User:Timothee Flutre/Notebook/Postdoc/2011/11/06: Difference between revisions

From OpenWetWare
Jump to navigationJump to search
(→‎Entry title: end of talk E. Whitelaw)
(→‎Entry title: save and reload a R object)
Line 19: Line 19:
** intangible variation (Klaus Gartner): most traits in inbred animals display a normal distribution around the mean -> could the stochastic establishment of epigenetic state underlie such developmental noise? (Whitelaw et al, Dev Cell, 2010))
** intangible variation (Klaus Gartner): most traits in inbred animals display a normal distribution around the mean -> could the stochastic establishment of epigenetic state underlie such developmental noise? (Whitelaw et al, Dev Cell, 2010))
** even in the absence of understanding underlying mechanisms, epigenomic landscapes from individuals will provide new diagnostics tools
** even in the absence of understanding underlying mechanisms, epigenomic landscapes from individuals will provide new diagnostics tools
* save and reload an object with R
toto <- c(1,2,3,4,5)
save(toto, file="toto.RData")
rm(toto)
load("toto.RData")


<!-- ##### DO NOT edit below this line unless you know what you are doing. ##### -->
<!-- ##### DO NOT edit below this line unless you know what you are doing. ##### -->

Revision as of 16:31, 6 November 2011

Project name <html><img src="/images/9/94/Report.png" border="0" /></html> Main project page
<html><img src="/images/c/c3/Resultset_previous.png" border="0" /></html>Previous entry<html>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</html>Next entry<html><img src="/images/5/5c/Resultset_next.png" border="0" /></html>

Entry title

  • video of the talk from Emma Whitelaw at the ASHG conference:
    • epigenetics: the study of changes in gene expression which occur in the absence of mutation but which are mitotically heritable
    • the epigenome undergoes dramatic reprogramming in early development, and that different cell-types acquire specific epigenomes, but how much is hard-wired and how much is modifiable by environment?
    • model system: inbred mice in a "constant" environment
    • example of variegation -> Agouti allele (DNA methylation at the promoter -> change in coat color). Inheritance: no difference whether the father is yellow or brown to the proportion of different coat colors in his offsprings -> clearly non-Mendelian, epigenetics marks have been cleared and reprogrammed between generations
    • could these types of alleles be an explanation for complex and sporadic disease? hard to study in outbred species like humans, so look at MZ twins, but evidence for epigenetics differences is not huge
    • diet of the pregnant female has an impact on the proportion of coat color in her offsprings: not a huge effect but reproducible -> epigenetic states as a record of environmental history. They tried this with ethanol (Chong et al, PLoS Genetics, 2010).
    • inheritance: proportion of different coat color offsprings varies depending on the mother, while it's not the case for the father (Morgan et al, Nature Genetics, 1999) -> epigenetics marks are incompletely cleared from mother to her gametes
    • non-genetic transmission of a metabolic phenotype across generations (Ng et al, Nature, 2010) -> from the father, thus via sperm (we now know that some histones remain, some RNAs also)
    • identify genes involved in epigenetics reprogramming, using transgene mutagenesis (as they can be subject to variegation): they found obvious candidates such as chromatin remodellers (Dnmt1, etc), homozygous lethality is frequent but not always (incomplete penetrance)
    • intangible variation (Klaus Gartner): most traits in inbred animals display a normal distribution around the mean -> could the stochastic establishment of epigenetic state underlie such developmental noise? (Whitelaw et al, Dev Cell, 2010))
    • even in the absence of understanding underlying mechanisms, epigenomic landscapes from individuals will provide new diagnostics tools
  • save and reload an object with R
toto <- c(1,2,3,4,5)
save(toto, file="toto.RData")
rm(toto)
load("toto.RData")