Synthetic Animal: Trends in Animal Breeding and Genetics

Main Article Content

Abolfazl Bahrami
Ali Najafi

Abstract

Synthetic biology is an interdisciplinary branch of biology and engineering. The subject combines various disciplines from within these domains, such as biotechnology, evolutionary biology, molecular biology, systems biology, biophysics, computer engineering, and genetic engineering. Synthetic biology aims to understand whole biological systems working as a unit, rather than investigating their individual components and design new genome. Significant advances have been made using systems biology and synthetic biology approaches, especially in the field of bacterial and eukaryotic cells. Similarly, progress is being made with ‘synthetic approaches’ in genetics and animal sciences, providing exciting opportunities to modulate, genome design and finally synthesis animal for favorite traits.

Article Details

Bahrami, A., & Najafi, A. (2019). Synthetic Animal: Trends in Animal Breeding and Genetics. Insights in Biology and Medicine, 3(1), 007–025. https://doi.org/10.29328/journal.ibm.1001015
Review Articles

Copyright (c) 2019 Bahrami A, et al.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Charles D. On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. Nature. 1859; 5: 502. Ref.: https://goo.gl/Vd9Zda

Wright S. Statistical genetics and evolution. Bull Amer Math Soc 1942; 48: 223–246. Ref.: https://goo.gl/kFP84Y

Fisher RA. The Correlation between Relatives on the Supposition of Mendelian Inheritance. Philosophical Transactions of the Royal Society of Edinburgh. 1918; 52: 399–433. Ref.: https://goo.gl/1FTvrH

Haldane JB. Linkage in poultry. Science. 1921; 54: 663. Ref.: https://goo.gl/ayCNS9

Morgan TH. Sex-limited inheritance in Drosophila. Science. 1910; 32:120–122. Ref.: https://goo.gl/cpCDXv

Lush JL. 1896 - 1982 Biographical Memoirs of the AAAS. Ref.: https://goo.gl/C133gz

Van Vleck LD. Charles Roy Henderson, 1911-1989: A brief biography. J Anim Sci. 1998; 76: 2959–2961. Ref.: https://goo.gl/Gjhraa

Bahrami A, Miraei-Ashtiani SR, Mehrabani-Yeganeh H. Associations of growth hormone secretagogue receptor (GHSR) genes polymorphisms and protein structure changes with carcass traits in sheep. Gene. 2012; 505: 379–383. Ref.: https://goo.gl/GZy8PK

Bahrami A, Behzadi SH, Miraei-Ashtiani SR, Roh SG, Katoh K. Genetic polymorphisms and protein structures in growth hormone, growth hormone receptor, ghrelin, insulin-like growth factor 1 and leptin in Mehraban sheep. Gene. 2013; 527: 397–404. Ref.: https://goo.gl/sZu7RM

Meuwissen TH, Goddard ME. Accurate prediction of genetic values for complex traits by whole-genome resequencing. Genetics. 2010; 185: 623–631. Ref.: https://goo.gl/2jynnU

Meuwissen TH, Hayes BJ, Goddard ME. Prediction of total genetic value using genome-wide dense marker maps. Genetics. 2001; 157: 1819–1829. Ref.: https://goo.gl/CdLnVe

Cole JB, VanRaden PM, O'Connell JR, Van Tassell CP, et al. Distribution and location of genetic effects for dairy traits. J Dairy Sci. 2009; 92: 2931–2946. Ref.: https://goo.gl/Jucx4Q

Daetwyler HD, Kemper KE, van der Werf JH, Hayes BJ. Components of the accuracy of genomic prediction in a multi-breed sheep population. J Anim Sci 2012; 90: 3375–3384. Ref.: https://goo.gl/mhxhnB

Pryce JE, Daetwyler HD. Designing dairy cattle breeding schemes under genomic selection: a review of international research. Anim Prod Sci. 2011; 52: 107–114. Ref.: https://goo.gl/tfrgDu

Schaeffer LR. Strategy for applying genome-wide selection in dairy cattle. J Anim Breed Genet. 2006; 123: 218–223. Ref.: https://goo.gl/iCbuqF

Erbe M, Hayes BJ, Matukumalli LK, Goswami S, Bowman PJ, et al., Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. J Dairy Sci. 2012; 95: 4114–4129. Ref.: https://goo.gl/XfWQiV

