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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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Cendron F, Cassandro M, Penasa M. Genome-wide investigation to assess copy number variants in the Italian local chicken population. J Anim Sci Biotechnol 2024; 15:2. [PMID: 38167097 PMCID: PMC10763469 DOI: 10.1186/s40104-023-00965-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Copy number variants (CNV) hold significant functional and evolutionary importance. Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock. High-density chips have enabled the detection of CNV with increased resolution, leading to the identification of even small CNV. This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome. RESULTS Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV. The majority of CNV in the investigated breeds were of types 0 and 1, and the minimum length of CNV was significantly larger than that reported in previous studies. Interestingly, a high proportion of the length of chromosome 16 was covered by copy number variation regions (CNVR), with the major histocompatibility complex being the likely cause. Among the genes identified within CNVR, only those present in at least five animals across breeds (n = 95) were discussed to reduce the focus on redundant CNV. Some of these genes have been associated to functional traits in chickens. Notably, several CNVR on different chromosomes harbor genes related to muscle development, tissue-specific biological processes, heat stress resistance, and immune response. Quantitative trait loci (QTL) were also analyzed to investigate potential overlapping with the identified CNVR: 54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size, carcass characteristics, egg production, egg components, fat deposition, and feed intake. CONCLUSIONS The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.
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Affiliation(s)
- Filippo Cendron
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale Dell'Università 16, 35020, Legnaro, PD, Italy.
| | - Martino Cassandro
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale Dell'Università 16, 35020, Legnaro, PD, Italy
- Federazione Delle Associazioni Nazionali Di Razza E Specie, Via XXIV Maggio 43, 00187, Rome, Italy
| | - Mauro Penasa
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale Dell'Università 16, 35020, Legnaro, PD, Italy
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Cui L, Yang B, Xiao S, Gao J, Baud A, Graham D, McBride M, Dominiczak A, Schafer S, Aumatell RL, Mont C, Teruel AF, Hübner N, Flint J, Mott R, Huang L. Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing. Genome Biol 2023; 24:215. [PMID: 37773188 PMCID: PMC10540365 DOI: 10.1186/s13059-023-03060-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 09/18/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. RESULTS We systematically investigate both dominance-here representing any non-additive within-locus interaction-and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. CONCLUSIONS Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.
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Affiliation(s)
- Leilei Cui
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
- UCL Genetics Institute, University College London, London, WC1E 6BT, UK
- Human Aging Research Institute and School of Life Science, Nanchang University, and Jiangxi Key Laboratory of Human Aging, Jiangxi, China
- School of Life Sciences, Nanchang University, Nanchang, China
| | - Bin Yang
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
| | - Shijun Xiao
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
| | - Jun Gao
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
| | - Amelie Baud
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Delyth Graham
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TA, UK
| | - Martin McBride
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TA, UK
| | - Anna Dominiczak
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TA, UK
| | - Sebastian Schafer
- Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Regina Lopez Aumatell
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Carme Mont
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Albert Fernandez Teruel
- Departamento de Psiquiatría y Medicina Legal, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Norbert Hübner
- Genetics and Genomics of Cardiovascular Diseases Research Group, Max Delbrück Center (MDC) for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- DZHK (German Center for Cardiovascular Research) Partner Site Berlin, Berlin, Germany
- Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jonathan Flint
- Department of Psychiatry and Behavioral Sciences, Brain Research Institute, University of California, Los Angeles, CA, USA
| | - Richard Mott
- UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| | - Lusheng Huang
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China.
