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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.
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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.
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Wang Y, Wang J, Shi Y, Ye H, Luo W, Geng F. Quantitative proteomic analyses during formation of chicken egg yolk. Food Chem 2021; 374:131828. [PMID: 34915371 DOI: 10.1016/j.foodchem.2021.131828] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 11/04/2021] [Accepted: 12/06/2021] [Indexed: 12/11/2022]
Abstract
A quantitative comparison of the proteomes during different periods of the formation of egg yolk, from yellow follicles (YF), small hierarchical follicles (9-12 mm, SF), and the largest hierarchical follicle (LF), was performed. The abundance of major egg yolk proteins (apolipoprotein B and vitellogenins) changed significantly during the yolk formation, and several protein hydrolases and isomerases, which may be related to the processing of egg yolk proteins, also varied significantly. The binding proteins for three vitamins (retinol, riboflavin, and vitamin D) and cholesterol were all most abundant in the LF period, suggesting that these nutrients were transported mainly at the final period of the egg yolk formation. Immunoglobulins decreased and complement proteins increased as formation progressed, indicating the dynamic nature of the egg yolk immune system. These results are helpful for understanding the nutrient composition, the formation of assembly structure, the preservation and processing properties of egg yolk.
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Affiliation(s)
- Yi Wang
- Institute for Egg Science and Technology, School of Food and Biological Engineering, Chengdu University, Chengdu 610106, China
| | - Jinqiu Wang
- Institute for Egg Science and Technology, School of Food and Biological Engineering, Chengdu University, Chengdu 610106, China
| | - Yaoqiang Shi
- Department of Biological Engineering, Sichuan Water Conservancy Vocational College, Chengdu 611830, China
| | - Haolong Ye
- Institute for Egg Science and Technology, School of Food and Biological Engineering, Chengdu University, Chengdu 610106, China
| | - Wei Luo
- Institute for Egg Science and Technology, School of Food and Biological Engineering, Chengdu University, Chengdu 610106, China
| | - Fang Geng
- Institute for Egg Science and Technology, School of Food and Biological Engineering, Chengdu University, Chengdu 610106, China.
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Long noncoding RNAs profiling in ovary during laying and nesting in Muscovy ducks (Cairina moschata). Anim Reprod Sci 2021; 230:106762. [PMID: 34022609 DOI: 10.1016/j.anireprosci.2021.106762] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 05/01/2021] [Accepted: 05/03/2021] [Indexed: 12/11/2022]
Abstract
There are recent reports of the important functions of long noncoding RNAs (lncRNAs) in female reproductive and ovarian development. Studies in which there was characterization of lncRNAs in the ovaries of laying compared with nesting poultry, however, are limited. In this study, RNA libraries were constructed by obtaining sequencing data of ovarian tissues from laying and nesting Muscovy ducks. In the ovarian tissues of Muscovy ducks, a total of 334 differentially abundant mRNA transcripts (DEGs) and 36 differentially abundant lncRNA transcripts were identified in the nesting period, when compared with during the laying period. These results were subsequently validated by qRT-PCR using nine randomly-selected lncRNAs and six randomly-selected DAMTs. Furthermore, the cis- and trans-regulatory target genes of differentially abundant lncRNA transcripts were identified, and lncRNA-gene interaction networks of 34 differentially abundant lncRNAs and 263 DEGs were constructed. A total of 7601 lncRNAs neighboring 10,542 protein-coding genes were identified and found to be enriched in the Wnt signaling pathway and oocyte meiosis pathways associated with follicular development. Overall, only 11 cis-targets and 57 mRNA-mRNA except trans-targets were involved in the lncRNA-gene interaction networks. Based on the interaction networks, nine DEGs were trans-regulated by differentially abundant lncRNAs and 20 differentially abundant lncRNAs were hypothesized to have important functions in the regulation of broodiness in Muscovy ducks. In this study, a predicted interaction network of differentially abundant lncRNAs and DEGs in Muscovy ducks was constructed for the first time leading to an enhanced understanding of lncRNA and gene interactions regulating broodiness.
