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Chen M, Gong L, Zhu L, Fang X, Zhang C, You Z, Chen H, Wei R, Wang R. Lipidomics combined with random forest machine learning algorithms to reveal freshness markers for duck eggs during storage in different rearing systems. Poult Sci 2024; 103:104201. [PMID: 39197340 PMCID: PMC11399630 DOI: 10.1016/j.psj.2024.104201] [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: 05/10/2024] [Revised: 07/29/2024] [Accepted: 08/05/2024] [Indexed: 09/01/2024] Open
Abstract
The differences in lipids in duck eggs between the 2 rearing systems during storage have not been fully studied. Herein, we propose untargeted lipidomics combined with a random forest (RF) algorithm to identify potential marker lipids based on ultra-performance liquid chromatography‒mass spectrometry (UPLPC-MS/MS). A total of 106 and 16 differential lipids (DL) were screened in egg yolk and white, respectively. In yolk, metabolic pathway analysis of DLs revealed that glycerophospholipid metabolism and sphingolipid metabolism were the key metabolic pathways in the traditional free-range system (TFS) during storage, glycosylphosphatidylinositol-anchored biosynthesis and glyceride metabolism were the key pathways in the floor-rearing system (FRS). In egg white, the key pathway in both systems is the biosynthesis of unsaturated fatty acids. Combined with RF algorithm, 12 marker lipids were screened during storage. Therefore, this study elucidates the changes in lipids in duck eggs during storage in 2 rearing systems and provides new ideas for screening marker lipids during storage. This approach is highly important for evaluating the quality of egg and egg products and provides guidance for duck egg production.
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Affiliation(s)
- Mengying Chen
- Institute of Quality Safety and Nutrition of Agricultural Products, Jiangsu Academy of Agricultural Sciences, Jiangsu Provincial Key Laboratory of Food Quality and Safety-Province and Ministry jointly built the cultivation base of the State Key Laboratory, Nanjing 210014, China; College of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Lan Gong
- Institute of Quality Safety and Nutrition of Agricultural Products, Jiangsu Academy of Agricultural Sciences, Jiangsu Provincial Key Laboratory of Food Quality and Safety-Province and Ministry jointly built the cultivation base of the State Key Laboratory, Nanjing 210014, China
| | - Lei Zhu
- Institute of Quality Safety and Nutrition of Agricultural Products, Jiangsu Academy of Agricultural Sciences, Jiangsu Provincial Key Laboratory of Food Quality and Safety-Province and Ministry jointly built the cultivation base of the State Key Laboratory, Nanjing 210014, China
| | - Xiaomin Fang
- Institute of Quality Safety and Nutrition of Agricultural Products, Jiangsu Academy of Agricultural Sciences, Jiangsu Provincial Key Laboratory of Food Quality and Safety-Province and Ministry jointly built the cultivation base of the State Key Laboratory, Nanjing 210014, China
| | - Can Zhang
- College of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Zhaorong You
- Gaoyou Duck Egg Association, Yangzhou 225600, China
| | | | - Ruicheng Wei
- Institute of Quality Safety and Nutrition of Agricultural Products, Jiangsu Academy of Agricultural Sciences, Jiangsu Provincial Key Laboratory of Food Quality and Safety-Province and Ministry jointly built the cultivation base of the State Key Laboratory, Nanjing 210014, China.
| | - Ran Wang
- Institute of Quality Safety and Nutrition of Agricultural Products, Jiangsu Academy of Agricultural Sciences, Jiangsu Provincial Key Laboratory of Food Quality and Safety-Province and Ministry jointly built the cultivation base of the State Key Laboratory, Nanjing 210014, China
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Wang G, Li M, Wang Y, Wang B, Pu H, Mao J, Zhang S, Zhou S, Luo P. Characterization of differentially expressed and lipid metabolism-related lncRNA-mRNA interaction networks during the growth of liver tissue through rabbit models. Front Vet Sci 2022; 9:998796. [PMID: 36118359 PMCID: PMC9477072 DOI: 10.3389/fvets.2022.998796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 08/10/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundCharacterization the long non-coding RNAs (lncRNAs) and their regulated mRNAs involved in lipid metabolism during liver growth and development is of great value for discovering new genomic biomarkers and therapeutic targets for fatty liver and metabolic syndrome.Materials and methodsLiver samples from sixteen rabbit models during the four growth stages (birth, weaning, sexual maturity, and somatic maturity) were used for RNA-seq and subsequent bioinformatics analyses. Differentially expressed (DE) lncRNAs and mRNAs were screened, and the cis/trans-regulation target mRNAs of DE lncRNAs were predicted. Then the function enrichment analyses of target mRNAs were performed through Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively. The target protein interaction (PPI) and lncRNA-mRNA co-expression networks were constructed using string version 11.0 platform and R Stats. Finally, six lncRNAs and six mRNAs were verified taking RT-qPCR.ResultsLiver Oil Red O detection found that the liver showed time-dependent accumulation of lipid droplets. 41,095 lncRNAs, 30,744 mRNAs, and amount to 3,384 DE lncRNAs and 2980 DE mRNAs were identified from 16 cDNA sequencing libraries during the growth of liver. 689 out of all DE lncRNAs corresponded to 440 DE mRNAs by cis-regulation and all DE mRNAs could be regulated by DE lncRNAs by trans-regulation. GO enrichment analysis showed significant enrichment of 892 GO terms, such as protein binding, cytosol, extracellular exsome, nucleoplasm, and oxidation-reduction process. Besides, 52 KEGG pathways were significantly enriched, including 11 pathways of lipid metabolism were found, like Arachidonic acid metabolism, PPAR signaling pathway and Biosynthesis of unsaturated fatty acids. After the low expression DE mRNAs and lncRNAs were excluded, we further obtained the 54 mRNAs were regulated by 249 lncRNAs. 351 interaction pairs were produced among 38 mRNAs and 215 lncRNAs through the co-expression analysis. The PPI network analysis found that 10 mRNAs such as 3β-Hydroxysteroid-Δ24 Reductase (DHCR24), lathosterol 5-desaturase (SC5D), and acetyl-CoA synthetase 2 (ACSS2) were highly interconnected hub protein-coding genes. Except for MSTRG.43041.1, the expression levels of the 11 genes by RT-qPCR were the similar trends to the RNA-seq results.ConclusionThe study revealed lncRNA-mRNA interation networks that regulate lipid metabolism during liver growth, providing potential research targets for the prophylaxis and treatment of related diseases caused by liver lipid metabolism disorders.
