1
|
Miao X, Wu T, Pan H, Zhang Y, Liu J, Fan Y, Du L, Gong Y, Li L, Huang T, Ning Z. Integrative analysis of the ovarian metabolome and transcriptome of the Yaoshan chicken and its improved hybrids. Front Genet 2024; 15:1416283. [PMID: 39040995 PMCID: PMC11260793 DOI: 10.3389/fgene.2024.1416283] [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: 04/12/2024] [Accepted: 06/07/2024] [Indexed: 07/24/2024] Open
Abstract
Introduction: Laying performance is a key factor affecting production efficiency in poultry, but its molecular mechanism is still indistinct. In this study, Yaoshan chickens, a local breed in Guizhou, China, and merchant chickens (GYR) with higher egg yield after the three-line cross improvement hybridization of Yaoshan chickens were used as animal samples. Methods: To explore the regulatory mechanism of the diversities in laying performance, RNA-seq and ultra-performance liquid chromatographytandem mass spectrometry (UPLC-MS/MS) were used to describe the transcriptional and metabolic profiles of the ovaries of Yaoshan and GYR chickens. Results: At the transcriptional level, 288 differentially expressed genes were upregulated in Yaoshan chickens and 353 differentially expressed genes were upregulated in GYR chickens. In addition, GSEA showed that ECM-receptor interactions and the TGF-β signaling pathway were restrained, resulting in increased egg production in GYR chickens. Furthermore, the upregulation of thiamine and carnitine was identified by metabolomic analysis to facilitate the laying performance of hens. Finally, comprehensive analyses of the transcriptome and metabolome found that thiamine and carnitine were negatively correlated with ECM-receptor interactions and the TGF-β signaling pathway, which jointly regulate the laying performance of Yaoshan chickens and GYR chickens. Discussion: Taken together, our research delineates differences in the transcriptional and metabolic profiles of the ovaries of Yaoshan and GYR chickens during the peak egg production period and provides new hypotheses and clues for further research on poultry egg production performance and the improvement of economic benefits.
Collapse
Affiliation(s)
- Xiaomeng Miao
- Institute of Animal Husbandry and Veterinary Medicine, Guizhou Academy of Agricultural Sciences, Guiyang, China
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Tian Wu
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Hongyuan Pan
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Yalan Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jia Liu
- Guizhou Province Livestock and Poultry Genetic Resources Management Station, Guiyang, China
| | - Ying Fan
- Guizhou Province Livestock and Poultry Genetic Resources Management Station, Guiyang, China
| | - Lin Du
- Guizhou Province Livestock and Poultry Genetic Resources Management Station, Guiyang, China
| | - Yu Gong
- Guizhou Province Livestock and Poultry Genetic Resources Management Station, Guiyang, China
| | - Liang Li
- Institute of Animal Husbandry and Veterinary Medicine, Guizhou Academy of Agricultural Sciences, Guiyang, China
| | - Tengda Huang
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Zhonghua Ning
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| |
Collapse
|
2
|
Luo W, Huang X, Li J, Gu L. Investigating the genetic determination of duration-of-fertility trait in breeding hens. Sci Rep 2024; 14:14819. [PMID: 38937575 PMCID: PMC11211418 DOI: 10.1038/s41598-024-65675-0] [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: 02/19/2024] [Accepted: 06/24/2024] [Indexed: 06/29/2024] Open
Abstract
The duration-of-fertility (DF), which was defined as the number of days when breeding hens lay fertile eggs following copulation or artificial insemination (AI), is an important economic trait in chick production when it has strong effects on fertile egg output and production costs. Little is known about the underlying genes and molecular markers related to DF trait to date. Here, we measured the DF of 701 Chinese Jinghong hens and 408 Jingfen hens. The DF showed high individual variability and potential for genetic improvement. Then, 192 Jinghong breeding hens were provided for a genome-wide association study, 27 SNPs respectively located in three genomic linkage regions (GGA1:41Kb; GGA3:39Kb and GGA8:39Kb) were suggested to be significantly associated with DF. Particularly, 6 of these 27 SNPs were further verified to be associated with DF in the 701 Jinghong and 408 Jingfen hens using PCR-RFLP genotyping method. These 27 SNPs were also mapped to 7 genes according to their genomic position. Furtherly, 5 of these 7 genes were tested using qPCR. Results show that the CYP2D6, WBP2NL, ESR1 and TGFBR3 mRNA expression levels of hens with long DF were significantly higher than the hens with short DF (P < 0.05). Overall, findings in our research provide new insight into the genetic basis of duration-of-fertility in breeding hens while providing new clues for further functional validation on the DF-related genetic regulation mechanism and improvement of DF through chicken breeding.
Collapse
Affiliation(s)
- Wei Luo
- Institute of Biotechnology of Guilin Medical University, Guilin, Guangxi, China
| | - Xishi Huang
- Institute of Biotechnology of Guilin Medical University, Guilin, Guangxi, China
| | - Jingxuan Li
- Institute of Biotechnology of Guilin Medical University, Guilin, Guangxi, China
| | - Lantao Gu
- Institute of Biotechnology of Guilin Medical University, Guilin, Guangxi, China.
| |
Collapse
|
3
|
Sun Y, Li Y, Jiang X, Wu Q, Lin R, Chen H, Zhang M, Zeng T, Tian Y, Xu E, Zhang Y, Lu L. Genome-wide association study identified candidate genes for egg production traits in the Longyan Shan-ma duck. Poult Sci 2024; 103:104032. [PMID: 39003796 DOI: 10.1016/j.psj.2024.104032] [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: 04/23/2024] [Revised: 06/19/2024] [Accepted: 06/22/2024] [Indexed: 07/16/2024] Open
Abstract
Egg production is an important economic trait in layer ducks and understanding the genetics basis is important for their breeding. In this study, a genome-wide association study (GWAS) for egg production traits in 303 female Longyan Shan-ma ducks was performed based on a genotyping-by-sequencing strategy. Sixty-two single nucleotide polymorphisms (SNPs) associated with egg weight traits were identified (P < 9.48 × 10-5), including 8 SNPs at 5% linkage disequilibrium (LD)-based Bonferroni-corrected genome-wide significance level (P < 4.74 × 10-6). One hundred and nineteen SNPs were associated with egg number traits (P < 9.48 × 10-5), including 13 SNPs with 5% LD-based Bonferroni-corrected genome-wide significance (P < 4.74 × 10-6). These SNPs annotated 146 target genes which contained known candidate genes for egg production traits, such as prolactin and prolactin releasing hormone receptor. This study identified that these associated genes were significantly enriched in egg production-related pathways (P < 0.05), such as the oxytocin signaling, MAPK signaling, and calcium signaling pathways. It was notable that 18 genes were differentially expressed in ovarian tissues between higher and lower egg production in Shan-ma ducks. The identified potential candidate genes and pathways provide insight into the genetic basis underlying the egg production trait of layer ducks.
Collapse
Affiliation(s)
- Yanfa Sun
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P.R. China
| | - Yan Li
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P.R. China
| | - Xiaobing Jiang
- Fujian Provincial Animal Husbandry Headquarters, Fuzhou, Fujian 350003, P.R. China
| | - Qiong Wu
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P.R. China
| | - Rulong Lin
- Longyan Shan-ma Duck Original Breeding Farm, Agricultural Bureau of Xinluo District, Longyan, 364031, P.R. China
| | - Hongping Chen
- Longyan Shan-ma Duck Original Breeding Farm, Agricultural Bureau of Xinluo District, Longyan, 364031, P.R. China
| | - Min Zhang
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P.R. China
| | - Tao Zeng
- Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, P.R. China
| | - Yong Tian
- Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, P.R. China
| | - Enrong Xu
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P.R. China
| | - Yeqiong Zhang
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P.R. China
| | - Lizhi Lu
- Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, P.R. China..
| |
Collapse
|
4
|
Zhou J, Yu JZ, Zhu MY, Yang FX, Hao JP, He Y, Zhu XL, Hou ZC, Zhu F. Genome-Wide Association Analysis and Genetic Parameters for Egg Production Traits in Peking Ducks. Animals (Basel) 2024; 14:1891. [PMID: 38998005 PMCID: PMC11240742 DOI: 10.3390/ani14131891] [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: 05/07/2024] [Revised: 06/08/2024] [Accepted: 06/12/2024] [Indexed: 07/14/2024] Open
Abstract
Egg production traits are crucial in the poultry industry, including age at first egg (AFE), egg number (EN) at different stages, and laying rate (LR). Ducks exhibit higher egg production capacity than other poultry species, but the genetic mechanisms are still poorly understood. In this study, we collected egg-laying data of 618 Peking ducks from 22 to 66 weeks of age and genotyped them by whole-genome resequencing. Genetic parameters were calculated based on SNPs, and a genome-wide association study (GWAS) was performed for these traits. The SNP-based heritability of egg production traits ranged from 0.09 to 0.54. The GWAS identified nine significant SNP loci associated with AFE and egg number from 22 to 66 weeks. These loci showed that the corresponding alleles were positively correlated with a decrease in the traits. Moreover, three potential candidate genes (ENSAPLG00020011445, ENSAPLG00020012564, TMEM260) were identified. Functional enrichment analyses suggest that specific immune responses may have a critical impact on egg production capacity by influencing ovarian function and oocyte maturation processes. In conclusion, this study deepens the understanding of egg-laying genetics in Peking duck and provides a sound theoretical basis for future genetic improvement and genomic selection strategies in poultry.
