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Xu L, Liu Y. Identification, Design, and Application of Noncoding Cis-Regulatory Elements. Biomolecules 2024; 14:945. [PMID: 39199333 PMCID: PMC11352686 DOI: 10.3390/biom14080945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 07/25/2024] [Accepted: 07/30/2024] [Indexed: 09/01/2024] Open
Abstract
Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology.
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Affiliation(s)
- Lingna Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China;
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China;
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan 528226, China
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2
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Wang Z, Tian W, Guo Y, Wang D, Zhang Y, Zhi Y, Li D, Li W, Li Z, Jiang R, Han R, Sun G, Li G, Tian Y, Li H, Kang X, Liu X. Dynamic alternations of three-dimensional chromatin architecture contribute to phenotypic characteristics of breast muscle in chicken. Commun Biol 2024; 7:910. [PMID: 39068219 PMCID: PMC11283561 DOI: 10.1038/s42003-024-06599-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 07/17/2024] [Indexed: 07/30/2024] Open
Abstract
Breast muscle growth rate and intramuscular fat (IMF) content show apparent differences between fast-growing broilers and slow-growing indigenous chickens. However, the underlying genetic basis of these phenotypic characteristics remains elusive. In this study, we investigate the dynamic alterations of three-dimensional genome architecture and chromatin accessibility in breast muscle across four key developmental stages from embryo to starter chick in Arbor Acres (AA) broilers and Yufen (YF) indigenous chickens. The limited breed-specifically up-regulated genes (Bup-DEGs) are embedded in breed-specific A compartment, while a majority of the Bup-DEGs involving myogenesis and adipogenesis are regulated by the breed-specific TAD reprogramming. Chromatin loops allow distal accessible regions to interact with myogenic genes, and those loops share an extremely low similarity between chicken with different growth rate. Moreover, AA-specific loop interactions promote the expression of 40 Bup-DEGs, such as IGF1, which contributes to myofiber hypertrophy. YF-specific loop interactions or distal accessible regions lead to increased expression of 5 Bup-DEGs, including PIGO, PEMT, DHCR7, TMEM38B, and DHDH, which contribute to IMF deposition. These results help elucidate the regulation of breast muscle growth and IMF deposition in chickens.
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Affiliation(s)
- Zhang Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
| | - Weihua Tian
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
| | - Yulong Guo
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
| | - Dandan Wang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
| | - Yanyan Zhang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
| | - Yihao Zhi
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
| | - Donghua Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Wenting Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Zhuanjian Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Ruirui Jiang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Ruili Han
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Guirong Sun
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Guoxi Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Yadong Tian
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China
| | - Hong Li
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China.
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China.
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China.
| | - Xiangtao Kang
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China.
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China.
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China.
| | - Xiaojun Liu
- College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450002, China.
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou, 450002, China.
- International Joint Research, Laboratory for Poultry Breeding of Henan, Zhengzhou, 450002, China.
