genes determining feed efficiency traits of broilers that were detected over the past decades are described. Classical and genomic selection strategies for feed efficiency in the context of its relationships with other performance traits are discussed as well. Finally, future strategies to improve feed digestibility are described as it is expected that they will decrease wastes and greenhouse gas emission. Further genetic improvement of feed efficiency, should be examined jointly with appropriate feeding strategies in broilers.
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Affiliation(s)
- Ewa Sell-Kubiak
- Departament of Genetics and Animal Breeding, Poznan University of Life Sciences, Wolynska st. 33, 60-637, Poznan, Poland
| | - Klaus Wimmers
- Institute of Genome Biology, Leibniz Institute of Farm Animal Biology, Wilhelm-Stahl-Allee 2, 18196, Dummerstorf, Germany
| | - Henry Reyer
- Institute of Genome Biology, Leibniz Institute of Farm Animal Biology, Wilhelm-Stahl-Allee 2, 18196, Dummerstorf, Germany
| | - Tomasz Szwaczkowski
- Departament of Genetics and Animal Breeding, Poznan University of Life Sciences, Wolynska st. 33, 60-637, Poznan, Poland.
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16
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Ren J, Du X, Zeng T, Chen L, Shen J, Lu L, Hu J. Divergently expressed gene identification and interaction prediction of long noncoding RNA and mRNA involved in duck reproduction. Anim Reprod Sci 2017; 185:8-17. [PMID: 28886878 DOI: 10.1016/j.anireprosci.2017.07.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Revised: 07/14/2017] [Accepted: 07/19/2017] [Indexed: 01/21/2023]
Abstract
Long noncoding RNAs (lncRNAs) and divergently expressed genes exist widely in different tissues of mammals and birds, in which they are involved in various biological processes. However, there is limited information on their role in the regulation of normal biological processes during differentiation, development, and reproduction in birds. In this study, whole transcriptome strand-specific RNA sequencing of the ovary from young ducks (60days), first-laying ducks (160days), and old ducks, i.e., ducks that stopped laying eggs (490days) was performed. The lncRNAs and mRNAs from these ducks were systematically analyzed and identified by duck genome sequencing in the three study groups. The transcriptome from the duck ovary comprised 15,011 protein-coding genes and 2905 lncRNAs; all the lncRNAs were identified as novel long noncoding transcripts. The comparison of transcriptome data from different study groups identified 2240 divergent transcription genes and 135 divergently expressed lncRNAs, which differed among the groups; most of them were significantly downregulated with age. Among the divergent genes, 38 genes were related to the reproductive process and 6 genes were upregulated. Further prediction analysis revealed that 52 lncRNAs were closely correlated with divergent reproductive mRNAs. More importantly, 6 remarkable lncRNAs were correlated significantly with the conversion of the ovary in different phases. Our results aid in the understanding of the divergent transcriptome of duck ovary in different phases and the underlying mechanisms that drive the specificity of protein-coding genes and lncRNAs in duck ovary.
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Affiliation(s)
- Jindong Ren
- College of Animal Science and Technology, Northwest A & F University, No. 21 Xinong Road, Yangling, Shaanxi 712100, PR China; Zhejiang Academy of Agricultural Sciences, No. 198 Shiqiao Road, Hangzhou, Zhejiang 310021, PR China.
| | - Xue Du
- Zhejiang Academy of Agricultural Sciences, No. 198 Shiqiao Road, Hangzhou, Zhejiang 310021, PR China.
| | - Tao Zeng
- Zhejiang Academy of Agricultural Sciences, No. 198 Shiqiao Road, Hangzhou, Zhejiang 310021, PR China.
| | - Li Chen
- Zhejiang Academy of Agricultural Sciences, No. 198 Shiqiao Road, Hangzhou, Zhejiang 310021, PR China.
| | - Junda Shen
- Zhejiang Academy of Agricultural Sciences, No. 198 Shiqiao Road, Hangzhou, Zhejiang 310021, PR China.
| | - Lizhi Lu
- Zhejiang Academy of Agricultural Sciences, No. 198 Shiqiao Road, Hangzhou, Zhejiang 310021, PR China.
| | - Jianhong Hu
- College of Animal Science and Technology, Northwest A & F University, No. 21 Xinong Road, Yangling, Shaanxi 712100, PR China.
