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Bibliometric Analysis of Next-Generation Sequence Applications in Livestock

Year 2023, , 485 - 491, 01.09.2023
https://doi.org/10.47115/bsagriculture.1296263

Abstract

Bibliometric analyzes are widely used in many fields. However, there are still insufficient bibliometric studies evaluating animal science studies from different perspectives. Therefore, we performed the comprehensive bibliometric analysis of 335 documents scanned in the Web of Science (WoS) database in next-generation sequence applications in livestock between 2009 and 2023. According to the analysis results, this field has been increasing interest recently. The fact that the studies (45.07% of total) were carried out by international large research groups with the participation of many researchers shows that the collaborative working culture in this field is developed. BMC Genomics, Animals and Frontiers in Genetics are among the most preferred journals in studies in this field, and 14, 10 and 10 articles have been published, respectively, to date. The number of citations per article indicates the high impact of the articles published in this field. It has been determined that the three most frequently used keywords in next-generation sequence studies in the field of livestock are "identification", "diversity" and "expression". Overall, studies about next-generation sequence applications in livestock seem to be very popular among the scientific community in recent years.

References

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  • Bordbar F, Jensen J, Du M, Abied A, Guo W, Xu L, Gao H, Zhang L, Li J. 2020. Identification and validation of a novel candidate gene regulating net meat weight in Simmental beef cattle based on imputed next‐generation sequencing. Cell Proliferation, 53(9): e12870.
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  • Dahm R, Banerjee M. 2019. How we forgot who discovered DNA: why it matters how you communicate your results. BioEssays, 41(4): 1900029.
  • Goddard ME, Hayes BJ. 2009. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Rev Genetics, 10(6): 381-391.
  • Goodwin S, McPherson JD, McCombie WR. 2016. Coming of age: ten years of next-generation sequencing technologies. Nature Rev Genetics, 17(6): 333-351.
  • Hood L, Galas D. 2003. The digital code of DNA. Nature, 421(6921): 444-448.
  • Jiang L, Liu X, Yang J, Wang H, Jiang J, Liu L, He S, Ding X, Liu J, Zhang Q. 2014. Targeted resequencing of GWAS loci reveals novel genetic variants for milk production traits. BMC Genomics, 15(1): 1-9.
  • Kim KM, Park JH, Bhattacharya D, Yoon HS. 2014. Applications of next-generation sequencing to unravelling the evolutionary history of algae. Int J Systematic Evolut Microbiol, 64(Pt_2): 333-345.
  • Koboldt DC, Steinberg KM, Larson DE, Wilson RK, Mardis ER. 2013. The next-generation sequencing revolution and its impact on genomics. Cell, 155(1): 27-38.
  • Lallar M, Phadke SR. 2016. Human genome project and after. Genetic Clin, 9(1): 9-15.
  • Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z. 2005. Genome sequencing in microfabricated high-density picolitre reactors. Nature, 437(7057): 376-380.
  • Mishra D, Gunasekaran A, Papadopoulos T, Dubey R. 2018. Supply chain performance measures and metrics: a bibliometric study. Benchmarking Int J, 25(3): 932-967.
  • Morozova O, Marra MA. 2008. Applications of next-generation sequencing technologies in functional genomics. Genomics, 92(5): 255-264.
  • Olson MV. 2002. The human genome project: A player's perspective. J Molec Biol, 319(4): 931-942.
  • Önder H, Tirink C. 2022. Bibliometric analysis for genomic selection studies in animal science. J Inst Sci Tech, 12(3): 1849-1856.
  • Osareh F. 1996. Bibliometrics, citation analysis and co-citation analysis: A review of literature I. Libri, 46: 149-158.
  • Pareek CS, Smoczynski R, Tretyn A. 2011. Sequencing technologies and genome sequencing. J Appl Genet, 52: 413-435.
  • Park ST, Kim J. 2016. Trends in next-generation sequencing and a new era for whole genome sequencing. Int Neurourol J, 20(Suppl 2): S76.
  • Pouladi N, Bime C, Garcia JG, Lussier YA. 2016. Complex genetics of pulmonary diseases: lessons from genome-wide association studies and next-generation sequencing. Translat Res, 168: 22-39.
  • Pritchard A. 1969. Statistical bibliography; an interim bibliography. Eric, London, UK, pp: 69.
  • Rasheed M. 2020. Next generation sequencing as an emerging technology in rare disease genetics. J Islamabad Medic Dental College, 9(1): 1-3.
  • Sanger F, Nicklen S, Coulson AR. 1977. DNA sequencing with chain-terminating inhibitors. Proc National Acad Sci, 74(12): 5463-5467.
  • Schloss JA. 2008. How to get genomes at one ten-thousandth the cost. Nature Biotechnol, 26(10): 1113-1115.
  • Schneeberger K, Weigel D. 2011. Fast-forward genetics enabled by new sequencing technologies. Trends Plant Sci, 16(5): 282-288.
  • Schuster SC. 2008. Next-generation sequencing transforms today's biology. Nature Methods, 5(1): 16-18.
  • Team RC. 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www. R-project. org/.
  • Thanuskodi S. 2010. Journal of Social Sciences: A bibliometric study. J Soc Sci, 24(2): 77-80.
  • Tipu HN, Shabbir A. 2015. Evolution of DNA sequencing. J Coll Physicians Surg Pak, 25(3): 210-215.
  • Toghiani S, Chang LY, Ling A, Aggrey SE, Rekaya R. 2017. Genomic differentiation as a tool for single nucleotide polymorphism prioritization for Genome wide association and phenotype prediction in livestock. Livestock Sci, 205: 24-30.
  • Totomoch-Serra A, Marquez MF, Cervantes-Barragán DE. 2017. Sanger sequencing as a first-line approach for molecular diagnosis of Andersen-Tawil syndrome. F1000 Res, 6(1016): 1016.
  • Van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. 2014. Ten years of next-generation sequencing technology. Trends Genet, 30(9): 418-426.
  • Voelkerding KV, Dames SA, Durtschi JD. 2009. Next-generation sequencing: from basic research to diagnostics. Clin Chem, 55(4): 641-658.
  • Waters CK. 2008. Beyond theoretical reduction and layer‐cake antireduction: How DNA retooled genetics and transformed biological practice. Oxford Press, Oxford, UK, pp: 262.
  • Watson JD, Crick FH. 1953. The structure of DNA. Cold Spring Harbor symposia on quantitative biology, New York, US.
  • Young AI. 2019. Solving the missing heritability problem. PLoS Genet, 15(6): e1008222.
  • Zahra AA, Nurmandi A, Tenario CB, Rahayu R, Benectitos SH, Mina FLP, Haictin KM. 2021. Bibliometric analysis of trends in theory-related policy publications. Emerging Sci J, 5(1): 96-110.
Year 2023, , 485 - 491, 01.09.2023
https://doi.org/10.47115/bsagriculture.1296263

