Kara M Dismuke Week 10 Journal: Difference between revisions

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**regulatory effect on gene can be expressed with a combination of its regulators
**regulatory effect on gene can be expressed with a combination of its regulators
*Equations
*Equations
**EQUATION 1
**EQUATION 1 [[Image: Mml-math-9.gif]]
***b: parameter that represents the initial delay or unspecific bias from regulatory effects associated with gene expression
***b: parameter that represents the initial delay or unspecific bias from regulatory effects associated with gene expression
***g: regulatory effect for particular gene
***g: regulatory effect for particular gene

Revision as of 20:08, 22 March 2015

Outline

Introduction

Regulation of gene expression

  • important process in cell
  • takes static information (in DNA) and transmits it into protein molecules (that serve various functions)
  • requires recognition of specific promoter sequences
  • the effects of transcription change with as the cell changes/develops

Microarrays

  • document changes in gene expression over time
    • analysis these changes can enable one to see a relationship between genes and their regulators
  • use microarray data to track the interaction between genes and their regulators

Saccharomyces cerevisiae

  • gene-expression data gathered from genome-wide microarrays
  • data analyzed using clustering methods
  • data modeled using singular value decomposition
  • genes were grouped according to their transcriptional regulatory networks (i.e. relationship between the genes and their respective regulators/promoters)

Previous Studies

  • use differential equations to try to develop a linear model that reflects the transcription pattern of each of the genes being studied
  • Woolf and Wang: used "fuzzy logic" to try to do this
    • Nachman: used kinetic model and Bayesian networks
    • Bar-Joseph: used genomic information and analysis of gene expression data
      • Wang and Makita: building of Bar-Joseph approach, the looked at the analysis of the promoter sequences and the sigma factor binding sequence motif

This Paper

  • alternative method b/c uses a nonlinear differential equation model
  • Procedure
    • choose set of all potential regulators (chose pool of 184)
    • choose set of target genes of S. cerevisiae (chose 40)
    • picks genes from possible regulators and applies model to then compare results to information known about the target gene
      • repeated to exhaust all possibilites
      • determine which regulators correctly model gene expression model
  • compare results and make conclusions using results from other studies & also a comparison of the linear model
  • result: this method can correctly identify a target gene's specific regulator and can say whether or not that regulator is an activator or repressor

Results

Dynamic model of transcription control

  • Model's Assumptions
    • recursive action of regulators on target gene (over time)
    • regulatory effect on gene can be expressed with a combination of its regulators
  • Equations
    • EQUATION 1
      • b: parameter that represents the initial delay or unspecific bias from regulatory effects associated with gene expression
      • g: regulatory effect for particular gene
      • wj: regulatory wegihts
      • yj: expression level of regulators
      • j=1,2,...m
        • m: the number of regulators controlling the gene
    • EQUATION 2
      • ρ: regulatory effects of other genes
      • x: effect of degradation
      • degradation: x = k*z where k is a constant in this kinetic equation
      • ρ and x make up the rate of expression of a target gene (dz/dt)
    • EQUATION 3*
      • z: target expression level
      • complete model for control of target gene expression z
    • EQUATION 4
      • k1: maximal rate of expression
      • k2: rate of degradation of target gene product
      • simplification of Equation 3
    • EQUATION 5
      • y: approximated with polynomial of degree n
      • APPROX OF Y
    • EQUATION 6
      • Once we have the expression profiles Z {z(t)} of the target and Y {y(t)} of the regulator genes, we search for gene profiles that minimize the mean square error function.
      • t: 1,2,...Q
        • Q: data points computed using Equation 4
      • {zc(t)}: reconstructed profile of z(t) in Z at all time points
    • EQUATION 7
    • Linear form of the model
      • parameters di (i=0,1,2): computed by minimizing error in function 6

Definitions

  1. transcription
    • Transcription is the first step of gene expression, in which a particular segment of DNA is copied into RNA by the enzyme RNA polymerase. Both RNA and DNA are nucleic acids, which use base pairs of nucleotides as a complementary language that can be converted back and forth from DNA to RNA by the action of the correct enzymes. During transcription, a DNA sequence is read by an RNA polymerase, which produces a complementary, antiparallel RNA strand called a primary transcript. As opposed to DNA replication, transcription results in an RNA complement that includes the nucleotide uracil (U) in all instances where thymine (T) would have occurred in a DNA complement. Also unlike DNA replication where DNA is synthesized, transcription does not involve an RNA primer to initiate RNA synthesis.Although Transcription is nice.
    • http://www.biology-online.org/dictionary/Transcription
  2. RNA polymerase
    • An enzyme that is responsible for making rna from a dna template. In all cells RNAP is needed for constructing rna chains from a dna template, a process termed transcription. In scientific terms, RNAP is a nucleotidyl transferase that polymerizes ribonucleotides at the 3' end of an rna transcript. Rna polymerase enzymes are essential and are found in all organisms, cells, and many viruses.
    • http://www.biology-online.org/dictionary/RNA_polymerase
  3. promoter
  4. activator
  5. repressor
  6. regulator
  7. mRNA
  8. gene expression
  9. punative
  10. combinatorial
    • Any system using a random assortment of components at any positions in the linear arrangement of atoms, i.e., a combinatorial library of mutations could contain positions where all four bases have been randomly inserted.
    • http://www.biology-online.org/dictionary/Combinatorial