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Zhang W, Lan F, Zhou Q, Gu S, Li X, Wen C, Yang N, Sun C. Host genetics and gut microbiota synergistically regulate feed utilization in egg-type chickens. J Anim Sci Biotechnol 2024; 15:123. [PMID: 39245742 PMCID: PMC11382517 DOI: 10.1186/s40104-024-01076-7] [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: 04/03/2024] [Accepted: 07/14/2024] [Indexed: 09/10/2024] Open
Abstract
BACKGROUND Feed efficiency is a crucial economic trait in poultry industry. Both host genetics and gut microbiota influence feed efficiency. However, the associations between gut microbiota and host genetics, as well as their combined contributions to feed efficiency in laying hens during the late laying period, remain largely unclear. METHODS In total, 686 laying hens were used for whole-genome resequencing and liver transcriptome sequencing. 16S rRNA gene sequencing was conducted on gut chyme (duodenum, jejunum, ileum, and cecum) and fecal samples from 705 individuals. Bioinformatic analysis was performed by integrating the genome, transcriptome, and microbiome to screen for key genetic variations, genes, and gut microbiota associated with feed efficiency. RESULTS The heritability of feed conversion ratio (FCR) and residual feed intake (RFI) was determined to be 0.28 and 0.48, respectively. The ileal and fecal microbiota accounted for 15% and 10% of the FCR variance, while the jejunal, cecal, and fecal microbiota accounted for 20%, 11%, and 10% of the RFI variance. Through SMR analysis based on summary data from liver eQTL mapping and GWAS, we further identified four protein-coding genes, SUCLA2, TNFSF13B, SERTM1, and MARVELD3, that influence feed efficiency in laying hens. The SUCLA2 and TNFSF13B genes were significantly associated with SNP 1:25664581 and SNP rs312433097, respectively. SERTM1 showed significant associations with rs730958360 and 1:33542680 and is a potential causal gene associated with the abundance of Corynebacteriaceae in feces. MARVELD3 was significantly associated with the 1:135348198 and was significantly correlated with the abundance of Enterococcus in ileum. Specifically, a lower abundance of Enterococcus in ileum and a higher abundance of Corynebacteriaceae in feces were associated with better feed efficiency. CONCLUSIONS This study confirms that both host genetics and gut microbiota can drive variations in feed efficiency. A small portion of the gut microbiota often interacts with host genes, collectively enhancing feed efficiency. Therefore, targeting both the gut microbiota and host genetic variation by supporting more efficient taxa and selective breeding could improve feed efficiency in laying hens during the late laying period.
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Affiliation(s)
- Wenxin Zhang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Fangren Lan
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Qianqian Zhou
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Shuang Gu
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Xiaochang Li
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Chaoliang Wen
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Ning Yang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Congjiao Sun
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
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Jie Y, Wen C, Huang Q, Gu S, Sun C, Li G, Yan Y, Wu G, Yang N. Distinct patterns of feed intake and their association with growth performance in broilers. Poult Sci 2024; 103:103974. [PMID: 38972283 PMCID: PMC11264188 DOI: 10.1016/j.psj.2024.103974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/07/2024] [Accepted: 06/07/2024] [Indexed: 07/09/2024] Open
Abstract
Improving feed utilization is a vital strategy to meet the growing global demand for meat and promote sustainable food production. Over the past few decades, significant improvements in the feed intake (FI) and feed utilization efficiency of broilers have been achieved through advanced breeding procedures, although dynamic changes in FI and their effects on the feed conversion ratio (FCR) have remained unclear. In this study, we measured individual weekly FI and body weight of 274 male broilers to characterize the dynamic FI patterns and investigate their relationship with growth performance. The broilers were from 2 purebred lines and their crossbreed and measurements were collected from 4 to 6 wk of age. Overall, a continuous increase in the weekly FI occurred from 4 to 6 wk of age, whereas the body weight gain (BWG) reached an inflection point in wk 5. The dynamic change in weekly FI was observed to follow 3 distinct FI patterns: pattern 1, a continuous weekly increase in FI; pattern 2, an increase followed by a plateau; pattern 3, an increase followed by a decrease. The prevalence of these patterns was similar in the purebred and crossbred populations: pattern 2 was most frequent, followed by a moderate proportion of pattern 1, and the lowest proportion of pattern 3. Broilers following pattern 1 displayed significantly better growth performance and feed utilization efficiency than those following pattern 3, emphasizing the importance of maintaining good appetite in the last stage of broiler production. In summary, this study has characterized the dynamic patterns of FI and their association with growth performance. Our results offer a new foundation for improving feed utilization efficiency and investigating feeding regulation in broilers.
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Affiliation(s)
- Yuchen Jie
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Chaoliang Wen
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Sanya Institute of China Agricultural University, Hainan, 572025, China
| | - Qiang Huang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shuang Gu
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Congjiao Sun
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Sanya Institute of China Agricultural University, Hainan, 572025, China
| | - Guangqi Li
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Yiyuan Yan
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Guiqin Wu
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Ning Yang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Sanya Institute of China Agricultural University, Hainan, 572025, China.
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3
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Liu H, Zhu C, Wang Y, Wang Z, Zou K, Song W, Tao Z, Xu W, Zhang S, Wang Z, Li H. Effects of residual feed intake on the economic traits of fast-growing meat ducks. Poult Sci 2024; 103:103879. [PMID: 38833748 PMCID: PMC11190701 DOI: 10.1016/j.psj.2024.103879] [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: 03/21/2024] [Revised: 05/12/2024] [Accepted: 05/14/2024] [Indexed: 06/06/2024] Open
Abstract
Feed efficiency (FE) is a crucial economic indicator of meat duck production. The objective of this study was to assess the impact of residual feed intake (RFI), defined as the difference between the actual and expected feed intake based on animal's production and maintenance requirements, on the growth performance (GP), slaughter and internal organ characteristics of fast-growing meat ducks. In total, 1,300 healthy 14-day-old male fast-growing meat ducks were housed in individual cages until slaughter at the age of 35 d. The characteristics of the carcass and internal organs of 30 ducks with the highest RFI (HRFI) and the lowest RFI (LRFI) were respectively determined. RFI, the feed conversion ratio (FCR), and average day feed intake (ADFI) were significantly lower in the LRFI group than the HRFI group (P < 0.001), while there were no significant differences in marketing BW or BW gain (BWG) (P > 0.05). The thigh muscle and lean meat yields were higher, and the abdominal fat content was lower (P < 0.001) in the LRFI group, while there were no significant differences in other carcass traits between the groups (P > 0.05). The liver and gizzard yields were significantly higher (P < 0.001) in the LRFI group, while there were no significant differences (P > 0.05) in intestinal length between the groups. RFI was highly positively correlate with FCR and ADFI (P < 0.01), but negatively correlated the yields of thigh muscle, lean meat, liver, and gizzard, and positively correlated with abdominal fat content. These results indicate that selection for low RFI could improve the FE of fast-growing meat ducks without affecting the marketing BW and BWG, while increasing yields of thigh muscle and lean meat and reducing abdominal fat content. These findings offer useful insights into the biological processes that influence FE of fast-growing meat ducks.
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Affiliation(s)
- Hongxiang Liu
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Chunhong Zhu
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Yifei Wang
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Zhen Wang
- Shandong Hekangyuan Group Co., Ltd, Jinan, 250000, China
| | - Kexin Zou
- Shandong Hekangyuan Group Co., Ltd, Jinan, 250000, China
| | - Weitao Song
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Zhiyun Tao
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Wenjuan Xu
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Shuangjie Zhang
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Zhicheng Wang
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China
| | - Huifang Li
- Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China.
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Yang C, Dong B, Chen A, Jiang Y, Bai H, Chen G, Chang G, Wang Z. Metagenomic insights into the relationship between intestinal flora and residual feed intake of meat ducks. Poult Sci 2024; 103:103836. [PMID: 38776859 PMCID: PMC11141266 DOI: 10.1016/j.psj.2024.103836] [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: 03/30/2024] [Revised: 04/23/2024] [Accepted: 05/03/2024] [Indexed: 05/25/2024] Open
Abstract
In this study, we sought to determine the effects of intestinal flora on the feed efficiency of meat ducks by evaluating the correlation between intestinal flora and residual feed intake. The F2 generation of Cherry Valley ducks × Runzhou Crested White ducks was used as the study subjects, and feed consumption being recorded from d 21 to 42. RFI was calculated based on growth performance, and 20 low RFI and 20 high RFI ducks were randomly selected to characterize the effect of RFI on growth performance. To analyze the intestinal flora affecting RFI, 16s rDNA sequencing was performed on the contents of 5 intestinal segments from the HR and LR groups, and macrogenomic sequencing was performed on the cecal contents. Feed intake, average daily feed intake, feed conversion ratio, and residual feed intake were lower in low RFI. Analysis of the intestinal flora revealed the cecum to be more highly enriched in the carbohydrate metabolism pathway and less enriched with potentially pathogenic taxa than the other assessed intestinal regions. Further analysis of the cecal microbiota identified nine significantly differentially enriched intestinal flora. In this study, we accordingly identified a basis for the mechanisms underlying the effects of the intestinal flora on meat duck feed efficiency.
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Affiliation(s)
- Chunyan Yang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China
| | - Bingqiang Dong
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China
| | - Anqi Chen
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China
| | - Yong Jiang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China
| | - Hao Bai
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou, China
| | - Guohong Chen
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou, China
| | - Guobin Chang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou, China
| | - Zhixiu Wang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou, China.
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Wang XG, Shen MM, Lu J, Dou TC, Ma M, Guo J, Wang KH, Qu L. Genome-wide association analysis of eggshell color of an F2 generation population reveals candidate genes in chickens. Animal 2024; 18:101167. [PMID: 38762993 DOI: 10.1016/j.animal.2024.101167] [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: 10/26/2023] [Revised: 04/11/2024] [Accepted: 04/12/2024] [Indexed: 05/21/2024] Open
Abstract
Eggshell color is an important visual characteristic that affects consumer preferences for eggs. Eggshell color, which has moderate to high heritability, can be effectively enhanced through molecular marker selection. Various studies have been conducted on eggshell color at specific time points. However, few longitudinal data are available on eggshell color. Therefore, the objective of this study was to investigate eggshell color using the Commission International de L'Eclairage L*a*b* system with multiple measurements at different ages (age at the first egg and at 32, 36, 40, 44, 48, 52, 56, 60, 66, and 72 weeks) within the same individuals from an F2 resource population produced by crossing White Leghorn and Dongxiang Blue chicken. Using an Affymetrix 600 single nucleotide polymorphism (SNP) array, we estimated the genetic parameters of the eggshell color trait, performed genome-wide association studies (GWASs), and screened for the potential candidate genes. The results showed that pink-shelled eggs displayed a significant negative correlation between L* values and both a* and b* values. Genetic heritability based on SNPs showed that the heritability of L*, a*, and b* values ranged from 0.32 to 0.82 for pink-shelled eggs, indicating a moderate to high level of genetic control. The genetic correlations at each time point were mostly above 0.5. The major-effect regions affecting the pink eggshell color were identified in the 10.3-13.0 Mb interval on Gallus gallus chromosome 20, and candidate genes were selected, including SLC35C2, PCIF1, and SLC12A5. Minor effect polygenic regions were identified on chromosomes 1, 6, 9, 12, and 15, revealing 11 candidate genes, including MTMR3 and SLC35E4. Members of the solute carrier family play an important role in influencing eggshell color. Overall, our findings provide valuable insights into the phenotypic and genetic aspects underlying the variation in eggshell color. Using GWAS analysis, we identified multiple quantitative trait loci (QTLs) for pink eggshell color, including a major QTL on chromosome 20. Genetic variants associated with eggshell color may be used in genomic breeding programs.
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Affiliation(s)
- X G Wang
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - M M Shen
- Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China
| | - J Lu
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - T C Dou
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - M Ma
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - J Guo
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - K H Wang
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China
| | - L Qu
- Jiangsu Institute of Poultry Science, Yangzhou 225125, China.