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Pértille F, Moreira GCM, Zanella R, Nunes JDRDS, Boschiero C, Rovadoscki GA, Mourão GB, Ledur MC, Coutinho LL. Genome-wide association study for performance traits in chickens using genotype by sequencing approach. Sci Rep 2017; 7:41748. [PMID: 28181508 PMCID: PMC5299454 DOI: 10.1038/srep41748] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Accepted: 12/23/2016] [Indexed: 12/11/2022] Open
Abstract
Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F2 chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs.
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Affiliation(s)
- Fábio Pértille
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Ricardo Zanella
- College of Agronomy and Veterinary Medicine, Veterinary School, University of Passo Fundo, Rio Grande do Sul, Brazil
| | | | - Clarissa Boschiero
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Gregori Alberto Rovadoscki
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Gerson Barreto Mourão
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Luiz Lehmann Coutinho
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
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Xiang T, Christensen OF, Vitezica ZG, Legarra A. Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs. Genet Sel Evol 2016; 48:92. [PMID: 27887565 PMCID: PMC5123321 DOI: 10.1186/s12711-016-0271-4] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 11/15/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Improved performance of crossbred animals is partly due to heterosis. One of the major genetic bases of heterosis is dominance, but it is seldom used in pedigree-based genetic evaluation of livestock. Recently, a trivariate genomic best linear unbiased prediction (GBLUP) model including dominance was developed, which can distinguish purebreds from crossbred animals explicitly. The objectives of this study were: (1) methodological, to show that inclusion of marker-based inbreeding accounts for directional dominance and inbreeding depression in purebred and crossbred animals, to revisit variance components of additive and dominance genetic effects using this model, and to develop marker-based estimators of genetic correlations between purebred and crossbred animals and of correlations of allele substitution effects between breeds; (2) to evaluate the impact of accounting for dominance effects and inbreeding depression on predictive ability for total number of piglets born (TNB) in a pig dataset composed of two purebred populations and their crossbreds. We also developed an equivalent model that makes the estimation of variance components tractable. RESULTS For TNB in Danish Landrace and Yorkshire populations and their reciprocal crosses, the estimated proportions of dominance genetic variance to additive genetic variance ranged from 5 to 11%. Genetic correlations between breeding values for purebred and crossbred performances for TNB ranged from 0.79 to 0.95 for Landrace and from 0.43 to 0.54 for Yorkshire across models. The estimated correlation of allele substitution effects between Landrace and Yorkshire was low for purebred performances, but high for crossbred performances. Predictive ability for crossbred animals was similar with or without dominance. The inbreeding depression effect increased predictive ability and the estimated inbreeding depression parameter was more negative for Landrace than for Yorkshire animals and was in between for crossbred animals. CONCLUSIONS Methodological developments led to closed-form estimators of inbreeding depression, variance components and correlations that can be easily interpreted in a quantitative genetics context. Our results confirm that genetic correlations of breeding values between purebred and crossbred performances within breed are positive and moderate. Inclusion of dominance in the GBLUP model does not improve predictive ability for crossbred animals, whereas inclusion of inbreeding depression does.
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Affiliation(s)
- Tao Xiang
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark. .,UR1388 GenPhySE, INRA, CS-52627, 31326, Castanet-Tolosan, France.
