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Related to shRNA algorithm and short hairpin design
A computational algorithm to predict shRNA potency. Volume 56, Issue 6, 18 December 2014, Pages 796–807. Knott et al., 2014. Simon R.V. Knott, Ashley R. Maceli, Nicolas Erard, Kenneth Chang, Krista Marran, Xin Zhou, Assaf Gordon, Osama El Demerdash, Elvin Wagenblast, Sun Kim, Christof Fellmann, and Gregory J. Hannon.
Additional Links:
http://www.cell.com/molecular-cell/fulltext/S1097-2765(14)00835-1
Summary: The key sequence characteristics for predicting shRNA potency are identified by the Sherwood algorithm. This algorithm’s prediction of shRNA and an improved miR30 backbone increases shRNA processing and potency.
Functional identification of optimized RNAi triggers using a massively parallel sensor assay. Mol Cell. 18; 41(6):733-46. Fellmann, C. et al., (2011). Lessons from Nature: microRNA-based shRNA libraries. Kenneth Chang, Stephen J Elledge & Gregory J Hannon.
Additional Links:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3130540/
Summary: Uses an unbiased system in an agnostic (chicken, non-mammalian) cell line, to test the shRNA potency against its own target sequence; and is measured against the reduction in the associated green fluorescent protein.
Sensor and Sensitivity: A Screen for Elite shRNAs. Molecular Therapy 19, 5, 823-825. Castanotto, D (2011). Jason Moffat,1,2,4,10 Dorre A. Grueneberg, Xiaoping Yang, So Young Kim, Angela M. Kloepfer, Gregory Hinkle, Bruno Piqani, Thomas M. Eisenhaure, Biao Luo, Jennifer K. Grenier, Anne E. Carpenter, Shi Yin Foo, Sheila A. Stewart, Brent R. Stockwell, Nir Hacohen, William C. Hahn, Eric S. Lander, David M. Sabatini, and David E. Root
Additional Links:
http://www.sciencedirect.com/science/article/pii/S1525001616318780
Summary: Multiplexed knock-down via shRNA, shows less combinatorial competition than multiple siRNA alone, when used as a multiplexed combination.
A Lentiviral RNAi Library for Human and Mouse Genes Applied to an Arrayed Viral High-Content Screen. Cell, 124(6): 1283-1298. Moffat, J. et al, (2006).
Additional Links:
http://www.cell.com/cell/fulltext/S0092-8674(06)00238-8
Summary: Describes the use of pooled screening as opposed to arrayed screening.
Defining the optimal parameters for hairpin-based knockdown constructs. RNA 13(10), 1765–1774. Li, L., et al., (2007).
Summary: The use of highly potent silencing constructs can maximize the possibility of obtaining target knockdown and thereby is intrinsically important for the chance of success. shRNA usage is integral to successful knock-down experiments.
Second-generation shRNA libraries covering the mouse and human genomes. Nature Genetics 37, 1281 - 1288 (2005). Jose M Silva, Mamie Z Li, Ken Chang, Wei Ge, Michael C Golding, Richard J Rickles, Despina Siolas, Guang Hu, Patrick J Paddison, Michael R Schlabach, Nihar Sheth, Jeff Bradshaw, Julia Burchard, Amit Kulkarni, Guy Cavet, Ravi Sachidanandam, W Richard McCombie, Michele A Cleary, Stephen J Elledge & Gregory J Hannon.
Summary: Second-generation shRNA libraries covering the mouse and human genomes, this is the 1st iteration of shERWOOD.
Related to microRNA (miR30) scaffold / UltramiR
Artificial miRNAs mitigate shRNA-mediated toxicity in the brain: Implications for the therapeutic development of RNAi. PNAS 105; 15, 5868-5873. McBride, J. L. et al., (2008).
Jodi L. McBride, Ryan L. Boudreau, Scott Q. Harper, Patrick D. Stabe , Alex Mas Monteys , Inâs Martins, Brian L. Gilmore, Haim Burstein, Richard W. Peluso, Barry Polisky, Barrie J. Carter, and Beverly L. Davidson.
Summary: miRNA-based (backbone) approaches may provide more appropriate biological tools for expressing inhibitory RNAs.
Beyond Secondary Structure: Primary-Sequence Determinants License Pri-miRNA Hairpins for Processing. Cell 152(4):844-858.Auyeung, V.C., I. Ulitsky, S.E. McGeary, and D.P. Bartel. (2013).
Additional Links:
https://www.ncbi.nlm.nih.gov/pubmed/23415231
Summary: Confirms the importance of primary-sequence determinants such as a miR30 backbone to mimic the “natural” hairpin and improve the cell’s processing of the shRNA all the way from the nucleus to the cytoplasm, thus increasing specificity, processing and potency.
