Anti-ZFX (C-terminal) polyclonal antibody

Objective: To evaluate methods of DNA extraction from single cells for their suitability to amplify and provide a correct diagnosis of target disease genes. Design: Experimental study. Setting: University hospital laboratory. Patient(s): Two normal adult male and female blood donors. Intervention(s): Exon 51 of the dystrophin gene and the ZFX/ZFY gene were amplified from single lymphocytes using nested PCR. Five different methods of DNA extraction were tested (lysis in distilled water with freezing and thawing using liquid nitrogen, lysis in distilled water, alkaline lysis buffer, Proteinase K/sodium dodecyl sulfate (SDS) buffer, and N-lauroylsarcosine salt solution). Main Outcome Measure(s): Allele drop out and amplification rate. Result(s): The amplification efficiency from single unaffected lymphocytes was 89.0% using the liquid nitrogen method, 88.1% with the distilled water lysis method, 97.5% with the alkaline lysis buffer method, 91.5% with the Proteinase K/SDS lysis buffer method, and 84.8% using the N-lauroylsarcosine salt solution method. The mean allele drop out rate was 16.7%, 43.9%, 2.0%, 9.8%, and 18.9%, respectively, for each lysis method using single male lymphocytes as a template. Conclusion(s): Based on these results, DNA extraction using an alkaline lysis buffer results in more efficient rates of DNA amplification and less allele drop out than the other methods of DNA extraction tested. This method is suitable for the lysis of single cells in clinical preimplantation genetic diagnosis. (Fertil Steril (R) 2009;92:814-8. (c) 2009 by American Society for Reproductive Medicine.)

Motif finding is a computationally expensive procedure subject to noise and false positives, but of major importance in understanding gene expression and cancer. Several authors argued in favor of using higher order background models to better discriminate motifs. This paper studies the effect of using Markov higher order models in three commonly used algorithms to identify the ZFX transcription factor's binding sites from a mouse embryonic stem cells dataset. We conclude that there are particular Markov orders that yield improved outcomes for each algorithm.