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Yang J, Tang J, He X, Di R, Zhang X, Zhang J, Guo X, Chu M, Hu W. Comparative Transcriptomics Identify Key Pituitary Circular RNAs That Participate in Sheep ( Ovis aries) Reproduction. Animals (Basel) 2023; 13:2711. [PMID: 37684975 PMCID: PMC10486758 DOI: 10.3390/ani13172711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 08/15/2023] [Accepted: 08/17/2023] [Indexed: 09/10/2023] Open
Abstract
CircRNAs have been found to play key roles in many biological processes and have diverse biological functions. There have been studies on circRNAs in sheep pituitary, and some important circRNAs have been found. But there are still few studies on circRNAs in sheep pituitary with different fecundity. In this study, we obtained the circRNAs expression profiles in the pituitary of FecB ++ genotype Small Tail Han sheep with different fecundity and estrous phases. A total of 34,878 circRNAs were identified in 12 pituitary samples, 300 differentially expressed circRNAs (DE circRNAs) (down: 104; up: 196) were identified in polytocous sheep in the follicular phase (PF) and monotocous sheep in the follicular phase (MF) (PF vs. MF), and 347 DE circRNAs (down: 162; up: 185) were identified in polytocous sheep in the luteal phase (PL) and monotocous sheep in the luteal phase (ML) (PL vs. ML). Cortisol synthesis and secretion pathway (follicular phase) and estrogen signaling pathway (luteal phase) were obtained by functional enrichment analysis of circRNAs source genes. Competing endogenous RNA (ceRNA) network analysis of key DE circRNAs revealed that oar-circ-0022776 (source gene ITPR2, follicular phase) targeted oar-miR-432, oar-circ-0009003 (source gene ITPR1, luteal phase) and oar-circ-0003113 (source gene PLCB1, luteal phase) targeted oar-miR-370-3p. We also explored the coding ability of DE circRNAs. In conclusion, our study shows that changes in the pituitary circRNAs may be related to the response of the pituitary to steroid hormones and regulate the reproductive process of sheep by affecting the pituitary function. Results of this study provide some new information for understanding the functions of circRNAs and the fecundity of FecB ++ genotype sheep.
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Affiliation(s)
- Jianqi Yang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (J.Y.); (X.H.); (R.D.)
| | - Jishun Tang
- Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China;
| | - Xiaoyun He
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (J.Y.); (X.H.); (R.D.)
| | - Ran Di
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (J.Y.); (X.H.); (R.D.)
| | - Xiaosheng Zhang
- Tianjin Key Laboratory of Animal Molecular Breeding and Biotechnology, Tianjin Engineering Research Center of Animal Healthy Farming, Institute of Animal Science and Veterinary, Tianjin Academy of Agricultural Sciences, Tianjin 300381, China; (X.Z.); (J.Z.); (X.G.)
| | - Jinlong Zhang
- Tianjin Key Laboratory of Animal Molecular Breeding and Biotechnology, Tianjin Engineering Research Center of Animal Healthy Farming, Institute of Animal Science and Veterinary, Tianjin Academy of Agricultural Sciences, Tianjin 300381, China; (X.Z.); (J.Z.); (X.G.)
| | - Xiaofei Guo
- Tianjin Key Laboratory of Animal Molecular Breeding and Biotechnology, Tianjin Engineering Research Center of Animal Healthy Farming, Institute of Animal Science and Veterinary, Tianjin Academy of Agricultural Sciences, Tianjin 300381, China; (X.Z.); (J.Z.); (X.G.)
| | - Mingxing Chu
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (J.Y.); (X.H.); (R.D.)
| | - Wenping Hu
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (J.Y.); (X.H.); (R.D.)