Collapse
Affiliation(s)
- Jun Zhou
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Jiang-Zhou Yu
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Mei-Yi Zhu
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Fang-Xi Yang
- Beijing Nankou Duck Breeding Technology Co., Ltd., Beijing 102202, China
| | - Jin-Ping Hao
- Beijing Nankou Duck Breeding Technology Co., Ltd., Beijing 102202, China
| | - Yong He
- Cherry Valley Breeding Technology Co., Ltd., Beijing 100088, China
| | - Xiao-Liang Zhu
- Cherry Valley Breeding Technology Co., Ltd., Beijing 100088, China
| | - Zhuo-Cheng Hou
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Feng Zhu
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| |
Collapse
|
5
|
Zhang L, Li H, Zhao X, Wu Y, Li J, Yao Y, Yao Y, Wang L. Whole genome resequencing reveals the adaptability of native chickens to drought, tropical and frigid environments in Xinjiang. Poult Sci 2024; 103:103947. [PMID: 38986358 DOI: 10.1016/j.psj.2024.103947] [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: 02/27/2024] [Revised: 05/17/2024] [Accepted: 06/03/2024] [Indexed: 07/12/2024] Open
Abstract
Chickens exhibit extensive genetic diversity and are distributed worldwide. Different chicken breeds have evolved to thrive in diverse environmental conditions. However, research on the genetic mechanisms underlying chicken adaptation to extreme environments, such as tropical, frigid and drought-prone regions, remains limited. In this study, we conducted whole-genome sequencing of 240 individuals from six native chicken breeds in Xinjiang, China, as well as 4 publicly available chicken breeds inhabiting regions with varying annual precipitations, temperatures, and altitudes. Our analysis revealed several genetic variants among the examined breeds. Furthermore, we investigated the genetic diversity and population structure of breeds residing in extreme drought and temperature environments by comparing them. Notably, native chicken breeds exhibited different genetic diversity and population structures. Moreover, we identified candidate genes associated with chicken adaptability to the environment, such as CORO2A, CTNNA3, AGMO, GRID2, BBOX1, COL3A1, INSR, SOX5, MAP2 and PLPPR1. Additionally, pathways such as lysosome, cysteine and methionine metabolism, glycosaminoglycan degradation, and Wnt signaling may be play crucial roles in regulating chicken adaptation to drought environments. Overall, these findings contribute to our understanding of the genetic mechanisms governing chicken adaptation to extreme environments, and also offer insights for enhancing the resilience of chicken breeds to different climatic conditions.
Collapse
Affiliation(s)
- Lihua Zhang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China; State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang 310021, China
| | - Haiying Li
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
| | - Xiaoyu Zhao
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Yingping Wu
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Jiahui Li
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Yingying Yao
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Yang Yao
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Lin Wang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| |
Collapse
|
6
|
Yang Q, Lu X, Li G, Zhang H, Zhou C, Yin J, Han W, Yang H. Genetic Analysis of Egg Production Traits in Luhua Chickens: Insights from a Multi-Trait Animal Model and a Genome-Wide Association Study. Genes (Basel) 2024; 15:796. [PMID: 38927732 PMCID: PMC11202424 DOI: 10.3390/genes15060796] [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: 05/04/2024] [Revised: 06/10/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024] Open
Abstract
Egg production plays a pivotal role in the economic viability of hens. To analyze the genetic rules of egg production, a total of 3151 Luhua chickens were selected, the egg production traits including egg weight at first laying (Start-EW), egg weight at 43 weeks (EW-43), egg number at 43 weeks (EN-43), and total egg number (EN-All) were recorded. Then, the effects of related factors on egg production traits were explored, using a multi-trait animal model for genetic parameter estimation and a genome-wide association study (GWAS). The results showed that body weight at first egg (BWFE), body weight at 43 weeks (BW-43), age at first egg (AFE), and seasons had significant effects on the egg production traits. Start-EW and EW-43 had moderate heritability of 0.30 and 0.21, while EN-43 and EN-All had low heritability of 0.13 and 0.16, respectively. Start-EW exhibited a robust positive correlation with EW-43, while Start-EW was negatively correlated with EN-43 and EN-All. Furthermore, gene ontology (GO) results indicated that Annexin A2 (ANXA2) and Frizzled family receptor 7 (FZD7) related to EW-43, Cyclin D1 (CCND1) and A2B adenosine receptor (ADORA2B) related to EN-All, and have been found to be mainly involved in metabolism and growth processes, and deserve more attention and further study. This study contributes to accelerating genetic progress in improving low heritability egg production traits in layers, especially in Luhua chickens.
Collapse
Affiliation(s)
- Qianwen Yang
- College of Mathematical Science, Yangzhou University, Yangzhou 225009, China;
| | - Xubin Lu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (X.L.); (H.Y.)
| | - Guohui Li
- Jiangsu Institute of Poultry Science, Yangzhou 225611, China; (G.L.); (H.Z.); (C.Z.); (J.Y.)
| | - Huiyong Zhang
- Jiangsu Institute of Poultry Science, Yangzhou 225611, China; (G.L.); (H.Z.); (C.Z.); (J.Y.)
| | - Chenghao Zhou
- Jiangsu Institute of Poultry Science, Yangzhou 225611, China; (G.L.); (H.Z.); (C.Z.); (J.Y.)
| | - Jianmei Yin
- Jiangsu Institute of Poultry Science, Yangzhou 225611, China; (G.L.); (H.Z.); (C.Z.); (J.Y.)
| | - Wei Han
- Jiangsu Institute of Poultry Science, Yangzhou 225611, China; (G.L.); (H.Z.); (C.Z.); (J.Y.)
| | - Haiming Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (X.L.); (H.Y.)
| |
Collapse
|
7
|
Yang J, Wang DF, Huang JH, Zhu QH, Luo LY, Lu R, Xie XL, Salehian-Dehkordi H, Esmailizadeh A, Liu GE, Li MH. Structural variant landscapes reveal convergent signatures of evolution in sheep and goats. Genome Biol 2024; 25:148. [PMID: 38845023 PMCID: PMC11155191 DOI: 10.1186/s13059-024-03288-6] [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: 01/17/2023] [Accepted: 05/21/2024] [Indexed: 06/10/2024] Open
Abstract
BACKGROUND Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution. RESULTS We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats. CONCLUSIONS Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.
Collapse
Affiliation(s)
- Ji Yang
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Dong-Feng Wang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Jia-Hui Huang
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Qiang-Hui Zhu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ling-Yun Luo
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ran Lu
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xing-Long Xie
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Hosein Salehian-Dehkordi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, Iran
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Meng-Hua Li
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China.
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| |
Collapse
|
8
|
Lei Q, Zhang S, Wang J, Qi C, Liu J, Cao D, Li F, Han H, Liu W, Li D, Tang C, Zhou Y. Genome-wide association studies of egg production traits by whole genome sequencing of Laiwu Black chicken. Poult Sci 2024; 103:103705. [PMID: 38598913 DOI: 10.1016/j.psj.2024.103705] [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: 01/17/2024] [Revised: 03/24/2024] [Accepted: 03/26/2024] [Indexed: 04/12/2024] Open
Abstract
Compared to high-yield commercial laying hens, Chinese indigenous chicken breeds have poor egg laying capacity due to the lack of intensive selection. However, as these breeds have not undergone systematic selection, it is possible that there is a greater abundance of genetic variations related to egg laying traits. In this study, we assessed 5 egg number (EN) traits at different stages of the egg-laying period: EN1 (from the first egg to 23 wk), EN2 (from 23 to 35 wk), EN3 (from 35 to 48 wk), EN4 (from the first egg to 35 wk), and EN5 (from the first egg to 48 wk). To investigate the molecular mechanisms underlying egg number traits in a Chinese local chicken breed, we conducted a genome-wide association study (GWAS) using data from whole-genome sequencing (WGS) of 399 Laiwu Black chickens. We obtained a total of 3.01 Tb of raw data with an average depth of 7.07 × per individual. A total of 86 genome-wide suggestive or significant single-nucleotide polymorphisms (SNP) contained within a set of 45 corresponding candidate genes were identified and found to be associated with stages EN1-EN5. The genes vitellogenin 2 (VTG2), lipase maturation factor 1 (LMF1), calcium voltage-gated channel auxiliary subunit alpha2delta 3 (CACNA2D3), poly(A) binding protein cytoplasmic 1 (PABPC1), programmed cell death 11 (PDCD11) and family with sequence similarity 213 member A (FAM213A) can be considered as the candidate genes associated with egg number traits, due to their reported association with animal reproduction traits. Noteworthy, results suggests that VTG2 and PDCD11 are not only involved in the regulation of EN3, but also in the regulation of EN5, implies that VTG2 and PDCD11 have a significant influence on egg production traits. Our study offers valuable genomic insights into the molecular genetic mechanisms that govern egg number traits in a Chinese indigenous egg-laying chicken breed. These findings have the potential to enhance the egg-laying performance of chickens.
Collapse
Affiliation(s)
- Qiuxia Lei
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Shuer Zhang
- Shandong Animal Husbandry General Station, 250023, Ji'nan, China
| | - Jie Wang
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Chao Qi
- Shandong Animal Husbandry General Station, 250023, Ji'nan, China
| | - Jie Liu
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Dingguo Cao
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Fuwei Li
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Haixia Han
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Wei Liu
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Dapeng Li
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China
| | - Cunwei Tang
- Fujian Sunnzer Biological Technology Development Co. Ltd., 354100, Guang'ze, China
| | - Yan Zhou
- Poultry Institute, Shandong Academy of Agricultural Sciences, 250100, Ji'nan, China.; Poultry Breeding Engineering Technology Center of Shandong Province, 250100, Ji'nan, China..
| |
Collapse
|
9
|
Chen A, Zhao X, Wen J, Zhao X, Wang G, Zhang X, Ren X, Zhang Y, Cheng X, Yu X, Mei X, Wang H, Guo M, Jiang X, Wei G, Wang X, Jiang R, Guo X, Ning Z, Qu L. Genetic parameter estimation and molecular foundation of chicken egg-laying trait. Poult Sci 2024; 103:103627. [PMID: 38593551 PMCID: PMC11015155 DOI: 10.1016/j.psj.2024.103627] [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: 01/08/2024] [Revised: 02/23/2024] [Accepted: 03/04/2024] [Indexed: 04/11/2024] Open
Abstract
The age of first egg (AFE) in chicken can affect early and even life-time egg production performance to some extent, and therefore is an important economic trait that affects production efficiency. To better understand the genetic patterns of AFE and other production traits including body weight at first egg (BWA), first egg weight (FEW), and total egg number from AFE to 58 wk of age (total-EN), we recorded the production performance of 2 widely used layer breeds, white leghorn (WL) and Rhode Island Red (RIR) and estimated genetic parameters based on pedigree and production data. The results showed that the heritability of AFE in both breeds ranged from 0.4 to 0.6, and AFE showed strong positive genetic and phenotypic correlations to BWA as well as FEW, while showing strong negative genetic and phenotypic correlations with total-EN. Furtherly, by genome-wide association analysis study (GWAS), we identified 12 and 26 significant SNPs to be related to AFE in the 2-layer breeds, respectively. A total of 18 genes were identified that could affect AFE based on the significant SNP annotations obtained, but there were no gene overlapped in the 2 breeds indicating the genetic foundation of AFE could differ from breed to breed. Our results provided a deeper understanding of genetic patterns and molecular basement of AFE in different breeds and could help in the selection of egg production traits.