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3
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Tu TC, Lin CJ, Liu MC, Hsu ZT, Chen CF. Comparison of genomic prediction accuracy using different models for egg production traits in Taiwan country chicken. Poult Sci 2024; 103:104063. [PMID: 39098301 DOI: 10.1016/j.psj.2024.104063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 06/20/2024] [Accepted: 07/01/2024] [Indexed: 08/06/2024] Open
Abstract
In local chickens targeted for niche markets, genotyping costs are relatively high due to the small population size and diverse breeding goals. The single-step genomic best linear unbiased prediction (ssGBLUP) model, which combines pedigree and genomic information, has been introduced to increase the accuracy of genomic estimated breeding value (GEBV). Therefore, this model may be more beneficial than the genomic BLUP (GBLUP) model for genomic selection in local chickens. Additionally, the single-step genome-wide association study (ssGWAS) can be used to extend the ssGBLUP model results to animals with available phenotypic information but without genotypic data. In this study, we compared the accuracy of (G)EBVs using the pedigree-based BLUP (PBLUP), GBLUP, and ssGBLUP models. Moreover, we conducted single-SNP GWAS (SNP-GWAS), GBLUP-GWAS, and ssGWAS methods to identify genes associated with egg production traits in the NCHU-G101 chicken to understand the feasibility of using genomic selection in a small population. The average prediction accuracy of (G)EBV for egg production traits using the PBLUP, GBLUP, and ssGBLUP models is 0.536, 0.531, and 0.555, respectively. In total, 22 suggestive- and 5% Bonferroni genome-wide significant-level SNPs for total egg number (EN), average laying rate (LR), average clutch length, and total clutch number are detected using 3 GWAS methods. These SNPs are mapped onto Gallus gallus chromosomes (GGA) 4, 6, 10, 18, and 25 in NCHU-G101 chicken. Furthermore, through SNP-GWAS and ssGWAS methods, we identify 2 genes on GGA4 associated with EN and LR: ENSGALG00000023172 and PPARGC1A. In conclusion, the ssGBLUP model demonstrates superior prediction accuracy, performing on average 3.41% than the PBLUP model. The implications of our gene results may guide future selection strategies for Taiwan Country chickens. Our results highlight the applicability of the ssGBLUP model for egg production traits selection in a small population, specifically NCHU-G101 chicken in Taiwan.
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Affiliation(s)
- Tsung-Che Tu
- Department of Animal Science, National Chung Hsing University, Taichung 402, Taiwan; Ray Hsing Agricultural Biotechnology Co. Ltd., Yunlin 633, Taiwan
| | - Chen-Jyuan Lin
- Department of Animal Science, National Chung Hsing University, Taichung 402, Taiwan
| | - Ming-Che Liu
- Ray Hsing Agricultural Biotechnology Co. Ltd., Yunlin 633, Taiwan
| | - Zhi-Ting Hsu
- Ray Hsing Agricultural Biotechnology Co. Ltd., Yunlin 633, Taiwan
| | - Chih-Feng Chen
- Department of Animal Science, National Chung Hsing University, Taichung 402, Taiwan; The iEGG and Animal Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan.
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4
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Chen X, Li X, Zhong C, Jiang X, Wu G, Li G, Yan Y, Yang N, Sun C. Genetic patterns and genome-wide association analysis of eggshell quality traits of egg-type chicken across an extended laying period. Poult Sci 2024; 103:103458. [PMID: 38350384 PMCID: PMC10875610 DOI: 10.1016/j.psj.2024.103458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 12/24/2023] [Accepted: 01/08/2024] [Indexed: 02/15/2024] Open
Abstract
The industry of egg-type chicken has shown a trend of extending the rearing period, with the goal of breeding chicken breeds capable of producing 500 qualified eggs by 700 d of age. However, the rapid decline in eggshell quality during the late laying period is one of the major challenges. In this study, a total of 3,261 Rhode Island Red chickens were used to measure eggshell quality traits including eggshell strength (ESS), eggshell thickness (EST), eggshell color (ESC) and eggshell gloss (ESG) at seven age points ranging from 36 to 90 wk of age. Phenotypic variations increased with the aging process, especially during the late laying period (> 55 wk), and the heritability during this period decreased by 22.7 to 81.4% compared to the initial and peak laying periods. Then we performed genome-wide association study (GWAS) to identify the genomic variants that associated with eggshell quality, with a custom Illumina 50K BeadChip, named PhenoixChip-I. The results indicated that 2 genomic regions on GGA1(23.24-25.15Mb; 175.95-176.05 Mb) were significantly (P < 4.48E-06) or suggestively (P < 8.97E-05) associated with ESS, which can explain 9.59% and 0.48% of the phenotypic variations of ESS46 and ESS36, respectively. Three genes, FRY, PCNX2, and ENSGALG00000052468, were considered to be the candidate genes for ESS. For other traits, the genome-wide suggestive SNPs were identified at each age point, exhibiting a certain trend with aging process. Additionally, SNP enrichment analysis and functional annotation of cross-tissue regulatory elements to ESS36 revealed a high concentration of enhancer elements specific to shell gland and kidney tissues. This study, deepened our knowledge of eggshells and laying a valued scientific foundation for chicken molecular breeding.
