GenE-HumDi Tutorials
Section outline
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This page contains a few tutorials based on the project GenE-HumDi (GenE-HumDi Site).
These tutorials are:
- GE-ON CRISPR Tools. A suite of free, web-based genome engineering tools.
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Welcome to crisprtools.org!
Welcome to your complete guide to mastering our suite of free, web-based genome engineering tools. Browse the tutorials below to learn how to:
- CHOPCHOP: Design highly efficient guide RNAs.
- CHOPOFF: Screen guides for dangerous off-targets and DNA bulges.
- SNIPSNP: Automate the design of complex HDR templates.
- Dual Cas13a: Build high-precision assays for RNA detection.
- OVERHANG: Connect with other researchers in our dedicated forum.
Read the quick summaries or dive into the full video tutorials below to get started!
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Designing a CRISPR gRNA library can become challenging when working with a large number of genes or with novel Cas proteins that recognize non-standard PAM sequences.
The Custom Cas gRNA Library Designer is a web-based pipeline that simplifies this process by supporting both whole-genome and pathway-specific gRNA library design. It also allows users to work with both already validated Cas proteins and novel or custom Cas variants with user-defined PAMs.
You can access the pipeline for free here:
Custom Cas gRNA Library Designer
1. Whole-Genome gRNA Library
If you want to design a gRNA library targeting genes across the genome, select the Whole Genome option.
You can then choose between:
- Already Validated Cas — for Cas proteins with predefined targeting and PAM requirements.
- Custom Cas — for novel or engineered Cas variants where you can define the relevant PAM and guide-design parameters.
This makes the pipeline useful for designing genome-wide libraries not only for established nucleases, but also for new Cas variants with novel PAM preferences.
The workflow is:
Whole Genome → Select Cas → Define PAM/parameters → Identify target sites → Generate gRNA library
2. Pathway-Specific gRNA Library
If you are interested in a particular biological process rather than the entire genome, select Pathway Specific.
The pipeline can retrieve genes associated with the selected pathway and subsequently identify compatible gRNA target sites.
For example, you could generate a focused library targeting genes involved in DNA repair, immune signaling, metabolism, or other biological pathways.
As with the whole-genome workflow, you can use either an already validated Cas or a custom Cas with a novel PAM.
The workflow is:
Pathway → Gene set → Select Cas → Identify target sites → Generate gRNA library
3. Which Option Should You Choose?
The pipeline essentially gives you four possible workflows:
Goal
Library
Cas option
Genome-wide screen
Whole Genome
Validated Cas
Genome-wide screen with a novel nuclease
Whole Genome
Custom Cas
Focused biological screen
Pathway Specific
Validated Cas
Focused screen with a novel nuclease
Pathway Specific
Custom Cas
This flexibility allows the same platform to be used for both routine CRISPR library design and emerging Cas-nuclease development.
Conclusion
The Custom Cas gRNA Library Designer provides a simple workflow for going from your genome or biological pathway and Cas nuclease to a candidate gRNA library.
Whether you are using an established Cas protein or developing a novel Cas variant with a new PAM, the pipeline can help streamline the guide-design process.
🎥 Want to see how the pipeline works in practice?
I have also prepared a step-by-step video tutorial showing how to use the different options and generate your gRNA library. Check out the video tutorial for a complete walkthrough of the pipeline.
Open the Custom Cas gRNA Library Designer
This pipeline was developed as part of work supported by COST Action CA21113 (GeneHumDi).
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LNPSpace: An AI-Assisted Literature Platform for Lipid Nanoparticle Research
Efficient delivery remains one of the major challenges in the development of nucleic-acid-based therapies, including mRNA therapeutics, gene therapy, and genome editing. Lipid nanoparticles (LNPs) have emerged as one of the most important delivery platforms in this field, but the rapid expansion of LNP research has also created a fragmented and increasingly difficult-to-navigate literature landscape.
LNPSpace was developed as a pilot-scale, AI-assisted literature platform designed to support the retrieval and exploration of scientific information related to LNP formulations and nucleic acid delivery.
The platform combines scientific literature retrieval with a Retrieval-Augmented Generation (RAG) workflow. Relevant open-access publications are identified, processed at the section level, and searched for evidence directly related to a user's question. Retrieved information is then used to generate concise, literature-grounded responses linked back to the supporting publications.
A central feature of LNPSpace is the structured retrieval of LNP formulation information. Users can explore reported lipid compositions, nucleic acid cargoes, particle characteristics, formulation parameters, and experimental applications where these data are available. Information from multiple studies can also be organized into comparative formulation tables, helping researchers evaluate reported LNP systems without manually extracting data from individual publications.
LNPSpace additionally includes a Talk-to-PDF function. Once a relevant publication has been identified, users can select that article and perform publication-specific queries to examine experimental methods, formulation details, results, or other information directly within the paper.
For the GenE-Humdi community, such literature tools may be particularly useful at the interface between genome editing and delivery technology. As increasingly sophisticated genome- and epigenome-editing systems are developed, identifying appropriate delivery strategies remains essential for translating these technologies toward therapeutic applications. AI-assisted literature retrieval can help researchers more rapidly connect emerging editing approaches with relevant delivery systems and formulation knowledge reported across the field.
LNPSpace is currently a pilot-scale platform with coverage focused on a limited recent literature window. Future development will expand the searchable literature corpus, improve automated extraction and standardization of formulation-level information, strengthen benchmarking and evidence evaluation, and extend the platform toward additional areas of nucleic acid delivery and nanomedicine.
The project was developed with support from an e-COST Virtual Mobility Grant within GenE-Humdi, providing an opportunity to explore how AI-assisted knowledge retrieval can complement conventional literature searching and support research at the intersection of genome editing, nucleic acid delivery, and computational technologies.
Explore LNPSpace: LNPSpace — Literature Review Platform
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