Collapse
Affiliation(s)
- Anqi Chen
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaoyu Zhao
- Xingrui Agricultural Stock Breeding, Baoding Hebei Province, 072550 China
| | - Junhui Wen
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
| | - Xiurong Zhao
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Gang Wang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xinye Zhang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xufang Ren
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yalan Zhang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xue Cheng
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaofan Yu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaohan Mei
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Huie Wang
- Xinjiang Production and Construction Corps, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, China
| | - Menghan Guo
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaoyu Jiang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Guozhen Wei
- Qingliu Animal Husbandry, Veterinary and Aquatic Products Center, Sanming, China
| | - Xue Wang
- VVBK Animal Medical Diagnostic Technology (Beijing) Co. Ltd, Beijing, China
| | - Runshen Jiang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Xing Guo
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Zhonghua Ning
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lujiang Qu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Xinjiang Production and Construction Corps, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, China.
| |
Collapse
|
10
|
Ma X, Ying F, Li Z, Bai L, Wang M, Zhu D, Liu D, Wen J, Zhao G, Liu R. New insights into the genetic loci related to egg weight and age at first egg traits in broiler breeder. Poult Sci 2024; 103:103613. [PMID: 38492250 PMCID: PMC10959720 DOI: 10.1016/j.psj.2024.103613] [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: 12/19/2023] [Revised: 02/29/2024] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
Egg weight (EW) and age at first egg (AFE) are economically important traits in breeder chicken production. The genetic basis of these traits, however, is far from understood, especially for broiler breeders. In this study, genetic parameter estimation, genome-wide association analysis, meta-analysis, and selective sweep analysis were carried out to identify genetic loci associated with EW and AFE in 6,842 broiler breeders. The study found that the heritability of EW ranged from 0.42 to 0.44, while the heritability of AFE was estimated at 0.33 in the maternal line. Meta-analysis and selective sweep analysis identified two colocalized regions on GGA4 that significantly influenced EW at 32 wk (EW32W) and at 43 wk (EW43W) with both paternal and maternal lines. The genes AR, YIPF6, and STARD8 were located within the significant region (GGA4: 366.86-575.50 kb), potentially affecting EW through the regulation of follicle development, cell proliferation, and lipid transfer etc. The promising genes LCORL and NCAPG were positioned within the significant region (GGA4:75.35-75.42 Mb), potentially influencing EW through pleiotropic effects on growth and development. Additionally, 3 significant regions were associated with AFE on chromosomes GGA7, GGA19, and GGA27. All of these factors affected the AFE by influencing ovarian development. In our study, the genomic information from both paternal and maternal lines was used to identify genetic regions associated with EW and AFE. Two genomic regions and eight genes were identified as the most likely candidates affecting EW and AFE. These findings contribute to a better understanding of the genetic basis of egg production traits in broiler breeders and provide new insights into future technology development.
Collapse
Affiliation(s)
- Xiaochun Ma
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Fan Ying
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Zhengda Li
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lu Bai
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Mengjie Wang
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Dan Zhu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Dawei Liu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan 528515, China
| | - Jie Wen
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Guiping Zhao
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ranran Liu
- State Key Laboratory of Animal Biotech Breeding; State Key Laboratory of Animal Nutrition and Feeding; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| |
Collapse
|
11
|
Meng F, Li J, Han X, Li L, Li T, Du X, Cao X, Liang Q, Huang A, Kong F, Zeng X, Bu G. TAC3 regulates GnRH/gonadotropin synthesis in female chickens. Theriogenology 2024; 215:302-311. [PMID: 38128223 DOI: 10.1016/j.theriogenology.2023.12.021] [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: 10/22/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
Neurokinin B (NKB), a peptide encoded by the tachykinin 3 (TAC3), is critical for reproduction in all studied species. However, its potential roles in birds are less clear. Using the female chicken (c-) as a model, we showed that cTAC3 is composed of five exons with a full-length cDNA of 787 bp, which was predicted to generate the mature NKB peptide containing 10 amino acids. Using cell-based luciferase reporter assays, we demonstrated that cNKB could effectively and specifically activate tachykinin receptor 3 (TACR3) in HEK293 cells, suggesting its physiological function is likely achieved via activating cTACR3 signaling. Notably, cTAC3 and cTACR3 were predominantly and abundantly expressed in the hypothalamus of hens and meanwhile the mRNA expression of cTAC3 was continuously increased during development, suggesting that NKB-TACR3 may emerge as important components of the neuroendocrine reproductive axis. In support, intraperitoneal injection of cNKB could significantly promote hypothalamic cGnRH-Ι, and pituitary cFSHβ and cLHβ expression in female chickens. Surprisingly, cTAC3 and cTACR3 were also expressed in the pituitary gland, and cNKB treatment significantly increased cLHβ and cFSHβ expression in cultured primary pituitary cells, suggesting cNKB can also act directly at the pituitary level to stimulate gonadotropin synthesis. Collectively, our results reveal that cNKB functionally regulate GnRH/gonadotropin synthesis in female chickens.
Collapse
Affiliation(s)
- Fengyan Meng
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China.
| | - Jinxuan Li
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Xingfa Han
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Lingyang Li
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Tianyang Li
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Xiaogang Du
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Xiaohan Cao
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Qiuxia Liang
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Anqi Huang
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Fanli Kong
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Xianyin Zeng
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China
| | - Guixian Bu
- College of Life Science, Sichuan Agricultural University, Xinkang Road, Ya'an, 625014, PR China.
| |
Collapse
|
12
|
Ni A, Calus MPL, Bovenhuis H, Yuan J, Wang Y, Sun Y, Chen J. Genetic parameters, reciprocal cross differences, and age-related heterosis of egg-laying performance in chickens. Genet Sel Evol 2023; 55:87. [PMID: 38062365 PMCID: PMC10702067 DOI: 10.1186/s12711-023-00862-7] [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: 03/31/2023] [Accepted: 11/28/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Egg-laying performance is economically important in poultry breeding programs. Crossbreeding between indigenous and elite commercial lines to exploit heterosis has been an upward trend in traditional layer breeding for niche markets. The objective of this study was to analyse the genetic background and to estimate the heterosis of longitudinal egg-laying traits in reciprocal crosses between an indigenous Beijing-You and an elite commercial White Leghorn layer line. Egg weights were measured for the first three eggs, monthly from 28 to 76 weeks of age, and at 86 and 100 weeks of age. Egg quality traits were measured at 32, 54, 72, 86, and 100 weeks of age. Egg production traits were measured from the start of lay until 43, 72, and 100 weeks of age. Heritabilities and phenotypic and genetic correlations were estimated. Heterosis was estimated as the percentage difference of performance of a crossbred from that of the parental average. Reciprocal cross differences were estimated as the difference between the reciprocal crossbreds as a percentage of the parental average. RESULTS Estimates of heritability of egg weights ranged from 0.29 to 0.75. Estimates of genetic correlations between egg weights at different ages ranged from 0.72 to 1.00. Estimates of heritability for cumulative egg numbers until 43, 72, and 100 weeks of age were around 0.15. Estimates of heterosis for egg weight and cumulative egg number increased with age, ranging from 1.0 to 9.0% and from 1.4 to 11.6%, respectively. From 72 to 100 weeks of age, crossbreds produced more eggs per week than the superior parent White Leghorn (3.5 eggs for White Leghorn, 3.8 and 3.9 eggs for crossbreds). Heterosis for eggshell thickness ranged from 2.7 to 6.6% when using Beijing-You as the sire breed. No significant difference between reciprocal crosses was observed for the investigated traits, except for eggshell strength at 54 weeks of age. CONCLUSIONS The heterosis was substantial for egg weight and cumulative egg number, and increased with age, suggesting that non-additive genetic effects are important in crossbreds between the indigenous and elite breeds. Generally, the crossbreds performed similar to or even outperformed the commercial White Leghorns for egg production persistency.
Collapse
Affiliation(s)
- Aixin Ni
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Mario P L Calus
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Henk Bovenhuis
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Jingwei Yuan
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yuanmei Wang
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yanyan Sun
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
| | - Jilan Chen
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
| |
Collapse
|
13
|
Haqani MI, Nakano M, Nagano AJ, Nakamura Y, Tsudzuki M. Association analysis of production traits of Japanese quail (Coturnix japonica) using restriction-site associated DNA sequencing. Sci Rep 2023; 13:21307. [PMID: 38042890 PMCID: PMC10693557 DOI: 10.1038/s41598-023-48293-0] [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: 01/06/2023] [Revised: 10/10/2023] [Accepted: 11/24/2023] [Indexed: 12/04/2023] Open
Abstract
This study was designed to perform an association analysis and identify SNP markers associated with production traits of Japanese quail using restriction-site-associated DNA sequencing. Weekly body weight data from 805 quail were collected from hatching to 16 weeks of age. A total number of 3990 eggs obtained from 399 female quail were used to assess egg quality traits. Egg-related traits were measured at the beginning of egg production (first stage) and at 12 weeks of age (second stage). Five eggs were analyzed at each stage. Traits, such as egg weight, egg length and short axes, eggshell strength and weight, egg equator thickness, yolk weight, diameter, and colour, albumen weight, age of first egg, total number of laid eggs, and egg production rate, were assessed. A total of 383 SNPs and 1151 associations as well as 734 SNPs and 1442 associations were identified in relation to quail production traits using general linear model (GLM) and mixed linear model (MLM) approaches, respectively. The GLM-identified SNPs were located on chromosomes 1-13, 15, 17-20, 24, 26-28, and Z, underlying phenotypic traits, except for egg and albumen weight at the first stage and yolk yellowness at the second stage. The MLM-identified SNPs were positioned on defined chromosomes associated with phenotypic traits except for the egg long axis at the second stage of egg production. Finally, 35 speculated genes were identified as candidate genes for the targeted traits based on their nearest positions. Our findings provide a deeper understanding and allow a more precise genetic improvement of production traits of Galliformes, particularly in Japanese quail.