Related to In vivo / Ex vivo screening
In Vivo RNA Interference Screens Identify Regulators of Antiviral CD4+ and CD8+ T Cell Differentiation. Volume 41, Issue 2, p325–338, 21 August 2014. Runqiang Chen, Simon Bélanger, Megan A. Frederick, Bin Li, Robert J. Johnston, Nengming Xiao, Yun-Cai Liu, Sonia Sharma, Bjoern Peters, Anjana Rao, Shane Crotty, Matthew E. Pipkin
Summary: Describes the use of ex vivo transduction of tissue culture cells, and then placed into a mouse model by in vivo introduction of these cells into the mouse.
Related to shRNA off target effects
Off-target effect of doublecortin family shRNA on neuronal migration associated with endogenous microRNA dysregulation. Neuron 18; 82, 1255–1262. Baek, S.T. et al. (2014).
Summary: Demonstration of shRNA-mediated off-target toxicity, without a miR based backbone
Related to the comparison of shRNA and CRISPR multiplex pooled library screening
Systematic comparison of CRISPR-Cas9 and RNAi screens for essential genes. Nature Biotechnology 34, 634–636 (2016). David W Morgens, Richard M Deans, Amy Li, and Michael Bassik.
Additional Links:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4900911/
Summary: A comparison of the ability of short hairpin RNA (shRNA) and CRISPR/Cas9 screens to identify essential genes.in the human chronic myelogenous leukemia cell line K562. It was found that the precision of the two libraries in detecting essential genes was similar and that combining data from both screens improved performance. Notably, results from the two screens showed little correlation when dealing with essential genes. shRNA screening picked up hits that CRISPR/Cas9 didn’t. Thus combining the results from the two methods could reveal information that neither could on its own.
Relatd to shRNA multiplex pooled library screening
In Vivo RNA Interference Screens Identify Regulators of Antiviral CD4+ and CD8+ T Cell Differentiation. Volume 41, Issue 2, p325–338, 21 August 2014. Runqiang Chen, Simon Bélanger, Megan A. Frederick, Bin Li, Robert J. Johnston, Nengming Xiao, Yun-Cai Liu, Sonia Sharma, Bjoern Peters, Anjana Rao, Shane Crotty, Matthew E. Pipkin
Summary: Describes the use of ex vivo transduction of tissue culture cells, and then placed into a mouse model by in vivo introduction of these cells into the mouse.
A Lentiviral RNAi Library for Human and Mouse Genes Applied to an Arrayed Viral High-Content Screen. Cell, 124(6): 1283-1298. Moffat, J. et al, (2006).
Summary: Describes the use of pooled screening as opposed to arrayed screening.
Relatd to shERWOOD-UltramiR shRNA used in research
BCL6 orchestrates Tfh cell differentiation via multiple distinct mechanisms. Hatzi, K., Nance, J. P., Kroenke, M. A., Bothwell, M., Haddad, E. K., Melnick, A., & Crotty, S. (2015). The Journal of Experimental Medicine, 212(4), 539–553.
Additional Links:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4387288/
Summary:
transOMIC shRNAs are designed using the shERWOOD algorithm, having a proven increasing knockdown potency and specificity at low concentration. cJun shRNAs were cloned into our pLMPd vector as described previously (Chen et al., 2014). Knockdown efficiency was assessed by Western blot. shRNA selected for cJun was transOMIC #RLGM-GU36521 with guide sequence 5′-AGAAACGACCTTCTACGACGAA-3′.
IGF-1 mediated Neurogenesis Involves a Novel RIT1/Akt/Sox2 Cascade. Mir, S., Cai, W., Carlson, S. W., Saatman, K. E., & Andres, D. A. (2017). Scientific Reports, 7, 3283.
Summary:
Lentiviral vector pZIP-mCMV containing the RIT1 was purchased from transOMIC Technologies (Huntsville, AL). Lentivirus was generated in 293LTV cells using the packaging vectors PsPAX2 and pMD2.G. The efficiency of shRNA silencing in HNPCs was determined to be >70% using RT-PCR and confocal microscopy. Both NTC and shRIT1-RNA were used at an MOI=3. These authors go onto explain rather extensive protocol for infection and assay.
Upregulation of Glucose-Regulated Protein 78 in Metastatic Cancer Cells Is Necessary for Lung Metastasis Progression. Lizardo, M. M., Morrow, J. J., Miller, T. E., Hong, E. S., Ren, L., Mendoza, A., … Khanna, C. (2016). Neoplasia (New York, N.Y.), 18(11), 699–710.