| | - Ole Fredslund Christensen
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark
| | | | - Andres Legarra
- UR1388 GenPhySE, INRA, CS-52627, 31326, Castanet-Tolosan, France
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19
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Xiang T, Nielsen B, Su G, Legarra A, Christensen OF. Application of single-step genomic evaluation for crossbred performance in pig1. J Anim Sci 2016; 94:936-48. [DOI: 10.2527/jas.2015-9930] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Affiliation(s)
- T. Xiang
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark
- INRA, UR1388 GenPhyse, CS-52627, F-31326 Castanet-Tolosan, France
| | - B. Nielsen
- SEGES, Pig Research Centre, DK-1609 Copenhagen, Denmark
| | - G. Su
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark
| | - A. Legarra
- INRA, UR1388 GenPhyse, CS-52627, F-31326 Castanet-Tolosan, France
| | - O. F. Christensen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark
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20
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Schmid M, Smith J, Burt DW, Aken BL, Antin PB, Archibald AL, Ashwell C, Blackshear PJ, Boschiero C, Brown CT, Burgess SC, Cheng HH, Chow W, Coble DJ, Cooksey A, Crooijmans RPMA, Damas J, Davis RVN, de Koning DJ, Delany ME, Derrien T, Desta TT, Dunn IC, Dunn M, Ellegren H, Eöry L, Erb I, Farré M, Fasold M, Fleming D, Flicek P, Fowler KE, Frésard L, Froman DP, Garceau V, Gardner PP, Gheyas AA, Griffin DK, Groenen MAM, Haaf T, Hanotte O, Hart A, Häsler J, Hedges SB, Hertel J, Howe K, Hubbard A, Hume DA, Kaiser P, Kedra D, Kemp SJ, Klopp C, Kniel KE, Kuo R, Lagarrigue S, Lamont SJ, Larkin DM, Lawal RA, Markland SM, McCarthy F, McCormack HA, McPherson MC, Motegi A, Muljo SA, Münsterberg A, Nag R, Nanda I, Neuberger M, Nitsche A, Notredame C, Noyes H, O'Connor R, O'Hare EA, Oler AJ, Ommeh SC, Pais H, Persia M, Pitel F, Preeyanon L, Prieto Barja P, Pritchett EM, Rhoads DD, Robinson CM, Romanov MN, Rothschild M, Roux PF, Schmidt CJ, Schneider AS, Schwartz MG, Searle SM, Skinner MA, Smith CA, Stadler PF, Steeves TE, Steinlein C, Sun L, Takata M, Ulitsky I, Wang Q, Wang Y, Warren WC, Wood JMD, Wragg D, Zhou H. Third Report on Chicken Genes and Chromosomes 2015. Cytogenet Genome Res 2015; 145:78-179. [PMID: 26282327 PMCID: PMC5120589 DOI: 10.1159/000430927] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Michael Schmid
- Department of Human Genetics, University of Würzburg, Würzburg, Germany
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21
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Xiang T, Ma P, Ostersen T, Legarra A, Christensen OF. Imputation of genotypes in Danish purebred and two-way crossbred pigs using low-density panels. Genet Sel Evol 2015; 47:54. [PMID: 26122927 PMCID: PMC4486706 DOI: 10.1186/s12711-015-0134-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Accepted: 06/13/2015] [Indexed: 01/30/2023] Open
Abstract
Background Genotype imputation is commonly used as an initial step in genomic selection since the accuracy of genomic selection does not decline if accurately imputed genotypes are used instead of actual genotypes but for a lower cost. Performance of imputation has rarely been investigated in crossbred animals and, in particular, in pigs. The extent and pattern of linkage disequilibrium differ in crossbred versus purebred animals, which may impact the performance of imputation. In this study, first we compared different scenarios of imputation from 5 K to 8 K single nucleotide polymorphisms (SNPs) in genotyped Danish Landrace and Yorkshire and crossbred Landrace-Yorkshire datasets and, second, we compared imputation from 8 K to 60 K SNPs in genotyped purebred and simulated crossbred datasets. All imputations were done using software Beagle version 3.3.2. Then, we investigated the reasons that could explain the differences observed. Results Genotype imputation performs as well in crossbred animals as in purebred animals when both parental breeds are included in the reference population. When the size of the reference population is very large, it is not necessary to use a reference population that combines the two breeds to impute the genotypes of purebred animals because a within-breed reference population can provide a very high level of imputation accuracy (correct rate ≥ 0.99, correlation ≥ 0.95). However, to ensure that similar imputation accuracies are obtained for crossbred animals, a reference population that combines both parental purebred animals is required. Imputation accuracies are higher when a larger proportion of haplotypes are shared between the reference population and the validation (imputed) populations. Conclusions The results from both real data and pedigree-based simulated data demonstrate that genotype imputation from low-density panels to medium-density panels is highly accurate in both purebred and crossbred pigs. In crossbred pigs, combining the parental purebred animals in the reference population is necessary to obtain high imputation accuracy. Electronic supplementary material The online version of this article (doi:10.1186/s12711-015-0134-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tao Xiang
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, DK-8830, Denmark. .,INRA, UR1388 GenPhySE, CS-52627, Castanet-Tolosan, F-31326, France.
| | - Peipei Ma
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, DK-8830, Denmark.
| | - Tage Ostersen
- Pig Research Centre, Danish Agricultural and Food Council, Copenhagen, DK-1609, Denmark.
| | - Andres Legarra
- INRA, UR1388 GenPhySE, CS-52627, Castanet-Tolosan, F-31326, France.
| | - Ole F Christensen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, DK-8830, Denmark.
