Integration of Murine and Human Studies for Mapping Periodontitis Susceptibility

Nashef, Aysar; Qabaja, R.; Salaymeh, Y.; Botzman, Maya; Munz, Matthias; Dommisch, Henrik; Krone, Bastian; Hoffmann, Per; Wellmann, Jürgen; Laudes, Matthias; Berger, Klaus; Kocher, Thomas; Loos, Bruno G.; Velde, Nathalie van der; Uitterlinden, André G.; Groot, Lisette C. P. G. M. de; Franke, André; Offenbacher, Steven; Lieb, Wolfgang; Divaris, Kimon; Mott, Richard; Gat‐Viks, Irit; Wiess, Ervin; Schäefer, Arne S.; Iraqi, Fuad A.; Haddad, Y.H.

doi:10.1177/0022034517744189

Cited by 22 publications

(27 citation statements)

References 41 publications

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“…Full details of CC lines and their power of mapping QTL with host susceptibility to complex traits are presented in various publications (Abu‐Toamih Atamni, Mott et al., ; Abu‐Toamih Atamni, Botzman et al., ; Abu‐Toamih Atamni et al. ; Aylor et al., ; Durrant et al., ; Iraqi et al., ; Iraqi, Churchill, & Mott, ; Levy et al., ; Lorè, Iraqi, & Bragonzi, ; Molenhuis et al., ; Nashef et al., ; Philip et al., ; Vered et al., ; Welsh et al., ). The CC mouse model is the focal point in our research, having exclusive access to the CC lines produced at our laboratory at Tel Aviv University (TAU).…”

Section: The Collaborative Crossmentioning

confidence: 99%

“…The updated genotype status of the population was presented recently (Iraqi et al., ), while numerous studies show the diversity of the phenotypic response of the CC lines to complex disease and the power of this resource for mapping QTL associated with this trait to small genomic intervals less than 0.5 centimorgans (CM), which contain only a few genes (Abu‐Toamih Atamni, Mott et al., ; Abu‐Toamih Atamni, Botzman et al., ; Abu‐Toamih Atamni et al. ; Abu‐Toamih Atamni, Botzman, Mott, Gat‐Viks, & Iraqi, ; Durrant et al., ; Levy et al., ; Molenhuis et al., ; Nashef et al., ; Vered et al., ). Herein, we present our various protocols and methods, using the CC mouse resource for dissecting the genetic architecture underlying the phenotypic variation of complex traits.…”

Section: The Collaborative Crossmentioning

confidence: 99%

“…The result is a unique collection of 72 RIL exhibiting large phenotypic and genetic diversity, and bringing the tremendous genetic variation potential of the mouse inbred lines to phenotypic expression (Churchill et al, 2004;Paterson, 1995). Full details of CC lines and their power of mapping QTL with host susceptibility to complex traits are presented in various publications (Abu-Toamih Abu-Toamih Atamni, Botzman et al, 2016;Abu-Toamih Atamni et al 2017;Aylor et al, 2011;Durrant et al, 2011;Iraqi et al, 2012;Iraqi, Churchill, & Mott, 2008;Levy et al, 2015;Lorè, Iraqi, & Bragonzi, 2015;Molenhuis et al, 2018;Nashef et al, 2018;Philip et al, 2011;Vered et al, 2014;Welsh et al, 2012). The CC mouse model is the focal point in our research, having exclusive access Soller et al…”

Section: The Collaborative Crossmentioning

confidence: 99%

“…The CC lines were genotyped three times: once using 620,000 single-nucleotide polymorphism (SNP) markers of the mouse diversity array (Yang et al, 2009); again with the first-generation mouse universal genotyping array (MUGA), built on the Illumina Infinium platform (7851 SNPs markers); and finally with the second-generation MegaMUGA genotyping array (superset of MUGA), using 77,808 SNPs markers (Iraqi et al, 2012;Morgan et al, 2015). The updated genotype status of the population was presented recently (Iraqi et al, 2012), while numerous studies show the diversity of the phenotypic response of the CC lines to complex disease and the power of this resource for mapping QTL associated with this trait to small genomic intervals less than 0.5 centimorgans (CM), which contain only a few genes (Abu-Toamih Atamni, Abu-Toamih Atamni, Botzman et al, 2016;Abu-Toamih Atamni et al 2017; Abu-Toamih Atamni, Botzman, Mott, Gat-Viks, & Iraqi, 2018;Durrant et al, 2011;Levy et al, 2015;Molenhuis et al, 2018;Nashef et al, 2018;Vered et al, 2014). Herein, we present our various protocols and methods, using the CC mouse resource for dissecting the genetic architecture underlying the phenotypic variation of complex traits.…”

Section: Of 14mentioning

confidence: 99%

“…Experience has shown that these can usually be relied upon to contribute one or more QTL having large effects on target trait value (i.e., explaining 20% or more of phenotypic variation among the CC strains) to the CC gene pool. Such loci can be mapped with high power and precision by the CC resource (Abu-Toamih Atamni, Mott, Soller, & Iraqi, 2016;Abu-Toamih Atamni, Botzman, Mott, Gat-Viks, & Iraqi, 2016;Abu-Toamih Atamni, Ziner, Mott, Wolf, & Iraqi, 2017;Aylor et al, 2011;Durrant et al, 2011;Levy, Mott, Iraqi, & Gabet, 2015;Molenhuis et al, 2018;Nashef et al, 2018;Philip et al, 2011;Vered, Durrant, Mott, & Iraqi, 2014). Thus, the CC resource is a valuable addition to the available genetic infrastructure for initial exploration of the physiological genetics of a target trait.…”