Additional Links:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5094383/
Summary:
Two different shRNAs against GRP78 were selected from the transOMIC technologies shERWOOD-UltramiR shRNA library. Cloning of shRNA into backbone construct was performed on contract by transOMIC Technologies into the TET-ON (doxycycline) inducible vector LT3REPIR.
Indirect ex vivo/in vivo work transformed cells and seeded them into mouse lungs.
A ROR1-HER3-LncRNA signaling axis modulates the Hippo-YAP pathway to regulate bone metastasis. Li, C., Wang, S., Xing, Z., Lin, A., Liang, K., Song, J., … Yang, L. (2017).
Nature Cell Biology, 19(2), 106–119.

Summary
: transOMIC technologies shERWOOD UltramiR shRNAs targeting MAYA (LncRNA) in pZIP-TRE3GS lentiviral vectors were used for in vitro, and ex-vivo (in vivo) to perform inducible knockdown of MAYA in xenograft experiments. NOTE: There is a 2bp sequence error in MAYA shRNA#2 in this publication versus what we synthesized for them.
Relatd to shERWOOD-UltramiR inducible shRNA used in research
Upregulation of Glucose-Regulated Protein 78 in Metastatic Cancer Cells Is Necessary for Lung Metastasis Progression. Lizardo, M. M., Morrow, J. J., Miller, T. E., Hong, E. S., Ren, L., Mendoza, A., … Khanna, C. (2016). Neoplasia (New York, N.Y.), 18(11), 699–710.
Additional Links:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5094383/
Summary:
Two different shRNAs against GRP78 were selected from the transOMIC technologies shERWOOD-UltramiR shRNA library. Cloning of shRNA into backbone construct was performed on contract by transOMIC Technologies into the TET-ON (doxycycline) inducible vector LT3REPIR.
Indirect ex vivo/in vivo work transformed cells and seeded them into mouse lungs.
A ROR1-HER3-LncRNA signaling axis modulates the Hippo-YAP pathway to regulate bone metastasis. Li, C., Wang, S., Xing, Z., Lin, A., Liang, K., Song, J., … Yang, L. (2017).
Nature Cell Biology, 19(2), 106–119.

Summary
: transOMIC technologies shERWOOD UltramiR shRNAs targeting MAYA (LncRNA) in pZIP-TRE3GS lentiviral vectors were used for in vitro, and ex-vivo (in vivo) to perform inducible knockdown of MAYA in xenograft experiments. NOTE: There is a 2bp sequence error in MAYA shRNA#2 in this publication versus what we synthesized for them.
Relatd to shERWOOD-UltramiR shRNA used in ex vivo / in vivo
A ROR1-HER3-LncRNA signaling axis modulates the Hippo-YAP pathway to regulate bone metastasis. Li, C., Wang, S., Xing, Z., Lin, A., Liang, K., Song, J., … Yang, L. (2017).
Nature Cell Biology, 19(2), 106–119.

Summary
: transOMIC technologies shERWOOD UltramiR shRNAs targeting MAYA (LncRNA) in pZIP-TRE3GS lentiviral vectors were used for in vitro, and ex-vivo (in vivo) to perform inducible knockdown of MAYA in xenograft experiments. NOTE: There is a 2bp sequence error in MAYA shRNA#2 in this publication versus what we synthesized for them.
Related to shRNA viral packaging – the use of Pasha siRNA
Packaging shRNA Retroviruses (protocol).  Kenneth Chang, Krista Marran, Amy Valentine, and Gregory J. Hannon
Summary: Viruses carrying shRNAs are packaged almost identically to viruses carrying protein-encoding genes, however, the shRNAs are efficiently cleaved by the packaging cells RNAi machinery, which can reduce the level of viral genomic RNA and consequently viral titers. Co-transfecting the viral plasmid with DGCR- 8/Pasha siRNA that targets Pasha itself can enhance titers. siRNAs against Drosha can also be used.
Related to using shRNAs in a single transfection or transduction
USP26 regulates TGF‐β signaling by deubiquitinating and stabilizing SMAD7 – Uses transOMIC shRNA.  EMBO Reports, 18(5), 797–808. Kit Leng Lui, S., Iyengar, P. V., Jaynes, P., Isa, Z. F. B. A., Pang, B., Tan, T. Z., and Eichhorn, P. J. A. (2017).
Summary: transOMIC shRNA against the deubiquitinating enzyme USP26 were used to knock-down the protein. The researchers were thus able to regulate downstream components in the TGF‐β pathway.
Additional Links:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5412796/