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Wen Z, Cai X, Liu Z, Tan L, Kong Y, Wang Y, Zhao Y. Genomic analyses reveal a lack of widespread strong selection in indigenous chickens. Poult Sci 2025; 104:105081. [PMID: 40138972 PMCID: PMC11985164 DOI: 10.1016/j.psj.2025.105081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2024] [Revised: 03/19/2025] [Accepted: 03/20/2025] [Indexed: 03/29/2025] Open
Abstract
The study of domestication has been revolutionized with the advent of molecular genetics. Chickens, with their clear domestication history, emerge as an excellent model for study into the paths of evolution in domestication and improvement. Here we used genomic data from wild, indigenous, and commercial chickens to better understand how genetic drift and selection translate into their differentiations. Our investigation into the patterns of allelic change and divergence reveals a polygenic architecture governing genetic differentiation during domestication and improvement. We uncover distinctive population-specific differentiations in terms of genes and functions among wild, indigenous, and commercial chickens. Using Runs Of Homozygosity (ROH) based mixed model approach developed in this study, we identified only directional selection signatures occurring in wild and commercial chickens. Notably, our findings suggest that indigenous chickens serve as reservoirs of genetic diversity, necessary for rapid adaptation to new environments or subsequent modern breeding. This work provides unprecedented insights into the chicken domestication and improvement, and it illuminates our understanding of the domestication of other animal species.
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Affiliation(s)
- Zilong Wen
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Xinyu Cai
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Zexuan Liu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Lizhi Tan
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Yuan Kong
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Yuzhan Wang
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Yiqiang Zhao
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China; National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, Beijing 100193, China.
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Kong Y, Wen Z, Cai X, Tan L, Liu Z, Wang Q, Li Q, Yang N, Wang Y, Zhao Y. Genetic traceability, conservation effectiveness, and selection signatures analysis based on ancestral information: a case study of Beijing-You chicken. BMC Genomics 2025; 26:402. [PMID: 40275158 PMCID: PMC12023635 DOI: 10.1186/s12864-025-11563-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2025] [Accepted: 04/02/2025] [Indexed: 04/26/2025] Open
Abstract
BACKGROUND Genetic resources are essential components of biodiversity. As national strategy, the conservation of genetic resources is crucial not only for biodiversity but also for sustainable agriculture and cultural heritage. However, the exact origin of most local breeds remains unclear at the genomic level. The conservation efforts are becoming more challenging as local breeds are currently experiencing genetic drift and admixture, which may be further complicated by historical hybridizations. A typical example is the Beijing-You chicken, a local breed renowned for its excellent meat flavor and unique appearance. With a relatively recent history (~ 300 years), it displays mixed phenotypes which may have resulted from genomic admixture, with its exact origin yet to be determined. RESULTS Through comprehensive genomic similarity analysis, we identified 12 genetic donor breeds for the Beijing-You chicken and quantified their genetic contributions, with the highest ancestry proportion coming from Henan chickens. The local ancestry components and genomic structure analyses of the Beijing-You chicken suggest recent hybridization in the formation of this breed. Furthermore, we innovatively used ancestry components as new material for genetic evaluation and selection signature detection, demonstrating that conservation efforts over the past decade have been effective. Analysis of selection signatures revealed genes and regions associated with polydactyly, egg production, intramuscular fat, and spermatogenesis. CONCLUSIONS By integrating various analytical strategies, we developed a novel framework for genetic traceability and evaluation. Our results highlight the effectiveness of ancestry components in genetic assessment and offer valuable insights for the conservation, improvement, and sustainable utilization of local breeds.
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Affiliation(s)
- Yuan Kong
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Zilong Wen
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Xinyu Cai
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Lizhi Tan
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Zexuan Liu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Qiao Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences of Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qinghe Li
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences of Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yuzhan Wang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
- National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, Beijing, 100193, China.
| | - Yiqiang Zhao
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China.
- National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, Beijing, 100193, China.
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Zhao J, Wang Y, Kamalibieke J, Gong P, Zhang F, Shi H, Wang W, Luo J. Design and verification of a 25 K multiple-SNP liquid-capture chip by target sequencing for dairy goat. BMC Genomics 2025; 26:377. [PMID: 40234771 PMCID: PMC12001634 DOI: 10.1186/s12864-025-11576-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2024] [Accepted: 04/07/2025] [Indexed: 04/17/2025] Open
Abstract
BACKGROUND In the genetic breeding research of dairy goats, traditional genotyping methods have limitations, and existing goat chips have shortcomings in functional loci and other aspects, which cannot meet the precise genetic analysis needs of dairy goats. Genotyping by Target Sequencing (GBTS) in the new generation of sequencing technology provides the possibility to solve these problems. RESULTS A large number of candidate SNP sites related to important economic traits in dairy goats were identified through various analysis and screening methods. The chip ultimately retained 27,396 SNP sites for probe design, which can detect 46,459 SNPs. The site distribution is uniform, and the sequencing data efficiency, base quality, alignment rate, and other indicators are good. The chip SNP detection rate is high and the heterozygosity of gene typing is reasonable. GWAS was performed on 200 dairy goats for litter size and birth weight traits, and multiple genome-wide significantly related SNPs and related genes (litter size trait: SCAP, PTPN23, KIF9, ANTXRL, and GRID1. birth weight trait: NALCN, LRRN2, TMEM132D, COL5A2, and HS3ST1) were detected. CONCLUSION The 25 K multiplex SNP liquid phase capture chip designed in this study has excellent performance and is of great value for genetic research and breeding of dairy goats, providing strong support for the development of the dairy goat industry.
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Affiliation(s)
- Jianqing Zhao
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Yaling Wang
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Jiayidaer Kamalibieke
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Ping Gong
- Institute of Animal Husbandry Quality Standards, Xinjiang Academy of Animal Sciences, Urumqi, Xinjiang, China
| | - Fuhong Zhang
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Huaiping Shi
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Wei Wang
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Jun Luo
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China.
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Castellano D, Vourlaki IT, Gutenkunst RN, Ramos-Onsins SE. Detection of domestication signals through the analysis of the full distribution of fitness effects. PEER COMMUNITY JOURNAL 2025; 5:e35. [PMID: 40256351 PMCID: PMC12007895 DOI: 10.24072/pcjournal.540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/22/2025]
Abstract
Domestication is a process marked by complex interactions between demographic changes and selective pressures, which together shape genetic diversity. While the phenotypic outcomes of domestication are well documented, its genetic basis-particularly the dynamics of selection-remain less well understood. To investigate these dynamics, we performed simulations designed to approximate the demographic history of large domestic mammals. These simulations used selection coefficients as a modeling tool to represent changes in selection pressures, recognizing that such coefficients are abstractions rather than direct representations of biological reality. Specifically, we analyzed site frequency spectra (SFS) under varying distributions of fitness effects (DFE) and proportions of mutations with divergent selective pressures. Our results show that the discretized deleterious DFE can be reliably inferred from the SFS of a single population, but reconstructing the beneficial DFE and demographic history remains challenging, even when using the joint SFS of both populations. We further developed a novel joint DFE inference model to estimate the proportion of mutations with divergent selection coefficients (p c), although we found that signals of classic hard sweeps can mimic increases in p c, complicating interpretation. These findings underscore both the utility and limitations of DFE inference and highlight the need for caution when interpreting demographic histories in domesticated populations based on such modeling assumptions.
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Affiliation(s)
- David Castellano
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
| | - Ioanna-Theoni Vourlaki
- Centre for Research in Agricultural Genomics (CRAG, CSIC-IRTA-UAB-UB), Campus UAB, Vall de la Moronta s/n, Cerdanyola del Valles, Barcelona, 08193, Spain
- Animal Breeding and Genetics Program, IRTA, Torre Marimón, 08140 Caldes de Montbui, Barcelona, Spain
| | - Ryan N Gutenkunst
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
| | - Sebastian E Ramos-Onsins
- Centre for Research in Agricultural Genomics (CRAG, CSIC-IRTA-UAB-UB), Campus UAB, Vall de la Moronta s/n, Cerdanyola del Valles, Barcelona, 08193, Spain
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Zhang X, Yang F, Zhang J, Zhu T, Zhao X, Liu Y, Wen J, Gu H, Wang G, Ren X, Chen A, Qu L. Genomic variation responding to artificial selection on different lines of Pekin duck. Poult Sci 2025; 104:104785. [PMID: 39813863 PMCID: PMC11783388 DOI: 10.1016/j.psj.2025.104785] [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: 10/22/2024] [Revised: 12/20/2024] [Accepted: 01/05/2025] [Indexed: 01/18/2025] Open
Abstract
Understanding the genomic variation in Pekin duck under artificial selection is important for improving the utilization of duck genetic resources. Here, the genomic changes in Pekin duck were analyzed by using the genome resequencing data from 96 individual samples, including 2 conservation populations and 4 breeding populations with different breeding backgrounds. The population structure, runs of homozygosity (ROH), effective population number (Ne), and other genetic parameters were analyzed. The breeding populations showed lower genetic diversity compared to the conservation populations. Maple Leaf duck and Cherry Valley duck retained low genetic diversity compared to other breeding populations, with Cherry Valley duck showing the lowest diversity and the highest inbreeding coefficient. This suggested that Cherry Valley and Maple Leaf ducks have undergone intensive selection compared to other breeding populations. By the analysis of runs of homozygosity (ROHs), some genes (e.g., IGF1R) associated with growth traits were identified. By the analysis of the selection signal, strong selection characteristics in certain genomic regions during the breeding of Peking duck across different selected lines were observed. In addition, copy number variations (CNVs) in Pekin duck populations were analyzed. Six regions of interest were identified, containing RPA1, DOT1L, SLC25A42, RALYL, TRPA1, and IGFBP2. Furthermore, the allele frequency distribution of these genes showed significant differences between breeding populations and conservation populations, indicating that these candidate genes could have undergone strong selection pressure during long-term selection for improved production. These findings contribute to a deeper understanding of the distinct evolutionary processes in Pekin ducks under artificial selection and provide valuable insights for future breeding strategies.
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Affiliation(s)
- Xinye Zhang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Fangxi Yang
- Beijing Nankou Duck Breeding Technology Co. Ltd., Beijing, China
| | - Jinxin Zhang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Tao Zhu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Xiurong Zhao
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Yuchen Liu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Junhui Wen
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Hongchang Gu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Gang Wang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Xufang Ren
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Anqi Chen
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China
| | - Lujiang Qu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing 100193, China.
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Ashari H, Liu LS, Dagong MIA, Cai ZF, Xie GL, Yin TT, Zhang YP, Han JL, Peng MS. Genome sequencing and assembly of feral chickens in the wild of Sulawesi, Indonesia. Anim Genet 2025; 56:e13497. [PMID: 39710860 DOI: 10.1111/age.13497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 12/01/2024] [Accepted: 12/03/2024] [Indexed: 12/24/2024]
Abstract
The feralization of domestic chicken makes the conservation and management of red jungle fowl (Gallus gallus) more complicated and challenging. We collected two Sulawesi feral chickens, located east of the Wallace Line, for whole-genome sequencing and de novo genome assembly. Phylogenetic and f4-statistics analyses indicated that the Sulawesi feralized domestic chickens (G. g. domesticus) received gene flow from G. g. gallus. We integrated ~45× ultra-long Oxford Nanopore Technology reads and ~28× PacBio HiFi reads to generate a de novo genome assembly of a female Sulawesi feral chicken (GGsula) with a contig N50 of 19.88 Mbp. We characterized structural variations in GGsula, and found some were related to nervous system. Our study provides the first genome assembly of feral chickens, which is a unique genomic resource to explore the process of chicken domestication and feralization.
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Affiliation(s)
- Hidayat Ashari
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Graduate School of Chinese Academy of Agriculture Sciences (CAAS), Beijing, China
- Research Center for Biosystematics and Evolution, National Research and Innovation Agency (BRIN), Bogor, Indonesia
| | - Li-Sheng Liu
- Key Laboratory of Genetic Evolution & Animal Models and Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | | | - Zheng-Fei Cai
- Key Laboratory of Genetic Evolution & Animal Models and Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, China
| | - Guo-Li Xie
- Key Laboratory of Genetic Evolution & Animal Models and Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ting-Ting Yin
- Key Laboratory of Genetic Evolution & Animal Models and Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Ya-Ping Zhang
- Key Laboratory of Genetic Evolution & Animal Models and Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Min-Sheng Peng
- Key Laboratory of Genetic Evolution & Animal Models and Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
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Schöneberg T. Modulating vertebrate physiology by genomic fine-tuning of GPCR functions. Physiol Rev 2025; 105:383-439. [PMID: 39052017 DOI: 10.1152/physrev.00017.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 07/08/2024] [Accepted: 07/20/2024] [Indexed: 07/27/2024] Open
Abstract
G protein-coupled receptors (GPCRs) play a crucial role as membrane receptors, facilitating the communication of eukaryotic species with their environment and regulating cellular and organ interactions. Consequently, GPCRs hold immense potential in contributing to adaptation to ecological niches and responding to environmental shifts. Comparative analyses of vertebrate genomes reveal patterns of GPCR gene loss, expansion, and signatures of selection. Integrating these genomic data with insights from functional analyses of gene variants enables the interpretation of genotype-phenotype correlations. This review underscores the involvement of GPCRs in adaptive processes, presenting numerous examples of how alterations in GPCR functionality influence vertebrate physiology or, conversely, how environmental changes impact GPCR functions. The findings demonstrate that modifications in GPCR function contribute to adapting to aquatic, arid, and nocturnal habitats, influencing camouflage strategies, and specializing in particular dietary preferences. Furthermore, the adaptability of GPCR functions provides an effective mechanism in facilitating past, recent, or ongoing adaptations in animal domestication and human evolution and should be considered in therapeutic strategies and drug development.
