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Cai K, Liu R, Wei L, Wang X, Cui H, Luo N, Wen J, Chang Y, Zhao G. Genome-wide association analysis identify candidate genes for feed efficiency and growth traits in Wenchang chickens. BMC Genomics 2024; 25:645. [PMID: 38943081 PMCID: PMC11212279 DOI: 10.1186/s12864-024-10559-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: 02/05/2024] [Accepted: 06/24/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND Wenchang chickens are one of the most popular local chicken breeds in the Chinese chicken industry. However, the low feed efficiency is the main shortcoming of this breed. Therefore, there is a need to find a more precise breeding method to improve the feed efficiency of Wenchang chickens. In this study, we explored important candidate genes and variants for feed efficiency and growth traits through genome-wide association study (GWAS) analysis. RESULTS Estimates of genomic heritability for growth and feed efficiency traits, including residual feed intake (RFI) of 0.05, average daily food intake (ADFI) of 0.21, average daily weight gain (ADG) of 0.24, body weight (BW) at 87, 95, 104, 113 days of age (BW87, BW95, BW104 and BW113) ranged from 0.30 to 0.44. Important candidate genes related to feed efficiency and growth traits were identified, such as PLCE1, LAP3, MED28, QDPR, LDB2 and SEL1L3 genes. CONCLUSION The results identified important candidate genes for feed efficiency and growth traits in Wenchang chickens and provide a theoretical basis for the development of new molecular breeding technology.
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Affiliation(s)
- Keqi Cai
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, P.R. China
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, P.R. China
| | - Ranran Liu
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, P.R. China
| | - Limin Wei
- The Sanya Research Institute, Hainan Academy of Agricultural Sciences, Sanya, 572025, P.R. China
| | - Xiuping Wang
- Hainan (Tan Niu) Wenchang Chicken Co., LTD, Haikou, 570100, P.R. China
| | - Huanxian Cui
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, P.R. China
| | - Na Luo
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, P.R. China
| | - Jie Wen
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, P.R. China
| | - Yuxiao Chang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, P.R. China.
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, P.R. China.
- The Sanya Research Institute, Hainan Academy of Agricultural Sciences, Sanya, 572025, P.R. China.
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [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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Disentangling clustering configuration intricacies for divergently selected chicken breeds. Sci Rep 2023; 13:3319. [PMID: 36849504 PMCID: PMC9971033 DOI: 10.1038/s41598-023-28651-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/23/2023] [Indexed: 03/01/2023] Open
Abstract
Divergently selected chicken breeds are of great interest not only from an economic point of view, but also in terms of sustaining diversity of the global poultry gene pool. In this regard, it is essential to evaluate the classification (clustering) of varied chicken breeds using methods and models based on phenotypic and genotypic breed differences. It is also important to implement new mathematical indicators and approaches. Accordingly, we set the objectives to test and improve clustering algorithms and models to discriminate between various chicken breeds. A representative portion of the global chicken gene pool including 39 different breeds was examined in terms of an integral performance index, i.e., specific egg mass yield relative to body weight of females. The generated dataset was evaluated within the traditional, phenotypic and genotypic classification/clustering models using the k-means method, inflection points clustering, and admixture analysis. The latter embraced SNP genotype datasets including a specific one focused on the performance-associated NCAPG-LCORL locus. The k-means and inflection points analyses showed certain discrepancies between the tested models/submodels and flaws in the produced cluster configurations. On the other hand, 11 core breeds were identified that were shared between the examined models and demonstrated more adequate clustering and admixture patterns. These findings will lay the foundation for future research to improve methods for clustering as well as genome- and phenome-wide association/mediation analyses.
