Genome-Wide RNAi Analysis of Growth and Viability in Drosophila Cells Michael Boutros,1*† Amy A. Kiger,1* Susan Armknecht,1,2 Kim Kerr,1,2 Marc Hild,3 Britta Koch,3 Stefan A. Haas,4 Heidelberg Fly Array Consortium,3 Renato Paro,3 Norbert Perrimon1,2‡ Presentation by: Alex Cunha and James Ao
Goals Ultimate goal: identify and characterize the function of every gene in an organism’s genome. Experimenter’s goal: identify and characterize the function of genes involved in hemocyte cell growth and viability in Drosophila melanogaster.
Background Information Drosophila melanogaster is one of the best-studied genetic organisms. Has a genome size of 170Mbp with 15,000-17,000 protein coding genes. 75% of known human disease genes have match in Drosophilagenome and 50% of protein sequences have mammalian homologs.
Background Information RNA interference (RNAi) is a method of post-transcriptional gene silencing through the destruction of mRNA. RNAi pathways are found in eukaryotic organisms as a defense mechanism against parasitic nucleotide sequences (viruses and transposons).
Background Information • dsRNA recognized by Dicer and cut into ~20bp fragment • RNA induced silencing complex (RISC) binds to target mRNA and degrades it
21,306 primer pairs amplified gene-specific fragments from gDNA using PCR. • T7-promoter sequences added to both ends of fragments and amplified again. • 19,470 dsRNA products generated in total. Generating dsRNA Library
Quantifying the Assay • Kc167 and S2R+ cell lines used for experiments. • Negative control: cells with no dsRNA treatment. • Positive control: cells treated with dsRNAtargettingD-IAP1, an inhibitor of apoptosis.
Analyzing essential gene function: chose cases where dsRNAsthat led to greatly reduced cell numbers • Based on Z-score of >3 • 438 cases, labeled in black in the graph • Z-score (AKA standard score) represents how many standard deviations a datum is away from the mean Choosing RNAi
Organized into predicted protein domains using InterPro • 20% of genes in these cases had associated mutant alleles • Roles in cell growth, cell cycle, anti-apoptotic cell survival • Majority of genes did not have known mutant alleles • RNAi with no prediction increased from the 438 cases (z-score >3) to the cases with severe phenotypes (z-score >5) Results
Significant changes from Graph B and Graph C in predicted protein domains for the RNAi phenotypes • No ribosome protein domains in Graph C compared to Graph B (13%) • Increased percentage of genes with phenotypes with no predicted domains from Graph B (41%) to Graph C (63%) Results
Identified two genes (CG11700 and CG15455) with similar phenotypes to D-IAP1, gene associated with apoptosis from loss-of function • 95% of cells treated with dsRNA to CG11700 or D-IAP1 were apoptotic • 20% of cells treated with dsRNA to CG15455 were apoptotic CG11700 and CG15455
Flow cytometry analysis of propidium stained DNA after 3 days exposure to RNAi • Decreased cell size and DNA content = apoptotic • GFP = normal, D-IAP1 = apoptotic Flow Cytometry
Treatment of RNAi to both CG11700 and CG15455 resulted in a decrease of the number of cells in the G1/S phase and an increase in the G2/M phase. • Concluded that the phenotypic severity could not be attributed to arrest in transition at one stage of the cell cycle Flow Cytometry
Rescued both CG11700 or D-IAP1 using RNAi inhibiting the proapoptoticcaspase, Nc, function but not CG15455 • Compared to z-VAD-fmk, a pan-caspase inhibitor • CG11700 may act on the same pathway as D-IAP1 to prevent Nccaspase-activated apoptotic cell death Rescue
Comparing complete proteomes: % of predicted orthologs found for genes with RNAi phenotypes was higher than the % of orthologs found in searches of the entire Drosophila proteome with other organisms • 50 genes had homology to human disease • 10 genes linked to blood-cell leukemia (AML1) • Other genes linked to anti-apoptotic functions (FOXOA1 and MLK) • In severe RNAi phenotypes: • Fewer yeast homologs identified (39% to 19.3%) • Similar proportion of animal-specific homologs (27.6% and 29.8%) • Increase number of genes without high-score matches (33.3% to 50.9%) • Suggests that specific mechanisms may have evolved in metazoans to maintain cell viability • Functional analysis in Drosophila identifies conserved regulators in animal cell survival Results
Genome-wide functional analysis by RNAi can reveal previously unknown and evolutionarily conserved gene functions • Able to determine quantitatively determine the contribution of potentially every gene to a particular process • Advantage of permitting the detection of gene functions associated with subtle or redundant phenotypes in organisms • Can gather and analyze many different cellular phenotypes to find complex gene functions • Can be adapted to screen many different cellular pathways for better understanding of cellular systems Conclusion