Daetwyler HD, Villanueva B, Woolliams JA. Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS ONE. 2008; 3: e3395. Ref.: https://goo.gl/JPHkUa

Goddard M. Genomic selection: prediction of accuracy and maximisation of long term response. Genetica. 2008; 136: 245-257. Ref.: https://goo.gl/SpuwtD

Habier D, Tetens J, Seefried FR, Lichtner P, Thaller G. The impact of genetic relationship information on genomic breeding values in German Holstein cattle. Genet Sel Evol. 2010; 42: 5. Ref.: https://goo.gl/QUYg71

Hayes BJ, Macleod I, Daetwyler MD, Goddard ME. Towards genomic prediction from genome sequence data and the 1000 bull genomes project, Proceedings 4th International Conference on Quantiative Genetics, Edinburgh. 2012; O–54. Ref.: https://goo.gl/rg4DZJ

Sanford JC, Klein TM, Wolf ED, Allen N. Delivery of substances into cells and tissues using a particle bombardment process. Journal of Particulate Science and Technology. 1987; 5: 27–37. Ref.: https://goo.gl/FXPGpK

Klein RM, Wolf ED, Wu R, Sanford JC. High-velocity microprojectiles for delivering nucleic acids into living cells. Nature. 1987; 327: 70–73. Ref.: https://goo.gl/dApfMA

Park F. Lentiviral vectors: are they the future of animal transgenesis? Physiol. Genomics. 2007; 31: 159–173. Ref.: https://goo.gl/2aqAeY

Lee LY, Gelvin SB. T-DNA binary vectors and systems. Plant Physiol. 2008; 146: 325–332. Ref.: https://goo.gl/qamdgR

Jackson DA, Symons RH, Berg P. Biochemical Method for Inserting New Genetic Information into DNA of Simian Virus 40: Circular SV40 DNA Molecules Containing Lambda Phage Genes and the Galactose Operon of Escherichia coli. PNAS. 1972; 69: 2904–2909. Ref.: https://goo.gl/YctKZY

Brophy B, Smolenski G, Wheeler T, Wells D, L'Huillier P, et al. Cloned transgenic cattle produce milk with higher levels of β-casein and κ-casein. Nat Biotechnol. 2003; 21; 157–162. Ref.: https://goo.gl/J24QzX

Clark J. The Mammary Gland as a Bioreactor: Expression, Processing, and Production of Recombinant Proteins. Journal of Mammary Gland Biology and Neoplasia. 1998; 3: 337–350. Ref.: https://goo.gl/EJfyn2

Gordon K, Lee E, Vitale JA, Smith AE, Westphal H, et al. Production of human tissue plasmnogen activator in transgenic mouse milk. Biotechnology. 1987; 5: 1183-1187. Ref.: https://goo.gl/iqhpp6

Anastasia B. Risk Assessment and Mitigation of AquAdvantage Salmon. 2010; ISB News Report. Ref.: https://goo.gl/Jjxcyw

Thomas MA, Roemer GW, Donlan CJ, Dickson BG, Matocq M, et al. Ecology: Gene tweaking for conservation. Nature. 2013; 501: 485–486. Ref.: https://goo.gl/GtDny1

Jaenisch R, Mintz B. Simian virus 40 DNA sequences in DNA of healthy adult mice derived from preimplantation blastocysts injected with viral DNA. Proc Natl Acad. 1974; 71: 1250–1254. Ref.: https://goo.gl/j3DBBS

Sathasivam K, Hobbs C, Mangiarini L, Mahal A, Turmaine M, et al. Transgenic models of Huntington's disease. Philos Trans R Soc Lond B Biol Sci. 1999; 354: 963–969. Ref.: https://goo.gl/7LR7Jo

Spencer LT, Humphries JE, Brantly ML; Transgenic Human Alpha 1-Antitrypsin Study Group. Antibody Response to Aerosolized Transgenic Human Alpha1-Antitrypsin. N Engl J Med. 2005; 352: 2030. Ref.: https://goo.gl/zgqVM4

Schatten G, Mitalipov S. Developmental biology: Transgenic primate offspring. Nature. 2009; 459: 515–516. Ref.: https://goo.gl/nfzPnV