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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: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [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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Zhou J, Jiang Z, Fu L, Qu F, Dai M, Xie N, Zhang S, Wang F. Contribution of labor related gene subtype classification on heterogeneity of polycystic ovary syndrome. PLoS One 2023; 18:e0282292. [PMID: 36857354 PMCID: PMC9977056 DOI: 10.1371/journal.pone.0282292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 02/11/2023] [Indexed: 03/02/2023] Open
Abstract
OBJECTIVE As one of the most common endocrine disorders in women of reproductive age, polycystic ovary syndrome (PCOS) is highly heterogeneous with varied clinical features and diverse gestational complications among individuals. The patients with PCOS have 2-fold higher risk of preterm labor which is associated with substantial infant morbidity and mortality and great socioeconomic cost. The study was designated to identify molecular subtypes and the related hub genes to facilitate the susceptibility assessment of preterm labor in women with PCOS. METHODS Four mRNA datasets (GSE84958, GSE5090, GSE43264 and GSE98421) were obtained from Gene Expression Omnibus database. Twenty-eight candidate genes related to preterm labor or labor were yielded from the researches and our unpublished data. Then, we utilized unsupervised clustering to identify molecular subtypes in PCOS based on the expression of above candidate genes. Key modules were generated with weighted gene co-expression network analysis R package, and their hub genes were generated with CytoHubba. The probable biological function and mechanism were explored through Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis. In addition, STRING and Cytoscape software were used to identify the protein-protein interaction (PPI) network, and the molecular complex detection (MCODE) was used to identify the hub genes. Then the overlapping hub genes were predicted. RESULTS Two molecular subtypes were found in women with PCOS based on the expression similarity of preterm labor or labor-related genes, in which two modules were highlighted. The key modules and PPI network have five overlapping five hub genes, two of which, GTF2F2 and MYO6 gene, were further confirmed by the comparison between clustering subgroups according to the expression of hub genes. CONCLUSIONS Distinct PCOS molecular subtypes were identified with preterm labor or labor-related genes, which might uncover the potential mechanism underlying heterogeneity of clinical pregnancy complications in women with PCOS.
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Affiliation(s)
- Jue Zhou
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, China
| | - Zhou Jiang
- Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Leyi Fu
- Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Fan Qu
- Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Minchen Dai
- Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Ningning Xie
- Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Songying Zhang
- Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- * E-mail: (FW); (SZ)
| | - Fangfang Wang
- Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- * E-mail: (FW); (SZ)
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Yawitz TA, Barts N, Kohl KD. Comparative digestive morphology and physiology of five species of Peromyscus under controlled environment and diet. Comp Biochem Physiol A Mol Integr Physiol 2022; 271:111265. [PMID: 35760269 DOI: 10.1016/j.cbpa.2022.111265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/22/2022] [Accepted: 06/22/2022] [Indexed: 10/17/2022]
Abstract
Digestive morphology and physiology differ across animal species, with many comparative studies uncovering relationships between animal ecology or diet, and the morphology and physiology of the gastrointestinal tract. However, many of these studies compare wild-caught animals feeding on uncontrolled diets and compare broadly related taxa. Thus, few studies have disentangled the phenotypic consequences of genetics from those potentially caused by the environment, especially across closely related species that occupy similar ecological niches. Here, we examined differences in digestive morphology and physiology of five closely related species of Peromyscus mice that were captive bred under identical environmental conditions and identical diets for multiple generations. Using phylogenetic generalized least squares (PGLS) of species means to control for body size, we identified a phylogenetic signal in the mass of the foregut and length of the small intestine across species. As proportions of total gut mass, we identified phylogenetic signals in relative foregut and small intestine masses, indicating that the sizes of these structures are more similar among closely related species. Finally, we detected differences in activities of the protease aminopeptidase-N enzyme across species. Overall, we demonstrate fine-scale differences in digestive morphology and physiology among closely related species. Our results suggest that Peromyscus could provide a system for future studies to explore the interplay between natural history, morphology, and physiology (e.g. ecomorphology and ecophysiology), and to investigate the genetic architecture that underlies gut anatomy.
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Affiliation(s)
- Tate A Yawitz
- Department of Biological Sciences, University of Pittsburgh, 4249 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Nick Barts
- Department of Biological Sciences, University of Pittsburgh, 4249 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Kevin D Kohl
- Department of Biological Sciences, University of Pittsburgh, 4249 Fifth Avenue, Pittsburgh, PA 15260, USA.
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The Impact of Probiotic Bacillus subtilis on Injurious Behavior in Laying Hens. Animals (Basel) 2022; 12:ani12070870. [PMID: 35405859 PMCID: PMC8997090 DOI: 10.3390/ani12070870] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/27/2022] [Accepted: 03/27/2022] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Injurious behavior prevention is a critical issue in the poultry industry due to increasing social stress, leading to negative effects on bird production and survivability, consequently enhancing gut microbiota dysbiosis and neuroinflammation via the microbiota–gut–brain axis. Probiotics have been used as potential therapeutic psychobiotics to treat or improve neuropsychiatric disorders or symptoms by boosting cognitive and behavioral processes and reducing stress reactions in humans and various experimental animals. The current data will first report that probiotic Bacillus subtilis reduces stress-induced injurious behavior in laying hens via regulating microbiota–gut–brain function with the potential to be an alternative to beak trimming during poultry egg production. Abstract Intestinal microbiota functions such as an endocrine organ to regulate host physiological homeostasis and behavioral exhibition in stress responses via regulating the gut–brain axis in humans and other mammals. In humans, stress-induced dysbiosis of the gut microbiota leads to intestinal permeability, subsequently affecting the clinical course of neuropsychiatric disorders, increasing the frequency of aggression and related violent behaviors. Probiotics, as direct-fed microorganism, have been used as dietary supplements or functional foods to target gut microbiota (microbiome) for the prevention or therapeutic treatment of mental diseases including social stress-induced psychiatric disorders such as depression, anxiety, impulsivity, and schizophrenia. Similar function of the probiotics may present in laying hens due to the intestinal microbiota having a similar function between avian and mammals. In laying hens, some management practices such as hens reared in conventional cages or at a high stocking density may cause stress, leading to injurious behaviors such as aggressive pecking, severe feather pecking, and cannibalism, which is a critical issue facing the poultry industry due to negative effects on hen health and welfare with devastating economic consequences. We discuss the current development of using probiotic Bacillus subtilis to prevent or reduce injurious behavior in laying hens.