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Affiliation(s)
- Guoze Wang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Maolin Li
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
- College of Food and Biological Engineering, Chengdu University, Chengdu, China
| | - Yi Wang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Binbin Wang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Hanxu Pu
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Jinxin Mao
- College of Pharmaceutical Sciences, Southwest University, Chongqing, China
| | - Shuai Zhang
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Shi Zhou
- Department of Interventional Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
- *Correspondence: Shi Zhou
| | - Peng Luo
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang, China
- Peng Luo
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Du K, Bai X, Yang L, Shi Y, Chen L, Wang H, Cai M, Wang J, Chen S, Jia X, Lai S. De Novo Reconstruction of Transcriptome Identified Long Non-Coding RNA Regulator of Aging-Related Brown Adipose Tissue Whitening in Rabbits. BIOLOGY 2021; 10:biology10111176. [PMID: 34827171 PMCID: PMC8614855 DOI: 10.3390/biology10111176] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/10/2021] [Accepted: 11/11/2021] [Indexed: 01/16/2023]
Abstract
Simple Summary Brown adipose tissues (BATs) undergo the conversion to white adipose tissues (WATs) with age. Long non-coding RNAs (lncRNAs) were widely involved in adipose biology. Rabbit is an ideal model for studying the dynamics of the transformation from BATs to WATs. However, our knowledge of lncRNAs that mediate the transformation remains unknown in rabbits. By histological analysis and sequencing, we found rabbit interscapular adipose tissues (iATs) from BATs to WATs within two years and identified a total of 631 differentially expressed lncRNAs (DELs) during the transformation process. Several signal pathways were involved in the transformation from BAT to WAT. A novel lncRNA that was highly expressed in iATs of aged rabbits was validated to impair brown adipocyte differentiation in vitro. Our study provided a comprehensive catalog of lncRNAs involved in the transformation from BATs to WATs in rabbits, facilitating a better understanding of adipose biology. Abstract Brown adipose tissues (BATs) convert to a “white-like” phenotype with age, which is also known as “aging-related BAT whitening (ARBW)”. Emerging evidence suggested that long non-coding RNAs (lncRNAs) were widely involved in adipose biology. Rabbit is an ideal model for studying the dynamics of ARBW. In this study, we performed histological analysis and strand-specific RNA-sequencing (ssRNA-seq) of rabbit interscapular adipose tissues (iATs). Our data indicated that the rabbit iATs underwent the ARBW from 0 days to 2 years and a total of 2281 novel lncRNAs were identified in the iATs. The classical rabbit BATs showed low lncRNA transcriptional complexity compared to white adipose tissues (WATs). A total of 631 differentially expressed lncRNAs (DELs) were identified in four stages. The signal pathways of purine metabolism, Wnt signaling pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway, cyclic guanosine monophosphate (cGMP)/cGMP-dependent protein kinase (cGMP-PKG) signaling pathway and lipid and atherosclerosis were significantly enriched by the DELs with unique expression patterns. A novel lncRNA that was highly expressed in the iATs of aged rabbits was validated to impair brown adipocyte differentiation in vitro. Our study provided a comprehensive catalog of lncRNAs involved in ARBW in rabbits, which facilitates a better understanding of adipose biology.
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Affiliation(s)
- Kun Du
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Xue Bai
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Li Yang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Yu Shi
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Li Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Haoding Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Mingchen Cai
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
- College of Landscape Architecture and Life Science/Institute of Special Plants, Chongqing University of Arts and Sciences, Chongqing 402160, China
| | - Jie Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Shiyi Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Xianbo Jia
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
| | - Songjia Lai
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, 211# Huimin Road, Chengdu 611130, China; (K.D.); (X.B.); (L.Y.); (Y.S.); (L.C.); (H.W.); (M.C.); (J.W.); (S.C.); (X.J.)
- Correspondence: or
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