Laboratory of Mammalian Genetics, Division of Genome Dynamics, Creative Research Initiative Sousei, Hokkaido University, North 10 West 8, Kita-ku, Sapporo 060-0810, Japan.
Published: February 2007
AI Article Synopsis
Article Abstract
Although the laboratory rat (Rattus norvegicus) is an indispensable experimental animal for biomedical research and drug development, the lack of embryonic stem cell lines hampers gene-knockout studies. Here we report the successful generation of insertional mutant rats using the Sleeping Beauty (SB) transposon system. This would benefit a variety of biomedical research fields for which the rat model is better suited than the mouse model.
The BonnMu resource is a transposon tagged mutant collection designed for functional genomics studies in maize. To expand this resource, we crossed an active Mutator (Mu) stock with dent (B73, Co125) and flint (DK105, EP1, and F7) germplasm, resulting in the generation of 8064 mutagenized BonnMu F-families. Sequencing of these Mu-tagged families revealed 425 924 presumptive heritable Mu insertions affecting 36 612 (83%) of the 44 303 high-confidence gene models of maize (B73v5).
To utilize a transposon-tagged mutant as a breeding material in rice, an endogenous DNA transposon, , was introduced into Koshihikari by successive backcrossing together with , an active autonomous element. The founder line for -tagged lines of Koshihikari carried on chromosome 9 and transposed on chromosomes 1 and 8 and on chromosome 11. In -tagged lines, there were the most abnormal phenotypic mutants and many aberrant chlorophyll mutants at seedling stage.
Background: Although chemotherapy is a core treatment for esophageal cancer, some patients develop drug resistance. Gene screening with transposons (i.e.
Cyanobacteria are photosynthetic prokaryotes that perform oxygenic photosynthesis by extracting electrons from water, with the generation of oxygen as a byproduct. Cyanobacteria use oxygen not only for respiration to produce energy in the dark but also for biosynthesis of various metabolites, such as heme and chlorophyll. Oxygen levels dynamically fluctuate in the field environments, from hyperoxic at daytime to almost anaerobic at night.
With next generation sequencing thousands of virus and viral vector integration genome targets are now under investigation to uncover specific integration preferences and to define clusters of integration, termed common integration sites (CIS), that may allow to assess gene therapy safety or to detect disease related genomic features such as oncogenes. Here, we addressed the challenge to: 1) define the notion of CIS on graph models, 2) demonstrate that the structure of CIS enters in the category of scale-free networks and 3) show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD) as a testing dataset.