Collapse
Affiliation(s)
- Mohammad Ibrahim Haqani
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan.
| | - Michiharu Nakano
- Faculty of Agriculture and Marine Sciences, Kochi University, Nankoku, Kochi, 783-8502, Japan
| | - Atsushi J Nagano
- Faculty of Agriculture, Ryukoku University, Otsu, Shiga, 520-2194, Japan
- Institute for Advanced Biosciences, Keio University, Yamagata, 997-0017, Japan
| | - Yoshiaki Nakamura
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan
- Japanese Avian Bioresource Project Research Center, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan
| | - Masaoki Tsudzuki
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan.
- Japanese Avian Bioresource Project Research Center, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan.
| |
Collapse
|
14
|
Fu M, Wu Y, Shen J, Pan A, Zhang H, Sun J, Liang Z, Huang T, Du J, Pi J. Genome-Wide Association Study of Egg Production Traits in Shuanglian Chickens Using Whole Genome Sequencing. Genes (Basel) 2023; 14:2129. [PMID: 38136951 PMCID: PMC10742582 DOI: 10.3390/genes14122129] [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: 10/28/2023] [Revised: 11/23/2023] [Accepted: 11/24/2023] [Indexed: 12/24/2023] Open
Abstract
Egg production is the most important economic trait in laying hens. To identify molecular markers and candidate genes associated with egg production traits, such as age at first egg (AFE), weight at first egg (WFE), egg weight (EW), egg number (EN), and maximum consecutive egg laying days (MCD), a genome-wide analysis by whole genome sequencing was performed in Shuanglian chickens. Through whole genome sequencing and quality control, a total of 11,006,178 SNPs were obtained for further analysis. Heritability estimates ranged from moderate to high for EW (0.897) and MCD (0.632), and from low to moderate (0.193~0.379) for AFE, WFE, and EN. The GWAS results showed 11 genome-wide significant SNPs and 23 suggestive significant SNPs were identified to be associated with EN, MCD, WFE, and EW. Linkage disequilibrium analysis revealed twenty-seven SNPs associated with EN were located in a 0.57 Mb region on GGA10, and clustered into five blocks. Through functional annotation, three candidate genes NEO1, ADPGK, and CYP11A1, were identified to be associated with EN, while the S1PR4, LDB2, and GRM8 genes was linked to MCD, WFE, and EW, respectively. These findings may help us to better understand the molecular mechanisms underlying egg production traits in chickens and contribute to genetic improvement of these traits.
Collapse
Affiliation(s)
- Ming Fu
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Yan Wu
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Jie Shen
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Ailuan Pan
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Hao Zhang
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Jing Sun
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Zhenhua Liang
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Tao Huang
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Jinping Du
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| | - Jinsong Pi
- Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Science, Wuhan 430064, China; (M.F.); (J.S.); (A.P.); (H.Z.); (J.S.); (Z.L.); (T.H.); (J.D.); (J.P.)
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Hubei Academy of Agricultural Science, Wuhan 430064, China
| |
Collapse
|
15
|
Yang H, Li Y, Yuan J, Ni A, Ma H, Wang Y, Zong Y, Zhao J, Jin S, Sun Y, Chen J. Research Note: Genetic parameters for egg production and clutch-related traits in indigenous Beijing-You chickens. Poult Sci 2023; 102:102904. [PMID: 37453280 PMCID: PMC10371837 DOI: 10.1016/j.psj.2023.102904] [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: 04/24/2023] [Revised: 06/12/2023] [Accepted: 06/24/2023] [Indexed: 07/18/2023] Open
Abstract
Egg products from indigenous chickens have growing market shares as consumers are pursuing differentiation in egg consumption. The genetic improvement in egg production performance of those breeds is crucial for increasing the economic profit. This study aimed to estimate genetic parameters for egg production and clutch-related traits in indigenous Beijing-You chickens for understanding the genetic architecture and exploring proper biological traits for selection. Data on traits including age at first egg (AFE), egg number (EN), average clutch length (ACL), maximum clutch length (MCL), number of clutches (NC) and pauses (NP), and average pause length (APL) were collected from 4 generations of purebred Beijing-You chickens based on the 43-wk and 66-wk of individual egg production record. The heritabilities, genetic and phenotypic correlations were analyzed by the DMU software with the restricted maximum likelihood method in a multivariate animal model. The results showed that the AFE of Beijing-You chickens was 174.45 d of age, and its heritability was as high as 0.62. The heritability was 0.26 for EN43 and 0.18 for EN66. The clutch traits including ACL, MCL, NC, and NP were moderate to high heritable (h2 = 0.15-0.39), but APL was very low heritable (h2 = 0.05). Genetic correlations were high between AFE and EN (rG(AFE, EN43) = -0.79, rG(AFE, EN66) = -0.39), whereas low between AFE and ACL (rG(AFE, ACL43) = -0.08, rG(AFE, ACL66) = 0.01) and MCL (rG(AFE, MCL) = -0.07). EN had higher correlations with ACL (rG(EN43, ACL43) = 0.59, rG(EN66, ACL66) = 0.40) than that with MCL (rG(EN43, MCL43) = 0.56, rG(EN66, MCL66) = 0.32). The heritability for ACL43 (h2 = 0.38) was higher than that for MCL43 (h2 = 0.33). ACL43 had a positive correlation with EN66 (rG(ACL43, EN66) = 0.62). These results indicated that the egg production of whole laying period could be improved by early selection for AFE and ACL at the same time in Beijing-You chickens.
Collapse
Affiliation(s)
- Hanhan Yang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Yunlei Li
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Jingwei Yuan
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Aixin Ni
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Hui Ma
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Yuanmei Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Yunhe Zong
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Jinmeng Zhao
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| | - Sihua Jin
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, P. R. China
| | - Yanyan Sun
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China.
| | - Jilan Chen
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China
| |
Collapse
|
16
|
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.
Collapse
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
| |
Collapse
|
17
|
Whole-genome sequencing identifies potential candidate genes for egg production traits in laying ducks (Anas platyrhynchos). Sci Rep 2023; 13:1821. [PMID: 36726023 PMCID: PMC9892591 DOI: 10.1038/s41598-022-21237-w] [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: 12/23/2021] [Accepted: 09/26/2022] [Indexed: 02/03/2023] Open
Abstract
Egg production traits are economically important in laying ducks. Genetic molecular mechanisms and candidate genes underlying these traits remain unclear. In this study, whole genome variants were identified through whole-genome resequencing using three high-egg producing (HEN) and three low-egg producing (LEN) laying ducks. The gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways for the genes of common differential variants between HEN and LEN ducks were determined. Frizzled class receptor 6 (FZD6) was further genotyped using the Sequenom MassARRAY iPLEX platform. The association of FZD6 gene polymorphisms with 73 egg production and weight traits in 329 female ducks were estimated. A total of 65,535 single nucleotide polymorphisms (SNPs) and 4,702 indels were identified across the genome. Fourteen GO terms and 14 KEGG pathways were determined for the genes of common differential variants, including MAPK signaling, Wnt signaling, melanogenesis and calcium signaling pathways, which are key functional pathways for poultry egg production reported in previous reports. Further analysis showed that 27 SNPs of FZD6 were associated with three early egg production of duck and egg weight traits, including egg production at 17 weeks (EP17), 18 weeks (EP18) and 19 weeks (EP19) and egg weight at 59 weeks (EW59). The FZD6 should be considered a novel candidate gene for egg production traits in laying ducks.
Collapse
|
18
|
Cai D, Wang Z, Zhou Z, Lin D, Ju X, Nie Q. Integration of transcriptome sequencing and whole genome resequencing reveal candidate genes in egg production of upright and pendulous-comb chickens. Poult Sci 2023; 102:102504. [PMID: 36739803 PMCID: PMC9932115 DOI: 10.1016/j.psj.2023.102504] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/30/2022] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
Egg production performance plays an important role in the poultry industry across the world. Previous studies have shown a great difference in egg production performance between pendulous-comb (PC) and upright-comb (UC) chickens. However, there are no reports to identify potential candidate genes for egg production in PC and UC chickens. In the present study, 1,606 laying chickens were raised, and the egg laid by individual chicken was collected for 100 d. Moreover, the expression level of estrogen and progesterone hormones was measured at the start-laying and peak-laying periods of hens. Besides, 4 PC and 4 UC chickens were selected at 217 d of age to perform transcriptome sequencing (RNA-seq) and whole genome resequencing (WGS) to screen the potential candidate genes of egg production. The results showed that PC chicken demonstrated better egg production performance (P < 0.05) and higher estrogen and progesterone hormone expression levels than UC chicken (P < 0.05). RNA-seq analysis showed that 341 upregulated and 1,036 downregulated differentially expressed genes (DEGs) were identified in the ovary tissues of PC and UC chickens. These DEGs were mainly enriched in protein-related, lipid-related, and nucleic acids-related biological processes including ribosome, peptide biosynthetic process, lipid transport terms, and catalytic activity acting on RNA which can significantly affect egg production in chicken. The enrichment results of WGS analysis were consistent with RNA-seq. Further, joint analysis of WGS and RNA-seq data was utilized to screen 30 genes and CAMK1D, CLSTN2, MAST2, PIK3C2G, TBC1D1, STK3, ADGRB3, and PPARGC1A were identified as potential candidate genes for egg production in PC and UC chickens. In summary, our study provides a wealth of information for a better understanding of the genetic and molecular mechanism for the future breeding of PC and UC chickens for egg production.