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Abdelmanova AS, Dotsev AV, Romanov MN, Stanishevskaya OI, Gladyr EA, Rodionov AN, Vetokh AN, Volkova NA, Fedorova ES, Gusev IV, Griffin DK, Brem G, Zinovieva NA. Unveiling Comparative Genomic Trajectories of Selection and Key Candidate Genes in Egg-Type Russian White and Meat-Type White Cornish Chickens. BIOLOGY 2021; 10:biology10090876. [PMID: 34571753 PMCID: PMC8469556 DOI: 10.3390/biology10090876] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 08/20/2021] [Accepted: 08/30/2021] [Indexed: 01/14/2023]
Abstract
Comparison of genomic footprints in chicken breeds with different selection history is a powerful tool in elucidating genomic regions that have been targeted by recent and more ancient selection. In the present work, we aimed at examining and comparing the trajectories of artificial selection in the genomes of the native egg-type Russian White (RW) and meat-type White Cornish (WC) breeds. Combining three different statistics (top 0.1% SNP by FST value at pairwise breed comparison, hapFLK analysis, and identification of ROH island shared by more than 50% of individuals), we detected 45 genomic regions under putative selection including 11 selective sweep regions, which were detected by at least two different methods. Four of such regions were breed-specific for each of RW breed (on GGA1, GGA5, GGA8, and GGA9) and WC breed (on GGA1, GGA5, GGA8, and GGA28), while three remaining regions on GGA2 (two sweeps) and GGA3 were common for both breeds. Most of identified genomic regions overlapped with known QTLs and/or candidate genes including those for body temperatures, egg productivity, and feed intake in RW chickens and those for growth, meat and carcass traits, and feed efficiency in WC chickens. These findings were concordant with the breed origin and history of their artificial selection. We determined a set of 188 prioritized candidate genes retrieved from the 11 overlapped regions of putative selection and reviewed their functions relative to phenotypic traits of interest in the two breeds. One of the RW-specific sweep regions harbored the known domestication gene, TSHR. Gene ontology and functional annotation analysis provided additional insight into a functional coherence of genes in the sweep regions. We also showed a greater candidate gene richness on microchromosomes relative to macrochromosomes in these genomic areas. Our results on the selection history of RW and WC chickens and their key candidate genes under selection serve as a profound information for further conservation of their genomic diversity and efficient breeding.
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Affiliation(s)
- Alexandra S. Abdelmanova
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Arsen V. Dotsev
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Michael N. Romanov
- School of Biosciences, University of Kent, Canterbury, Kent CT2 7NJ, UK;
- K.I. Skryabin Moscow State Academy of Veterinary Medicine and Biotechnology, 23 Akademika Skryabina St., 109472 Moscow, Russia
- Correspondence: (M.N.R.); (N.A.Z.); Tel.: +798-57154351 (M.N.R.); +749-67651163 (N.A.Z.)
| | - Olga I. Stanishevskaya
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (O.I.S.); (E.S.F.)
| | - Elena A. Gladyr
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Andrey N. Rodionov
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Anastasia N. Vetokh
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Natalia A. Volkova
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Elena S. Fedorova
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (O.I.S.); (E.S.F.)
| | - Igor V. Gusev
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
| | - Darren K. Griffin
- School of Biosciences, University of Kent, Canterbury, Kent CT2 7NJ, UK;
| | - Gottfried Brem
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine, 1210 Vienna, Austria;
| | - Natalia A. Zinovieva
- L.K. Ernst Federal Research Center for Animal Husbandry, 142132 Podolsk, Russia; (A.S.A.); (A.V.D.); (E.A.G.); (A.N.R.); (A.N.V.); (N.A.V.); (I.V.G.)
- Correspondence: (M.N.R.); (N.A.Z.); Tel.: +798-57154351 (M.N.R.); +749-67651163 (N.A.Z.)
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Zhao X, Nie C, Zhang J, Li X, Zhu T, Guan Z, Chen Y, Wang L, Lv XZ, Yang W, Jia Y, Ning Z, Li H, Qu C, Wang H, Qu L. Identification of candidate genomic regions for chicken egg number traits based on genome-wide association study. BMC Genomics 2021; 22:610. [PMID: 34376144 PMCID: PMC8356427 DOI: 10.1186/s12864-021-07755-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 05/25/2021] [Indexed: 02/07/2023] Open
Abstract
Background Since the domestication of chicken, various breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic differences of egg number between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model. Results We obtained 148 single nucleotide polymorphisms (SNPs) associated with egg number traits (57 significantly, 91 suggestively). Among them, 4 SNPs overlapped with previously reported quantitative trait loci (QTL), including 2 for egg production and 2 for reproductive traits. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2 (neural EGFL like 2), KITLG (KIT ligand), GHRHR (Growth hormone releasing hormone receptor), NCOA1 (Nuclear receptor coactivator 1), ITPR1 (inositol 1, 4, 5-trisphosphate receptor type 1), GAMT (guanidinoacetate N-methyltransferase), and CAMK4 (calcium/calmodulin-dependent protein kinase IV) deserve our attention and further study since they have been reported to be closely related to egg production, egg number and reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61–48.84 Mb on GGA5. In this region, we have repeatedly identified four genes, in which YY1 (YY1 transcription factor) and WDR25 (WD repeat domain 25) have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg number traits. Conclusion Our study utilized the genomic information from various chicken breeds or populations differed in the average annual egg number to understand the molecular genetic mechanisms involved in egg number traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with egg number, which could help us in developing the egg production trait in chickens. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07755-3.
