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From screen to gene: how you can get more out of your RNAi screen

RNAi screen using IN Cell Analyzer 6000 identifies key gene in genetic risk for Alzheimer’s disease

RNAi screen using IN Cell Analyzer 6000 identifies key gene in genetic risk for Alzheimer’s disease


Many people know at least one person with Alzheimer’s disease or dementia. Today, 46 million people around the world live with dementia and it is estimated that in the next 33 years, there will be over 130 million dementia patients. Dementia is the group of symptoms the patient experiences (such as memory loss, difficulty thinking, or speaking) while Alzheimer’s is the progressive neurodegenerative disorder where brain cells degenerate and die. Alzheimer’s is the leading cause of dementia, and scientists are actively working to understand how the hallmark clusters of protein called amyloid plaques are associated with cellular death in brain tissue.

Given the high prevalence of Alzheimer’s and dementia worldwide, scientists in academia and industry alike are continually searching for new drug targets and treatments. Recently, a paper was published from the Institut Pasteur de Lille where they used a clever strategy which involved performing an siRNA screen on an IN Cell Analyzer 6000 and cross referencing their top hits to the results of a previous genome-wide association study (GWAS). Doing so led to the identification of a single gene that when knocked down was associated with an increase in the levels of a peptide that leads to the hallmark amyloid plaques of Alzheimer’s.

Rab4 and APP localization in a FERMT2 knock down

Title: Genome-wide, high-content siRNA screening identifies the Alzheimer's genetic risk factor FERMT2 as a major modulator of APP metabolism
Authors: J. Chapuis, A. Flaig, B. Grenier-Boley, F. Eysert, V. Pottiez, G. Deloison, A. Vandeputte, A. Aryal, T. Mendes, S. Desai, A. Goate, J. Kauwe, F. Leroux, A. Herledan, F. Demiautte, C. Bauer, F. Checler, R. Petersen, K. Blennow, H. Zetterberg, L. Minthon, V. M. Van Deerlin, V. Man-Yee Lee, L. Shaw, J. Trojanowski, M. Albert, A. Moghekar, R. O’Brien, E. Peskind, N. Malmanche, G. Schellenberg, P. Dourlen, O. Song, C. Cruchaga, P. Amouyel, B. Deprez, P. Brodin, J. Lambert
Modification: Cropped
License: CC BY 4.0

A deeper dive into the screen

Chapuis and colleagues noted that the GWAS found 19 different regions of the genome associated with Alzheimer’s (2). The problem is that these 19 regions contain 123 genes and it just isn’t practical or efficient to go hunting one by one to find the genes with the strongest link to Alzheimer’s. So they performed an siRNA screen examining changes in fluorescence intensity of a reporter protein called Amyloid Precursor Protein (APP). This screen utilized a Dharmacon siGENOME SMARTpool siRNA library that targets all 18, 107 genes of the human genome. For maximum efficiency, the screen used 384 well plates and acquired a single image per well in 3 colors with a 20x objective on an IN Cell Analyzer 6000 high content analysis instrument. From their high content screen they had 8 hits in the top 5% of the screen that matched the 123 GWAS gene candidates. Only 2 of the 8 had the particular cellular phenotype they were interested in (increased secretion of amyloid Aß peptides), and only 1 of the 2 also had the patient phenotype they were interested in (changes in Aß level of cerebrospinal fluid in Alzheimer’s patients).

That one remaining gene was FERMT2, a ß3-integrin coactivator. When FERMT2 is knocked down by siRNA, cells increase Aß peptide production by increasing the amount of APP at the cell surface. The researchers went on to further characterize FERMT2 to understand it’s role in Alzheimer’s pathology.

Future studies may be aimed towards:

  • Better understanding the pathophysiology associated with altered levels of FERMT2
  • Modifying Alzheimer’s disease risk in patients by altering APP metabolism and/or Aß peptide production through FERMT2
  • Developing a therapy by altering APP metabolism and/or Aß peptide production through FERMT2

What can we take away from this study?

  1. The strategy to utilize previously published GWAS data in analysis of an siRNA screen successfully lead to the identification of a gene associated with Alzheimer’s genetic risk.
  2. There’s a lot of GWAS data out there, so perhaps this strategy could work for you, too! Perhaps you already have the siRNA screen done and can start the exciting part of cross referencing? Or perhaps you have a CRISPR screen in the works?
  3. High content analysis screening is an effective method to study an entire genome and quickly find actionable hits.
  4. This is a great example of out-of-the box thinking to answer a scientific question with available tools.
  5. Screening an arrayed Dharmacon siRNA library for genomic analysis with an IN Cell Analyzer is a winning combination!


  1. Chapuis, J. et al. Genome-wide, high content siRNA screening identifies the Alzheimer’s genetic risk factor FERMT2 as a major modulator of APP metabolism. Acta Neuropathol (2016) doi:10.1007/s00401-016-1652-z.
  2. Lambert, J-CC, et al. Meta-analysis of 74, 046 individuals identifies 11 new susceptibility loci for Alzheimer’s Disease. Nat Genet 45:1452-1458 (2013), doi:10.1038/ng.2802.

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