Improving laboratory animal genetic reporting: LAG-R guidelines.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
02 Jul 2024
02 Jul 2024
Historique:
received:
12
02
2024
accepted:
05
06
2024
medline:
3
7
2024
pubmed:
3
7
2024
entrez:
2
7
2024
Statut:
epublish
Résumé
The biomedical research community addresses reproducibility challenges in animal studies through standardized nomenclature, improved experimental design, transparent reporting, data sharing, and centralized repositories. The ARRIVE guidelines outline documentation standards for laboratory animals in experiments, but genetic information is often incomplete. To remedy this, we propose the Laboratory Animal Genetic Reporting (LAG-R) framework. LAG-R aims to document animals' genetic makeup in scientific publications, providing essential details for replication and appropriate model use. While verifying complete genetic compositions may be impractical, better reporting and validation efforts enhance reliability of research. LAG-R standardization will bolster reproducibility, peer review, and overall scientific rigor.
Identifiants
pubmed: 38956430
doi: 10.1038/s41467-024-49439-y
pii: 10.1038/s41467-024-49439-y
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
5574Subventions
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : ANR-10-INBS-07
Investigateurs
Atsushi Yoshiki
(A)
Chi-Kuang Wang
(CK)
Jacqueline Marvel
(J)
Ana Zarubica
(A)
Sara Wells
(S)
Jason Heaney
(J)
Sara Wells
(S)
Ian F Korf
(IF)
Cathleen Cat Lutz
(CC)
Andrew J Kueh
(AJ)
Paul Q Thomas
(PQ)
Ruth M Arkell
(RM)
Graham J Mann
(GJ)
Informations de copyright
© 2024. The Author(s).
Références
Baker, M. 1,500 scientists lift the lid on reproducibility. Nature 533, 452–454 (2016).
pubmed: 27225100
doi: 10.1038/533452a
Lloyd, K., Franklin, C., Lutz, C. & Magnuson, T. Reproducibility: Use mouse biobanks or lose them. Nature 522, 151–153 (2015).
pubmed: 26062496
pmcid: 4636083
doi: 10.1038/522151a
Dessimoz, C., Škunca N. The Gene Ontology Handbook Vol. 1446 (Springer, New York, NY, 2017).
Alliance of Genome Resources Consortium et al. Harmonizing model organism data in the Alliance of Genome Resources. Genetics 220, iyac022 (2022).
doi: 10.1093/genetics/iyac022
Smith, A. J., Clutton, R. E., Lilley, E., Hansen, K. E. A. & Brattelid, T. PREPARE: guidelines for planning animal research and testing. Lab. Anim. 52, 135–141 (2018).
pubmed: 28771074
doi: 10.1177/0023677217724823
Percie du Sert, N. et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biol. 18, e3000410 (2020).
pubmed: 32663219
pmcid: 7360023
doi: 10.1371/journal.pbio.3000410
the FAIRsharing Community et al. FAIRsharing as a community approach to standards, repositories and policies. Nat. Biotechnol. 37, 358–367 (2019).
doi: 10.1038/s41587-019-0080-8
Percie du Sert, N. et al. Reporting animal research: explanation and elaboration for the ARRIVE guidelines 2.0. PLoS Biol. 18, e3000411 (2020).
pubmed: 32663221
pmcid: 7360025
doi: 10.1371/journal.pbio.3000411
Sittig, L. J. et al. Genetic background limits generalizability of genotype–phenotype relationships. Neuron 91, 1253–1259 (2016).
pubmed: 27618673
pmcid: 5033712
doi: 10.1016/j.neuron.2016.08.013
Doetschman, T. Influence of genetic background on genetically engineered mouse phenotypes. In Gene Knockout Protocols Vol. 530 (eds. Wurst, W. & Kühn, R.) 423–433 (Humana Press, Totowa, NJ, 2009).
