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Life (Basel, Switzerland)2022; 12(11); 1893; doi: 10.3390/life12111893

The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research.

Abstract: For more than a decade, next-generation sequencing (NGS) has been emerging as the mainstay of agrigenomics research. High-throughput technologies have made it feasible to facilitate research at the scale and cost required for using this data in livestock research. Scale frameworks of sequencing for agricultural and livestock improvement, management, and conservation are partly attributable to innovative informatics methodologies and advancements in sequencing practices. Genome-wide sequence-based investigations are often conducted worldwide, and several databases have been created to discover the connections between worldwide scientific accomplishments. Such studies are beginning to provide revolutionary insights into a new era of genomic prediction and selection capabilities of various domesticated livestock species. In this concise review, we provide selected examples of the current state of sequencing methods, many of which are already being used in animal genomic studies, and summarize the state of the positive attributes of genome-based research for cattle (), sheep (), pigs (), horses (), chickens (), and ducks (). This review also emphasizes the advantageous features of sequencing technologies in monitoring and detecting infectious zoonotic diseases. In the coming years, the continued advancement of sequencing technologies in livestock agrigenomics will significantly influence the sustained momentum toward regulatory approaches that encourage innovation to ensure continued access to a safe, abundant, and affordable food supplies for future generations.
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Publication Date: 2022-11-15 PubMed ID: 36431028PubMed Central: PMC9695872DOI: 10.3390/life12111893Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research discusses the role of high-throughput technologies and innovative informatics in agrigenomics research, and their impacts on livestock sustainability and management. It also entails sequenced-based investigations of various livestock species, contributing to genomic prediction and selection capabilities in the scientific world.

Utilization of Next-Generation Sequencing in Agrigenomics

  • The research emphasizes the evolution of Next-Generation Sequencing (NGS) as a cornerstone of agrigenomics over the past decade. High-throughput technologies have made it possible to conduct research at the necessary scale and cost for practical application in livestock studies.
  • The researchers discuss how sequencing frameworks have significantly impacted agricultural and livestock improvement, management, and conservation, especially the innovative informatics methodologies and advancements in sequencing practices.

Importance of Genome-Wide Sequence-Based Investigations

  • These investigations are widespread, and numerous databases have been established to link global scientific achievements. This kind of study is facilitating revolutionary insights into a new era of genomic prediction and selection capabilities for a variety of domesticated livestock species.
  • The research provides specific examples of sequencing methods currently in use in animal genomic studies and highlights their positive attributes in genome-based research for numerous livestock species such as cattle, sheep, pigs, horses, chickens, and ducks.

Sequencing Technologies in Monitoring and Detecting Infectious Zoonotic Diseases

  • The researchers underscore that sequencing technologies hold significant advantages in monitoring and detecting infectious zoonotic diseases, illnesses that can be passed from animals to humans.

Future Impact of Sequencing Technologies in Livestock Agrigenomics

  • The research concludes with a look to the future, predicting that the ongoing evolution of sequencing technologies in livestock agrigenomics will have a substantial influence on regulatory approaches, fostering innovation and ensuring continued access to safe, abundant, and affordable food supplies.

Cite This Article

APA
Suminda GGD, Ghosh M, Son YO. (2022). The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research. Life (Basel), 12(11), 1893. https://doi.org/10.3390/life12111893

Publication

Life (Basel, Switzerland)
ISSN: 2075-1729
NlmUniqueID: 101580444
Country: Switzerland
Language: English
Volume: 12
Issue: 11
PII: 1893

Researcher Affiliations

Suminda, Godagama Gamaarachchige Dinesh
  • Interdisciplinary Graduate Program in Advanced Convergence Technology and Science, Jeju National University, Jeju-si 63243, Republic of Korea.
Ghosh, Mrinmoy
  • Department of Biotechnology, School of Bio, Chemical and Processing Engineering (SBCE), Kalasalingam Academy of Research and Educational, Krishnankoil, Virudhunagar 626126, India.
  • Department of Animal Biotechnology, Faculty of Biotechnology, College of Applied Life Sciences, Jeju National University, Jeju-si 63243, Republic of Korea.
Son, Young-Ok
  • Interdisciplinary Graduate Program in Advanced Convergence Technology and Science, Jeju National University, Jeju-si 63243, Republic of Korea.
  • Department of Animal Biotechnology, Faculty of Biotechnology, College of Applied Life Sciences, Jeju National University, Jeju-si 63243, Republic of Korea.
  • Bio-Health Materials Core-Facility Center, Jeju National University, Jeju-si 63243, Republic of Korea.
  • Practical Translational Research Center, Jeju National University, Jeju-si 63243, Republic of Korea.