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22
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Felipe VPS, Silva MA, Valente BD, Rosa GJM. Using multiple regression, Bayesian networks and artificial neural networks for prediction of total egg production in European quails based on earlier expressed phenotypes. Poult Sci 2015; 94:772-80. [PMID: 25713397 DOI: 10.3382/ps/pev031] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The prediction of total egg production (TEP) potential in poultry is an important task to aid optimized management decisions in commercial enterprises. The objective of the present study was to compare different modeling approaches for prediction of TEP in meat type quails (Coturnix coturnix coturnix) using phenotypes such as weight, weight gain, egg production and egg quality measurements. Phenotypic data on 30 traits from two lines (L1, n=180; and L2, n=205) of quail were modeled to predict TEP. Prediction models included multiple linear regression and artificial neural network (ANN). Moreover, Bayesian network (BN) and a stepwise approach were used as variable selection methods. BN results showed that TEP is independent from other earlier expressed traits when conditioned on egg production from 35 to 80 days of age (EP1). In addition, the prediction accuracy was much lower when EP1 was not included in the model. The best predictive model was ANN, after feature selection, showing prediction correlations of r=0.792 and r=0.714 for L1 and L2, respectively. In conclusion, machine learning methods may be useful, but reasonable prediction accuracies are obtained only when partial egg production measurements are included in the model.
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Affiliation(s)
- Vivian P S Felipe
- Department of Animal Sciences, University of Wisconsin - Madison, Wisconsin 53706
| | - Martinho A Silva
- Department of Animal Sciences, Federal University of Jequitinhonha and Mucuri Valleys, Minas Gerais - Brazil
| | - Bruno D Valente
- Department of Animal Sciences, University of Wisconsin - Madison, Wisconsin 53706
| | - Guilherme J M Rosa
- Department of Animal Sciences, University of Wisconsin - Madison, Wisconsin 53706
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Evaluation of measures of correctness of genotype imputation in the context of genomic prediction: a review of livestock applications. Animal 2014; 8:1743-53. [PMID: 25045914 DOI: 10.1017/s1751731114001803] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
In livestock, many studies have reported the results of imputation to 50k single nucleotide polymorphism (SNP) genotypes for animals that are genotyped with low-density SNP panels. The objective of this paper is to review different measures of correctness of imputation, and to evaluate their utility depending on the purpose of the imputed genotypes. Across studies, imputation accuracy, computed as the correlation between true and imputed genotypes, and imputation error rates, that counts the number of incorrectly imputed alleles, are commonly used measures of imputation correctness. Based on the nature of both measures and results reported in the literature, imputation accuracy appears to be a more useful measure of the correctness of imputation than imputation error rates, because imputation accuracy does not depend on minor allele frequency (MAF), whereas imputation error rate depends on MAF. Therefore imputation accuracy can be better compared across loci with different MAF. Imputation accuracy depends on the ability of identifying the correct haplotype of a SNP, but many other factors have been identified as well, including the number of genotyped immediate ancestors, the number of animals with genotypes at the high-density panel, the SNP density on the low- and high-density panel, the MAF of the imputed SNP and whether imputed SNP are located at the end of a chromosome or not. Some of these factors directly contribute to the linkage disequilibrium between imputed SNP and SNP on the low-density panel. When imputation accuracy is assessed as a predictor for the accuracy of subsequent genomic prediction, we recommend that: (1) individual-specific imputation accuracies should be used that are computed after centring and scaling both true and imputed genotypes; and (2) imputation of gene dosage is preferred over imputation of the most likely genotype, as this increases accuracy and reduces bias of the imputed genotypes and the subsequent genomic predictions.