Collapse
Affiliation(s)
- Danfeng Cai
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Lingnan Guangdong Laboratory of Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China,Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - Zhijun Wang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Lingnan Guangdong Laboratory of Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China,Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China,College of Animal Science and Technology, Zhejiang Agriculture and Forestry University, Lin'an 311300, China
| | - Zhen Zhou
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Lingnan Guangdong Laboratory of Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China,Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - Duo Lin
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Lingnan Guangdong Laboratory of Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China,Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - Xing Ju
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Lingnan Guangdong Laboratory of Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China,Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - Qinghua Nie
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Lingnan Guangdong Laboratory of Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China.
| |
Collapse
|
19
|
Shibak A, Maghsoudi A, Rokouei M, Farhangfar H, Faraji-Arough H. Investigation of egg production curve in ostrich using nonlinear functions. Poult Sci 2022; 102:102333. [PMID: 36463766 PMCID: PMC9719868 DOI: 10.1016/j.psj.2022.102333] [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: 06/10/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 11/21/2022] Open
Abstract
In most countries, ostrich farming is considered a developing branch of the efficient poultry industry. The profitability of ostrich farm requires specific consideration of productions features such as the female fertility, egg production, hatchability, and growth performance. Hence, this study aimed to fit nonlinear functions to describe the ostrich egg production pattern to achieve the most appropriate and recommendable mathematical function for future studies. For this purpose, 14,507 daily records of 184 female ostriches in 5 production seasons (periods) during 2016 to 2021 were used. Five nonlinear functions including Incomplete gamma (Wood function), Corrected gamma (McNally), nonlinear Logistic (Yang), Logistic (Nelder), and Lokhorst were fitted for modeling the egg production curve in ostrich. The goodness of fit criteria's including Mean Square Error (MSE), Likelihood Ratio Test (LRT), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) were used to evaluate and selection of the best function. The results indicated that the Wood and the McNally functions with a slight difference in all fitting criteria were the best-fitted functions and the Yang function with the highest values of MSE, LRT, AIC, BIC, were the most inappropriate function to describe the ostrich egg production curve. The McNally and the Wood can be recommended as appropriate functions to describe egg production during 5 production seasons in the studied ostrich flock.
Collapse
Affiliation(s)
- Abbas Shibak
- Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Ali Maghsoudi
- Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Iran,Department of Animal Science, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran,Corresponding author:
| | - Mohammad Rokouei
- Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Homayoun Farhangfar
- Department of Animal Science, Faculty of Agriculture, University of Birjand, Birjand, Iran
| | - Hadi Faraji-Arough
- Department of Ostrich, Special Domestic Animals Institute, Research Institute of Zabol, Zabol, Iran
| |
Collapse
|
20
|
El-Sabrout K, Aggag S, Mishra B. Advanced Practical Strategies to Enhance Table Egg Production. SCIENTIFICA 2022; 2022:1393392. [PMID: 36349300 PMCID: PMC9637464 DOI: 10.1155/2022/1393392] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 10/19/2022] [Indexed: 05/31/2023]
Abstract
The global demand for table eggs has increased exponentially due to the growing human population. To meet this demand, major advances in hen genetics, nutrition, and husbandry procedures are required. Developing cost-effective and practically applicable strategies to improve egg production and quality is necessary for the development of egg industry worldwide. Consumers have shown a strong desire regarding the improvement of hens' welfare and egg quality. They also become interested in functional and designer foods. Modifications in the nutritional composition of laying hen diets significantly impact egg nutritional composition and quality preservation. According to previous scientific research, enriched egg products can benefit human health. However, producers are facing a serious challenge in optimizing breeding, housing, and dietary strategies to ensure hen health and high product quality. This review discussed several practical strategies to increase egg production, quality, and hens' welfare. These practical strategies can potentially be used in layer farms for sustainable egg production. One of these strategies is the transition from conventional to enriched or cage-free production systems, thereby improving bird behavior and welfare. In addition, widely use of plant/herbal substances as dietary supplements in layers' diets positively impacts hens' physiological, productive, reproductive, and immunological performances.
Collapse
Affiliation(s)
- Karim El-Sabrout
- Department of Poultry Production, Faculty of Agriculture (El-Shatby), Alexandria University, Alexandria, Egypt
| | - Sarah Aggag
- Department of Genetics, Faculty of Agriculture (El-Shatby), Alexandria University, Alexandria, Egypt
| | - Birendra Mishra
- Department of Human Nutrition Food and Animal Sciences, University of Hawaii at Manoa, 1955 East-West Road, Honolulu, HI, 96822, USA
| |
Collapse
|
21
|
A significant quantitative trait locus on chromosome Z and its impact on egg production traits in seven maternal lines of meat-type chicken. J Anim Sci Biotechnol 2022; 13:96. [PMID: 35941697 PMCID: PMC9361671 DOI: 10.1186/s40104-022-00744-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 06/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Egg production is economically important in the meat-type chicken industry. To better understand the molecular genetic mechanism of egg production in meat-type chicken, genetic parameter estimation, genome-wide association analyses combined with meta-analyses, Bayesian analyses, and selective sweep analyses were performed to screen single nucleotide polymorphisms (SNPs) and other genetic loci that were significantly associated with egg number traits in 11,279 chickens from seven material lines. RESULTS Yellow-feathered meat-type chickens laid 115 eggs at 43 weeks of age and white-feathered chickens laid 143 eggs at 60 weeks of age, with heritability ranging from 0.034-0.258. Based on meta-analyses and selective sweep analyses, one region (10.81-13.05 Mb) on chromosome Z was associated with egg number in all lines. Further analyses using the W2 line was also associated with the same region, and 29 SNPs were identified that significantly affected estimation of breeding value of egg numbers. The 29 SNPs were identified as having a significant effect on the egg number EBV in 3194 birds in line W2. There are 36 genes in the region, with glial cell derived neurotrophic factor, DAB adaptor protein 2, protein kinase AMP-activated catalytic subunit alpha 1, NAD kinase 2, mitochondrial, WD repeat domain 70, leukemia inhibitory factor receptor alpha, complement C6, and complement C7 identified as being potentially affecting to egg number. In addition, three SNPs (rs318154184, rs13769886, and rs313325646) associated with egg number were located on or near the prolactin receptor gene. CONCLUSION Our study used genomic information from different chicken lines and populations to identify a genomic region (spanning 2.24 Mb) associated with egg number. Nine genes and 29 SNPs were identified as the most likely candidate genes and variations for egg production. These results contribute to the identification of candidate genes and variants for egg traits in poultry.
Collapse
|
22
|
Wang S, Wang Y, Li Y, Xiao F, Guo H, Gao H, Wang N, Zhang H, Li H. Genome-Wide Association Study and Selective Sweep Analysis Reveal the Genetic Architecture of Body Weights in a Chicken F2 Resource Population. Front Vet Sci 2022; 9:875454. [PMID: 35958311 PMCID: PMC9361851 DOI: 10.3389/fvets.2022.875454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 06/20/2022] [Indexed: 11/29/2022] Open
Abstract
Rapid growth is one of the most important economic traits in broiler breeding programs. Identifying markers and genes for growth traits may not only benefit marker-assisted selection (MAS)/genomic selection (GS) but also provide important information for understanding the genetic architecture of growth traits in broilers. In the present study, an F2 resource population derived from a cross between the broiler and Baier yellow chicken (a Chinese local breed) was used and body weights from 1 to 12 weeks of age [body weight (BW) 1–BW12)] were measured. A total of 519 F2 birds were genome re-sequenced, and a combination of genome-wide association study (GWAS) and selective sweep analysis was carried out to characterize the genetic architecture affecting chicken body weight comprehensively. As a result, 1,539 SNPs with significant effects on body weights at different weeks of age were identified using a genome-wide efficient mixed-model association (GEMMA) package. These SNPs were distributed on chromosomes 1 and 4. Besides, windows under selection identified for BW1–BW12 varied from 1,581 to 2,265. A total of 42 genes were also identified with significant effects on BW1–BW12 based on both GWAS and selective sweep analysis. Among these genes, diacylglycerol kinase eta (DGKH), deleted in lymphocytic leukemia (DLEU7), forkhead box O17 (FOXO1), karyopherin subunit alpha 3 (KPNA3), calcium binding protein 39 like (CAB39L), potassium voltage-gated channel interacting protein 4 (KCNIP4), and slit guidance ligand 2 (SLIT2) were considered as important genes for broiler growth based on their basic functions. The results of this study may supply important information for understanding the genetic architecture of growth traits in broilers.
Collapse
Affiliation(s)
- 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
| | - Yuxiang 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
| | - Yudong 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
| | - Fan Xiao
- Fujian Sunnzer Biotechnology Development Co., Ltd., Fujian, China
| | - Huaishun Guo
- Fujian Sunnzer Biotechnology Development Co., Ltd., Fujian, China
| | - Haihe Gao
- Fujian Sunnzer Biotechnology Development Co., Ltd., Fujian, China
| | - Ning 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 Zhang
- 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
- *Correspondence: Hui Zhang
| | - 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
- Hui Li
| |
Collapse
|
23
|
Gao J, Xu W, Zeng T, Tian Y, Wu C, Liu S, Zhao Y, Zhou S, Lin X, Cao H, Lu L. Genome-Wide Association Study of Egg-Laying Traits and Egg Quality in LingKun Chickens. Front Vet Sci 2022; 9:877739. [PMID: 35795788 PMCID: PMC9251537 DOI: 10.3389/fvets.2022.877739] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/23/2022] [Indexed: 11/23/2022] Open
Abstract
Egg production is the most important trait of laying hens. To identify molecular markers and candidate genes associated with egg production and quality, such as body weight at first oviposition (BWF), the number of eggs produced in 500 days (EN500), egg weight (EW), egg shell thickness (EST), egg shell strength (ESS), and Haugh unit (HU), a genome-wide analysis was performed in 266 LingKun Chickens. The results showed that thirty-seven single nucleotide polymorphisms (SNPs) were associated with all traits (p < 9.47 × 10−8, Bonferroni correction). These SNPs were located in close proximity to or within the sequence of the thirteen candidate genes, such as Galanin And GMAP Prepropeptide (GAL), Centromere Protein (CENPF), Glypican 2 (GPC2), Phosphatidylethanolamine N-Methyltransferase (PEMT), Transcription Factor AP-2 Delta (TFAP2D), and Carboxypeptidase Q (CPQ) gene related to egg-laying and Solute Carrier Family 5 Member 7 (SLC5A7), Neurocalcin Delta (NCALD), Proteasome 20S Subunit Beta 2 (PSMB2), Slit Guidance Ligand 3 (SLIT3), and Tubulin Tyrosine Ligase Like 7 (TTLL7) genes related to egg quality. Interestingly, one of the genes involved in bone formation (SLIT3) was identified as a candidate gene for ESS. Our candidate genes and SNPs associated with egg-laying traits were significant for molecular breeding of egg-laying traits and egg quality in LingKun chickens.