Richard G. Genetically modified cows produce 'human' milk. 2011; Ref.: https://goo.gl/QaBjjC

Wagner JS, McCracken J, Wells DN, Laible G, Targeted microRNA expression in dairy cattle directs production of -lactoglobulin-free, high-casein milk. Proceedings of the National Academy of Sciences. 2012; 109: 16811–16816. Ref.: https://goo.gl/oaZ6hT

Margawati ET. Transgenic Animals: Their Benefits To Human Welfare. Actionbioscience. Retrieved June 29, 2014; Ref.: https://goo.gl/yvMECq

Capecchi MR. Gene targeting in mice: functional analysis of the mammalian genome for the twenty-first century. Nat Rev Genet. 2005; 6: 507–512. Ref.: https://goo.gl/xeXiqP

Cong L, Ran FA, Cox D, Lin S, Barretto R, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. 2013; 339: 819–823. Ref.: https://goo.gl/QkraAU

DiCarlo JE, Norville JE, Mali P, Rios X, Aach J, et al. Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems. Nucleic Acids Res. 2013; 41: 4336–4343. Ref.: https://goo.gl/rT4FKq

Mali P, Yang L, Esvelt KM, Aach J, Guell M, et al. RNA-guided human genome engineering via Cas9. Science. 2013; 339: 823–826. Ref.: https://goo.gl/keJNi3

Friedland AE, Tzur YB, Esvelt KM, Colaiácovo MP, Church GM, et al. Heritable genome editing in C. elegans via a CRISPR-Cas9 system. Nat Methods. 2013; 10: 741–743. Ref.: https://goo.gl/QV1akB

Xue H, Wu J, Li S, Rao MS, Liu Y. Genetic Modification in Human Pluripotent Stem Cells by Homologous Recombination and CRISPR/Cas9 System. Methods Mol Biol. 2016; 1307:173-190. Ref.: https://goo.gl/TtwWqh

Esvelt KM, Wang HH. Genome-scale engineering for systems and synthetic biology. Mol Syst Biol. 2013; 9: 641. Ref.: https://goo.gl/yFaS15

Ling MM, Robinson BH. Approaches to DNA mutagenesis: an overview, Analytical Biochemistry. 1997; 254: 157–178. Ref.: https://goo.gl/ayHjC4

Capecchi MR. Altering the genome by homologous recombination. Science. 1989; 244: 1288-1292. Ref.: https://goo.gl/vZhv6s

de Souza N. Primer: genome editing with engineered nucleases. Nat Meth. 2011; 9: 27-27. Ref.: https://goo.gl/zT5kkz

Chevalier BS, Kortemme T, Chadsey MS, Baker D, Monnat RJ, et al. Design, Activity, and Structure of a Highly Specific Artificial Endonuclease. Molecular Cell. 2002; 10: 895-905. Ref.: https://goo.gl/GuDWgo

Smith J, Grizot S, Arnould S, Duclert A, Epinat JC, et al. A combinatorial approach to create artificial homing endonucleases cleaving chosen sequences. Nucleic Acids Research. 2006; 34: e149. Ref.: https://goo.gl/KMHBAH

Baker M. Gene-editing nucleases. Nat Meth. 2012; 9: 23-26. Ref.: https://goo.gl/qoViMw

Urnov FD, Rebar EJ, Holmes MC, Zhang HS, Gregory PD. Genome editing with engineered zinc finger nucleases. Nat Rev Genet. 2010; 11: 636-646. Ref.: https://goo.gl/gYL6WE

Boissel S, Jarjour J, Astrakhan A, Adey A, Gouble A, et al. megaTALs: a rare-cleaving nuclease architecture for therapeutic genome engineering. Nucleic Acids Research. 2014; 42: 2591–2601. Ref.: https://goo.gl/hEuSdm

Bahrami A, Miraie-Ashtiani SR, Sadeghi M, Najafi A. miRNA-mRNA network involved in folliculogenesis interactome: systems biology approach. Reproduction. 2017; 154: 51-65. Ref.: https://goo.gl/cVfrhx

Bahrami A, Miraie-Ashtiani SR, Sadeghi M, Najafi A, Ranjbar R. Dynamic modeling of folliculogenesis signaling pathways in the presence of miRNAs expression. J Ovarian Res. 2017; 10: 76. Ref.: https://goo.gl/LrNcDQ

Alberghina L, Westerhoff HV. Systems Biology: Definitions and Perspectives. Topics in Current Genetics. 2005; 13: 13–30. Ref.: https://goo.gl/zYUL73

Kholodenko BN, Sauro HM, eds. Systems Biology: Definitions and Perspectives. Topics in Current Genetics. 2005; 13: 357–451.