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Yuan J, Zhao J, Sun Y, Wang Y, Li Y, Ni A, Zong Y, Ma H, Wang P, Shi L, Chen J. The mRNA-lncRNA landscape of multiple tissues uncovers key regulators and molecular pathways that underlie heterosis for feed intake and efficiency in laying chickens. Genet Sel Evol 2023; 55:69. [PMID: 37803296 PMCID: PMC10559425 DOI: 10.1186/s12711-023-00834-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 08/24/2023] [Indexed: 10/08/2023] Open
Abstract
BACKGROUND Heterosis is routinely exploited to improve animal performance. However, heterosis and its underlying molecular mechanism for feed intake and efficiency have been rarely explored in chickens. Feed efficiency continues to be an important breeding goal trait since feed accounts for 60 to 70% of the total production costs in poultry. Here, we profiled the mRNA-lncRNA landscape of 96 samples of the hypothalamus, liver and duodenum mucosa from White Leghorn (WL), Beijing-You chicken (YY), and their reciprocal crosses (WY and YW) to elucidate the regulatory mechanisms of heterosis. RESULTS We observed negative heterosis for both feed intake and residual feed intake (RFI) in YW during the laying period from 43 to 46 weeks of age. Analysis of the global expression pattern showed that non-additivity was a major component of the inheritance of gene expression in the three tissues for YW but not for WY. The YW-specific non-additively expressed genes (YWG) and lncRNA (YWL) dominated the total number of non-additively expressed genes and lncRNA in the hypothalamus and duodenum mucosa. Enrichment analysis of YWG showed that mitochondria components and oxidation phosphorylation (OXPHOS) pathways were shared among the three tissues. The OXPHOS pathway was enriched by target genes for YWL with non-additive inheritance of expression in the liver and duodenum mucosa. Weighted gene co-expression network analysis revealed divergent co-expression modules associated with feed intake and RFI in the three tissues from WL, YW, and YY. Among the negatively related modules, the OXPHOS pathway was enriched by hub genes in the three tissues, which supports the critical role of oxidative phosphorylation. Furthermore, protein quantification of ATP5I was highly consistent with ATP5I expression in the liver, which suggests that, in crossbred YW, non-additive gene expression is down-regulated and decreases ATP production through oxidative phosphorylation, resulting in negative heterosis for feed intake and efficiency. CONCLUSIONS Our results demonstrate that non-additively expressed genes and lncRNA involved in oxidative phosphorylation in the hypothalamus, liver, and duodenum mucosa are key regulators of the negative heterosis for feed intake and RFI in layer chickens. These findings should facilitate the rational choice of suitable parents for producing crossbred chickens.
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Affiliation(s)
- Jingwei Yuan
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jinmeng Zhao
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Yanyan Sun
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Yuanmei Wang
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Yunlei Li
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Aixin Ni
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Yunhe Zong
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Hui Ma
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Panlin Wang
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Lei Shi
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jilan Chen
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
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7
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Pan Z, Wang Y, Wang M, Wang Y, Zhu X, Gu S, Zhong C, An L, Shan M, Damas J, Halstead MM, Guan D, Trakooljul N, Wimmers K, Bi Y, Wu S, Delany ME, Bai X, Cheng HH, Sun C, Yang N, Hu X, Lewin HA, Fang L, Zhou H. An atlas of regulatory elements in chicken: A resource for chicken genetics and genomics. SCIENCE ADVANCES 2023; 9:eade1204. [PMID: 37134160 PMCID: PMC10156120 DOI: 10.1126/sciadv.ade1204] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
A comprehensive characterization of regulatory elements in the chicken genome across tissues will have substantial impacts on both fundamental and applied research. Here, we systematically identified and characterized regulatory elements in the chicken genome by integrating 377 genome-wide sequencing datasets from 23 adult tissues. In total, we annotated 1.57 million regulatory elements, representing 15 distinct chromatin states, and predicted about 1.2 million enhancer-gene pairs and 7662 super-enhancers. This functional annotation of the chicken genome should have wide utility on identifying regulatory elements accounting for gene regulation underlying domestication, selection, and complex trait regulation, which we explored. In short, this comprehensive atlas of regulatory elements provides the scientific community with a valuable resource for chicken genetics and genomics.
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Affiliation(s)
- Zhangyuan Pan
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ying Wang
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mingshan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650000, China
| | - Yuzhe Wang
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100193, China
| | - Xiaoning Zhu
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100193, China
| | - Shenwen Gu
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Conghao Zhong
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Liqi An
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mingzhu Shan
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Joana Damas
- The Genome Center, University of California, Davis, CA 95616, USA
| | - Michelle M Halstead
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Dailu Guan
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Nares Trakooljul
- Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Klaus Wimmers
- Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
- Faculty of Agricultural and Environmental Sciences, University Rostock, Rostock, Germany
| | - Ye Bi
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Shang Wu
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mary E Delany
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Xuechen Bai
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Hans H Cheng
- USDA-ARS, Avian Disease and Oncology Laboratory, East Lansing, MI 48823, USA
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Xiaoxiang Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650000, China
| | - Harris A Lewin
- The Genome Center, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, DK
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
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Zhou Q, Lan F, Gu S, Li G, Wu G, Yan Y, Li X, Jin J, Wen C, Sun C, Yang N. Genetic and microbiome analysis of feed efficiency in laying hens. Poult Sci 2022; 102:102393. [PMID: 36805401 PMCID: PMC9958098 DOI: 10.1016/j.psj.2022.102393] [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: 08/03/2022] [Revised: 12/01/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Improving feed efficiency is an important target for poultry breeding. Feed efficiency is affected by host genetics and the gut microbiota, but many of the mechanisms remain elusive in laying hens, especially in the late laying period. In this study, we measured feed intake, body weight, and egg mass of 714 hens from a pedigreed line from 69 to 72 wk of age and calculated the residual feed intake (RFI) and feed conversion ratio (FCR). In addition, fecal samples were also collected for 16S ribosomal RNA gene sequencing (V4 region). Genetic analysis was then conducted in DMU packages by using AI-REML with animal model. Moderate heritability estimates for FCR (h2 = 0.31) and RFI (h2 = 0.52) were observed, suggesting that proper selection programs can directly improve feed efficiency. Genetically, RFI was less correlated with body weight and egg mass than that of FCR. The phenotypic variance explained by gut microbial variance is defined as the microbiability (m2). The microbiability estimates for FCR (m2 = 0.03) and RFI (m2 = 0.16) suggested the gut microbiota was also involved in the regulation of feed efficiency. In addition, our results showed that the effect of host genetics on fecal microbiota was minor in three aspects: 1) microbial diversity indexes had low heritability estimates, and genera with heritability estimates more than 0.1 accounted for only 1.07% of the tested fecal microbiota; 2) the genetic relationship correlations between host genetics and different microbial distance were very weak, ranging from -0.0057 to -0.0003; 3) the microbial distance between different kinships showed no significant difference. Since the RFI has the highest microbiability, we further screened out three genera, including Anaerosporobacter, Candidatus Stoquefichus, and Fournierella, which were negatively correlated with RFI and played positive roles in improving the feed efficiency. These findings contribute to a great understanding of the genetic background and microbial influences on feed efficiency.
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Affiliation(s)
- Qianqian Zhou
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Fangren Lan
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Shuang Gu
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Guangqi Li
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Guiqin Wu
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Yiyuan Yan
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Xiaochang Li
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Jiaming Jin
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Chaoliang Wen
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China.
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9
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Yu Y, Liu L, Windig J, Bosse M, Groenen MAM, Crooijmans RPMA. Unique genetic signature and selection footprints in Dutch population of German Longhaired Pointer dogs. Anim Genet 2022; 53:829-840. [PMID: 35993291 PMCID: PMC9804189 DOI: 10.1111/age.13253] [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: 08/03/2022] [Revised: 08/03/2022] [Accepted: 08/03/2022] [Indexed: 01/05/2023]
Abstract
The German Longhaired Pointer (GLP) breed is a versatile pointer dog breed. In the current study, we investigated the genetic diversity of these dogs based on SNP array data and compared it to 11 other pointer setter breeds. The results show that GLPs have a relatively low level of inbreeding among these pointer breeds. In addition, with the availability of pedigree information of the GLPs, we demonstrate that the correlation between pedigree-based inbreeding and genotype-based inbreeding coefficients was high (R = 0.89 and 0.85). By investigating population structure between these 12 pointer setter breeds we showed that GLP is a breed distinct from other pointers and shares common ancestry with a few other pointing breeds. Finally, we identified selection signatures in GLPs using the runs of homozygosity islands method. The most significant runs of homozygosity island was detected on chromosome 30 harboring the genes RYR3, FMN1, and GREM1. The RYR3 gene plays a role in skeletal muscle contraction while the FMN1 and GREM1 genes are involved in limb development. The selection on these three genes could have contributed to the excellent athletic performance of GLPs, which is an extremely important characteristic for this hunting dog.
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Affiliation(s)
- Yun Yu
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
| | - Langqing Liu
- Division of Evolutionary Biology, Faculty of BiologyLudwig‐Maximilians‐Universität (LMU) MünchenPlanegg‐MartinsriedGermany
| | - Jack Windig
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands,Centre for Genetic Resources the NetherlandsWageningen University & ResearchWageningenThe Netherlands
| | - Mirte Bosse
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands,Amsterdam Institute for Life and Environment (A‐Life)Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Martien A. M. Groenen
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
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10
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Jiao Y, Hao L, Xia P, Cheng Y, Song J, Chen X, Wang Z, Ma Z, Zheng S, Chen T, Zhang Y, Yu H. Identification of Potential miRNA-mRNA Regulatory Network Associated with Pig Growth Performance in the Pituitaries of Bama Minipigs and Landrace Pigs. Animals (Basel) 2022; 12:3058. [PMID: 36359184 PMCID: PMC9657654 DOI: 10.3390/ani12213058] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/02/2022] [Accepted: 11/03/2022] [Indexed: 08/27/2023] Open
Abstract
Pig growth performance is one of the criteria for judging pork production and is influenced by genotype and external environmental factors such as feeding conditions. The growth performance of miniature pigs, such as Bama minipigs, differs considerably from that of the larger body size pigs, such as Landrace pigs, and can be regarded as good models in pig growth studies. In this research, we identified differentially expressed genes in the pituitary gland of Bama minipigs and Landrace pigs. Through the pathway enrichment analysis, we screened the growth-related pathways and the genes enriched in the pathways and established the protein-protein interaction network. The RNAHybrid algorithm was used to predict the interaction between differentially expressed microRNAs and differentially expressed mRNAs. Four regulatory pathways (Y-82-ULK1/CDKN1A, miR-4334-5p-STAT3/PIK3R1/RPS6KA3/CAB39L, miR-4331-SCR/BCL2L1, and miR-133a-3p-BCL2L1) were identified via quantitative real-time PCR to detect the expression and correlation of candidate miRNAs and mRNAs. In conclusion, we revealed potential miRNA-mRNA regulatory networks associated with pig growth performance in the pituitary glands of Bama minipigs and Landrace pigs, which may help to elucidate the underlying molecular mechanisms of growth differences in pigs of different body sizes.
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Affiliation(s)
- Yingying Jiao
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Linlin Hao
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Peijun Xia
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Yunyun Cheng
- Ministry of Health Key Laboratory of Radiobiology, College of Public Health, Jilin University, Changchun 130061, China
| | - Jie Song
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Xi Chen
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Zhaoguo Wang
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Ze Ma
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Shuo Zheng
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Ting Chen
- Chinese National Engineering Research Center for Breeding Swine Industry, SCAU-Alltech Research Joint Alliance, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Ying Zhang
- College of Animal Science, Jilin University, Changchun 130061, China
| | - Hao Yu
- College of Animal Science, Jilin University, Changchun 130061, China
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11
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Bai H, Guo Q, Yang B, Dong Z, Li X, Song Q, Jiang Y, Wang Z, Chang G, Chen G. Effects of residual feed intake divergence on growth performance, carcass traits, meat quality, and blood biochemical parameters in small-sized meat ducks. Poult Sci 2022; 101:101990. [PMID: 35841639 PMCID: PMC9289854 DOI: 10.1016/j.psj.2022.101990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/10/2022] [Accepted: 05/29/2022] [Indexed: 11/28/2022] Open
Abstract
Feed efficiency (FE) is a major economic trait of meat duck. This study aimed to evaluate the effects of residual feed intake (RFI) divergence on growth performance, carcass traits, meat quality, and blood biochemical parameters in small-sized meat ducks. A total of 500 healthy 21-day-old male ducks were housed in individual cages until slaughter at 63 d of age. The growth performance was determined for all the ducks. The carcass yield, meat quality, and blood biochemical parameters were determined for the selected 30 high-RFI (HRFI) and 30 low-RFI (LRFI) ducks. In terms of growth performance, the RFI, feed conversion ratio (FCR), and average daily feed intake (ADFI) were found to be significantly lower in the LRFI group (P < 0.01), whereas no differences were observed in the BW and body weight gain (P > 0.05). For slaughter performance, no differences were observed in the carcass traits between the LRFI and HRFI groups (P > 0.05). For meat quality, the shear force of breast muscle was significantly lower in the LRFI group (P < 0.05), while the other meat quality traits of breast and thigh muscles demonstrated no differences (P > 0.05). For blood biochemical parameters, the serum concentrations of triglycerides (TG) and glucose (GLU) were significantly lower in the LRFI group (P < 0.05), while the other parameters showed no differences (P > 0.05). The correlation analysis demonstrated a high positive correlation between RFI, FCR, and ADFI (P < 0.01). The RFI demonstrated a negative effect on the breast muscle and lean meat yields, but a positive effect on the shear force of breast muscle (P < 0.05). Further, the RFI demonstrated a positive effect on the TG and GLU levels (P < 0.05). These results indicate that the selection for low RFI could improve the FE of small-sized meat ducks without affecting the production performance. This study provides valuable insight into the biological processes underlying the variations in FE in small-sized meat ducks.