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Affiliation(s)
- Torsten Schöneberg
- Rudolf Schönheimer Institute of Biochemistry, Molecular Biochemistry, Medical Faculty, University of Leipzig, Leipzig, Germany
- School of Medicine, University of Global Health Equity, Kigali, Rwanda
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Mogano RR, Mpofu TJ, Mtileni B, Hadebe K. South African indigenous chickens' genetic diversity, and the adoption of ecological niche modelling and landscape genomics as strategic conservation techniques. Poult Sci 2025; 104:104508. [PMID: 39657468 PMCID: PMC11681890 DOI: 10.1016/j.psj.2024.104508] [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: 06/18/2024] [Revised: 10/14/2024] [Accepted: 11/04/2024] [Indexed: 12/12/2024] Open
Abstract
Selection pressures found in the prevailing production environments have shaped the genetic structure of indigenous chickens we see today. Indigenous chickens, raised in villages, provide essential genetic resources and income for poverty alleviation by providing affordable protein. However, they are threatened by predators, emerging diseases, and market demand for ideal breeds and fast production which causes loss of their valuable traits. The lack of knowledge about genetic diversity and genetic mechanisms underlying adaptive variants may compromise the goal of conserving indigenous chicken breeds. The main insights of the study are that indigenous chickens are highly diversified, and environmental factors play a key role in enabling chicken adaptation and distribution. Genomic and spatial technologies have made it possible to explore the genetic structure and fully comprehend the mechanism underlying the local adaptation of indigenous chickens. These technologies can aid in creating programs that enhance productivity and promote climate-resilient breeds. This review explores the impact of natural selection on indigenous chicken, genetic diversity, population size, and the advancement of technologies in understanding local adaptation drivers. In conclusion, this review highlights the importance of studying the habitats and how this will guide in conserving local breeds in their intended production environment.
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Affiliation(s)
- Reneilwe Rose Mogano
- Department of Animal Sciences, Tshwane University of Technology, Pretoria 0001, South Africa; Agricultural Research Council, Biotechnology Platform, Ondersterpoort 0110, South Africa
| | - Takalani Judas Mpofu
- Department of Animal Sciences, Tshwane University of Technology, Pretoria 0001, South Africa
| | - Bohani Mtileni
- Department of Animal Sciences, Tshwane University of Technology, Pretoria 0001, South Africa
| | - Khanyisile Hadebe
- Agricultural Research Council, Biotechnology Platform, Ondersterpoort 0110, South Africa.
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Rostamzadeh Mahdabi E, Esmailizadeh A, Han J, Wang M. Comparative Analysis of Runs of Homozygosity Islands in Indigenous and Commercial Chickens Revealed Candidate Loci for Disease Resistance and Production Traits. Vet Med Sci 2025; 11:e70074. [PMID: 39655377 PMCID: PMC11629026 DOI: 10.1002/vms3.70074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 08/08/2024] [Accepted: 09/20/2024] [Indexed: 12/13/2024] Open
Abstract
Runs of homozygosity (ROH) are contiguous stretches of identical genomic regions inherited from both parents. Assessment of ROH in livestock species contributes significantly to our understanding of genetic health, population genetic structure, selective pressure and conservation efforts. In this study, whole genome re-sequencing data from 140 birds of 10 Iranian indigenous chicken ecotypes, 3 commercial chicken breeds and 1 red junglefowl (RJF) population were used to investigate their population genetic structure, ROH characteristics (length and frequency) and genomic inbreeding coefficients (FROH). Additionally, we examined ROH islands for selection footprints in the indigenous chicken populations. Our results revealed distinct genetic backgrounds, among which the White Leghorn breed exhibited the greatest genetic distance from other populations, while the gamecock populations formed a separate cluster. We observed significant differences in ROH characteristics, in which the commercial breeds showed a higher number of ROH compared to indigenous chickens and red junglefowls. Short ROH ranging from 0.1 to 1 Mb were dominant among the populations. The Arian line had the highest mean length of ROH, while the White Leghorn breed showed the highest number of ROH. Among indigenous chickens, the Lari-Afghani ecotype exhibited the highest FROH, but the Sari inherited the richest genetic diversity. Interestingly, GGA16 carried no ROH in the red junglefowls, whereas GGA22 had the highest FROH across all populations, except in the Isfahan ecotype. We also identified ROH islands associated with genetic adaptations in indigenous ecotypes. These islands harboured immune-related genes contributing to disease resistance (TLR2, TICAM1, IL22RA1, NOS2, CCL20 and IFNLR1), heat tolerance and oxidative stress response (NFKB1, HSF4, OSGIN1 and BDNF), and muscle development, lipid metabolism and reproduction (MEOX2, CEBPB, CDS2 and GnRH-I). Overall, this study highlights the genetic potential of indigenous chickens to survive and adapt to their respective environments.
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Affiliation(s)
| | - Ali Esmailizadeh
- Department of Animal ScienceFaculty of AgricultureShahid Bahonar University of KermanKermanIran
- Key Laboratory of Genetic Evolution & Animal ModelsState Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of ZoologyChinese Academy of SciencesKunmingYunnanChina
| | - Jianlin Han
- CAAS‐ILRI Joint Laboratory on Livestock and Forage Genetic ResourcesInstitute of Animal ScienceChinese Academy of Agricultural Sciences (CAAS)BeijingChina
| | - Ming‐Shan Wang
- Key Laboratory of Genetic Evolution & Animal ModelsState Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of ZoologyChinese Academy of SciencesKunmingYunnanChina
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Rabbani MAG, Vallejo-Trujillo A, Wu Z, Miedzinska K, Faruque S, Watson KA, Smith J. Whole genome sequencing of three native chicken varieties (Common Deshi, Hilly and Naked Neck) of Bangladesh. Sci Data 2024; 11:1432. [PMID: 39719437 DOI: 10.1038/s41597-024-04291-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Accepted: 12/04/2024] [Indexed: 12/26/2024] Open
Abstract
Bangladeshi indigenous chicken varieties - Common Deshi, Hilly and Naked Neck are notable for their egg production, meat quality, extraordinary survivability and disease resistance. However, the potential to harness their unique genetic merits are being eroded by various factors, including crossbreeding. In-depth genomic studies have not been carried out on these breeds so far. To this end, blood samples and associated phenotypic metadata have been collected from local, unimproved birds sampled from 8 different locations across the country, and from Bangladesh Livestock Research Institute (BLRI)-improved chickens of the same mentioned breeds. Whole Genome Sequencing (WGS) of 96 selected samples, representing local and improved populations of each breed, has been carried out. Around 22 M high-quality SNPs have been identified, with 25% of these being novel variants previously undescribed in public databases. This data set will allow for genetic comparison between breeds, and between selected and unimproved birds, providing a resource for genomic selection in Bangladeshi breeding schemes to create more productive and resilient poultry stock.
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Affiliation(s)
- Md Ataul Goni Rabbani
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK.
- Poultry Production Research Division, Bangladesh Livestock Research Institute (BLRI), Savar, Dhaka, 1341, Bangladesh.
| | - Adriana Vallejo-Trujillo
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Zhou Wu
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Katarzyna Miedzinska
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Shakila Faruque
- Poultry Production Research Division, Bangladesh Livestock Research Institute (BLRI), Savar, Dhaka, 1341, Bangladesh
| | - Kellie A Watson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Jacqueline Smith
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
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Deng C, Li M, Wang T, Duan W, Guo A, Ma G, Yang F, Dai F, Li Q. Integrating genomics and transcriptomics to identify candidate genes for high-altitude adaptation and egg production in Nixi chicken. Br Poult Sci 2024; 65:652-664. [PMID: 38922310 DOI: 10.1080/00071668.2024.2367228] [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: 01/30/2024] [Accepted: 05/17/2024] [Indexed: 06/27/2024]
Abstract
1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was analysed by sliding window analysis. The selected genes were screened by combination with the population differentiation statistic (FST). The sequence diversity statistic (θπ). RNA-seq was performed on the ovarian tissues of NXC (n = 6) and Lohmann laying hens (n = 6) to analyse the differentially expressed genes (DEGs) between the two groups. The functional enrichment analysis of the selected genes and differentially expressed genes was performed.3. There were 742 genes under strong positive selection and 509 differentially expressed genes screened in NXC. Integrated analysis of the genome and transcriptome revealing 26 overlapping genes. The candidate genes for adaptation to a high-altitude environment, as well as for egg production, disease resistance, vision and pigmentation in NXC were preliminarily screened.4. The results provided theoretical guidance for further research on the genetic resource protection and utilisation of NXC.
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Affiliation(s)
- C Deng
- College of Biology and Food Engineering, Southwest Forestry University, Kunming, China
| | - M Li
- School of Mathematics and Computer Science, Yunnan Nationalities University, Kunming, China
| | - T Wang
- School of Pharmacy, Chengdu University, Chengdu, China
| | - W Duan
- College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - A Guo
- College of Biology and Food Engineering, Southwest Forestry University, Kunming, China
| | - G Ma
- Agricultural and Rural Bureau of Gejiu County, Honghe, China
| | - F Yang
- Agricultural and Rural Bureau of Gejiu County, Honghe, China
| | - F Dai
- College of Veterinary Medicine, Yunnan Agricultural University, Kunming, China
| | - Q Li
- College of Biology and Food Engineering, Southwest Forestry University, Kunming, China
- Kunming Xianghao Technology Co. Ltd., Kunming, China
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12
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Wu S, Chen Z, Zhou X, Lu J, Tian Y, Jiang Y, Liu Q, Wang Z, Li H, Qu L, Zhang F. Analysis of genetic diversity and genetic structure of indigenous chicken populations in Guizhou province based on genome-wide single nucleotide polymorphism markers. Poult Sci 2024; 103:104383. [PMID: 39447329 PMCID: PMC11539430 DOI: 10.1016/j.psj.2024.104383] [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: 05/24/2024] [Revised: 08/23/2024] [Accepted: 10/01/2024] [Indexed: 10/26/2024] Open
Abstract
Guizhou province in China is rich in indigenous chicken breeds, playing an essential role in the genetic improvement of modern chickens. Genetic diversity has decreased in recent decades due to accelerated breeding processes and changing conservation priorities. To determine the genetic diversity and population structure of Guizhou indigenous chicken breeds, we used 55K genotyping arrays to conduct population genetic analysis on 233 individuals from 8 Guizhou indigenous breeds and 263 individuals from 9 Guizhou indigenous chicken populations. We evaluated the genetic diversity parameter (heterozygosity, proportion of polymorphic markers, and nucleotide diversity), linkage disequilibrium (LD), population structure, and genetic differentiation (FST and genetics distance). Genetic diversity results indicated that the genetic diversity of chicken breeds in Guizhou province is relatively affluent. Among Guizhou breeds, Baiyi black-bone and Guizhou yellow chicken displayed the lowest genetic diversity, as the 2 breeds exhibit lower PN and heterozygosity, the extent of linkage disequilibrium is higher. According to the LD pattern, Guizhou indigenous breeds can be divided into 3 categories. Population structure analysis showed a certain degree of genetic differentiation among local chickens in Guizhou. We argue that Chishui black-bone and Puan black-bone chickens are 2 different geographical regional groups of the same breed. In principal component analysis, individuals from the 2 groups clustered together, and the phylogenetic tree results showed that the 2 groups clustered together to form a branch independent of other breeds, and they displayed an identical pattern of ancestral lineage composition. The research results will provide a reference for protecting local chicken genetic resources in Guizhou Province and promote the protection and utilization of genetic resources.
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Affiliation(s)
- Sheng Wu
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Zhiwen Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Xiaohong Zhou
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Juanhong Lu
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Yingping Tian
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Yaozhou Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Qinsong Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Zhong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Hui Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China
| | - Lujiang Qu
- Department of Animal Genetics and Breeding, State Key Laboratory of Animal Nutrition, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Fuping Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, College of Animal Sciences, Guizhou University, Guiyang, 550025, Guizhou Province, China.
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13
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Liu C, Liu P, Liu S, Guo H, Zhu T, Li W, Wang K, Kang X, Sun G. Genetic structure, selective characterization and specific molecular identity cards of high-yielding Houdan chickens based on genome-wide SNP. Poult Sci 2024; 103:104325. [PMID: 39316988 PMCID: PMC11462333 DOI: 10.1016/j.psj.2024.104325] [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: 05/29/2024] [Revised: 09/04/2024] [Accepted: 09/07/2024] [Indexed: 09/26/2024] Open
Abstract
The high-yielding Houdan chicken (GGF) is characterized by high egg production and disease resistance. This study conducted whole genome resequencing of the GGF population and compared it to data from other breeds. Genetic diversity analysis revealed higher observed heterozygosity (Ho), Polymorphism information content (PIC), number of runs of homozygosity (ROH), and inbreeding coefficient (FROH) in GGF. Linkage disequilibrium (LD) decay was slowest in GGF, indicating intensive inbreeding and strong selection. These findings suggest a need for appropriate strategies to enhance genetic diversity conservation in this breed. Population structure analysis demonstrated that GGF was genetically distinct from both the red jungle fowl (RJF) and Chinese indigenous chicken (CIC) populations, highlighting GGF as a unique genetic resource warranting intensive protection and utilization. Selective sweep analysis identified genes under selection in GGF, primarily enriched in signaling pathways related to oocyte meiosis and progesterone-mediated oocyte maturation. Key candidate genes included: CCNE1, SKP1, CDC20, CDK2, ADCY8, RPS6KA6, PPP3CB, PDE3B, HSP90AB1, and AKT3. These findings provide a theoretical foundation for their potential application in poultry breeding. Additionally, this study combined bioinformatics analysis with PCR amplification and Sanger sequencing to identify 4 SNPs that can serve as a molecular identity card (ID) for GGF: SNP1 (Chr2: 136130976), SNP3 (Chr4:11705164), SNP4 (Chr4: 63255588), and SNP5 (Chr24: 3271008). This study provides a scientific basis for effective management and conservation of GGF genetic resources, and establishes a simple, economical, and accurate set of molecular IDs to combat the proliferation of inferior breeds and protect genetic resources.
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Affiliation(s)
- Cong Liu
- The Shennong Laboratory, Henan Agricultural University, Zhengzhou 450046, China
| | - Pingquan Liu
- Key Laboratory of Livestock and Poultry Resources (Poultry) Evaluation and Utilization of Ministry of Agriculture and Rural Affairs, Henan Agricultural University, Zhengzhou 450046, China
| | - Shuangxing Liu
- Key Laboratory of Livestock and Poultry Resources (Poultry) Evaluation and Utilization of Ministry of Agriculture and Rural Affairs, Henan Agricultural University, Zhengzhou 450046, China
| | - Haishan Guo
- Key Laboratory of Livestock and Poultry Resources (Poultry) Evaluation and Utilization of Ministry of Agriculture and Rural Affairs, Henan Agricultural University, Zhengzhou 450046, China
| | - Tingqi Zhu
- Key Laboratory of Livestock and Poultry Resources (Poultry) Evaluation and Utilization of Ministry of Agriculture and Rural Affairs, Henan Agricultural University, Zhengzhou 450046, China
| | - Wenting Li
- The Shennong Laboratory, Henan Agricultural University, Zhengzhou 450046, China; Key Laboratory of Livestock and Poultry Resources (Poultry) Evaluation and Utilization of Ministry of Agriculture and Rural Affairs, Henan Agricultural University, Zhengzhou 450046, China
| | - Kejun Wang
- The Shennong Laboratory, Henan Agricultural University, Zhengzhou 450046, China
| | - Xiangtao Kang
- The Shennong Laboratory, Henan Agricultural University, Zhengzhou 450046, China
| | - Guirong Sun
- The Shennong Laboratory, Henan Agricultural University, Zhengzhou 450046, China; Key Laboratory of Livestock and Poultry Resources (Poultry) Evaluation and Utilization of Ministry of Agriculture and Rural Affairs, Henan Agricultural University, Zhengzhou 450046, China.
