Page 84 - Mouse Molecular Genetics

Full Abstracts
Program number is above title. Author in bold is the presenter.
interrogate 20-fold more samples in an equivalent time in a simple read-mode configuration. Second, TaqMan has proven to be
more sensitive and specific for genetic screening than PCR alone. Because of these large improvements in using TaqMan for
genetic screening, we have developed a method to convert PCR-based genotyping assays into TaqMan assays. One critical
component in this process is the validation required to ensure data fidelity during assay conversion. We also describe the
elements of various validation procedures as well as ensuring assay concordance.
Class Switch Recombination in RNA Exosome Deficient Mouse Models. Evangelos Pefanis
Aris Economides
. 1)
Columbia University, New York, NY; 2) Regeneron Pharmaceuticals, Tarrytown, NY.
Class switch recombination (CSR) and somatic hypermutation (SHM) are critical steps in the diversification of the
immunoglobulin heavy chain locus (IgH) in B lymphocytes. CSR involves a somatic rearrangement/deletion event replacing
the heavy chain constant region with that of a different isotype, whereas SHM introduces somatic mutations in the variable
regions of Ig exons. Both CSR and SHM are initiated by the cytidine deaminase AID. We have previously shown using
biochemical assays and CH12F3 B lymphoma cells that the RNA exosome complex provides AID with access to both strands of
transcribed duplex DNA. As a continuation of this work we have targeted the Exosc3 and Exosc10 subunits of the RNA exosome
complex for conditional mutagenesis in mice. Here we describe a novel Cre mediated conditional inversion (COIN) mutagenesis
approach, whereby inversion leads to simultaneous inactivation of the targeted allele and induction of a fluorescent protein
reporter. Exosc3-COIN/COIN homozygous B cells have reduced CSR efficiency despite normal expression of AID. These
findings further support the role of nuclear RNA surveillance pathways in the generation of immunoglobulin diversification.
A pipeline of bioinformatics tools for whole-genome analysis in mouse models. Matthew A Richardson
Clinton L Cario
Matthew Hsieh
George D Leikauf
Steven D Shapiro
Annerose Berndt
. 1)
Pulmonary, Allergy and Critical Care Medicine,
University of Pittsburgh, Pittsburgh, PA; 2) University of Pittsburgh Medical Center, Pittsburgh, PA; 3) Department of
Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania,
United States; 4) Information Technology, Carnagie Mellon University, Pittsburgh, PA.
Purpose: Genome analysis in mouse models has entered a high demand era as a result of generating high-density and most
recently whole-genome single nucleotide polymorphism (SNP) panels for many laboratory mouse strains. Additionally, an
increasing number of investigators determine disease phenotypes across multiple mouse strains, which in combination with dense
genotype panels can be used in genome-wide association (GWA) analyses to identify novel biomarkers. While several GWA
algorithms are publicly available (e.g., EMMA, EMMAX, GEMMA), most often they are computationally intensive and often
require skilled personnel for their operation. Additional bioinformatics approaches subsequently to GWA analysis are necessary
for SNP annotation, which frequently vary among investigators. Here, we present the development of an automated, user-friendly
bioinformatics workflow to increase accuracy and reproducibility in genome analyses that lead to biomarker identification.
Methods: We implemented a bioinformatics pipeline through developing three computationally integrated layers: a presentation,
middle, and processing layer. The presentation layer was designed using jQuery, Javascript, HTML5, and CSS3 and the middle
ware was implemented with Django and the Python programming language. The processing layer operates with custom C and
C++ programs and awk, R, Perl, and Python scripts. Results: We generated an open-access web interface (freely available at
hosting bioinformatics tools to streamline genome analysis from GWA to biomarker
identification. The functionality of the new interface is two-fold: variant identification (tools: Local EMMA/EMMAX/GEMMA
Server, the Manhattan Plot Generator, and the Genome Region Search Tool) and gene/variant annotation (tools: SNP Annotator,
PolyPhen-2 Submitter, and Microarray Data Explorer). GWA analysis can be performed with EMMA, EMMAX, or GEMMA
using one of several high-density and whole-genome SNP panels (incl., 65 million Sanger SNPs) and computation ranges
between 3 and 10 minutes per analysis depending on algorithm and SNP panel. SNP annotations are performed using Ensembls
Variant Effect Predictor and Harvards PolyPhen-2 algorithms. Conclusions: The work of this project enables high-throughput
genome-analysis and biomarker identification to a broad audience of investigators with multi-strain phenotype data.
Assessment of cryopreserved samples of mutant mice.
Johannes Schenkel
Cryopreservation W430, German Cancer
Research Center (DKFZ), Heidelberg, Germany.
Genetically modified animals are unique mutants with an enormous scientific potential. Cryopreservation of pre-implantation
embryos or of spermatozoa is a common approach to save those lines. Following sufficient cryopreservation and assessment, a
mutant line can be taken out of a breeding nucleus. The quality of different donors of the same line may be heterogeneous and the
procedure error-prone, too. To make sure that the quality of the frozen material is satisfying, several assessments are available,
resource saving approaches should be preferred:
of the donor animals is helpful, but not ever applicable.
in vitro
over-night culture can demonstrate the capacity of further development. At least one statistically selected
sample must be revitalized and transferred into pseudo-pregnant foster mothers. The litter must be genotyped, if the outcome of
genetically modified pups is smaller than to be expected, the reason has to be found out, additional embryos are to be
in vitro
fertilization (IVF) capacity of each line must be shown; it can be reduced or lost due to the