The identification and characterization of previously unidentified signal transduction molecules has expanded our understanding of biological systems and facilitated the development of mechanism-based therapeutics. We present a highly validated small interfering RNA (siRNA) screen that functionally annotates the human genome for modulation of the Wnt/beta-catenin signal transduction pathway. Merging these functional data with an extensive Wnt/beta-catenin protein interaction network produces an integrated physical and functional map of the pathway. The power of this approach is illustrated by the positioning of siRNA screen hits into discrete physical complexes of proteins. Similarly, this approach allows one to filter discoveries made through protein-protein interaction screens for functional contribution to the phenotype of interest. Using this methodology, we characterized AGGF1 as a nuclear chromatin-associated protein that participates in beta-catenin-mediated transcription in human colon cancer cells.

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Rare familial forms of Alzheimer's disease (AD) are thought to be caused by elevated proteolytic production of the 〈␤42 peptide from the ␤-amyloid-precursor protein (APP). Although the pathogenesis of the more common late-onset AD (LOAD) is not understood, BACE1, the protease that cleaves APP to generate the N terminus of A␤42, is more active in patients with LOAD, suggesting that increased amyloid production processing might also contribute to the sporadic disease. Using high-throughput siRNA screening technology, we assessed 15,200 genes for their role in 〈␤42 secretion and identified leucine-rich repeat transmembrane 3 (LRRTM3) as a neuronal gene that promotes APP processing by BACE1. siRNAs targeting LRRTM3 inhibit the secretion of A␤40, A␤42, and sAPP␤, the N-terminal APP fragment produced by BACE1 cleavage, from cultured cells and primary neurons by up to 60%, whereas overexpression increases A␤ secretion. LRRTM3 is expressed nearly exclusively in the nervous system, including regions affected during AD, such as the dentate gyrus. Furthermore, LRRTM3 maps to a region of chromosome 10 linked to both LOAD and elevated plasma A␤42, and is structurally similar to a family of neuronal receptors that includes the NOGO receptor, an inhibitor of neuronal regeneration and APP processing. Thus, LRRTM3 is a functional and positional candidate gene for AD, and, given its receptor-like structure and restricted expression, a potential therapeutic target.is the most common form of dementia and a debilitating neurodegenerative disease. In the majority of cases, the disease presents after age 65 because of largely unknown causes. However, in familial AD (FAD), the likely pathogenic trigger is release of amyloidogenic A␤ peptides from amyloid-precursor protein (APP), a transmembrane domain protein present in neuronal and other cells (1). A␤, the primary constituent of amyloid plaques, is generated from APP by proteolysis of the extracellular domain by BACE1 (Fig. 1A, 2), followed by intramembranous cleavage within its residual transmembrane domain by ␥-secretase [composed of presenilin-1 (PSEN1) or -2 (PSEN2) plus nicastrin (NCSTN), aph-1 (APH1), and pen-2 (PSENEN) (3)]. ␥-Secretase cleaves at multiple sites and yields mostly the 40-aa A␤40 peptide along with the more amyloidogenic 42-aa A␤42 (1). Alternatively, APP is cleaved by ␣-secretase within A␤, resulting in nonamyloidogenic metabolites. Mutations in APP or the presenilins account for most cases of FAD, and all increase A␤42 production from APP (1, 4, 5). These data are the basis of the amyloid hypothesis of AD.In late-onset (LO)AD, the etiology is not understood, but the major genetic risk factor is APOE4, which promotes A␤ deposition in the brains of mice (6), and BACE1 protein and activity are increased in LOAD (7-9). Furthermore, LOAD (10-12) and circulating A␤42 (13) levels were independently linked to chromosome 10q21-22, suggesting that genetic modifiers of LOAD risk also regulate A␤ metabolism. These data raise the possibility that genes regulating A␤ metabol...

The Wnt signaling pathways play pivotal roles in carcinogenesis. Modulation of the cell-surface abundance of Wnt receptors is emerging as an important mechanism for regulating sensitivity to Wnt ligands. Endocytosis and degradation of the Wnt receptors Frizzled (Fzd) and lipoprotein-related protein 6 (LRP6) are regulated by the E3 ubiquitin ligases zinc and ring finger 3 (ZNRF3) and ring finger protein 43 (RNF43), which are disrupted in cancer. In a genome-wide small interfering RNA screen, we identified the deubiquitylase ubiquitin-specific protease 6 (USP6) as a potent activator of Wnt signaling. USP6 enhances Wnt signaling by deubiquitylating Fzds, thereby increasing their cell-surface abundance. Chromosomal translocations in nodular fasciitis result in USP6 overexpression, leading to transcriptional activation of the Wnt/β-catenin pathway. Inhibition of Wnt signaling using Dickkopf-1 (DKK1) or a Porcupine (PORCN) inhibitor significantly decreased the growth of USP6-driven xenograft tumors, indicating that Wnt signaling is a key target of USP6 during tumorigenesis. Our study defines an additional route to ectopic Wnt pathway activation in human disease, and identifies a potential approach to modulate Wnt signaling for therapeutic benefit.

We introduce a method for analyzing small interfering RNA (siRNA) genetic screens based entirely on off-target effects. Using a screen for members of the Wnt pathway, we demonstrate that this method identifies known pathway components, some of which are not present in the screening library. This technique can be applied to siRNA screen results retroactively to confirm positives and identify genes missed using conventional methods for on-target gene selection.

Genome-scale small interfering RNA (siRNA) screens have become an increasingly popular approach to new target identification and pathway elucidation. However, the large data sets generated from siRNA screens have demonstrated high false-positive rates and the requirement for extensive experimental triage to distinguish true hits. A number of groups have independently reported the presence of siRNAs with identical seed sequences among their top screening hits. Based on these observations, we have developed a comprehensive technique for detecting and visualizing seed-based off-target effects in siRNA screening data. This is accomplished by analyzing the behavior of siRNAs that share identical seed sequences, which we refer to as common seed analysis (CSA). By applying these techniques to primary screening data of the Wnt pathway, we identify 158 distinct seed sequences that have a statistically significant effect on the assay. The promiscuous seed sequences identified in this manner can then be discounted in the analysis of follow-up experiments using single siRNAs. The ability to detect off-target effects when sufficient numbers of siRNAs share a common seed has significant implications for the design of siRNA screening experiments, data analysis, hit selection, and library design.

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