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14
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Gering E, Johnsson M, Theunissen D, Martin Cerezo ML, Steep A, Getty T, Henriksen R, Wright D. Signals of selection and ancestry in independently feral Gallus gallus populations. Mol Ecol 2024; 33:e17336. [PMID: 38553993 DOI: 10.1111/mec.17336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 03/15/2024] [Accepted: 03/20/2024] [Indexed: 10/18/2024]
Abstract
Recent work indicates that feralisation is not a simple reversal of domestication, and therefore raises questions about the predictability of evolution across replicated feral populations. In the present study we compare genes and traits of two independently established feral populations of chickens (Gallus gallus) that inhabit archipelagos within the Pacific and Atlantic regions to test for evolutionary parallelism and/or divergence. We find that feral populations from each region are genetically closer to one another than other domestic breeds, despite their geographical isolation and divergent colonisation histories. Next, we used genome scans to identify genomic regions selected during feralisation (selective sweeps) in two independently feral populations from Bermuda and Hawaii. Three selective sweep regions (each identified by multiple detection methods) were shared between feral populations, and this overlap is inconsistent with a null model in which selection targets are randomly distributed throughout the genome. In the case of the Bermudian population, many of the genes present within the selective sweeps were either not annotated or of unknown function. Of the nine genes that were identifiable, five were related to behaviour, with the remaining genes involved in bone metabolism, eye development and the immune system. Our findings suggest that a subset of feralisation loci (i.e. genomic targets of recent selection in feral populations) are shared across independently established populations, raising the possibility that feralisation involves some degree of parallelism or convergence and the potential for a shared feralisation 'syndrome'.
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Affiliation(s)
- E Gering
- Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, Florida, USA
| | - M Johnsson
- AVIAN Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - D Theunissen
- AVIAN Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | - M L Martin Cerezo
- AVIAN Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | - A Steep
- Genetics and Genome Sciences Program, Michigan State University, East Lansing, Michigan, USA
| | - T Getty
- Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan, USA
| | - R Henriksen
- AVIAN Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | - D Wright
- AVIAN Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
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15
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Wang D, Tan L, Zhi Y, Bu L, Wang Y, Wang Z, Guo Y, Tian W, Xu C, Li D, Li Z, Jiang R, Han R, Li G, Wang Y, Xia D, Tian Y, Dunn IC, Hu X, Li H, Zhao Y, Kang X, Liu X. Genome-wide variation study and inter-tissue communication analysis unveil regulatory mechanisms of egg-laying performance in chickens. Nat Commun 2024; 15:7069. [PMID: 39152103 PMCID: PMC11329784 DOI: 10.1038/s41467-024-50809-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 07/22/2024] [Indexed: 08/19/2024] Open
Abstract
Egg-laying performance is of great economic importance in poultry, but the underlying genetic mechanisms are still elusive. In this work, we conduct a multi-omics and multi-tissue integrative study in hens with distinct egg production, to detect the hub candidate genes and construct hub molecular networks contributing to egg-laying phenotypic differences. We identifiy three hub candidate genes as egg-laying facilitators: TFPI2, which promotes the GnRH secretion in hypothalamic neuron cells; CAMK2D, which promotes the FSHβ and LHβ secretion in pituitary cells; and OSTN, which promotes granulosa cell proliferation and the synthesis of sex steroid hormones. We reveal key endocrine factors involving egg production by inter-tissue crosstalk analysis, and demonstrate that both a hepatokine, APOA4, and an adipokine, ANGPTL2, could increase egg production by inter-tissue communication with hypothalamic-pituitary-ovarian axis. Together, These results reveal the molecular mechanisms of multi-tissue coordinative regulation of chicken egg-laying performance and provide key insights to avian reproductive regulation.
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Affiliation(s)
- Dandan Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang, China
| | - Lizhi Tan
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yihao Zhi
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
| | - Lina Bu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yangyang Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
| | - Zhang Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
| | - Yulong Guo
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
| | - Weihua Tian
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
| | - Chunlin Xu
- Henan Sangao Agriculture and Animal Husbandry Co, Ltd, Gushi, China
| | - Donghua Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China
| | - Zhuanjian Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China
| | - Ruirui Jiang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China
| | - Ruili Han
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China
| | - Guoxi Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China
| | - Yongqiang Wang
- College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang, China
| | - Dong Xia
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK
| | - Yadong Tian
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China
| | - Ian C Dunn
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Xiaoxiang Hu
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Hong Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China.
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China.
| | - Yiqiang Zhao
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China.
| | - Xiangtao Kang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China.
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China.
| | - Xiaojun Liu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China.
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China.
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16
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Mazocco CC, de Castro Júnior SL, Silveira RMF, Poletto R, da Silva IJO. Laying Hens: Why Smothering and Not Surviving?-A Literature Review. Animals (Basel) 2024; 14:1518. [PMID: 38891565 PMCID: PMC11171085 DOI: 10.3390/ani14111518] [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: 02/14/2024] [Revised: 04/12/2024] [Accepted: 04/15/2024] [Indexed: 06/21/2024] Open
Abstract
The proliferation of rearing systems providing opportunities for birds to engage in natural behaviors can trigger behavioral repertoires that when not manageable compromise animal welfare and the economic viability of the flock. Smothering in laying hens has long been perceived as "natural" or the result of hysteria among birds in the flock. However, the current literature has recognized smothering as an abnormal outcome with the potential to result in significant losses in cage-free poultry systems. Recent studies have specifically aimed to categorize the organization of smothering behavior and highlight its potential causes and consequences. In this study, literature review and bibliographic mapping, drawing on published articles and engagement with poultry farmers through extension and rural technical assistance, were employed. The findings indicate that smothering is a behavior triggered by factors related to the environment in which the laying hens are kept. This study concludes that there is a critical need for more rigorous and detailed research to elucidate the nuances of avian behavioral physiology and assess the impact of production systems on animal welfare and the economic impacts on the flock. This research contributes to a deeper understanding of bird behavior in high-production environments and provides practical insights for the poultry industry.
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Affiliation(s)
- Caroline Citta Mazocco
- Núcleo de Pesquisa em Ambiência (NUPEA), Escola Superior de Agricultura ‘‘Luiz de Queiroz’’ (ESALQ), Universidade de São Paulo (USP), Piracicaba 13418-900, SP, Brazil; (S.L.d.C.J.); (R.M.F.S.); (I.J.O.d.S.)
| | - Sérgio Luís de Castro Júnior
- Núcleo de Pesquisa em Ambiência (NUPEA), Escola Superior de Agricultura ‘‘Luiz de Queiroz’’ (ESALQ), Universidade de São Paulo (USP), Piracicaba 13418-900, SP, Brazil; (S.L.d.C.J.); (R.M.F.S.); (I.J.O.d.S.)
| | - Robson Mateus Freitas Silveira
- Núcleo de Pesquisa em Ambiência (NUPEA), Escola Superior de Agricultura ‘‘Luiz de Queiroz’’ (ESALQ), Universidade de São Paulo (USP), Piracicaba 13418-900, SP, Brazil; (S.L.d.C.J.); (R.M.F.S.); (I.J.O.d.S.)
| | - Rosangela Poletto
- Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS)-Campus Sertão, Sertão 99170-000, RS, Brazil;
| | - Iran José Oliveira da Silva
- Núcleo de Pesquisa em Ambiência (NUPEA), Escola Superior de Agricultura ‘‘Luiz de Queiroz’’ (ESALQ), Universidade de São Paulo (USP), Piracicaba 13418-900, SP, Brazil; (S.L.d.C.J.); (R.M.F.S.); (I.J.O.d.S.)
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17
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Wu S, Dou T, Yuan S, Yan S, Xu Z, Liu Y, Jian Z, Zhao J, Zhao R, Zi X, Gu D, Liu L, Li Q, Wu DD, Jia J, Ge C, Su Z, Wang K. Annotations of four high-quality indigenous chicken genomes identify more than one thousand missing genes in subtelomeric regions and micro-chromosomes with high G/C contents. BMC Genomics 2024; 25:430. [PMID: 38693501 PMCID: PMC11061957 DOI: 10.1186/s12864-024-10316-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 04/16/2024] [Indexed: 05/03/2024] Open
Abstract
BACKGROUND Although multiple chicken genomes have been assembled and annotated, the numbers of protein-coding genes in chicken genomes and their variation among breeds are still uncertain due to the low quality of these genome assemblies and limited resources used in their gene annotations. To fill these gaps, we recently assembled genomes of four indigenous chicken breeds with distinct traits at chromosome-level. In this study, we annotated genes in each of these assembled genomes using a combination of RNA-seq- and homology-based approaches. RESULTS We identified varying numbers (17,497-17,718) of protein-coding genes in the four indigenous chicken genomes, while recovering 51 of the 274 "missing" genes in birds in general, and 36 of the 174 "missing" genes in chickens in particular. Intriguingly, based on deeply sequenced RNA-seq data collected in multiple tissues in the four breeds, we found 571 ~ 627 protein-coding genes in each genome, which were missing in the annotations of the reference chicken genomes (GRCg6a and GRCg7b/w). After removing redundancy, we ended up with a total of 1,420 newly annotated genes (NAGs). The NAGs tend to be found in subtelomeric regions of macro-chromosomes (chr1 to chr5, plus chrZ) and middle chromosomes (chr6 to chr13, plus chrW), as well as in micro-chromosomes (chr14 to chr39) and unplaced contigs, where G/C contents are high. Moreover, the NAGs have elevated quadruplexes G frequencies, while both G/C contents and quadruplexes G frequencies in their surrounding regions are also high. The NAGs showed tissue-specific expression, and we were able to verify 39 (92.9%) of 42 randomly selected ones in various tissues of the four chicken breeds using RT-qPCR experiments. Most of the NAGs were also encoded in the reference chicken genomes, thus, these genomes might harbor more genes than previously thought. CONCLUSION The NAGs are widely distributed in wild, indigenous and commercial chickens, and they might play critical roles in chicken physiology. Counting these new genes, chicken genomes harbor more genes than originally thought.
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Affiliation(s)
- Siwen Wu
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Tengfei Dou
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Sisi Yuan
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Shixiong Yan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zhiqiang Xu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yong Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zonghui Jian
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Jingying Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Rouhan Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Xiannian Zi
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dahai Gu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Lixian Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Qihua Li
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Junjing Jia
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Changrong Ge
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Kun Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China.
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18
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Wu S, Dou T, Wang K, Yuan S, Yan S, Xu Z, Liu Y, Jian Z, Zhao J, Zhao R, Wu H, Gu D, Liu L, Li Q, Wu DD, Ge C, Su Z, Jia J. Artificial selection footprints in indigenous and commercial chicken genomes. BMC Genomics 2024; 25:428. [PMID: 38689225 PMCID: PMC11061962 DOI: 10.1186/s12864-024-10291-5] [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: 12/22/2023] [Accepted: 04/08/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Although many studies have been done to reveal artificial selection signatures in commercial and indigenous chickens, a limited number of genes have been linked to specific traits. To identify more trait-related artificial selection signatures and genes, we re-sequenced a total of 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan Province, China. RESULTS We found 30 million non-redundant single nucleotide variants and small indels (< 50 bp) in the indigenous chickens, of which 10 million were not seen in 60 broilers, 56 layers and 35 red jungle fowls (RJFs) that we compared with. The variants in each breed are enriched in non-coding regions, while those in coding regions are largely tolerant, suggesting that most variants might affect cis-regulatory sequences. Based on 27 million bi-allelic single nucleotide polymorphisms identified in the chickens, we found numerous selective sweeps and affected genes in each indigenous chicken breed and substantially larger numbers of selective sweeps and affected genes in the broilers and layers than previously reported using a rigorous statistical model. Consistent with the locations of the variants, the vast majority (~ 98.3%) of the identified selective sweeps overlap known quantitative trait loci (QTLs). Meanwhile, 74.2% known QTLs overlap our identified selective sweeps. We confirmed most of previously identified trait-related genes and identified many novel ones, some of which might be related to body size and high egg production traits. Using RT-qPCR, we validated differential expression of eight genes (GHR, GHRHR, IGF2BP1, OVALX, ELF2, MGARP, NOCT, SLC25A15) that might be related to body size and high egg production traits in relevant tissues of relevant breeds. CONCLUSION We identify 30 million single nucleotide variants and small indels in the five indigenous chicken breeds, 10 million of which are novel. We predict substantially more selective sweeps and affected genes than previously reported in both indigenous and commercial breeds. These variants and affected genes are good candidates for further experimental investigations of genotype-phenotype relationships and practical applications in chicken breeding programs.
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Affiliation(s)
- Siwen Wu
- Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Tengfei Dou
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Kun Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Sisi Yuan
- Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Shixiong Yan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zhiqiang Xu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yong Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Zonghui Jian
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Jingying Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Rouhan Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Hao Wu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dahai Gu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Lixian Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Qihua Li
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Changrong Ge
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China.
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
| | - Junjing Jia
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China.
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19
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Romanov MN, Shakhin AV, Abdelmanova AS, Volkova NA, Efimov DN, Fisinin VI, Korshunova LG, Anshakov DV, Dotsev AV, Griffin DK, Zinovieva NA. Dissecting Selective Signatures and Candidate Genes in Grandparent Lines Subject to High Selection Pressure for Broiler Production and in a Local Russian Chicken Breed of Ushanka. Genes (Basel) 2024; 15:524. [PMID: 38674458 PMCID: PMC11050503 DOI: 10.3390/genes15040524] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 04/16/2024] [Accepted: 04/20/2024] [Indexed: 04/28/2024] Open
Abstract
Breeding improvements and quantitative trait genetics are essential to the advancement of broiler production. The impact of artificial selection on genomic architecture and the genetic markers sought remains a key area of research. Here, we used whole-genome resequencing data to analyze the genomic architecture, diversity, and selective sweeps in Cornish White (CRW) and Plymouth Rock White (PRW) transboundary breeds selected for meat production and, comparatively, in an aboriginal Russian breed of Ushanka (USH). Reads were aligned to the reference genome bGalGal1.mat.broiler.GRCg7b and filtered to remove PCR duplicates and low-quality reads using BWA-MEM2 and bcftools software; 12,563,892 SNPs were produced for subsequent analyses. Compared to CRW and PRW, USH had a lower diversity and a higher genetic distinctiveness. Selective sweep regions and corresponding candidate genes were examined based on ZFST, hapFLK, and ROH assessment procedures. Twenty-seven prioritized chicken genes and the functional projection from human homologs suggest their importance for selection signals in the studied breeds. These genes have a functional relationship with such trait categories as body weight, muscles, fat metabolism and deposition, reproduction, etc., mainly aligned with the QTLs in the sweep regions. This information is pivotal for further executing genomic selection to enhance phenotypic traits.
