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Sığır türünde gen ifadesi ve RNA-dizileme alanında yapılan çalışmaların bibliyometrik analizi

Year 2024, Volume: 95 Issue: 2, 115 - 131, 15.06.2024
https://doi.org/10.33188/vetheder.1449573

Abstract

Bu çalışmanın amacı; Web of Science (WOS) veri tabanında 2010-2023 yılları arasında sığır türünde “gen ifadesi ve RNA-dizileme” konusunun incelendiği araştırma makalelerinin bilimsel haritalama yöntemiyle gelişiminin incelenmesidir. Bu hususta ilgili anahtar kelimeler kullanılarak ilk taramada 500 adet makale incelenmiş ve analize uygun 353 makale Bibliometrix R paketinin Shiny web uygulaması ve bazı analizler VOSviewer uygulaması ile analiz edilmiştir. Yapılan analizler; ana veri bilgileri, yıllık bilimsel üretim, ülkeler ve kurum analizleri, kaynaklarla bibliyografik eşleştirme, Bradford analizi, Lotka kanunu analizi, en çok alıntı yapılan makaleler ve en etkili yazarlar gibi alt başlıkları içermektedir. Analiz sonrası elde edilen sonuçlara göre ilgili alanda en çok çalışma yapan ilişkili kurumun “Universidade De Sao Paulo” olduğu, en çok yayın yapan ülkenin ABD olduğu, en çok yayın yapılan derginin “BMC Genomics” olduğu belirlenmiştir. Anahtar kelime analizine göre son yıllarda öne çıkan konuların mastitis, süt sığırcılığı ve ısı stresi konuları olduğu belirlenmiştir. Çalışmaların reproduktif sistem, immun sistem ve hastalıklar, et ve süt sığır üretimi ile ilişkili olmak üzere farklı kümelere ayrıldığı belirlenmiştir. Sığır türünde bu araştırma alanında çalışma planlayacak araştırmacıların araştırmalarını tasarlama, yayınlanacağı dergiyi belirleme ya da kurumsal bağlantıların kurulmasında bildirilen çalışmayı inceleyerek planlama yapmaları önerilmektedir.

Ethical Statement

Bu makaledeki sunulan verilerin, bilgilerin ve dokümanların akademik ve etik kurallar çerçevesinde elde edildiği, tüm bilgi, belge, değerlendirme ve sonuçlarının bilimsel etik ve ahlak kurallarına uygun olarak sunulduğuna dair yazarlardan etik beyan alınmıştır.