Chiara R, Gerolamo L. Statistical Tools for Gene Expression Analysis and Systems Biology and Related Web Resources. In Stephen Krawetz, Bioinformatics for Systems Biology. 2009; Humana Press:. 181–205. Ref.: https://goo.gl/Jyuatn

von Bertalanffy L. General System theory: Foundations, Development, Applications. George Braziller. 1976; 295. Ref.: https://goo.gl/d3kjVH

Hodgkin AL, Huxley AF. A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol. 1952; 117: 500–544. Ref.: https://goo.gl/KTq2ER

Noble D. Cardiac action and pacemaker potentials based on the Hodgkin-Huxley equations. Nature.1960; 188: 495–497. Ref.: https://goo.gl/4w7HtK

Rosen R. A Means toward a New Holism. Science. 1968; 161: 34–35. Ref.: https://goo.gl/USthvk

Hunter P. Back down to Earth: Even if it has not yet lived up to its promises, systems biology has now matured and is about to deliver its first results. EMBO Reports. 2012; 13: 408–411. Ref.: https://goo.gl/7eoD7E

Zeng BJ. On the concept of system biological engineering. Communication on Transgenic Animals. 1994a; 6.

Zeng BJ. Transgenic animal expression system – transgenic egg plan (goldegg plan). Communication on Transgenic Animals. 1994b; 1:11

Zeng BJ. From positive to synthetic science. Communication on Transgenic Animals. 1995; 11.

Tomita M, Hashimoto K, Takahashi K, Shimizu TS, Matsuzaki Y, et al. E-CELL: Software Environment for Whole Cell Simulation,. Genome Inform Ser Workshop Genome Inform. 199; P 8: 147–155. Ref.: https://goo.gl/vRcbX5

Karr JR, Sanghvi JC, Macklin DN, Gutschow MV, Jacobs JM, et al. A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell. 2012; 150: 389–401. Ref.: https://goo.gl/H9dwgF

Tavassoly I. Dynamics of Cell Fate Decision Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells. Springer International Publishing. ISBN. 2015; 978-3-319-14961-5. Ref.: https://goo.gl/T5GmRj

Nakano T. Molecular Communication. Cambridge. ISBN. 2013, 978-1-107-02308-6. Ref.: https://goo.gl/EsqF63

Elowitz MB, Leibler S. A synthetic oscillatory network of transcriptional regulators. Nature. 2000; 403: 335–338. Ref.: https://goo.gl/Nw8FLz

Gardner TS, Cantor CR, Collins JJ. Construction of a genetic toggle switch in Escherichia coli. Nature. 2000; 403: 339–342. Ref.: https://goo.gl/Bmkvyg

Channon K, Bromley EH, Woolfson DN. Synthetic Biology through Biomolecular Design and Engineering. Curr Opin Struct Biol. 2008; 18: 491–498. Ref.: https://goo.gl/MpkfdD

Stone M. Life Redesigned to Suit the Engineering Crowd. Microbe. 2006; 1: 566–570. Ref.: https://goo.gl/HkEBp2

Zhang R, Lin Y. DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes. Nucleic Acids Res. 2009; 37: D455–D458. Ref.: https://goo.gl/dmRreS

Juhas M, Eberl L, Glass JI. Essence of life: Essential genes of minimal genomes. Trends Cell Biol. 2011; 21: 562–568. Ref.: https://goo.gl/zt5r8q

Hutchison CA, Peterson SN, Gill SR, Cline RT, White O, et al., Global transposon mutagenesis and a minimal Myco- plasma genome. Science. 1999; 286: 2165–2169. Ref.: https://goo.gl/tU1oag

Goodman AL, Wu M, Gordon JI. Identifying microbial fitness determinants by insertion sequencing using genome-wide transposon mutant libraries. Nat Protoc. 2011; 6: 1969 –1980. Ref.: https://goo.gl/oh2yj1

van Opijnen T, Bodi KL, Camilli A. Tn-seq: High-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms. Nat Methods. 2009; 6: 767–772. Ref.: https://goo.gl/p1bJZf