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Affiliation(s)
- Michael N. Romanov
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (A.V.S.); (A.S.A.); (N.A.V.); (A.V.D.)
- School of Biosciences, University of Kent, Canterbury CT2 7NJ, UK;
| | - Alexey V. Shakhin
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (A.V.S.); (A.S.A.); (N.A.V.); (A.V.D.)
| | - Alexandra S. Abdelmanova
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (A.V.S.); (A.S.A.); (N.A.V.); (A.V.D.)
| | - Natalia A. Volkova
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (A.V.S.); (A.S.A.); (N.A.V.); (A.V.D.)
| | - Dmitry N. Efimov
- Federal State Budget Scientific Institution Federal Scientific Center “All-Russian Research and Technological Poultry Institute”, Sergiev Posad 141311, Moscow Oblast, Russia; (D.N.E.); (V.I.F.); (L.G.K.)
| | - Vladimir I. Fisinin
- Federal State Budget Scientific Institution Federal Scientific Center “All-Russian Research and Technological Poultry Institute”, Sergiev Posad 141311, Moscow Oblast, Russia; (D.N.E.); (V.I.F.); (L.G.K.)
| | - Liudmila G. Korshunova
- Federal State Budget Scientific Institution Federal Scientific Center “All-Russian Research and Technological Poultry Institute”, Sergiev Posad 141311, Moscow Oblast, Russia; (D.N.E.); (V.I.F.); (L.G.K.)
| | - Dmitry V. Anshakov
- Breeding and Genetic Center “Zagorsk Experimental Breeding Farm”—Branch of the Federal Research Center “All-Russian Poultry Research and Technological Institute”, Russian Academy of Sciences, Sergiev Posad 141311, Moscow Oblast, Russia;
| | - Arsen V. Dotsev
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (A.V.S.); (A.S.A.); (N.A.V.); (A.V.D.)
| | | | - Natalia A. Zinovieva
- L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk 142132, Moscow Oblast, Russia; (A.V.S.); (A.S.A.); (N.A.V.); (A.V.D.)
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20
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Contriciani RE, Grade CVC, Buzzatto-Leite I, da Veiga FC, Ledur MC, Reverter A, Alexandre PA, Cesar ASM, Coutinho LL, Alvares LE. Phenotypic divergence between broiler and layer chicken lines is regulated at the molecular level during development. BMC Genomics 2024; 25:168. [PMID: 38347479 PMCID: PMC10863267 DOI: 10.1186/s12864-024-10083-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/02/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Understanding the molecular underpinnings of phenotypic variations is critical for enhancing poultry breeding programs. The Brazilian broiler (TT) and laying hen (CC) lines exhibit striking differences in body weight, growth potential, and muscle mass. Our work aimed to compare the global transcriptome of wing and pectoral tissues during the early development (days 2.5 to 3.5) of these chicken lines, unveiling disparities in gene expression and regulation. RESULTS Different and bona-fide transcriptomic profiles were identified for the compared lines. A similar number of up- and downregulated differentially expressed genes (DEGs) were identified, considering the broiler line as a reference. Upregulated DEGs displayed an enrichment of protease-encoding genes, whereas downregulated DEGs exhibited a prevalence of receptors and ligands. Gene Ontology analysis revealed that upregulated DEGs were mainly associated with hormone response, mitotic cell cycle, and different metabolic and biosynthetic processes. In contrast, downregulated DEGs were primarily linked to communication, signal transduction, cell differentiation, and nervous system development. Regulatory networks were constructed for the mitotic cell cycle and cell differentiation biological processes, as their contrasting roles may impact the development of distinct postnatal traits. Within the mitotic cell cycle network, key upregulated DEGs included CCND1 and HSP90, with central regulators being NF-κB subunits (RELA and REL) and NFATC2. The cell differentiation network comprises numerous DEGs encoding transcription factors (e.g., HOX genes), receptors, ligands, and histones, while the main regulatory hubs are CREB, AR and epigenetic modifiers. Clustering analyses highlighted PIK3CD as a central player within the differentiation network. CONCLUSIONS Our study revealed distinct developmental transcriptomes between Brazilian broiler and layer lines. The gene expression profile of broiler embryos seems to favour increased cell proliferation and delayed differentiation, which may contribute to the subsequent enlargement of pectoral tissues during foetal and postnatal development. Our findings pave the way for future functional studies and improvement of targeted traits of economic interest in poultry.
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Affiliation(s)
- Renata Erbert Contriciani
- Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Carla Vermeulen Carvalho Grade
- Instituto Latino-Americano de Ciências da Vida e da Natureza, Universidade Federal da Integração Latino-Americana (UNILA), Foz do Iguaçu, Brazil
| | - Igor Buzzatto-Leite
- Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Fernanda Cristina da Veiga
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo (USP), Piracicaba, Brazil
| | | | - Antonio Reverter
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Agriculture and Food, Brisbane, QLD, Australia
| | - Pamela Almeida Alexandre
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Agriculture and Food, Brisbane, QLD, Australia
| | - Aline Silva Mello Cesar
- Department of Agri-Food Industry, Food and Nutrition, Luiz de Queiroz College of Agriculture, University of São Paulo (USP), Piracicaba, Brazil
| | - Luiz Lehmann Coutinho
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo (USP), Piracicaba, Brazil.
| | - Lúcia Elvira Alvares
- Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
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21
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Tan X, Zhang J, Dong J, Huang M, Li Q, Wang H, Bai L, Cui M, Zhou Z, Yang S, Wang D. Whole-genome variants dataset of 209 local chickens from China. Sci Data 2024; 11:169. [PMID: 38316816 PMCID: PMC10844214 DOI: 10.1038/s41597-024-02995-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 01/25/2024] [Indexed: 02/07/2024] Open
Abstract
Compared to commercial chickens, local breeds exhibit better in meat quality and flavour, but the productivity (e.g., growth rate, body weight) of local chicken breeds is rather low. Genetic analysis based on whole-genome sequencing contributes to elucidating the genetic markers or putative candidate genes related to some economic traits, facilitating the improvement of production performance, the acceleration of breeding progress, and the conservation of genetic resources. Here, a total of 209 local chickens from 13 breeds were investigated, and the observation of approximately 91.4% high-quality sequences (Q30 > 90%) and a mapping rate over 99% for each individual indicated good results of this study, as confirmed by a genome coverage of 97.6%. Over 19 million single nucleotide polymorphisms (SNPs) and 1.98 million insertion-deletions (InDels) were identified using the reference genome (GRCg7b), further contributing to the public database. This dataset provides valuable resources for studying genetic diversity and adaptation and for the cultivation of new chicken breeds/lines.
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Affiliation(s)
- Xiaodong Tan
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Jiawen Zhang
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Jie Dong
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Minjie Huang
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Qinghai Li
- Animal Husbandry Institute, Hangzhou Academy of Agricultural Sciences, Hangzhou, 310024, China
| | - Huanhuan Wang
- Animal Husbandry Institute, Hangzhou Academy of Agricultural Sciences, Hangzhou, 310024, China
| | - Lijuan Bai
- Zhejiang Animal Husbandry Technology Extension and Breeding Livestock and Poultry Monitoring Station, Hangzhou, 310020, China
| | - Ming Cui
- Zhejiang Animal Husbandry Technology Extension and Breeding Livestock and Poultry Monitoring Station, Hangzhou, 310020, China
| | - Zhenzhen Zhou
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Shuyuan Yang
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Deqian Wang
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China.
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22
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Liu C, He Y, Liang W, Zhu T, Zhang B, Li D, Li W, Wang K, Tian Y, Kang X, Sun G. Research Note: Development and application of specific molecular identity cards for "Yufen 1" H line chickens. Poult Sci 2024; 103:103343. [PMID: 38113703 PMCID: PMC10770742 DOI: 10.1016/j.psj.2023.103343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/29/2023] [Accepted: 11/29/2023] [Indexed: 12/21/2023] Open
Abstract
The "Yufen 1" H line chicken (YF) has excellent characteristics including early sexual maturity and high egg production, and the conservation of its genetic diversity is the core of the breeding activity. To overcome misrepresented breeds and protect the integrity of the germplasm genetic resources, it is important to develop accurate and convenient methods to identify YF. In this study, whole genome resequencing was performed on the YF population, and bioinformatics analysis was conducted by combining the data from different breeds. Linkage disequilibrium (LD) analysis revealed that YF had the slowest LD-decay rate, suggesting strong natural and artificial selection in its history. Through selective sweep analysis, 1,126 selected regions in YF were identified, which contained 163,661 single nucleotide polymorphisms (SNPs). In particular, 5 specific SNPs (SNP1: Chr2:45509616, SNP2: Chr2:45510792, SNP3: Chr9:13788193, SNP4: Chr9:13795646, SNP5: Chr9:13798154) were found exclusively in the YF population. Subsequently, PCR amplification and Sanger sequencing confirmed the presence of these 5 SNPs in YF. Finally, 4 SNPs (SNP1, SNP2, SNP4, SNP5) were screened and verified using the Kompetitive Allele Specific PCR (KASP) typing technique. These SNPs can be used as specific molecular identity cards (IDs) for YF authentication. The present study is of great significance to ensure sustainable conservation and promotion of YF germplasm resources.
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Affiliation(s)
- Cong Liu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Yuehua He
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Wenjie Liang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Tingqi Zhu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Binbin Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Donghua Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Wenting Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; The Shennong Laboratory, Zhengzhou 450002, China
| | - Kejun Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Yadong Tian
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
| | - Xiangtao Kang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; The Shennong Laboratory, Zhengzhou 450002, China
| | - Guirong Sun
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; The Shennong Laboratory, Zhengzhou 450002, China.
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23
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Rachman MP, Bamidele O, Dessie T, Smith J, Hanotte O, Gheyas AA. Genomic analysis of Nigerian indigenous chickens reveals their genetic diversity and adaptation to heat-stress. Sci Rep 2024; 14:2209. [PMID: 38278850 PMCID: PMC10817956 DOI: 10.1038/s41598-024-52569-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/20/2024] [Indexed: 01/28/2024] Open
Abstract
Indigenous poultry breeds from Africa can survive in harsh tropical environments (such as long arid seasons, excessive rain and humidity, and extreme heat) and are resilient to disease challenges, but they are not productive compared to their commercial counterparts. Their adaptive characteristics are in response to natural selection or to artificial selection for production traits that have left selection signatures in the genome. Identifying these signatures of positive selection can provide insight into the genetic bases of tropical adaptations observed in indigenous poultry and thereby help to develop robust and high-performing breeds for extreme tropical climates. Here, we present the first large-scale whole-genome sequencing analysis of Nigerian indigenous chickens from different agro-climatic conditions, investigating their genetic diversity and adaptation to tropical hot climates (extreme arid and extreme humid conditions). The study shows a large extant genetic diversity but low level of population differentiation. Using different selection signature analyses, several candidate genes for adaptation were detected, especially in relation to thermotolerance and immune response (e.g., cytochrome P450 2B4-like, TSHR, HSF1, CDC37, SFTPB, HIF3A, SLC44A2, and ILF3 genes). These results have important implications for conserving valuable genetic resources and breeding improvement of chickens for thermotolerance.
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Affiliation(s)
- Mifta P Rachman
- School of Biosciences, University of Nottingham, Nottingham, LE12 5RD, UK.
| | - Oladeji Bamidele
- African Chicken Genetic Gains (ACGG), Department of Animal Sciences, Obafemi Awolowo University, Ile Ife, 220282, Nigeria
| | - Tadelle Dessie
- LiveGene-CTLGH, International Livestock Research Institute (ILRI), P.O. Box 5689, Addis Ababa, Ethiopia
| | - Jacqueline Smith
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Olivier Hanotte
- LiveGene-CTLGH, International Livestock Research Institute (ILRI), P.O. Box 5689, Addis Ababa, Ethiopia.
- School of Life Sciences, University of Nottingham, Nottingham, NG7 2RD, UK.
| | - Almas A Gheyas
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Edinburgh, EH25 9RG, UK.
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24
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Tan X, Liu R, Zhao D, He Z, Li W, Zheng M, Li Q, Wang Q, Liu D, Feng F, Zhu D, Zhao G, Wen J. Large-scale genomic and transcriptomic analyses elucidate the genetic basis of high meat yield in chickens. J Adv Res 2024; 55:1-16. [PMID: 36871617 PMCID: PMC10770282 DOI: 10.1016/j.jare.2023.02.016] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/16/2023] [Accepted: 02/26/2023] [Indexed: 03/07/2023] Open
Abstract
INTRODUCTION Investigating the genetic markers and genomic signatures related to chicken meat production by combing multi-omics methods could provide new insights into modern chicken breeding technology systems. OBJECT Chicken is one of the most efficient and environmentally friendly livestock, especially the fast-growing white-feathered chicken (broiler), which is well known for high meat yield, but the underlying genetic basis is poorly understood. METHOD We generated whole-genome resequencing of three purebred broilers (n = 748) and six local breeds/lines (n = 114), and sequencing data of twelve chicken breeds (n = 199) were obtained from the NCBI database. Additionally, transcriptome sequencing of six tissues from two chicken breeds (n = 129) at two developmental stages was performed. A genome-wide association study combined with cis-eQTL mapping and the Mendelian randomization was applied. RESULT We identified > 17 million high-quality SNPs, of which 21.74% were newly identified, based on 21 chicken breeds/lines. A total of 163 protein-coding genes underwent positive selection in purebred broilers, and 83 genes were differentially expressed between purebred broilers and local chickens. Notably, muscle development was proven to be the major difference between purebred broilers and local chickens, or ancestors, based on genomic and transcriptomic evidence from multiple tissues and stages. The MYH1 gene family showed the top selection signatures and muscle-specific expression in purebred broilers. Furthermore, we found that the causal gene SOX6 influenced breast muscle yield and also related to myopathy occurrences. A refined haplotype was provided, which had a significant effect on SOX6 expression and phenotypic changes. CONCLUSION Our study provides a comprehensive atlas comprising the typical genomic variants and transcriptional characteristics for muscle development and suggests a new regulatory target (SOX6-MYH1s axis) for breast muscle yield and myopathy, which could aid in the development of genome-scale selective breeding aimed at high meat yield in broiler chickens.
