Book contents
- Genetics, Ethics, and Education
- Current Perspectives in Social and Behavioral Sciences
- Genetics, Ethics, and Education
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Abbreviations
- Introduction
- 1 What Is Heritability and Why Does It Matter?
- 2 Molecular Genetics and Genomics
- 3 Can (and Should) We Personalize Education Along Genetic Lines? Lessons from Behavioral Genetics
- 4 Early Adversity and Epigenetics: Implications for Early Care and Educational Policy
- 5 Intelligence: The Ongoing Quest for Its Etiology
- 6 A Behavioral Genetic Perspective on Non-Cognitive Factors and Academic Achievement
- 7 Precision Education Initiative: The Possibility of Personalized Education
- 8 Using Genetic Etiology to Intervene with Students with Intellectual Disabilities
- 9 Ethical Implications of Behavioral Genetics on Education
- 10 Genomic Literacy and the Communication of Genetic and Genomic Information
- 11 Legal Issues Associated with the Introduction of Genetic Testing to the Education System
- 12 Ethical Risks and Remedies in Social-Behavioral Research Involving Genetic Testing
- 13 Development of the Personal Genomics Industry
- 14 Ethical Issues in Using Genomics to Influence Educational Practice
- 15 Teaching and Genetic/Genomic Variation: An Educator’s Perspective
- 16 Will the Next Einstein Get Left in the Petri Dish? Be Careful What You Wish for in the Designer Baby Era
- Conclusion: How Might School Systems Use Genetic Data?
- Index
- References
2 - Molecular Genetics and Genomics
Published online by Cambridge University Press: 06 October 2017
Book contents
- Genetics, Ethics, and Education
- Current Perspectives in Social and Behavioral Sciences
- Genetics, Ethics, and Education
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Abbreviations
- Introduction
- 1 What Is Heritability and Why Does It Matter?
- 2 Molecular Genetics and Genomics
- 3 Can (and Should) We Personalize Education Along Genetic Lines? Lessons from Behavioral Genetics
- 4 Early Adversity and Epigenetics: Implications for Early Care and Educational Policy
- 5 Intelligence: The Ongoing Quest for Its Etiology
- 6 A Behavioral Genetic Perspective on Non-Cognitive Factors and Academic Achievement
- 7 Precision Education Initiative: The Possibility of Personalized Education
- 8 Using Genetic Etiology to Intervene with Students with Intellectual Disabilities
- 9 Ethical Implications of Behavioral Genetics on Education
- 10 Genomic Literacy and the Communication of Genetic and Genomic Information
- 11 Legal Issues Associated with the Introduction of Genetic Testing to the Education System
- 12 Ethical Risks and Remedies in Social-Behavioral Research Involving Genetic Testing
- 13 Development of the Personal Genomics Industry
- 14 Ethical Issues in Using Genomics to Influence Educational Practice
- 15 Teaching and Genetic/Genomic Variation: An Educator’s Perspective
- 16 Will the Next Einstein Get Left in the Petri Dish? Be Careful What You Wish for in the Designer Baby Era
- Conclusion: How Might School Systems Use Genetic Data?
- Index
- References
- Type
- Chapter
- Information
- Genetics, Ethics and Education , pp. 45 - 62Publisher: Cambridge University PressPrint publication year: 2017
References
Bamshad, M. J., Ng, S. B., Bigham, A. W., Tabor, H. K., Emond, M. J., Nickerson, D. A., et al. (2011). Exome sequencing as a tool for Mendelian disease gene discovery. Nature Review Genetics, 12(11), 745–755. doi:10.1038/nrg3031Google Scholar
Botstein, D., & Risch, N. (2003). Discovering genotypes underlying human phenotypes: Past successes for Mendelian disease, future approaches for complex disease. Nature Genetics, 33(suppl.), 228–237. doi:10.1038/ng1090Google Scholar
Boycott, K. M., Vanstone, M. R., Bulman, D. E., & MacKenzie, A. E. (2013). Rare-disease genetics in the era of next-generation sequencing: Discovery to translation. Nature Reviews Genetics, 14(10), 681–691. doi:10.1038/nrg3555Google Scholar
Campbell, C. D., & Eichler, E. E. (2013). Properties and rates of germline mutations in humans. Trends in Genetics, 29(10), 575–584. doi:10.1016/j.tig.2013.04.005Google Scholar
Coe, B. P., Witherspoon, K., Rosenfeld, J. A., van Bon, B. W., Vulto-van Silfhout, A. T., Bosco, P., et al. (2014). Refining analyses of copy number variation identifies specific genes associated with developmental delay. Nature Genetics, 46, 1063–1071. doi:10.1038/ng.3092Google Scholar
Cooper, G. M., Nickerson, D. A., & Eichler, E. E. (2007). Mutational and selective effects on copy-number variants in the human genome. Nature Genetics, 39(S), 22–29. doi:10.1038/ng2054Google Scholar
Gerstein, M. B., Bruce, C., Rozowsky, J. S., Zheng, D., Du, J., Korbel, J. O., et al. (2007). What is a gene, post-ENCODE? History and updated definition. Genome Research, 17(6), 669–681. doi:10.1101/gr.6339607Google Scholar
