4.4 Article

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

期刊

GENETICS
卷 216, 期 4, 页码 905-930

出版社

OXFORD UNIV PRESS INC
DOI: 10.1534/genetics.120.303596

关键词

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

资金

  1. National Health Institutes (NIH) National Human Genome Research Institute [U24HG010100]
  2. NIH Office of the Director [U42OD010924, U42OD010921, U42OD012210]
  3. National Institute of Allergy and Infectious Diseases [U19AI100625, P01AI132130]
  4. National Institute of General Medical Sciences [R01GM121806]
  5. National Institute on Drug Abuse [P50DA039841]
  6. National Institute of Mental Health [R01MH100241]
  7. National Heart, Lung, and Blood Institute [5R01HL128119, K08HL143271]
  8. National Institute of Diabetes and Digestive and Kidney Diseases [5R01DK058702, P01DK058335, RG1607-25207]
  9. Neogen Inc.
  10. [R01ES029925]
  11. [P42ES031007]

向作者/读者索取更多资源

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.

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