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Affiliation(s)
- Xiaodong Tan
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ranran Liu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Di Zhao
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Zhengxiao He
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Wei Li
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Maiqing Zheng
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Qinghe Li
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Qiao Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Dawei Liu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Furong Feng
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Dan Zhu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Jie Wen
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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25
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Guo Y, Rubin CJ, Rönneburg T, Wang S, Li H, Hu X, Carlborg Ö. Whole-genome selective sweep analyses identifies the region and candidate gene associated with white earlobe color in Mediterranean chickens. Poult Sci 2024; 103:103232. [PMID: 37980749 PMCID: PMC10692716 DOI: 10.1016/j.psj.2023.103232] [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: 08/03/2023] [Revised: 10/07/2023] [Accepted: 10/20/2023] [Indexed: 11/21/2023] Open
Abstract
We compared the genomes of multiple domestic chicken breeds with red and white earlobes to identify the differentiated regions between groups of breeds differing in earlobe color. This was done using a selective sweep mapping approach based on whole-genome sequence data. The most significant selective sweep was identified on chromosome 11, where the white earlobe chicken breeds originated from Mediterranean share a common haplotype, and where multiple candidate genes are located. The most plausible functional candidate gene is the Melanocortin 1 Receptor (MC1R), a receptor known to regulate pigmentation in the skin and hair, and it is also the gene with the strongest positional support from the haplotype-based analyses. It, however, still needs to be explored experimentally to identify effects also on chicken earlobe color variation. Our study is the first exploration of the genetic basis of white earlobe color in Mediterranean chickens using a selective sweep mapping method based on whole-genome sequencing data and shows its value for identifying likely functional genes mediating the pigmentation in earlobe. It also indicates a potential novel role of MC1R in birds and exemplifies how selection on fancy traits has influenced the genome during formation of the modern chicken breeds.
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Affiliation(s)
- Ying Guo
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, China; National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing, China; Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden; Yazhouwan National Laboratory, Sanya, China
| | - Carl-Johan Rubin
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Tilman Rönneburg
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Shouzhi Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, China; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin, China; College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Xiaoxiang Hu
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, China; National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing, China.
| | - Örjan Carlborg
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
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Yang K, Zhang J, Zhao Y, Shao Y, Zhai M, Liu H, Zhang L. Whole Genome Resequencing Revealed the Genetic Relationship and Selected Regions among Baicheng-You, Beijing-You, and European-Origin Broilers. BIOLOGY 2023; 12:1397. [PMID: 37997996 PMCID: PMC10669838 DOI: 10.3390/biology12111397] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 11/25/2023]
Abstract
As the only two You-chicken breeds in China, Baicheng-You (BCY) and Beijing-You (BJY) chickens are famous for their good meat quality. However, so far, the molecular basis of germplasm of the two You-chicken breeds is not yet clear. The genetic relationship among BCY, BJY, and European-origin broilers (BRs) was analyzed using whole genome resequencing data to contribute to this issue. A total of 18,852,372 single nucleotide polymorphisms (SNPs) were obtained in this study. After quality control, 8,207,242 SNPs were applied to subsequent analysis. The data indicated that BJY chickens possessed distant distance with BRs (genetic differentiation coefficient (FST) = 0.1681) and BCY (FST = 0.1231), respectively, while BCY and BRs had a closer relationship (FST = 0.0946). In addition, by using FST, cross-population extended haplotype homozygosity (XP-EHH), and cross-population composite likelihood ratio (XP-CLR) methods, we found 374 selected genes between BJY and BRs chickens and 279 selected genes between BCY and BJY chickens, respectively, which contained a number of important candidates or genetic variations associated with feather growth and fat deposition of BJY chickens and potential disease resistance of BCY chickens. Our study demonstrates a genome-wide view of genetic diversity and differentiation among BCY, BJY, and BRs. These results may provide useful information on a molecular basis related to the special characteristics of these broiler breeds, thus enabling us to better understand the formation mechanism of Chinese-You chickens.
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Affiliation(s)
- Kai Yang
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; (K.Y.); (Y.Z.)
| | - Jian Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.Z.); (H.L.)
| | - Yuelei Zhao
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; (K.Y.); (Y.Z.)
| | - Yonggang Shao
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.S.); (M.Z.)
| | - Manjun Zhai
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.S.); (M.Z.)
| | - Huagui Liu
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.Z.); (H.L.)
| | - Lifan Zhang
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; (K.Y.); (Y.Z.)
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Xu D, Zhu W, Wu Y, Wei S, Shu G, Tian Y, Du X, Tang J, Feng Y, Wu G, Han X, Zhao X. Whole-genome sequencing revealed genetic diversity, structure and patterns of selection in Guizhou indigenous chickens. BMC Genomics 2023; 24:570. [PMID: 37749517 PMCID: PMC10521574 DOI: 10.1186/s12864-023-09621-w] [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: 04/03/2023] [Accepted: 08/23/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND The eight phenotypically distinguishable indigenous chicken breeds in Guizhou province of China are great resources for high-quality development of the poultry industry in China. However, their full value and potential have yet to be understood in depth. To illustrate the genetic diversity, the relationship and population structure, and the genetic variation patterns shaped by selection in Guizhou indigenous chickens, we performed a genome-wide analysis of 240 chickens from 8 phenotypically and geographically representative Guizhou chicken breeds and 60 chickens from 2 commercial chicken breeds (one broiler and one layer), together with 10 red jungle fowls (RJF) genomes available from previous studies. RESULTS The results obtained in this present study showed that Guizhou chicken breed populations harbored higher genetic diversity as compared to commercial chicken breeds, however unequal polymorphisms were present within Guizhou indigenous chicken breeds. The results from the population structure analysis markedly reflected the breeding history and the geographical distribution of Guizhou indigenous chickens, whereas, some breeds with complex genetic structure were ungrouped into one cluster. In addition, we confirmed mutual introgression within Guizhou indigenous chicken breeds and from commercial chicken breeds. Furthermore, selective sweep analysis revealed candidate genes which were associated with specific and common phenotypic characteristics evolved rapidly after domestication of Guizhou local chicken breeds and economic traits such as egg production performance, growth performance, and body size. CONCLUSION Taken together, the results obtained from the comprehensive analysis of the genetic diversity, genetic relationships and population structures in this study showed that Guizhou indigenous chicken breeds harbor great potential for commercial utilization, however effective conservation measures are currently needed. Additionally, the present study drew a genome-wide selection signature draft for eight Guizhou indigenous chicken breeds and two commercial breeds, as well as established a resource that can be exploited in chicken breeding programs to manipulate the genes associated with desired phenotypes. Therefore, this study will provide an essential genetic basis for further research, conservation, and breeding of Guizhou indigenous chickens.
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Affiliation(s)
- Dan Xu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China
| | - Wei Zhu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China
| | - Youhao Wu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China
| | - Shuo Wei
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China
| | - Gang Shu
- Department of Basic Veterinary Medicine, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Yaofu Tian
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China
| | - Xiaohui Du
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China
| | - Jigao Tang
- Institute of Animal Husbandry and Veterinary Medicine, Guizhou Academy of Agricultural Sciences, Guiyang, Guizhou Province, China
| | - Yulong Feng
- Institute of Animal Husbandry and Veterinary Medicine, Guizhou Academy of Agricultural Sciences, Guiyang, Guizhou Province, China
| | - Gemin Wu
- Institute of Animal Husbandry and Veterinary Medicine, Guizhou Academy of Agricultural Sciences, Guiyang, Guizhou Province, China
| | - Xue Han
- Institute of Animal Husbandry and Veterinary Medicine, Guizhou Academy of Agricultural Sciences, Guiyang, Guizhou Province, China.
| | - Xiaoling Zhao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Ya'an, P. R. China.
- Key Laboratory of Livestock and Poultry Multi-Omics, MinistryofAgricultureandRuralAffairs, College of Animal Science and Technology(Institute of Animal Genetics and Breeding), Sichuan Agricultural University, Ya'an, P. R. China.
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Shinde SS, Sharma A, Vijay N. Decoding the fibromelanosis locus complex chromosomal rearrangement of black-bone chicken: genetic differentiation, selective sweeps and protein-coding changes in Kadaknath chicken. Front Genet 2023; 14:1180658. [PMID: 37424723 PMCID: PMC10325862 DOI: 10.3389/fgene.2023.1180658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/05/2023] [Indexed: 07/11/2023] Open
Abstract
Black-bone chicken (BBC) meat is popular for its distinctive taste and texture. A complex chromosomal rearrangement at the fibromelanosis (Fm) locus on the 20th chromosome results in increased endothelin-3 (EDN3) gene expression and is responsible for melanin hyperpigmentation in BBC. We use public long-read sequencing data of the Silkie breed to resolve high-confidence haplotypes at the Fm locus spanning both Dup1 and Dup2 regions and establish that the Fm_2 scenario is correct of the three possible scenarios of the complex chromosomal rearrangement. The relationship between Chinese and Korean BBC breeds with Kadaknath native to India is underexplored. Our data from whole-genome re-sequencing establish that all BBC breeds, including Kadaknath, share the complex chromosomal rearrangement junctions at the fibromelanosis (Fm) locus. We also identify two Fm locus proximal regions (∼70 Kb and ∼300 Kb) with signatures of selection unique to Kadaknath. These regions harbor several genes with protein-coding changes, with the bactericidal/permeability-increasing-protein-like gene having two Kadaknath-specific changes within protein domains. Our results indicate that protein-coding changes in the bactericidal/permeability-increasing-protein-like gene hitchhiked with the Fm locus in Kadaknath due to close physical linkage. Identifying this Fm locus proximal selective sweep sheds light on the genetic distinctiveness of Kadaknath compared to other BBC.
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Affiliation(s)
| | | | - Nagarjun Vijay
- Computational Evolutionary Genomics Lab, Department of Biological Sciences, IISER Bhopal, Bhauri, Madhya Pradesh, India
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29
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Iqbal MA, Hadlich F, Reyer H, Oster M, Trakooljul N, Murani E, Perdomo‐Sabogal A, Wimmers K, Ponsuksili S. RNA-Seq-based discovery of genetic variants and allele-specific expression of two layer lines and broiler chicken. Evol Appl 2023; 16:1135-1153. [PMID: 37360029 PMCID: PMC10286233 DOI: 10.1111/eva.13557] [Citation(s) in RCA: 6] [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: 12/21/2022] [Revised: 04/21/2023] [Accepted: 04/22/2023] [Indexed: 06/28/2023] Open
Abstract
Recent advances in the selective breeding of broilers and layers have made poultry production one of the fastest-growing industries. In this study, a transcriptome variant calling approach from RNA-seq data was used to determine population diversity between broilers and layers. In total, 200 individuals were analyzed from three different chicken populations (Lohmann Brown (LB), n = 90), Lohmann Selected Leghorn (LSL, n = 89), and Broiler (BR, n = 21). The raw RNA-sequencing reads were pre-processed, quality control checked, mapped to the reference genome, and made compatible with Genome Analysis ToolKit for variant detection. Subsequently, pairwise fixation index (F ST) analysis was performed between broilers and layers. Numerous candidate genes were identified, that were associated with growth, development, metabolism, immunity, and other economically significant traits. Finally, allele-specific expression (ASE) analysis was performed in the gut mucosa of LB and LSL strains at 10, 16, 24, 30, and 60 weeks of age. At different ages, the two-layer strains showed significantly different allele-specific expressions in the gut mucosa, and changes in allelic imbalance were observed across the entire lifespan. Most ASE genes are involved in energy metabolism, including sirtuin signaling pathways, oxidative phosphorylation, and mitochondrial dysfunction. A high number of ASE genes were found during the peak of laying, which were particularly enriched in cholesterol biosynthesis. These findings indicate that genetic architecture as well as biological processes driving particular demands relate to metabolic and nutritional requirements during the laying period shape allelic heterogeneity. These processes are considerably affected by breeding and management, whereby elucidating allele-specific gene regulation is an essential step towards deciphering the genotype to phenotype map or functional diversity between the chicken populations. Additionally, we observed that several genes showing significant allelic imbalance also colocalized with the top 1% of genes identified by the FST approach, suggesting a fixation of genes in cis-regulatory elements.
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Affiliation(s)
| | - Frieder Hadlich
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
| | - Henry Reyer
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
| | - Michael Oster
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
| | - Nares Trakooljul
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
| | - Eduard Murani
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
| | | | - Klaus Wimmers
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
- Faculty of Agricultural and Environmental SciencesUniversity RostockRostockGermany
| | - Siriluck Ponsuksili
- Research Institute for Farm Animal BiologyInstitute of Genome BiologyDummerstorfGermany
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30
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Pan Z, Wang Y, Wang M, Wang Y, Zhu X, Gu S, Zhong C, An L, Shan M, Damas J, Halstead MM, Guan D, Trakooljul N, Wimmers K, Bi Y, Wu S, Delany ME, Bai X, Cheng HH, Sun C, Yang N, Hu X, Lewin HA, Fang L, Zhou H. An atlas of regulatory elements in chicken: A resource for chicken genetics and genomics. SCIENCE ADVANCES 2023; 9:eade1204. [PMID: 37134160 PMCID: PMC10156120 DOI: 10.1126/sciadv.ade1204] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
A comprehensive characterization of regulatory elements in the chicken genome across tissues will have substantial impacts on both fundamental and applied research. Here, we systematically identified and characterized regulatory elements in the chicken genome by integrating 377 genome-wide sequencing datasets from 23 adult tissues. In total, we annotated 1.57 million regulatory elements, representing 15 distinct chromatin states, and predicted about 1.2 million enhancer-gene pairs and 7662 super-enhancers. This functional annotation of the chicken genome should have wide utility on identifying regulatory elements accounting for gene regulation underlying domestication, selection, and complex trait regulation, which we explored. In short, this comprehensive atlas of regulatory elements provides the scientific community with a valuable resource for chicken genetics and genomics.