Gibson, G. (2012). Rare and common variants: Twenty arguments. Nature Reviews Genetics, 13(2), 135–145. doi:10.1038/nrg3118Google Scholar
Girirajan, S., Brkanac, Z., Coe, B. P., Baker, C., Vives, L., Vu, T. H., et al. (2011). Relative burden of large CNVs on a range of neurodevelopmental phenotypes. PLoS Genetics, 7(11), e1002334. doi:10.1371/journal.pgen.1002334Google Scholar
Goldstein, D. B., Allen, A., Keebler, J., Margulies, E. H., Petrou, S., Petrovski, S., et al. (2013). Sequencing studies in human genetics: Design and interpretation. Nature Review Genetics, 14(7), 460–470. doi:10.1038/nrg3455Google Scholar
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., et al. (2012). An anatomically comprehensive atlas of the adult human brain transcriptome. Nature, 489, 391–399. doi:10.1038/nature11405Google Scholar
International Human Genome Sequencing Consortium. (2001). Initial sequencing and analysis of the human genome. Nature, 409(6822), 860–921. doi:10.1038/35057062Google Scholar
International Human Genome Sequencing Consortium. (2004). Finishing the euchromatic sequence of the human genome. Nature, 431(7011), 931–945. doi:10.1038/nature03001Google Scholar
Itsara, A., Cooper, G. M., Baker, C., Girirajan, S., Li, J., Absher, D., et al. (2009). Population analysis of large copy number variants and hotspots of human genetic disease. The American Journal of Human Genetics, 84(2), 148–161. doi:10.1016/j.ajhg.2008.12.014Google Scholar
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., et al. (2011). Spatio-temporal transcriptome of the human brain. Nature, 478(7370), 483–489. doi:10.1038/nature10523Google Scholar
Keightley, P. D. (2012). Rates and fitness consequences of new mutations in humans. Genetics, 190(2), 295–304. doi:10.1534/genetics.111.134668Google Scholar
Kircher, M., & Kelso, J. (2010). High-throughput DNA sequencing – Concepts and limitations. Bioessays, 32, 524–536. doi:10.1002/bies.200900181Google Scholar
Lynch, M. (2010). Rate, molecular spectrum, and consequences of human mutation. Proceedings of the National Academy of Sciences, 107(3), 961–968. doi:10.1073/pnas.0912629107Google Scholar
Naumova, O. Y., Lee, M., Rychkov, S. Y., Vlasova, N. V., & Grigorenko, E. L. (2013). Gene expression in the human brain: The current state of the study of specificity and spatiotemporal dynamics. Child Development, 84(1), 76–88. doi:10.1111/cdev.12014Google Scholar
Pearson, H. (2006). Genetics: What is a gene? Nature, 441, 398–401. doi:10.1038/441398aGoogle Scholar
Sanger, F., & Coulson, A. R. (1975). A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase. Journal of Molecular Biology, 94(3), 441–448. doi:10.1016/0022-2836(75)90213-2Google Scholar
Sanger, F., Nicklen, S., & Coulson, A. R. (1977). DNA sequencing with chain-terminating inhibitors. Proceedings of the National Academy of Sciences, 74(12), 5463–5467.Google Scholar
Segura, M., Pedreno, C., Obiols, J., Taurines, R., Pamias, M., Grunblatt, E., et al. (2015). Neurotrophin blood-based gene expression and social cognition analysis in patients with autism spectrum disorder. Neurogenetics, 16(2), 123–131. doi:10.1007/s10048-014-0434-9Google Scholar
Schork, N. J., Murray, S. S., Frazer, K. A., & Topol, E. J. (2009). Common vs. rare allele hypotheses for complex diseases. Current Opinion in Genetics & Development, 19(3), 212–219. doi:10.1016/j.gde.2009.04.010Google Scholar
Sollis, S., Graham, S. A., Vino, A., Froehlich, H., Vreeburg, M., Dimitropoulou, D., et al. (2015). Identification and functional characterization of de novo FOXP1 variants provides novel insights into the etiology of neurodevelopmental disorder. Human Molecular Genetics. doi:10.1093/hmg/ddv495Google Scholar
Sullivan, P. F., Fan, C., & Perou, C. M. (2006). Evaluating the comparability of gene expression in blood and brain. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 141B(3), 261–268. doi:10.1002/ajmg.b.30272Google Scholar
The 1000 Genomes Project Consortium. (2010). A map of human genome variation from population-scale sequencing. Nature, 467(7319), 1061–1073. doi:10.1038/nature09534Google Scholar
The ENCODE Project Consortium. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489(7414), 57–74. doi:10.1038/nature11247Google Scholar
van Dijk, E. L., Auger, H., Jaszczyszyn, Y., & Thermes, C. (2014). Ten years of next-generation sequencing technology. Trends in Genetics, 30(9), 418–426. doi:10.1016/j.tig.2014.07.001Google Scholar
Yuen, R. K. C., Thiruvahindrapuram, B., Merico, D., Walker, S., Tammimies, K., Hoang, N., et al. (2015). Whole-genome sequencing of quartet families with autism spectrum disorder. Nature Medicine, 21, 185–191. doi:10.1038/nm.3792Google Scholar