Collapse
Affiliation(s)
- Jinfeng Gao
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Science, Hangzhou, China
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, China
| | - Wenwu Xu
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Science, Hangzhou, China
| | - Tao Zeng
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Science, Hangzhou, China
| | - Yong Tian
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Science, Hangzhou, China
| | - Chunqin Wu
- Wenzhou Vocational College of Science and Technology, Wenzhou, China
| | - Suzhen Liu
- Wenzhou Vocational College of Science and Technology, Wenzhou, China
| | - Yan Zhao
- Wenzhou Vocational College of Science and Technology, Wenzhou, China
| | - Shuhe Zhou
- Wenzhou Golden Land Agricultural Development Co., Ltd., Wenzhou, China
| | - Xinqin Lin
- Wenzhou Golden Land Agricultural Development Co., Ltd., Wenzhou, China
| | - Hongguo Cao
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, China
- Hongguo Cao
| | - Lizhi Lu
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Institute of Animal Science and Veterinary, Zhejiang Academy of Agricultural Science, Hangzhou, China
- *Correspondence: Lizhi Lu
| |
Collapse
|
24
|
Feng Y, Liu D, Liu Y, Yang X, Zhang M, Wei F, Li D, Hu Y, Guo Y. Host-genotype-dependent cecal microbes are linked to breast muscle metabolites in Chinese chickens. iScience 2022; 25:104469. [PMID: 35707722 PMCID: PMC9189123 DOI: 10.1016/j.isci.2022.104469] [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: 10/27/2021] [Revised: 04/08/2022] [Accepted: 05/20/2022] [Indexed: 11/18/2022] Open
Abstract
In chickens, the effect of host genetics on the gut microbiota is not fully understood, and the extent to which the heritable gut microbes affect chicken metabolism and physiology is still an open question. Here, we explored the interactions among chicken genetics, the cecal microbiota and metabolites in breast muscle from ten chicken breeds in China. We found that different chicken breeds displayed distinct cecal microbial community structures and functions, and 15 amplicon sequence variants (ASVs) were significantly associated with host genetics through different genetic loci, such as those related to the intestinal barrier function. We identified five heritable ASVs significantly associated with 53 chicken muscle metabolites, among which the Megamonas probably affected lipid metabolism through the production of propionate. Our study revealed that the chicken genetically associated cecal microbes may have the potential to affect the bird’s physiology and metabolism. The cecal microbiota are different among ten chicken breeds The chicken genetics influences the cecal microbiota structures and functions The chicken heritable cecal microbes are associated with muscle metabolites Megamonas may affect lipid metabolism by the production of propionate
Collapse
Affiliation(s)
- Yuqing Feng
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Dan Liu
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Yan Liu
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Xinyue Yang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Meihong Zhang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Fuxiao Wei
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Depeng Li
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
| | - Yongfei Hu
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
- Corresponding author
| | - Yuming Guo
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China
- Corresponding author
| |
Collapse
|
25
|
Bedere N, Berghof TVL, Peeters K, Pinard-van der Laan MH, Visscher J, David I, Mulder HA. Using egg production longitudinal recording to study the genetic background of resilience in purebred and crossbred laying hens. Genet Sel Evol 2022; 54:26. [PMID: 35439920 PMCID: PMC9020098 DOI: 10.1186/s12711-022-00716-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 03/28/2022] [Indexed: 12/02/2022] Open
Abstract
Background There is growing interest in using genetic selection to obtain more resilient farm animals (i.e. that are minimally affected by disturbances or rapidly recover from them). The aims of this study were to: (i) estimate the genetic parameters of resilience indicator traits based on egg production data, (ii) assess whether these traits are genetically correlated in purebreds and crossbreds, and (iii) assess the genetic correlations of these traits with egg production (EP) as total number of eggs between 25 and 83 weeks. Purebred hens (33,825 from a White Leghorn (WA) line and 34,397 from a Rhode Island (BD) line were housed in individual cages, while crossbred hens were housed in collective cages of 6 to 8 paternal half-sibs (12,852 WA and 3898 BD crossbred groups, where the name of the group refers to the line used as the sire). Deviations of a hen’s weekly egg production from the average of the corresponding batch were calculated. Resilience indicator traits investigated were the natural logarithm of the variance (LNVAR), the skewness (SKEW), and the lag-one autocorrelation (AUTO-R) of these deviations. Results In both purebred lines, EP was estimated to be lowly heritable (WA: 0.11 and BD: 0.12). Resilience indicators were also estimated to be lowly heritable in both lines (LNVAR: 0.10 and 0.12, SKEW: 0.04 and 0.02, AUTO-R: 0.06 and 0.08 in WA and BD, respectively). In both crossbred groups, EP, AUTO-R, and SKEW were estimated to be less heritable than in purebreds (EP: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$h^{2}$$\end{document}h2 ≤ 0.07; and resilience indicator traits: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$h^{2}$$\end{document}h2 ≤ 0.03), while LNVAR had an \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$h^{2}$$\end{document}h2 estimate that was similar to or higher in crossbreds (\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$h^{2}$$\end{document}h2 ranged from 0.13 to 0.21) than in purebreds. In both purebreds and crossbreds, resilience indicator traits were estimated to have favorable genetic correlations with EP and between each other. For all traits and in both lines, estimates of genetic correlations between purebreds and crossbreds (\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$r_{pc}$$\end{document}rpc) differed from 1 and ranged from 0.16 to 0.63. Conclusions These results show that selection for resilience based on EP data can be considered in breeding programs for layers. Genetic improvement of resilience in crossbreds can be achieved by using information on purebreds, but would be greatly enhanced by the integration of information on crossbreds in breeding programs. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00716-8.
Collapse
Affiliation(s)
- Nicolas Bedere
- PEGASE, INRAE, Institut Agro, 35590, Saint Gilles, France.
| | - Tom V L Berghof
- Wageningen University & Research Animal Breeding & Genomics, P.O. Box 338, 6700 AH, Wageningen, The Netherlands.,Reproductive Biotechnology, TUM School of Life Sciences, Technical University of Munich, Liesel‑Beckmann‑Strasse 1, 85354, Freising, Germany
| | - Katrijn Peeters
- Hendrix Genetics B.V., P.O. Box 114, 5830 AC, Boxmeer, The Netherlands
| | | | - Jeroen Visscher
- Hendrix Genetics B.V., P.O. Box 114, 5830 AC, Boxmeer, The Netherlands
| | - Ingrid David
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31320, Castanet Tolosan, France
| | - Han A Mulder
- Wageningen University & Research Animal Breeding & Genomics, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| |
Collapse
|
26
|
Xu W, Wang Z, Qu Y, Li Q, Tian Y, Chen L, Tang J, Li C, Li G, Shen J, Tao Z, Cao Y, Zeng T, Lu L. Genome-Wide Association Studies and Haplotype-Sharing Analysis Targeting the Egg Production Traits in Shaoxing Duck. Front Genet 2022; 13:828884. [PMID: 35419032 PMCID: PMC8995972 DOI: 10.3389/fgene.2022.828884] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Accepted: 02/11/2022] [Indexed: 12/30/2022] Open
Abstract
Age at first egg (AFE) and egg number (EN) are economically important traits related to egg production, as they directly influence the benefits of the poultry industry, but the molecular genetic research that affects those traits in laying ducks is still sparse. Our objective was to identify the genomic regions and candidate genes associated with AFE, egg production at 43 weeks (EP43w), and egg production at 66 weeks (EP66w) in a Shaoxing duck population using genome-wide association studies (GWASs) and haplotype-sharing analysis. Single-nucleotide polymorphism (SNP)-based genetic parameter estimates showed that the heritability was 0.15, 0.20, and 0.22 for AFE, EP43w, and EP66w, respectively. Subsequently, three univariate GWASs for AFE, EP43w, and EP66w were carried out independently. Twenty-four SNPs located on chromosome 25 within a 0.01-Mb region that spans from 4.511 to 4.521 Mb were associated with AFE. There are two CIs that affect EP43w, i.e., twenty-five SNPs were in strong linkage disequilibrium region spanning from 3.186 to 3.247 Mb on chromosome 25, a region spanning from 4.442 to 4.446 Mb on chromosome 25, and two interesting genes, ACAD8 and THYN1, that may affect EP43w in laying ducks. There are also two CIs that affect EP66w, i.e., a 2.412-Mb region that spans from 127.497 to 129.910 Mb on chromosome 2 and a 0.355-Mb region that spans from 4.481 to 4.837 Mb on chromosome 29, and CA2 and GAMT may be the putative candidate genes. Our study also found some haplotypes significantly associated with these three traits based on haplotype-sharing analysis. Overall, this study was the first publication of GWAS on egg production in laying ducks, and our findings will be helpful to provide some candidate genes and haplotypes to improve egg production performance based on breeding in laying duck. Additionally, we learned from a method called bootstrap test to verify the reliability of a GWAS with small experimental samples that users can access at https://github.com/xuwenwu24/Bootstrap-test.