Strobel, M. C., Reinholdt, L. G., Malcolm, R. D. & Pritchett-Corning, K. Genetic monitoring of laboratory mice and rats. In Laboratory Animal Medicine. (eds Fox, J. G. et al.) 1403–1416 (Elsevier, 2015).
Simon, M. M. et al. A comparative phenotypic and genomic analysis of C57BL/6J and C57BL/6N mouse strains. Genome Biol. 14, R82 (2013).
pubmed: 23902802
pmcid: 4053787
doi: 10.1186/gb-2013-14-7-r82
Voelkl, B. et al. Reproducibility of animal research in light of biological variation. Nat. Rev. Neurosci. 21, 384–393 (2020).
pubmed: 32488205
doi: 10.1038/s41583-020-0313-3
Zeldovich, L. Genetic drift: the ghost in the genome. Lab Anim. 46, 255–257 (2017).
doi: 10.1038/laban.1275
Freedman, L. P., Cockburn, I. M. & Simcoe, T. S. The economics of reproducibility in preclinical research. PLoS Biol. 13, e1002165 (2015).
pubmed: 26057340
pmcid: 4461318
doi: 10.1371/journal.pbio.1002165
Jacquot, S., Chartoire, N., Piguet, F., Hérault, Y. & Pavlovic, G. Optimizing PCR for mouse genotyping: recommendations for reliable, rapid, cost effective, robust and adaptable to high‐throughput genotyping protocol for any type of mutation. Curr. Protoc. Mouse Biol. 9, e65 1–28 (2019).
Russell, W. M. S. & Burch, R. L. The Principles of Humane Experimental Technique. (Methuen, 1959).
Engle, S. HPRT-APRT-deficient mice are not a model for Lesch–Nyhan syndrome. Hum. Mol. Genet. 5, 1607–1610 (1996).
pubmed: 8894695
doi: 10.1093/hmg/5.10.1607
Meek, S. et al. Reduced levels of dopamine and altered metabolism in brains of HPRT knock-out rats: a new rodent model of Lesch–Nyhan Disease. Sci. Rep. 6, 25592 (2016).
pubmed: 27185277
pmcid: 4869022
doi: 10.1038/srep25592
Bilovocky, N. A., Romito-DiGiacomo, R. R., Murcia, C. L., Maricich, S. M. & Herrup, K. Factors in the genetic background suppress the Engrailed-1 cerebellar phenotype. J. Neurosci. 23, 5105–5112 (2003).
pubmed: 12832534
pmcid: 6741147
doi: 10.1523/JNEUROSCI.23-12-05105.2003
Axelsson, E. et al. The genetic consequences of dog breed formation—accumulation of deleterious genetic variation and fixation of mutations associated with myxomatous mitral valve disease in cavalier King Charles spaniels. PLoS Genet. 17, e1009726 (2021).
pubmed: 34473707
pmcid: 8412370
doi: 10.1371/journal.pgen.1009726
Sigmon, J. S. et al. Content and performance of the MiniMUGA genotyping array: a new tool to improve rigor and reproducibility in mouse research. Genetics 216, 905–930 (2020).
pubmed: 33067325
pmcid: 7768238
doi: 10.1534/genetics.120.303596
Barbaric, I. et al. An ENU-induced mutation in the Ankrd11 gene results in an osteopenia-like phenotype in the mouse mutant Yoda. Physiol. Genom. 32, 311–321 (2008).
doi: 10.1152/physiolgenomics.00116.2007
De Angelis, M. H. et al. Genome-wide, large-scale production of mutant mice by ENU mutagenesis. Nat. Genet. 25, 444–447 (2000).
doi: 10.1038/78146
Andersson, L. Molecular consequences of animal breeding. Curr. Opin. Genet. Dev. 23, 295–301 (2013).
pubmed: 23601626
doi: 10.1016/j.gde.2013.02.014
Ciepłoch, A., Rutkowska, K., Oprządek, J. & Poławska, E. Genetic disorders in beef cattle: a review. Genes Genom. 39, 461–471 (2017).