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Affiliation(s)
- Xiurong Zhao
- 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
| | - Changsheng Nie
- 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
| | - Jinxin Zhang
- 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
| | - Xinghua Li
- 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
| | - Tao Zhu
- 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
| | - Zi Guan
- 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
| | - Yu Chen
- Beijing Municipal General Station of Animal Science, Beijing, 100107, China
| | - Liang Wang
- Beijing Municipal General Station of Animal Science, Beijing, 100107, China
| | - Xue Ze Lv
- Beijing Municipal General Station of Animal Science, Beijing, 100107, China
| | - Weifang Yang
- Beijing Municipal General Station of Animal Science, Beijing, 100107, China
| | - Yaxiong Jia
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Zhonghua Ning
- 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
| | - Haiying Li
- College of Animal Science, Xinjiang Agricultural University, Urumqi, 830000, China
| | - Changqing Qu
- Engineering Technology Research Center of Anti-aging Chinese Herbal Medicine of Anhui Province, Fuyang Normal University, Fuyang, 236037, Anhui, China
| | - Huie Wang
- College of Animal Science, Tarim University, Alar, 843300, Xingjiang, China.,Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & amp; Construction Corps, Alar, 843300, Xingjiang, 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.
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7
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Tarsani E, Kranis A, Maniatis G, Hager-Theodorides AL, Kominakis A. Detection of loci exhibiting pleiotropic effects on body weight and egg number in female broilers. Sci Rep 2021; 11:7441. [PMID: 33811218 PMCID: PMC8018976 DOI: 10.1038/s41598-021-86817-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 03/16/2021] [Indexed: 12/14/2022] Open
Abstract
The objective of the present study was to discover the genetic variants, functional candidate genes, biological processes and molecular functions underlying the negative genetic correlation observed between body weight (BW) and egg number (EN) traits in female broilers. To this end, first a bivariate genome-wide association and second stepwise conditional-joint analyses were performed using 2586 female broilers and 240 k autosomal SNPs. The aforementioned analyses resulted in a total number of 49 independent cross-phenotype (CP) significant SNPs with 35 independent markers showing antagonistic action i.e., positive effects on one trait and negative effects on the other trait. A number of 33 independent CP SNPs were located within 26 and 14 protein coding and long non-coding RNA genes, respectively. Furthermore, 26 independent markers were situated within 44 reported QTLs, most of them related to growth traits. Investigation of the functional role of protein coding genes via pathway and gene ontology analyses highlighted four candidates (CPEB3, ACVR1, MAST2 and CACNA1H) as most plausible pleiotropic genes for the traits under study. Three candidates (CPEB3, MAST2 and CACNA1H) were associated with antagonistic pleiotropy, while ACVR1 with synergistic pleiotropic action. Current results provide a novel insight into the biological mechanism of the genetic trade-off between growth and reproduction, in broilers.
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Affiliation(s)
- Eirini Tarsani
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece.
| | - Andreas Kranis
- Aviagen, Newbridge, EH28 8SZ, Midlothian, UK
- The Roslin Institute, University of Edinburgh, Midlothian, EH25 9RG, UK
| | | | - Ariadne L Hager-Theodorides
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
| | - Antonios Kominakis
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
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