An enhanced method for sequence walking and paralog mining: TOPO(R) Vector-Ligation PCR.

Academic Article

Abstract

  • BACKGROUND: Although technological advances allow for the economical acquisition of whole genome sequences, many organisms' genomes remain unsequenced, and fully sequenced genomes may contain gaps. Researchers reliant upon partial genomic or heterologous sequence information require methods for obtaining unknown sequences from loci of interest. Various PCR based techniques are available for sequence walking - i.e., the acquisition of unknown DNA sequence adjacent to known sequence. Many such methods require rigid, elaborate protocols and/or impose narrowly confined options in the choice of restriction enzymes for necessary genomic digests. We describe a new method, TOPO(R) Vector-Ligation PCR (or TVL-PCR) that innovatively integrates available tools and familiar concepts to offer advantages as a means of both targeted sequence walking and paralog mining. FINDINGS: TVL-PCR exploits the ligation efficiency of the pCR(R)4-TOPO(R) (Invitrogen, Carlsbad, California) vector system to capture fragments of unknown sequence by creating chimeric molecules containing defined priming sites at both ends. Initially, restriction enzyme-digested genomic DNA is end-repaired to create 3' adenosine overhangs and is then ligated to pCR4-TOPO vectors. The ligation product pool is used directly as a template for nested PCR, using specific primers to target orthologous sequences, or degenerate primers to enable capture of paralogous gene family members. We demonstrated the efficacy of this method by capturing entire coding and partial promoter sequences of several strawberry Superman-like genes. CONCLUSIONS: TVL-PCR is a convenient and efficient method for DNA sequence walking and paralog mining that is applicable to any organism for which relevant DNA sequence is available as a basis for primer design.
  • Authors

  • Orcheski, Benjamin B
  • Davis, Thomas
  • Publication Date

  • March 4, 2010
  • Has Subject Area

    Published In

  • BMC Research Notes  Journal
  • Keywords

  • Biotechnology
  • Generic Health Relevance
  • Genetics
  • Digital Object Identifier (doi)

    Start Page

  • 61
  • Volume

  • 3
  • Issue

  • 1