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Affiliation(s)
- Zhangyuan Pan
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ying Wang
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mingshan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650000, China
| | - Yuzhe Wang
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100193, China
| | - Xiaoning Zhu
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100193, China
| | - Shenwen Gu
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Conghao Zhong
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Liqi An
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mingzhu Shan
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Joana Damas
- The Genome Center, University of California, Davis, CA 95616, USA
| | - Michelle M Halstead
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Dailu Guan
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Nares Trakooljul
- Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Klaus Wimmers
- Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
- Faculty of Agricultural and Environmental Sciences, University Rostock, Rostock, Germany
| | - Ye Bi
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Shang Wu
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mary E Delany
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Xuechen Bai
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Hans H Cheng
- USDA-ARS, Avian Disease and Oncology Laboratory, East Lansing, MI 48823, USA
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Xiaoxiang Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650000, China
| | - Harris A Lewin
- The Genome Center, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, DK
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
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Tiemann I, Becker S, Fournier J, Damiran D, Büscher W, Hillemacher S. Differences among domestic chicken breeds in tonic immobility responses as a measure of fearfulness. PeerJ 2023; 11:e14703. [PMID: 37033722 PMCID: PMC10081456 DOI: 10.7717/peerj.14703] [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: 02/15/2021] [Accepted: 12/15/2022] [Indexed: 04/07/2023] Open
Abstract
Background One priority for animal welfare is for animals to experience less fear, especially during human contact. For domestic animals, breeds that are less fearful may provide genetic resources to develop strains with improved welfare due to lower susceptibility to fear. Genetic predispositions inherited in these breeds might reflect the large diversity of chicken breeds. The goal of the present study was to systematically test a diverse group of chicken breeds to search for breeds that experience less fear. Methods Nineteen chicken breeds from commercial hybrid lines, native layer-type, meat-type and dual-purpose breeds, ornamental breeds as well as bantam breeds were tested in a standardized tonic immobility (TI) test. Chickens were manually restrained on their back, and the time to first head movement and first leg movement, the duration of TI, as well as the number of attempts needed to induce TI were measured. Results The TI response differed among chicken breeds (p ≤ 0.001) for naïve, mature hens. The median number of attempts required to induce TI ranged from 1 to 2 and did not differ significantly among breeds. Median durations were much more variable, with Lohmann Brown showing shortest durations (6 s, 12 s, 58 s for time to first head movement, first leg movement and total duration of TI, respectively). In contrast, medians reached the maximum of 600 s for all three measures in German Creepers. Repeated tests on the same individuals did not affect attempts needed to induce TI nor TI durations. Breeds clustered into two main groups, with layer-type native breeds and ornamental breeds having longer TI durations, and bantam, dual-purpose and meat-type native breeds having shorter TI durations. Conclusions Our findings provide evidence for substantial variation of fearfulness among breeds. This variation could be linked to the intended use during the breed's specific history. Knowledge and quantitative measurement of these behavioural responses provide the opportunity to improve welfare through selection and future breeding.
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Affiliation(s)
- Inga Tiemann
- Institute of Agricultural Engineering, University of Bonn, Bonn, Germany
| | - Senta Becker
- Institute of Agricultural Engineering, University of Bonn, Bonn, Germany
| | - Jocelyn Fournier
- Department of Animal & Poultry Science, University of Saskatchewan, Saskatoon, Canada
| | - Daalkhaijav Damiran
- Department of Animal & Poultry Science, University of Saskatchewan, Saskatoon, Canada
| | - Wolfgang Büscher
- Institute of Agricultural Engineering, University of Bonn, Bonn, Germany
| | - Sonja Hillemacher
- Institute of Agricultural Engineering, University of Bonn, Bonn, Germany
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Population Structure and Genetic Diversity Analysis of “Yufen 1” H Line Chickens Using Whole-Genome Resequencing. Life (Basel) 2023; 13:life13030793. [PMID: 36983948 PMCID: PMC10059704 DOI: 10.3390/life13030793] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/13/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
The effective protection and utilization of poultry resources depend on an accurate understanding of the genetic diversity and population structure. The breeding of the specialized poultry lineage “Yufen 1”, with its defined characteristics, was approved by the China Poultry Genetic Resource Committee in 2015. Thus, to investigate the relationship between the progenitor H line and other poultry breeds, the genetic diversity and population structure of “Yufen 1” H line (YF) were investigated and compared with those of 2 commercial chicken breeds, the ancestor breed Red Jungle Fowls, and 11 Chinese indigenous chicken breeds based on a whole-genome resequencing approach using 8,112,424 SNPs. The genetic diversity of YF was low, and the rate of linkage disequilibrium decay was significantly slower than that of the other Chinese indigenous breeds. In addition, it was shown that the YF population was strongly selected during intensive breeding and that genetic resources have been seriously threatened, which highlights the need to establish a systematic conservation strategy as well as utilization techniques to maintain genetic diversity within YF. Moreover, a principal component analysis, a neighbor-joining tree analysis, a structure analysis, and genetic differentiation indices indicated that YF harbors a distinctive genetic resource with a unique genetic structure separate from that of Chinese indigenous breeds at the genome level. The findings provide a valuable resource and the theoretical basis for the further conservation and utilization of YF.
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Genomic diversity and signals of selection processes in wild and farm-reared red-legged partridges (Alectoris rufa). Genomics 2023; 115:110591. [PMID: 36849018 DOI: 10.1016/j.ygeno.2023.110591] [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: 04/15/2022] [Revised: 02/18/2023] [Accepted: 02/22/2023] [Indexed: 02/27/2023]
Abstract
The genetic dynamics of wild populations with releases of farm-reared reinforcements are very complex. These releases can endanger wild populations through genetic swamping or by displacing them. We assessed the genomic differences between wild and farm-reared red-legged partridges (Alectoris rufa) and described differential selection signals between both populations. We sequenced the whole genome of 30 wild and 30 farm-reared partridges. Both partridges had similar nucleotide diversity (π). Farm-reared partridges had a more negative Tajima's D and more and longer regions of extended haplotype homozygosity than wild partridges. We observed higher inbreeding coefficients (FIS and FROH) in wild partridges. Selective sweeps (Rsb) were enriched with genes that contribute to the reproductive, skin and feather colouring, and behavioural differences between wild and farm-reared partridges. The analysis of genomic diversity should inform future decisions for the preservation of wild populations.
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Romanov MN, Abdelmanova AS, Fisinin VI, Gladyr EA, Volkova NA, Koshkina OA, Rodionov AN, Vetokh AN, Gusev IV, Anshakov DV, Stanishevskaya OI, Dotsev AV, Griffin DK, Zinovieva NA. Selective footprints and genes relevant to cold adaptation and other phenotypic traits are unscrambled in the genomes of divergently selected chicken breeds. J Anim Sci Biotechnol 2023; 14:35. [PMID: 36829208 PMCID: PMC9951459 DOI: 10.1186/s40104-022-00813-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 11/27/2022] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND The genomes of worldwide poultry breeds divergently selected for performance and other phenotypic traits may also be affected by, and formed due to, past and current admixture events. Adaptation to diverse environments, including acclimation to harsh climatic conditions, has also left selection footprints in breed genomes. RESULTS Using the Chicken 50K_CobbCons SNP chip, we genotyped four divergently selected breeds: two aboriginal, cold tolerant Ushanka and Orloff Mille Fleur, one egg-type Russian White subjected to artificial selection for cold tolerance, and one meat-type White Cornish. Signals of selective sweeps were determined in the studied breeds using three methods: (1) assessment of runs of homozygosity islands, (2) FST based population differential analysis, and (3) haplotype differentiation analysis. Genomic regions of true selection signatures were identified by two or more methods or in two or more breeds. In these regions, we detected 540 prioritized candidate genes supplemented them with those that occurred in one breed using one statistic and were suggested in other studies. Amongst them, SOX5, ME3, ZNF536, WWP1, RIPK2, OSGIN2, DECR1, TPO, PPARGC1A, BDNF, MSTN, and beta-keratin genes can be especially mentioned as candidates for cold adaptation. Epigenetic factors may be involved in regulating some of these important genes (e.g., TPO and BDNF). CONCLUSION Based on a genome-wide scan, our findings can help dissect the genetic architecture underlying various phenotypic traits in chicken breeds. These include genes representing the sine qua non for adaptation to harsh environments. Cold tolerance in acclimated chicken breeds may be developed following one of few specific gene expression mechanisms or more than one overlapping response known in cold-exposed individuals, and this warrants further investigation.
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Affiliation(s)
- Michael N. Romanov
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia ,grid.9759.20000 0001 2232 2818School of Biosciences, University of Kent, Canterbury, UK
| | - Alexandra S. Abdelmanova
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Vladimir I. Fisinin
- grid.4886.20000 0001 2192 9124Federal State Budget Scientific Institution Federal Research Centre “All-Russian Poultry Research and Technological Institute” of the Russian Academy of Sciences, Sergiev Posad, Moscow Region Russia
| | - Elena A. Gladyr
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Natalia A. Volkova
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Olga A. Koshkina
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Andrey N. Rodionov
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Anastasia N. Vetokh
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Igor V. Gusev
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Dmitry V. Anshakov
- grid.4886.20000 0001 2192 9124Breeding and Genetic Centre “Zagorsk Experimental Breeding Farm” – Branch of the Federal Research Centre “All-Russian Poultry Research and Technological Institute” of the Russian Academy of Sciences, Sergiev Posad, Moscow Region Russia
| | - Olga I. Stanishevskaya
- grid.473314.6Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Research Centre for Animal Husbandry, St. Petersburg, Russia
| | - Arsen V. Dotsev
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
| | - Darren K. Griffin
- grid.9759.20000 0001 2232 2818School of Biosciences, University of Kent, Canterbury, UK
| | - Natalia A. Zinovieva
- L.K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Region Russia
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Zhi Y, Wang D, Zhang K, Wang Y, Geng W, Chen B, Li H, Li Z, Tian Y, Kang X, Liu X. Genome-Wide Genetic Structure of Henan Indigenous Chicken Breeds. Animals (Basel) 2023; 13:753. [PMID: 36830540 PMCID: PMC9952073 DOI: 10.3390/ani13040753] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 02/14/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
There are five indigenous chicken breeds in Henan Province, China. These breeds have their own unique phenotypic characteristics in terms of morphology, behavior, skin and feather color, and productive performance, but their genetic basis is not well understood. Therefore, we analyzed the genetic structure, genomic diversity, and migration history of Henan indigenous chicken populations and the selection signals and genes responsible for Henan gamecock unique phenotypes using whole genome resequencing. The results indicate that Henan native chickens clustered most closely with the chicken populations in neighboring provinces. Compared to other breeds, Henan gamecock's inbreeding and selection intensity were more stringent. TreeMix analysis revealed the gene flow from southern chicken breeds into the Zhengyang sanhuang chicken and from the Xichuan black-bone chicken into the Gushi chicken. Selective sweep analysis identified several genes and biological processes/pathways that were related to body size, head control, muscle development, reproduction, and aggression control. Additionally, we confirmed the association between genotypes of SNPs in the strong selective gene LCORL and body size and muscle development in the Gushi-Anka F2 resource population. These findings made it easier to understand the traits of the germplasm and the potential for using the Henan indigenous chicken.
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Affiliation(s)
- Yihao Zhi
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Dandan Wang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Ke Zhang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Yangyang Wang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Wanzhuo Geng
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Botong Chen
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Hong Li
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Zhuanjian Li
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Yadong Tian
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Xiangtao Kang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Xiaojun Liu
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
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Nan J, Yang S, Zhang X, Leng T, Zhuoma J, Zhuoma R, Yuan J, Pi J, Sheng Z, Li S. Identification of candidate genes related to highland adaptation from multiple Chinese local chicken breeds by whole genome sequencing analysis. Anim Genet 2023; 54:55-67. [PMID: 36305422 DOI: 10.1111/age.13268] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/30/2022] [Accepted: 09/20/2022] [Indexed: 01/07/2023]
Abstract
Understanding the genetic mechanism of highland adaptation is of great importance for breeding improvement of Tibetan chickens (TBC). Some studies of TBC have identified some candidate genes and pathways from multiple subgroups, but the related genetic mechanisms remain largely unknown. Different genetic backgrounds and the independent genetic basis of highland adaptation make it difficult to identity the selective region of highland adaptation with all TBC samples. In this study, we conducted pre-analysis in a large-scale population to select a TBC subgroup with the purest and highest level of highland-specific lineage for the further analysis. Finally, the 37 samples from a TBC subgroup and 19 Lahsa White chickens were used to represent the highland group for further analysis with 80 samples from five Chinese local lowland breeds as controls. Population structure analysis revealed that highland adaptation significantly affected population stratification in Chinese local chicken breeds. Genome-wide selection signal analysis identified 201 candidate genes associated with highland adaptation of TBC, and these genes were significantly enriched in calcium signaling, vascular smooth muscle contraction and the cellular response to oxidative stress pathways. Additionally, we identified a narrow 1.76 kb region containing an overlapping region between HBZ and an active enhancer, and our identified region showed a highly significant signal. The highland group selected the haplotype with high activity to improve the oxygen-carrying capacity, thus being adapted to a hypoxic environment. We also found that STX2 was significantly selected in the highland group, thus potentially reducing the oxidative stress caused by hypoxia, and that STX2 exhibited the opposite effects on highland adaptation and reproductive traits. Our findings advance our understanding of extreme environment adaptation of highland chickens, and provide some variants and genes beneficial to TBC genetic breeding improvement.
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Affiliation(s)
- Jiuhong Nan
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Sendong Yang
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Xiaojian Zhang
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Tianze Leng
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Marine Ecosystem Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China
| | - Joan Zhuoma
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Neighborhood Committee Office, Xigaze City, China
| | - Rensang Zhuoma
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Luomai Township People's Government of Seni District, Naqu City, China
| | - Jingwei Yuan
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinsong Pi
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan, China
| | - Zheya Sheng
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Shijun Li
- State Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.,Key Laboratory of Smart Farming for Agricultural Animals, Ministry of Education, Huazhong Agricultural University, Wuhan, China.,Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
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Wu MY, Forcina G, Low GW, Sadanandan KR, Gwee CY, van Grouw H, Wu S, Edwards SV, Baldwin MW, Rheindt FE. Historic samples reveal loss of wild genotype through domestic chicken introgression during the Anthropocene. PLoS Genet 2023; 19:e1010551. [PMID: 36656838 PMCID: PMC9851510 DOI: 10.1371/journal.pgen.1010551] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 11/30/2022] [Indexed: 01/20/2023] Open
Abstract
Human activities have precipitated a rise in the levels of introgressive gene flow among animals. The investigation of conspecific populations at different time points may shed light on the magnitude of human-mediated introgression. We used the red junglefowl Gallus gallus, the wild ancestral form of the chicken, as our study system. As wild junglefowl and domestic chickens readily admix, conservationists fear that domestic introgression into junglefowl may compromise their wild genotype. By contrasting the whole genomes of 51 chickens with 63 junglefowl from across their natural range, we found evidence of a loss of the wild genotype across the Anthropocene. When comparing against the genomes of junglefowl from approximately a century ago using rigorous ancient-DNA protocols, we discovered that levels of domestic introgression are not equal among and within modern wild populations, with the percentage of domestic ancestry around 20-50%. We identified a number of domestication markers in which chickens are deeply differentiated from historic junglefowl regardless of breed and/or geographic provenance, with eight genes under selection. The latter are involved in pathways dealing with development, reproduction and vision. The wild genotype is an allelic reservoir that holds most of the genetic diversity of G. gallus, a species which is immensely important to human society. Our study provides fundamental genomic infrastructure to assist in efforts to prevent a further loss of the wild genotype through introgression of domestic alleles.