Christen B, Abeliuk E, Collier JM, Kalogeraki VS, Passarelli B, et al. The essential genome of a bacterium. Mol Syst Biol. 2011; 7: 528. Ref.: https://goo.gl/PRdo5h

Luo H, Lin Y, Gao F, Zhang CT, Zhang R. DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements. Nucleic Acids Res. 2014; 42: D574–D580. Ref.: https://goo.gl/15WnQ7

Wetmore KM, Price MN, Waters RJ, Lamson JS, He J, et al. Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons. MBio. 2015; 6: e00306-15. Ref.: https://goo.gl/cDDxcR

Zhang R, Patena W, Armbruster U, Gang SS, Blum SR, et al. High-throughput genotyping of green algal mutants reveals random distribution of mutagenic insertion sites and endonucleolytic cleavage of transforming DNA. Plant Cell. 2014; 26: 1398–1409. Ref.: https://goo.gl/NwYcc2

Angermayr SA, Gorchs Rovira A, Hellingwerf KJ. Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends Biotechnol. 2015; 33: 352–361. Ref.: https://goo.gl/QsVikZ

Basulto D. Everything you need to know about why CRISPR is such a hot technology. Washington Post. 2015 Retrieved 5 December.

Rollié S, Mangold M, Sundmacher K. Designing biological systems: Systems Engineering meets Synthetic Biology. Chemical Engineering Science. 2012; 69: 1–29. Ref.: https://goo.gl/AiVUFu

Kaznessis YN. Models for synthetic biology. BMC Systems Biology. 2007; 1: 47. Ref.: https://goo.gl/ze2Sdr

Masoudi-Nejad A, Bidkhori G2, Hosseini Ashtiani S2, Najafi A2, Bozorgmehr JH, et al. Cancer systems biology and modeling: microscopic scale and multiscale approaches. Semin. Cancer Biol. 2015; 30: 60–69. Ref.: https://goo.gl/LZwrco

Najafi A, Bidkhori G, Bozorgmehr JH, Koch I, Masoudi-Nejad A. Genome scale modeling in systems biology: algorithms and resources. Curr. Genomics. 2014; 15: 130–159. Ref.: https://goo.gl/KXqKHi

Kosuri S, Church GM. Large-scale de novo DNA synthesis: technologies and applications. Nature Methods. 2014; 11: 499–507. Ref.: https://goo.gl/SHRaZY

Blight KJ, Kolykhalov AA, Rice CM. Efficient initiation of HCV RNA replication in cell culture. Science. 2000; 290: 1972–1974. Ref.: https://goo.gl/j344wQ

Smith HO, Hutchison CA 3rd, Pfannkoch C, Venter JC. Generating a synthetic genome by whole genome assembly: {phi} X174 bacteriophage from synthetic oligonucleotides. Proc Natl Acad Sci USA. 2003; 100: 15440–15445. Ref.: https://goo.gl/ggr443

Gibson DG, Benders GA, Andrews-Pfannkoch C, Denisova EA, Baden-Tillson H, et al. Complete chemical synthesis, assembly, and cloning of a Mycoplasma genitalium genome. Science.2008; 319: 1215–1220. Ref.: https://goo.gl/h3bj48

Kramer BP, Fischer C, Fussenegger M. Biologic gates enable logical transcription control in mammalian cells. Biotechnol. Bioeng. 2004; 87: 478–484. Ref.: https://goo.gl/6NcbQL

Nissim L, Bar-Ziv RH. A tunable dual-promoter integrator for targeting of cancer cells. Mol Syst Biol. 2010; 6: 444. Ref.: https://goo.gl/9KgZ27

Lohmueller JJ, Armel TZ, Silver PA. A tunable zinc finger-based framework for Boolean logic computation in mammalian cells. Nucleic Acids Res. 2012; 40: 5180–5187. Ref.: https://goo.gl/aaS2eL

Qi LS, Larson MH, Gilbert LA, Doudna JA, Weissman JS, et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell. 2013, 152: 1173–1183. Ref.: https://goo.gl/xE5Pzc