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Affiliation(s)
- H Bai
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Jiangsu Yangzhou 225009, China
| | - Q Guo
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - B Yang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Z Dong
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - X Li
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Q Song
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Y Jiang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Z Wang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - G Chang
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Jiangsu Yangzhou 225009, China; Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - G Chen
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Jiangsu Yangzhou 225009, China; Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China.
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12
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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.
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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
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13
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Yang R, Xu Z, Wang Q, Zhu D, Bian C, Ren J, Huang Z, Zhu X, Tian Z, Wang Y, Jiang Z, Zhao Y, Zhang D, Li N, Hu X. Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing. Genet Sel Evol 2021; 53:82. [PMID: 34706641 PMCID: PMC8555081 DOI: 10.1186/s12711-021-00672-9] [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: 10/08/2020] [Accepted: 09/08/2021] [Indexed: 12/25/2022] Open
Abstract
Background Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features. Results We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model. Conclusions A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00672-9.
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Affiliation(s)
- Ruifei Yang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China.,College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhenqiang Xu
- Wen's Nanfang Poultry Breeding Co. Ltd, Yunfu, 527400, Guangdong Province, China
| | - Qi Wang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Di Zhu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Cheng Bian
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Jiangli Ren
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Zhuolin Huang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Xiaoning Zhu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Zhixin Tian
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yuzhe Wang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Ziqin Jiang
- Wen's Nanfang Poultry Breeding Co. Ltd, Yunfu, 527400, Guangdong Province, China
| | - Yiqiang Zhao
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Dexiang Zhang
- Wen's Nanfang Poultry Breeding Co. Ltd, Yunfu, 527400, Guangdong Province, China.
| | - Ning Li
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Xiaoxiang Hu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China.
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14
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Barría A, Benzie JAH, Houston RD, De Koning DJ, de Verdal H. Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia ( Oreochromis niloticus) Population. Front Genet 2021; 12:737906. [PMID: 34616434 PMCID: PMC8488396 DOI: 10.3389/fgene.2021.737906] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 08/31/2021] [Indexed: 11/24/2022] Open
Abstract
Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; -0.60 and -0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.
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Affiliation(s)
- Agustin Barría
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Easter Bush, Midlothian, United Kingdom
| | - John A. H. Benzie
- WorldFish, Bayan Lepas, Malaysia
- School of Biological Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Ross D. Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Easter Bush, Midlothian, United Kingdom
| | - Dirk-Jan De Koning
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Hugues de Verdal
- CIRAD, UMR ISEM, Montpellier, France
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
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15
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Tarsani E, Kranis A, Maniatis G, Hager-Theodorides AL, Kominakis A. Detection of loci exhibiting pleiotropic effects on body weight and egg number in female broilers. Sci Rep 2021; 11:7441. [PMID: 33811218 PMCID: PMC8018976 DOI: 10.1038/s41598-021-86817-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 03/16/2021] [Indexed: 12/14/2022] Open
Abstract
The objective of the present study was to discover the genetic variants, functional candidate genes, biological processes and molecular functions underlying the negative genetic correlation observed between body weight (BW) and egg number (EN) traits in female broilers. To this end, first a bivariate genome-wide association and second stepwise conditional-joint analyses were performed using 2586 female broilers and 240 k autosomal SNPs. The aforementioned analyses resulted in a total number of 49 independent cross-phenotype (CP) significant SNPs with 35 independent markers showing antagonistic action i.e., positive effects on one trait and negative effects on the other trait. A number of 33 independent CP SNPs were located within 26 and 14 protein coding and long non-coding RNA genes, respectively. Furthermore, 26 independent markers were situated within 44 reported QTLs, most of them related to growth traits. Investigation of the functional role of protein coding genes via pathway and gene ontology analyses highlighted four candidates (CPEB3, ACVR1, MAST2 and CACNA1H) as most plausible pleiotropic genes for the traits under study. Three candidates (CPEB3, MAST2 and CACNA1H) were associated with antagonistic pleiotropy, while ACVR1 with synergistic pleiotropic action. Current results provide a novel insight into the biological mechanism of the genetic trade-off between growth and reproduction, in broilers.
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Affiliation(s)
- Eirini Tarsani
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece.
| | - Andreas Kranis
- Aviagen, Newbridge, EH28 8SZ, Midlothian, UK
- The Roslin Institute, University of Edinburgh, Midlothian, EH25 9RG, UK
| | | | - Ariadne L Hager-Theodorides
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
| | - Antonios Kominakis
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
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16
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Marchesi JAP, Ono RK, Cantão ME, Ibelli AMG, Peixoto JDO, Moreira GCM, Godoy TF, Coutinho LL, Munari DP, Ledur MC. Exploring the genetic architecture of feed efficiency traits in chickens. Sci Rep 2021; 11:4622. [PMID: 33633287 PMCID: PMC7907133 DOI: 10.1038/s41598-021-84125-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 02/12/2021] [Indexed: 11/09/2022] Open
Abstract
Chicken feed efficiency (FE) traits are the most important economic traits in broiler production. Several studies evaluating genetic factors affecting food consumption in chickens are available. However, most of these studies identified genomic regions containing putative quantitative trait loci for each trait separately. It is still a challenge to find common gene networks related to these traits. Therefore, here, a genome-wide association study (GWAS) was conducted to explore candidate genomic regions responsible for Feed Intake (FI), Body Weight Gain (BWG) and Feed Conversion Ratio (FCR) traits and their gene networks. A total of 1430 broilers from an experimental population was genotyped with the high density Affymetrix 600K SNP array. A total of 119 associated SNPs located in 20 chromosomes were identified, where some of them were common in more than one FE trait. In addition, novel genomic regions were prospected considering the SNPs dominance effects and sex interaction, identifying putative candidate genes only when these effects were fit in the model. Relevant candidate genes such as ATRNL1, PIK3C2A, PTPRN2, SORCS3 and gga-mir-1759 were highlighted in this study helping to elucidate the genomic architecture of feed efficiency traits. These results provide new insights on the mechanisms underlying the consumption and utilization of food in chickens.
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Affiliation(s)
- Jorge Augusto Petroli Marchesi
- Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, 14884-900, Brazil.,Departamento de Genética, Universidade de São Paulo, Ribeirão Preto, SP, 14049-900, Brazil
| | - Rafael Keith Ono
- Embrapa Suínos e Aves, Concórdia, SC, 89715-899, Brazil.,Pamplona Alimentos S/A, Rio do Sul, SC, 89164-900, Brazil
| | | | | | | | - Gabriel Costa Monteiro Moreira
- Departamento de Zootecnia, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, Av. Pádua Dias 11, Piracicaba, SP, 13419-900, Brazil
| | - Thaís Fernanda Godoy
- Departamento de Zootecnia, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, Av. Pádua Dias 11, Piracicaba, SP, 13419-900, Brazil
| | - Luiz Lehmann Coutinho
- Departamento de Zootecnia, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, Av. Pádua Dias 11, Piracicaba, SP, 13419-900, Brazil
| | - Danísio Prado Munari
- Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, 14884-900, Brazil
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17
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Liu Z, Sun C, Yan Y, Li G, Li XC, Wu G, Yang N. Design and evaluation of a custom 50K Infinium SNP array for egg-type chickens. Poult Sci 2021; 100:101044. [PMID: 33743497 PMCID: PMC8010521 DOI: 10.1016/j.psj.2021.101044] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 12/14/2020] [Accepted: 02/04/2021] [Indexed: 11/28/2022] Open
Abstract
With the development of molecular genetics and high-throughput sequencing technology, genotyping arrays consisting of large numbers of SNP have raised great interest in animal and plant research. However, the application of commercial chicken 600K SNP arrays has varied in different populations of egg-type chickens. Moreover, their genotyping cost is too high for large-scale population applications. Herein, we independently developed a custom Illumina 50K BeadChip, named PhenoixChip-I, for egg-type chickens based on SNP from 479 sequenced individuals in 7 lines. We filtered and selected SNP with stringent criteria, such as high polymorphism, genome coverage, design score, and priorities. Finally, a total of 43,681 effective SNP successfully genotyped were included on our custom array. Approximately 14K SNP were previously reported to be associated with important economic traits in egg-type chickens. Subsequently, we verified the applicability and efficiency of the PhenoixChip-I SNP array from many aspects, including evaluating its use scientific research (population structure analysis and genome-wide association study) and the poultry breeding industry (genomic selection). The findings in our study will play a crucial role in accelerating the genetic improvement of egg-type chickens.
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Affiliation(s)
- Zhuang Liu
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yiyuan Yan
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Beijing Engineering Research Centre of Layer, Beijing 101206, China
| | - Guangqi Li
- Beijing Engineering Research Centre of Layer, Beijing 101206, China
| | - Xiao Chang Li
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Guiqin Wu
- Beijing Engineering Research Centre of Layer, Beijing 101206, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
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18
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Li W, Zheng M, Zhao G, Wang J, Liu J, Wang S, Feng F, Liu D, Zhu D, Li Q, Guo L, Guo Y, Liu R, Wen J. Identification of QTL regions and candidate genes for growth and feed efficiency in broilers. Genet Sel Evol 2021; 53:13. [PMID: 33549052 PMCID: PMC7866652 DOI: 10.1186/s12711-021-00608-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 01/26/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Feed accounts for about 70% of the total cost of poultry meat production. Residual feed intake (RFI) has become the preferred measure of feed efficiency because it is phenotypically independent of growth rate and body weight. In this study, our aim was to estimate genetic parameters and identify quantitative trait loci (QTL) for feed efficiency in 3314 purebred broilers using a genome-wide association study. Broilers were genotyped using a custom 55 K single nucleotide polymorphism (SNP) array. RESULTS Estimates of genomic heritability for seven growth and feed efficiency traits, including body weight at 28 days of age (BW28), BW42, average daily feed intake (ADFI), RFI, and RFI adjusted for weight of abdominal fat (RFIa), ranged from 0.12 to 0.26. Eleven genome-wide significant SNPs and 15 suggestively significant SNPs were detected, of which 19 clustered around two genomic regions. A region on chromosome 16 (2.34-2.66 Mb) was associated with both BW28 and BW42, and the most significant SNP in this region, AX_101003762, accounted for 7.6% of the genetic variance of BW28. The other region, on chromosome 1 (91.27-92.43 Mb) was associated with RFI and ADFI, and contains the NSUN3 and EPHA6 as candidate genes. The most significant SNP in this region, AX_172588157, accounted for 4.4% of the genetic variance of RFI. In addition, a genomic region containing the gene AGK on chromosome 1 was found to be associated with RFIa. The NSUN3 and AGK genes were found to be differentially expressed in breast muscle, thigh muscle, and abdominal fat between male broilers with high and low RFI. CONCLUSIONS We identified QTL regions for BW28 and BW42 (spanning 0.32 Mb) and RFI (spanning 1.16 Mb). The NSUN3, EPHA6, and AGK were identified as the most likely candidate genes for these QTL. These genes are involved in mitochondrial function and behavioral regulation. These results contribute to the identification of candidate genes and variants for growth and feed efficiency in poultry.