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25
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Christensen OF, Madsen P, Nielsen B, Su G. Genomic evaluation of both purebred and crossbred performances. Genet Sel Evol 2014; 46:23. [PMID: 24666469 PMCID: PMC3994295 DOI: 10.1186/1297-9686-46-23] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Accepted: 02/24/2014] [Indexed: 11/14/2022] Open
Abstract
Background For a two-breed crossbreeding system, Wei and van der Werf presented a model for genetic evaluation using information from both purebred and crossbred animals. The model provides breeding values for both purebred and crossbred performances. Genomic evaluation incorporates marker genotypes into a genetic evaluation system. Among popular methods are the so-called single-step methods, in which marker genotypes are incorporated into a traditional animal model by using a combined relationship matrix that extends the marker-based relationship matrix to non-genotyped animals. However, a single-step method for genomic evaluation of both purebred and crossbred performances has not been developed yet. Results An extension of the Wei and van der Werf model that incorporates genomic information is presented. The extension consists of four steps: (1) the Wei van der Werf model is reformulated using two partial relationship matrices for the two breeds; (2) marker-based partial relationship matrices are constructed; (3) marker-based partial relationship matrices are adjusted to be compatible to pedigree-based partial relationship matrices and (4) combined partial relationship matrices are constructed using information from both pedigree and marker genotypes. The extension of the Wei van der Werf model can be implemented using software that allows inverse covariance matrices in sparse format as input. Conclusions A method for genomic evaluation of both purebred and crossbred performances was developed for a two-breed crossbreeding system. The method allows information from crossbred animals to be incorporated in a coherent manner for such crossbreeding systems.
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Affiliation(s)
- Ole F Christensen
- Aarhus University, Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Blichers Allé 20, P,O, BOX 50, DK-8830 Tjele, Denmark.
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Dhama K, Singh R, Karthik K, Chakrabort S, Tiwari R, Wani M, Mohan J. Artificial Insemination in Poultry and Possible Transmission of Infectious
Pathogens: A Review. ACTA ACUST UNITED AC 2014. [DOI: 10.3923/ajava.2014.211.228] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Stock KF, Reents R. Genomic selection: Status in different species and challenges for breeding. Reprod Domest Anim 2014; 48 Suppl 1:2-10. [PMID: 23962210 DOI: 10.1111/rda.12201] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Technical advances and development in the market for genomic tools have facilitated access to whole-genome data across species. Building-up on the acquired knowledge of the genome sequences, large-scale genotyping has been optimized for broad use, so genotype information can be routinely used to predict genetic merit. Genomic selection (GS) refers to the use of aggregates of estimated marker effects as predictors which allow improved individual differentiation at young age. Realizable benefits of GS are influenced by several factors and vary in quantity and quality between species. General characteristics and challenges of GS in implementation and routine application are described, followed by an overview over the current status of its use, prospects and challenges in important animal species. Genetic gain for a particular trait can be enhanced by shortening of the generation interval, increased selection accuracy and increased selection intensity, with species- and breed-specific relevance of the determinants. Reliable predictions based on genetic marker effects require assembly of a reference for linking of phenotype and genotype data to allow estimation and regular re-estimation. Experiences from dairy breeding have shown that international collaboration can set the course for fast and successful implementation of innovative selection tools, so genomics may significantly impact the structures of future breeding and breeding programmes. Traits of great and increasing importance, which were difficult to improve in the conventional systems, could be emphasized, if continuous availability of high-quality phenotype data can be assured. Equally elaborate strategies for genotyping and phenotyping will allow tailored approaches to balance efficient animal production, sustainability, animal health and welfare in future.
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Affiliation(s)
- K F Stock
- Vereinigte Informationssysteme Tierhaltung w.V. (vit), Verden, Germany.
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Fulton JE. The value of resequence data for poultry breeding: a primary layer breeder perspective. Poult Sci 2014; 93:494-7. [PMID: 24570474 DOI: 10.3382/ps.2013-03556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Poultry breeding companies are facing a new paradigm. Since 2004, extensive resources have been developed to increase understanding of the fundamental biology of the chicken. The chicken genome has been sequenced and revised twice, millions of novel DNA variants have been identified, and new tools have been created that allow rapid and inexpensive detection of these DNA variations. These developments have led to the establishment of molecular-based breeding programs within major poultry breeding companies that are revolutionizing the primary poultry breeding industries. Costs of sequencing continue to drop and are predicted to eventually reach the point where it is feasible to sequence the entire genome of elite birds before selection. There are multiple challenges to be resolved before this information can be fully incorporated into a breeding program. These include handling and analyzing the extremely large data sets generated, understanding which genes, variants, or both are relevant for commercial production traits, development of new bio-informatic tools, and integration of molecular information with traditional breeding programs. The novel variation identified within elite commercial lines will lead to enhancements in commercial breeding programs. Applications of this information include whole genomic selection, parentage identification, trait association studies, and quality control.