Grant Funding

  • 2022 scientific promotion program / Jeju National University

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 158 references
  1. Bai Y, Sartor M, Cavalcoli J. Current status and future perspectives for sequencing livestock genomes.. J Anim Sci Biotechnol 2012 Mar 1;3(1):8.
    doi: 10.1186/2049-1891-3-8pmc: PMC3436607pubmed: 22958500google scholar: lookup
  2. Diaz-Sanchez S, Hanning I, Pendleton S, D'Souza D. Next-generation sequencing: the future of molecular genetics in poultry production and food safety.. Poult Sci 2013 Feb;92(2):562-72.
    doi: 10.3382/ps.2012-02741pubmed: 23300324google scholar: lookup
  3. McAdam PR, Richardson EJ, Fitzgerald JR. High-throughput sequencing for the study of bacterial pathogen biology.. Curr Opin Microbiol 2014 Jun;19:106-113.
    doi: 10.1016/j.mib.2014.06.002pmc: PMC4150483pubmed: 25033019google scholar: lookup
  4. Athanasopoulou K, Boti MA, Adamopoulos PG, Skourou PC, Scorilas A. Third-Generation Sequencing: The Spearhead towards the Radical Transformation of Modern Genomics.. Life (Basel) 2021 Dec 26;12(1).
    doi: 10.3390/life12010030pmc: PMC8780579pubmed: 35054423google scholar: lookup
  5. . Next-Generation Sequencing Services Market Size, Share & Trends Analysis Report By Service Type (Human Genome Sequencing, Gene Regulation Services), By Workflow, By End-Use, And Segment Forecasts, 2022–2030. May 2022.
  6. Wray-Cahen D, Bodnar A, Rexroad C, Siewerdt F, Kovich D. Advancing genome editing to improve the sustainability and resiliency of animal agriculture. CABI Agric. Biosci. 2022;3:21.
    doi: 10.1186/s43170-022-00091-wgoogle scholar: lookup
  7. Narrod C, Zinsstag J, Tiongco M. A one health framework for estimating the economic costs of zoonotic diseases on society.. Ecohealth 2012 Jun;9(2):150-62.
    doi: 10.1007/s10393-012-0747-9pmc: PMC3415616pubmed: 22395956google scholar: lookup
  8. Behravesh CB, Brinson D, Hopkins BA, Gomez TM. Backyard poultry flocks and salmonellosis: a recurring, yet preventable public health challenge.. Clin Infect Dis 2014 May;58(10):1432-8.
    doi: 10.1093/cid/ciu067pubmed: 24501387google scholar: lookup
  9. Nicholson CW, Campagnolo ER, Boktor SW, Butler CL. Zoonotic disease awareness survey of backyard poultry and swine owners in southcentral Pennsylvania.. Zoonoses Public Health 2020 May;67(3):280-290.
    doi: 10.1111/zph.12686pmc: PMC7231624pubmed: 32020787google scholar: lookup
  10. Benton B, King S, Greenfield SR, Puthuveetil N, Reese AL, Duncan J, Marlow R, Tabron C, Pierola AE, Yarmosh DA Jr, Combs PF, Riojas MA, Bagnoli J, Jacobs JL. The ATCC Genome Portal: Microbial Genome Reference Standards with Data Provenance.. Microbiol Resour Announc 2021 Nov 24;10(47):e0081821.
    doi: 10.1128/MRA.00818-21pmc: PMC8612085pubmed: 34817215google scholar: lookup
  11. SINSHEIMER RL. A single-stranded DNA from bacteriophage phi X174.. Brookhaven Symp Biol 1959 Nov;No 12:27-34.
    pubmed: 14447155
  12. Ghosh M, Sharma N, Singh AK, Gera M, Pulicherla KK, Jeong DK. Transformation of animal genomics by next-generation sequencing technologies: a decade of challenges and their impact on genetic architecture.. Crit Rev Biotechnol 2018 Dec;38(8):1157-1175.
    doi: 10.1080/07388551.2018.1451819pubmed: 29631431google scholar: lookup
  13. Hutchison CA 3rd. DNA sequencing: bench to bedside and beyond.. Nucleic Acids Res 2007;35(18):6227-37.
    doi: 10.1093/nar/gkm688pmc: PMC2094077pubmed: 17855400google scholar: lookup
  14. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors.. Proc Natl Acad Sci U S A 1977 Dec;74(12):5463-7.
    doi: 10.1073/pnas.74.12.5463pmc: PMC431765pubmed: 271968google scholar: lookup
  15. Pei S, Liu T, Ren X, Li W, Chen C, Xie Z. Benchmarking variant callers in next-generation and third-generation sequencing analysis.. Brief Bioinform 2021 May 20;22(3).
    doi: 10.1093/bib/bbaa148pubmed: 32698196google scholar: lookup
  16. Liu L, Li Y, Li S, Hu N, He Y, Pong R, Lin D, Lu L, Law M. Comparison of next-generation sequencing systems.. J Biomed Biotechnol 2012;2012:251364.
    doi: 10.1155/2012/251364pmc: PMC3398667pubmed: 22829749google scholar: lookup
  17. Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, Alonge M, Antonarakis SE, Borchers M, Bouffard GG, Brooks SY, Caldas GV, Chen NC, Cheng H, Chin CS, Chow W, de Lima LG, Dishuck PC, Durbin R, Dvorkina T, Fiddes IT, Formenti G, Fulton RS, Fungtammasan A, Garrison E, Grady PGS, Graves-Lindsay TA, Hall IM, Hansen NF, Hartley GA, Haukness M, Howe K, Hunkapiller MW, Jain C, Jain M, Jarvis ED, Kerpedjiev P, Kirsche M, Kolmogorov M, Korlach J, Kremitzki M, Li H, Maduro VV, Marschall T, McCartney AM, McDaniel J, Miller DE, Mullikin JC, Myers EW, Olson ND, Paten B, Peluso P, Pevzner PA, Porubsky D, Potapova T, Rogaev EI, Rosenfeld JA, Salzberg SL, Schneider VA, Sedlazeck FJ, Shafin K, Shew CJ, Shumate A, Sims Y, Smit AFA, Soto DC, Sović I, Storer JM, Streets A, Sullivan BA, Thibaud-Nissen F, Torrance J, Wagner J, Walenz BP, Wenger A, Wood JMD, Xiao C, Yan SM, Young AC, Zarate S, Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O'Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM. The complete sequence of a human genome.. Science 2022 Apr;376(6588):44-53.
    doi: 10.1126/science.abj6987pmc: PMC9186530pubmed: 35357919google scholar: lookup
  18. Diaz MH, Winchell JM. The Evolution of Advanced Molecular Diagnostics for the Detection and Characterization of Mycoplasma pneumoniae.. Front Microbiol 2016;7:232.
    doi: 10.3389/fmicb.2016.00232pmc: PMC4781879pubmed: 27014191google scholar: lookup
  19. Voelkerding KV, Dames SA, Durtschi JD. Next-generation sequencing: from basic research to diagnostics.. Clin Chem 2009 Apr;55(4):641-58.
    doi: 10.1373/clinchem.2008.112789pubmed: 19246620google scholar: lookup
  20. . Applications of Clinical Microbial Next-Generation Sequencing: Report on an American Academy of Microbiology Colloquium held in Washington, DC, in April 2015. American Society for Microbiology; Washington, DC, USA: 2016.
    pubmed: 30063310
  21. Golan D, Medvedev P. Using state machines to model the Ion Torrent sequencing process and to improve read error rates.. Bioinformatics 2013 Jul 1;29(13):i344-51.
    doi: 10.1093/bioinformatics/btt212pmc: PMC3694666pubmed: 23813003google scholar: lookup
  22. Shendure J, Porreca GJ, Reppas NB, Lin X, McCutcheon JP, Rosenbaum AM, Wang MD, Zhang K, Mitra RD, Church GM. Accurate multiplex polony sequencing of an evolved bacterial genome.. Science 2005 Sep 9;309(5741):1728-32.
    doi: 10.1126/science.1117389pubmed: 16081699google scholar: lookup
  23. Barba E, Tsermpini E-E, Patrinos GP, Koromina M. Applied Genomics and Public Health. Elsevier; Amsterdam, The Netherlands: 2020. Genome Informatics Pipelines and Genome Browsers; pp. 149–169.
  24. Gourlé H, Karlsson-Lindsjö O, Hayer J, Bongcam-Rudloff E. Simulating Illumina metagenomic data with InSilicoSeq.. Bioinformatics 2019 Feb 1;35(3):521-522.
    doi: 10.1093/bioinformatics/bty630pmc: PMC6361232pubmed: 30016412google scholar: lookup