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Affiliation(s)
- Xiaoman Chen
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Xiaochang Li
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Conghao Zhong
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Xinwei Jiang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Guiqin Wu
- Beijing Engineering Research Center of Layer, Beijing, 101206, China
| | - Guangqi Li
- Beijing Engineering Research Center of Layer, Beijing, 101206, China
| | - Yiyuan Yan
- Beijing Engineering Research Center of Layer, Beijing, 101206, China
| | - Ning Yang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Congjiao Sun
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
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Zhou W, Huang K, Bu D, Zhang Q, Fu J, Hu B, Zhou Y, Chen W, Fu Y, Zhang A, Fu J, Jiang G. Remarkable Contamination of Short- and Medium-Chain Chlorinated Paraffins in Free-Range Chicken Eggs from Rural Tibetan Plateau. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5093-5102. [PMID: 38386012 DOI: 10.1021/acs.est.3c08815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Rapid social-economic development introduces modern lifestyles into rural areas, not only bringing numerous modern products but also new pollutants, such as chlorinated paraffins (CPs). The rural Tibetan Plateau has limited industrial activities and is a unique place to investigate this issue. Herein we collected 90 free-range chicken egg pool samples across the rural Tibetan Plateau to evaluate the pollution status of CPs. Meanwhile, CPs in related soils, free-range chicken eggs from Jiangxi, and farmed eggs from markets were also analyzed. The median concentrations of SCCPs (159 ng g-1 wet weight (ww)) and MCCPs (1390 ng g-1 ww) in Tibetan free-range chicken eggs were comparable to those from Jiangxi (259 and 938 ng g-1 ww) and significantly higher than those in farmed eggs (22.0 and 81.7 ng g-1 ww). In the rural Tibetan Plateau, the median EDI of CPs via egg consumption by adults and children were estimated to be 81.6 and 220.2 ng kg-1 bw day-1 for SCCPs and 483.4 and 1291 ng kg-1 bw day-1 for MCCPs, respectively. MCCPs might pose potential health risks for both adults and children in the worst scenario. Our study demonstrates that new pollutants should not be ignored and need further attention in remote rural areas.
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Affiliation(s)
- Wei Zhou
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Kai Huang
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Duo Bu
- School of Ecology and Environment, Tibet University, Lhasa 850000, China
| | - Qiangying Zhang
- School of Ecology and Environment, Tibet University, Lhasa 850000, China
| | - Jie Fu
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Boyuan Hu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Yunqiao Zhou
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Weifang Chen
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Yilin Fu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Aiqian Zhang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Jianjie Fu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- School of Ecology and Environment, Tibet University, Lhasa 850000, China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- School of Ecology and Environment, Tibet University, Lhasa 850000, China
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Hubert JN, Perret M, Riquet J, Demars J. Livestock species as emerging models for genomic imprinting. Front Cell Dev Biol 2024; 12:1348036. [PMID: 38500688 PMCID: PMC10945557 DOI: 10.3389/fcell.2024.1348036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 01/19/2024] [Indexed: 03/20/2024] Open
Abstract
Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.
