Mapping novel QTL and fine mapping of previously identified QTL associated with glucose tolerance using the collaborative cross mice

Abstract

A chronic metabolic illness, type 2 diabetes (T2D) is a polygenic and multifactorial complicated disease.With an estimated 463 million persons aged 20 to 79 having diabetes, the number is expected to rise to 700 million by 2045, creating a signi cant worldwide health burden. Polygenic variants of diabetes are in uenced by environmental variables. Diabetes polygenic variants frequently run in families. T2D is regarded as a silent illness that can advance for years before being diagnosed. Numerous metabolic issues are noticed once T2D is diagnosed, either as comorbidities or as side effects. Finding genetic markers for T2D and metabolic syndrome in groups with similar environmental exposure is therefore essential to understanding the mechanism of such complex characteristic illnesses. So herein, we demonstrated the exclusive use of the collaborative cross (CC) mouse reference population to identify novel quantitative trait loci (QTL) and, subsequently, suggested genes associated with host glucose tolerance in response to a high-fat diet. In the current study, we used 539 mice from 60 different CC lines.The diabetogenic effect in response to high-fat dietary challenge was measured by the intraperitoneal glucose tolerance test (IPGTT) after 12 weeks of dietary challenge. Data analysis was performed using a statistical software package IBM SPSS Statistic 23. Using the mouse genome informatics (MGI) database resource enabled us to examine the reported QTL in detail for genetic features related to glucose metabolism. Afterward, the total area under the curve (AUC0-180) of the glucose clearance was computed and utilized as a marker for the presence and severity of diabetes. The observed AUC0-180 averages for males and females were 51267.5 and 36537.5 mg/dL, respectively, representing a 1.4-fold difference in favor of females with lower AUC0-180 indicating adequate glucose clearance. The AUC0-180 mean differences between the sexes within each speci c CC line varied widely within the CC population. A total of 46 new QTL, designated as T2DSL and its number, for Type 2 Diabetes Speci c Locus and its number, were identi ed during our study, among which 19 QTL are novel. The interval locations of these novel QTL have not been found in any other previously identi ed QTL. The remaining 27 QTL observed during our study have been ne mapped. As far as the genome-wide signi cance is concerned, three sets of QTL were identi ed during our entire study. The rst group is the one which had a 50% of genome-wide signi cance, the second group is of 90%, and the third group had a 95% of genomewide signi cance. Further, our study showed a complex pattern of haplotype effects of the founders, with the wild-derived strains (mainly PWK) playing a signi cant role in the increase of AUC values.

Identifying genetic susceptibility to Aspergillus fumigatus infection using collaborative cross mice and RNA‐Seq approach

“…Some strains show resistance to the infection, while others show sensitivity to the infection, presumably due to the genetic diversity of the CC founders (mouse being the most commonly used animal model) 45 . This demonstrates the ability of the CC resource to provide high‐resolution mapping of QTL affecting a wide variety of traits, including susceptibility to a spectrum of infectious diseases 36,46,47 …”

“… 45 This demonstrates the ability of the CC resource to provide high‐resolution mapping of QTL affecting a wide variety of traits, including susceptibility to a spectrum of infectious diseases. 36 , 46 , 47 …”

The Complexity of Skeletal Transverse Dimension: From Diagnosis, Management, and Treatment Strategies to the Application of Collaborative Cross (CC) Mouse Model

“…In order to gain a deeper comprehension of the mechanisms underlying STDs, the ideal animal model would spontaneously develop STDs in a way akin to that of people. Many novel medications have been developed and assessed using conventional animal models [ 82 , 83 ]. For in vivo research looking at the role of certain genes and genetic changes in acquiring STDs, genetically modified mice are perfect models [ 84 ].…”