  25. Pérez-Enciso M, Ferretti L. Massive parallel sequencing in animal genetics: wherefroms and wheretos.. Anim Genet 2010 Dec;41(6):561-9.
    doi: 10.1111/j.1365-2052.2010.02057.xpubmed: 20477787google scholar: lookup
  26. Goodwin S, McPherson JD, McCombie WR. Coming of age: ten years of next-generation sequencing technologies.. Nat Rev Genet 2016 May 17;17(6):333-51.
    doi: 10.1038/nrg.2016.49pubmed: 27184599google scholar: lookup
  27. Feng Y, Zhang Y, Ying C, Wang D, Du C. Nanopore-based fourth-generation DNA sequencing technology.. Genomics Proteomics Bioinformatics 2015 Feb;13(1):4-16.
    doi: 10.1016/j.gpb.2015.01.009pmc: PMC4411503pubmed: 25743089google scholar: lookup
  28. Gupta AK, Gupta U. Animal Biotechnology. Elsevier; Amsterdam, The Netherlands: 2020. Next generation sequencing and its applications; pp. 395–421.
  29. Kortenhoeven C, Joubert F, Bastos AD, Abolnik C. Virus genome dynamics under different propagation pressures: reconstruction of whole genome haplotypes of West Nile viruses from NGS data.. BMC Genomics 2015 Feb 22;16(1):118.
    doi: 10.1186/s12864-015-1340-8pmc: PMC4338619pubmed: 25766117google scholar: lookup
  30. Miller JR, Koren S, Sutton G. Assembly algorithms for next-generation sequencing data.. Genomics 2010 Jun;95(6):315-27.
    doi: 10.1016/j.ygeno.2010.03.001pmc: PMC2874646pubmed: 20211242google scholar: lookup
  31. Greenwood PL. Review: An overview of beef production from pasture and feedlot globally, as demand for beef and the need for sustainable practices increase.. Animal 2021 Dec;15 Suppl 1:100295.
    doi: 10.1016/j.animal.2021.100295pubmed: 34274250google scholar: lookup
  32. Elsik CG, Unni DR, Diesh CM, Tayal A, Emery ML, Nguyen HN, Hagen DE. Bovine Genome Database: new tools for gleaning function from the Bos taurus genome.. Nucleic Acids Res 2016 Jan 4;44(D1):D834-9.
    doi: 10.1093/nar/gkv1077pmc: PMC4702796pubmed: 26481361google scholar: lookup
  33. Arias JA, Keehan M, Fisher P, Coppieters W, Spelman R. A high density linkage map of the bovine genome.. BMC Genet 2009 Apr 24;10:18.
    doi: 10.1186/1471-2156-10-18pmc: PMC2680908pubmed: 19393043google scholar: lookup
  34. Snelling WM, Chiu R, Schein JE, Hobbs M, Abbey CA, Adelson DL, Aerts J, Bennett GL, Bosdet IE, Boussaha M, Brauning R, Caetano AR, Costa MM, Crawford AM, Dalrymple BP, Eggen A, Everts-van der Wind A, Floriot S, Gautier M, Gill CA, Green RD, Holt R, Jann O, Jones SJ, Kappes SM, Keele JW, de Jong PJ, Larkin DM, Lewin HA, McEwan JC, McKay S, Marra MA, Mathewson CA, Matukumalli LK, Moore SS, Murdoch B, Nicholas FW, Osoegawa K, Roy A, Salih H, Schibler L, Schnabel RD, Silveri L, Skow LC, Smith TP, Sonstegard TS, Taylor JF, Tellam R, Van Tassell CP, Williams JL, Womack JE, Wye NH, Yang G, Zhao S. A physical map of the bovine genome.. Genome Biol 2007;8(8):R165.
    doi: 10.1186/gb-2007-8-8-r165pmc: PMC2374996pubmed: 17697342google scholar: lookup
  35. Zimin AV, Delcher AL, Florea L, Kelley DR, Schatz MC, Puiu D, Hanrahan F, Pertea G, Van Tassell CP, Sonstegard TS, Marçais G, Roberts M, Subramanian P, Yorke JA, Salzberg SL. A whole-genome assembly of the domestic cow, Bos taurus.. Genome Biol 2009;10(4):R42.
    doi: 10.1186/gb-2009-10-4-r42pmc: PMC2688933pubmed: 19393038google scholar: lookup
  36. McKay SD, Schnabel RD, Murdoch BM, Aerts J, Gill CA, Gao C, Li C, Matukumalli LK, Stothard P, Wang Z, Van Tassell CP, Williams JL, Taylor JF, Moore SS. Construction of bovine whole-genome radiation hybrid and linkage maps using high-throughput genotyping.. Anim Genet 2007 Apr;38(2):120-5.
    doi: 10.1111/j.1365-2052.2006.01564.xpmc: PMC2063635pubmed: 17302794google scholar: lookup
  37. Tellam RL, Lemay DG, Van Tassell CP, Lewin HA, Worley KC, Elsik CG. Unlocking the bovine genome.. BMC Genomics 2009 Apr 24;10:193.
    doi: 10.1186/1471-2164-10-193pmc: PMC2680899pubmed: 19393070google scholar: lookup
  38. Tan MP, Wong LL, Razali SA, Afiqah-Aleng N, Mohd Nor SA, Sung YY, Van de Peer Y, Sorgeloos P, Danish-Daniel M. Applications of Next-Generation Sequencing Technologies and Computational Tools in Molecular Evolution and Aquatic Animals Conservation Studies: A Short Review.. Evol Bioinform Online 2019;15:1176934319892284.
    doi: 10.1177/1176934319892284pmc: PMC6896124pubmed: 31839703google scholar: lookup
  39. Groenen MA. A decade of pig genome sequencing: a window on pig domestication and evolution.. Genet Sel Evol 2016 Mar 29;48:23.
    doi: 10.1186/s12711-016-0204-2pmc: PMC4812630pubmed: 27025270google scholar: lookup
  40. Outlook F. Biannual Report on Global Food Markets. FAO; Rome, Italy: 2017.
  41. Groenen MA, Archibald AL, Uenishi H, Tuggle CK, Takeuchi Y, Rothschild MF, Rogel-Gaillard C, Park C, Milan D, Megens HJ, Li S, Larkin DM, Kim H, Frantz LA, Caccamo M, Ahn H, Aken BL, Anselmo A, Anthon C, Auvil L, Badaoui B, Beattie CW, Bendixen C, Berman D, Blecha F, Blomberg J, Bolund L, Bosse M, Botti S, Bujie Z, Bystrom M, Capitanu B, Carvalho-Silva D, Chardon P, Chen C, Cheng R, Choi SH, Chow W, Clark RC, Clee C, Crooijmans RP, Dawson HD, Dehais P, De Sapio F, Dibbits B, Drou N, Du ZQ, Eversole K, Fadista J, Fairley S, Faraut T, Faulkner GJ, Fowler KE, Fredholm M, Fritz E, Gilbert JG, Giuffra E, Gorodkin J, Griffin DK, Harrow JL, Hayward A, Howe K, Hu ZL, Humphray SJ, Hunt T, Hornshøj H, Jeon JT, Jern P, Jones M, Jurka J, Kanamori H, Kapetanovic R, Kim J, Kim JH, Kim KW, Kim TH, Larson G, Lee K, Lee KT, Leggett R, Lewin HA, Li Y, Liu W, Loveland JE, Lu Y, Lunney JK, Ma J, Madsen O, Mann K, Matthews L, McLaren S, Morozumi T, Murtaugh MP, Narayan J, Nguyen DT, Ni P, Oh SJ, Onteru S, Panitz F, Park EW, Park HS, Pascal G, Paudel Y, Perez-Enciso M, Ramirez-Gonzalez R, Reecy JM, Rodriguez-Zas S, Rohrer GA, Rund L, Sang Y, Schachtschneider K, Schraiber JG, Schwartz J, Scobie L, Scott C, Searle S, Servin B, Southey BR, Sperber G, Stadler P, Sweedler JV, Tafer H, Thomsen B, Wali R, Wang J, Wang J, White S, Xu X, Yerle M, Zhang G, Zhang J, Zhang J, Zhao S, Rogers J, Churcher C, Schook LB. Analyses of pig genomes provide insight into porcine demography and evolution.. Nature 2012 Nov 15;491(7424):393-8.
    doi: 10.1038/nature11622pmc: PMC3566564pubmed: 23151582google scholar: lookup
  42. Ruan J, Xu J, Chen-Tsai RY, Li K. Genome editing in livestock: Are we ready for a revolution in animal breeding industry?. Transgenic Res 2017 Dec;26(6):715-726.
    doi: 10.1007/s11248-017-0049-7pubmed: 29094286google scholar: lookup
  43. Chen K, Baxter T, Muir WM, Groenen MA, Schook LB. Genetic resources, genome mapping and evolutionary genomics of the pig (Sus scrofa).. Int J Biol Sci 2007 Feb 10;3(3):153-65.
    doi: 10.7150/ijbs.3.153pmc: PMC1802013pubmed: 17384734google scholar: lookup
  44. Prather RS. Pig genomics for biomedicine.. Nat Biotechnol 2013 Feb;31(2):122-4.
    doi: 10.1038/nbt.2490pubmed: 23392511google scholar: lookup
  45. Padhi MK. Importance of Indigenous Breeds of Chicken for Rural Economy and Their Improvements for Higher Production Performance.. Scientifica (Cairo) 2016;2016:2604685.
    doi: 10.1155/2016/2604685pmc: PMC4838803pubmed: 27144053google scholar: lookup