Collapse
Affiliation(s)
- Wenwu Xu
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Zhenzhen Wang
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Yuanqi Qu
- Hubei Shendan Co., Ltd., Wuhan, China
| | - Qingyi Li
- Hubei Shendan Co., Ltd., Wuhan, China
| | - Yong Tian
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Li Chen
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | | | | | - Guoqin Li
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Junda Shen
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Zhengrong Tao
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Yongqing Cao
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Tao Zeng
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Lizhi Lu
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| |
Collapse
|
27
|
Genome-wide association studies for growth traits in broilers. BMC Genom Data 2022; 23:1. [PMID: 34979907 PMCID: PMC8725492 DOI: 10.1186/s12863-021-01017-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 11/30/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The identification of markers and genes for growth traits may not only benefit for marker assist selection /genomic selection but also provide important information for understanding the genetic foundation of growth traits in broilers. RESULTS In the current study, we estimated the genetic parameters of eight growth traits in broilers and carried out the genome-wide association studies for these growth traits. A total of 113 QTNs discovered by multiple methods together, and some genes, including ACTA1, IGF2BP1, TAPT1, LDB2, PRKCA, TGFBR2, GLI3, SLC16A7, INHBA, BAMBI, APCDD1, GPR39, and GATA4, were identified as important candidate genes for rapid growth in broilers. CONCLUSIONS The results of this study will provide important information for understanding the genetic foundation of growth traits in broilers.
Collapse
|
28
|
Wang H, Cahaner A, Lou L, Zhang L, Ge Y, Li Q, Zhang X. Genetics and breeding of a black-bone and blue eggshell chicken line. 2. Laying patterns and egg production in two consecutive generations. Poult Sci 2021; 101:101679. [PMID: 35306315 PMCID: PMC8933698 DOI: 10.1016/j.psj.2021.101679] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 12/08/2021] [Accepted: 12/10/2021] [Indexed: 12/04/2022] Open
Abstract
The BG line was originated from the cross between 2 Chinese indigenous breeds, Dongxiang blue eggshell, and Jiangshan black-bone, and has been bred to combine dark heavy black-bone body and high production of blue-shell eggs, into single dual-purpose line. Full-pedigree hens from 2 generations, G4 (n = 441) and G5 (n = 464), were reared in the same single-cage laying facility in 2019–2020 and 2020–2021, respectively. Starting from the first egg of each hen, its daily egg production was recorded until 300 days-of-age. Up to 7 "no-egg" days were considered normal laying breaks between clutches, whereas laying cessation of 8 or more days was considered Pause, and the laying pattern of each hen was assigned either with Pause or No-Pause. The other traits included PsDays: number of Pause days; AFE: age at first egg; EN300: eggs laid until 300 d; %L300: total laying rate (EN300/[300-AFE]); %Lnet: net laying rate (EN300/[300-AFE-PsDays]); ClLng: average clutch length; EW200 and EW300: average egg weight around 200 d and 300 d. Estimates of heritability (h2) of each trait, and phenotypic and genetic correlation between traits, were calculated in each generation using the animal model. Heritability estimates were calculated also by regressing the means of full-sib G5 hens on their G4 parents' means. Mean overall laying rate of all G4 hens was low (%L300 = 57%) because 53% of them had Pause in their laying pattern. In G5, incidence of Pause was higher (75%) due to a 3-wk cold stress, with mean %L300 = 54%. However, significant estimates of heritability and genetic correlations suggest that selection for low PsDays will reduce the incidence of Pause in BG hens and elevate the line's mean laying rate towards %L300 = 70%, as the No-Pause hens in G5. PsDays-free laying rate (%Lnet) was found to be highly correlated with the significantly heritable (h2≈0.4) clutch length (ClLng). Selection index combining the genetically independent low PsDays and high ClLng is expected to maximize egg production improvement in the BG line, and in similar populations derived from indigenous breeds.
Collapse
|
29
|
Habimana R, Ngeno K, Okeno TO, Hirwa CDA, Keambou Tiambo C, Yao NK. Genome-Wide Association Study of Growth Performance and Immune Response to Newcastle Disease Virus of Indigenous Chicken in Rwanda. Front Genet 2021; 12:723980. [PMID: 34745207 PMCID: PMC8570395 DOI: 10.3389/fgene.2021.723980] [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: 06/11/2021] [Accepted: 07/15/2021] [Indexed: 11/13/2022] Open
Abstract
A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs (rs74098018, rs13792572, rs314702374, and rs14123335) significantly (p ≤ 7.6E-5) associated with BW were identified on chromosomes (CHRs) 8, 11, and 19. In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs (rs314787954, rs13623466, rs13910430, and rs737507850) all located on chromosome 1 were strongly (p ≤ 7.6E-5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E-5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.
Collapse
Affiliation(s)
- Richard Habimana
- College of Agriculture, Animal Science and Veterinary Medicine, University of Rwanda, Kigali, Rwanda.,Animal Breeding and Genomics Group, Department of Animal Science, Egerton University, Egerton, Kenya
| | - Kiplangat Ngeno
- Animal Breeding and Genomics Group, Department of Animal Science, Egerton University, Egerton, Kenya
| | - Tobias Otieno Okeno
- Animal Breeding and Genomics Group, Department of Animal Science, Egerton University, Egerton, Kenya
| | | | - Christian Keambou Tiambo
- Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Nairobi, Kenya
| | - Nasser Kouadio Yao
- Biosciences Eastern and Central Africa - International Livestock Research Institute (BecA-ILRI) Hub, Nairobi, Kenya
| |
Collapse
|
30
|
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.
Collapse
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
| |
Collapse
|
31
|
Novel genome reveals susceptibility of popular gamebird, the red-legged partridge (Alectoris rufa, Phasianidae), to climate change. Genomics 2021; 113:3430-3438. [PMID: 34400239 DOI: 10.1016/j.ygeno.2021.08.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 08/02/2021] [Accepted: 08/11/2021] [Indexed: 01/15/2023]
Abstract
We produced a high-quality de novo genome assembly of the red-legged partridge A. rufa, the first reference genome of its genus, by utilising novel 10× Chromium technology. The estimated genome size was 1.19 Gb with an overall genome heterozygosity of 0.0022; no runs of homozygosity were observed. In total, 21,589 protein coding genes were identified and assigned to 16,772 orthologs. Of these, 201 emerged as unique to Alectoris and were enriched for positive regulation of epithelial cell migration, viral genome integration and maturation. Using PSMC analysis, we inferred a major demographic decline commencing ~140,000 years ago, consistent with forest expansion and reduction of open habitats during the Eemian interglacial. Present-day populations exhibit the historically lowest genetic diversity. Besides implications for management and conservation, this genome also promises key insights into the physiology of these birds with a view to improving poultry husbandry practices.
Collapse
|
32
|
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.
Collapse
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.
| |
Collapse
|
33
|
Comparison of Selection Signatures between Korean Native and Commercial Chickens Using 600K SNP Array Data. Genes (Basel) 2021; 12:genes12060824. [PMID: 34072132 PMCID: PMC8230197 DOI: 10.3390/genes12060824] [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: 04/12/2021] [Revised: 05/18/2021] [Accepted: 05/24/2021] [Indexed: 12/14/2022] Open
Abstract
Korean native chickens (KNCs) comprise an indigenous chicken breed of South Korea that was restored through a government project in the 1990s. The KNC population has not been developed well and has mostly been used to maintain purebred populations in the government research institution. We investigated the genetic features of the KNC population in a selection signal study for the efficient improvement of this breed. We used 600K single nucleotide polymorphism data sampled from 191 KNCs (NG, 38; NL, 29; NR, 52; NW, 39; and NY, 33) and 54 commercial chickens (Hy-line Brown, 10; Lohmann Brown, 10; Arbor Acres, 10; Cobb, 12; and Ross, 12). Haplotype phasing was performed using EAGLE software as the initial step for the primary data analysis. Pre-processed data were analyzed to detect selection signals using the ‘rehh’ package in R software. A few common signatures of selection were identified in KNCs. Most quantitative trait locus regions identified as candidate regions were associated with traits related to reproductive organs, eggshell characteristics, immunity, and organ development. Block patterns with high linkage disequilibrium values were observed for LPP, IGF11, LMNB2, ERBB4, GABRB2, NTM, APOO, PLOA1, CNTN1, NTSR1, DEF3, CELF1, and MEF2D genes, among regions with confirmed selection signals. NL and NW lines contained a considerable number of selective sweep regions related to broilers and layers, respectively. We recommend focusing on improving the egg and meat traits of KNC NL and NW lines, respectively, while improving multiple traits for the other lines.
Collapse
|
34
|
Bitaraf Sani M, Zare Harofte J, Banabazi MH, Esmaeilkhanian S, Shafei Naderi A, Salim N, Teimoori A, Bitaraf A, Zadehrahmani M, Burger PA, Landi V, Silawi M, Taghipour Sheshdeh A, Faghihi MA. Genomic prediction for growth using a low-density SNP panel in dromedary camels. Sci Rep 2021; 11:7675. [PMID: 33828208 PMCID: PMC8027435 DOI: 10.1038/s41598-021-87296-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Accepted: 03/26/2021] [Indexed: 11/29/2022] Open
Abstract
For thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees.