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Li Y, Liu X, Bai X, Wang Y, Leng L, Zhang H, Li Y, Cao Z, Luan P, Xiao F, Gao H, Sun Y, Wang N, Li H, Wang S. Genetic parameters estimation and genome‐wide association studies for internal organ traits in an F
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chicken population. J Anim Breed Genet 2022; 139:434-446. [DOI: 10.1111/jbg.12674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/24/2022] [Accepted: 02/12/2022] [Indexed: 11/29/2022]
Affiliation(s)
- Yudong Li
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Xin Liu
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Xue Bai
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Yuxiang Wang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Li Leng
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Hui Zhang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Yumao Li
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Zhiping Cao
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Peng Luan
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Fan Xiao
- Fujian Sunnzer Biotechnology Development Co., Ltd Guangze P.R. China
| | - Haihe Gao
- Fujian Sunnzer Biotechnology Development Co., Ltd Guangze P.R. China
| | - Yuhang Sun
- Fujian Sunnzer Biotechnology Development Co., Ltd Guangze P.R. China
| | - Ning Wang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Shouzhi Wang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
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Liu H, Wang L, Guo Z, Xu Q, Fan W, Xu Y, Hu J, Zhang Y, Tang J, Xie M, Zhou Z, Hou S. Genome-wide association and selective sweep analyses reveal genetic loci for FCR of egg production traits in ducks. Genet Sel Evol 2021; 53:98. [PMID: 34930109 PMCID: PMC8690979 DOI: 10.1186/s12711-021-00684-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 11/10/2021] [Indexed: 12/30/2022] Open
Abstract
Background As a major economic trait in poultry, egg production efficiency attracts widespread interest in breeding and production. However, limited information is available about the underlying genetic architecture of egg production traits in ducks. In this paper, we analyzed six egg production-related traits in 352 F2 ducks derived from reciprocal crosses between mallard and Pekin ducks. Results Feed conversation ratio (FCR) was positively correlated with feed intake but negatively correlated with egg-related traits, including egg weight and egg production, both phenotypically and genetically. Estimates of pedigree-based heritability were higher than 0.2 for all traits investigated, except hip-width. Based on whole-genome sequencing data, we conducted genome-wide association studies to identify genomic regions associated with these traits. In total, 11 genomic regions were associated with FCR. No genomic regions were identified as significantly associated with hip-width, total feed intake, average daily feed intake, and total egg production. Analysis of selective sweeps between mallard and Pekin ducks confirmed three of these genomic regions on chromosomes 13, 3 and 6. Within these three regions, variants in candidate genes that were in linkage disequilibrium with the GWAS leader single nucleotide polymorphisms (SNPs) (Chr13:2,196,728, P = 7.05 × 10–14; Chr3:76,991,524, P = 1.06 × 10–12; Chr6:20,356,803, P = 1.14 × 10–10) were detected. Thus, we identified 31 potential candidate genes associated with FCR, among which the strongest candidates are those that are highly expressed in tissues involved in reproduction and nervous system functions of ducks: CNTN4, CRBR, GPR63, KLHL32, FHL5, TRNT1, MANEA, NDUFAF4, and SCD. Conclusions For the first time, we report the identification of genomic regions that are associated with FCR in ducks and our results illustrate the genomic changes that occurred during their domestication and are involved in egg production efficiency. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00684-5.
