TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction

Abstract

Transcription activator-like (TAL) effectors are repeat-containing proteins used by plant pathogenic bacteria to manipulate host gene expression. Repeats are polymorphic and individually specify single nucleotides in the DNA target, with some degeneracy. A TAL effector-nucleotide binding code that links repeat type to specified nucleotide enables prediction of genomic binding sites for TAL effectors and customization of TAL effectors for use in DNA targeting, in particular as custom transcription factors for engineered gene regulation and as site-specific nucleases for genome editing. We have developed a suite of web-based tools called TAL Effector-Nucleotide Targeter 2.0 (TALE-NT 2.0; https://boglab.plp.iastate.edu/) that enables design of custom TAL effector repeat arrays for desired targets and prediction of TAL effector binding sites, ranked by likelihood, in a genome, promoterome or other sequence of interest. Search parameters can be set by the user to work with any TAL effector or TAL effector nuclease architecture. Applications range from designing highly specific DNA targeting tools and identifying potential off-target sites to predicting effector targets important in plant disease.

Efficient genome engineering by targeted homologous recombination in mouse embryos using transcription activator-like effector nucleases

“…TALENs targeting the murine Satb1 locus were designed using the TAL Effector Nucleotide Targeter 36 and assembled with the TALE toolbox following the published recommendations 37 . The plasmids for TALEN assembly were obtained from Addgene.…”

TALE-induced bHLH transcription factors that activate a pectate lyase contribute to water soaking in bacterial spot of tomato

“…We used the TALE-NT 2.0 algorithm (27) to computationally predict the AvrHah1 EBEs in the tomato promoterome, defined here as the set of sequences 300 bp upstream of the start codon for annotated genes in the Heinz 1706 genome (32). This prediction resulted in 4,106 possible binding sites (on both the plus and minus strands).…”

“…Data analysis was performed using the CLC Genomics Workbench software to identify differentially expressed genes (at least twofold different with P < 0.05). Computational predictions for AvrHah1 EBEs were performed using the TALE-NT 2.0 algorithm (27) with RVDs for AvrHah1 (NN_IG_NI_ NI_NI_HD_HD_NG_NN_NI_HD_HD_HD_NG) and a cutoff of 4 times the best possible score of 3.76. Up-regulation of genes of interest were confirmed with semiquantitative RT-PCR.…”

Lateral organ boundaries 1 is a disease susceptibility gene for citrus bacterial canker disease

“…Genes with a P ≤ 0.01 were considered as differentially expressed genes at a statistically significant level. The 1,000-bp upstream sequences of selected genes were obtained from Phytozome (www.phytozome.org/citrus.php), and the regions were scanned by Target Finder using RVD sequences of PthA4 and PthAw (49).…”