Abstract

References

  • Akhavan P, Ebrahim NA, Fetrati MA, Pezeshkan A. 2016. Major trends in knowledge management research: a bibliometric study. Scientometrics, 107: 1249-1264.
  • Alex A, Brundha M, Prathap L. 2020. Sanger sequencing and its recent advances-a review. PalArch's J Archaeol Egypt/Egyptol, 17(7): 698-705.
  • Altimari A, de Biase D, de Maglio G, Gruppioni E, Capizzi E, Degiovanni A, D’Errico A, Pession A, Pizzolitto S, Fiorentino M. 2013. 454 next generation-sequencing outperforms allele-specific PCR, Sanger sequencing, and pyrosequencing for routine KRAS mutation analysis of formalin-fixed, paraffin-embedded samples. Onco Targets Therap, 2013: 1057-1064.
  • Aria M, Cuccurullo C. 2017. Bibliometrix: An R-tool for comprehensive science mapping analysis. J Informet, 11(4): 959-975.
  • Behjati S, Tarpey PS. 2013. What is next generation sequencing? Arch Diseas Childhood Educ Pract, 98(6): 236-238.
  • Bordbar F, Jensen J, Du M, Abied A, Guo W, Xu L, Gao H, Zhang L, Li J. 2020. Identification and validation of a novel candidate gene regulating net meat weight in Simmental beef cattle based on imputed next‐generation sequencing. Cell Proliferation, 53(9): e12870.
  • Chan EY. 2005. Advances in sequencing technology. Mutat Res/Fundam Molec Mechan Mutagenesis, 573(1-2): 13-40.
  • Dahm R, Banerjee M. 2019. How we forgot who discovered DNA: why it matters how you communicate your results. BioEssays, 41(4): 1900029.
  • Goddard ME, Hayes BJ. 2009. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Rev Genetics, 10(6): 381-391.
  • Goodwin S, McPherson JD, McCombie WR. 2016. Coming of age: ten years of next-generation sequencing technologies. Nature Rev Genetics, 17(6): 333-351.
  • Hood L, Galas D. 2003. The digital code of DNA. Nature, 421(6921): 444-448.
  • Jiang L, Liu X, Yang J, Wang H, Jiang J, Liu L, He S, Ding X, Liu J, Zhang Q. 2014. Targeted resequencing of GWAS loci reveals novel genetic variants for milk production traits. BMC Genomics, 15(1): 1-9.
  • Kim KM, Park JH, Bhattacharya D, Yoon HS. 2014. Applications of next-generation sequencing to unravelling the evolutionary history of algae. Int J Systematic Evolut Microbiol, 64(Pt_2): 333-345.
  • Koboldt DC, Steinberg KM, Larson DE, Wilson RK, Mardis ER. 2013. The next-generation sequencing revolution and its impact on genomics. Cell, 155(1): 27-38.
  • Lallar M, Phadke SR. 2016. Human genome project and after. Genetic Clin, 9(1): 9-15.
  • Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z. 2005. Genome sequencing in microfabricated high-density picolitre reactors. Nature, 437(7057): 376-380.
  • Mishra D, Gunasekaran A, Papadopoulos T, Dubey R. 2018. Supply chain performance measures and metrics: a bibliometric study. Benchmarking Int J, 25(3): 932-967.
  • Morozova O, Marra MA. 2008. Applications of next-generation sequencing technologies in functional genomics. Genomics, 92(5): 255-264.
  • Olson MV. 2002. The human genome project: A player's perspective. J Molec Biol, 319(4): 931-942.
  • Önder H, Tirink C. 2022. Bibliometric analysis for genomic selection studies in animal science. J Inst Sci Tech, 12(3): 1849-1856.
  • Osareh F. 1996. Bibliometrics, citation analysis and co-citation analysis: A review of literature I. Libri, 46: 149-158.
