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Understanding Human Genetic Variation: Insights from Genomics and Gene Regulation

The human genome is remarkably similar across individuals, with about 99% of DNA sequences being identical. This leaves a mere 1% that accounts for human diversity, making it a critical area of study. Discover how geneticists analyze the genetic differences not only among humans but also between species like humans and chimpanzees, which differ by approximately 1-1.8%. Additionally, the role of stem cells in differentiating into various cell types (e.g., neural, muscle) highlights the intricate regulation of genes, emphasizing the importance of genomic research and technologies for understanding biological systems.

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Understanding Human Genetic Variation: Insights from Genomics and Gene Regulation

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  1. Life Science: Organisms

  2. Genomics “The genetic blueprints of all people generally have the same information, with approximately 99% of one human genome sequence being identical to all others. That makes the 1% of places in the genetic code that account for human variation very interesting…” Momentum Winter 2006-2007, DNA Rubic “Some geneticists have calculated the differences in human and chimpanzee DNA as just over 1%, some at 1.6%, and others at 1.8%.” Momentum Winter 2006-2007, What we learn from Chimpanzees

  3. Genomics Organism Genome size Number of genes http://en.wikipedia.org/wiki/List_of_sequenced_eukaryotic_genomes http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml

  4. Biological Systems http://www.innerbody.com/htm/body.html

  5. Cell types The human embryonic stem cells cultured have been observed to randomly differentiate in culture into a variety of different cell types, including (A) gut, (B) neural cells, (C) bone marrow cells, (D) cartilage, (E) muscle and (F) kidney cells. www.news.wisc.edu/packages/ stemcells/3327.html

  6. A Cell http://micro.magnet.fsu.edu/cells/animalcell.html

  7. They are all the same cells – They all have the same genetic material, The only difference is what is turned on and what is silent.

  8. Central Dogmahttp://www.accessexcellence.org/RC/VL/GG/protein_synthesis.html

  9. DNA

  10. DNA

  11. RNA

  12. Central Dogmahttp://www.accessexcellence.org/RC/VL/GG/protein_synthesis.html

  13. Translation RNA to Protein

  14. Proteins

  15. Gene to Protein

  16. Sites of Regulation

  17. Sites of Regulation

  18. How do we measure it? presence, concentration, activation state, etc. of specific biological molecules. How do we measure the variations?

  19. DNA • Sequencing • Genomic library • Genome sequencing • PCR • SNPs • Linkage analysis

  20. Life Science http://www.genomenewsnetwork.org/articles/06_00/sequence_primer.shtml

  21. Life Science http://www.genomenewsnetwork.org/articles/06_00/sequence_primer.shtml

  22. http://mekentosj.com/4peaks/science.html

  23. Genomic Library

  24. Genome sequencing and Display http://www.genomenewsnetwork.org/articles/06_00/sequence_primer.shtml • BAC-to-BAC method • whole genome shotgun sequencing UCSC Genome Browser • http://genome.ucsc.edu/

  25. Life Science

  26. Microarray Probe hybridization to DNA on chips Probes bind to unique features on chips Flourescent labels highlight bound probes http://www.affymetrix.com

  27. RNAi : RNA silencing http://fig.cox.miami.edu/~cmallery/150/gene/how_siRNA_works.htm

  28. Life Science

  29. Proteomics: Mass Spectrometry http://www.proteomesoftware.com/Proteome_software_ed_mass_spec.html

  30. Proteomics: Mass Spectrometryhttp://www.academysavant.com/cmsp.htm

  31. Yeast 2 hybrid used to measure protein-protein interactions.

  32. Life Science Flow of information

  33. Life Science Flow of information

  34. NCBI Derivative Sequence Data (Maureen J. Donlin, St. Louis University) C C Curators GA ATT GA GA C ATT GA C RefSeq TATAGCCG ACGTGC TATAGCCG AGCTCCGATA CCGATGACAA ATTGACTA CGTGA TTGACA Labs TTGACA TTGACA ACGTGC Genome Assembly TATAGCCG ACGTGC TATAGCCG ATTGACTA CGTGA CGTGA ATTGACTA TATAGCCG CGTGA ATTGACTA ATTGACTA TATAGCCG TTGACA ATTGACTA TATAGCCG TATAGCCG TATAGCCG TATAGCCG ATT C GenBank UniGene GA AT GA C C Algorithms ATT C C GA ATT GA GA ATT GA GA ATT C GA C ATT GA

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