@article{9c16d22b3d574b61ae78cc567d1df3bc,
title = "Noncanonical genomic imprinting in the monoamine system determines naturalistic foraging and brain-adrenal axis functions",
abstract = "Noncanonical genomic imprinting can cause biased expression of one parental allele in a tissue; however, the functional relevance of such biases is unclear. To investigate ethological roles for noncanonical imprinting in dopa decarboxylase (Ddc) and tyrosine hydroxylase (Th), we use machine learning to decompose naturalistic foraging in maternal and paternal allele mutant heterozygous mice. We uncover distinct roles for the maternal versus paternal alleles on foraging, where maternal alleles affect sons while daughters are under paternal allelic control. Each parental allele controls specific action sequences reflecting decisions in naive or familiar contexts. The maternal Ddc allele is preferentially expressed in subsets of hypothalamic GABAergic neurons, while the paternal allele predominates in subsets of adrenal cells. Each Ddc allele affects distinct molecular and endocrine components of the brain-adrenal axis. Thus, monoaminergic noncanonical imprinting has ethological roles in foraging and endocrine functions and operates by affecting discrete subsets of cells.",
keywords = "adrenaline, decision making, dopa decarboxylase, epigenetics, foraging, genomic imprinting, hypothalamic-pituitary-adrenal axis, machine learning, monoamine, tyrosine hydroxylase",
author = "Bonthuis, {Paul J.} and Susan Steinwand and {Stacher H{\"o}rndli}, {Cornelia N.} and Jared Emery and Huang, {Wei Chao} and Stephanie Kravitz and Elliott Ferris and Christopher Gregg",
note = "The statistical methodology in the study was supervised and developed by statisticians, including Drs. Greg Stoddard and Alun Thomas, in the University of Utah Biostatistics Core Facility. We thank Drs. Dimitri Tr{\"a}nkner, Adrian Rothenfluh, Monica Vetter, Richard Dorsky, and Jan Christian and members of the C.G. lab for their critical reading of the manuscript and input on the study. We thank Dr. Channabasavaiah B. Gurumurthy and Rolen M. Quadros (University of Nebraska Medical Center) for help generating the Ddc allelic knockin reporter lines. This work was supported by funding from the National Institutes of Health ( R01AG064013 , R21MH120468 , R01MH109577 , and R21MH118570 grants to C.G.) and a K99 award to P.J.B. ( K99MH111912 ). The statistical methodology in the study was supervised and developed by statisticians, including Drs. Greg Stoddard and Alun Thomas, in the University of Utah Biostatistics Core Facility. We thank Drs. Dimitri Tr{\"a}nkner, Adrian Rothenfluh, Monica Vetter, Richard Dorsky, and Jan Christian and members of the C.G. lab for their critical reading of the manuscript and input on the study. We thank Dr. Channabasavaiah B. Gurumurthy and Rolen M. Quadros (University of Nebraska Medical Center) for help generating the Ddc allelic knockin reporter lines. This work was supported by funding from the National Institutes of Health (R01AG064013, R21MH120468, R01MH109577, and R21MH118570 grants to C.G.) and a K99 award to P.J.B. (K99MH111912). S.S. and P.J.B. performed the behavior studies; C.N.S.H. J.E. P.J.B. S.S. and C.G. analyzed the behavior data; P.J.B. and S.S. performed studies of Ddc allelic reporter mice; S.S. W.-C.H. E.F. S.K. and C.G. performed the genomics studies; S.S. performed the ELISA studies; C.G. P.J.B. S.S. and C.N.S.H. wrote the manuscript with input from all of the authors. C.G. is a co-founder of and has equity in Storyline Health, Inc. which uses artificial intelligence to build scalable research, behavior analysis, and clinical tools for precision medicine.",
year = "2022",
month = mar,
day = "8",
doi = "10.1016/j.celrep.2022.110500",
language = "English (US)",
volume = "38",
journal = "Cell Reports",
issn = "2211-1247",
publisher = "Cell Press",
number = "10",
}