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Affiliation(s)
| | | | | | - Julie Demars
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
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Wang Z, Chen Q, Wang Y, Wang Y, Liu R. Refine localizations of functional variants affecting eggshell color of Lueyang black-boned chicken in the SLCO1B3. Poult Sci 2024; 103:103212. [PMID: 37980747 PMCID: PMC10685018 DOI: 10.1016/j.psj.2023.103212] [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: 08/17/2023] [Revised: 10/13/2023] [Accepted: 10/13/2023] [Indexed: 11/21/2023] Open
Abstract
Table eggs with color-uniformity shell are visually attractive for consumers. Lueyang black-boned chicken (LBC) lays colorful eggs, which is undesirable for sale of table eggs, but provides a segregating population for mapping functional variants affecting eggshell color. SLCO1B3 was identified as the causative gene for blue eggs in the Dongxiang and Araucana chickens. The aim of this study is to map functional variants associated with chicken eggshell color in the SLCO1B3. Eggshell color of LBC (n = 383) was measured using the L*a*b color space. SLCO1B3 was resequencing using a subset (n = 30) of 383 samples. Linkage disequilibrium among 139 SNP was analyzed. Association of 16 SNP in the SLCO1B3 and 8 in CPOX, ALAS1, and ABCG2 genes with L*a*b were tested by a polygenic model (LMM) and a polygenic/oligogenic mixed model (BSLMM). Chromatin state annotations were retrieved from the UCSC database. Effect of SLCO1B3 variants distributed in mapping and upstream 1.6-kb regions on promoter activities were analyzed using dual-luciferase reporter assay. One hundred and thirty-nine variants maintained low linkage disequilibrium with 80% of r2 less than 0.226. Fifteen SLCO1B3 variants were significantly associated with a*, of which 1B3_SNP108 was showed the strongest association and the largest effect on a*. In the BSLMM, 1B3_SNP108 alone appeared in the Markov chain Monte Carlo as major variants in 100% of posterior inclusion probability. None of variants in CPOX, ALAS1, and ABCG2 were significantly associated with color indexes except that 2 ALAS1 variants were associated with L*. 1B3_SNP108 distributes in the Intron4 where 6 active enhancers and 1 ATAC island were enriched. However, 1B3_SNP108-containing constructs showed negligible activities in the reporter assay. No significant differences of activities between haplotypes were found for five 5'-deleted promoter constructs. The data recognizes 1B3_SNP108 as a valuable marker for breeding of eggshell color. Functional variants are localized in the region adjacent to the 1B3_SNP108 due to low linkage disequilibrium in the LBC. Our findings extend the role of SLCO1B3 from a causative gene for blue eggs to a major regulator driving continuous variation of LBC eggshell color.
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Affiliation(s)
- Zhepeng Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
| | - Qiu Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Yiwei Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Yulu Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Ruifang Liu
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
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Woolley SA, Salavati M, Clark EL. Recent advances in the genomic resources for sheep. Mamm Genome 2023; 34:545-558. [PMID: 37752302 PMCID: PMC10627984 DOI: 10.1007/s00335-023-10018-z] [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: 04/11/2023] [Accepted: 08/30/2023] [Indexed: 09/28/2023]
Abstract
Sheep (Ovis aries) provide a vital source of protein and fibre to human populations. In coming decades, as the pressures associated with rapidly changing climates increase, breeding sheep sustainably as well as producing enough protein to feed a growing human population will pose a considerable challenge for sheep production across the globe. High quality reference genomes and other genomic resources can help to meet these challenges by: (1) informing breeding programmes by adding a priori information about the genome, (2) providing tools such as pangenomes for characterising and conserving global genetic diversity, and (3) improving our understanding of fundamental biology using the power of genomic information to link cell, tissue and whole animal scale knowledge. In this review we describe recent advances in the genomic resources available for sheep, discuss how these might help to meet future challenges for sheep production, and provide some insight into what the future might hold.
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Affiliation(s)
- Shernae A Woolley
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
| | - Mazdak Salavati
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
- Scotland's Rural College, Parkgate, Barony Campus, Dumfries, DG1 3NE, UK
| | - Emily L Clark
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK.
