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Tong X, Li X, Wang Y, Xie F, Li R, Ren M, Hu Q, Li S. Comprehensive analysis of mRNA and miRNA differential expression profiles in the hypothalamus-pituitary-gonadal axis in laying and broodiness period of Wanxi white geese. Poult Sci 2024; 104:104510. [PMID: 39549391 DOI: 10.1016/j.psj.2024.104510] [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: 08/18/2024] [Revised: 10/22/2024] [Accepted: 11/04/2024] [Indexed: 11/18/2024] Open
Abstract
The hypothalamus-pituitary-gonadal (HPG) axis is an important neuroendocrine regulatory center involved in egg-laying process in poultry. However, its mechanism of regulating broodiness behavior and laying performance in geese remains unclear. This study explored the molecular mechanism by which the HPG axis regulates brooding behavior in Wanxi white geese (WWG). The hypothalamus, pituitary, and ovarian tissues of Wanxi white geese were collected at laying and brooding periods for transcriptome sequencing analysis. A total of 240 (BH vs. LH), 319 (BP vs. LP), and 445 (BO vs. LO) differentially expressed genes, and 56 (BH vs. LH), 82 (BP vs. LP), and 48 (BO vs. LO) differentially expressed miRNAs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis showed that differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were significantly enriched in hormone level regulation, cell communication, calcium signaling pathway, GnRH signaling pathway, MAPK signaling pathway, Wnt signaling pathway, and other processes. Six DEGs and four DEMs were randomly selected for real-time fluorescence quantitative reverse transcription PCR (RT-qPCR). The results showed that the transcriptome sequencing data were accurate and reliable. In addition, 22 potential hub miRNAs were screened. Dual luciferase reporter assays confirmed the targeting relationship between miR-144-y and DIO3. The results showed that the miRNAs mainly regulated the laying performance and brooding behavior of WWG by mediating the expression of target genes. In this study, we systematically elucidated the mechanisms by which the HPG axis regulates the broodiness behavior and laying performance of WWG at the post-transcriptional level. Several miRNAs and mRNAs associated with the reproductive performance of WWG were identified, providing a crucial reference for the subsequent use of gene editing technologies to breed new varieties and advance the development of WWG breeding industry.
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Affiliation(s)
- Xinwei Tong
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Xiaojin Li
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Yuhua Wang
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Fei Xie
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Ruidong Li
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Man Ren
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Qianqian Hu
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China
| | - Shenghe Li
- College of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China; Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Chuzhou 233100, China.
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Wang H, Chen Z, Ma L, Wu Y, Zhao X, Zhang K, Xue J, Luo Y, Wang C, Liu Z, Xie Y, Chen Y, Gao G, Wang Q. Identification of Single Nucleotide Polymorphisms Through Genome-Wide Association Studies of pH Traits in Goose Meat. BIOLOGY 2024; 13:865. [PMID: 39596820 PMCID: PMC11592244 DOI: 10.3390/biology13110865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 10/18/2024] [Accepted: 10/21/2024] [Indexed: 11/29/2024]
Abstract
The genetic regulation of goose meat quality traits remains relatively unexplored, and the underlying mechanisms are yet to be elucidated. This study aims to employ single nucleotide polymorphism (SNP) genotyping in conjunction with genome-wide association studies (GWAS) to investigate critical candidate regions and genes associated with the pH trait of meat in Sichuan white geese. A cohort of 203 healthy male Sichuan white geese was randomly selected and slaughtered at 70 days of age. Measurements were taken of meat pH, growth parameters, body dimensions, and post-slaughter traits. High-throughput sequencing on the Illumina HiSeq X Ten platform facilitated gene resequencing and SNP evaluation, and GWAS was employed to detect key genes within quantitative trait loci (QTL) intervals. The sequencing of 203 individuals yielded a total of 2601.19 Gb of genomic data, with an average sequencing depth of 10.89×. Through GWAS analysis, a total of 30 SNPs associated with pH were identified. These SNPs were identified on multiple chromosomes, including on chromosome 17 (chr: 23.57-23.68 Mb) and chromosome 13 (chr13: 31.52-31.61 Mb). By annotating these associated SNPs, nine candidate genes (including C19L2, AMFR, POL, RERGL, ZN484, GMDS, WAC) associated with the pH of goose meat were identified. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) genotyping of 10 SNPs centered on these nine candidate genes was confirmed. GO enrichment analysis revealed that genes within 1 Mb of the associated SNPs are significantly enriched in pathways involved in lymphocyte activation, in response to hydrogen peroxide, Salmonella infection, and other metabolic processes. This study explores the gene regulatory pathways influencing pH traits in goose meat and provides molecular markers for enhancing meat quality. These findings are expected to facilitate the advancement of molecular breeding programs in geese.