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Affiliation(s)
- Hehe Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.,Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 613000, China
| | - Lei Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 613000, China
| | - Zhanbao Guo
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qian Xu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 613000, China
| | - Wenlei Fan
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yaxi Xu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jian Hu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yunsheng Zhang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jing Tang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Ming Xie
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Zhengkui Zhou
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Shuisheng Hou
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
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10
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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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11
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Yang Z, Zou L, Sun T, Xu W, Zeng L, Jia Y, Jiang J, Deng J, Yang X. Genome-Wide Association Study Using Whole-Genome Sequencing Identifies a Genomic Region on Chromosome 6 Associated With Comb Traits in Nandan-Yao Chicken. Front Genet 2021; 12:682501. [PMID: 34408769 PMCID: PMC8365347 DOI: 10.3389/fgene.2021.682501] [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: 03/18/2021] [Accepted: 07/05/2021] [Indexed: 11/13/2022] Open
Abstract
Comb traits have potential economic value in the breeding of indigenous chickens in China. Identifying and understanding relevant molecular markers for comb traits can be beneficial for genetic improvement. The purpose of this study was to utilize genome-wide association studies (GWAS) to detect promising loci and candidate genes related to comb traits, namely, comb thickness (CT), comb weight (CW), comb height, comb length (CL), and comb area. Genome-wide single-nucleotide polymorphisms (SNPs) and small insertions/deletions (INDELs) in 300 Nandan-Yao chickens were detected using whole-genome sequencing. In total, we identified 134 SNPs and 25 INDELs that were strongly associated with the five comb traits. A remarkable region spanning from 29.6 to 31.4 Mb on chromosome 6 was found to be significantly associated with comb traits in both SNP- and INDEL-based GWAS. In this region, two lead SNPs (6:30,354,876 for CW and CT and 6:30,264,318 for CL) and one lead INDEL (a deletion from 30,376,404 to 30,376,405 bp for CL and CT) were identified. Additionally, two genes were identified as potential candidates for comb development. The nearby gene fibroblast growth factor receptor 2 (FGFR2)-associated with epithelial cell migration and proliferation-and the gene cytochrome b5 reductase 2 (CYB5R2)-identified on chromosome 5 from INDEL-based GWAS-are significantly correlated with collagen maturation. The findings of this study could provide promising genes and biomarkers to accelerate genetic improvement of comb development based on molecular marker-assisted breeding in Nandan-Yao chickens.
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Affiliation(s)
- Zhuliang Yang
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Leqin Zou
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Tiantian Sun
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Wenwen Xu
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Linghu Zeng
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Yinhai Jia
- Guangxi Institute of Animal Science, Nanning, China
| | - Jianping Jiang
- Guangxi Botanical Garden of Medicinal Plants, Nanning, China
| | - Jixian Deng
- Guangxi Institute of Animal Science, Nanning, China
| | - Xiurong Yang
- College of Animal Science and Technology, Guangxi University, Nanning, China
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12
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Genome-Wide Association Study Identifies Candidate Genes Associated with Feet and Leg Conformation Traits in Chinese Holstein Cattle. Animals (Basel) 2021; 11:ani11082259. [PMID: 34438715 PMCID: PMC8388412 DOI: 10.3390/ani11082259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 07/24/2021] [Accepted: 07/28/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Feet and leg problems are among the major reasons for dairy cows leaving the herd, as well as having direct association with production and reproduction efficiency, health (e.g., claw disorders and lameness) and welfare. Hence, understanding the genetic architecture underlying feet and conformation traits in dairy cattle offers new opportunities toward the genetic improvement and long-term selection. Through a genome-wide association study on Chinese Holstein cattle, we identified several candidate genes associated with feet and leg conformation traits. These results could provide useful information about the molecular breeding basis of feet and leg traits, thus improving the longevity and productivity of dairy cattle. Abstract Feet and leg conformation traits are considered one of the most important economical traits in dairy cattle and have a great impact on the profitability of milk production. Therefore, identifying the single nucleotide polymorphisms (SNPs), genes and pathways analysis associated with these traits might contribute to the genomic selection and long-term plan selection for dairy cattle. We conducted genome-wide association studies (GWASs) using the fixed and random model circulating probability unification (FarmCPU) method to identify SNPs associated with bone quality, heel depth, rear leg side view and rear leg rear view of Chinese Holstein cows. Phenotypic measurements were collected from 1000 individuals of Chinese Holstein cattle and the GeneSeek Genomic Profiler Bovine 100 K SNP chip was utilized for individual genotyping. After quality control, 984 individual cows and 84,906 SNPs remained for GWAS work; as a result, we identified 20 significant SNPs after Bonferroni correction. Several candidate genes were identified within distances of 200 kb upstream or downstream to the significant SNPs, including ADIPOR2, INPP4A, DNMT3A, ALDH1A2, PCDH7, XKR4 and CADPS. Further bioinformatics analyses showed 34 gene ontology terms and two signaling pathways were significantly enriched (p ≤ 0.05). Many terms and pathways are related to biological quality, metabolism and development processes; these identified SNPs and genes could provide useful information about the genetic architecture of feet and leg traits, thus improving the longevity and productivity of Chinese Holstein dairy cattle.