  46. Burt DW. Chicken genome: current status and future opportunities.. Genome Res 2005 Dec;15(12):1692-8.
    doi: 10.1101/gr.4141805pubmed: 16339367google scholar: lookup
  47. . Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution.. Nature 2004 Dec 9;432(7018):695-716.
    pubmed: 15592404doi: 10.1038/nature03154google scholar: lookup
  48. Hackett SJ, Kimball RT, Reddy S, Bowie RC, Braun EL, Braun MJ, Chojnowski JL, Cox WA, Han KL, Harshman J, Huddleston CJ, Marks BD, Miglia KJ, Moore WS, Sheldon FH, Steadman DW, Witt CC, Yuri T. A phylogenomic study of birds reveals their evolutionary history.. Science 2008 Jun 27;320(5884):1763-8.
    doi: 10.1126/science.1157704pubmed: 18583609google scholar: lookup
  49. Lee D, Lee J, Heo KN, Kwon K, Moon Y, Lim D, Lee KT, Kim J. Population analysis of the Korean native duck using whole-genome sequencing data.. BMC Genomics 2020 Aug 12;21(1):554.
    doi: 10.1186/s12864-020-06933-zpmc: PMC7430827pubmed: 32787779google scholar: lookup
  50. Zhang Z, Jia Y, Almeida P, Mank JE, van Tuinen M, Wang Q, Jiang Z, Chen Y, Zhan K, Hou S, Zhou Z, Li H, Yang F, He Y, Ning Z, Yang N, Qu L. Whole-genome resequencing reveals signatures of selection and timing of duck domestication.. Gigascience 2018 Apr 1;7(4).
    doi: 10.1093/gigascience/giy027pmc: PMC6007426pubmed: 29635409google scholar: lookup
  51. Lewis GS. Present and future role of small ruminants in animal agriculture. Lat. Am. Arch. Anim. Prod. 2015 23.
  52. Morris ST. Advances in Sheep Welfare. Elsevier; Amsterdam, The Netherlands: 2017. Overview of sheep production systems; pp. 19–35.
  53. Manach C, Donovan JL. Pharmacokinetics and metabolism of dietary flavonoids in humans.. Free Radic Res 2004 Aug;38(8):771-85.
    doi: 10.1080/10715760410001727858pubmed: 15493450google scholar: lookup
  54. Upadhyay M, Hauser A, Kunz E, Krebs S, Blum H, Dotsev A, Okhlopkov I, Bagirov V, Brem G, Zinovieva N, Medugorac I. The First Draft Genome Assembly of Snow Sheep (Ovis nivicola).. Genome Biol Evol 2020 Aug 1;12(8):1330-1336.
    doi: 10.1093/gbe/evaa124pmc: PMC7487135pubmed: 32592471google scholar: lookup
  55. Sabir J, Mutwakil M, El-Hanafy A, Al-Hejin A, Sadek MA, Abou-Alsoud M, Qureshi M, Saini K, Ahmed M. Applying molecular tools for improving livestock performance: From DNA markers to next generation sequencing technologies. J. Food Agric. Environ. 2014;12:541–553.
  56. Smith P, Juengel J, Maclean P, Rand C, Stanton JL. Gestational nutrition 2: gene expression in sheep fetal ovaries exposed to gestational under nutrition.. Reproduction 2019 Jan;157(1):13-25.
    doi: 10.1530/REP-18-0358pubmed: 30394704google scholar: lookup
  57. Reese JT, Childers CP, Sundaram JP, Dickens CM, Childs KL, Vile DC, Elsik CG. Bovine Genome Database: supporting community annotation and analysis of the Bos taurus genome.. BMC Genomics 2010 Nov 19;11:645.
    doi: 10.1186/1471-2164-11-645pmc: PMC3012608pubmed: 21092105google scholar: lookup
  58. Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI, Kusano K, Nagata SI. Rare and common variant discovery by whole-genome sequencing of 101 Thoroughbred racehorses.. Sci Rep 2021 Aug 6;11(1):16057.
    doi: 10.1038/s41598-021-95669-1pmc: PMC8346562pubmed: 34362995google scholar: lookup
  59. Felkel S, Vogl C, Rigler D, Dobretsberger V, Chowdhary BP, Distl O, Fries R, Jagannathan V, Janečka JE, Leeb T, Lindgren G, McCue M, Metzger J, Neuditschko M, Rattei T, Raudsepp T, Rieder S, Rubin CJ, Schaefer R, Schlötterer C, Thaller G, Tetens J, Velie B, Brem G, Wallner B. The horse Y chromosome as an informative marker for tracing sire lines.. Sci Rep 2019 Apr 15;9(1):6095.
    doi: 10.1038/s41598-019-42640-wpmc: PMC6465346pubmed: 30988347google scholar: lookup
  60. Bowling AT, Ruvinsky A. The Genetics of the Horse. CABI; Wallingford, UK: 2000.
  61. Jagannathan V, Gerber V, Rieder S, Tetens J, Thaller G, Drögemüller C, Leeb T. Comprehensive characterization of horse genome variation by whole-genome sequencing of 88 horses.. Anim Genet 2019 Feb;50(1):74-77.
    doi: 10.1111/age.12753pubmed: 30525216google scholar: lookup
  62. Orlando L, Ginolhac A, Zhang G, Froese D, Albrechtsen A, Stiller M, Schubert M, Cappellini E, Petersen B, Moltke I, Johnson PL, Fumagalli M, Vilstrup JT, Raghavan M, Korneliussen T, Malaspinas AS, Vogt J, Szklarczyk D, Kelstrup CD, Vinther J, Dolocan A, Stenderup J, Velazquez AM, Cahill J, Rasmussen M, Wang X, Min J, Zazula GD, Seguin-Orlando A, Mortensen C, Magnussen K, Thompson JF, Weinstock J, Gregersen K, Røed KH, Eisenmann V, Rubin CJ, Miller DC, Antczak DF, Bertelsen MF, Brunak S, Al-Rasheid KA, Ryder O, Andersson L, Mundy J, Krogh A, Gilbert MT, Kjær K, Sicheritz-Ponten T, Jensen LJ, Olsen JV, Hofreiter M, Nielsen R, Shapiro B, Wang J, Willerslev E. Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse.. Nature 2013 Jul 4;499(7456):74-8.
    doi: 10.1038/nature12323pubmed: 23803765google scholar: lookup
  63. Raudsepp T, Gustafson-Seabury A, Durkin K, Wagner ML, Goh G, Seabury CM, Brinkmeyer-Langford C, Lee EJ, Agarwala R, Stallknecht-Rice E, Schäffer AA, Skow LC, Tozaki T, Yasue H, Penedo MC, Lyons LA, Khazanehdari KA, Binns MM, MacLeod JN, Distl O, Guérin G, Leeb T, Mickelson JR, Chowdhary BP. A 4,103 marker integrated physical and comparative map of the horse genome.. Cytogenet Genome Res 2008;122(1):28-36.
    doi: 10.1159/000151313pmc: PMC2587302pubmed: 18931483google scholar: lookup
  64. Huang J, Zhao Y, Shiraigol W, Li B, Bai D, Ye W, Daidiikhuu D, Yang L, Jin B, Zhao Q, Gao Y, Wu J, Bao W, Li A, Zhang Y, Han H, Bai H, Bao Y, Zhao L, Zhai Z, Zhao W, Sun Z, Zhang Y, Meng H, Dugarjaviin M. Analysis of horse genomes provides insight into the diversification and adaptive evolution of karyotype.. Sci Rep 2014 May 14;4:4958.
    doi: 10.1038/srep04958pmc: PMC4021364pubmed: 24828444google scholar: lookup
  65. Ghosh S, Qu Z, Das PJ, Fang E, Juras R, Cothran EG, McDonell S, Kenney DG, Lear TL, Adelson DL, Chowdhary BP, Raudsepp T. Copy number variation in the horse genome.. PLoS Genet 2014 Oct;10(10):e1004712.
    doi: 10.1371/journal.pgen.1004712pmc: PMC4207638pubmed: 25340504google scholar: lookup
  66. Bhati M, Kadri NK, Crysnanto D, Pausch H. Assessing genomic diversity and signatures of selection in Original Braunvieh cattle using whole-genome sequencing data.. BMC Genomics 2020 Jan 8;21(1):27.
    doi: 10.1186/s12864-020-6446-ypmc: PMC6950892pubmed: 31914939google scholar: lookup
  67. Rexroad C, Vallet J, Matukumalli LK, Reecy J, Bickhart D, Blackburn H, Boggess M, Cheng H, Clutter A, Cockett N, Ernst C, Fulton JE, Liu J, Lunney J, Neibergs H, Purcell C, Smith TPL, Sonstegard T, Taylor J, Telugu B, Eenennaam AV, Tassell CPV, Wells K. Genome to Phenome: Improving Animal Health, Production, and Well-Being - A New USDA Blueprint for Animal Genome Research 2018-2027.. Front Genet 2019;10:327.
    doi: 10.3389/fgene.2019.00327pmc: PMC6532451pubmed: 31156693google scholar: lookup
