Vetting & Analysis of RNA for In Situ Hybridization (VARNISH) for RNA probe design

VARNISH is an online software tool for designing probes used for super resolution imaging of RNAs with Points Accumulation for Imaging in Nanoscale Topography (RNA-PAINT). The current version focuses on probes for RNA-PAINT using small RNAs (sRNAs). These probes are composed of an LNA-locked reverse complementary sequence targeting the sRNA of interest (~20 nt), a docking stranding for later binding of the imager strand (~10 nt), and a linker sequence that connects these two components (~7 nt). Using the sRNA-PAINT technique, we can localize sRNA targets with sub-10 nm resolution, and quantify the exact copy number of binding sites using the qPAINT software Picasso. The VARNISH tool utilizes the Analyze, SelfDimer, and UNAFoldRun functions from the web API of IDT, and it outputs the top 10 candidates. VARNISH also provides ordering information for the designed probes and corresponding imager strands.

Analyze, Self Dimer and UnaFold Operations from are used to calculate TM and Delta G values.
Stability and Mismatch Discrimination of Locked Nucleic Acid–DNA Duplexes and Sequence-Dependent Thermodynamic Parameters for Locked Nucleic Acid (LNA)−DNA Duplex Formation are used as references.

Paste your small RNA sequence (max 24 nt): 

Enter the parameters: 
(*concentration in the experimental hybridization buffer)

Either select or enter custom docking strand: 
You can choose multiple docking strands by using ctrl button when clicking or enter a custom docking strand. If All of Above is chosen, the system will pick the best docking strand.

Enter linker: 

Select LNA base number: 

Enter your e-mail address and subject: 

Varnish Creators
Feray Demirci Technical Specialist Application Development
Kun Huang Post-doctoral Scientist RNA Imaging & Microscopy
Blake Meyers Principal Investigator Small RNAs
Jeff Caplan Principal Investigator Imaging & Microscopy


Kun Huang, Feray Demirci, Mona Batish, Wayne Treible, Blake C Meyers, Jeffrey L Caplan, Quantitative, super-resolution localization of small RNAs with sRNA-PAINT, Nucleic Acids Research, Volume 48, Issue 16, 18 September 2020, Page e96,

The grant awards that funded the development of this application include support from the National Science Foundation, Plant Genome Research Program, awards #1822293 and #1754097 to JLC and BCM.