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Updating the Model Definition of the Gene in the Modern Genomic Era with Implications for Instruction

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Abstract

Gericke and Hagberg (G & H, Sci Educ 16:849–881, 2007) recently published in this journal a thoughtful analysis of the historical progression of our understanding of the nature of the gene for use in instruction. This analysis, however, did not include the findings of the Human Genome Project (HGP), which must be included in any introductory genetics in the modern genomic era today. Many of these findings, especially the limited number of genes and the similarity of this number to that of primitive animals such as roundworms, were surprising and led to questions about the definition of the gene, many of which are addressed in this manuscript. The G & H models are also amended to include crucial concepts, including the history of determining that DNA and not protein is the molecule of inheritance, the work of Barbara McClintock and the discovery of transposons, polygenic/multi-factorial inheritance, and reverse transcription. The following discussion further extends the G & H work to include the more recent work of the ENCyclopedia Of DNA Elements (ENCODE) Project. The results of this work have resulted in even more fundamental questions about the gene. For example, large sections of the genome that were previously identified as non-protein-coding ‘junk’ have been shown to be transcribed into RNA that is likely involved in regulation of genome function that might be more crucial than the coding DNA itself in distinguishing simpler from more complex species. Should these transcribed but not translated sequences be recognized as genes? This level of questioning of our basic definition has not occurred since the modern synthesis of genetics based on the work of Watson and Crick and makes this one of the most exciting times for genetics and medicine.

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Notes

  1. Techniques have now been developed to address this question, including microarray hybridization, serial analysis of gene expression (SAGE), cDNA mapping, and sequencing of expressed sequence tags.

  2. ORFs with unknown functions are sometimes referred to as ‘nominal’ or ‘putative genes’.

  3. For more on the Gene Sweepstakes, see http://query.nytimes.com/gst/fullpage.html?res=9A02E0D81230F930A35755C0A9659C8B63.

  4. Given the later attention to recombination, mutation, and function separately in the work of Seymour Benzer and his adherents, we prefer to separate these concepts in the earlier map to make them more parallel for study by students. Also for instructional purposes, we prefer to place the function concept as intermediary between the enzyme and trait it produces because the function of the enzyme is in fact what results in the effect on the phenotype—the ‘trait’.

  5. For more visual learners, we have also added a simple cartoon of gene structure to each model.

  6. The first author actually has CMT. Using examples of genetic traits that students can see in themselves or people they know can reinforce relevance and enhance motivation.

  7. CMT is also an excellent teaching example of a trait that is typically inherited in a Mendelian dominant fashion but is uncommon in the population at large. This fact can be used to generate discussion that helps to counter the common student misconception that dominant traits are somehow necessarily ‘dominant’ (frequent/common) in the population and, of course, that recessive traits are rare.

  8. Likewise, penetrance and expressivity may vary with the specific mutation.

  9. Historically, it might be appropriate to recognize transposons and dispersed regulation as parts of the pre-HGP understanding of the gene, but in fact the impact of these observations was largely ignored as ‘noise’ before the HGP sequencing and other research made it obvious that a paradigm shift in the definition of the gene was required.

  10. For an update, see http://www.ncbi.nlm.nih.gov/mapview/stats/BuildStats.cgi?taxid=9606&build=36&ver=2#GBSourceSeq.

  11. For more information about the HGP, see http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml.

  12. Non-random distribution of codons.

  13. Analysis of the function of various sequences is possible by a variety of methods, including computer comparison of the unknown sequence to sequences of known function in other organisms.

  14. or ‘transfrags’.

  15. These experiments may, for example, be transcriptional tiling array experiments. In this view, gene models may be thought of as splicing graphs. For more, see Gerstein et al. 2007, p. 676.

  16. http://www.ornl.gov/sci/techresources/Human_Genome/glossary/glossary_g.shtml.

  17. SNPs are single-nucleotide polymorphisms, ‘points in the genome sequence where one large fraction of the human population has one nucleotide while another large fraction has another’ (Alberts et al. 2002, p. 464). SNPs can be thought of as alleles of a locus.

  18. A megabase is the unit of length for DNA fragments equal to 1 million nucleotides and roughly equal to 1 cM. http://www.ornl.gov/sci/techresources/Human_Genome/glossary/glossary_m.shtml.

  19. A valuable reference on McClintock’s work that is also accessible to student readers is Keller (1936).

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Authors and Affiliations

  1. Department of Internal Medicine, Mercer University School of Medicine, Macon, GA, 31201, USA

    Mike U. Smith

  2. Department of Biochemistry and Curriculum & Instruction, Kansas City University of Medicine & Biosciences, Kansas City, MO, 64119, USA

    Linda R. Adkison

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Correspondence to Mike U. Smith.

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Smith, M.U., Adkison, L.R. Updating the Model Definition of the Gene in the Modern Genomic Era with Implications for Instruction. Sci & Educ 19, 1–20 (2010). https://doi.org/10.1007/s11191-008-9161-7

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