  • Pareek CS, Smoczynski R, Tretyn A. 2011. Sequencing technologies and genome sequencing. J Appl Genet, 52: 413-435.
  • Park ST, Kim J. 2016. Trends in next-generation sequencing and a new era for whole genome sequencing. Int Neurourol J, 20(Suppl 2): S76.
  • Pouladi N, Bime C, Garcia JG, Lussier YA. 2016. Complex genetics of pulmonary diseases: lessons from genome-wide association studies and next-generation sequencing. Translat Res, 168: 22-39.
  • Pritchard A. 1969. Statistical bibliography; an interim bibliography. Eric, London, UK, pp: 69.
  • Rasheed M. 2020. Next generation sequencing as an emerging technology in rare disease genetics. J Islamabad Medic Dental College, 9(1): 1-3.
  • Sanger F, Nicklen S, Coulson AR. 1977. DNA sequencing with chain-terminating inhibitors. Proc National Acad Sci, 74(12): 5463-5467.
  • Schloss JA. 2008. How to get genomes at one ten-thousandth the cost. Nature Biotechnol, 26(10): 1113-1115.
  • Schneeberger K, Weigel D. 2011. Fast-forward genetics enabled by new sequencing technologies. Trends Plant Sci, 16(5): 282-288.
  • Schuster SC. 2008. Next-generation sequencing transforms today's biology. Nature Methods, 5(1): 16-18.
  • Team RC. 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www. R-project. org/.
  • Thanuskodi S. 2010. Journal of Social Sciences: A bibliometric study. J Soc Sci, 24(2): 77-80.
  • Tipu HN, Shabbir A. 2015. Evolution of DNA sequencing. J Coll Physicians Surg Pak, 25(3): 210-215.
  • Toghiani S, Chang LY, Ling A, Aggrey SE, Rekaya R. 2017. Genomic differentiation as a tool for single nucleotide polymorphism prioritization for Genome wide association and phenotype prediction in livestock. Livestock Sci, 205: 24-30.
  • Totomoch-Serra A, Marquez MF, Cervantes-Barragán DE. 2017. Sanger sequencing as a first-line approach for molecular diagnosis of Andersen-Tawil syndrome. F1000 Res, 6(1016): 1016.
  • Van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. 2014. Ten years of next-generation sequencing technology. Trends Genet, 30(9): 418-426.
  • Voelkerding KV, Dames SA, Durtschi JD. 2009. Next-generation sequencing: from basic research to diagnostics. Clin Chem, 55(4): 641-658.
  • Waters CK. 2008. Beyond theoretical reduction and layer‐cake antireduction: How DNA retooled genetics and transformed biological practice. Oxford Press, Oxford, UK, pp: 262.
  • Watson JD, Crick FH. 1953. The structure of DNA. Cold Spring Harbor symposia on quantitative biology, New York, US.
  • Young AI. 2019. Solving the missing heritability problem. PLoS Genet, 15(6): e1008222.
  • Zahra AA, Nurmandi A, Tenario CB, Rahayu R, Benectitos SH, Mina FLP, Haictin KM. 2021. Bibliometric analysis of trends in theory-related policy publications. Emerging Sci J, 5(1): 96-110.
There are 41 citations in total.

Details

Primary Language English
Subjects Zootechny (Other)
Journal Section Research Articles
Authors

Selçuk Kaplan 0000-0003-1101-2296

Yasin Altay 0000-0003-4049-8301

Publication Date September 1, 2023
Submission Date May 12, 2023
Acceptance Date July 23, 2023
Published in Issue Year 2023

Cite

APA Kaplan, S., & Altay, Y. (2023). Bibliometric Analysis of Next-Generation Sequence Applications in Livestock. Black Sea Journal of Agriculture, 6(5), 485-491. https://doi.org/10.47115/bsagriculture.1296263

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