Back to Search Start Over

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

Authors :
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
Source :
Genetics [Genetics] 2020 Dec; Vol. 216 (4), pp. 905-930. Date of Electronic Publication: 2020 Oct 16.
Publication Year :
2020

Abstract

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 X O 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.<br /> (Copyright © 2020 by the Genetics Society of America.)

Details

Language :
English
ISSN :
1943-2631
Volume :
216
Issue :
4
Database :
MEDLINE
Journal :
Genetics
Publication Type :
Academic Journal
Accession number :
33067325
Full Text :
https://doi.org/10.1534/genetics.120.303596