1 / 51

欢迎随时提问、切磋！

欢迎随时提问、切磋！. How does a simple cell turn into a complicated organism? How do genes coordinate and orchestrate the body planning?. Developmental Genetics how genes control development Historical Perspectives Classic developmental genetics (1900-1960)

stu
Télécharger la présentation

欢迎随时提问、切磋！

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 欢迎随时提问、切磋！

  2. How does a simple cell turn into a complicated organism? How do genes coordinate and orchestrate the body planning?

  3. Developmental Genetics • how genes control development • Historical Perspectives • Classic developmental genetics (1900-1960) • mutant phenotypes > what gene was and how it worked? • The impact of molecular ideas (1961-1980) • the discovery of mRNA > gene activities are regulated!

  4. Phenomenon > mechanism • Mutant phenotype > function of WT gene • Development > a program encoded in the genome

  5. Basic approaches: • Saturation mutagenesis • best example: the Nobel-winning Heidelberg screen • Clonal analysis • track cell lineage, fate, behavior…

  6. An ideal organism to study development • Short life cycle (~11 days) • Highly prolific (>100 offsprings / female) • Genetic details established since T.H. Morgan • Relatively small genome (~120Mb, 1/11 of cricket’s) • Only 4 pairs of chromosomes

  7. 4d 1d ~hrs 1d 3d 1d ~11days @ 25C

  8. salivary gland chromosomes: 1024 copies

  9. Those who succeed… …are the most hard-working and persistent.

  10. A Turning Point in the Historyof Developmental Genetics The October 30, 1980 cover “Mutations Affecting Segment Number and Polarity in Drosophila”

  11. Phenomenon > mechanism • Mutant phenotype > function of WT gene • Development > a program encoded in the genome

  12. ~150 development-regulating genes that affect gross morphology in Drosophila stimulated the search for mutant genes affecting development in other systems (nematode and mouse) virtually all the genes involved in early development of Drosophila are represented also in vertebrates an amazing conservation of regulatory mechanisms across over 600 million years of evolution

  13. The generation of A-P axis posterior anterior

  14. WT Bicoid Deficient (maternal)

  15. The hierarchy of gene action

  16. Examples of gene action at the molecular levels

  17. 3’UTR contains localization signal

  18. Fluorescence resonance energy transfer Why this is more accurate than single probe detection?

  19. Denise Montell D. Godt The Sekelsky Lab

  20. Visualiztion of oskar mRNA in fly ovary

  21. The molecular mechanism of Hb-gradient formation: Nanos inhibits Hb translation.

  22. Specific promoter regions of the even-skipped gene control specific transcription bands in the embryo eve gene region

  23. How are the repetitive segments made different from each other?

  24. Homeotic gene expression Why colinearize? All transcription factors

  25. homeo ~ similar

  26. The generation of D-V axis Dorsal Ventral

  27. Early 80’s: 11 maternal effect mutations isolated by Anderson & Nusllein-Volhard Dorsalizing Phenotype Rescued by injecting mRNA from WT egg

  28. The gradient of nuclear Dl protein determines D-V polarity dorsalizing ventralizing WT

  29. A conserved pathway for regulating nuclear transport of transcription factors in Drosophila and mammals. Anderson’s work

  30. Proximal-distal axis

  31. Fly leg

  32. Based on the previous data obtained by experimental approaches, can we generate a mathematical model to predict the unknown? • Can we generate a model that fits current data? • If a model fits observation, prediction can be made. • Prediction has to be validated by experiments.

  33. Reaction-diffusion (Turing model, 1952) Alan Turing: one of the founders of computer science

  34. A computer simulation based on a Turing reaction-diffusion system A photograph of the snail Oliva porphyria (left), and a computer model of the same snail (right) in which the growth parameters of the shell and its pigmentation pattern were both mathematically generated. (From Meinhardt 1998; computer image courtesy of D. Fowler, P. Prusinkiewicz, and H. Meinhardt.)

  35. A computer simulation based on a Turing reaction-diffusion system Actural pattern pigmentation enzyme mut wt Coputer model (From Asai et al. 1999; photographs courtesy of S. Kondo.)

  36. Models can only be as good as the data on which it is based, genetic analyses are indispensable for another k years!

  37. A case study • Name a few morphogens • How many diverse structures they’re involved?

  38. Why the haltere doesn’t become another wing? How is the same morphogen system modulated to generate diver structures?

  39. Dpp-Z A P Dally: a glypican, or heparin sulfate proteoglycans

  40. Dpp made in the wing is able to travel further from AP organizer cells than is Dpp made in the haltere. • Why is that? • The Tkv (receptor)-mediated narrowing of the Dpp activity profile (reflected by pMad) in the haltere contributes to the smaller size. • Differential levels of Dally

  41. dally expression and Dpp signaling are reduced in the posterior haltere.

  42. Using dally-lacZ as a reporter, What’s the phenotype of Ubx-/-, en-/-, or antagonizing Dpp signalling?

  43. What’s the effect of over-expressing dally?

  44. Your conclusions?

More Related