  68. Hu R, Yao R, Li L, Xu Y, Lei B, Tang G, Liang H, Lei Y, Li C, Li X, Liu K, Wang L, Zhang Y, Wang Y, Cui Y, Dai J, Ni W, Zhou P, Yu B, Hu S. A database of animal metagenomes.. Sci Data 2022 Jun 16;9(1):312.
    doi: 10.1038/s41597-022-01444-wpmc: PMC9203544pubmed: 35710683google scholar: lookup
  69. Ko G, Kim PG, Cho Y, Jeong S, Kim JY, Kim KH, Lee HY, Han J, Yu N, Ham S, Jang I, Kang B, Shin S, Kim L, Lee SW, Nam D, Kim JF, Kim N, Kim SY, Lee S, Roh TY, Lee B. Bioinformatics services for analyzing massive genomic datasets.. Genomics Inform 2020 Mar;18(1):e8.
    doi: 10.5808/GI.2020.18.1.e8pmc: PMC7120352pubmed: 32224841google scholar: lookup
  70. Hu ZL, Park CA, Reecy JM. Developmental progress and current status of the Animal QTLdb.. Nucleic Acids Res 2016 Jan 4;44(D1):D827-33.
    doi: 10.1093/nar/gkv1233pmc: PMC4702873pubmed: 26602686google scholar: lookup
  71. Childers CP, Reese JT, Sundaram JP, Vile DC, Dickens CM, Childs KL, Salih H, Bennett AK, Hagen DE, Adelson DL, Elsik CG. Bovine Genome Database: integrated tools for genome annotation and discovery.. Nucleic Acids Res 2011 Jan;39(Database issue):D830-4.
    doi: 10.1093/nar/gkq1235pmc: PMC3013744pubmed: 21123190google scholar: lookup
  72. Chen N, Fu W, Zhao J, Shen J, Chen Q, Zheng Z, Chen H, Sonstegard TS, Lei C, Jiang Y. BGVD: An Integrated Database for Bovine Sequencing Variations and Selective Signatures.. Genomics Proteomics Bioinformatics 2020 Apr;18(2):186-193.
    doi: 10.1016/j.gpb.2019.03.007pmc: PMC7646086pubmed: 32540200google scholar: lookup
  73. Nicolazzi EL, Caprera A, Nazzicari N, Cozzi P, Strozzi F, Lawley C, Pirani A, Soans C, Brew F, Jorjani H, Evans G, Simpson B, Tosser-Klopp G, Brauning R, Williams JL, Stella A. SNPchiMp v.3: integrating and standardizing single nucleotide polymorphism data for livestock species.. BMC Genomics 2015 Apr 10;16(1):283.
    doi: 10.1186/s12864-015-1497-1pmc: PMC4399246pubmed: 25881165google scholar: lookup
  74. Foroutan A, Fitzsimmons C, Mandal R, Piri-Moghadam H, Zheng J, Guo A, Li C, Guan LL, Wishart DS. The Bovine Metabolome.. Metabolites 2020 Jun 5;10(6).
    doi: 10.3390/metabo10060233pmc: PMC7345087pubmed: 32517015google scholar: lookup
  75. Maity S, Bhat AH, Giri K, Ambatipudi K. BoMiProt: A database of bovine milk proteins.. J Proteomics 2020 Mar 20;215:103648.
    doi: 10.1016/j.jprot.2020.103648pubmed: 31958638google scholar: lookup
  76. Hu ZL, Fritz ER, Reecy JM. AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond.. Nucleic Acids Res 2007 Jan;35(Database issue):D604-9.
    doi: 10.1093/nar/gkl946pmc: PMC1781224pubmed: 17135205google scholar: lookup
  77. Wang ZH, Zhu QH, Li X, Zhu JW, Tian DM, Zhang SS, Kang HL, Li CP, Dong LL, Zhao WM, Li MH. iSheep: an Integrated Resource for Sheep Genome, Variant and Phenotype.. Front Genet 2021;12:714852.
    doi: 10.3389/fgene.2021.714852pmc: PMC8418083pubmed: 34490043google scholar: lookup
  78. Tian X, Li R, Fu W, Li Y, Wang X, Li M, Du D, Tang Q, Cai Y, Long Y, Zhao Y, Li M, Jiang Y. Building a sequence map of the pig pan-genome from multiple de novo assemblies and Hi-C data.. Sci China Life Sci 2020 May;63(5):750-763.
    doi: 10.1007/s11427-019-9551-7pubmed: 31290097google scholar: lookup
  79. Schook LB, Beever JE, Rogers J, Humphray S, Archibald A, Chardon P, Milan D, Rohrer G, Eversole K. Swine Genome Sequencing Consortium (SGSC): a strategic roadmap for sequencing the pig genome.. Comp Funct Genomics 2005;6(4):251-5.
    doi: 10.1002/cfg.479pmc: PMC2447480pubmed: 18629187google scholar: lookup
  80. Uenishi H, Morozumi T, Toki D, Eguchi-Ogawa T, Rund LA, Schook LB. Large-scale sequencing based on full-length-enriched cDNA libraries in pigs: contribution to annotation of the pig genome draft sequence.. BMC Genomics 2012 Nov 15;13:581.
    doi: 10.1186/1471-2164-13-581pmc: PMC3499286pubmed: 23150988google scholar: lookup
  81. Uenishi H, Eguchi T, Suzuki K, Sawazaki T, Toki D, Shinkai H, Okumura N, Hamasima N, Awata T. PEDE (Pig EST Data Explorer): construction of a database for ESTs derived from porcine full-length cDNA libraries.. Nucleic Acids Res 2004 Jan 1;32(Database issue):D484-8.
    doi: 10.1093/nar/gkh037pmc: PMC308771pubmed: 14681463google scholar: lookup
  82. Wang MS, Thakur M, Peng MS, Jiang Y, Frantz LAF, Li M, Zhang JJ, Wang S, Peters J, Otecko NO, Suwannapoom C, Guo X, Zheng ZQ, Esmailizadeh A, Hirimuthugoda NY, Ashari H, Suladari S, Zein MSA, Kusza S, Sohrabi S, Kharrati-Koopaee H, Shen QK, Zeng L, Yang MM, Wu YJ, Yang XY, Lu XM, Jia XZ, Nie QH, Lamont SJ, Lasagna E, Ceccobelli S, Gunwardana HGTN, Senasige TM, Feng SH, Si JF, Zhang H, Jin JQ, Li ML, Liu YH, Chen HM, Ma C, Dai SS, Bhuiyan AKFH, Khan MS, Silva GLLP, Le TT, Mwai OA, Ibrahim MNM, Supple M, Shapiro B, Hanotte O, Zhang G, Larson G, Han JL, Wu DD, Zhang YP. 863 genomes reveal the origin and domestication of chicken.. Cell Res 2020 Aug;30(8):693-701.
    doi: 10.1038/s41422-020-0349-ypmc: PMC7395088pubmed: 32581344google scholar: lookup
  83. Wang MS, Zhang JJ, Guo X, Li M, Meyer R, Ashari H, Zheng ZQ, Wang S, Peng MS, Jiang Y, Thakur M, Suwannapoom C, Esmailizadeh A, Hirimuthugoda NY, Zein MSA, Kusza S, Kharrati-Koopaee H, Zeng L, Wang YM, Yin TT, Yang MM, Li ML, Lu XM, Lasagna E, Ceccobelli S, Gunwardana HGTN, Senasig TM, Feng SH, Zhang H, Bhuiyan AKFH, Khan MS, Silva GLLP, Thuy LT, Mwai OA, Ibrahim MNM, Zhang G, Qu KX, Hanotte O, Shapiro B, Bosse M, Wu DD, Han JL, Zhang YP. Large-scale genomic analysis reveals the genetic cost of chicken domestication.. BMC Biol 2021 Jun 16;19(1):118.
    doi: 10.1186/s12915-021-01052-xpmc: PMC8207802pubmed: 34130700google scholar: lookup
  84. Antin PB, Yatskievych TA, Davey S, Darnell DK. GEISHA: an evolving gene expression resource for the chicken embryo.. Nucleic Acids Res 2014 Jan;42(Database issue):D933-7.
    doi: 10.1093/nar/gkt962pmc: PMC3964962pubmed: 24150938google scholar: lookup
  85. Wade CM, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F, Lear TL, Adelson DL, Bailey E, Bellone RR, Blöcker H, Distl O, Edgar RC, Garber M, Leeb T, Mauceli E, MacLeod JN, Penedo MC, Raison JM, Sharpe T, Vogel J, Andersson L, Antczak DF, Biagi T, Binns MM, Chowdhary BP, Coleman SJ, Della Valle G, Fryc S, Guérin G, Hasegawa T, Hill EW, Jurka J, Kiialainen A, Lindgren G, Liu J, Magnani E, Mickelson JR, Murray J, Nergadze SG, Onofrio R, Pedroni S, Piras MF, Raudsepp T, Rocchi M, Røed KH, Ryder OA, Searle S, Skow L, Swinburne JE, Syvänen AC, Tozaki T, Valberg SJ, Vaudin M, White JR, Zody MC, Lander ES, Lindblad-Toh K. Genome sequence, comparative analysis, and population genetics of the domestic horse.. Science 2009 Nov 6;326(5954):865-7.
    doi: 10.1126/science.1178158pmc: PMC3785132pubmed: 19892987google scholar: lookup
  86. Kalbfleisch TS, Rice ES, DePriest MS Jr, Walenz BP, Hestand MS, Vermeesch JR, O Connell BL, Fiddes IT, Vershinina AO, Saremi NF, Petersen JL, Finno CJ, Bellone RR, McCue ME, Brooks SA, Bailey E, Orlando L, Green RE, Miller DC, Antczak DF, MacLeod JN. Improved reference genome for the domestic horse increases assembly contiguity and composition.. Commun Biol 2018;1:197.
    doi: 10.1101/306928pmc: PMC6240028pubmed: 30456315google scholar: lookup