doi: 10.1007/s13258-017-0525-8
Bunton-Stasyshyn, R. K., Codner, G. F. & Teboul, L. Screening and validation of genome-edited animals. Lab Anim. 56, 69–82 (2022).
pubmed: 34192966
doi: 10.1177/00236772211016922
Marx, V. Method of the year: long-read sequencing. Nat. Methods 20, 6–11 (2023).
pubmed: 36635542
doi: 10.1038/s41592-022-01730-w
De Coster, W. & Van Broeckhoven, C. Newest methods for detecting structural variations. Trends Biotechnol. 37, 973–982 (2019).
pubmed: 30902345
doi: 10.1016/j.tibtech.2019.02.003
Chan, S. et al. Structural variation detection and analysis using bionano optical mapping. In Copy Number Variants Vol. 1833 (ed. Bickhart, D. M.) 193–203 (Springer, New York, 2018).
Benavides, F. et al. Genetic quality assurance and genetic monitoring of laboratory mice and rats: FELASA Working Group Report. Lab. Anim. 54, 135–148 (2020).
pubmed: 31431136
doi: 10.1177/0023677219867719
Cagan, A. et al. Somatic mutation rates scale with lifespan across mammals. Nature 604, 517–524 (2022).
pubmed: 35418684
pmcid: 9021023
doi: 10.1038/s41586-022-04618-z
Milholland, B. et al. Differences between germline and somatic mutation rates in humans and mice. Nat. Commun. 8, 15183 (2017).
pubmed: 28485371
pmcid: 5436103
doi: 10.1038/ncomms15183
Lynch, M. Evolution of the mutation rate. Trends Genet. 26, 345–352 (2010).
pubmed: 20594608
pmcid: 2910838
doi: 10.1016/j.tig.2010.05.003
Fox, J.G. et al. The Mouse in Biomedical Research (Elsevier, Amsterdam; Boston, 2007).
Rogers, J. Genomic resources for rhesus macaques (Macaca mulatta). Mamm. Genome 33, 91–99 (2022).
pubmed: 34999909
pmcid: 8742695
doi: 10.1007/s00335-021-09922-z
Vaysse, A. et al. Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping. PLoS Genet. 7, e1002316 (2011).
pubmed: 22022279
pmcid: 3192833
doi: 10.1371/journal.pgen.1002316
Matsuda, K. PCR-based detection methods for single-nucleotide polymorphism or mutation. In Advances in Clinical Chemistry Vol. 80 45–72 (Elsevier, 2017).
Rawle, D. J. et al. Widespread discrepancy in Nnt genotypes and genetic backgrounds complicates granzyme A and other knockout mouse studies. eLife 11, e70207 (2022).
pubmed: 35119362
pmcid: 8816380
doi: 10.7554/eLife.70207
Kelmenson, P. How to Refresh Your Mutant or Transgenic Mouse Strains https://www.jax.org/news-and-insights/jax-blog/2018/april/how-to-refresh-your-mutant-or-transgenic-mouse-strains (2018).
Trevarrow, B. & Robison, B. Genetic backgrounds, standard lines, and husbandry of zebrafish. Methods Cell Biol. 77, 599–616 (2004).
pubmed: 15602934
doi: 10.1016/S0091-679X(04)77032-6
Varga, Z. M. Aquaculture, husbandry, and shipping at the Zebrafish International Resource Center. Methods Cell Biol. 135, 509–534 (2016).
pubmed: 27443942
doi: 10.1016/bs.mcb.2016.01.007
Martins, S. et al. Toward an integrated zebrafish health management program supporting cancer and neuroscience research. Zebrafish 13, S47–S55 (2016).
pubmed: 26959533
doi: 10.1089/zeb.2015.1198
Liang, Q., Conte, N., Skarnes, W. C. & Bradley, A. Extensive genomic copy number variation in embryonic stem cells. Proc. Natl Acad. Sci. USA 105, 17453–17456 (2008).
pubmed: 18988746
pmcid: 2582305
doi: 10.1073/pnas.0805638105
Lintott, L. G. & Nutter, L. M. J. Genetic and Molecular Quality Control of Genetically Engineered Mice. In Transgenesis Vol. 2631 (ed. Saunders, T. L.) 53–101 (Springer US, New York, NY, 2023).