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Mapping of Quantitative Trait Loci Controlling Egg-Quality and -Production Traits in Japanese Quail ( Coturnix japonica) Using Restriction-Site Associated DNA Sequencing. Genes (Basel) 2021; 12:genes12050735. [PMID: 34068239 PMCID: PMC8153160 DOI: 10.3390/genes12050735] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 05/07/2021] [Accepted: 05/08/2021] [Indexed: 02/07/2023] Open
Abstract
This research was conducted to identify quantitative trait loci (QTL) associated with egg-related traits by constructing a genetic linkage map based on single nucleotide polymorphism (SNP) markers using restriction-site associated DNA sequencing (RAD-seq) in Japanese quail. A total of 138 F2 females were produced by full-sib mating of F1 birds derived from an intercross between a male of the large-sized strain with three females of the normal-sized strain. Eggs were investigated at two different stages: the beginning stage of egg-laying and at 12 weeks of age (second stage). Five eggs were analyzed for egg weight, lengths of the long and short axes, egg shell strength and weight, yolk weight and diameter, albumen weight, egg equator thickness, and yolk color (L*, a*, and b* values) at each stage. Moreover, the age at first egg, the cumulative number of eggs laid, and egg production rate were recorded. RAD-seq developed 118 SNP markers and mapped them to 13 linkage groups using the Map Manager QTX b20 software. Markers were spanned on 776.1 cM with an average spacing of 7.4 cM. Nine QTL were identified on chromosomes 2, 4, 6, 10, 12, and Z using the simple interval mapping method in the R/qtl package. The QTL detected affected 10 egg traits of egg weight, lengths of the long and short axes of egg, egg shell strength, yolk diameter and weight, albumen weight, and egg shell weight at the beginning stage, yellowness of the yolk color at the second stage, and age at first egg. This is the first report to perform a quail QTL analysis of egg-related traits using RAD-seq. These results highlight the effectiveness of RAD-seq associated with targeted QTL and the application of marker-assisted selection in the poultry industry, particularly in the Japanese quail.
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Wang YM, Khederzadeh S, Li SR, Otecko NO, Irwin DM, Thakur M, Ren XD, Wang MS, Wu DD, Zhang YP. Integrating Genomic and Transcriptomic Data to Reveal Genetic Mechanisms Underlying Piao Chicken Rumpless Trait. GENOMICS PROTEOMICS & BIOINFORMATICS 2021; 19:787-799. [PMID: 33631431 PMCID: PMC9170765 DOI: 10.1016/j.gpb.2020.06.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 04/14/2020] [Accepted: 06/10/2020] [Indexed: 11/19/2022]
Abstract
Piao chicken, a rare Chinese native poultry breed, lacks primary tail structures, such as pygostyle, caudal vertebra, uropygial gland, and tail feathers. So far, the molecular mechanisms underlying tail absence in this breed remain unclear. In this study, we comprehensively employed comparative transcriptomic and genomic analyses to unravel potential genetic underpinnings of rumplessness in Piao chicken. Our results reveal many biological factors involved in tail development and several genomic regions under strong positive selection in this breed. These regions contain candidate genes associated with rumplessness, including Irx4, Il18, Hspb2, and Cryab. Retrieval of quantitative trait loci (QTL) and gene functions implies that rumplessness might be consciously or unconsciously selected along with the high-yield traits in Piao chicken. We hypothesize that strong selection pressures on regulatory elements might lead to changes in gene activity in mesenchymal stem cells of the tail bud. The ectopic activity could eventually result in tail truncation by impeding differentiation and proliferation of the stem cells. Our study provides fundamental insights into early initiation and genetic basis of the rumpless phenotype in Piao chicken.
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Affiliation(s)
- Yun-Mei Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China; Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, Moscow 143026, Russia
| | - Saber Khederzadeh
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - Shi-Rong Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - Newton Otieno Otecko
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - David M Irwin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto M5S 1A8, Canada
| | - Mukesh Thakur
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Zoological Survey of India, Kolkata 700053, India
| | - Xiao-Die Ren
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China.
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of the Chinese Academy of Sciences, Kunming 650223, China.
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