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Affiliation(s)
- Meng Yue Wu
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Giovanni Forcina
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Gabriel Weijie Low
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Keren R. Sadanandan
- Evolution of Sensory Systems Research Group, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Chyi Yin Gwee
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Hein van Grouw
- Bird Group, Department of Life Sciences, Natural History Museum, Tring, United Kingdom
| | - Shaoyuan Wu
- Department of Biochemistry and Molecular Biology, Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, Chin
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, China
| | - Scott V. Edwards
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Maude W. Baldwin
- Evolution of Sensory Systems Research Group, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Frank E. Rheindt
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
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Wang D, Li X, Zhang P, Cao Y, Zhang K, Qin P, Guo Y, Li Z, Tian Y, Kang X, Liu X, Li H. ELOVL gene family plays a virtual role in response to breeding selection and lipid deposition in different tissues in chicken (Gallus gallus). BMC Genomics 2022; 23:705. [PMID: 36253734 PMCID: PMC9575239 DOI: 10.1186/s12864-022-08932-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 10/10/2022] [Indexed: 11/11/2022] Open
Abstract
Background Elongases of very long chain fatty acids (ELOVLs), a family of first rate-limiting enzymes in the synthesis of long-chain fatty acids, play an essential role in the biosynthesis of complex lipids. Disrupting any of ELOVLs affects normal growth and development in mammals. Genetic variations in ELOVLs are associated with backfat or intramuscular fatty acid composition in livestock. However, the effects of ELOVL gene family on breeding selection and lipid deposition in different tissues are still unknown in chickens. Results Genetic variation patterns and genetic associations analysis showed that the genetic variations of ELOVL genes were contributed to breeding selection of commercial varieties in chicken, and 14 SNPs in ELOVL2-6 were associated with body weight, carcass or fat deposition traits. Especially, one SNP rs17631638T > C in the promoter of ELOVL3 was associated with intramuscular fat content (IMF), and its allele frequency was significantly higher in native and layer breeds compared to that in commercial broiler breeds. Quantitative real-time PCR (qRT-PCR) determined that the ELOVL3 expressions in pectoralis were affected by the genotypes of rs17631638T > C. In addition, the transcription levels of ELOVL genes except ELOVL5 were regulated by estrogen in chicken liver and hypothalamus with different regulatory pathways. The expression levels of ELOVL1-6 in hypothalamus, liver, abdominal fat and pectoralis were correlated with abdominal fat weight, abdominal fat percentage, liver lipid content and IMF. Noteworthily, expression of ELOVL3 in pectoralis was highly positively correlated with IMF and glycerophospholipid molecules, including phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl glycerol and phospholipids inositol, rich in ω-3 and ω-6 long-chain unsaturated fatty acids, suggesting ELOVL3 could contribute to intramuscular fat deposition by increasing the proportion of long-chain unsaturated glycerophospholipid molecules in pectoralis. Conclusions In summary, we demonstrated the genetic contribution of ELOVL gene family to breeding selection for specialized varieties, and revealed the expression regulation of ELOVL genes and their potential roles in regulating lipid deposition in different tissues. This study provides new insights into understanding the functions of ELOVL family on avian growth and lipid deposition in different tissues and the genetic variation in ELOVL3 may aid the marker-assisted selection of meat quality in chicken. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08932-8.
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Affiliation(s)
- Dandan Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
| | - Xinyan Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
| | - Panpan Zhang
- Henan Institute of Veterinary Drug and Feed Control, Zhengzhou, 450002, China
| | - Yuzhu Cao
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
| | - Ke Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
| | - Panpan Qin
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
| | - Yulong Guo
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
| | - Zhuanjian Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China.,Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, 450046, China.,International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, 450046, China
| | - Yadong Tian
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China.,Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, 450046, China.,International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, 450046, China
| | - Xiangtao Kang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China.,Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, 450046, China.,International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, 450046, China
| | - Xiaojun Liu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China. .,Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, 450046, China. .,International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, 450046, China.
| | - Hong Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China. .,Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, 450046, China. .,International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, 450046, China.
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39
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Marcos S, Parejo M, Estonba A, Alberdi A. Recovering High-Quality Host Genomes from Gut Metagenomic Data through Genotype Imputation. ADVANCED GENETICS (HOBOKEN, N.J.) 2022; 3:2100065. [PMID: 36620197 PMCID: PMC9744478 DOI: 10.1002/ggn2.202100065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 03/05/2022] [Indexed: 01/11/2023]
Abstract
Metagenomic datasets of host-associated microbial communities often contain host DNA that is usually discarded because the amount of data is too low for accurate host genetic analyses. However, genotype imputation can be employed to reconstruct host genotypes if a reference panel is available. Here, the performance of a two-step strategy is tested to impute genotypes from four types of reference panels built using different strategies to low-depth host genome data (≈2× coverage) recovered from intestinal samples of two chicken genetic lines. First, imputation accuracy is evaluated in 12 samples for which both low- and high-depth sequencing data are available, obtaining high imputation accuracies for all tested panels (>0.90). Second, the impact of reference panel choice in population genetics statistics on 100 chickens is assessed, all four panels yielding comparable results. In light of the observations, the feasibility and application of the applied imputation strategy are discussed for different species with regard to the host DNA proportion, genomic diversity, and availability of a reference panel. This method enables leveraging insofar discarded host DNA to get insights into the genetic structure of host populations, and in doing so, facilitates the implementation of hologenomic approaches that jointly analyze host and microbial genomic data.
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Affiliation(s)
- Sofia Marcos
- Applied Genomics and BioinformaticsUniversity of the Basque Country (UPV/EHU)LeioaBilbao48940Spain
| | - Melanie Parejo
- Applied Genomics and BioinformaticsUniversity of the Basque Country (UPV/EHU)LeioaBilbao48940Spain
| | - Andone Estonba
- Applied Genomics and BioinformaticsUniversity of the Basque Country (UPV/EHU)LeioaBilbao48940Spain
| | - Antton Alberdi
- Center for Evolutionary HologenomicsGLOBE InstituteUniversity of CopenhagenCopenhagen1353Denmark
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40
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Bakovic V, Höglund A, Martin Cerezo ML, Henriksen R, Wright D. Genomic and gene expression associations to morphology of a sexual ornament in the chicken. G3 GENES|GENOMES|GENETICS 2022; 12:6633936. [PMID: 35801935 PMCID: PMC9434260 DOI: 10.1093/g3journal/jkac174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 06/27/2022] [Indexed: 11/12/2022]
Abstract
How sexual selection affects the genome ultimately relies on the strength and type of selection, and the genetic architecture of the involved traits. While associating genotype with phenotype often utilizes standard trait morphology, trait representations in morphospace using geometric morphometric approaches receive less focus in this regard. Here, we identify genetic associations to a sexual ornament, the comb, in the chicken system (Gallus gallus). Our approach combined genome-wide genotype and gene expression data (>30k genes) with different aspects of comb morphology in an advanced intercross line (F8) generated by crossing a wild-type Red Junglefowl with a domestic breed of chicken (White Leghorn). In total, 10 quantitative trait loci were found associated to various aspects of comb shape and size, while 1,184 expression QTL were found associated to gene expression patterns, among which 98 had overlapping confidence intervals with those of quantitative trait loci. Our results highlight both known genomic regions confirming previous records of a large effect quantitative trait loci associated to comb size, and novel quantitative trait loci associated to comb shape. Genes were considered candidates affecting comb morphology if they were found within both confidence intervals of the underlying quantitative trait loci and eQTL. Overlaps between quantitative trait loci and genome-wide selective sweeps identified in a previous study revealed that only loci associated to comb size may be experiencing on-going selection under domestication.
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Affiliation(s)
- Vid Bakovic
- IFM Biology, University of Linköping , Linköping 581 83, Sweden
| | - Andrey Höglund
- Science for Life Laboratory, Department of Environmental Science, Stockholm University , Stockholm 106 91, Sweden
| | | | - Rie Henriksen
- IFM Biology, University of Linköping , Linköping 581 83, Sweden
| | - Dominic Wright
- IFM Biology, University of Linköping , Linköping 581 83, Sweden
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41
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Shi S, Shao D, Yang L, Liang Q, Han W, Xue Q, Qu L, Leng L, Li Y, Zhao X, Dong P, Walugembe M, Kayang BB, Muhairwa AP, Zhou H, Tong H. Whole Genome Analyses Reveal Novel Genes Associated with Chicken Adaptation to Tropical and Frigid Environments. J Adv Res 2022; 47:13-25. [PMID: 35907630 PMCID: PMC10173185 DOI: 10.1016/j.jare.2022.07.005] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/01/2022] [Accepted: 07/17/2022] [Indexed: 01/25/2023] Open
Abstract
INTRODUCTION Investigating the genetic footprints of historical temperature selection can get insights to the local adaptation and feasible influences of climate change on long-term population dynamics. OBJECT Chicken is a significative species to study genetic adaptation on account of its similar domestication track related to human activity with the most diversified varieties. Yet, few studies have demonstrated the genetic signatures of its adaptation to naturally tropical and frigid environments. METHOD Here, we generated whole genome resequencing of 119 domesticated chickens in China including the following breeds which are in order of breeding environmental temperature from more tropical to more frigid: Wenchang chicken (WCC), green-shell chicken (GSC), Tibetan chicken (TBC), and Lindian chicken (LDC). RESULTS Our results showed WCC branched off earlier than LDC with an evident genetic admixture between WCC and LDC, suggesting their closer genetic relationship. Further comparative genomic analyses solute carrier family 33 member 1 (SLC33A1) and thyroid stimulating hormone receptor (TSHR) genes exhibited stronger signatures for positive selection in the genome of the more tropical WCC. Furthermore, genotype data from about 3,000 African local ecotypes confirmed that allele frequencies of single nucleotide polymorphisms (SNPs) in these 2 genes appeared strongly associated with tropical environment adaptation. In addition, the NADH:ubiquinone oxidoreductase subunit S4 (NDUFS4) gene exhibited a strong signature for positive selection in the LDC genome, and SNPs with marked allele frequency differences indicated a significant relationship with frigid environment adaptation. CONCLUSION Our findings partially clarify how selection footprints from environmental temperature stress can lead to advantageous genomic adaptions to tropical and frigid environments in poultry and provide a valuable resource for selective breeding of chickens.
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Affiliation(s)
- Shourong Shi
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Dan Shao
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Lingyun Yang
- Novogene Bioinformatics Institute, Beijing 10089, China
| | - Qiqi Liang
- Novogene Bioinformatics Institute, Beijing 10089, China
| | - Wei Han
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Qian Xue
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Liang Qu
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Li Leng
- College of Animal Science and technology, Northeast Agricultural University, Harbin, Heilongjiang, 150038, China
| | - Yishu Li
- Tropical Crop Germplasm Research Institute, Haikou, Hainan, 571101, China
| | - Xiaogang Zhao
- Agriculture and Animal Husbandry Rural and Science and Technology Bureau, Xiangcheng County, Ganzi Tibetan Autonomous Prefecture, Sichuan, 626000, China
| | - Ping Dong
- Agriculture and Animal Husbandry Rural and Science and Technology Bureau, Xiangcheng County, Ganzi Tibetan Autonomous Prefecture, Sichuan, 626000, China
| | - Muhammed Walugembe
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - Boniface B Kayang
- Department of Animal Science, University of Ghana, Legon, Accra 233, Ghana
| | - Amandus P Muhairwa
- Department of Veterinary Medicine and Public Health, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, P.O. Box 3000 Chuo Kikuu, Morogoro, Tanzania
| | - Huaijun Zhou
- Department of Animal Science, College of Agricultural and Environmental Sciences, University of California, Davis, CA 95616, USA
| | - Haibing Tong
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China.
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42
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Heidaritabar M, Carney V, Groenen MAM, Plastow G. Assessing the genomic diversity and relatedness in 10 Canadian heritage chicken lines using whole-genome sequence data. J Anim Breed Genet 2022; 139:556-573. [PMID: 35579203 DOI: 10.1111/jbg.12720] [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: 03/24/2021] [Accepted: 05/01/2022] [Indexed: 11/29/2022]
Abstract
In the past 50 years, there has been a steep increase in the demand for poultry products, met by increasing production along with genetic selection for improved growth, efficiency, health and reproduction. The selection tends to reduce the number and type of genetic resources contributing to the majority of production. The University of Alberta maintains 10 heritage chicken lines (Brown Leghorn (BL), Light Sussex (LS), New Hampshire (NH), Saskatchewan Barred Rock (SaskBR), Shaver Barred Rock (ShaverBR), Shaver Rhode Island Red (RIR), White Leghorn (WL) and three commercial crosses called Alberta Meat Control strains 1957 (AMC-1957), 1978 sire line (AMC-1978-20S) and 1978 dam line (AMC-1978-30D), that played a large role in the evolution of the poultry industry in Canada. Since these lines have not been subjected to the same intensive selection pressures as commercial counterparts, they may contain unique genetic variants lost in commercial lines. Thus, for conservation management of these lines, the first step is to assess their genetic diversity. 71 male samples from across 10 lines were analysed using whole-genome sequencing and patterns of genetic diversity and relatedness among these lines were explored. AMC-1978-30D showed the highest genetic diversity as reflected in observed and expected heterozygosity (0.327 and 0.250), percentage of polymorphic markers (~ 65%) and average recent inbreeding coefficient (-0.039), followed by AMC-1978-20S and AMC-1957. BL showed the lowest genetic diversity as reflected in observed and expected heterozygosity (0.130 and 0.116), percentage of polymorphic markers (~31%) and average recent inbreeding coefficient (0.577), followed by LS, WL and NH. Our findings highlight the need for special attention for the populations of BL, WL, LS and NH, with the largest levels of inbreeding. Our results can be used to develop a breeding strategy to optimize and conserve the genetic variation present in heritage lines.