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Affiliation(s)
- Wei Li
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Maiqing Zheng
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Wang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Shunli Wang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Furong Feng
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan, 528515 China
| | - Dawei Liu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan, 528515 China
| | - Dan Zhu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan, 528515 China
| | - Qinghe Li
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Liping Guo
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Yuming Guo
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Ranran Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Wen
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
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19
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Qu L, Shen MM, Dou TC, Ma M, Lu J, Wang XG, Guo J, Hu YP, Li YF, Wang KH. Genome-wide association studies for mottled eggs in chickens using a high-density single-nucleotide polymorphism array. Animal 2020; 15:100051. [PMID: 33516007 DOI: 10.1016/j.animal.2020.100051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 10/22/2022] Open
Abstract
Mottled eggs in layer chickens are gaining increasing attention because of the economic impact on the egg industry caused by the reduced sale value of commodity eggs. However, the genetic architecture underlying mottled eggs is not well understood. The genetic architecture underlying the mottled egg trait was investigated using genome-wide association studies (GWAS) by high-density arrays, using a total of 407 pink eggs and 799 blue eggs from an F2 resource population generated by crossing Dongxiang Blue-shelled and White Leghorn chickens. The mottled egg score in blue eggs was found to be higher than that in pink eggs. The single-nucleotide polymorphism heritability of mottled egg at laying day and storage for 7 days was 0.18 and 0.20, respectively. Bivariate GWAS provided 29 significant loci, mainly located on GGA2, GGA3, GGA8, GGA10, GGA15, GGA17, and GGA23, affecting mottled egg on laying day. Candidate genes RIMS2, SLC25A32, RIMBP2, VPS13B, and RGS3 were obtained for mottled eggshell by bivariate GWAS and gene annotation. Our findings provide new insights into the genetic architecture of mottled egg in hens, and demonstrate that a genomic selection method would be profitable for breeding out the mottled egg trait.
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Affiliation(s)
- L Qu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - M M Shen
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China; College of Biotechnology, Jiangsu University of Science and Technology, 212003 Zhenjiang, Jiangsu, China
| | - T C Dou
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - M Ma
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - J Lu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - X G Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - J Guo
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - Y P Hu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - Y F Li
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China
| | - K H Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, 225125 Yangzhou, Jiangsu, China.
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20
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Li W, Jing Z, Cheng Y, Wang X, Li D, Han R, Li W, Li G, Sun G, Tian Y, Liu X, Kang X, Li Z. Analysis of four complete linkage sequence variants within a novel lncRNA located in a growth QTL on chromosome 1 related to growth traits in chickens. J Anim Sci 2020; 98:5822640. [PMID: 32309860 DOI: 10.1093/jas/skaa122] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 04/16/2020] [Indexed: 12/18/2022] Open
Abstract
An increasing number of studies have shown that quantitative trait loci (QTLs) at the end of chromosome 1 identified in different chicken breeds and populations exert significant effects on growth traits in chickens. Nevertheless, the causal genes underlying the QTL effect remain poorly understood. Using an updated gene database, a novel lncRNA (named LncFAM) was found at the end of chromosome 1 and located in a growth and digestion QTL. This study showed that the expression level of LncFAM in pancreas tissues with a high weight was significantly higher than that in pancreas tissues with a low weight, which indicates that the expression level of LncFAM was positively correlated with various growth phenotype indexes, such as growth speed and body weight. A polymorphism screening identified four polymorphisms with strong linkage disequilibrium in LncFAM: a 5-bp indel in the second exon, an A/G base mutation, and 7-bp and 97-bp indels in the second intron. A study of a 97-bp insertion in the second intron using an F2 chicken resource population produced by Anka and Gushi chickens showed that the mutant individuals with genotype II had the highest values for body weight (BW) at 0 days and 2, 4, 6, 8, 10 and 12 weeks, shank girth (SG) at 4, 8 and 12 weeks, chest width (CW) at 4, 8 and 12 weeks, body slant length (BSL) at 8 and 12 weeks, and pelvic width (PW) at 4, 8 and 12 weeks, followed by ID and DD genotypes. The amplification and typing of 2,716 chickens from ten different breeds, namely, the F2 chicken resource population, dual-type chickens, including Xichuan black-bone chickens, Lushi green-shell layers, Dongxiang green-shell layers, Changshun green-shell layers, and Gushi chickens, and commercial broilers, including Ross 308, AA, Cobb and Hubbard broilers, revealed that II was the dominant genotype. Interestingly, only genotype II existed among the tested populations of commercial broilers. Moreover, the expression level in the pancreas tissue of Ross 308 chickens was significantly higher than that in the pancreas tissue of Gushi chickens (P < 0.001), which might be related to the conversion rates among different chickens. The prediction and verification of the target gene of LncFAM showed that LncFAM might regulate the expression of its target gene FAM48A through cis-expression. Our results provide useful information on the mutation of LncFAM, which can be used as a potential molecular breeding marker.
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Affiliation(s)
- Wenya Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Zhenzhu Jing
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Yingying Cheng
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China
| | - Xiangnan Wang
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Donghua Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Ruili Han
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Wenting Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Guoxi Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Guirong Sun
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Yadong Tian
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Xiaojun Liu
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Xiangtao Kang
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Zhuanjian Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
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21
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Li W, Liu R, Zheng M, Feng F, Liu D, Guo Y, Zhao G, Wen J. New insights into the associations among feed efficiency, metabolizable efficiency traits and related QTL regions in broiler chickens. J Anim Sci Biotechnol 2020; 11:65. [PMID: 32607230 PMCID: PMC7318453 DOI: 10.1186/s40104-020-00469-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 05/01/2020] [Indexed: 12/30/2022] Open
Abstract
Background Improving the feed efficiency would increase profitability for producers while also reducing the environmental footprint of livestock production. This study was conducted to investigate the relationships among feed efficiency traits and metabolizable efficiency traits in 180 male broilers. Significant loci and genes affecting the metabolizable efficiency traits were explored with an imputation-based genome-wide association study. The traits measured or calculated comprised three growth traits, five feed efficiency related traits, and nine metabolizable efficiency traits. Results The residual feed intake (RFI) showed moderate to high and positive phenotypic correlations with eight other traits measured, including average daily feed intake (ADFI), dry excreta weight (DEW), gross energy excretion (GEE), crude protein excretion (CPE), metabolizable dry matter (MDM), nitrogen corrected apparent metabolizable energy (AMEn), abdominal fat weight (AbF), and percentage of abdominal fat (AbP). Greater correlations were observed between growth traits and the feed conversion ratio (FCR) than RFI. In addition, the RFI, FCR, ADFI, DEW, GEE, CPE, MDM, AMEn, AbF, and AbP were lower in low-RFI birds than high-RFI birds (P < 0.01 or P < 0.05), whereas the coefficients of MDM and MCP of low-RFI birds were greater than those of high-RFI birds (P < 0.01). Five narrow QTLs for metabolizable efficiency traits were detected, including one 82.46-kb region for DEW and GEE on Gallus gallus chromosome (GGA) 26, one 120.13-kb region for MDM and AMEn on GGA1, one 691.25-kb region for the coefficients of MDM and AMEn on GGA5, one region for the coefficients of MDM and MCP on GGA2 (103.45–103.53 Mb), and one 690.50-kb region for the coefficient of MCP on GGA14. Linkage disequilibrium (LD) analysis indicated that the five regions contained high LD blocks, as well as the genes chromosome 26 C6orf106 homolog (C26H6orf106), LOC396098, SH3 and multiple ankyrin repeat domains 2 (SHANK2), ETS homologous factor (EHF), and histamine receptor H3-like (HRH3L), which are known to be involved in the regulation of neurodevelopment, cell proliferation and differentiation, and food intake. Conclusions Selection for low RFI significantly decreased chicken feed intake, excreta output, and abdominal fat deposition, and increased nutrient digestibility without changing the weight gain. Five novel QTL regions involved in the control of metabolizable efficiency in chickens were identified. These results, combined through nutritional and genetic approaches, should facilitate novel insights into improving feed efficiency in poultry and other species.
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Affiliation(s)
- Wei Li
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China.,College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Ranran Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Maiqing Zheng
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Furong Feng
- Foshan Gaoming Xinguang Agricultural and animal Industrials Corporation, Foshan, 528515 China
| | - Dawei Liu
- Foshan Gaoming Xinguang Agricultural and animal Industrials Corporation, Foshan, 528515 China
| | - Yuming Guo
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Wen
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
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22
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Ye S, Chen ZT, Zheng R, Diao S, Teng J, Yuan X, Zhang H, Chen Z, Zhang X, Li J, Zhang Z. New Insights From Imputed Whole-Genome Sequence-Based Genome-Wide Association Analysis and Transcriptome Analysis: The Genetic Mechanisms Underlying Residual Feed Intake in Chickens. Front Genet 2020; 11:243. [PMID: 32318090 PMCID: PMC7147382 DOI: 10.3389/fgene.2020.00243] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 02/28/2020] [Indexed: 12/26/2022] Open
Abstract
Poultry feed constitutes the largest cost in poultry production, estimated to be up to 70% of the total cost. Moreover, there is pressure on the poultry industry to increase production to meet the protein demand of humans and simultaneously reduce emissions to protect the environment. Therefore, improving feed efficiency plays an important role to improve profits and the environmental footprint in broiler production. In this study, using imputed whole-genome sequencing data, genome-wide association analysis (GWAS) was performed to identify single-nucleotide polymorphisms (SNPs) and genes associated with residual feed intake (RFI) and its component traits. Furthermore, a transcriptomic analysis between the high-RFI and the low-RFI groups was performed to validate the candidate genes from GWAS. The results showed that the heritability estimates of average daily gain (ADG), average daily feed intake (ADFI), and RFI were 0.29 (0.004), 0.37 (0.005), and 0.38 (0.004), respectively. Using imputed sequence-based GWAS, we identified seven significant SNPs and five candidate genes [MTSS I-BAR domain containing 1, folliculin, COP9 signalosome subunit 3, 5′,3′-nucleotidase (mitochondrial), and gametocyte-specific factor 1] associated with RFI, 20 significant SNPs and one candidate gene (inositol polyphosphate multikinase) associated with ADG, and one significant SNP and one candidate gene (coatomer protein complex subunit alpha) associated with ADFI. After performing a transcriptomic analysis between the high-RFI and the low-RFI groups, both 38 up-regulated and 26 down-regulated genes were identified in the high-RFI group. Furthermore, integrating regional conditional GWAS and transcriptome analysis, ras-related dexamethasone induced 1 was the only overlapped gene associated with RFI, which also suggested that the region (GGA14: 4767015–4882318) is a new quantitative trait locus associated with RFI. In conclusion, using imputed sequence-based GWAS is an efficient method to identify significant SNPs and candidate genes in chicken. Our results provide valuable insights into the genetic mechanisms of RFI and its component traits, which would further improve the genetic gain of feed efficiency rapidly and cost-effectively in the context of marker-assisted breeding selection.
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Affiliation(s)
- Shaopan Ye
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zi-Tao Chen
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Rongrong Zheng
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Shuqi Diao
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Jinyan Teng
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Xiaolong Yuan
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Hao Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zanmou Chen
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Xiquan Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Jiaqi Li
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China
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23
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Ramayo-Caldas Y, Mármol-Sánchez E, Ballester M, Sánchez JP, González-Prendes R, Amills M, Quintanilla R. Integrating genome-wide co-association and gene expression to identify putative regulators and predictors of feed efficiency in pigs. Genet Sel Evol 2019; 51:48. [PMID: 31477014 PMCID: PMC6721172 DOI: 10.1186/s12711-019-0490-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 08/19/2019] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Feed efficiency (FE) has a major impact on the economic sustainability of pig production. We used a systems-based approach that integrates single nucleotide polymorphism (SNP) co-association and gene-expression data to identify candidate genes, biological pathways, and potential predictors of FE in a Duroc pig population. RESULTS We applied an association weight matrix (AWM) approach to analyse the results from genome-wide association studies (GWAS) for nine FE associated and production traits using 31K SNPs by defining residual feed intake (RFI) as the target phenotype. The resulting co-association network was formed by 829 SNPs. Additive effects of this SNP panel explained 61% of the phenotypic variance of RFI, and the resulting phenotype prediction accuracy estimated by cross-validation was 0.65 (vs. 0.20 using pedigree-based best linear unbiased prediction and 0.12 using the 31K SNPs). Sixty-eight transcription factor (TF) genes were identified in the co-association network; based on the lossless approach, the putative main regulators were COPS5, GTF2H5, RUNX1, HDAC4, ESR1, USP16, SMARCA2 and GTF2F2. Furthermore, gene expression data of the gluteus medius muscle was explored through differential expression and multivariate analyses. A list of candidate genes showing functional and/or structural associations with FE was elaborated based on results from both AWM and gene expression analyses, and included the aforementioned TF genes and other ones that have key roles in metabolism, e.g. ESRRG, RXRG, PPARGC1A, TCF7L2, LHX4, MAML2, NFATC3, NFKBIZ, TCEA1, CDCA7L, LZTFL1 or CBFB. The most enriched biological pathways in this list were associated with behaviour, immunity, nervous system, and neurotransmitters, including melatonin, glutamate receptor, and gustation pathways. Finally, an expression GWAS allowed identifying 269 SNPs associated with the candidate genes' expression (eSNPs). Addition of these eSNPs to the AWM panel of 829 SNPs did not improve the accuracy of genomic predictions. CONCLUSIONS Candidate genes that have a direct or indirect effect on FE-related traits belong to various biological processes that are mainly related to immunity, behaviour, energy metabolism, and the nervous system. The pituitary gland, hypothalamus and thyroid axis, and estrogen signalling play fundamental roles in the regulation of FE in pigs. The 829 selected SNPs explained 61% of the phenotypic variance of RFI, which constitutes a promising perspective for applying genetic selection on FE relying on molecular-based prediction.
