Genetic influences on motor learning and performance and superperforming mutants revealed by random mutational survey of the mouse genome

Evolution depends upon genetic variations that influence physiology. As defined in a genetic screen, phenotypic performance may be enhanced or degraded by such mutations. We set out to detect mutations that influence motor function, including motor learning. Thus, we tested the motor effects of 36,4...

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Published inThe Journal of physiology Vol. 602; no. 11; pp. 2649 - 2664
Main Authors Jakkamsetti, Vikram, Ma, Qian, Angulo, Gustavo, Scudder, William, Beutler, Bruce, Pascual, Juan M.
Format Journal Article
LanguageEnglish
Published England Wiley Subscription Services, Inc 01.06.2024
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Summary:Evolution depends upon genetic variations that influence physiology. As defined in a genetic screen, phenotypic performance may be enhanced or degraded by such mutations. We set out to detect mutations that influence motor function, including motor learning. Thus, we tested the motor effects of 36,444 non‐synonymous coding/splicing mutations induced in the germline of C57BL/6J mice with N‐ethyl–N‐nitrosourea by measuring changes in the performance of repetitive rotarod trials while blinded to genotype. Automated meiotic mapping was used to implicate individual mutations in causation. In total, 32,726 mice bearing all the variant alleles were screened. This was complemented with the simultaneous testing of 1408 normal mice for reference. In total, 16.3% of autosomal genes were thus rendered detectably hypomorphic or nullified by mutations in homozygosity and motor tested in at least three mice. This approach allowed us to identify superperformance mutations in Rif1, Tk1, Fan1 and Mn1. These genes are primarily related, among other less well‐characterized functions, to nucleic acid biology. We also associated distinct motor learning patterns with groups of functionally related genes. These functional sets included, preferentially, histone H3 methyltransferase activity for mice that learnt at an accelerated rate relative to the remaining mutant mice. The results allow for an estimation of the fraction of mutations that can modify a behaviour influential for evolution such as locomotion. They may also enable, once the loci are further validated and the mechanisms elucidated, the harnessing of the activity of the newly identified genes to enhance motor ability or to counterbalance disability or disease. Key points We studied the effect of chemically induced random mutations on mouse motor performance. An array of mutations influenced the rate of motor learning. DNA regulation genes predominated among these mutant loci. Several mutations in unsuspected genes led to superperformance. Assuming little‐biased mutagenicity, the results allow for an estimation of the probability for any spontaneous mutation to influence a behaviour such as motor learning and ultimate performance. figure legend Discovery of mutants with altered motor performance, including motor learning, after random N‐ethyl–N‐nitrosourea (ENU) mutagenesis. Over 30,000 ENU‐mutated and non‐mutant control mice were repetitively subject to a rotarod task over several days to measure motor performance (time to fall off the accelerating rotarod) and learning (rate of decrease in the time to fall over the days that the task was completed). Machine learning analysis of each mouse DNA sequence allowed for the causal attribution of motor changes to genotype. Most mutations degraded motor performance but four mutations, residing in unsuspected genes involved in nucleic acid maintenance, enabled superperformance. In contrast, motor learning at an accelerated rate relative to the remaining mutant mice was associated with mutations in genes involved in histone H3 methyltransferase activity. The results offer a novel perspective that broadly relates genomic regulation to motor performance and learning.
Bibliography:This article was first published as a preprint. Jakkamsetti V, Ma Q, Angulo G, Scudder W, Beutler B, Pascual JM. 2023. Genetic influences on motor learning and superperformance mutants revealed by random mutational survey of mouse locomotion. bioRxiv.
https://doi.org/10.1113/JP285505#support‐information‐section
https://doi.org/10.1101/2023.06.28.546756
The peer review history is available in the Supporting Information section of this article
Handling Editors: Laura Bennet & Michael Joyner
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Conception and design: JMP, BB
Drafting of the manuscript: JMP, BB, VJ
Both at: UT Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390. USA
Acquisition, analysis, and interpretation of data: All authors
All authors approved the final version of the manuscript, agree to be accountable for all aspects of the work regarding the accuracy or integrity of any part of the work and qualify for authorship. All of those who qualify for authorship are listed.
Critical revision of the manuscript for important intellectual content: All authors
Author contributions
ISSN:0022-3751
1469-7793
1469-7793
DOI:10.1113/JP285505