References

  • Law J, Bauin S, Courtial JP, Whittaker J. Policy and the mapping of scientific change: a co-word analysis of research into environmental acidification. Scientometrics 1988;14:251–264.
  • Cánovas A, Rincon G, Islas-Trejo A, Wickramasinghe S, Medrano JF. SNP discovery in the bovine milk transcriptome using RNA-Seq technology. Mamm Genome 2010;11-12:592–598.
  • Huang W, Khatib H. Comparison of transcriptomic landscapes of bovine embryos using RNA-Seq. BMC Genomics 2010;11:711.
  • Mamo S, Mehta JP, Forde N, McGettigan P, Lonergan P. Conceptus-endometrium crosstalk during maternal recognition of pregnancy in cattle. Biol Reprod 2012;87(1):6, 1–9.
  • McGettigan PA, Browne JA, Carrington SD, Crowe MA, Fair T, Forde N, et al. Fertility and genomics: comparison of gene expression in contrasting reproductive tissues of female cattle. Reprod Fertil Dev 2016;28(1-2):11–24.
  • Bahrami A, Miraie-Ashtiani SR, Sadeghi M, Najafi A. miRNA-mRNA network involved in folliculogenesis interactome: systems biology approach. Reproduction 2017;154(1):51–65.
  • Wang N, Li CY, Zhu HB, Hao HS, Wang HY, Yan CL, et al. Effect of vitrification on the mRNA transcriptome of bovine oocytes. Reprod Domest Anim 2017;52(4):531–541.
  • Passaro C, Tutt D, Bagés-Arnal S, Maicas C, Laguna-Barraza R, Gutierrez-Adán A, et al. Global transcriptomic response of bovine endometrium to blastocyst-stage embryos. Reproduction 2019;158(3):223–235.
  • Prakash MA, Kumaresan A, Ebenezer Samuel King JP, Nag P, Sharma A, Sinha MK, et al. Comparative Transcriptomic Analysis of Spermatozoa From High- and Low-Fertile Crossbred Bulls: Implications for Fertility Prediction. Front Cell Dev Biol 202;9:647717.
  • Xu X, Bai J, Liu K, Xiao L, Qin Y, Gao M, et al. Association of Metabolic and Endocrine Disorders with Bovine Ovarian Follicular Cysts. Animals (Basel) 2023;13(21):3301.
  • Nalpas NC, Park SD, Magee DA, Taraktsoglou M, Browne JA, Conlon KM, et al. Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro. BMC Genomics. 2013;14:230.
  • Liang G, Malmuthuge N, Bao H, Stothard P, Griebel PJ, Guan le L. Transcriptome analysis reveals regional and temporal differences in mucosal immune system development in the small intestine of neonatal calves. BMC Genomics. 2016;17(1):602.
  • Pošćić N, Montanari T, D'Andrea M, Licastro D, Pilla F, Ajmone-Marsan P, et al. Breed and adaptive response modulate bovine peripheral blood cells' transcriptome. J Anim Sci Biotechnol 2017;8:11.
  • Barreto DM, Barros GS, Santos LABO, Soares RC, Batista MVA. Comparative transcriptomic analysis of bovine papillomatosis. BMC Genomics 2018;19(1):949.
  • Scott MA, Woolums AR, Swiderski CE, Perkins AD, Nanduri B, Smith DR, et al. Whole blood transcriptomic analysis of beef cattle at arrival identifies potential predictive molecules and mechanisms that indicate animals that naturally resist bovine respiratory disease. PLoS One 2020;15(1):e0227507.
  • He H, Liu X. Characterization of transcriptional complexity during longissimus muscle development in bovines using high-throughput sequencing. PLoS One 2013;8(6):e64356.
  • Sheng X, Ni H, Liu Y, Li J, Zhang L, Guo Y. RNA-seq analysis of bovine intramuscular, subcutaneous and perirenal adipose tissues. Mol Biol Rep 2014;41(3):1631–1637.
  • Liu G F, Cheng HJ, You W, Song EL, Liu XM, Wan FC. Transcriptome profiling of muscle by RNA-Seq reveals significant differences in digital gene expression profiling between Angus and Luxi cattle. Anim Prod Sci 2015; 55:1172–1178.
  • Tizioto PC, Coutinho LL, Decker JE, Schnabel RD, Rosa KO, Oliveira PS, et al. Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes. BMC Genomics 2015;16(1):242.