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Affiliation(s)
- Yuliaxis Ramayo-Caldas
- 0000 0001 1943 6646grid.8581.4Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
| | - Emilio Mármol-Sánchez
- grid.7080.fDepartment of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSCIC-IRTA-UAB-UB, Campus de LA Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
| | - Maria Ballester
- 0000 0001 1943 6646grid.8581.4Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
| | - Juan Pablo Sánchez
- 0000 0001 1943 6646grid.8581.4Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
| | - Rayner González-Prendes
- grid.7080.fDepartment of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSCIC-IRTA-UAB-UB, Campus de LA Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
| | - Marcel Amills
- grid.7080.fDepartment of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSCIC-IRTA-UAB-UB, Campus de LA Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
- grid.7080.fDepartament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
| | - Raquel Quintanilla
- 0000 0001 1943 6646grid.8581.4Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
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24
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Tarsani E, Kranis A, Maniatis G, Avendano S, Hager-Theodorides AL, Kominakis A. Discovery and characterization of functional modules associated with body weight in broilers. Sci Rep 2019; 9:9125. [PMID: 31235723 PMCID: PMC6591351 DOI: 10.1038/s41598-019-45520-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 06/04/2019] [Indexed: 12/31/2022] Open
Abstract
Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes (GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.
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Affiliation(s)
- Eirini Tarsani
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece.
| | - Andreas Kranis
- Aviagen Ltd., Newbridge, Midlothian, EH28 8SZ, UK.,The Roslin Institute, University of Edinburgh, EH25 9RG, Midlothian, United Kingdom
| | | | | | - Ariadne L Hager-Theodorides
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
| | - Antonios Kominakis
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
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25
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Fathi MM, Al-Homidan I, Ebeid TA, Galal A, Abou-Emera OK. Assessment of Residual Feed Intake and Its Relevant Measurements in Two Varieties of Japanese Quails (Coturnixcoturnix japonica) under High Environmental Temperature. Animals (Basel) 2019; 9:ani9060299. [PMID: 31151298 PMCID: PMC6617549 DOI: 10.3390/ani9060299] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Revised: 05/21/2019] [Accepted: 05/22/2019] [Indexed: 11/16/2022] Open
Abstract
Three hundred and ten 12-week-old laying Japanese quails (Coturnixcoturnix japonica) from gray and white varieties (155 each) were randomly selected from the initial population and kept in individual battery cages. The measurements of growth and egg production were determined to derive residual feed intake (RFI). The relationship between RFI and egg quality, blood parameters, and carcass characteristics was also determined. The results indicated that the gray quails had significantly higher egg mass and lower broken eggs compared to the white quails. A significant increase of eggshell strength and shell percentage was found in eggs produced from gray quails compared to their white counterparts, although their shell thickness means weresimilar. The results of multiple regression analysis clearly identified a significant effect of metabolic body weight and egg mass for the computation of expected feed intake, rather than body weight gain, in both varieties of Japanese quails. A strong positive correlation between RFI and feed intake in both gray and white quail varieties was found. The same trend was also observed for feed conversion ratio (FCR). Therefore, including RFI in the selection criteria of Japanese quails in order to improve FCR under high environmental temperature is highly recommended.
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Affiliation(s)
- Moataz M Fathi
- Department of Animal Production and Breeding, College of Agriculture and Veterinary Medicine, Qassim University, Al-Qassim 51452, Saudi Arabia.
- Department of Poultry Production, Faculty of Agriculture, Ain Shams University, HadayekShoubra 11241, Cairo, Egypt.
| | - Ibrahim Al-Homidan
- Department of Animal Production and Breeding, College of Agriculture and Veterinary Medicine, Qassim University, Al-Qassim 51452, Saudi Arabia.
| | - Tarek A Ebeid
- Department of Animal Production and Breeding, College of Agriculture and Veterinary Medicine, Qassim University, Al-Qassim 51452, Saudi Arabia.
- Department of Poultry Production, Faculty of Agriculture, Kafrelsheikh University, 33516 Kafr El-Sheikh, Egypt.
| | - Ahmed Galal
- Department of Poultry Production, Faculty of Agriculture, Ain Shams University, HadayekShoubra 11241, Cairo, Egypt.
| | - Osama K Abou-Emera
- Department of Animal Production and Breeding, College of Agriculture and Veterinary Medicine, Qassim University, Al-Qassim 51452, Saudi Arabia.
- Animal Production Research Institute, Agriculture Research Center, Dokki 12618, Giza, Egypt.
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26
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Allais S, Hennequet-Antier C, Berri C, Salles L, Demeure O, Le Bihan-Duval E. Mapping of QTL for chicken body weight, carcass composition, and meat quality traits in a slow-growing line. Poult Sci 2019; 98:1960-1967. [PMID: 30535096 DOI: 10.3382/ps/pey549] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 11/09/2018] [Indexed: 01/28/2023] Open
Abstract
Slow-growing chicken lines are valuable genetic resources for the development of well-perceived alternative free-range production. While there is no constraint on increasing growth rate, breeding programs have to evolve in order to include new traits improving the positioning of such lines in the growing market for parts and processed products. In this study, we used dense genotyping to fine map QTL for chicken growth, body composition, and meat quality traits in view of developing new tools for selection of a slow-growing line. The dataset included a total of 836 birds (10 sires, 87 dams, 739 descendants) and 40,203 SNP. QTL for the 15 traits analyzed were detected by 3 different methods, i.e., linkage and linkage disequilibrium haplotype-based analysis (LDLA), family-based single marker association (FASTA), and Bayesian multi-marker regression (Bayes Cπ). After filtering for QTL redundancy, we found 16, 16, and 9 QTL when using the FASTA, LDLA, and Bayes Cπ methods, respectively, with a threshold of 2.49 × 10-5 for FASTA and LDLA, and a Bayes factor of 150 for the Bayes Cπ analysis. They comprised 17 QTL for body weight, 9 QTL for body composition, and 15 QTL for breast meat quality or behavior at slaughter. The 3 methods agreed in the detection of highly significant QTL such as that detected on GGA24 for body weight at 3, 6, and 9 wk, and the 2 QTL detected on GGA17 and GGA18 for breast meat yield. Several significant QTL were also detected for the different components of breast meat quality. This study provided new locations for investigation in order to improve our understanding of the genetic architecture of growth, carcass composition, and meat quality in the chicken and to develop molecular tools for the selection of these traits in a slow-growing line.
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Affiliation(s)
- S Allais
- PEGASE, Agrocampus Ouest, INRA, 35590 Saint-Gilles, France
| | | | - C Berri
- BOA, INRA, Université de Tours, 37380 Nouzilly, France
| | | | - O Demeure
- PEGASE, Agrocampus Ouest, INRA, 35590 Saint-Gilles, France
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27
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Bidirectional Selection for Body Weight on Standing Genetic Variation in a Chicken Model. G3-GENES GENOMES GENETICS 2019; 9:1165-1173. [PMID: 30737239 PMCID: PMC6469407 DOI: 10.1534/g3.119.400038] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Experimental populations of model organisms provide valuable opportunities to unravel the genomic impact of selection in a controlled system. The Virginia body weight chicken lines represent a unique resource to investigate signatures of selection in a system where long-term, single-trait, bidirectional selection has been carried out for more than 60 generations. At 55 generations of divergent selection, earlier analyses of pooled genome resequencing data from these lines revealed that 14.2% of the genome showed extreme differentiation between the selected lines, contained within 395 genomic regions. Here, we report more detailed analyses of these data exploring the regions displaying within- and between-line genomic signatures of the bidirectional selection applied in these lines. Despite the strict selection regime for opposite extremes in body weight, this did not result in opposite genomic signatures between the lines. The lines often displayed a duality of the sweep signatures, where an extended region of homozygosity in one line, in contrast to mosaic pattern of heterozygosity in the other line. These haplotype mosaics consisted of short, distinct haploblocks of variable between-line divergence, likely the results of a complex demographic history involving bottlenecks, introgressions and moderate inbreeding. We demonstrate this using the example of complex haplotype mosaicism in the growth1 QTL. These mosaics represent the standing genetic variation available at the onset of selection in the founder population. Selection on standing genetic variation can thus result in different signatures depending on the intensity and direction of selection.
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28
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Kudinov AA, Dementieva NV, Mitrofanova OV, Stanishevskaya OI, Fedorova ES, Larkina TA, Mishina AI, Plemyashov KV, Griffin DK, Romanov MN. Genome-wide association studies targeting the yield of extraembryonic fluid and production traits in Russian White chickens. BMC Genomics 2019; 20:270. [PMID: 30947682 PMCID: PMC6449956 DOI: 10.1186/s12864-019-5605-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 03/13/2019] [Indexed: 01/09/2023] Open
Abstract
Background The Russian White is a gene pool breed, registered in 1953 after crossing White Leghorns with local populations and, for 50 years, selected for cold tolerance and high egg production (EL). The breed has great potential in meeting demands of local food producers, commercial farmers and biotechnology sector of specific pathogen-free (SPF) eggs, the former valuing the breed for its egg weight (EW), EL, age at first egg (AFE), body weight (BW), and the latter for its yield of extraembryonic fluid (YEF) in 12.5-day embryos, ratio of extraembryonic fluid to egg weight, and embryo mass. Moreover, its cold tolerance has been presumably associated with day-old chick down colour (DOCDC) – white rather than yellow, the genetic basis of these traits being however poorly understood. Results We undertook genome-wide association studies (GWASs) for eight performance traits using single nucleotide polymorphism (SNP) genotyping of 146 birds and an Illumina 60KBeadChip. Several suggestive associations (p < 5.16*10− 5) were found for YEF, AFE, BW and EW. Moreover, on chromosome 2, an association with the white DOCDC was found where there is an linkage disequilibrium block of SNPs including genes that are responsible not for colour, but for immune resistance. Conclusions The obtained GWAS data can be used to explore the genetics of immunity and carry out selection for increasing YEF for SPF eggs production. Electronic supplementary material The online version of this article (10.1186/s12864-019-5605-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrei A Kudinov
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia.,University of Helsinki, FI-00014, Helsinki, Finland
| | - Natalia V Dementieva
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Olga V Mitrofanova
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Olga I Stanishevskaya
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Elena S Fedorova
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Tatiana A Larkina
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Arina I Mishina
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Kirill V Plemyashov
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia
| | - Darren K Griffin
- School of Biosciences, University of Kent, Canterbury, Kent, CT2 7NJ, UK.
| | - Michael N Romanov
- Russian Research Institute of Farm Animal Genetics and Breeding Branch of the L. K. Ernst Federal Science Centre for Animal Husbandry, Pushkin, St Petersburg, 196601, Russia.,School of Biosciences, University of Kent, Canterbury, Kent, CT2 7NJ, UK
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29
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Qu L, Shen M, Guo J, Wang X, Dou T, Hu Y, Li Y, Ma M, Wang K, Liu H. Identification of potential genomic regions and candidate genes for egg albumen quality by a genome-wide association study. Arch Anim Breed 2019; 62:113-123. [PMID: 31807621 PMCID: PMC6853030 DOI: 10.5194/aab-62-113-2019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 03/05/2019] [Indexed: 11/17/2022] Open
Abstract
Albumen
quality is a leading economic trait in the chicken industry. Major studies have paid
attention to genetic architecture underlying albumen quality. However, the putative
quantitative trait locus (QTL) for this trait is still unclear. In this genome-wide
association study, we used an F2 resource population to study longitudinal albumen
quality. Seven single-nucleotide polymorphism (SNP) loci were found to be significantly
(p<8.43×10-7) related to albumen quality by univariate analysis,
while 11 SNPs were significantly (p<8.43×10-7) associated with
albumen quality by multivariate analysis. A QTL on GGA4 had a pervasive function on
albumen quality, including a SNP at the missense of NCAPG, and a SNP at the
intergenic region of FGFPB1. It was further found that the putative QTLs at
GGA1, GGA2, and GGA7 had the strongest effects on albumen height (AH) at 32 weeks, Haugh
units (HU) at 44 weeks, and AH at 55 weeks. Moreover, novel SNPs on GGA5 and GGA3 were
associated with AH and HU at 32, 44, and 48 weeks of age. These results confirmed the
regions for egg weight that were detected in a previous study and were similar with QTL
for albumen quality. These results showed that GGA4 had the strongest effect on albumen
quality. Only a few significant loci were detected for most characteristics probably
reflecting the attributes of a pleiotropic gene and a minor-polygene in quantitative
traits.