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Intarapat S, Sukparangsi W, Gusev O, Sheng G. A Bird's-Eye View of Endangered Species Conservation: Avian Genomics and Stem Cell Approaches for Green Peafowl ( Pavo muticus). Genes (Basel) 2023; 14:2040. [PMID: 38002983 PMCID: PMC10671381 DOI: 10.3390/genes14112040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/30/2023] [Accepted: 11/02/2023] [Indexed: 11/26/2023] Open
Abstract
Aves ranks among the top two classes for the highest number of endangered and extinct species in the kingdom Animalia. Notably, the IUCN Red List classified the green peafowl as endangered. This highlights promising strategies using genetics and reproductive technologies for avian wildlife conservation. These platforms provide the capacity to predict population trends and enable the practical breeding of such species. The conservation of endangered avian species is facilitated through the application of genomic data storage and analysis. Storing the sequence is a form of biobanking. An analysis of sequence can identify genetically distinct individuals for breeding. Here, we reviewed avian genomics and stem cell approaches which not only offer hope for saving endangered species, such as the green peafowl but also for other birds threatened with extinction.
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Affiliation(s)
- Sittipon Intarapat
- Department of Anatomy, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Woranop Sukparangsi
- Department of Biology, Faculty of Science, Burapha University, Chonburi 20131, Thailand;
| | - Oleg Gusev
- Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan Federal University, 420008 Kazan, Russia;
- Intractable Disease Research Center, Graduate School of Medicine, Juntendo University, Tokyo 113-8421, Japan
- Life Improvement by Future Technologies (LIFT) Center, 143025 Moscow, Russia
| | - Guojun Sheng
- International Research Center for Medical Sciences, Kumamoto University, Kumamoto 860-0811, Japan;
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10
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Yang Y, Li X, Meng Z, Liu Y, Qian K, Chu M, Pan Z. A body map of super-enhancers and their function in pig. Front Vet Sci 2023; 10:1239965. [PMID: 37869495 PMCID: PMC10587440 DOI: 10.3389/fvets.2023.1239965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 09/26/2023] [Indexed: 10/24/2023] Open
Abstract
Introduction Super-enhancers (SEs) are clusters of enhancers that act synergistically to drive the high-level expression of genes involved in cell identity and function. Although SEs have been extensively investigated in humans and mice, they have not been well characterized in pigs. Methods Here, we identified 42,380 SEs in 14 pig tissues using chromatin immunoprecipitation sequencing, and statistics of its overall situation, studied the composition and characteristics of SE, and explored the influence of SEs characteristics on gene expression. Results We observed that approximately 40% of normal enhancers (NEs) form SEs. Compared to NEs, we found that SEs were more likely to be enriched with an activated enhancer and show activated functions. Interestingly, SEs showed X chromosome depletion and short interspersed nuclear element enrichment, implying that SEs play an important role in sex traits and repeat evolution. Additionally, SE-associated genes exhibited higher expression levels and stronger conservation than NE-associated genes. However, genes with the largest SEs had higher expression levels than those with the smallest SEs, indicating that SE size may influence gene expression. Moreover, we observed a negative correlation between SE gene distance and gene expression, indicating that the proximity of SEs can affect gene activity. Gene ontology enrichment and motif analysis revealed that SEs have strong tissue-specific activity. For example, the CORO2B gene with a brain-specific SE shows strong brain-specific expression, and the phenylalanine hydroxylase gene with liver-specific SEs shows strong liver-specific expression. Discussion In this study, we illustrated a body map of SEs and explored their functions in pigs, providing information on the composition and tissue-specific patterns of SEs. This study can serve as a valuable resource of gene regulatory and comparative analyses to the scientific community and provides a theoretical reference for genetic control mechanisms of important traits in pigs.
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Affiliation(s)
- Youbing Yang
- College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
| | - Xinyue Li
- College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
- Key Laboratory of Animal Genetics and Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhu Meng
- Key Laboratory of Animal Genetics and Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yongjian Liu
- College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
| | - Kaifeng Qian
- College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
| | - Mingxing Chu
- Key Laboratory of Animal Genetics and Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhangyuan Pan
- College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
- Key Laboratory of Animal Genetics and Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
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