  • Keogh K, Kenny DA, Kelly AK, Waters SM. Insulin secretion and signaling in response to dietary restriction and subsequent re-alimentation in cattle. Physiol Genomics 2015;47(8):344–354.
  • Wærp HKL, Waters SM, McCabe MS, Cormican P, Salte R. RNA-seq analysis of bovine adipose tissue in heifers fed diets differing in energy and protein content. PLoS One 2018;13(9):e0201284.
  • de Las Heras-Saldana S, Chung KY, Lee SH, Gondro C. Gene expression of Hanwoo satellite cell differentiation in longissimus dorsi and semimembranosus. BMC Genomics 2019;20(1):156.
  • Wu ZL, Chen SY, Qin C, Jia X, Deng F, Wang J, et al. Clinical Ketosis-Associated Alteration of Gene Expression in Holstein Cows. Genes (Basel) 2020;11(2):219.
  • Chen W, Alexandre PA, Ribeiro G, Fukumasu H, Sun W, Reverter A, et al. Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data. Front Genet 2021;12:619857.
  • Li Q, Wang Y, Hu X, Zhang Y, Li H, Zhang Q, et al. Transcriptional states and chromatin accessibility during bovine myoblasts proliferation and myogenic differentiation. Cell Prolif 2022;55(5):e13219.
  • Raven LA, Cocks BG, Kemper KE, Chamberlain AJ, Vander Jagt CJ, Goddard ME, et al. Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle. Mamm Genome 2016;27(1-2):81–97.
  • Yang J, Jiang J, Liu X, Wang H, Guo G, Zhang Q, et al. Differential expression of genes in milk of dairy cattle during lactation. Anim Genet. 2016;47(2):174–180.
  • Ahmad SM, Bhat B, Manzoor Z, Dar MA, Taban Q, Ibeagha-Awemu EM, et al. Genome wide expression analysis of circular RNAs in mammary epithelial cells of cattle revealed difference in milk synthesis. PeerJ 2022;10:e13029.
  • Aria M, Cuccurullo C. Bibliometrix: An R-Tool for Comprehensive Science Mapping Analysis. J Informetr 2017;11, 959–975.
  • van Eck NJ, Waltman L. Software Survey: VOSviewer, a Computer Program for Bibliometric Mapping. Scientometrics 2010; 84, 523–538.
  • Bogliotti YS, Wu J, Vilarino M, Okamura D, Soto DA et al. Efficient derivation of stable primed pluripotent embryonic stem cells from bovine blastocysts. Proc Natl Acad Sci 2018;115(9):2090–2095.
  • Jiang Z, Sun J, Dong H, Luo O, Zheng X, Obergfell C, et al. Transcriptional profiles of bovine in vivo pre-implantation development. BMC Genomics 2014;15(1):756.
  • Li M, Sun X, Cai H, Sun Y, Plath M, Li C, et al. Long non-coding RNA ADNCR suppresses adipogenic differentiation by targeting miR-204. Biochim Biophys Acta 2016;1859(7):871–882.
  • Jin W, Ibeagha-Awemu EM, Liang G, Beaudoin F, Zhao X, Guan le L. Transcriptome microRNA profiling of bovine mammary epithelial cells challenged with Escherichia coli or Staphylococcus aureus bacteria reveals pathogen directed microRNA expression profiles. BMC Genomics 2014;15:181.
  • Ruhanen L, Weiler B, Moyle BD, McLennan CLJ. Trends and patterns in sustainable tourism research: A 25-year bibliometric analysis. J Sustain Tour 2015; 23(4):517–535.
  • Silva-Vignato B, Cesar ASM, Afonso J, Moreira GCM, Poleti MD, Petrini J, et al. Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness. Front Genet 2022; 13:935238.
  • Cardoso TF, Coutinho LL, Bruscadin JJ, da Silva Diniz WJ, Petrini J, Andrade BGN, et al. Multi-Omics Approach Reveals miR-SNPs Affecting Muscle Fatty Acids Profile in Nelore Cattle. Genes 2021;12(1):67.
  • de Lima AO, Koltes JE, Diniz WJS, de Oliveira PSN, Cesar ASM, Tizioto PC, et al. Potential Biomarkers for Feed Efficiency-Related Traits in Nelore Cattle Identified by Co-expression Network and Integrative Genomics Analyses. Front Genet 2020;11:189.
  • Diniz WJS, Mazzoni G, Coutinho LL, Banerjee P, Geistlinger L, Cesar ASM, et al. Detection of Co-expressed Pathway Modules Associated With Mineral Concentration and Meat Quality in Nelore Cattle. Front Genet 2019;10:210.
