siRNA Data Collection and Analysis

1. siRNA Data Collection and Analysis Blake Adams CS 6985 12/08/2004

2. What is RNA silencing? Data Collection Data Extraction Articles of Interest siRNA scoring technique siRNA scoring program Some results Conclusion Overview

3. How RNA Interference (RNAi Silencing) Works • Inhibiting the expression of individual genes by interfering with a mRNA being transcribed. • This is done vai a small double-stranded RNA.   An enzyme named DICER snips short interfering RNAs (siRNA) from longer doublestranded RNAs made by (A) self-copying gene sequences,  (B) by replicating viruses, or (C) regulatory RNA sequences known asmicroRNAs.   All the RNAs (A, B, & C) are cleaved by DICER enzyme into short siRNA pieces that can suppress gene expression. 

4. Data Collection/Extraction • EBSCO Host • MEDLINE Database • Search criteria: siRNA • Satisfactory articles were read and scanned for siRNA used during the research.

5. Binding of mouse VL30 retrotransposon RNA to PSFprotein induces genes repressed by PSF: Effectson steroidogenesis and oncogenesis • Retrotransposon - A transposon copied from RNA with the use of reverse transcript. • Steroidogenesis - Production of steroids by living organisms. • Oncogenesis - The progression of cytological, genetic, and cellular changes that culminate in a malignant tumor. • Hypothisis: Steroidogenesis is damaged or surpressed in mammals with cancer. Evidence suggests VL30 RNA and PSF protein control the process of steroidogenesis. • What happened? Introduction of siRNA activated steroid synthesis in the mice with adrenal gland tumors. • What does this mean? This solidifies the evidence that VL30 RNA and PSF regulates steroidogenesis, further evidence suggests that the same is true of humans. If true, we may be reaching a better understanding of the process of steroidogenesis at a genetic level.

6. Transfection of “naked” siRNA results in endosomal uptake and metabolic impairment in cultured neurons • Transfection - Infection of a cell with purified viral nucleic acid, resulting in subsequent replication of the virus in the cell. • “naked” siRNA – introduction of siRNA to a system without the assistance of any sort of delivery or calalyst mechanism. • Hypothesis: siRNA delivery to primary neuron cultures is possible without the use of cationic lipids or other transfection agents. • What happened? While the siRNA worked its way into the cells, it showed little to no presence within the nucleus of the cells. siRNA presence in the cell suggests silencing should have occurred within the cells but none was observed.

7. Functional inhibition of the p75 receptor using a small interfering RNA • P75 – mediates a wide variety of biological effects. Contributes to the inhibition of neuron regeneration and the death of neurons • Hypothisis – knocking down the expression of p75NTR is possible with siRNA, doing so may have useful applications a therapeutic agent. • What happened? Knocked down the expression of p75NTR, however the effects on test subject varied depending on the subject.

8. An algorithm for design of functional siRNA • An algorithm for selection of functional siRNA sequences. - Mohammed Amarzguioui • Manual - An algorithm for design of functional siRNA - Mohammed Amarzguioui • Selection rules based entirely on consideration of the sequence of the siRNA • MAJOR FACTORS: • Duplex GC content within the range of 31.6 – 57.9 • A/U differential of the three terminal base-pairs at either end of the duplex exhibiting a higher A/U content at the 3’ end, lower at the 5’ end. (relative to the sense strand) • Minor Positive Determinants: • G or C at the 1 position • A or U at the last position • A at the 6 position • Minor Negative Determinants • U at the 1 position • G at the end position

9. Programmatic Implementation • Perl • Takes sense and antisense as entry from user • Duplex G/C content between 31.6 – 57.9 +2 • A/U Differential in first 3 and last 3 of DUPLEX favors 3’ end of SENSE +2 • G or C at the 1 position of sense +1 • G or C at the 1 position of antisense +1 • A or U at the end position of sense +1 • A or U at the end position of antisense +1 • A at the 6 position of sense +1 • A at the 6 position of antisense +1 • U at the 1 position of sense -1 • U at the 1 position of antisense -1 • G at the end position of sense -1 • G at the end position of antisense -1

10. Some Results • mVL30 • Sense: GACGCCAGGAACAAUUAAG • Antisense:CUUAAUUCUUCCUGGCGUC • GC Content = 0.47 +2 • A/U Differential = 0 (5’ A&UU, 3’ AA&U) +0 • G at 1 pos (sense) +1 • C at 1 pos (antisense) +1 • G at end pos (sense) -1 • FINAL SCORE: 3

11. EGFP Sense: GACGUAAACGGCCACAAGUUC Antisense: CGCUGCAUUUGCCGGUGUUCA GC Content = 0.54 +2 A/U Differential = 3 (5’ A, 3’ UU&U_A) +2 G at 1 pos (sense) +1 C at 1 pos (antisense) +1 A at 6 pos (sense) +1 A at end pos (antisense) +1 FINAL SCORE: 8 Cdc42 Sense: GUAGUCUGUCAUAAUCCUCUU Antisense: GAGGAUUAUGACAGACUACUU GC Content = 0.38 +2 A/U Differential = 1 (5’ UA&A, 3’ UU&UU) +2 G at 1 pos (sense) +1 G at 1 pos (antisense) +1 U at end pos (sense) +1 U at end pos (antisen) +1 FINAL SCORE: 8 Some Results

12. Some Results • p75NTR • Sense: GGAGACAUGUUCCACAGGCAU • Antisense:CCUCUGUACAAGGUGUCCGUA • GC Content = 0.52 +2 • A/U Differential = 2 (5’ A&U, 3’ AU&UA) +2 • G at 1 pos (sense) +1 • C at 1 pos (antisense) +1 • U at end pos (sense) +1 • A at end pos (antisense) +1 • FINAL SCORE: 8