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Affiliation(s)
- Janet E Fulton
- Hy-Line International, PO Box 310, Dallas Center, IA 50063
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Morota G, Abdollahi-Arpanahi R, Kranis A, Gianola D. Genome-enabled prediction of quantitative traits in chickens using genomic annotation. BMC Genomics 2014; 15:109. [PMID: 24502227 PMCID: PMC3922252 DOI: 10.1186/1471-2164-15-109] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2013] [Accepted: 02/04/2014] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Genome-wide association studies have been deemed successful for identifying statistically associated genetic variants of large effects on complex traits. Past studies have found enrichment of trait-associated SNPs in functionally annotated regions, while depletion was reported for intergenic regions (IGR). However, no systematic examination of connections between genomic regions and predictive ability of complex phenotypes has been carried out. RESULTS In this study, we partitioned SNPs based on their annotation to characterize genomic regions that deliver low and high predictive power for three broiler traits in chickens using a whole-genome approach. Additive genomic relationship kernels were constructed for each of the genic regions considered, and a kernel-based Bayesian ridge regression was employed as prediction machine. We found that the predictive performance for ultrasound area of breast meat from using genic regions marked by SNPs was consistently better than that from SNPs in IGR, while IGR tagged by SNPs were better than the genic regions for body weight and hen house egg production. We also noted that predictive ability delivered by the whole battery of markers was close to the best prediction achieved by one of the genomic regions. CONCLUSIONS Whole-genome regression methods use all available quality filtered SNPs into a model, contrary to accommodating only validated SNPs from exonic or coding regions. Our results suggest that, while differences among genomic regions in terms of predictive ability were observed, the whole-genome approach remains as a promising tool if interest is on prediction of complex traits.
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Affiliation(s)
- Gota Morota
- Department of Animal Sciences, University of Wisconsin-Madison, Wisconsin, USA.
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Van Eenennaam AL, Weigel KA, Young AE, Cleveland MA, Dekkers JCM. Applied animal genomics: results from the field. Annu Rev Anim Biosci 2013; 2:105-39. [PMID: 25384137 DOI: 10.1146/annurev-animal-022513-114119] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Genomic selection (GS) is the use of statistical methods to estimate the genetic merit of a genotyped animal based on prediction equations derived from large ancestral populations with both phenotypes and genotypes. It has revolutionized the dairy cattle breeding industry and has been implemented with varying degrees of success in other animal breeding programs, including swine, poultry, and beef cattle. The findings of empirical field studies applying GS to the breeding sectors of these main animal protein industries are reviewed. Several translational considerations must be addressed before implementing GS in genetic improvement programs. These include determining and obtaining economically relevant phenotypes and determining the optimal size of the training population, cost-effective genotyping strategies, the practicality of field implementation, and the relative costs versus the benefits of the realized rate of genetic gain. GS may additionally change the optimal breeding scheme design, and studies that address this consideration are also reviewed briefly.
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Sodhi SS, Jeong DK, Sharma N, Lee JH, Kim JH, Kim SH, Kim SW, Oh SJ. Marker Assisted Selection-Applications and Evaluation for Commercial Poultry Breeding. ACTA ACUST UNITED AC 2013. [DOI: 10.5536/kjps.2013.40.3.223] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Frésard L, Morisson M, Brun JM, Collin A, Pain B, Minvielle F, Pitel F. Epigenetics and phenotypic variability: some interesting insights from birds. Genet Sel Evol 2013; 45:16. [PMID: 23758635 PMCID: PMC3693910 DOI: 10.1186/1297-9686-45-16] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2012] [Accepted: 04/26/2013] [Indexed: 11/14/2022] Open
Abstract
Little is known about epigenetic mechanisms in birds with the exception of the phenomenon of dosage compensation of sex chromosomes, although such mechanisms could be involved in the phenotypic variability of birds, as in several livestock species. This paper reviews the literature on epigenetic mechanisms that could contribute significantly to trait variability in birds, and compares the results to the existing knowledge of epigenetic mechanisms in mammals. The main issues addressed in this paper are: (1) Does genomic imprinting exist in birds? (2) How does the embryonic environment influence the adult phenotype in avian species? (3) Does the embryonic environment have an impact on phenotypic variability across several successive generations? The potential for epigenetic studies to improve the performance of individual animals through the implementation of limited changes in breeding conditions or the addition of new parameters in selection models is still an open question.