Goodwin, L. O. et al. Large-scale discovery of mouse transgenic integration sites reveals frequent structural variation and insertional mutagenesis. Genome Res. 29, 494–505 (2019).
pubmed: 30659012
pmcid: 6396414
doi: 10.1101/gr.233866.117
Burgio, G. & Teboul, L. Anticipating and Identifying Collateral Damage in Genome Editing. Trends Genet. 36, 905–914 (2020).
pubmed: 33039248
pmcid: 7658041
doi: 10.1016/j.tig.2020.09.011
Peterson, K. A. et al. Whole genome analysis for 163 gRNAs in Cas9-edited mice reveals minimal off-target activity. Commun. Biol. 6, 626 (2023).
pubmed: 37301944
pmcid: 10257658
doi: 10.1038/s42003-023-04974-0
Anderson, K. R. et al. CRISPR off-target analysis in genetically engineered rats and mice. Nat. Methods 15, 512–514 (2018).
pubmed: 29786090
pmcid: 6558654
doi: 10.1038/s41592-018-0011-5
Manghwar, H. et al. CRISPR/Cas systems in genome editing: methodologies and tools for sgRNA design, off‐target evaluation, and strategies to mitigate off‐target effects. Adv. Sci. 7, 1902312 (2020).
doi: 10.1002/advs.201902312
CRISPR off-targets: a reassessment. Nat Methods 15, 229–230 (2018).
Norris, A. L. et al. Template plasmid integration in germline genome-edited cattle. Nat. Biotechnol. 38, 163–164 (2020).
pubmed: 32034391
doi: 10.1038/s41587-019-0394-6
Leibowitz, M. L. et al. Chromothripsis as an on-target consequence of CRISPR–Cas9 genome editing. Nat. Genet. 53, 895–905 (2021).
pubmed: 33846636
pmcid: 8192433
doi: 10.1038/s41588-021-00838-7
Bertelsen, B. et al. A germline chromothripsis event stably segregating in 11 individuals through three generations. Genet. Med. 18, 494–500 (2016).
pubmed: 26312826
doi: 10.1038/gim.2015.112
Nurk, S. et al. The complete sequence of a human genome. Science 376, 44–53 (2022).
pubmed: 35357919
pmcid: 9186530
doi: 10.1126/science.abj6987
Schoch, C. L. et al. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database 2020, baaa062 (2020).
pubmed: 32761142
pmcid: 7408187
doi: 10.1093/database/baaa062
Tweedie, S. et al. Genenames.org: the HGNC and VGNC resources in 2021. Nucleic Acids Res. 49, D939–D946 (2021).
pubmed: 33152070
doi: 10.1093/nar/gkaa980
McCarthy, F. M. et al. The case for standardizing gene nomenclature in vertebrates. Nature 614, E31–E32 (2023).
pubmed: 36792746
pmcid: 9931569
doi: 10.1038/s41586-022-05633-w
Wells, D. J. et al. Assessing the welfare of genetically altered mice. Lab Anim. 40, 111–114 (2006).
pubmed: 16600070
doi: 10.1258/002367706776318971
Lalonde, R., Filali, M. & Strazielle, C. SHIRPA as a neurological screening battery in mice. Curr. Protoc. 1, e135 1–30 (2021).
Patange, S. & Maragh, S. Fire burn and cauldron bubble: what is in your genome editing brew? Biochemistry https://doi.org/10.1021/acs.biochem.2c00431 (2022).