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Affiliation(s)
- Liang Qu
- College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, China.,Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Manman Shen
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China.,College of Animal Science & Technology, Yangzhou University, Yangzhou, China
| | - Jun Guo
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Xingguo Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Taocun Dou
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Yuping Hu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Yongfeng Li
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Meng Ma
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Kehua Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Honglin Liu
- College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, China
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30
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Genome wide association study of body weight and feed efficiency traits in a commercial broiler chicken population, a re-visitation. Sci Rep 2019; 9:922. [PMID: 30696883 PMCID: PMC6351590 DOI: 10.1038/s41598-018-37216-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 11/29/2018] [Indexed: 01/14/2023] Open
Abstract
Genome wide association study was conducted using a mixed linear model (MLM) approach that accounted for family structure to identify single nucleotide polymorphisms (SNPs) and candidate genes associated with body weight (BW) and feed efficiency (FE) traits in a broiler chicken population. The results of the MLM approach were compared with the results of a general linear model approach that does not take family structure in to account. In total, 11 quantitative trait loci (QTL) and 21 SNPs, were identified to be significantly associated with BW traits and 5 QTL and 5 SNPs were found associated with FE traits using MLM approach. Besides some overlaps between the results of the two GWAS approaches, there are considerable differences in the detected QTL. Even though the genomic inflation factor (λ) values indicate that there is no strong family structure in this population, using models that account for the existing family structure may reduce bias and increase accuracy of the estimated SNP effects in the association analysis. The SNPs and candidate genes identified in this study provide information on the genetic background of BW and FE traits in broiler chickens and might be used as prior information for genomic selection.
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31
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32
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Lillie M, Sheng ZY, Honaker CF, Andersson L, Siegel PB, Carlborg Ö. Genomic signatures of 60 years of bidirectional selection for 8-week body weight in chickens. Poult Sci 2018; 97:781-790. [PMID: 29272516 DOI: 10.3382/ps/pex383] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 11/27/2017] [Indexed: 12/30/2022] Open
Abstract
Sixty years, constituting 60 generations, have passed since the founding of the Virginia body weight lines, an experimental population of White Plymouth Rock chickens. Using a stringent breeding scheme for divergent 8-week body weight, the lines, which originated from a common founder population, have responded to bidirectional selection with an approximate 15-fold difference in the selected trait. They provide a model system to study the genetics of complex traits in general and the influences of artificial selection on quantitative genetic architectures in particular. As we reflect on the 60th anniversary of the initiation of the Virginia body weight lines, there is opportunity to discuss the findings obtained using different analytical and experimental genetic and genomic strategies and integrate them with a recent pooled genome resequencing dataset. Hundreds of regions across the genome show differentiation between the 2 lines, reinforcing previous findings that response to selection relied on standing variation across many genes and giving insights into the haplotype complexity underlying regions associated with body weight.
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Affiliation(s)
- M Lillie
- Department of Medical Biochemistry and Microbiology, Genomics, Uppsala University, Uppsala, Sweden
| | - Z Y Sheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, People's Republic of China
| | - C F Honaker
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg
| | - L Andersson
- Department of Medical Biochemistry and Microbiology, Genomics, Uppsala University, Uppsala, Sweden.,Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.,Department of Veterinary Integrative Biosciences, Texas A&M University, College Station
| | - P B Siegel
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg
| | - Ö Carlborg
- Department of Medical Biochemistry and Microbiology, Genomics, Uppsala University, Uppsala, Sweden
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33
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Dou T, Shen M, Ma M, Qu L, Li Y, Hu Y, Lu J, Guo J, Wang X, Wang K. Genetic architecture and candidate genes detected for chicken internal organ weight with a 600 K single nucleotide polymorphism array. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2018; 32:341-349. [PMID: 30056651 PMCID: PMC6409475 DOI: 10.5713/ajas.18.0274] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 07/23/2018] [Indexed: 12/22/2022]
Abstract
Objective Internal organs indirectly affect economic performance and well-being of animals. Study of internal organs during later layer period will allow full utilization of layer hens. Hence, we conducted a genome-wide association study (GWAS) to identify potential quantitative trait loci or genes that potentially contribute to internal organ weight. Methods A total of 1,512 chickens originating from White Leghorn and Dongxiang Blue-Shelled chickens were genotyped using high-density Affymetrix 600 K single nucleotide polymorphism (SNP) array. We conducted a GWAS, linkage disequilibrium analysis, and heritability estimated based on SNP information by using GEMMA, Haploview and GCTA software. Results Our results displayed that internal organ weights show moderate to high (0.283 to 0.640) heritability. Variance partitioned across chromosomes and chromosome lengths had a linear relationship for liver weight and gizzard weight (R2 = 0.493, 0.753). A total of 23 highly significant SNPs that associated with all internal organ weights were mainly located on Gallus gallus autosome (GGA) 1 and GGA4. Six SNPs on GGA2 affected heart weight. After the final analysis, five top SNPs were in or near genes 5-Hydroxytryptamine receptor 2A, general transcription factor IIF polypeptide 2, WD repeat and FYVE domain containing 2, non-SMC condensin I complex subunit G, and sonic hedgehog, which were considered as candidate genes having a pervasive role in internal organ weights. Conclusion Our findings provide an understanding of the underlying genetic architecture of internal organs and are beneficial in the selection of chickens.
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Affiliation(s)
- Taocun Dou
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Manman Shen
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China.,College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu 225009, China
| | - Meng Ma
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Liang Qu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China.,College of Animal Science and Technology, Nanjing Agriculture University, Nanjing, Jiangsu 210095, China
| | - Yongfeng Li
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Yuping Hu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Jian Lu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Jun Guo
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Xingguo Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
| | - Kehua Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Sciences, Yangzhou, Jiangsu 225216, China
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34
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Rovadoscki GA, Pertile SFN, Alvarenga AB, Cesar ASM, Pértille F, Petrini J, Franzo V, Soares WVB, Morota G, Spangler ML, Pinto LFB, Carvalho GGP, Lanna DPD, Coutinho LL, Mourão GB. Estimates of genomic heritability and genome-wide association study for fatty acids profile in Santa Inês sheep. BMC Genomics 2018; 19:375. [PMID: 29783944 PMCID: PMC5963081 DOI: 10.1186/s12864-018-4777-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Accepted: 05/10/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Despite the health concerns and nutritional importance of fatty acids, there is a relative paucity of studies in the literature that report genetic or genomic parameters, especially in the case of sheep populations. To investigate the genetic architecture of fatty acid composition of sheep, we conducted genome-wide association studies (GWAS) and estimated genomic heritabilities for fatty acid profile in Longissimus dorsi muscle of 216 male sheep. RESULTS Genomic heritability estimates for fatty acid content ranged from 0.25 to 0.46, indicating that substantial genetic variation exists for the evaluated traits. Therefore, it is possible to alter fatty acid profiles through selection. Twenty-seven genomic regions of 10 adjacent SNPs associated with fatty acids composition were identified on chromosomes 1, 2, 3, 5, 8, 12, 14, 15, 16, 17, and 18, each explaining ≥0.30% of the additive genetic variance. Twenty-three genes supporting the understanding of genetic mechanisms of fat composition in sheep were identified in these regions, such as DGAT2, TRHDE, TPH2, ME1, C6, C7, UBE3D, PARP14, and MRPS30. CONCLUSIONS Estimates of genomic heritabilities and elucidating important genomic regions can contribute to a better understanding of the genetic control of fatty acid deposition and improve the selection strategies to enhance meat quality and health attributes.
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Affiliation(s)
- G A Rovadoscki
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - S F N Pertile
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - A B Alvarenga
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - A S M Cesar
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - F Pértille
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - J Petrini
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - V Franzo
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - W V B Soares
- Institute of Zootechny (IZ), Nova Odessa, SP, Brazil
| | - G Morota
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - L F B Pinto
- Department of Animal Science, Federal University of Bahia (UFBA), Salvador, BA, Brazil
| | - G G P Carvalho
- Department of Animal Science, Federal University of Bahia (UFBA), Salvador, BA, Brazil
| | - D P D Lanna
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - L L Coutinho
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil
| | - G B Mourão
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Av. Pádua Dias, 11, ESALQ/USP, Piracicaba, São Paulo, 13418-900, Brazil.
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35
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Identifying artificial selection signals in the chicken genome. PLoS One 2018; 13:e0196215. [PMID: 29698423 PMCID: PMC5919632 DOI: 10.1371/journal.pone.0196215] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 04/09/2018] [Indexed: 12/28/2022] Open
Abstract
Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF), Jinghong (JH), Araucanas (AR), White Leghorn (WL), Pekin-Bantam (PB), Shamo (SH), Gallus-Gallus-Spadiceus (GA), Rheinlander (RH) and Vorwerkhuhn (VO). Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a 'two-step' strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study.
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A genome-wide study to identify genes responsible for oviduct development in chickens. PLoS One 2017; 12:e0189955. [PMID: 29281706 PMCID: PMC5744973 DOI: 10.1371/journal.pone.0189955] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Accepted: 12/05/2017] [Indexed: 12/16/2022] Open
Abstract
Molecular genetic tools provide a method for improving the breeding selection of chickens (Gallus gallus). Although some studies have identified genes affecting egg quality, little is known about the genes responsible for oviduct development. To address this issue, here we used a genome-wide association (GWA) study to detect genes or genomic regions that are related to oviduct development in a chicken F2 resource population by employing high-density 600 K single-nucleotide polymorphism (SNP) arrays. For oviduct length and weight, which exhibited moderate heritability estimates of 0.35 and 0.39, respectively, chromosome 1 (GGA1) explained 9.45% of the genetic variance, while GGA4 to GGA8 and GGA11 explained over 1% of the variance. Independent univariate genome-wide screens for oviduct length and weight detected 69 significant SNPs on GGA1 and 49 suggestive SNPs on GGA1, GGA4, and GGA8. One hundred and fourteen suggestive SNPs were associated with oviduct length, while 73 SNPs were associated with oviduct weight. The significant genomic regions affecting oviduct weight ranged from 167.79–174.29 Mb on GGA1, 73.16–75.70 Mb on GGA4, and 4.88–4.92 Mb on GGA8. The genes CKAP2, CCKAR, NCAPG, IGFBP3, and GORAB were shown to have potential roles in oviduct development. These genes are involved in cell survival, appetite, and growth control. Our results represent the first GWA analysis of genes controlling oviduct weight and length. The identification of genomic loci and potential candidate genes affecting oviduct development greatly increase our understanding of the genetic basis underlying oviduct development, which could have an impact on the selection of egg quality.
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Zeng T, Huang L, Ren J, Chen L, Tian Y, Huang Y, Zhang H, Du J, Lu L. Gene expression profiling reveals candidate genes related to residual feed intake in duodenum of laying ducks. J Anim Sci 2017; 95:5270-5277. [PMID: 29293758 PMCID: PMC6292259 DOI: 10.2527/jas2017.1714] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 09/22/2017] [Indexed: 12/12/2022] Open
Abstract
Feed represents two-thirds of the total costs of poultry production, especially in developing countries. Improvement in feed efficiency would reduce the amount of feed required for production (growth or laying), the production cost, and the amount of nitrogenous waste. The most commonly used measures for feed efficiency are feed conversion ratio (FCR) and residual feed intake (RFI). As a more suitable indicator assessing feed efficiency, RFI is defined as the difference between observed and expected feed intake based on maintenance and growth or laying. However, the genetic and biological mechanisms regulating RFI are largely unknown. Identifying molecular mechanisms explaining divergence in RFI in laying ducks would lead to the development of early detection methods for the selection of more efficient breeding poultry. The objective of this study was to identify duodenum genes and pathways through transcriptional profiling in 2 extreme RFI phenotypes (HRFI and LRFI) of the duck population. Phenotypic aspects of feed efficiency showed that RFI was strongly positive with FCR and feed intake (FI). Transcriptomic analysis identified 35 differentially expressed genes between LRFI and HRFI ducks. These genes play an important role in metabolism, digestibility, secretion, and innate immunity including (), (), (), β (), and (). These results improve our knowledge of the biological basis underlying RFI, which would be useful for further investigations of key candidate genes for RFI and for the development of biomarkers.
