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da Silva Pescador, G.

Publications and source records attributed to da Silva Pescador, G..

2 recordsLinked to original sources

Enhanced RNA-targeting CRISPR-Cas technology in zebrafish

CRISPR-Cas13 systems are widely used in basic and applied sciences. However, its application has recently generated controversy due to collateral activity in mammalian cells and mouse models. Moreover, its efficiency could be improved in vivo. Here, we optimized transient formulations as ribonucleoprotein complexes or mRNA-gRNA combinations to enhance the CRISPR-RfxCas13d system in zebrafish. We i) used chemically modified gRNAs to allow more penetrant loss-of-function phenotypes, ii) improved nuclear RNA-targeting, and iii) compared different computational models and determined the most accurate to predict gRNA activity in vivo. Furthermore, we demonstrated that transient CRISPR-RfxCas13d can effectively deplete endogenous mRNAs in zebrafish embryos without inducing collateral effects, except when targeting extremely abundant and ectopic RNAs. Finally, we implemented alternative RNA-targeting CRISPR-Cas systems with reduced or absent collateral activity. Altogether, these findings contribute to CRISPR-Cas technology optimization for RNA targeting in zebrafish through transient approaches and assist in the progression of in vivo applications.

developmental biology↗

iCodon: ideal codon design for customized gene expression

Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability, in turn, is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon (www.iCodon.org), an algorithm for customizing mRNA expression through the introduction of synonymous codon substitutions into the coding sequence. iCodon is optimized for four vertebrate transcriptomes: mouse, human, frog, and fish. Users can predict the mRNA stability of any coding sequence based on its codon composition and subsequently generate more stable (optimized) or unstable (deoptimized) variants encoding for the same protein. Further, we show that codon optimality predictions correlate with expression levels using fluorescent reporters and endogenous genes in human cells and zebrafish embryos. Therefore, iCodon will benefit basic biological research, as well as a wide range of applications for biotechnology and biomedicine.

molecular biology↗