Section: Introductionmentioning

confidence: 99%

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Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population

et al. 2019

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The Collaborative Cross (CC) mouse resource is a next‐generation mouse genetic reference population (GRP) designed for high‐resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild‐derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions. These traits are observed at multiple levels of the animals’ systems, including metabolism, body weight, immune profile, and susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present general guidelines for design of QTL mapping experiments using the CC resource—along with full step‐by‐step protocols and methods that were implemented in our lab for the phenotypic and genotypic characterization of the different CC lines—for mapping the genes underlying host response to infectious and chronic diseases. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: CC lines for whole body mass index (BMI) Basic Protocol 2: A detailed assessment of the power to detect effect sizes based on the number of lines used, and the number of replicates per line Basic Protocol 3: Obtaining power for QTL with given target effect by interpolating in Table 1 of Keele et al. (2019)

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Section: The Collaborative Crossmentioning

confidence: 99%

Section: The Collaborative Crossmentioning

confidence: 99%

Section: The Collaborative Crossmentioning

confidence: 99%

Section: Of 14mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population

et al. 2019

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Efficient protocols and methods for high‐throughput utilization of the Collaborative Cross mouse model for dissecting the genetic basis of complex traits

Atamni

Iraqi

2019

Anim Models and Exp Med

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The Collaborative Cross (CC) mouse model is a next‐generation mouse genetic reference population (GRP) designated for a high‐resolution quantitative trait loci (QTL) mapping of complex traits during health and disease. The CC lines were generated from reciprocal crosses of eight divergent mouse founder strains composed of five classical and three wild‐derived strains. Complex traits are defined to be controlled by variations within multiple genes and the gene/environment interactions. In this article, we introduce and present variety of protocols and results of studying the host response to infectious and chronic diseases, including type 2 diabetes and metabolic diseases, body composition, immune response, colorectal cancer, susceptibility to Aspergillus fumigatus, Klebsiella pneumoniae, Pseudomonas aeruginosa, sepsis, and mixed infections of Porphyromonas gingivalis and Fusobacterium nucleatum, which were conducted at our laboratory using the CC mouse population. These traits are observed at multiple levels of the body systems, including metabolism, body weight, immune profile, susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present full protocols and step‐by‐step methods, implemented in our laboratory for the phenotypic and genotypic characterization of the different CC lines, mapping the gene underlying the host response to these infections and chronic diseases. The CC mouse model is a unique and powerful GRP for dissecting the host genetic architectures underlying complex traits, including chronic and infectious diseases.

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Studying host genetic background effects on multimorbidity of intestinal cancer development, type 2 diabetes and obesity in response to oral bacterial infection and high‐fat diet using the collaborative cross (CC) lines

Milhem

Toamih-Atamni

Karkar

et al. 2021

Anim Models and Exp Med

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Background Multimorbidity of intestinal cancer (IC), type 2 diabetes (T2D) and obesity is a complex set of diseases, affected by environmental and genetic risk factors. High‐fat diet (HFD) and oral bacterial infection play important roles in the etiology of these diseases through inflammation and various biological mechanisms. Methods To study the complexity of this multimorbidity, we used the collaborative cross (CC) mouse genetics reference population. We aimed to study the multimorbidity of IC, T2D, and obesity using CC lines, measuring their responses to HFD and oral bacterial infection. The study used 63 mice of both sexes generated from two CC lines (IL557 and IL711). For 12 weeks, experimental mice were maintained on specific dietary regimes combined with co‐infection with oral bacteria Porphyromonas gingivalis and Fusobacterium nucleatum, while control groups were not infected. Body weight (BW) and results of a intraperitoneal glucose tolerance test (IPGTT) were recorded at the end of 12 weeks, after which length and size of the intestines were assessed for polyp counts. Results Polyp counts ranged between 2 and 10 per CC line. The combination of HFD and infection significantly reduced (P < .01) the colon polyp size of IL557 females to 2.5 cm2, compared to the other groups. Comparing BW gain, IL557 males on HFD gained 18 g, while the females gained 10 g under the same conditions and showed the highest area under curve (AUC) values of 40 000‐45 000 (min mg/dL) in the IPGTT. Conclusion The results show that mice from different genetic backgrounds respond differently to a high fat diet and oral infection in terms of polyp development and glucose tolerance, and this effect is gender related.

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Integration of Murine and Human Studies for Mapping Periodontitis Susceptibility

Cited by 22 publications

References 41 publications

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population

Efficient protocols and methods for high‐throughput utilization of the Collaborative Cross mouse model for dissecting the genetic basis of complex traits

Studying host genetic background effects on multimorbidity of intestinal cancer development, type 2 diabetes and obesity in response to oral bacterial infection and high‐fat diet using the collaborative cross (CC) lines

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