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Cao Z, Meng B, Fan R, Liu M, Gao M, Xing Z, Luan X. Comparative proteomic analysis of ovaries from Huoyan geese between pre-laying and laying periods using an iTRAQ-based approach. Poult Sci 2018; 97:2170-2182. [DOI: 10.3382/ps/pey029] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Accepted: 02/22/2018] [Indexed: 01/12/2023] Open
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Liu L, Li D, Gilbert ER, Xiao Q, Zhao X, Wang Y, Yin H, Zhu Q. Effect of Monochromatic Light on Expression of Estrogen Receptor (ER) and Progesterone Receptor (PR) in Ovarian Follicles of Chicken. PLoS One 2015; 10:e0144102. [PMID: 26624893 PMCID: PMC4666490 DOI: 10.1371/journal.pone.0144102] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2015] [Accepted: 11/12/2015] [Indexed: 11/18/2022] Open
Abstract
Artificial illumination is widely used in modern poultry houses and different wavelengths of light affect poultry production and behaviour. In this study, we measure mRNA and protein abundance of estrogen receptors (ERs) and progesterone receptors (PRs) in order to investigate the effect of monochromatic light on egg production traits and gonadal hormone function in chicken ovarian follicles. Five hundred and fifty-two 19-wk-old laying hens were exposed to three monochromatic lights: red (RL; 660 nm), green (GL; 560 nm), blue (BL; 480 nm) and control cool white (400–760 nm) light with an LED (light-emitting diode). There were 4 identical light-controlled rooms (n = 138) each containing 3 replicate pens (46 birds per pen). Water was supplied ad libitum and daily rations were determined according to the nutrient suggestions for poultry. Results showed that under BL conditions there was an increase in the total number of eggs at 300 days of age and egg-laying rate during the peak laying period. The BL and GL extended the duration of the peak laying period. Plasma melatonin was lowest in birds reared under BL. Plasma estradiol was elevated in the GL-exposed laying hens, and GL and BL increased progesterone at 28 wk of age. In the granulosa layers of the fifth largest preovulatory follicle (F5), the third largest preovulatory follicle (F3) and the largest preovulatory follicle (F1), ERα mRNA was increased by BL and GL. Treatment with BL increased ERβ mRNA in granulosa layers of F5, F3 and F1, while GL increased ERβ mRNA in F5 and F3. There was a corresponding increase in abundance of the proteins in the granulosa layers of F5, with an increase in PR-B, generated via an alternative splice site, relative to PR-A. Treatment with BL also increased expression of PR mRNA in all of the granulosa layers of follicles, while treatment with GL increased expression of PR mRNA in granulosa layers of SYF(small yellow follicle), F5 and F1. These results indicate that blue and green monochromatic lights promote egg production traits via stimulating gonadal hormone secretion and up-regulating expression of ERs and PRs. Changes in PR-B protein suggest that this form of the progesterone receptor is predominant for progesterone action in the granulosa layers of preovulatory follicles in chickens during light stimulation.
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Affiliation(s)
- Lingbin Liu
- Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
| | - Diyan Li
- Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
| | - Elizabeth R. Gilbert
- Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Qihai Xiao
- Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
| | - Xiaoling Zhao
- College of Animal science and technology, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
| | - Yan Wang
- Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
| | - Huadong Yin
- Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
| | - Qing Zhu
- Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Ya’an, Sichuan, P. R. China
- * E-mail:
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Muckova P, Wendler S, Rubel D, Büchler R, Alert M, Gross O, Rhode H. Preclinical Alterations in the Serum of COL(IV)A3–/– Mice as Early Biomarkers of Alport Syndrome. J Proteome Res 2015; 14:5202-14. [DOI: 10.1021/acs.jproteome.5b00814] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Petra Muckova
- Institute
of Biochemistry I, University Hospital Jena, Nonnenplan 2-4, 07740 Jena, Germany
- Clinic
of Neurology, University Hospital Jena, Erlanger Allee 101, 07740 Jena, Germany
| | - Sindy Wendler
- Institute
of Biochemistry I, University Hospital Jena, Nonnenplan 2-4, 07740 Jena, Germany
| | - Diana Rubel
- Department
of Nephrology and Rheumatology, University Medicine Göttingen, Robert-Koch Str. 40, 37075 Göttingen, Germany
| | - Rita Büchler
- Institute
of Biochemistry I, University Hospital Jena, Nonnenplan 2-4, 07740 Jena, Germany
| | - Mandy Alert
- Institute
of Biochemistry I, University Hospital Jena, Nonnenplan 2-4, 07740 Jena, Germany
| | - Oliver Gross
- Department
of Nephrology and Rheumatology, University Medicine Göttingen, Robert-Koch Str. 40, 37075 Göttingen, Germany
| | - Heidrun Rhode
- Institute
of Biochemistry I, University Hospital Jena, Nonnenplan 2-4, 07740 Jena, Germany
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Wang Y, Xu HY, Gilbert ER, Peng X, Zhao XL, Liu YP, Zhu Q. Detection of SNPs in the TBC1D1 gene and their association with carcass traits in chicken. Gene 2014; 547:288-94. [DOI: 10.1016/j.gene.2014.06.061] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2014] [Revised: 06/25/2014] [Accepted: 06/27/2014] [Indexed: 11/25/2022]
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