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Affiliation(s)
- Haiwei Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Zhuping Chen
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Lin Ma
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Yifan Wu
- College of Animal Science and Technology, Southwest University, Chongqing 402460, China;
| | - Xianzhi Zhao
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Keshan Zhang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Jiajia Xue
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Yi Luo
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Chao Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Zuohua Liu
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Youhui Xie
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Ying Chen
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Guangliang Gao
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
| | - Qigui Wang
- Chongqing Engineering Research Center of Goose Genetic Improvement, Institute of Poultry Science, Chongqing Academy of Animal Science, Chongqing 402460, China; (H.W.); (Z.C.); (L.M.); (X.Z.); (K.Z.); (J.X.); (Y.L.); (C.W.); (Z.L.); (Y.X.); (Y.C.)
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Liu J, Shi Y, Mo D, Luo L, Xu S, Lv F. The goat pan-genome reveals patterns of gene loss during domestication. J Anim Sci Biotechnol 2024; 15:132. [PMID: 39367490 PMCID: PMC11453020 DOI: 10.1186/s40104-024-01092-7] [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: 05/31/2024] [Accepted: 08/19/2024] [Indexed: 10/06/2024] Open
Abstract
BACKGROUND Unveiling genetic diversity features and understanding the genetic mechanisms of diverse goat phenotypes are pivotal in facilitating the preservation and utilization of these genetic resources. However, the total genetic diversity within a species can't be captured by the reference genome of a single individual. The pan-genome is a collection of all the DNA sequences that occur in a species, and it is expected to capture the total genomic diversity of the specific species. RESULTS We constructed a goat pan-genome using map-to-pan assemble based on 813 individuals, including 723 domestic goats and 90 samples from their wild relatives, which presented a broad regional and global representation. In total, 146 Mb sequences and 974 genes were identified as absent from the reference genome (ARS1.2; GCF_001704415.2). We identified 3,190 novel single nucleotide polymorphisms (SNPs) using the pan-genome analysis. These novel SNPs could properly reveal the population structure of domestic goats and their wild relatives. Presence/absence variation (PAV) analysis revealed gene loss and intense negative selection during domestication and improvement. CONCLUSIONS Our research highlights the importance of the goat pan-genome in capturing the missing genetic variations. It reveals the changes in genomic architecture during goat domestication and improvement, such as gene loss. This improves our understanding of the evolutionary and breeding history of goats.
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Affiliation(s)
- Jiaxin Liu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yilong Shi
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Dongxin Mo
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Lingyun Luo
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Songsong Xu
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Fenghua Lv
- Frontiers Science Center for Molecular Design Breeding (MOE); State Key Laboratory of Animal Biotech Breeding; College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Wadood AA, Zhang X. The Omics Revolution in Understanding Chicken Reproduction: A Comprehensive Review. Curr Issues Mol Biol 2024; 46:6248-6266. [PMID: 38921044 PMCID: PMC11202932 DOI: 10.3390/cimb46060373] [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: 05/16/2024] [Revised: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024] Open
Abstract
Omics approaches have significantly contributed to our understanding of several aspects of chicken reproduction. This review paper gives an overview of the use of omics technologies such as genomics, transcriptomics, proteomics, and metabolomics to elucidate the mechanisms of chicken reproduction. Genomics has transformed the study of chicken reproduction by allowing the examination of the full genetic makeup of chickens, resulting in the discovery of genes associated with reproductive features and disorders. Transcriptomics has provided insights into the gene expression patterns and regulatory mechanisms involved in reproductive processes, allowing for a better knowledge of developmental stages and hormone regulation. Furthermore, proteomics has made it easier to identify and quantify the proteins involved in reproductive physiology to better understand the molecular mechanisms driving fertility, embryonic development, and egg quality. Metabolomics has emerged as a useful technique for understanding the metabolic pathways and biomarkers linked to reproductive performance, providing vital insights for enhancing breeding tactics and reproductive health. The integration of omics data has resulted in the identification of critical molecular pathways and biomarkers linked with chicken reproductive features, providing the opportunity for targeted genetic selection and improved reproductive management approaches. Furthermore, omics technologies have helped to create biomarkers for fertility and embryonic viability, providing the poultry sector with tools for effective breeding and reproductive health management. Finally, omics technologies have greatly improved our understanding of chicken reproduction by revealing the molecular complexities that underpin reproductive processes.
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Affiliation(s)
- Armughan Ahmed Wadood
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangzhou 510642, China;
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou 510642, China
| | - Xiquan Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangzhou 510642, China;
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou 510642, China
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Liu X, Zheng J, Ding J, Wu J, Zuo F, Zhang G. When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications. Genes (Basel) 2024; 15:245. [PMID: 38397234 PMCID: PMC10888458 DOI: 10.3390/genes15020245] [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: 12/23/2023] [Revised: 01/30/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024] Open
Abstract
Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.
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Affiliation(s)
- Xinyue Liu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Junyuan Zheng
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jialan Ding
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jiaxin Wu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Fuyuan Zuo
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
| | - Gongwei Zhang
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
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