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Comm meeting 03

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Genomic clusters of genes Arabidopsis 43% of genes ... vs recombination rate for each gene, compare to selection models Expression Data NASC Expression data ... – PowerPoint PPT presentation

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Title: Comm meeting 03


1
Is Gene Position Adaptively Favored?
2
Why do we care?
  • Genomic clusters of genes
  • Yeast
  • 98 of genes in metabolic pathways cluster (Lee
    Sonnhammer)
  • 25 of cell-cycle dependent genes are directly
    adjacent (Cho et al.)
  • Drosophila
  • 20 of genes in co-expression clusters (Spellman
    et al.)

3
Why do we care?
  • Genomic clusters of genes
  • Arabidopsis
  • 43 of genes in metabolic pathways cluster (Lee
    Sonnhammer)
  • Blocks of neighboring genes co-express (Williams
    Bowles)
  • Clusters up to 20 genes, 100kb
  • Evolutionary process?

4
Idea to test
  • Gene clusters occur due to evolutionary processes
  • Look for evidence of selection on clusters

5
Method
  • Plot co-expression vs recombination rate for each
    gene, compare to selection models

Co-expression / Co-expression
Recombination rate
Chromosomal position
6
Hill-Robertson Effect
  • Reduction in the efficacy of selection
  • In regions of low recombination, mutations are
    linked
  • This limits the effective population size for
    region
  • Mutations more likely to be fixed in small
    populations

7
The test
  • Selection
  • Relatively neutral - clusters scattered
  • Positive - skew toward high recombination
  • Negative - skew toward low recomb regions

8
Method
  • Plot co-expression vs recombination rate for each
    gene, compare to selection models

Recombination rate
Chromosomal position
9
Recombination rate
  • Estimated for 17.8k genes by Jianhua Hu

cM (genetic dist)
Chromosome position
10
Recombination rate
11
Method
  • Plot co-expression vs recombination rate for each
    gene, compare to selection models

Co-expression / Co-expression
Chromosomal position
12
Expression Data
  • NASC Expression data
  • Affymetrix arrays of Arabidopsis genes
  • 22,700 genes
  • 59 datasets, 534 arrays
  • AtGenExpress data
  • gt500 datasets, 1300 arrays

13
Co-expression measurement
  • Measures of co-expression
  • R Pearson / Spearman correlation
  • Linear relationship between points (scaled)
  • Demonstrate positive or negative correlation
    (-1..1)
  • Euclidean distance
  • Distance between two points
  • Demonstrates correlation (0..1)
  • Calculate for neighboring genes

14
Other factors
  • Factors to consider
  • Tandem duplicates likely to co-express
  • Array conditions

15
Method
  • Plot co-expression vs recombination rate for each
    gene, compare to selection models

Co-expression / Co-expression
Recombination rate
Chromosomal position
16
Regional transcription
  • Mechanisms
  • Matrix attachment sites
  • Change chromatin loops (3D structure)
  • Insulators, Boundary elements

17
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