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Affiliation(s)
- T. Zeng
- Institute of Animal Husbandry and Veterinary Medicine, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - L. Huang
- Institute of Animal Husbandry and Veterinary Medicine, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
- College of Animal Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - J. Ren
- Institute of Animal Husbandry and Veterinary Medicine, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - L. Chen
- Institute of Animal Husbandry and Veterinary Medicine, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Y. Tian
- Institute of Animal Husbandry and Veterinary Medicine, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Y. Huang
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural sciences, Fuzhou, 350003, China
| | - H. Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Hubei Academy of Agricultural sciences, Wuhan, 430064, China
| | - J. Du
- Institute of Animal Husbandry and Veterinary Medicine, Hubei Academy of Agricultural sciences, Wuhan, 430064, China
| | - L. Lu
- Institute of Animal Husbandry and Veterinary Medicine, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
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Wang Y, Ding X, Tan Z, Ning C, Xing K, Yang T, Pan Y, Sun D, Wang C. Genome-Wide Association Study of Piglet Uniformity and Farrowing Interval. Front Genet 2017; 8:194. [PMID: 29234349 PMCID: PMC5712316 DOI: 10.3389/fgene.2017.00194] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Accepted: 11/15/2017] [Indexed: 02/04/2023] Open
Abstract
Piglet uniformity (PU) and farrowing interval (FI) are important reproductive traits related to production and economic profits in the pig industry. However, the genetic architecture of the longitudinal trends of reproductive traits still remains elusive. Herein, we performed a genome-wide association study (GWAS) to detect potential genetic variation and candidate genes underlying the phenotypic records at different parities for PU and FI in a population of 884 Large White pigs. In total, 12 significant SNPs were detected on SSC1, 3, 4, 9, and 14, which collectively explained 1–1.79% of the phenotypic variance for PU from parity 1 to 4, and 2.58–4.11% for FI at different stages. Of these, seven SNPs were located within 16 QTL regions related to swine reproductive traits. One QTL region was associated with birth body weight (related to PU) and contained the peak SNP MARC0040730, and another was associated with plasma FSH concentration (related to FI) and contained the SNP MARC0031325. Finally, some positional candidate genes for PU and FI were identified because of their roles in prenatal skeletal muscle development, fetal energy substrate, pre-implantation, and the expression of mammary gland epithelium. Identification of novel variants and candidate genes will greatly advance our understanding of the genetic mechanisms of PU and FI, and suggest a specific opportunity for improving marker assisted selection or genomic selection in pigs.
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Affiliation(s)
- Yuan Wang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xiangdong Ding
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhen Tan
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Chao Ning
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Kai Xing
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ting Yang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yongjie Pan
- Beijing Shunxin Agriculture Co., Ltd., Beijing, China
| | - Dongxiao Sun
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Chuduan Wang
- Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Li S, Wang X, Qu L, Dou T, Ma M, Shen M, Guo J, Hu Y, Wang K. Genome-wide association studies for small intestine length in an F2 population of chickens. ITALIAN JOURNAL OF ANIMAL SCIENCE 2017. [DOI: 10.1080/1828051x.2017.1368419] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Shangmin Li
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Xingguo Wang
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Liang Qu
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Taocun Dou
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Meng Ma
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Manman Shen
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Jun Guo
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - Yuping Hu
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
| | - KeHua Wang
- Department of Laying Hen Breeding, Jiangsu Institute of Poultry Science, Yangzhou, China
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Yuan J, Chen S, Shi F, Wu G, Liu A, Yang N, Sun C. Genome-wide association study reveals putative role of gga-miR-15a in controlling feed conversion ratio in layer chickens. BMC Genomics 2017; 18:699. [PMID: 28877683 PMCID: PMC5586008 DOI: 10.1186/s12864-017-4092-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 08/28/2017] [Indexed: 11/24/2022] Open
Abstract
Background Efficient use of feed resources for farm animals is a critical concern in animal husbandry. Numerous genetic and nutritional studies have been conducted to investigate feed efficiency during the regular laying cycle of chickens. However, by prolonging the laying period of layers, the performance of feed utilization in the late-laying period becomes increasingly important. In the present study, we measured daily feed intake (FI), residual feed intake (RFI) and feed conversion ratio (FCR) of 808 hens during 81–82 weeks of age to evaluate genetic properties and then used a genome-wide association study (GWAS) to reveal the genetic determinants. Results The heritability estimates for the investigated traits were medium and between 0.15 and 0.28 in both pedigree- and genomic-based estimates, whereas the genetic correlations among these traits were high and ranged from 0.49 to 0.90. Three genome-wide significant SNPs located on chromosome 1 (GGA1) were detected for FCR. Linkage disequilibrium (LD) and conditional GWA analysis indicated that these 3 SNPs were highly correlated with one another, located at 13.55–45.16 Kb upstream of gga-miR-15a. Results of quantitative real-time polymerase chain reaction (qRT-PCR) analysis in liver tissue showed that the expression of gga-miR-15a was significantly higher in the high FCR birds than that in the medium or low FCR birds. Bioinformatics analysis further revealed that gga-mir-15a could act on many target genes, such as forkhead box O1 (FOXO1) that is involved in the insulin-signaling pathway, which influences nutrient metabolism in many organisms. Additionally, some suggestively significant variants, located on GGA3 and GGA9, were identified to associate with FI and RFI. Conclusions This GWA analysis was conducted on feed intake and efficiency traits for chickens and was innovative for application in the late laying period. Our findings can be used as a reference in the genomic breeding programs for increasing the efficiency performance of old hens and to improve our understanding of the molecular determinants for feed efficiency. Electronic supplementary material The online version of this article (10.1186/s12864-017-4092-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jingwei Yuan
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Sirui Chen
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Fengying Shi
- Beijing Engineering Research Center of Layer, Beijing, China
| | - Guiqin Wu
- Beijing Engineering Research Center of Layer, Beijing, China
| | - Aiqiao Liu
- Beijing Engineering Research Center of Layer, Beijing, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
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Wang YM, Xu HB, Wang MS, Otecko NO, Ye LQ, Wu DD, Zhang YP. Annotating long intergenic non-coding RNAs under artificial selection during chicken domestication. BMC Evol Biol 2017; 17:192. [PMID: 28810830 PMCID: PMC5558714 DOI: 10.1186/s12862-017-1036-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Accepted: 08/04/2017] [Indexed: 12/18/2022] Open
Abstract
Background Numerous biological functions of long intergenic non-coding RNAs (lincRNAs) have been identified. However, the contribution of lincRNAs to the domestication process has remained elusive. Following domestication from their wild ancestors, animals display substantial changes in many phenotypic traits. Therefore, it is possible that diverse molecular drivers play important roles in this process. Results We analyzed 821 transcriptomes in this study and annotated 4754 lincRNA genes in the chicken genome. Our population genomic analysis indicates that 419 lincRNAs potentially evolved during artificial selection related to the domestication of chicken, while a comparative transcriptomic analysis identified 68 lincRNAs that were differentially expressed under different conditions. We also found 47 lincRNAs linked to special phenotypes. Conclusions Our study provides a comprehensive view of the genome-wide landscape of lincRNAs in chicken. This will promote a better understanding of the roles of lincRNAs in domestication, and the genetic mechanisms associated with the artificial selection of domestic animals. Electronic supplementary material The online version of this article (doi:10.1186/s12862-017-1036-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yun-Mei Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hai-Bo Xu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Newton Otieno Otecko
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ling-Qun Ye
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China.
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Lien CY, Tixier-Boichard M, Wu SW, Wang WF, Ng CS, Chen CF. Detection of QTL for traits related to adaptation to sub-optimal climatic conditions in chickens. Genet Sel Evol 2017; 49:39. [PMID: 28427323 PMCID: PMC5399330 DOI: 10.1186/s12711-017-0314-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 03/31/2017] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Growth traits can be used as indicators of adaptation to sub-optimal conditions. The current study aimed at identifying quantitative trait loci (QTL) that control performance under variable temperature conditions in chickens. METHODS An F2 population was produced by crossing the Taiwan Country chicken L2 line (selected for body weight, comb area, and egg production) with an experimental line of Rhode Island Red layer R- (selected for low residual feed consumption). A total of 844 animals were genotyped with the 60 K Illumina single nucleotide polymorphism (SNP) chip. Whole-genome interval linkage mapping and a genome-wide association study (GWAS) were performed for body weight at 0, 4, 8, 12, and 16 weeks of age, shank length at 8 weeks of age, size of comb area at 16 weeks of age, and antibody response to sheep red blood cells at 11 weeks of age (7 and 14 days after primary immunization). Relevant genes were identified based on functional annotation of candidate genes and potentially relevant SNPs were detected by comparing whole-genome sequences of several birds between the parental lines. RESULTS Whole-genome QTL analysis revealed 47 QTL and 714 effects associated with 178 SNPs were identified by GWAS with 5% Bonferroni genome-wide significance. Little overlap was observed between the QTL and GWAS results, with only two chromosomal regions detected by both approaches, i.e. one on GGA24 (GGA for Gallus gallus chromosome) for BW04 and one on GGAZ for six growth-related traits. Based on whole-genome sequence, differences between the parental lines based on several birds were screened in the genome-wide QTL regions and in a region detected by both methods, resulting in the identification of 106 putative candidate genes with a total of 15,443 SNPs, of which 41 were missense and 1698 were not described in the dbSNP archive. CONCLUSIONS The QTL detected in this study for growth and morphological traits likely influence adaptation of chickens to sub-tropical climate. Using whole-genome sequence data, we identified candidate SNPs for further confirmation of QTL in the F2 design. A strong QTL effect found on GGAZ underlines the importance of sex-linked inheritance for growth traits in chickens.
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Affiliation(s)
- Ching-Yi Lien
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.,Department of Animal Science, National Chung Hsing University, 145 Xingda Rd., South District, Taichung, 40227, Taiwan.,Livestock Research Institute, Council of Agriculture, Executive Yuan, 112 Muchang, Xinhua District, Tainan, 71246, Taiwan
| | | | - Shih-Wen Wu
- Fonghuanggu Bird and Ecology Park, National Museum of Natural Science, 1-9 Renyi Rd., Lugu Township, Nantou County, 55841, Taiwan
| | - Woei-Fuh Wang
- Biodiversity Research Center, Academia Sinica, 128 Academia Rd., Section 2, Nankang, Taipei, 11529, Taiwan
| | - Chen Siang Ng
- Institute of Molecular and Cellular Biology, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Rd., Hsinchu, 30013, Taiwan
| | - Chih-Feng Chen
- Department of Animal Science, National Chung Hsing University, 145 Xingda Rd., South District, Taichung, 40227, Taiwan. .,Center for the Integrative and Evolutionary Galliformes Genomics, National Chung Hsing University, No. 250, Guoguang Rd., South District, Taichung, 40227, Taiwan.
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Pértille F, Moreira GCM, Zanella R, Nunes JDRDS, Boschiero C, Rovadoscki GA, Mourão GB, Ledur MC, Coutinho LL. Genome-wide association study for performance traits in chickens using genotype by sequencing approach. Sci Rep 2017; 7:41748. [PMID: 28181508 PMCID: PMC5299454 DOI: 10.1038/srep41748] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Accepted: 12/23/2016] [Indexed: 12/11/2022] Open
Abstract
Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F2 chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs.