  • Silva-Vignato B, Coutinho LL, Cesar ASM, Poleti MD, Regitano LCA, Balieiro JCC. Comparative muscle transcriptome associated with carcass traits of Nellore cattle. BMC Genomics 2017;18(1):506.
  • Berton MP, Fonseca LF, Gimenez DF, Utembergue BL, Cesar AS, Coutinho LL, et al. Gene expression profile of intramuscular muscle in Nellore cattle with extreme values of fatty acid. BMC Genomics 2016;17(1):972.
  • Cesar AS, Regitano LC, Poleti MD, Andrade SC, Tizioto PC, Oliveira PS et al. Differences in the skeletal muscle transcriptome profile associated with extreme values of fatty acids content. BMC genomics 2016;17(1):961.
  • Sá Filho MF, Gonella-Diaza AM, Sponchiado M, Mendanha MF, Pugliesi G, Ramos RDS, et al. Impact of hormonal modulation at proestrus on ovarian responses and uterine gene expression of suckled anestrous beef cows. J Anim Sci Biotechnol 2017; 8:79.
  • Mesquita FS, Ramos RS, Pugliesi G, Andrade SC, Van Hoeck V, Langbeen A, et al. Endometrial transcriptional profiling of a bovine fertility model by Next-Generation Sequencing. Genom Data 2015;7:26–28.
  • Van Hoeck V, Scolari SC, Pugliesi G, Gonella-Diaza AM, Andrade SC, Gasparin GR, et al. Gene expression profiling by high throughput sequencing to determine signatures for the bovine receptive uterus at early gestation. Genom Data 2015;5:94–96.
  • Gonella-Diaza AM, Andrade SC, Sponchiado M, Pugliesi G, Mesquita FS, Van Hoeck V, et al. Size of the Ovulatory Follicle Dictates Spatial Differences in the Oviductal Transcriptome in Cattle. PloS one 2015;10(12):e0145321.
  • Kang X, Li C, Liu S, Baldwin RL, Liu GE, Li CJ. Genome-Wide Acetylation Modification of H3K27ac in Bovine Rumen Cell Following Butyrate Exposure. Biomolecules 2023;13(7):1137.
  • Li CJ, Lin S, Ranilla-García MJ, Baldwin RL. Transcriptomic Profiling of Duodenal Epithelium Reveals Temporally Dynamic Impacts of Direct Duodenal Starch-Infusion During Dry Period of Dairy Cattle. Front Vet Sci 2019;6:214.
  • Shin JH, Li RW, Gao Y, Bickhart DM, Liu GE, Li W, et al. Butyrate Induced IGF2 Activation Correlated with Distinct Chromatin Signatures Due to Histone Modification. Gene regulation and systems biology 2013;7:57–70.
  • Li M, Sun X, Cai H, Sun Y, Plath M, Li C, et al. Long non-coding RNA ADNCR suppresses adipogenic differentiation by targeting miR-204. Biochim Biophys Acta 2016;1859(7):871–882.
  • Zhou Y, Liu S, Hu Y, Fang L, Gao Y, Xia H, et al. Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns. BMC Biol 2020;18(1):85.
  • Liu S, Gao Y, Canela-Xandri O, Wang S, Yu Y, Cai W, et al. A multi-tissue atlas of regulatory variants in cattle. Nat Genet 2022;54(9):1438–1447.
  • Passaro C, Tutt D, Bagés-Arnal S, Maicas C, Laguna-Barraza R, Gutierrez-Adán A, et al. Global transcriptomic response of bovine endometrium to blastocyst-stage embryos. Reprod 2019;158(3): 223–235.
  • McGettigan PA, Browne JA, Carrington SD, Crowe MA, Fair T, Forde N, et al. Fertility and genomics: comparison of gene expression in contrasting reproductive tissues of female cattle. Reprod Fertil Dev 2016;28(1-2):11–24.
  • McLoughlin KE, Correia CN, Browne JA, Magee DA, Nalpas NC, Rue-Albrecht K, et al. RNA-Seq Transcriptome Analysis of Peripheral Blood From Cattle Infected With Mycobacterium bovis Across an Experimental Time Course. Front Vet Sci 2021;8:662002.
  • Hall TJ, Mullen MP, McHugo GP, Killick KE, Ring SC, Berry DP, et al. Integrative genomics of the mammalian alveolar macrophage response to intracellular mycobacteria. BMC Genomics 2021;22(1):343.
  • McLoughlin KE, Nalpas NC, Rue-Albrecht K, Browne JA, Magee DA, Killick KE, et al. RNA-seq Transcriptional Profiling of Peripheral Blood Leukocytes from Cattle Infected with Mycobacterium bovis. Front Immunol 2014;5:396.