Collapse
Affiliation(s)
- Morteza Bitaraf Sani
- Animal Science Research Department, Yazd Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), 8915813155, Yazd, Iran.
| | - Javad Zare Harofte
- Animal Science Research Department, Yazd Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), 8915813155, Yazd, Iran
| | - Mohammad Hossein Banabazi
- Department of Biotechnology, Animal Science Research Institute of IRAN (ASRI), Agricultural Research, Education & Extension Organization (AREEO), 3146618361, Karaj, Iran
| | - Saeid Esmaeilkhanian
- Department of Biotechnology, Animal Science Research Institute of IRAN (ASRI), Agricultural Research, Education and Extension Organization (AREEO), 3146618361, Karaj, Iran
| | - Ali Shafei Naderi
- Animal Science Research Department, Yazd Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), 8915813155, Yazd, Iran
| | - Nader Salim
- Organization of Agriculture - Jahad -Yazd, Ministry of Agriculture-Jahad, 8916713449, Yazd, Iran
| | - Abbas Teimoori
- Organization of Agriculture - Jahad -Yazd, Ministry of Agriculture-Jahad, 8916713449, Yazd, Iran
| | - Ahmad Bitaraf
- Animal Science Research Department, Yazd Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), 8915813155, Yazd, Iran
| | | | - Pamela Anna Burger
- Research Institute of Wildlife Ecology, Vetmeduni Vienna, 1160, Vienna, Austria
| | - Vincenzo Landi
- Departement of Veterinary Medicine, Università Di Bari "Aldo Moro", Bari, Italy
| | - Mohammad Silawi
- Persian BayanGene Research and Training Center, 7134767617, Shiraz, Iran
| | | | - Mohammad Ali Faghihi
- Persian BayanGene Research and Training Center, 7134767617, Shiraz, Iran.,Center for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, 33136, USA
| |
Collapse
|
35
|
Hanlon C, Takeshima K, Bédécarrats GY. Changes in the Control of the Hypothalamic-Pituitary Gonadal Axis Across Three Differentially Selected Strains of Laying Hens ( Gallus gallus domesticus). Front Physiol 2021; 12:651491. [PMID: 33841186 PMCID: PMC8027345 DOI: 10.3389/fphys.2021.651491] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 03/05/2021] [Indexed: 11/13/2022] Open
Abstract
Genetic selection for earlier sexual maturation and extended production cycles in laying hens has significantly improved reproductive efficiency. While limited emphasis has been placed on the underlying physiological changes, we hypothesize that modifications in the control of the hypothalamic-pituitary gonadal (HPG) axis have occurred. Thus, three strains of White leghorn derivatives were followed from hatch to 100 weeks of age (woa), including Lohmann LSL-lite (n = 120) as current commercial hens, heritage Shaver White leghorns (n = 100) as 2000s commercial equivalents, and Smoky Joe hens (n = 68) as 1960s commercial equivalents. Body weight (BW) and egg production were monitored, and blood samples were collected throughout to monitor estradiol (E2) concentrations. Tissue samples were collected at 12, 17, 20, 25, 45, 60, 75, and 100 woa to capture changes in mRNA levels of key genes involved in the HPG axis and monitor ovarian follicular pools. All hens, regardless of strain, age or photoperiod laid their first egg within a 64-gram BW window and, as E2 levels increased prior to photostimulation (PS) in Lohmann and Shaver hens, a metabolic trigger likely induced sexual maturation. However, increased levels of Opsin 5 (OPN5) were observed during the maturation period. Although an elevation in gonadotrophin-releasing hormone I (GnRH-I) mRNA levels was associated with early maturation, no changes in gonadotrophin-inhibitory hormone (GnIH) mRNA levels were observed. Nonetheless, a significant shift in pituitary sensitivity to GnRH was associated with maturation. Throughout the trial, Lohmann, Shaver, and Smoky Joe hens laid 515, 417, and 257 eggs, respectively (p < 0.0001). Results show that the extended laying persistency in Lohmann hens was supported by sustained pituitary sensitivity to GnRH-I, recurrent elevations in follicle-stimulating hormone (FSH) mRNA levels, and five cyclical elevations in E2 levels. This was also associated with a consistently higher pool of small white ovarian follicles. In summary, our results demonstrate first that, regardless of photoperiodic cues, meeting a specific narrow body weight threshold is sufficient to initiate sexual maturation in Leghorn chicken derivatives. Furthermore, recurrent increases in E2 and FSH may be the key to sustain extended laying period, allowing modern layers to double their reproductive capacity compared to their 1960s-counterparts.
Collapse
Affiliation(s)
- Charlene Hanlon
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Kayo Takeshima
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | | |
Collapse
|
36
|
Gao G, Gao D, Zhao X, Xu S, Zhang K, Wu R, Yin C, Li J, Xie Y, Hu S, Wang Q. Genome-Wide Association Study-Based Identification of SNPs and Haplotypes Associated With Goose Reproductive Performance and Egg Quality. Front Genet 2021; 12:602583. [PMID: 33777090 PMCID: PMC7994508 DOI: 10.3389/fgene.2021.602583] [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: 09/03/2020] [Accepted: 02/24/2021] [Indexed: 01/10/2023] Open
Abstract
Geese are one of the most economically important waterfowl. However, the low reproductive performance and egg quality of geese hinder the development of the goose industry. The identification and application of genetic markers may improve the accuracy of beneficial trait selection. To identify the genetic markers associated with goose reproductive performance and egg quality traits, we performed a genome-wide association study (GWAS) for body weight at birth (BBW), the number of eggs at 48 weeks of age (EN48), the number of eggs at 60 weeks of age (EN60) and egg yolk color (EYC). The GWAS acquired 2.896 Tb of raw sequencing data with an average depth of 12.44× and identified 9,279,339 SNPs. The results of GWAS showed that 26 SNPs were significantly associated with BBW, EN48, EN60, and EYC. Moreover, five of these SNPs significantly associated with EN48 and EN60 were in a haplotype block on chromosome 35 from 4,512,855 to 4,541,709 bp, oriented to TMEM161A and another five SNPs significantly correlated to EYC were constructed in haplotype block on chromosome 5 from 21,069,009 to 21,363,580, which annotated by TMEM161A, CALCR, TFPI2, and GLP1R. Those genes were enriched in epidermal growth factor-activated receptor activity, regulation of epidermal growth factor receptor signaling pathway. The SNPs, haplotype markers, and candidate genes identified in this study can be used to improve the accuracy of marker-assisted selection for the reproductive performance and egg quality traits of geese. In addition, the candidate genes significantly associated with these traits may provide a foundation for better understanding the mechanisms underlying reproduction and egg quality in geese.
Collapse
Affiliation(s)
- Guangliang Gao
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Dengfeng Gao
- State Key Laboratory of Agrobiotechnology, China Agricultural University, Beijing, China
| | - Xianzhi Zhao
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | | | - Keshan Zhang
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Rui Wu
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Chunhui Yin
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Jing Li
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Youhui Xie
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| | - Silu Hu
- Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Qigui Wang
- Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing, China
- Chongqing Engineering Research Center of Goose Genetic Improvement, Chongqing, China
| |
Collapse
|
37
|
Jing Z, Wang X, Cheng Y, Wei C, Hou D, Li T, Li W, Han R, Li H, Sun G, Tian Y, Liu X, Kang X, Li Z. Detection of CNV in the SH3RF2 gene and its effects on growth and carcass traits in chickens. BMC Genet 2020; 21:22. [PMID: 32111154 PMCID: PMC7048116 DOI: 10.1186/s12863-020-0831-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 02/25/2020] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The SH3RF2 gene is a protein-coding gene located in a quantitative trait locus associated with body weight, and its deletion has been shown to be positively associated with body weight in chickens. RESULTS In the present study, CNV in the SH3RF2 gene was detected in 4079 individuals from 17 populations, including the "Gushi ×Anka" F2 resource population and populations of Chinese native chickens, commercial layers, and commercial broilers. The F2 resource population was then used to investigate the genetic effects of the chicken SH3RF2 gene. The results showed that the local chickens and commercial layers were all homozygous for the wild-type allele. Deletion mutation individuals were detected in all of the commercial broiler breeds except Hubbard broiler. A total of, 798 individuals in the F2 resource group were used to analyze the effects of genotype (DD/ID/II) on chicken production traits. The results showed that CNV was associated with 2-, 6-, 10-, and 12-week body weight (P = 0.026, 0.042, 0.021 and 0.039 respectively) and significantly associated with 8-week breast bone length (P = 0.045). The mutation was significantly associated with 8-week body weight (P = 0.007) and 4-week breast bone length (P = 0.010). CNV was significantly associated with evisceration weight, leg muscle weight, carcass weight, breast muscle weight and gizzard weight (P = 0.032, 0.033, 0.045, 0.004 and 0.000, respectively). CONCLUSIONS CNV of the SH3RF2 gene contributed to variation in the growth and weight gain of chickens.
Collapse
Affiliation(s)
- Zhenzhu Jing
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Xinlei Wang
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Yingying Cheng
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Chengjie Wei
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Dan Hou
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Tong Li
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Wenya Li
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Ruili Han
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Hong Li
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Guirong Sun
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Yadong Tian
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Xiaojun Liu
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Xiangtao Kang
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China
| | - Zhuanjian Li
- Department of Animal genetics and breeding, College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China.
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, Henan, China.
| |
Collapse
|
38
|
Lu Z, Yue Y, Yuan C, Liu J, Chen Z, Niu C, Sun X, Zhu S, Zhao H, Guo T, Yang B. Genome-Wide Association Study of Body Weight Traits in Chinese Fine-Wool Sheep. Animals (Basel) 2020; 10:E170. [PMID: 31963922 PMCID: PMC7022301 DOI: 10.3390/ani10010170] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/10/2020] [Accepted: 01/14/2020] [Indexed: 02/07/2023] Open
Abstract
Body weight is an important economic trait for sheep and it is vital for their successful production and breeding. Therefore, identifying the genomic regions and biological pathways that contribute to understanding variability in body weight traits is significant for selection purposes. In this study, the genome-wide associations of birth, weaning, yearling, and adult weights of 460 fine-wool sheep were determined using resequencing technology. The results showed that 113 single nucleotide polymorphisms (SNPs) reached the genome-wide significance levels for the four body weight traits and 30 genes were annotated effectively, including AADACL3, VGF, NPC1, and SERPINA12. The genes annotated by these SNPs significantly enriched 78 gene ontology terms and 25 signaling pathways, and were found to mainly participate in skeletal muscle development and lipid metabolism. These genes can be used as candidate genes for body weight in sheep, and provide useful information for the production and genomic selection of Chinese fine-wool sheep.
Collapse
Affiliation(s)
- Zengkui Lu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Yaojing Yue
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Chao Yuan
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Jianbin Liu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Zhiqiang Chen
- Novogene Bioinformatics Institute, Beijing 100029, China;
| | - Chune Niu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xiaoping Sun
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Shaohua Zhu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Hongchang Zhao
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Tingting Guo
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Bohui Yang
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (Z.L.); (Y.Y.); (C.Y.); (J.L.); (C.N.); (X.S.); (S.Z.); (H.Z.)
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| |
Collapse
|