Kara M Dismuke Week 10 Journal

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 weights
• 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

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
   • A site in a DNA molecule at which RNA polymerase and transcription factors bind to initiate transcription of mRNA.
   • http://www.biology-online.org/dictionary/Promoter
4. activator
   • A DNA-binding transcription metabolite that positively modulates an allosteric Enzyme or regulates one or more genes by increasing the rate of transcription.
   • http://www.biology-online.org/dictionary/Activator
5. repressor
   • A regulatory protein that binds to an operator and blocks transcription of the genes of an opreon
   • http://www.biology-online.org/dictionary/Repressor
6. regulator
   • In genetics, a regulator pertains to a gene that codes for substances capable of repressing expression of another gene.
   • http://www.biology-online.org/dictionary/Regulator
7. mRNA
   • Abbreviated form for messenger ribonucleic acid, the type of RNA that codes for the chemical blueprint for a protein (during protein synthesis).
   • http://www.biology-online.org/dictionary/Mrna
8. gene expression
   • The conversion of the information from the gene into mRNA via transcription and then to protein via translation resulting in the phenotypic manifestation of the gene.
   • http://www.biology-online.org/dictionary/Gene_Expression
9. punative
   • Denoting a supposition or inference based on what was commonly believed, reputed, or deemed rather than on a direct evidence
   • http://www.biology-online.org/dictionary/Putative
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