Bibliometric analysis of studies on gene expression and RNA-seq in cattle species

Year 2024, Volume: 95 Issue: 2, 115 - 131, 15.06.2024
https://doi.org/10.33188/vetheder.1449573

Abstract

The aim of this study is to examine the development of research articles on "gene expression and RNA-seq" in cattle species in the Web of Science (WOS) database between 2010 and 2023 using bibliometric mapping methods. Initially, 500 articles were screened using relevant keywords, and 353 articles suitable for analysis were analyzed using the Bibliometrix R package's shiny web application and some analyses were conducted using the VOSviewer application. The conducted analyses included subheadings such as main data information, annual scientific production, countries, and institution analysis, bibliographic coupling with sources, Bradford analysis, Lotka’s law analyasis, highly cited articles, and most influential authors. According to the results obtained after the analysis, it was determined that the institution conducting the most studies in the relevant field is "Universidade De Sao Paulo", the country with the most publications is the USA, and the most published journal is "BMC Genomics". Keyword analysis revealed that the trending topics in recent years are mastitis, dairy cattle farming, and heat stress. The studies were categorized into different clusters related to the reproductive system, immune system and diseases, meat and dairy cattle production. It is recommended that researchers planning to work in this research area on cattle species should design their research, determine the journal to be published, or establish institutional connections by examining the reported study and planning accordingly.

Ethical Statement

Ethical statements have been obtained from the authors confirming that the data, information, and documents presented in this article have been obtained within the framework of academic and ethical rules and that all information, documents, evaluations, and results are presented by scientific ethics and moral rules.

