Angiogenesis, the formation of new blood vessels from existing vasculature, is a complex process that is essential for normal embryonic development. Current models for experimental evaluation of angiogenesis often use tissue from large vessels like the aorta and umbilical vein, which are phenotypically distinct from microvasculature. We demonstrate that the utilization of skin to measure microvascular angiogenesis in embryonic and adult tissues is an efficient way to quantify microvasculature angiogenesis. We validate this approach and demonstrate its added value by showing significant differences in angiogenesis in monogenic and polygenic mouse models. We discovered that the pattern of angiogenic response among inbred mouse strains in this ex vivo assay differ from the strain distributions of previous in vivo angiogenesis assays. The difference between the ex vivo and in vivo assays may be related to systemic factors present in whole animals. Expression analysis of cultured skin biopsies from strains of mice with opposing angiogenic response were performed to identify pathways that contribute to differential angiogenic response. Increased expression of negative regulators of angiogenesis in C57Bl/6J mice was associated with lower growth rates.

The Kidd locus phenotype Jk(a-b-) was detected in 0.9 percent of Polynesians living in New Zealand. Over a period of 13 years, nine examples of anti-Jk3 were detected, one of which caused a delayed hemolytic transfusion reaction. Other examples resulted in mild hemolytic disease of the newborn. The anti-Jk3 reacted as an inseparable antibody, confirmed that inheritance of the Jk(a-b-) phenotype was best explained by the presence of a silent Jk allele.

Epilepsy has many causes and comorbidities affecting as many as 4% of people in their lifetime. Both idiopathic and symptomatic epilepsies are highly heritable, but genetic factors are difficult to characterize among humans due to complex disease etiologies. Rodent genetic studies have been critical to the discovery of seizure susceptibility loci, including Kcnj10 mutations identified in both mouse and human cohorts. However, genetic analyses of epilepsy phenotypes in mice to date have been carried out as acute studies in seizure-naive animals or in Mendelian models of epilepsy, while humans with epilepsy have a history of recurrent seizures that also modify brain physiology. We have applied a repeated seizure model to a genetic reference population, following seizure susceptibility over a 36-d period. Initial differences in generalized seizure threshold among the Hybrid Mouse Diversity Panel (HMDP) were associated with a well-characterized seizure susceptibility locus found in mice: Seizure susceptibility 1. Remarkably, Szs1 influence diminished as subsequent induced seizures had diminishing latencies in certain HMDP strains. Administration of eight seizures, followed by an incubation period and an induced retest seizure, revealed novel associations within the calmodulin-binding transcription activator 1, Camta1. Using systems genetics, we have identified four candidate genes that are differentially expressed between seizure-sensitive and -resistant strains close to our novel Epileptogenesis susceptibility factor 1 (Esf1) locus that may act individually or as a coordinated response to the neuronal stress of seizures.

Objective: MRL/MpJ mice are known for enhanced healing, but mechanistic details or how specific aspects of wounding (e.g., angiogenesis) contribute to healing are unknown. While previous studies investigated the systemic effects of immunity in MRL/MpJ healing, few have focused on tissue-intrinsic effects. Approach: Ex vivo skin biopsies from MRL/MpJ and C57BL/6J mice were cultured in ex vivo conditions that favor endothelial cell growth to compare their angiogenic potential. We localized enhanced angiogenesis quantitative trait loci (QTL) in an F2 intercross. We then performed an expression analysis in cultured skin biopsies from MRL/MpJ and C57BL/6J mice to determine the pathways that are associated with the capacity for differential growth.