sarah aerni july 8, 2005

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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 - PowerPoint PPT Presentation

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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?

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