본문 바로가기
KERD
논문KCI 등재

Identifying long non-coding RNAs and characterizing their functional roles in swine mammary gland from colostrogenesis to lactogenesis

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

Objective: This study was conducted to identify the functional long non-coding RNAs (lncRNAs) for swine lactation by RNA-seq data of mammary gland. Methods: According to the RNA-seq data of swine mammary gland, we screened lncRNAs, performed differential expression analysis, and confirmed the functional lncRNAs for swine lactation by validation of genome wide association study (GWAS) signals, functional annotation and weighted gene co-expression network analysis (WGCNA). Results: We totally identified 286 differentially expressed (DE) lncRNAs in mammary gland at different stages from 14 days prior to (-) parturition to day 1 after (+) parturition, and the expressions of most of lncRNAs were strongly changed from day -2 to day +1. Further, the GWAS signals of sow milk ability trait were significantly enriched in DE lncRNAs. Functional annotation revealed that these DE lncRNAs were mainly involved in mammary gland and lactation developing, milk composition metabolism and colostrum function. By performing weighted WGCNA, we identified 7 out of 12 lncRNA-mRNA modules that were highly associated with the mammary gland at day -14, day -2, and day +1, in which, 35 lncRNAs and 319 mRNAs were involved. Conclusion: This study suggested that 18 lncRNAs and their 20 target genes were promising candidates for swine parturition and colostrum occurrence processes. Our research provided new insights into lncRNA profiles and their regulating mechanisms from colostrogenesis to lactogenesis in swine.

Abstract

Objective: This study was conducted to identify the functional long non-coding RNAs (lncRNAs) for swine lactation by RNA-seq data of mammary gland. Methods: According to the RNA-seq data of swine mammary gland, we screened lncRNAs, performed differential expression analysis, and confirmed the functional lncRNAs for swine lactation by validation of genome wide association study (GWAS) signals, functional annotation and weighted gene co-expression network analysis (WGCNA). Results: We totally identified 286 differentially expressed (DE) lncRNAs in mammary gland at different stages from 14 days prior to (-) parturition to day 1 after (+) parturition, and the expressions of most of lncRNAs were strongly changed from day -2 to day +1. Further, the GWAS signals of sow milk ability trait were significantly enriched in DE lncRNAs. Functional annotation revealed that these DE lncRNAs were mainly involved in mammary gland and lactation developing, milk composition metabolism and colostrum function. By performing weighted WGCNA, we identified 7 out of 12 lncRNA-mRNA modules that were highly associated with the mammary gland at day -14, day -2, and day +1, in which, 35 lncRNAs and 319 mRNAs were involved. Conclusion: This study suggested that 18 lncRNAs and their 20 target genes were promising candidates for swine parturition and colostrum occurrence processes. Our research provided new insights into lncRNA profiles and their regulating mechanisms from colostrogenesis to lactogenesis in swine.

참고문헌 (35)