  87. Gim JA, Lee S, Kim DS, Jeong KS, Hong CP, Bae JH, Moon JW, Choi YS, Cho BW, Cho HG, Bhak J, Kim HS. HEpD: a database describing epigenetic differences between Thoroughbred and Jeju horses.. Gene 2015 Apr 10;560(1):83-8.
    doi: 10.1016/j.gene.2015.01.047pubmed: 25637569google scholar: lookup
  88. Lee JR, Hong CP, Moon JW, Jung YD, Kim DS, Kim TH, Gim JA, Bae JH, Choi Y, Eo J, Kwon YJ, Song S, Ko J, Yang YM, Lee HK, Park KD, Ahn K, Do KT, Ha HS, Han K, Yi JM, Cha HJ, Cho BW, Bhak J, Kim HS. Genome-wide analysis of DNA methylation patterns in horse.. BMC Genomics 2014 Jul 15;15(1):598.
    doi: 10.1186/1471-2164-15-598pmc: PMC4117963pubmed: 25027854google scholar: lookup
  89. Procop GW. Molecular diagnostics for the detection and characterization of microbial pathogens.. Clin Infect Dis 2007 Sep 1;45 Suppl 2:S99-S111.
    doi: 10.1086/519259pubmed: 17683022google scholar: lookup
  90. Ammari MG, Gresham CR, McCarthy FM, Nanduri B. HPIDB 2.0: a curated database for host-pathogen interactions.. Database (Oxford) 2016;2016.
    doi: 10.1093/database/baw103pmc: PMC4930832pubmed: 27374121google scholar: lookup
  91. Rahman MT, Sobur MA, Islam MS, Ievy S, Hossain MJ, El Zowalaty ME, Rahman AT, Ashour HM. Zoonotic Diseases: Etiology, Impact, and Control.. Microorganisms 2020 Sep 12;8(9).
    doi: 10.3390/microorganisms8091405pmc: PMC7563794pubmed: 32932606google scholar: lookup
  92. Lange S, Ramirez MI. Editorial: Tissue Remodeling in Health and Disease Caused by Bacteria, Parasites, Fungi, and Viruses.. Front Cell Infect Microbiol 2021;11:642311.
    doi: 10.3389/fcimb.2021.642311pmc: PMC7884623pubmed: 33604310google scholar: lookup
  93. Tenorio J. Emerging zoonotic infectious diseases: A folly of human development. J. Livest. Sci. 2022;13:76–79.
    doi: 10.33259/JLivestSci.2022.76-79google scholar: lookup
  94. van Doorn HR. Emerging infectious diseases.. Medicine (Abingdon) 2014 Jan;42(1):60-63.
    doi: 10.1016/j.mpmed.2013.10.014pmc: PMC3929004pubmed: 24563608google scholar: lookup
  95. Pal S. Incidence of foodborne illness. US Pharm. 2017;42:14.
  96. Suminda GGD, Bhandari S, Won Y, Goutam U, Kanth Pulicherla K, Son YO, Ghosh M. High-throughput sequencing technologies in the detection of livestock pathogens, diagnosis, and zoonotic surveillance.. Comput Struct Biotechnol J 2022;20:5378-5392.
    doi: 10.1016/j.csbj.2022.09.028pmc: PMC9526013pubmed: 36212529google scholar: lookup
  97. Chen J, Yang CC. The Impact of COVID-19 on the Revenue of the Livestock Industry: A Case Study of China.. Animals (Basel) 2021 Dec 17;11(12).
    doi: 10.3390/ani11123586pmc: PMC8697937pubmed: 34944361google scholar: lookup
  98. Leifels M, Khalilur Rahman O, Sam IC, Cheng D, Chua FJD, Nainani D, Kim SY, Ng WJ, Kwok WC, Sirikanchana K, Wuertz S, Thompson J, Chan YF. The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond.. ISME Commun 2022;2(1):107.
    doi: 10.1038/s43705-022-00191-8pmc: PMC9618154pubmed: 36338866google scholar: lookup
  99. Hatcher EL, Zhdanov SA, Bao Y, Blinkova O, Nawrocki EP, Ostapchuck Y, Schäffer AA, Brister JR. Virus Variation Resource - improved response to emergent viral outbreaks.. Nucleic Acids Res 2017 Jan 4;45(D1):D482-D490.
    doi: 10.1093/nar/gkw1065pmc: PMC5210549pubmed: 27899678google scholar: lookup
  100. Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching.. Nucleic Acids Res 2011 Jul;39(Web Server issue):W29-37.
    doi: 10.1093/nar/gkr367pmc: PMC3125773pubmed: 21593126google scholar: lookup
  101. Johnson LS, Eddy SR, Portugaly E. Hidden Markov model speed heuristic and iterative HMM search procedure.. BMC Bioinformatics 2010 Aug 18;11:431.
    doi: 10.1186/1471-2105-11-431pmc: PMC2931519pubmed: 20718988google scholar: lookup
  102. Mistry J, Finn RD, Eddy SR, Bateman A, Punta M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions.. Nucleic Acids Res 2013 Jul;41(12):e121.
    doi: 10.1093/nar/gkt263pmc: PMC3695513pubmed: 23598997google scholar: lookup
  103. Tisza MJ, Belford AK, Domínguez-Huerta G, Bolduc B, Buck CB. Cenote-Taker 2 democratizes virus discovery and sequence annotation.. Virus Evol 2021 Jan;7(1):veaa100.
    doi: 10.1093/ve/veaa100pmc: PMC7816666pubmed: 33505708google scholar: lookup
  104. Roux S, Páez-Espino D, Chen IA, Palaniappan K, Ratner A, Chu K, Reddy TBK, Nayfach S, Schulz F, Call L, Neches RY, Woyke T, Ivanova NN, Eloe-Fadrosh EA, Kyrpides NC. IMG/VR v3: an integrated ecological and evolutionary framework for interrogating genomes of uncultivated viruses.. Nucleic Acids Res 2021 Jan 8;49(D1):D764-D775.
    doi: 10.1093/nar/gkaa946pmc: PMC7778971pubmed: 33137183google scholar: lookup
  105. Mitchell AL, Almeida A, Beracochea M, Boland M, Burgin J, Cochrane G, Crusoe MR, Kale V, Potter SC, Richardson LJ, Sakharova E, Scheremetjew M, Korobeynikov A, Shlemov A, Kunyavskaya O, Lapidus A, Finn RD. MGnify: the microbiome analysis resource in 2020.. Nucleic Acids Res 2020 Jan 8;48(D1):D570-D578.
    doi: 10.1093/nar/gkz1035pmc: PMC7145632pubmed: 31696235google scholar: lookup
  106. Markowitz VM, Korzeniewski F, Palaniappan K, Szeto E, Werner G, Padki A, Zhao X, Dubchak I, Hugenholtz P, Anderson I, Lykidis A, Mavromatis K, Ivanova N, Kyrpides NC. The integrated microbial genomes (IMG) system.. Nucleic Acids Res 2006 Jan 1;34(Database issue):D344-8.
    doi: 10.1093/nar/gkj024pmc: PMC1347387pubmed: 16381883google scholar: lookup
  107. Zhu W, Lomsadze A, Borodovsky M. Ab initio gene identification in metagenomic sequences.. Nucleic Acids Res 2010 Jul;38(12):e132.
    doi: 10.1093/nar/gkq275pmc: PMC2896542pubmed: 20403810google scholar: lookup
  108. Besemer J, Borodovsky M. GeneMark: web software for gene finding in prokaryotes, eukaryotes and viruses.. Nucleic Acids Res 2005 Jul 1;33(Web Server issue):W451-4.
    doi: 10.1093/nar/gki487pmc: PMC1160247pubmed: 15980510google scholar: lookup
  109. Besemer J, Lomsadze A, Borodovsky M. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.. Nucleic Acids Res 2001 Jun 15;29(12):2607-18.
    doi: 10.1093/nar/29.12.2607pmc: PMC55746pubmed: 11410670google scholar: lookup
  110. Kinsella RJ, Kähäri A, Haider S, Zamora J, Proctor G, Spudich G, Almeida-King J, Staines D, Derwent P, Kerhornou A, Kersey P, Flicek P. Ensembl BioMarts: a hub for data retrieval across taxonomic space.. Database (Oxford) 2011;2011:bar030.
    doi: 10.1093/database/bar030pmc: PMC3170168pubmed: 21785142google scholar: lookup
  111. Hammond MP, Birney E. Genome information resources - developments at Ensembl.. Trends Genet 2004 Jun;20(6):268-72.
    doi: 10.1016/j.tig.2004.04.002pubmed: 15145580google scholar: lookup
  112. Birney E, Andrews TD, Bevan P, Caccamo M, Chen Y, Clarke L, Coates G, Cuff J, Curwen V, Cutts T, Down T, Eyras E, Fernandez-Suarez XM, Gane P, Gibbins B, Gilbert J, Hammond M, Hotz HR, Iyer V, Jekosch K, Kahari A, Kasprzyk A, Keefe D, Keenan S, Lehvaslaiho H, McVicker G, Melsopp C, Meidl P, Mongin E, Pettett R, Potter S, Proctor G, Rae M, Searle S, Slater G, Smedley D, Smith J, Spooner W, Stabenau A, Stalker J, Storey R, Ureta-Vidal A, Woodwark KC, Cameron G, Durbin R, Cox A, Hubbard T, Clamp M. An overview of Ensembl.. Genome Res 2004 May;14(5):925-8.
