Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research

UMMS Affiliation

Department of Microbiology and Physiological Systems

Publication Date


Document Type



Genetics | Genomics | Investigative Techniques | Research Methods in Life Sciences


The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.


chromosomal sex, diagnostic SNPs, genetic QC, genetic background, genetic constructs, substrains

Rights and Permissions

Copyright © 2020 by the Genetics Society of America. Available freely online through the author-supported open access option.

DOI of Published Version



Sigmon JS, Blanchard MW, Baric RS, Bell TA, Brennan J, Brockmann GA, Burks AW, Calabrese JM, Caron KM, Cheney RE, Ciavatta D, Conlon F, Darr DB, Faber J, Franklin C, Gershon TR, Gralinski L, Gu B, Gaines CH, Hagan RS, Heimsath EG, Heise MT, Hock P, Ideraabdullah F, Jennette JC, Kafri T, Kashfeen A, Kulis M, Kumar V, Linnertz C, Livraghi-Butrico A, Lloyd KCK, Lutz C, Lynch RM, Magnuson T, Matsushima GK, McMullan R, Miller DR, Mohlke KL, Moy SS, Murphy CEY, Najarian M, O'Brien L, Palmer AA, Philpot BD, Randell SH, Reinholdt L, Ren Y, Rockwood S, Rogala AR, Saraswatula A, Sassetti CM, Schisler JC, Schoenrock SA, Shaw GD, Shorter JR, Smith CM, St Pierre CL, Tarantino LM, Threadgill DW, Valdar W, Vilen BJ, Wardwell K, Whitmire JK, Williams L, Zylka MJ, Ferris MT, McMillan L, Manuel de Villena FP. Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research. Genetics. 2020 Dec;216(4):905-930. doi: 10.1534/genetics.120.303596. Epub 2020 Oct 16. PMID: 33067325. Link to article on publisher's site

Journal/Book/Conference Title



This article is based on a previously available preprint on bioRxiv that is also available in eScholarship@UMMS.

Full author list omitted for brevity. For the full list of authors, see article.

Related Resources

Link to Article in PubMed

PubMed ID