References

  • Law J, Bauin S, Courtial JP, Whittaker J. Policy and the mapping of scientific change: a co-word analysis of research into environmental acidification. Scientometrics 1988;14:251–264.
  • Cánovas A, Rincon G, Islas-Trejo A, Wickramasinghe S, Medrano JF. SNP discovery in the bovine milk transcriptome using RNA-Seq technology. Mamm Genome 2010;11-12:592–598.
  • Huang W, Khatib H. Comparison of transcriptomic landscapes of bovine embryos using RNA-Seq. BMC Genomics 2010;11:711.
  • Mamo S, Mehta JP, Forde N, McGettigan P, Lonergan P. Conceptus-endometrium crosstalk during maternal recognition of pregnancy in cattle. Biol Reprod 2012;87(1):6, 1–9.
  • McGettigan PA, Browne JA, Carrington SD, Crowe MA, Fair T, Forde N, et al. Fertility and genomics: comparison of gene expression in contrasting reproductive tissues of female cattle. Reprod Fertil Dev 2016;28(1-2):11–24.
  • Bahrami A, Miraie-Ashtiani SR, Sadeghi M, Najafi A. miRNA-mRNA network involved in folliculogenesis interactome: systems biology approach. Reproduction 2017;154(1):51–65.
  • Wang N, Li CY, Zhu HB, Hao HS, Wang HY, Yan CL, et al. Effect of vitrification on the mRNA transcriptome of bovine oocytes. Reprod Domest Anim 2017;52(4):531–541.
  • Passaro C, Tutt D, Bagés-Arnal S, Maicas C, Laguna-Barraza R, Gutierrez-Adán A, et al. Global transcriptomic response of bovine endometrium to blastocyst-stage embryos. Reproduction 2019;158(3):223–235.
  • Prakash MA, Kumaresan A, Ebenezer Samuel King JP, Nag P, Sharma A, Sinha MK, et al. Comparative Transcriptomic Analysis of Spermatozoa From High- and Low-Fertile Crossbred Bulls: Implications for Fertility Prediction. Front Cell Dev Biol 202;9:647717.
  • Xu X, Bai J, Liu K, Xiao L, Qin Y, Gao M, et al. Association of Metabolic and Endocrine Disorders with Bovine Ovarian Follicular Cysts. Animals (Basel) 2023;13(21):3301.
  • Nalpas NC, Park SD, Magee DA, Taraktsoglou M, Browne JA, Conlon KM, et al. Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro. BMC Genomics. 2013;14:230.
  • Liang G, Malmuthuge N, Bao H, Stothard P, Griebel PJ, Guan le L. Transcriptome analysis reveals regional and temporal differences in mucosal immune system development in the small intestine of neonatal calves. BMC Genomics. 2016;17(1):602.
  • Pošćić N, Montanari T, D'Andrea M, Licastro D, Pilla F, Ajmone-Marsan P, et al. Breed and adaptive response modulate bovine peripheral blood cells' transcriptome. J Anim Sci Biotechnol 2017;8:11.
  • Barreto DM, Barros GS, Santos LABO, Soares RC, Batista MVA. Comparative transcriptomic analysis of bovine papillomatosis. BMC Genomics 2018;19(1):949.
  • Scott MA, Woolums AR, Swiderski CE, Perkins AD, Nanduri B, Smith DR, et al. Whole blood transcriptomic analysis of beef cattle at arrival identifies potential predictive molecules and mechanisms that indicate animals that naturally resist bovine respiratory disease. PLoS One 2020;15(1):e0227507.
  • He H, Liu X. Characterization of transcriptional complexity during longissimus muscle development in bovines using high-throughput sequencing. PLoS One 2013;8(6):e64356.
  • Sheng X, Ni H, Liu Y, Li J, Zhang L, Guo Y. RNA-seq analysis of bovine intramuscular, subcutaneous and perirenal adipose tissues. Mol Biol Rep 2014;41(3):1631–1637.
  • Liu G F, Cheng HJ, You W, Song EL, Liu XM, Wan FC. Transcriptome profiling of muscle by RNA-Seq reveals significant differences in digital gene expression profiling between Angus and Luxi cattle. Anim Prod Sci 2015; 55:1172–1178.
  • Tizioto PC, Coutinho LL, Decker JE, Schnabel RD, Rosa KO, Oliveira PS, et al. Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes. BMC Genomics 2015;16(1):242.
  • Keogh K, Kenny DA, Kelly AK, Waters SM. Insulin secretion and signaling in response to dietary restriction and subsequent re-alimentation in cattle. Physiol Genomics 2015;47(8):344–354.
  • Wærp HKL, Waters SM, McCabe MS, Cormican P, Salte R. RNA-seq analysis of bovine adipose tissue in heifers fed diets differing in energy and protein content. PLoS One 2018;13(9):e0201284.
  • de Las Heras-Saldana S, Chung KY, Lee SH, Gondro C. Gene expression of Hanwoo satellite cell differentiation in longissimus dorsi and semimembranosus. BMC Genomics 2019;20(1):156.
  • Wu ZL, Chen SY, Qin C, Jia X, Deng F, Wang J, et al. Clinical Ketosis-Associated Alteration of Gene Expression in Holstein Cows. Genes (Basel) 2020;11(2):219.
  • Chen W, Alexandre PA, Ribeiro G, Fukumasu H, Sun W, Reverter A, et al. Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data. Front Genet 2021;12:619857.
  • Li Q, Wang Y, Hu X, Zhang Y, Li H, Zhang Q, et al. Transcriptional states and chromatin accessibility during bovine myoblasts proliferation and myogenic differentiation. Cell Prolif 2022;55(5):e13219.
  • Raven LA, Cocks BG, Kemper KE, Chamberlain AJ, Vander Jagt CJ, Goddard ME, et al. Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle. Mamm Genome 2016;27(1-2):81–97.
  • Yang J, Jiang J, Liu X, Wang H, Guo G, Zhang Q, et al. Differential expression of genes in milk of dairy cattle during lactation. Anim Genet. 2016;47(2):174–180.
