AnthOligo

AnthOligo automates generation of oligonucleotide sequences for capture and enrichment of large and complex genomic regions using region-specific extraction (RSE) targeting long DNA fragments (15–20 kb) for magnetic bead–based capture following enzymatic extension of hybridized oligonucleotides.


Key Features:

  • Automated Oligo Sequence Generation: Generates oligonucleotide candidates and optimizes melting temperature (Tm), Gibbs free energy (ΔG), and minimizes primer-dimer formation for pooled experiments.
  • Customizable Parameters and Input: Accepts target region input in BED format and allows customization of selection criteria for oligo design.
  • RSE Probe Design: Tailors probes for region-specific extraction (RSE) compatible with enzymatic extension of hybridized oligonucleotides and magnetic bead capture of 15–20 kb fragments.
  • Applications to Gene Panels and CGH: Designs internal oligos for gene panel analysis and probes for comparative genomic hybridization (CGH) arrays.
  • Validation: Demonstrated capture of the Major Histocompatibility Complex (MHC) in experimental testing.

Scientific Applications:

  • Targeted Genomic Resequencing: Supports design of capture probes for targeted resequencing of large genomic regions.
  • Gene Panel Analysis: Enables creation of internal oligos for targeted gene panels.
  • Comparative Genomic Hybridization (CGH): Generates probes suitable for large-scale CGH array experiments.

Methodology:

Given a BED file of target regions, AnthOligo computes oligonucleotide candidates and evaluates melting temperature (Tm), Gibbs free energy (ΔG), and primer-dimer formation to select probes suitable for capture.

Topics

Details

Programming Languages:
Java
Added:
1/14/2020
Last Updated:
12/2/2020

Operations

Publications

Jayaraman P, Mosbruger T, Hu T, Tairis NG, Wu C, Clark PM, D’Arcy M, Ferriola D, Mackiewicz K, Gai X, Monos D, Sarmady M. AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies. Bioinformatics. 2020;36(15):4353-4356. doi:10.1093/bioinformatics/btaa552. PMID:32484858. PMCID:PMC7520035.

Funding: - National Institute of Diabetes and Digestive and Kidney Diseases: P30DK019525