# Presentation: 226808

## Discovery and Characterization of 

**Discovery and Characterization of **
**protein-coding genes in *****D. melanogaster***

**Mark Yandell**
- HHMI
- Berkeley Drosophila
- Genome project

## Slide 2

## Validation & Coordination

**Most fly protein coding genes have been at least provisionally identified.**

**We have just completed a large-scale genome-wide search for**
**additional protein coding genes.**

**Looking for new protein-coding genes means searching very large **
**collections of predictions for only a few additional genes.**

**Doing so in a coordinated and cost effective manner is essential.**

**Validation & Coordination**

## Where would missing genes lie?

- ~50 % of genome is intergenic (61,971,014)

**Where would missing genes lie?**

## Distribution of intergenic lengths

**Distribution of intergenic lengths**

**Genes distributed**
**randomly within Genome**

## Distribution of intergenic lengths

**Distribution of intergenic lengths**

**Genes distributed**
**randomly within Genome**

**Actual distribution**

- 26,346,479 million bp

## 14263 new gene predictions

**1,167**** non-overlapping FgenesH predictions (V. Solovyev)**
**1266****‘new’ genes from Hild et al**
**159 ****control annotations**

**14263**** new gene predictions**

**~62 mega bases of DNA**

**How many are real?**

## 14,263 new gene predictions

**~62 mega bases of DNA**

**Standardized validation procedure**

## validation procedure

- 1. Pool mRNA from 6 different stages
- 2. RVT with T15 TAGGED primer
- 3. PCR w/exon specific primers
- 4. Sequence PCR product
- 5. Realign to genome
- 6. Examine in browser

- PCR PRODUCT

- GENE PREDICTION

- genome browser

- GENE PREDICTION

**validation procedure**

## 14263 new gene predictions

**~62 mega bases of DNA**

**sub-categorization seemed advised**
**          ****homology seemed a logical criterion**

## 34%

**GT**

**AG**

**GT**

**AG**

**‘****new’ genes from***** Hild et al.***

**34%**

***D. p. genome***

***D. p. genome***

***D. p. genome***

**Platinum annotations**

**96%**

**Split  the gene models in to 5 different sets**

**1**

**2**

**3**

**4**

**5**

**About 800 protein coding genes **
**remain to be identified*.**
**~95%* of all fly protein-coding genes have at least**
** ****provisional annotations.**

***Why are there  so many predictions & so few genes?***

**‘****One or none set’**

**‘****two or more set’**

**‘****splice junction**
**conserved set’**

**‘****Heidelberg set’**

- 339
- (339)

- 207
- (207)

- 196
- (1266)

- 293
- (9,276)

**‘****control set’**

- 159

## A negative control

**Random **
**sequence generator**

- AATGCGGATTTGCGGGATTAGGCGTTGAAAAAAAAAGATTCG~

- A=T=G=C=0.25

**Genscan, CpG island finder**

**Examine results**

## CpG

**CpG**

**Genscan**

**Genscan**

- Random DNA contains genes and CpG islands...

- thus we argue that an abundance of predictions is itself not
- evidence for missed genes.

## As far as Genscan is concerned D. melanogaster

**As far as Genscan is concerned *****D. melanogaster***
**intergenic regions look like random DNA.**

- It now appears that much of the genome is transcribed.
- We believe that in many cases spurious predictions
- overlap transcribed regions simply by chance.

##  Confirmation of expression is not 

**   ****confirmation of existence.**

** ****At the very least show that its spliced, **
**   ****or failing that discrete.**

**accurate annotation of each protein-coding gene’s intron-exon structure**
**accurate annotation of every alternate transcript.**
**extend *****in-situ *****information to individual alternative transcripts.**

** ****Determining the true structure of the**
**   ****transcriptome is the next logical step **
**   ****for annotation.**

**For protein-coding genes:**

## Conclusions

**Most fly protein coding genes have been at least provisionally identified.**

**We have just completed a large-scale genome-wide search for**
**Additional protein coding genes.**

**Looking for new protein-coding genes means searching very large **
**collections of predictions for only a few additional genes.**
***-- finding more will require new/retrained gene-finders; casting a wider net.***
***-- this will make for even larger collections of predictions.***

***RE: protein-coding genes the real issue is ‘finalizing’ provisional annotations. This will a computationally & experimentally complex task!***

**Doing so in a coordinated and cost effective manner is essential.**
***Ditto for annotation ‘finalization’ and non-coding RNA genes***

**Conclusions**

## Coordination and

**group A**

**group C**

**group B**

**gene-finder 1**

**gene-finder 2**

**gene-finder 3**

**validation results**

**gff3**

**gff3**

**primers**

**results**

**wet-lab**

**wet-lab**

**Coordination and**
**Standardization will**
**be key!**
** *****of validation procedures***
***of data exchange formats***
***Some centralized coordination***

**Why doing this responsibly will require a common software infrastructure.**

## Acknowledgements

**Acknowledgements**

**Sima Misra**
**Adina Bailey**
**Colin Wiel **
**ShengQiang Shu **
**Joe Carlson**
**Martha Evans-Holm**
**Pavel Tomancak **
**Sue Celniker**

**Suzi Lewis**
**Gerald M. Rubin**