  • Ahmad SM, Bhat B, Manzoor Z, Dar MA, Taban Q, Ibeagha-Awemu EM, et al. Genome wide expression analysis of circular RNAs in mammary epithelial cells of cattle revealed difference in milk synthesis. PeerJ 2022;10:e13029.
  • Aria M, Cuccurullo C. Bibliometrix: An R-Tool for Comprehensive Science Mapping Analysis. J Informetr 2017;11, 959–975.
  • van Eck NJ, Waltman L. Software Survey: VOSviewer, a Computer Program for Bibliometric Mapping. Scientometrics 2010; 84, 523–538.
  • Bogliotti YS, Wu J, Vilarino M, Okamura D, Soto DA et al. Efficient derivation of stable primed pluripotent embryonic stem cells from bovine blastocysts. Proc Natl Acad Sci 2018;115(9):2090–2095.
  • Jiang Z, Sun J, Dong H, Luo O, Zheng X, Obergfell C, et al. Transcriptional profiles of bovine in vivo pre-implantation development. BMC Genomics 2014;15(1):756.
  • Li M, Sun X, Cai H, Sun Y, Plath M, Li C, et al. Long non-coding RNA ADNCR suppresses adipogenic differentiation by targeting miR-204. Biochim Biophys Acta 2016;1859(7):871–882.
  • Jin W, Ibeagha-Awemu EM, Liang G, Beaudoin F, Zhao X, Guan le L. Transcriptome microRNA profiling of bovine mammary epithelial cells challenged with Escherichia coli or Staphylococcus aureus bacteria reveals pathogen directed microRNA expression profiles. BMC Genomics 2014;15:181.
  • Ruhanen L, Weiler B, Moyle BD, McLennan CLJ. Trends and patterns in sustainable tourism research: A 25-year bibliometric analysis. J Sustain Tour 2015; 23(4):517–535.
  • Silva-Vignato B, Cesar ASM, Afonso J, Moreira GCM, Poleti MD, Petrini J, et al. Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness. Front Genet 2022; 13:935238.
  • Cardoso TF, Coutinho LL, Bruscadin JJ, da Silva Diniz WJ, Petrini J, Andrade BGN, et al. Multi-Omics Approach Reveals miR-SNPs Affecting Muscle Fatty Acids Profile in Nelore Cattle. Genes 2021;12(1):67.
  • de Lima AO, Koltes JE, Diniz WJS, de Oliveira PSN, Cesar ASM, Tizioto PC, et al. Potential Biomarkers for Feed Efficiency-Related Traits in Nelore Cattle Identified by Co-expression Network and Integrative Genomics Analyses. Front Genet 2020;11:189.
  • Diniz WJS, Mazzoni G, Coutinho LL, Banerjee P, Geistlinger L, Cesar ASM, et al. Detection of Co-expressed Pathway Modules Associated With Mineral Concentration and Meat Quality in Nelore Cattle. Front Genet 2019;10:210.
  • Silva-Vignato B, Coutinho LL, Cesar ASM, Poleti MD, Regitano LCA, Balieiro JCC. Comparative muscle transcriptome associated with carcass traits of Nellore cattle. BMC Genomics 2017;18(1):506.
  • Berton MP, Fonseca LF, Gimenez DF, Utembergue BL, Cesar AS, Coutinho LL, et al. Gene expression profile of intramuscular muscle in Nellore cattle with extreme values of fatty acid. BMC Genomics 2016;17(1):972.
  • Cesar AS, Regitano LC, Poleti MD, Andrade SC, Tizioto PC, Oliveira PS et al. Differences in the skeletal muscle transcriptome profile associated with extreme values of fatty acids content. BMC genomics 2016;17(1):961.
  • Sá Filho MF, Gonella-Diaza AM, Sponchiado M, Mendanha MF, Pugliesi G, Ramos RDS, et al. Impact of hormonal modulation at proestrus on ovarian responses and uterine gene expression of suckled anestrous beef cows. J Anim Sci Biotechnol 2017; 8:79.
  • Mesquita FS, Ramos RS, Pugliesi G, Andrade SC, Van Hoeck V, Langbeen A, et al. Endometrial transcriptional profiling of a bovine fertility model by Next-Generation Sequencing. Genom Data 2015;7:26–28.
  • Van Hoeck V, Scolari SC, Pugliesi G, Gonella-Diaza AM, Andrade SC, Gasparin GR, et al. Gene expression profiling by high throughput sequencing to determine signatures for the bovine receptive uterus at early gestation. Genom Data 2015;5:94–96.
  • Gonella-Diaza AM, Andrade SC, Sponchiado M, Pugliesi G, Mesquita FS, Van Hoeck V, et al. Size of the Ovulatory Follicle Dictates Spatial Differences in the Oviductal Transcriptome in Cattle. PloS one 2015;10(12):e0145321.
  • Kang X, Li C, Liu S, Baldwin RL, Liu GE, Li CJ. Genome-Wide Acetylation Modification of H3K27ac in Bovine Rumen Cell Following Butyrate Exposure. Biomolecules 2023;13(7):1137.
  • Li CJ, Lin S, Ranilla-García MJ, Baldwin RL. Transcriptomic Profiling of Duodenal Epithelium Reveals Temporally Dynamic Impacts of Direct Duodenal Starch-Infusion During Dry Period of Dairy Cattle. Front Vet Sci 2019;6:214.
  • Shin JH, Li RW, Gao Y, Bickhart DM, Liu GE, Li W, et al. Butyrate Induced IGF2 Activation Correlated with Distinct Chromatin Signatures Due to Histone Modification. Gene regulation and systems biology 2013;7:57–70.
  • Li M, Sun X, Cai H, Sun Y, Plath M, Li C, et al. Long non-coding RNA ADNCR suppresses adipogenic differentiation by targeting miR-204. Biochim Biophys Acta 2016;1859(7):871–882.
  • Zhou Y, Liu S, Hu Y, Fang L, Gao Y, Xia H, et al. Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns. BMC Biol 2020;18(1):85.
  • Liu S, Gao Y, Canela-Xandri O, Wang S, Yu Y, Cai W, et al. A multi-tissue atlas of regulatory variants in cattle. Nat Genet 2022;54(9):1438–1447.
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There are 57 citations in total.

