1. Computational Identification of Drosophila microRNA Genes Journal Club 09/05/03 Jared Bischof

2. Computational Identification of Drosophila microRNA Genes What are microRNAs? Evolutionarily conserved genomic sequences ~22nt non-coding RNAs They form extended stem-loop structures They are presumed to have post- transcriptional regulatory activity

3. Computational Identification of Drosophila microRNA Genes microRNA structure

4. Computational Identification of Drosophila microRNA Genes Reference Set 24 Drosophila pre-miRNA sequences These were analyzed in order to derive rules and parameters that could be used to describe microRNAs in anonymous genomic sequence By examining D. melanogaster and D. pseudoobscura they determined that the reference set of pre-miRNAs was highly conserved What does this mean?

5. Computational Identification of Drosophila microRNA Genes Alignment of Drosophila melanogaster and Drosophila pseudoobscura Program used: AVID (a global alignment tool) Sequence included:  Intronic and intergenic sequence Sequence omitted:  Exons, transposable elements, snRNA, snoRNA, tRNA and rRNA genes Result:  51.3 out of 90.2 megabases of intronic and intergenic D. melanogaster sequence was aligned

6. Computational Identification of Drosophila microRNA Genes Narrowing the Search 51.3 Mbases (Dm)  436,000 regions of ~100 bases each Each region was analyzed with the use of mfold for both the forward and reverse complement of each region 436,000 regions x 2 = 872,000 mfolds For the Dm regions scoring in the top 25%, the corresponding Dp regions were also analyzed with mfold

7. Computational Identification of Drosophila microRNA Genes Narrowing the Search (cont.) The scores from the mfold analysis of the corresponding Dm and Dp regions were averaged and ranked 21/24 members of the reference set were in the top 600 results from this scoring Next, they filtered out regions that did not meet the following criteria:  Perfectly conserved sequence >= 22 nt  Located < 10 nt from the terminal loop

8. Computational Identification of Drosophila microRNA Genes Narrowing the Search (cont.) Next, they evaluated some of the divergence patterns between the known pre-microRNAs in Dm and Dp.

9. Computational Identification of Drosophila microRNA Genes Narrowing the Search (cont.)

10. Computational Identification of Drosophila microRNA Genes Top Scoring Set 23/24 members of the Drosophila reference set fell into one of classes 1-3 Thus, candidates that did not fall into one of these classes were eliminated This filtered the set down to the top 208 scoring candidates 18/24 (75%) of the reference set were in the top 124 candidates

11. Computational Identification of Drosophila microRNA Genes Top Scoring Set (cont.) 42 novel candidates out of the top 208 candidates were found to be conserved in a third species (Anopheles, Apis, nematodes, or vertebrates)

12. Computational Identification of Drosophila microRNA Genes Overview

13. Computational Identification of Drosophila microRNA Genes Experimental Verification They attempted to validate the predicted miRNAs by northern blot analysis 38 candidates were tested  27 candidates were conserved outside of Drosophila  11 candidates were Drosophila specific Expression was observed for:  20/27 (74%)  4/11 (36%) 25 novel verified microRNA genes  20 + 4 != 25  25 th ?  expression was not obtained but this candidate was orthologous to miR-137

14. Computational Identification of Drosophila microRNA Genes The End