Maeder ML, Linder SJ, Cascio VM, Fu Y, Ho QH, et al. CRISPR RNA-guided activation of endogenous human genes. Nat Methods. 2013; 10: 977–979. Ref.: https://goo.gl/zHZdkq

Kiani S, Beal J, Ebrahimkhani MR, Huh J, Hall RN, et al. CRISPR transcriptional repression devices and layered circuits in mammalian cells. Nat Methods. 2014; 11: 723–726. Ref.: https://goo.gl/EE86T4

Nissim L, Perli SD, Fridkin A, Perez-Pinera P, Lu TK. Multiplexed and programmable regulation of gene networks with an integrated RNA and CRISPR/ CAS toolkit in human cells. Mol Cell. 2014; 54: 698–710. Ref.: https://goo.gl/LVgoyy

Fussenegger M, Morris RP, Fux C, Rimann M, von Stockar B, et al. Streptogramin-based gene regulation systems for mammalian cells. Nat Biotechnol. 2000; 18: 1203–1208. Ref.: https://goo.gl/kGbh64

Gillette MU, Sejnowski TJ. Physiology: biological clocks coordinately keep life on time. Science. 2005; 309: 1196–1198. Ref.: https://goo.gl/Bs48Gc

Kaasik K, Lee CC. Reciprocal regulation of haem biosynthesis and the circadian clock in mammals. Nature. 2004; 430: 467–471. Ref.: https://goo.gl/YF6FNt

Covert MW, Leung TH, Gaston JE, Baltimore D. Achieving stability of lipopolysaccharide-induced NF-kappa B activation. Science. 2005; 309: 1854–1857. Ref.: https://goo.gl/wCS2Qk

Lahav G. The strength of indecisiveness: oscillatory behavior for better cell fate determination. Sci STKE. 2004; 55. Ref.: https://goo.gl/ufX2Y8

Tigges M, Marquez-Lago TT, Stelling J, Fussenegger M. A tunable synthetic mammalian oscillator. Nature. 2009; 457: 309–312. Ref.: https://goo.gl/GseoBW

Tigges M, Dénervaud N, Greber D, Stelling J, Fussenegger M. A synthetic low-frequency mammalian oscillator. Nucleic Acids Res. 2010; 38: 2702–2711. Ref.: https://goo.gl/SZy5fZ

Stricker J, Cookson S, Bennett MR, Mather WH, Tsimring LS, et al. A fast, robust and tunable synthetic gene oscillator. Nature. 2008; 456: 516–519. Ref.: https://goo.gl/LPSYtK

Ausländer S, Ausländer D, Müller M, Wieland M, Fussenegger M. Programmable single-cell mammalian biocomputers. Nature. 2012; 487: 123–127. Ref.: https://goo.gl/uU1EVR

Montague MG, Lartigue C, Vashee S. Synthetic genomics: potential and limitations. Current Opinion in Biotechnology. 2012; 23: 659-665. Ref.: https://goo.gl/qa5AYx

Deamer A. giant step towards artificial life? Trends Biotechnol. 2005; 23: 336–338. Ref.: https://goo.gl/4RkuQ6

Malyshev DA, Dhami K, Lavergne T, Chen T, Dai N, et al. A semi-synthetic organism with an expanded genetic alphabet. Nature. 2014; 509: 385–388. Ref.: https://goo.gl/98PDPH

Gibson DG, Glass JI, Lartigue C, Noskov VN, Chuang RY, et al. Creation of a Bacterial Cell Controlled by a Chemically Synthesized Genome. Science. 2010; 329: 52–56. Ref.: https://goo.gl/RTEw3p

Rogers-Hayden T, Pidgeon N. Reflecting upon the UK’s Citizens’ Jury on Nanotechnologies: Nano Jury UK. Nanotechnology Law & Business. 2006; 167-178. Ref.: https://goo.gl/6dmCpM

Wynne B. Creating Public Alienation: Expert Cultures of Risk and Ethics on GMOs. Sci Cult (Lond). 2001; 10: 445-481. Ref.: https://goo.gl/JWk4vh

Gregory R, Fischhoff B, McDaniels T. Acceptable Input: Using Decision Analysis to Guide Public Policy Deliberations. Decision Analysis. 2005; 2: 4-16. Ref.: https://goo.gl/5hhYx2