Physical Confirmation and Mapping of Overlapping Rat Mammary Carcinoma Susceptibility QTLs, Mcs2 and Mcs6

Only a portion of the estimated heritability of breast cancer susceptibility has been explained by individual loci. Comparative genetic approaches that first use an experimental organism to map susceptibility QTLs are unbiased methods to identify human orthologs to target in human population-based genetic association studies. Here, overlapping rat mammary carcinoma susceptibility (Mcs) predicted QTLs, Mcs6 and Mcs2, were physically confirmed and mapped to identify the human orthologous region. To physically confirm Mcs6 and Mcs2, congenic lines were established using the Wistar-Furth (WF) rat strain, which is susceptible to developing mammary carcinomas, as the recipient (genetic background) and either Wistar-Kyoto (WKy, Mcs6) or Copenhagen (COP, Mcs2), which are resistant, as donor strains. By comparing Mcs phenotypes of WF.WKy congenic lines with distinct segments of WKy chromosome 7 we physically confirmed and mapped Mcs6 to ∼33 Mb between markers D7Rat171 and gUwm64-3. The predicted Mcs2 QTL was also physically confirmed using segments of COP chromosome 7 introgressed into a susceptible WF background. The Mcs6 and Mcs2 overlapping genomic regions contain multiple annotated genes, but none have a clear or well established link to breast cancer susceptibility. Igf1 and Socs2 are two of multiple potential candidate genes in Mcs6. The human genomic region orthologous to rat Mcs6 is on chromosome 12 from base positions 71,270,266 to 105,502,699. This region has not shown a genome-wide significant association to breast cancer risk in pun studies of breast cancer susceptibility

Contrasting epistatic interactions between rat quantitative trait loci controlling mammary cancer development.

We previously defined quantitative trait loci (QTLs) that control susceptibility to 7,12-dimethylbenz(alpha)anthracene-induced mammary carcinoma in SPRD-Cu3 (susceptible) and WKY (resistant) rats. Two of these QTLs, assigned to chromosomes (Chr) 10 and 18, control tumor growth rate and invasiveness. In this study we characterized a congenic strain in which a large segment of WKY Chr 10 was introduced in the SPRD-Cu3 genetic background and demonstrated that this chromosome segment controls this tumor trait. The WKY allele at this QTL (Mcsta1) reduces the growth rate of the fastest growing tumors by 26%. We also previously showed that two SPRD-Cu3-WKY congenic strains containing a WKY chromosome segment derived either from Chr 5 or from Chr 18 exhibit a reduction in tumor multiplicity (QTLs Msctm1 and Mcstm2, respectively) (with no reduction in tumor growth rate in the Chr 18 congenic). In this study we generated a double congenic strain, which contains the two WKY differential segments from Chr 5 and 18, to determine how these two segments interact with one another. Interestingly, two types of epistatic interactions were found: no additive effect was seen with respect to tumor multiplicity, while a reduction in tumor growth rate was observed. It thus appears that WKY alleles located on Chr 5 and Chr 8 interact epistatically in a contrasting manner to modulate tumor multiplicity (in a nonadditive manner) and growth rate (in a synergic manner). Tumor growth rate is thus influenced by two QTLs, on Chr 10 (Mcsta1) and on Chr 18 (Mcsta2), the action of the latter being dependent on the presence of the Chr5 QTL (Mcstm1). The expression level of positional and functional candidate genes was also analyzed. On Chr 5, Pla2g2a is subject to a syntenic control while expression of the Tp53 (Chr 10) and Pmai1/Noxa (Chr 18) genes appears to be controlled by several mammary cancer resistance QTLs.Journal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

Model organism data evolving in support of translational medicine

Model organism databases (MODs) have been collecting and integrating biomedical research data for 30 years and were designed to meet specific needs of each model organism research community. The contributions of model organism research to understanding biological systems would be hard to overstate. Modern molecular biology methods and cost reductions in nucleotide sequencing have opened avenues for direct application of model organism research to elucidating mechanisms of human diseases. Thus, the mandate for model organism research and databases has now grown to include facilitating use of these data in translational applications. Challenges in meeting this opportunity include the distribution of research data across many databases and websites, a lack of data format standards for some data types, and sustainability of scale and cost for genomic database resources like MODs. The issues of widely distributed data and application of data standards are some of the challenges addressed by FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles. The Alliance of Genome Resources is now moving to address these challenges by bringing together expertly curated research data from fly, mouse, rat, worm, yeast, zebrafish, and the Gene Ontology consortium. Centralized multi-species data access, integration, and format standardization will lower the data utilization barrier in comparative genomics and translational applications and will provide a framework in which sustainable scale and cost can be addressed. This article presents a brief historical perspective on how the Alliance model organisms are complementary and how they have already contributed to understanding the etiology of human diseases. In addition, we discuss four challenges for using data from MODs in translational applications and how the Alliance is working to address them, in part by applying FAIR data principles. Ultimately, combined data from these animal models are more powerful than the sum of the parts