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Methodologies for motif finding using Comparative Genomics : Strengths and Limitations

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In homologous regions, functional parts evolve more slowly ... Human/Chimp/Mouse/Rat/Chicken/Fugu. The BIG Picture. Motif Finding Using Comparative Genomics ... – PowerPoint PPT presentation

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Title: Methodologies for motif finding using Comparative Genomics : Strengths and Limitations


1
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2
Comparative Genomics in Vertebrates
  • Amol Prakash, Martin Tompa
  • Computer Science Engineering

3
Talk Outline
  • Introduction to gene regulation
  • Comparative Genomics the big picture
  • Analysis
  • Our contribution
  • Future Work

4
Introduction
1. DNA
Gene
Upstream Sequence
5
Introduction
1. DNA
Gene
Upstream Sequence
  • Goal To identify all regulatory elements.
  • Motifs putative regulatory regions

6
Comparative Genomics
  • geneA.human geneB.frog
  • They have evolved from a common ancestor
  • (geneA.fruman)

7
Whole GenomeComparative Genomics
  • Used in yeast
  • Cliften et al. (2003), Kellis et al. (2003)
  • Vertebrates ?
  • Human/Chimp/Mouse/Rat
  • Human/Chimp/Mouse/Rat/Chicken
  • Human/Chimp/Mouse/Rat/Chicken/Fugu

8
The BIG Picture
  • Motif Finding Using Comparative Genomics
  • Module 1 Module 2 Module
    3

Assemble homologous promoter sequences
Find conserved regions i.e. motifs
Validate motifs for their biological significance
9
Module 1 Homologous promoter sequences
  • Hazards
  • Most annotations, homology predictions are highly
    error prone, especially distant species
  • Current tools cannot differentiate wrong
    dataset from correct one.
  • Methods
  • Dataset filters to avoid the above problems

10
Module 2 Search for motifs
  • Hazards
  • Most tools were not intended for this purpose
  • Sensitivity/Specificity issues
  • Method
  • Likelihood based method
  • to evaluate performance of the various tools
  • to evaluate significance of a motif

11
Module 3 Motif treasure
  • Method
  • A statistical clustering of similar motifs
  • Result
  • A high quality list of motifs, many of which are
    novel

12
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13
Future Work
  • Short term goal publishing
  • Long term goals
  • Analyze not-so-highly conserved regions.
  • Very long term goals
  • Analyze more species
  • Dog,cow should be available soon
  • Increase datasize more homologous regions

14
Acknowledgements
  • Mathieu Blanchette
  • Saurabh Sinha
  • Larry Ruzzo
  • Zasha Weinberg
  • Zizhen Yao
  • Nan Li
  • Ensembl Helpdesk
  • GS support staff
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