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Affiliation(s)
- Marzieh Heidaritabar
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, Alberta, Canada
| | - Valerie Carney
- Poultry Innovation Partnership, University of Alberta, Edmonton, Alberta, Canada
| | - Martien A M Groenen
- Animal Breeding and Genomics, Wageningen University & Research, Wageningen, the Netherlands
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, Alberta, Canada
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43
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Fu W, Wang R, Xu N, Wang J, Li R, Asadollahpour Nanaei H, Nie Q, Zhao X, Han J, Yang N, Jiang Y. Galbase: a comprehensive repository for integrating chicken multi-omics data. BMC Genomics 2022; 23:364. [PMID: 35549894 PMCID: PMC9097087 DOI: 10.1186/s12864-022-08598-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/28/2022] [Indexed: 11/10/2022] Open
Abstract
Background Multi-omics data can provide a stereoscopic view to explore potential causal variations and genes, as well as underlying genetic mechanisms of complex traits. However, for many non-mammalian species, including chickens, these resources are poorly integrated and reused, greatly limiting genetic research and breeding processes of the species. Results Here, we constructed Galbase, an easily accessible repository that integrates public chicken multi-omics data from 928 re-sequenced genomes, 429 transcriptomes, 379 epigenomes, 15,275 QTL entries, and 7,526 associations. A total of 21.67 million SNPs, 2.71 million InDels, and 488,583 cis-regulatory elements were included. Galbase allows users to retrieve genomic variations in geographical maps, gene expression profiling in heatmaps, and epigenomic signals in peak patterns. It also provides modules for batch annotation of genes, regions, and loci based on multi-layered omics data. Additionally, a series of convenient tools, including the UCSC Genome Browser, WashU Epigenome Browser, BLAT, BLAST, and LiftOver, were also integrated to facilitate search, visualization, and analysis of sequence features. Conclusion Galbase grants new opportunities to research communities to undertake in-depth functional genomic studies on chicken. All features of Galbase make it a useful resource to identify genetic variations responsible for chicken complex traits. Galbase is publicly available at http://animal.nwsuaf.edu.cn/ChickenVar. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08598-2.
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Affiliation(s)
- Weiwei Fu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Rui Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Naiyi Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Jinxin Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Hojjat Asadollahpour Nanaei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Qinghua Nie
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong, China
| | - Xin Zhao
- Department of Animal Science, McGill University, Montreal, Québec, Canada
| | - Jianlin Han
- CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.,Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China. .,Center for Functional Genomics, Institute of Future Agriculture, Northwest A&F University, Yangling, China.
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Shen M, Li T, Feng Y, Chen Z, Dou T, Wu P, Wang K, Lu J, Qu L. Exploring the expression and preliminary function of chicken regulator of G protein signalling 3 ( RGS3) gene in follicular development. Br Poult Sci 2022; 63:613-620. [PMID: 35522181 DOI: 10.1080/00071668.2022.2071597] [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: 11/02/2022]
Abstract
1. The following study explored the expression and preliminary function of RGS3. The spatial and temporal expression patterns of the RGS3 gene were analysed in the ovarian stroma of Shendan No. 6 Green shell hens and Hy-line Brown hens at four time points (6, 28, 40 and 52 weeks old), as well as in various organs and follicles of Hy-line Brown hens.2. Based on the genomic and protein sequences of RGS3 in NCBI database, phylogenetic trees were constructed using MEGA-X. The protein interaction network was analysed using STRING. According to the results of protein-protein interaction network and pathways, the mRNA expression levels of RGS3 and three interaction proteins were explored by qRT-PCR in vitro.3. Spatio-temporal expression data revealed that RGS3 mRNA was expressed in all the organs tested, being highest in the hypothalamus. In different follicles, RGS3 mRNA was highly expressed in post-ovulatory follicles, followed by ovarian stroma and large white follicles. The expression levels of RGS3 mRNA in the ovarian stroma were significantly higher in Shendan No. 6 Green shell hens than that in the Hy-line Brown hens at all egg-laying stages.4. The phylogenetic tree results showed that ducks, geese and chickens had higher homology based on the genomic and protein sequence of RGS3. Moreover, chicken RGS3 interacted with GSK3B, RAF1 and BRAF based on STRING prediction. In vitro follicle stimulating hormone (FSH) treatment showed that mRNA expression levels of RGS3 and those of its predicted interacting proteins BRAF and GSK3B decreased with increasing FSH concentration. The results suggested that RGS3 responds to FSH and may play an important role in the regulation follicular development in chicken.
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Affiliation(s)
- Manman Shen
- College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, 225108, China.,Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, China.,Jiangsu Key Laboratory of Animal genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Tao Li
- College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, 225108, China
| | - Yuan Feng
- College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, 225108, China
| | - Zikang Chen
- College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, 225108, China
| | - Taocun Dou
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, China
| | - Ping Wu
- College of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, 225108, China
| | - Kehua Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, China
| | - Jian Lu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, China
| | - Liang Qu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, China
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Alberdi A, Andersen SB, Limborg MT, Dunn RR, Gilbert MTP. Disentangling host-microbiota complexity through hologenomics. Nat Rev Genet 2022; 23:281-297. [PMID: 34675394 DOI: 10.1038/s41576-021-00421-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2021] [Indexed: 02/07/2023]
Abstract
Research on animal-microbiota interactions has become a central topic in biological sciences because of its relevance to basic eco-evolutionary processes and applied questions in agriculture and health. However, animal hosts and their associated microbial communities are still seldom studied in a systemic fashion. Hologenomics, the integrated study of the genetic features of a eukaryotic host alongside that of its associated microbes, is becoming a feasible - yet still underexploited - approach that overcomes this limitation. Acknowledging the biological and genetic properties of both hosts and microbes, along with the advantages and disadvantages of implemented techniques, is essential for designing optimal studies that enable some of the major questions in biology to be addressed.
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Affiliation(s)
- Antton Alberdi
- Center for Evolutionary Hologenomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Sandra B Andersen
- Center for Evolutionary Hologenomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Morten T Limborg
- Center for Evolutionary Hologenomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Robert R Dunn
- Center for Evolutionary Hologenomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,Department of Applied Ecology, North Carolina State University, Raleigh, NC, USA
| | - M Thomas P Gilbert
- Center for Evolutionary Hologenomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,University Museum, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
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Willson NL, Hughes RJ, Hynd PI, Forder REA. Layers, broiler chickens and their F1 cross develop distinctly different caecal microbial communities when hatched and reared together. J Appl Microbiol 2022; 133:448-457. [PMID: 35362651 PMCID: PMC9546199 DOI: 10.1111/jam.15558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/15/2022] [Accepted: 03/29/2022] [Indexed: 12/03/2022]
Abstract
Aim To compare the caecal microbiota of layer, broiler, and intermediate F1 layer × broiler cross birds with the hypothesis that significant differences in caecal microbial composition would persist between the three groups when host and environmental interactions were minimized. Methods and Results Caecal contents were characterized using 16S rRNA for males of broiler (n = 12), layer (n = 12) and F1 layer × broiler cross (n = 9) birds that were hatched and reared under the same conditions. The microbial community structure differed significantly between the three groups of birds at phylum, genus and OTU levels, with clear separation of the groups observed. Firmicutes was the phylum most represented across samples; however, the high abundance of Proteobacteria in the layer birds at d28 post‐hatch was unexpected, and driven by a higher abundance of E. coli. Conclusions The microbiota phylotype between broilers, layers and their F1 cross significantly differed in community structure, diversity and relative abundance in the absence of environmental confounding, which is generally difficult to avoid in microbial studies. Significance and Impact of Study The results provide a unique comparison and evidence that there is a strong genetic component driving microbial composition within poultry strains, despite the embryonic development occurring in ovo.
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Affiliation(s)
- Nicky-Lee Willson
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, South Australia, Australia
| | - Robert J Hughes
- Formerly with the South Australian Research and Development Institute (SARDI), Pig and Poultry Production Institute (PPPI), Roseworthy, South Australia, Australia
| | - Philip I Hynd
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, South Australia, Australia
| | - Rebecca E A Forder
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, South Australia, Australia
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Sun J, Chen T, Zhu M, Wang R, Huang Y, Wei Q, Yang M, Liao Y. Whole-genome sequencing revealed genetic diversity and selection of Guangxi indigenous chickens. PLoS One 2022; 17:e0250392. [PMID: 35290380 PMCID: PMC8923445 DOI: 10.1371/journal.pone.0250392] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 02/20/2022] [Indexed: 11/19/2022] Open
Abstract
Guangxi chickens play a crucial role in promoting the high-quality development of the broiler industry in China, but their value and potential are yet to be discovered. To determine the genetic diversity and population structure of Guangxi indigenous chicken, we analyzed the whole genomes of 185 chickens from 8 phenotypically and geographically representative Guangxi chicken breeds, together with 12 RJFt, 12 BRA and 12 WL genomes available from previous studies. Calculation of heterozygosity (Hp), nucleotide diversity (π), and LD level indicated that Guangxi populations were characterized by higher genetic diversity and lower differentiation than RJFt and commercial breeds except for HGFC. Population structure analysis also confirmed the introgression from commercial broiler breeds. Each population clustered together while the overall differentiation was slight. MA has the richest genetic diversity among all varieties. Selective sweep analysis revealed BCO2, EDN3 and other candidate genes had received strong selection in local breeds. These also provided novel breeding visual and data basis for future breeding.
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Affiliation(s)
- Junli Sun
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Tao Chen
- BGI Institute of Applied Agriculture, BGI-Shenzhen, Shenzhen, China
| | - Min Zhu
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Ran Wang
- BGI Institute of Applied Agriculture, BGI-Shenzhen, Shenzhen, China
| | - Yingfei Huang
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Qiang Wei
- BGI Institute of Applied Agriculture, BGI-Shenzhen, Shenzhen, China
| | - Manman Yang
- BGI-Shenzhen, Shenzhen, China
- * E-mail: (MY); (YL)
| | - Yuying Liao
- Guangxi Veterinary Research Institute, Nanning, Guangxi, China
- * E-mail: (MY); (YL)
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Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations. BMC Genomics 2022; 23:193. [PMID: 35264116 PMCID: PMC8908679 DOI: 10.1186/s12864-022-08418-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 02/24/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens. RESULTS The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP - SNP and DUP - SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays. CONCLUSIONS The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.
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Liu J, Shen Q, Bao H. Comparison of seven SNP calling pipelines for the next-generation sequencing data of chickens. PLoS One 2022; 17:e0262574. [PMID: 35100292 PMCID: PMC8803190 DOI: 10.1371/journal.pone.0262574] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 12/29/2021] [Indexed: 11/18/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs) are widely used in genome-wide association studies and population genetics analyses. Next-generation sequencing (NGS) has become convenient, and many SNP-calling pipelines have been developed for human NGS data. We took advantage of a gap knowledge in selecting the appropriated SNP calling pipeline to handle with high-throughput NGS data. To fill this gap, we studied and compared seven SNP calling pipelines, which include 16GT, genome analysis toolkit (GATK), Bcftools-single (Bcftools single sample mode), Bcftools-multiple (Bcftools multiple sample mode), VarScan2-single (VarScan2 single sample mode), VarScan2-multiple (VarScan2 multiple sample mode) and Freebayes pipelines, using 96 NGS data with the different depth gradients of approximately 5X, 10X, 20X, 30X, 40X, and 50X coverage from 16 Rhode Island Red chickens. The sixteen chickens were also genotyped with a 50K SNP array, and the sensitivity and specificity of each pipeline were assessed by comparison to the results of SNP arrays. For each pipeline, except Freebayes, the number of detected SNPs increased as the input read depth increased. In comparison with other pipelines, 16GT, followed by Bcftools-multiple, obtained the most SNPs when the input coverage exceeded 10X, and Bcftools-multiple obtained the most when the input was 5X and 10X. The sensitivity and specificity of each pipeline increased with increasing input. Bcftools-multiple had the highest sensitivity numerically when the input ranged from 5X to 30X, and 16GT showed the highest sensitivity when the input was 40X and 50X. Bcftools-multiple also had the highest specificity, followed by GATK, at almost all input levels. For most calling pipelines, there were no obvious changes in SNP numbers, sensitivities or specificities beyond 20X. In conclusion, (1) if only SNPs were detected, the sequencing depth did not need to exceed 20X; (2) the Bcftools-multiple may be the best choice for detecting SNPs from chicken NGS data, but for a single sample or sequencing depth greater than 20X, 16GT was recommended. Our findings provide a reference for researchers to select suitable pipelines to obtain SNPs from the NGS data of chickens or nonhuman animals.
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Affiliation(s)
- Jing Liu
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Qingmiao Shen
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Haigang Bao
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, China
- * E-mail:
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Ballan M, Bovo S, Schiavo G, Schiavitto M, Negrini R, Fontanesi L. Genomic diversity and signatures of selection in meat and fancy rabbit breeds based on high-density marker data. Genet Sel Evol 2022; 54:3. [PMID: 35062866 PMCID: PMC8780294 DOI: 10.1186/s12711-022-00696-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 01/07/2022] [Indexed: 11/23/2022] Open
Abstract
Background Domestication of the rabbit (Oryctolagus cuniculus) has led to a multi-purpose species that includes many breeds and lines with a broad phenotypic diversity, mainly for external traits (e.g. coat colours and patterns, fur structure, and morphometric traits) that are valued by fancy rabbit breeders. As a consequence of this human-driven selection, distinct signatures are expected to be present in the rabbit genome, defined as signatures of selection or selective sweeps. Here, we investigated the genome of three Italian commercial meat rabbit breeds (Italian Silver, Italian Spotted and Italian White) and 12 fancy rabbit breeds (Belgian Hare, Burgundy Fawn, Champagne d’Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex, Rhinelander and Thuringian) by using high-density single nucleotide polymorphism data. Signatures of selection were identified based on the fixation index (FST) statistic with different approaches, including single-breed and group-based methods, the latter comparing breeds that are grouped based on external traits (different coat colours and body sizes) and types (i.e. meat vs. fancy breeds). Results We identified 309 genomic regions that contained signatures of selection and that included genes that are known to affect coat colour (ASIP, MC1R and TYR), coat structure (LIPH), and body size (LCORL/NCAPG, COL11A1 and HOXD) in rabbits and that characterize the investigated breeds. Their identification proves the suitability of the applied methodologies for capturing recent selection events. Other regions included novel candidate genes that might contribute to the phenotypic variation among the analyzed breeds, including genes for pigmentation-related traits (EDNRA, EDNRB, MITF and OCA2) and body size, with a strong candidate for dwarfism in rabbit (COL2A1). Conclusions We report a genome-wide view of genetic loci that underlie the main phenotypic differences in the analyzed rabbit breeds, which can be useful to understand the shift from the domestication process to the development of breeds in O. cuniculus. These results enhance our knowledge about the major genetic loci involved in rabbit external traits and add novel information to understand the complexity of the genetic architecture underlying body size in mammals. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00696-9.
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