An analysis of “Alignments anchored on genomic landmarks can aid in the identification of regulatory elements” by Kannan Tharakaraman et al. Sarah Aerni.

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Presentation transcript:

An analysis of “Alignments anchored on genomic landmarks can aid in the identification of regulatory elements” by Kannan Tharakaraman et al. Sarah Aerni July 8, 2005

Gene Regulation Transcription factors – Cis-acting elements Gene expression is regulated by gene itself (gene acts upon itself) – Trans-acting elements Gene expression is regulated by other genes (gene inhibits another)

Gene Regulation US Department of Energy Office of Science

Motifs Binding sites – Transcription factors – Zinc Finger Hard to identify – Relatively short sequences – Some indices well conserved – Usually localized in certain proximity of the gene

Techniques to Identify Regulatory Elements Enumerative Methods – Align sequences, usually use orthologous genes – Depends on local alignments – Cannot be too similar or too distant Alignment Methods – Create w-mers and find over-represented motifs – Frequency may be misconstrued due to repeats Tharakaraman Technique – Combine both methods – Include word placement with frequency – is the location of Cis-Regulatory regions correlated?

Initial Steps Mask repeats – Avoid identifying repeats as motifs – Maintain one position for possible motifs Align Transcription Start Site (TSS) – Depend on proximity to TSS – Allow for slight shifts – look for clusters

Define Significance Alignment scores – Assign significance using gap penalties from Mock Set – Jittering – watch for overrepresented octonucleotides – ρ = 5 determined to be significant without jittering

TRANSFAC Database of Eukaryotic Transcriptional Regulatory Elements Comparison of TRANSFAC octonucleotides to those identified by paper’s technique

GLAM Sequence input Every sequence arbitrary position and window size chosen – Gapless multiple alignment in window sequences – Uses probability to determine whether windows are repositioned or resized (Gibbs Sampling) “seed” constraints – OOPS (1 occurrence per sequence) – ZOOPS(0 or 1 occurrence per sequence)

Alignment Techniques Different techniques show different results A-GLAM determined to be best – Compare to TRANSFAC – AlignACE cannot function computationally at genomic scale

Distance to TSS Cis-acting element locations determined by blocks Largest number close to 0 (TSS) Identified element correlated with TRANSFAC

Further Discussion Discussion is limited to method results – Little information given on whether location is truly correlated – No Biological discussion Proximity of TSS and Cis-Acting binding sites – Narrow search range to a smaller field – Use in identification of types of element?