# Presentation: 157374

## Functional Elements DefinedExperimentally and Computationally

*Drosophila Encode Workshop*
*Dec. 4, 2004*

## Session 1: 10:45-12:15

- Transcripts
- Protein-coding		Mark Yandell (C), Kevin White (E) Transcription Start	Michael Brent (C), Akilesh Pandey (E) Transcription Stop	UTRs
- Alternate Splicing		Steve Mount (E)
- Non-coding			Ian Holmes(C), Eric Lai (E) 		tRNA, rRNAs,
- 	snoRNAs, microRNAs,

## Session 2: 1:15-2:45

- Regulatory elements
- Promoters, DNase sensitivity	Roger Hoskins (E)
- Cis Regulatory Elements		Mike Eisen (C), Sue Celniker (E)
- Enhancers, repressors, silencers, insulators,
- 		Transcription factor binding sites
- 		Conserved sequences of unknown function
- Chromatin Modification		Gary Karpen (E)
- Origins of Replication
- 		Sites of Replication termination
- Genetic variation and Gene Evolution	Andy Clark (C), David Begun (E)
- Wrap-up				Gene Myers

## Experiments & Computation

- How accurate?
- Room for improvement?
- What inputs would help?

- Experiment

- Experiment

- Computation

- DNA sequencing
- cDNA/EST sequencing
- ChIP/chip
- DNAse hypersensitivity

- Validate vs. Refine?
- Cost/benefit analysis

- How accurate?
- Scalability / HTP ?
- Cost/benefit analysis

- Assembly
- WG Alignment
- Protein Gene Prediction
- Cis-Module finding

- 5’ RACE
- RT-PCR
- Transposon Reporters

- Why flies?
- Outputs: Information _& Materials_

## Why Flies?

- “Flies are most like humans”
- Gene features are the most similar to human
- Have a tightly spaced ladder of species as for mammals
- Lot’s of alternative splicing, complex cis-control.
- Closest model for human diseases.
- “Flies are easy to play with”
- Compact genome
- Short generation times, many labs, ...
- “Existing Resources”
- Genomes of 12 species, 50 melanogaster individuals
- More known enhancers than any other organism
- Good array sets, many functional assays.
- Many lines of mutational variants

## State of the Art

- Coding Genes
- Most protein genes located, remainder “unusual”
- Refinement of model: 5’ + 3’ ends, splice junctions, alternate splicing possible
- Comparative methods are improving, could improve more along with alignments.
- Proteomics could further inform transcription
- RNA Genes / The Transcriptome
- Must have comparative data, look for correlated structure
- High throughput validation.  Not currently available.
- Cis-Elements
- Can predict core promoters sufficiently well to assist experimental validation
- Enhancers are much, much harder: current need PWMs or
- Lots of approaches possible:  SELEX, ChIP/chip, Reporter “searches”

## State of the Art

- Higher-Order Structure
- Histone modification is important
- Population Statistics and Disease Correlation
- “Good” model for human disease studies, only viable model for understanding functional consequences of variation
- Long standing pop-stat model

## The Basics

- Enable Comparative Informatics
- Extend ladder with 1 or 2 out species
- Finish some of the 12 (to some greater degree)
- EST/cDNA sequencing of all of the 12 (level?)
- The Usual Suspects
- RACE and/or rt-PCR verification of all coding genes.
- Capped EST sequencing.
- Junction arrays + tiling arrays
- Continued refinement of annotation
- Functional understanding of alternate transcription
- Purification of every (most?) TF’s + SELEX
- ChIP/chip of all TFs + Core promotor proteins
- ChIP/chip of histone modification, DH-map on cell types

## Novel Components

- MS/MS of the proteome (Pandey)
- Complete annotation of the transcriptome (Mount, Lai, Holmes)
- Dros-map + complex phenotype/genotype correlation project (Clark, Begun)
- Recombinant libraries of all transcripts, all enhancers (Celniker, Bellen)
- Time (Development stage) and space (cell type) for all the above