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Affiliation(s)
- Laure Frésard
- INRA, UMR444, Laboratoire de Génétique Cellulaire, Castanet-Tolosan F-31326, France
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Cheng HH, Kaiser P, Lamont SJ. Integrated Genomic Approaches to Enhance Genetic Resistance in Chickens. Annu Rev Anim Biosci 2013; 1:239-60. [DOI: 10.1146/annurev-animal-031412-103701] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Hans H. Cheng
- Avian Disease and Oncology Laboratory, USDA, ARS, East Lansing, Michigan 48823;
| | - Pete Kaiser
- The Roslin Institute & Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, United Kingdom;
| | - Susan J. Lamont
- Department of Animal Science, Iowa State University, Ames, Iowa 50011;
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Association of single nucleotide polymorphism of RB1 gene with body weight traits in chicken. YI CHUAN = HEREDITAS 2012; 34:1320-7. [DOI: 10.3724/sp.j.1005.2012.01320] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Aslam ML, Bastiaansen JWM, Elferink MG, Megens HJ, Crooijmans RPMA, Blomberg LA, Fleischer RC, Van Tassell CP, Sonstegard TS, Schroeder SG, Groenen MAM, Long JA. Whole genome SNP discovery and analysis of genetic diversity in Turkey (Meleagris gallopavo). BMC Genomics 2012; 13:391. [PMID: 22891612 PMCID: PMC3496629 DOI: 10.1186/1471-2164-13-391] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2012] [Accepted: 08/09/2012] [Indexed: 11/23/2022] Open
Abstract
Background The turkey (Meleagris gallopavo) is an important agricultural species and the second largest contributor to the world’s poultry meat production. Genetic improvement is attributed largely to selective breeding programs that rely on highly heritable phenotypic traits, such as body size and breast muscle development. Commercial breeding with small effective population sizes and epistasis can result in loss of genetic diversity, which in turn can lead to reduced individual fitness and reduced response to selection. The presence of genomic diversity in domestic livestock species therefore, is of great importance and a prerequisite for rapid and accurate genetic improvement of selected breeds in various environments, as well as to facilitate rapid adaptation to potential changes in breeding goals. Genomic selection requires a large number of genetic markers such as e.g. single nucleotide polymorphisms (SNPs) the most abundant source of genetic variation within the genome. Results Alignment of next generation sequencing data of 32 individual turkeys from different populations was used for the discovery of 5.49 million SNPs, which subsequently were used for the analysis of genetic diversity among the different populations. All of the commercial lines branched from a single node relative to the heritage varieties and the South Mexican turkey population. Heterozygosity of all individuals from the different turkey populations ranged from 0.17-2.73 SNPs/Kb, while heterozygosity of populations ranged from 0.73-1.64 SNPs/Kb. The average frequency of heterozygous SNPs in individual turkeys was 1.07 SNPs/Kb. Five genomic regions with very low nucleotide variation were identified in domestic turkeys that showed state of fixation towards alleles different than wild alleles. Conclusion The turkey genome is much less diverse with a relatively low frequency of heterozygous SNPs as compared to other livestock species like chicken and pig. The whole genome SNP discovery study in turkey resulted in the detection of 5.49 million putative SNPs compared to the reference genome. All commercial lines appear to share a common origin. Presence of different alleles/haplotypes in the SM population highlights that specific haplotypes have been selected in the modern domesticated turkey.
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Affiliation(s)
- Muhammad L Aslam
- Animal Breeding and Genomics Centre, Wageningen University, De Elst 1, 6708WD Wageningen, The Netherlands.
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Rodenburg T, Turner S. The role of breeding and genetics in the welfare of farm animals. Anim Front 2012. [DOI: 10.2527/af.2012-0044] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- T.B. Rodenburg
- Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700 AH Wageningen, The Netherlands
| | - S.P. Turner
- Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, United Kingdom
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Affiliation(s)
| | - Andrea Rosati
- European Federation of Animal Science, 00161 Rome, Italy
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