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Affiliation(s)
- Fábio Pértille
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Ricardo Zanella
- College of Agronomy and Veterinary Medicine, Veterinary School, University of Passo Fundo, Rio Grande do Sul, Brazil
| | | | - Clarissa Boschiero
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Gregori Alberto Rovadoscki
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Gerson Barreto Mourão
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Luiz Lehmann Coutinho
- University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
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Genome-Wide Detection of Selective Signatures in Chicken through High Density SNPs. PLoS One 2016; 11:e0166146. [PMID: 27820849 PMCID: PMC5098818 DOI: 10.1371/journal.pone.0166146] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2016] [Accepted: 10/24/2016] [Indexed: 11/25/2022] Open
Abstract
Chicken is recognized as an excellent model for studies of genetic mechanism of phenotypic and genomic evolution, with large effective population size and strong human-driven selection. In the present study, we performed Extended Haplotype Homozygosity (EHH) tests to identify significant core regions employing 600K SNP Chicken chip in an F2 population of 1,534 hens, which was derived from reciprocal crosses between White Leghorn and Dongxiang chicken. Results indicated that a total of 49,151 core regions with an average length of 9.79 Kb were identified, which occupied approximately 52.15% of genome across all autosomes, and 806 significant core regions attracted us mostly. Genes in candidate regions may experience positive selection and were considered to have possible influence on beneficial economic traits. A panel of genes including AASDHPPT, GDPD5, PAR3, SOX6, GPC1 and a signal pathway of AKT1 were detected with the most extreme P-values. Further enrichment analyses indicated that these genes were associated with immune function, sensory organ development and neurogenesis, and may have experienced positive selection in chicken. Moreover, some of core regions exactly overlapped with genes excavated in our previous GWAS, suggesting that these genes have undergone positive selection may affect egg production. Findings in our study could draw a comparatively integrate genome-wide map of selection signature in the chicken genome, and would be worthy for explicating the genetic mechanisms of phenotypic diversity in poultry breeding.
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Genetic Determinism of Fearfulness, General Activity and Feeding Behavior in Chickens and Its Relationship with Digestive Efficiency. Behav Genet 2016; 47:114-124. [PMID: 27604231 DOI: 10.1007/s10519-016-9807-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 08/13/2016] [Indexed: 10/21/2022]
Abstract
The genetic relationships between behavior and digestive efficiency were studied in 860 chickens from a cross between two lines divergently selected on digestive efficiency. At 2 weeks of age each chick was video-recorded in the home pen to characterize general activity and feeding behavior. Tonic immobility and open-field tests were also carried out individually to evaluate emotional reactivity (i.e. the propensity to express fear responses). Digestive efficiency was measured at 3 weeks. Genetic parameters of behavior traits were estimated. Birds were genotyped on 3379 SNP markers to detect QTLs. Heritabilities of behavioral traits were low, apart from tonic immobility (0.17-0.18) and maximum meal length (0.14). The genetic correlations indicated that the most efficient birds fed more frequently and were less fearful. We detected 14 QTL (9 for feeding behavior, 3 for tonic immobility, 2 for frequency of lying). Nine of them co-localized with QTL for efficiency, anatomy of the digestive tract, feed intake or microbiota composition. Four genes involved in fear reactions were identified in the QTL for tonic immobility on GGA1.
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Xu Z, Ji C, Zhang Y, Zhang Z, Nie Q, Xu J, Zhang D, Zhang X. Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens. BMC Genomics 2016; 17:594. [PMID: 27506765 PMCID: PMC4979145 DOI: 10.1186/s12864-016-2861-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 06/29/2016] [Indexed: 01/07/2023] Open
Abstract
Background Residual feed intake (RFI) is a powerful indicator for energy utilization efficiency and responds to selection. Low RFI selection enables a reduction in feed intake without affecting growth performance. However, the effective variants or major genes dedicated to phenotypic differences in RFI in quality chickens are unclear. Therefore, a genome-wide association study (GWAS) and RNA sequencing were performed on RFI to identify genetic variants and potential candidate genes associated with energy improvement. Results A lower average daily feed intake was found in low-RFI birds compared to high-RFI birds. The heritability of RFI measured from 44 to 83 d of age was 0.35. GWAS showed that 32 of the significant single nucleotide polymorphisms (SNPs) associated with the RFI (P < 10−4) accounted for 53.01 % of the additive genetic variance. More than half of the effective SNPs were located in a 1 Mb region (16.3–17.3 Mb) of chicken (Gallus gallus) chromosome (GGA) 12. Thus, focusing on this region should enable a deeper understanding of energy utilization. RNA sequencing was performed to profile the liver transcriptomes of four male chickens selected from the high and low tails of the RFI. One hundred and sixteen unique genes were identified as differentially expressed genes (DEGs). Some of these genes were relevant to appetite, cell activities, and fat metabolism, such as CCKAR, HSP90B1, and PCK1. Some potential genes within the 500 Kb flanking region of the significant RFI-related SNPs detected in GWAS (i.e., MGP, HIST1H110, HIST1H2A4L3, OC3, NR0B2, PER2, ST6GALNAC2, and G0S2) were also identified as DEGs in chickens with divergent RFIs. Conclusions The GWAS findings showed that the 1 Mb narrow region of GGA12 should be important because it contained genes involved in energy-consuming processes, such as lipogenesis, social behavior, and immunity. Similar results were obtained in the transcriptome sequencing experiments. In general, low-RFI birds seemed to optimize energy employment by reducing energy expenditure in cell activities, immune responses, and physical activity compared to eating. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2861-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zhenqiang Xu
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.,Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Congliang Ji
- Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Yan Zhang
- Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China
| | - Qinghua Nie
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China
| | - Jiguo Xu
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China
| | - Dexiang Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.,Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Xiquan Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
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Shen M, Qu L, Ma M, Dou T, Lu J, Guo J, Hu Y, Yi G, Yuan J, Sun C, Wang K, Yang N. Genome-Wide Association Studies for Comb Traits in Chickens. PLoS One 2016; 11:e0159081. [PMID: 27427764 PMCID: PMC4948856 DOI: 10.1371/journal.pone.0159081] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2016] [Accepted: 06/27/2016] [Indexed: 12/21/2022] Open
Abstract
The comb, as a secondary sexual character, is an important trait in chicken. Indicators of comb length (CL), comb height (CH), and comb weight (CW) are often selected in production. DNA-based marker-assisted selection could help chicken breeders to accelerate genetic improvement for comb or related economic characters by early selection. Although a number of quantitative trait loci (QTL) and candidate genes have been identified with advances in molecular genetics, candidate genes underlying comb traits are limited. The aim of the study was to use genome-wide association (GWA) studies by 600 K Affymetrix chicken SNP arrays to detect genes that are related to comb, using an F2 resource population. For all comb characters, comb exhibited high SNP-based heritability estimates (0.61-0.69). Chromosome 1 explained 20.80% genetic variance, while chromosome 4 explained 6.89%. Independent univariate genome-wide screens for each character identified 127, 197, and 268 novel significant SNPs with CL, CH, and CW, respectively. Three candidate genes, VPS36, AR, and WNT11B, were determined to have a plausible function in all comb characters. These genes are important to the initiation of follicle development, gonadal growth, and dermal development, respectively. The current study provides the first GWA analysis for comb traits. Identification of the genetic basis as well as promising candidate genes will help us understand the underlying genetic architecture of comb development and has practical significance in breeding programs for the selection of comb as an index for sexual maturity or reproduction.
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Affiliation(s)
- Manman Shen
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Liang Qu
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Meng Ma
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Taocun Dou
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Jian Lu
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Jun Guo
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Yuping Hu
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Guoqiang Yi
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jingwei Yuan
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Kehua Wang
- Layer Breeding and Production, Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
- * E-mail:
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Cohen-Zinder M, Asher A, Lipkin E, Feingersch R, Agmon R, Karasik D, Brosh A, Shabtay A. FABP4 is a leading candidate gene associated with residual feed intake in growing Holstein calves. Physiol Genomics 2016; 48:367-76. [PMID: 26993365 DOI: 10.1152/physiolgenomics.00121.2015] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 03/09/2016] [Indexed: 01/08/2023] Open
Abstract
Ecological and economic concerns drive the need to improve feed utilization by domestic animals. Residual feed intake (RFI) is one of the most acceptable measures for feed efficiency (FE). However, phenotyping RFI-related traits is complex and expensive and requires special equipment. Advances in marker technology allow the development of various DNA-based selection tools. To assimilate these technologies for the benefit of RFI-based selection, reliable phenotypic measures are prerequisite. In the current study, we identified single nucleotide polymorphisms (SNPs) associated with RFI phenotypic consistency across different ages and diets (named RFI 1-3), using DNA samples of high or low RFI ranked Holstein calves. Using targeted sequencing of chromosomal regions associated with FE- and RFI-related traits, we identified 48 top SNPs significantly associated with at least one of three defined RFIs. Eleven of these SNPs were harbored by the fatty acid binding protein 4 (FABP4). While 10 significant SNPs found in FABP4 were common for RFI 1 and RFI 3, one SNP (FABP4_5; A<G substitution), in the promoter region of the gene, was significantly associated with all three RFIs. As the three RFI classes reflect changing diets and ages with concomitant RFI phenotypic consistency, the above polymorphisms and in particular FABP4_5, might be considered possible markers for RFI-based selection for FE in the Holstein breed, following a larger-scale validation.
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Affiliation(s)
- Miri Cohen-Zinder
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel;
| | - Aviv Asher
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel; Israeli Center for Interdisciplinary Research in Chronobiology, University of Haifa, Haifa, Israel
| | - Ehud Lipkin
- Department of Genetics, The Hebrew University of Jerusalem, Jerusalem, Israel; and
| | - Roi Feingersch
- Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Rotem Agmon
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - David Karasik
- Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Arieh Brosh
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Ariel Shabtay
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
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Van Goor A, Bolek KJ, Ashwell CM, Persia ME, Rothschild MF, Schmidt CJ, Lamont SJ. Identification of quantitative trait loci for body temperature, body weight, breast yield, and digestibility in an advanced intercross line of chickens under heat stress. Genet Sel Evol 2015; 47:96. [PMID: 26681307 PMCID: PMC4683778 DOI: 10.1186/s12711-015-0176-7] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Accepted: 12/01/2015] [Indexed: 12/03/2022] Open
Abstract
Background Losses in poultry production due to heat stress have considerable negative economic consequences. Previous studies in poultry have elucidated a genetic influence on response to heat. Using a unique chicken genetic resource, we identified genomic regions associated with body temperature (BT), body weight (BW), breast yield, and digestibility measured during heat stress. Identifying genes associated with a favorable response during high ambient temperature can facilitate genetic selection of heat-resilient chickens. Methods Generations F18 and F19 of a broiler (heat-susceptible) × Fayoumi (heat-resistant) advanced intercross line (AIL) were used to fine-map quantitative trait loci (QTL). Six hundred and thirty-one birds were exposed to daily heat cycles from 22 to 28 days of age, and phenotypes were measured before heat treatment, on the 1st day and after 1 week of heat treatment. BT was measured at these three phases and BW at pre-heat treatment and after 1 week of heat treatment. Breast muscle yield was calculated as the percentage of BW at day 28. Ileal feed digestibility was assayed from digesta collected from the ileum at day 28. Four hundred and sixty-eight AIL were genotyped using the 600 K Affymetrix chicken SNP (single nucleotide polymorphism) array. Trait heritabilities were estimated using an animal model. A genome-wide association study (GWAS) for these traits and changes in BT and BW was conducted using Bayesian analyses. Candidate genes were identified within 200-kb regions around SNPs with significant association signals. Results Heritabilities were low to moderate (0.03 to 0.35). We identified QTL for BT on Gallus gallus chromosome (GGA)14, 15, 26, and 27; BW on GGA1 to 8, 10, 14, and 21; dry matter digestibility on GGA19, 20 and 21; and QTL of very large effect for breast muscle yield on GGA1, 15, and 22 with a single 1-Mb window on GGA1 explaining more than 15 % of the genetic variation. Conclusions This is the first study to estimate heritabilities and perform GWAS using this AIL for traits measured during heat stress. Significant QTL as well as low to moderate heritabilities were found for each trait, and these QTL may facilitate selection for improved animal performance in hot climatic conditions.
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Affiliation(s)
| | - Kevin J Bolek
- Department of Animal Science, University of California, Davis, CA, USA.
| | - Chris M Ashwell
- Department Poultry Science, North Carolina State University, Raleigh, NC, USA.
| | - Mike E Persia
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
| | - Max F Rothschild
- Department of Animal Science, Iowa State University, Ames, IA, USA.
| | - Carl J Schmidt
- Department of Animal and Food Sciences, University of Delaware, Newark, DE, USA.
| | - Susan J Lamont
- Department of Animal Science, Iowa State University, Ames, IA, USA.
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