  1. Kim S, "Mammary gland growth and nutrient mobilization in lactating sows: a dynamic model to describe nutrient flow", pp.1999
  2. Boyd RD, "Metabolic precursors for milk synthesis" (1998), Wageningen Press
  3. Quesnel H, "Colostrum intake : Influence on piglet performance and factors of variation", Livest Sci, 146, pp.105~114 (2012)[DOI]
  4. Vadmand CN, "Impact of sow and litter characteristics on colostrum yield, time for onset of lactation, and milk yield of sows", J Anim Sci, 93, pp.2488~2500 (2015)[DOI]
  5. Hurley WL, "Review : Mammary gland development in swine : embryo to early lactation", Animal, 13, pp.S11~S19 (2019)[DOI]
  6. Balzani A, "Heritability of udder morphology and colostrum quality traits in swine", J Anim Sci, 94, pp.3636~3644 (2016)[DOI]
  7. Palombo V, "Transcriptional profiling of swine mammary gland during the transition from colostrogenesis to lactogenesis using RNA sequencing", BMC Genomics, 19, pp.322~ (2018)[DOI]
  8. Jin Y, "Identification of functional lncRNAs in pseudorabies virus type II infected cells", Vet Microbiol, 242, pp.108564~ (2020)[DOI]
  9. Liang G, "LncRNAnet : a comprehensive Sus scrofa lncRNA database", Anim Genet, 49, pp.632~635 (2018)[DOI]
  10. St Laurent G, "The Landscape of long noncoding RNA classification", Trends Genet, 31, pp.239~251 (2015)[DOI]
  11. Miao Z, "Identification and comparison of long non-conding RNA in Jinhua and Landrace pigs", Biochem Biophys Res Commun, 506, pp.765~771 (2018)[DOI]
  12. Huang W, "Genome-wide analysis of mRNAs and lncRNAs of intramuscular fat related to lipid metabolism in two pig breeds", Cell Physiol Biochem, 50, pp.2406~2422 (2018)[DOI]
  13. Wang J, "Comprehensive analysis of differentially expressed mRNA, lncRNA and circRNA and their ceRNA networks in the longissimus dorsi muscle of two different pig breeds", Int J Mol Sci, 20, pp.1107~ (2019)[DOI]
  14. Li S, "Identification and analysis of lncRNAs by whole-transcriptome sequencing in porcine preadipocytes induced by BMP2", Cytogenet Genome Res, 158, pp.133~144 (2019)[DOI]
  15. Wang Y, "Identification of non-coding and coding RNAs in porcine endometrium", Genomics, 109, pp.43~50 (2017)[DOI]
  16. Bolger AM, "Trimmomatic : a flexible trimmer for Illumina sequence data", Bioinformatics, 30, pp.2114~2120 (2014)[DOI]
  17. Pertea M, "StringTie enables improved reconstruction of a transcriptome from RNA-seq reads", Nat Biotechnol, 33, pp.290~295 (2015)[DOI]
  18. Guttman M, "Correction : Corrigendum : Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs(2010;28 : 503-10)", Nat Biotechnol, 28, pp.756~ (2010)[DOI]
  19. Ahmad A, "A k-mean clustering algorithm for mixed numeric and categorical data", Data Knowl Eng, 63, pp.503~527 (2007)[DOI]
  20. Cai WT, "Integrated small RNA sequencing, transcriptome and GWAS data reveal microRNA regulation in response to milk protein traits in Chinese Holstein cattle", Front Genet, 12, pp.726706~ (2021)
  21. Guil S, "Cis-acting noncoding RNAs : friends and foes", Nat Struct Mol Biol, 19, pp.1068~1075 (2012)[DOI]
  22. Derrien T, "The GENCODE v7catalog of human long noncoding RNAs : analysis of their gene structure, evolution, and expression", Genome Res, 22, pp.1775~1789 (2012)[DOI]
  23. Xie C, "KOBAS 2. 0 : a web server for annotation and identification of enriched pathways and diseases", Nucleic Acids Res, 39(Suppl_2), pp.W316~W322 (2011)
  24. Le K, "Gene and lncRNA co-expression network analysis reveals novel ceRNA network for triplenegative breast cancer", Sci Rep, 9, pp.15122~ (2019)[DOI]
  25. Langfelder P, "WGCNA : an R package for weighted correlation network analysis", BMC Bioinformatics, 9, pp.559~ (2008)[DOI]
  26. Kensinger RS, "Nucleic acid, metabolic and histological changes in gilt mammary tissue during pregnancy and lactogenesis", J Anim Sci, 54, pp.1297~1308 (1982)[DOI]
  27. Wang L, "Long noncoding RNA(lncRNA)-mediated competing endogenous RNA networks provide novel potential biomarkers and therapeutic targets for colorectal cancer", Int J Mol Sci, 20, pp.5758~ (2019)[DOI]
  28. Li X, "lncRNA H19", miR-675 axis regulates cardiomyocyte apoptosis by targeting VDAC1 in diabetic cardiomyopathy, 2016, pp.6, 36340~
  29. Nguyen DA, "Tight junction regulation in the mammary gland", J Mammary Gland Biol Neoplasia, 3, pp.233~246 (1998)[DOI]
  30. Kessler EC, "Short communication : Mammary gland tight junction permeability after parturition is greater in dairy cows with elevated circulating serotonin concentrations", J Dairy Sci, 102, pp.1768~1774 (2019)[DOI]
  31. Arrowsmith S, "Oxytocin : its mechanism of action and receptor signalling in the myometrium", J Neuroendocrinol, 26, pp.356~369 (2014)[DOI]
  32. Gimpl G, "The oxytocin receptor system : structure, function, and regulation", Physiol Rev, 81, pp.629~683 (2001)[DOI]
  33. Hennighausen L, "Signaling pathways in mammary gland development", Dev Cell, 1, pp.467~475 (2001)[DOI]
  34. Wan YH, "Maternal PPAR gamma protects nursing neonates by suppressing the production of inflammatory milk", Gene Dev, 21, pp.1895~1908 (2007)[DOI]
  35. Quesnel H, "Review : nutritional and endocrine control of colostrogenesis in swine", Animal, 13, pp.S26~S34 (2019)[DOI]

관련 논문AI추천

Genome-wide identification of long noncoding RNA genes and their potential association with mammary gland development in water buffaloFan Xinyang, Guo Wenbo, Huang Jing, Jin Yuhan, Miao Yongwang, Ouyang Yina아세아·태평양축산학회 · Animal Bioscience2022 · 제35권 제11호Long noncoding RNA network for lncRNA-mRNA interactions throughout swine estrous cycle reveals developmental and hormonal regulations in reproductive tissues임병휘, Chiwoong Lim, Jun-Mo Kim, Yoon-Been Park한국축산학회 · 한국축산학회지2024 · 제66권 제6호Long non-coding RNAs in Sus scrofa ileum under starvation stressCai Chunbo, Cao Guoqing, Gao Pengfei, Ge Xu Sheng, Guo Xiaohong, Liang Guo Ming, Li Bugao, Li Yong Shi, Lu Chang, Ma Yi Jia, Wang Shu, Yang Yang, Zhao Yan아세아·태평양축산학회 · Animal Bioscience2022 · 제35권 제7호The role of long noncoding RNAs in livestock adipose tissue deposition — A reviewChen Wei, Wang Lixue, Xie Yuhuai, Zeng Yongqing, Zhang Yu아세아·태평양축산학회 · Animal Bioscience2021 · 제34권 제7호Identification and functional prediction of long noncoding RNAs related to intramuscular fat content in Laiwu pigsChen Wei, Wang Lixue, Xie Yuhuai, Zeng Yongqing, Zhang Yu아세아·태평양축산학회 · Animal Bioscience2022 · 제35권 제1호Identification and functional prediction of long non-coding RNAs related to skeletal muscle development in Duroc pigsChen Wei, Li Shiyin, Ma Lixia, Qin Ming, Xue Hui, Zeng Yongqing, Zhang Yulun아세아·태평양축산학회 · Animal Bioscience2022 · 제35권 제10호

이 간행물의 다른 논문 (13건)