    doi: 10.1101/gr.1860604pmc: PMC479121pubmed: 15078858google scholar: lookup
  113. Jolley KA, Maiden MC. BIGSdb: Scalable analysis of bacterial genome variation at the population level.. BMC Bioinformatics 2010 Dec 10;11:595.
    doi: 10.1186/1471-2105-11-595pmc: PMC3004885pubmed: 21143983google scholar: lookup
  114. Rhead B, Karolchik D, Kuhn RM, Hinrichs AS, Zweig AS, Fujita PA, Diekhans M, Smith KE, Rosenbloom KR, Raney BJ, Pohl A, Pheasant M, Meyer LR, Learned K, Hsu F, Hillman-Jackson J, Harte RA, Giardine B, Dreszer TR, Clawson H, Barber GP, Haussler D, Kent WJ. The UCSC Genome Browser database: update 2010.. Nucleic Acids Res 2010 Jan;38(Database issue):D613-9.
    doi: 10.1093/nar/gkp939pmc: PMC2808870pubmed: 19906737google scholar: lookup
  115. Amos B, Aurrecoechea C, Barba M, Barreto A, Basenko EY, Bażant W, Belnap R, Blevins AS, Böhme U, Brestelli J, Brunk BP, Caddick M, Callan D, Campbell L, Christensen MB, Christophides GK, Crouch K, Davis K, DeBarry J, Doherty R, Duan Y, Dunn M, Falke D, Fisher S, Flicek P, Fox B, Gajria B, Giraldo-Calderón GI, Harb OS, Harper E, Hertz-Fowler C, Hickman MJ, Howington C, Hu S, Humphrey J, Iodice J, Jones A, Judkins J, Kelly SA, Kissinger JC, Kwon DK, Lamoureux K, Lawson D, Li W, Lies K, Lodha D, Long J, MacCallum RM, Maslen G, McDowell MA, Nabrzyski J, Roos DS, Rund SSC, Schulman SW, Shanmugasundram A, Sitnik V, Spruill D, Starns D, Stoeckert CJ, Tomko SS, Wang H, Warrenfeltz S, Wieck R, Wilkinson PA, Xu L, Zheng J. VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center.. Nucleic Acids Res 2022 Jan 7;50(D1):D898-D911.
    doi: 10.1093/nar/gkab929pmc: PMC8728164pubmed: 34718728google scholar: lookup
  116. Harris TW, Antoshechkin I, Bieri T, Blasiar D, Chan J, Chen WJ, De La Cruz N, Davis P, Duesbury M, Fang R, Fernandes J, Han M, Kishore R, Lee R, Müller HM, Nakamura C, Ozersky P, Petcherski A, Rangarajan A, Rogers A, Schindelman G, Schwarz EM, Tuli MA, Van Auken K, Wang D, Wang X, Williams G, Yook K, Durbin R, Stein LD, Spieth J, Sternberg PW. WormBase: a comprehensive resource for nematode research.. Nucleic Acids Res 2010 Jan;38(Database issue):D463-7.
    doi: 10.1093/nar/gkp952pmc: PMC2808986pubmed: 19910365google scholar: lookup
  117. Laing R, Kikuchi T, Martinelli A, Tsai IJ, Beech RN, Redman E, Holroyd N, Bartley DJ, Beasley H, Britton C, Curran D, Devaney E, Gilabert A, Hunt M, Jackson F, Johnston SL, Kryukov I, Li K, Morrison AA, Reid AJ, Sargison N, Saunders GI, Wasmuth JD, Wolstenholme A, Berriman M, Gilleard JS, Cotton JA. The genome and transcriptome of Haemonchus contortus, a key model parasite for drug and vaccine discovery.. Genome Biol 2013 Aug 28;14(8):R88.
    doi: 10.1186/gb-2013-14-8-r88pmc: PMC4054779pubmed: 23985316google scholar: lookup
  118. Doyle SR, Tracey A, Laing R, Holroyd N, Bartley D, Bazant W, Beasley H, Beech R, Britton C, Brooks K, Chaudhry U, Maitland K, Martinelli A, Noonan JD, Paulini M, Quail MA, Redman E, Rodgers FH, Sallé G, Shabbir MZ, Sankaranarayanan G, Wit J, Howe KL, Sargison N, Devaney E, Berriman M, Gilleard JS, Cotton JA. Genomic and transcriptomic variation defines the chromosome-scale assembly of Haemonchus contortus, a model gastrointestinal worm.. Commun Biol 2020 Nov 9;3(1):656.
    doi: 10.1038/s42003-020-01377-3pmc: PMC7652881pubmed: 33168940google scholar: lookup
  119. Stephens PR, Pappalardo P, Huang S, Byers JE, Farrell MJ, Gehman A, Ghai RR, Haas SE, Han B, Park AW, Schmidt JP, Altizer S, Ezenwa VO, Nunn CL. Global Mammal Parasite Database version 2.0.. Ecology 2017 May;98(5):1476.
    doi: 10.1002/ecy.1799pubmed: 28273333google scholar: lookup
  120. Cherry JM, Ball C, Weng S, Juvik G, Schmidt R, Adler C, Dunn B, Dwight S, Riles L, Mortimer RK, Botstein D. Genetic and physical maps of Saccharomyces cerevisiae.. Nature 1997 May 29;387(6632 Suppl):67-73.
    doi: 10.1038/387s067pmc: PMC3057085pubmed: 9169866google scholar: lookup
  121. Engel SR, Dietrich FS, Fisk DG, Binkley G, Balakrishnan R, Costanzo MC, Dwight SS, Hitz BC, Karra K, Nash RS, Weng S, Wong ED, Lloyd P, Skrzypek MS, Miyasato SR, Simison M, Cherry JM. The reference genome sequence of Saccharomyces cerevisiae: then and now.. G3 (Bethesda) 2014 Mar 20;4(3):389-98.
    doi: 10.1534/g3.113.008995pmc: PMC3962479pubmed: 24374639google scholar: lookup
  122. Cherry JM, Hong EL, Amundsen C, Balakrishnan R, Binkley G, Chan ET, Christie KR, Costanzo MC, Dwight SS, Engel SR, Fisk DG, Hirschman JE, Hitz BC, Karra K, Krieger CJ, Miyasato SR, Nash RS, Park J, Skrzypek MS, Simison M, Weng S, Wong ED. Saccharomyces Genome Database: the genomics resource of budding yeast.. Nucleic Acids Res 2012 Jan;40(Database issue):D700-5.
    doi: 10.1093/nar/gkr1029pmc: PMC3245034pubmed: 22110037google scholar: lookup
  123. Mukherjee S, Stamatis D, Bertsch J, Ovchinnikova G, Sundaramurthi JC, Lee J, Kandimalla M, Chen IA, Kyrpides NC, Reddy TBK. Genomes OnLine Database (GOLD) v.8: overview and updates.. Nucleic Acids Res 2021 Jan 8;49(D1):D723-D733.
    doi: 10.1093/nar/gkaa983pmc: PMC7778979pubmed: 33152092google scholar: lookup
  124. Keegan KP, Glass EM, Meyer F. MG-RAST, a Metagenomics Service for Analysis of Microbial Community Structure and Function.. Methods Mol Biol 2016;1399:207-33.
    pubmed: 26791506doi: 10.1007/978-1-4939-3369-3_13google scholar: lookup
  125. Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M, Paczian T, Rodriguez A, Stevens R, Wilke A, Wilkening J, Edwards RA. The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes.. BMC Bioinformatics 2008 Sep 19;9:386.
    doi: 10.1186/1471-2105-9-386pmc: PMC2563014pubmed: 18803844google scholar: lookup
  126. Huerta-Cepas J, Szklarczyk D, Heller D, Hernández-Plaza A, Forslund SK, Cook H, Mende DR, Letunic I, Rattei T, Jensen LJ, von Mering C, Bork P. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses.. Nucleic Acids Res 2019 Jan 8;47(D1):D309-D314.
    doi: 10.1093/nar/gky1085pmc: PMC6324079pubmed: 30418610google scholar: lookup
  127. Shew AM, Snell HA, Nayga RM Jr, Lacity MC. Consumer valuation of blockchain traceability for beef in the United States. Appl. Econ. Perspect. Policy. 2022;44:299–323.
    doi: 10.1002/aepp.13157google scholar: lookup
  128. Pelzer KD, Currin N. Zoonotic Diseases of Cattle. Virginia Cooperative Extension; Blacksburg, VA, USA: 2005.
  129. Masuda T, Nagai M, Yamasato H, Tsuchiaka S, Okazaki S, Katayama Y, Oba M, Nishiura N, Sassa Y, Omatsu T, Furuya T, Koyama S, Shirai J, Taniguchi K, Fujii Y, Todaka R, Katayama K, Mizutani T. Identification of novel bovine group A rotavirus G15P[14] strain from epizootic diarrhea of adult cows by de novo sequencing using a next-generation sequencer.. Vet Microbiol 2014 Jun 25;171(1-2):66-73.
    doi: 10.1016/j.vetmic.2014.03.009pmc: PMC7127257pubmed: 24725447google scholar: lookup