Details

Primary Language English
Subjects Animal Science, Genetics and Biostatistics
Journal Section RESEARCH ARTICLE
Authors

Esma Gamze Aksel 0000-0002-0040-8933

Ahu Cephe 0000-0001-9374-4495

Funda İpekten 0000-0002-6916-9563

Gözde Ertürk Zararsız 0000-0002-5495-7540

Aytaç Akçay 0000-0001-6263-5181

Early Pub Date June 12, 2024
Publication Date June 15, 2024
Submission Date March 11, 2024
Acceptance Date May 14, 2024
Published in Issue Year 2024 Volume: 95 Issue: 2

Cite

Vancouver Aksel EG, Cephe A, İpekten F, Ertürk Zararsız G, Akçay A. Bibliometric analysis of studies on gene expression and RNA-seq in cattle species. Vet Hekim Der Derg. 2024;95(2):115-31.

Veteriner Hekimler Derneği Dergisi (Journal of Turkish Veterinary Medical Society) is an open access publication, and the journal’s publication model is based on Budapest Access Initiative (BOAI) declaration. All published content is licensed under a Creative Commons CC BY-NC 4.0 license, available online and free of charge. Authors retain the copyright of their published work in Veteriner Hekimler Derneği Dergisi (Journal of Turkish Veterinary Medical Society). 

Veteriner Hekimler Derneği / Turkish Veterinary Medical Society