  130. Beato MS, Marcacci M, Schiavon E, Bertocchi L, Di Domenico M, Peserico A, Mion M, Zaccaria G, Cavicchio L, Mangone I, Soranzo E, Patavino C, Cammà C, Lorusso A. Identification and genetic characterization of bovine enterovirus by combination of two next generation sequencing platforms.. J Virol Methods 2018 Oct;260:21-25.
    doi: 10.1016/j.jviromet.2018.07.002pubmed: 29981296google scholar: lookup
  131. Jose T, Joseph A. Domestic animals and zoonosis: A review. Pharma Innov. J. 2020;9:27–29.
  132. Olson ME, Guselle N. Are pig parasites a human health risk?. Adv. Pork Prod. 2000;11:153–162.
  133. FAOSTAT. FAOSTAT Statistical Database. FAO (Food and Agriculture Organization of the United Nations); Rome, Italy: 2016.
  134. FAOSTAT Agriculture Organization Corporate Statistical Database. [(accessed on 6 December 2018)]. Available online: https://www.fao.org/faostat/en/#home.
  135. Dodgson JB, Delany ME, Cheng HH. Poultry genome sequences: progress and outstanding challenges.. Cytogenet Genome Res 2011;134(1):19-26.
    doi: 10.1159/000324413pubmed: 21335957google scholar: lookup
  136. Deeg CA, Hauck SM, Amann B, Pompetzki D, Altmann F, Raith A, Schmalzl T, Stangassinger M, Ueffing M. Equine recurrent uveitis--a spontaneous horse model of uveitis.. Ophthalmic Res 2008;40(3-4):151-3.
    doi: 10.1159/000119867pubmed: 18421230google scholar: lookup
  137. Tenter AM, Heckeroth AR, Weiss LM. Toxoplasma gondii: from animals to humans.. Int J Parasitol 2000 Nov;30(12-13):1217-58.
    doi: 10.1016/S0020-7519(00)00124-7pmc: PMC3109627pubmed: 11113252google scholar: lookup
  138. Skinner LJ, Timperley AC, Wightman D, Chatterton JM, Ho-Yen DO. Simultaneous diagnosis of toxoplasmosis in goats and goatowner's family.. Scand J Infect Dis 1990;22(3):359-61.
    doi: 10.3109/00365549009027060pubmed: 2371548google scholar: lookup
  139. Sacks JJ, Roberto RR, Brooks NF. Toxoplasmosis infection associated with raw goat's milk.. JAMA 1982 Oct 8;248(14):1728-32.
    doi: 10.1001/jama.1982.03330140038029pubmed: 7120593google scholar: lookup
  140. Dubey JP, Lindsay DS, Speer CA. Structures of Toxoplasma gondii tachyzoites, bradyzoites, and sporozoites and biology and development of tissue cysts.. Clin Microbiol Rev 1998 Apr;11(2):267-99.
    doi: 10.1128/CMR.11.2.267pmc: PMC106833pubmed: 9564564google scholar: lookup
  141. Gilchrist CA, Turner SD, Riley MF, Petri WA Jr, Hewlett EL. Whole-genome sequencing in outbreak analysis.. Clin Microbiol Rev 2015 Jul;28(3):541-63.
    doi: 10.1128/CMR.00075-13pmc: PMC4399107pubmed: 25876885google scholar: lookup
  142. Sobel Leonard A, McClain MT, Smith GJ, Wentworth DE, Halpin RA, Lin X, Ransier A, Stockwell TB, Das SR, Gilbert AS, Lambkin-Williams R, Ginsburg GS, Woods CW, Koelle K. Deep Sequencing of Influenza A Virus from a Human Challenge Study Reveals a Selective Bottleneck and Only Limited Intrahost Genetic Diversification.. J Virol 2016 Dec 15;90(24):11247-11258.
    doi: 10.1128/JVI.01657-16pmc: PMC5126380pubmed: 27707932google scholar: lookup
  143. Imanian B, Donaghy J, Jackson T, Gummalla S, Ganesan B, Baker RC, Henderson M, Butler EK, Hong Y, Ring B, Thorp C, Khaksar R, Samadpour M, Lawless KA, MacLaren-Lee I, Carleton HA, Tian R, Zhang W, Wan J. The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems.. NPJ Sci Food 2022 Aug 16;6(1):35.
    doi: 10.1038/s41538-022-00150-6pmc: PMC9381742pubmed: 35974024google scholar: lookup
  144. Hossain MJ, Attia Y, Ballah FM, Islam MS, Sobur MA, Islam MA, Ievy S, Rahman A, Nishiyama A, Islam MS. Zoonotic significance and antimicrobial resistance in Salmonella in poultry in Bangladesh for the period of 2011–2021. Zoonoticdis. 2021;1:3–24.
    doi: 10.3390/zoonoticdis1010002google scholar: lookup
  145. Lynch M, Ackerman MS, Gout JF, Long H, Sung W, Thomas WK, Foster PL. Genetic drift, selection and the evolution of the mutation rate.. Nat Rev Genet 2016 Oct 14;17(11):704-714.
    doi: 10.1038/nrg.2016.104pubmed: 27739533google scholar: lookup
  146. Aswad A, Katzourakis A. Cell-Derived Viral Genes Evolve under Stronger Purifying Selection in Rhadinoviruses.. J Virol 2018 Oct 1;92(19).
    doi: 10.1128/JVI.00359-18pmc: PMC6146799pubmed: 29997213google scholar: lookup
  147. Lauring AS. Within-Host Viral Diversity: A Window into Viral Evolution.. Annu Rev Virol 2020 Sep 29;7(1):63-81.
    doi: 10.1146/annurev-virology-010320-061642pmc: PMC10150642pubmed: 32511081google scholar: lookup
  148. Hughes AL, Hughes MA. More effective purifying selection on RNA viruses than in DNA viruses.. Gene 2007 Dec 1;404(1-2):117-25.
    doi: 10.1016/j.gene.2007.09.013pmc: PMC2756238pubmed: 17928171google scholar: lookup
  149. Arcangeli C, Torricelli M, Sebastiani C, Lucarelli D, Ciullo M, Passamonti F, Giammarioli M, Biagetti M. Genetic Characterization of Small Ruminant Lentiviruses (SRLVs) Circulating in Naturally Infected Sheep in Central Italy.. Viruses 2022 Mar 25;14(4).
    doi: 10.3390/v14040686pmc: PMC9032261pubmed: 35458416google scholar: lookup
  150. Duffy S, Shackelton LA, Holmes EC. Rates of evolutionary change in viruses: patterns and determinants.. Nat Rev Genet 2008 Apr;9(4):267-76.
    doi: 10.1038/nrg2323pubmed: 18319742google scholar: lookup
  151. Combe M, Sanjuan R. Variability in the mutation rates of RNA viruses. Future Virol. 2014;9:605–615.
    doi: 10.2217/fvl.14.41google scholar: lookup
  152. Pareek CS, Smoczynski R, Tretyn A. Sequencing technologies and genome sequencing.. J Appl Genet 2011 Nov;52(4):413-35.
    doi: 10.1007/s13353-011-0057-xpmc: PMC3189340pubmed: 21698376google scholar: lookup
  153. Resources N, Council NR. Critical Role of Animal Science Research in Food Security and Sustainability. National Academies Press; Washington, DC, USA: 2015. Global considerations for animal agriculture research.
    pubmed: 25927118
  154. Rothschild MF, Plastow GS. Applications of genomics to improve livestock in the developing world. Livest. Sci. 2014;166:76–83.
    doi: 10.1016/j.livsci.2014.03.020google scholar: lookup
  155. Jensen K, de Miranda Santos IK, Glass EJ. Using genomic approaches to unravel livestock (host)-tick-pathogen interactions.. Trends Parasitol 2007 Sep;23(9):439-44.
    doi: 10.1016/j.pt.2007.07.006pubmed: 17656152google scholar: lookup
  156. Koehler AV, Jabbar A, Hall RS, Gasser RB. A Targeted "Next-Generation" Sequencing-Informatic Approach to Define Genetic Diversity in Theileria orientalis Populations within Individual Cattle: Proof-of-Principle.. Pathogens 2020 Jun 5;9(6).
    doi: 10.3390/pathogens9060448pmc: PMC7350381pubmed: 32517045google scholar: lookup
  157. Pinnapureddy AR, Stayner C, McEwan J, Baddeley O, Forman J, Eccles MR. Large animal models of rare genetic disorders: sheep as phenotypically relevant models of human genetic disease.. Orphanet J Rare Dis 2015 Sep 2;10:107.
    doi: 10.1186/s13023-015-0327-5pmc: PMC4557632pubmed: 26329332google scholar: lookup
  158. Colitti B, Elisabetta C, Giantonella P, Capucchio MT, Reina R, Bertolotti L, Rosati S. A new NGS approach for SRLV full genome characterisation. Proceedings of the XXXVIII Annual Meeting ECCO 2019; Torino, Italy. 12–14 June 2019; p. 20.

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