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2. Hierarchical organization of cortical and thalamic connectivity

Author

Harris, Julie A., Mihalas, Stefan, Hirokawa, Karla E., Whitesell, Jennifer D., Choi, Hannah, Bernard, Amy, Bohn, Phillip, Caldejon, Shiella, Casal, Linzy, Cho, Andrew, Feiner, Aaron, Feng, David, Gaudreault, Nathalie, Gerfen, Charles R., Graddis, Nile, Groblewski, Peter A., Henry, Alex M., Ho, Anh, Howard, Robert, Knox, Joseph E., Kuan, Leonard, Kuang, Xiuli, Lecoq, Jerome, Lesnar, Phil, Li, Yaoyao, Luviano, Jennifer, McConoughey, Stephen, Mortrud, Marty T., Naeemi, Maitham, Ng, Lydia, Oh, Seung Wook, Ouellette, Benjamin, Shen, Elise, Sorensen, Staci A., Wakeman, Wayne, Wang, Quanxin, Wang, Yun, Williford, Ali, Phillips, John W., Jones, Allan R., Koch, Christof, and Zeng, Hongkui

Published
2019
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3. Endogenous pathology in tauopathy mice progresses via brain networks

Author

Ramirez, Denise M, primary, Whitesell, Jennifer D, additional, Bhagwat, Nikhil, additional, Thomas, Talitha L, additional, Ajay, Apoorva D, additional, Nawaby, Ariana, additional, Delatour, Benoît, additional, Bay, Sylvie, additional, Lafaye, Pierre, additional, Knox, Joseph E, additional, Harris, Julie A, additional, Meeks, Julian P, additional, and Diamond, Marc I, additional

Published
2023
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6. Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network

Author

Whitesell, Jennifer D., primary, Liska, Adam, additional, Coletta, Ludovico, additional, Hirokawa, Karla E., additional, Bohn, Phillip, additional, Williford, Ali, additional, Groblewski, Peter A., additional, Graddis, Nile, additional, Kuan, Leonard, additional, Knox, Joseph E., additional, Ho, Anh, additional, Wakeman, Wayne, additional, Nicovich, Philip R., additional, Nguyen, Thuc Nghi, additional, van Velthoven, Cindy T.J., additional, Garren, Emma, additional, Fong, Olivia, additional, Naeemi, Maitham, additional, Henry, Alex M., additional, Dee, Nick, additional, Smith, Kimberly A., additional, Levi, Boaz, additional, Feng, David, additional, Ng, Lydia, additional, Tasic, Bosiljka, additional, Zeng, Hongkui, additional, Mihalas, Stefan, additional, Gozzi, Alessandro, additional, and Harris, Julie A., additional

Published
2021
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7. Regional, layer, and cell-class specific connectivity of the mouse default mode network

Author

Whitesell, Jennifer D., primary, Liska, Adam, additional, Coletta, Ludovico, additional, Hirokawa, Karla E., additional, Bohn, Phillip, additional, Williford, Ali, additional, Groblewski, Peter A., additional, Graddis, Nile, additional, Kuan, Leonard, additional, Knox, Joseph E., additional, Ho, Anh, additional, Wakeman, Wayne, additional, Nicovich, Philip R., additional, Nguyen, Thuc Nghi, additional, Garren, Emma, additional, van Velthoven, Cindy T. J., additional, Fong, Olivia, additional, Feng, David, additional, Naeemi, Maitham, additional, Henry, Alex M., additional, Dee, Nick, additional, Smith, Kimberly A., additional, Levi, Boaz P., additional, Ng, Lydia, additional, Tasic, Bosiljka, additional, Zeng, Hongkui, additional, Mihalas, Stefan, additional, Gozzi, Alessandro, additional, and Harris, Julie A., additional

Published
2020
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8. A brain network basis of Fragile X syndrome behavioral penetrance determined by X chromosome inactivation in female mice

Author

Szelenyi, Eric, Fisenne, Danielle, Knox, Joseph E, Harris, Julie A, Gornet, James A, Palaniswamy, Ramesh, Kim, Yongsoo, Venkataraju, Kannan Umadevi, and Osten, Pavel

Abstract

X-chromosome inactivation (XCI) in females is vital for normal brain function and cognition, as many X-linked genetic mutations lead to mental retardation and autism spectrum disorders, such as the fragile X syndrome (FXS). However, the degree by which XCI regulates disease presentation has been poorly investigated. To study this regulation in the mouse, here we quantified the brainwide composition of active-XC cells at single cell resolution using an X-linked MECP2-EGFP allele with known parent-of-origin. We present evidence that whole-brains, including all regions, on average favor maternal XC-active cells by 20%, or 8 million cells. This bias was conserved in heterozygous FXS mutant mice, which also corresponded to disease penetrance in maternal but not paternal FMR1 null mice. To localize the physical source of behavioral penetrance, brain-wide correlational screens successfully mapped mouse performance to cell densities in putative sensorimotor (e.g. sensory hindbrain, thalamus, globus pallidus) and sociability (e.g. visual/entorhinal cortices, bed nucleus stria terminalis, medial preoptic area) behavioral circuits of the open field sensorimotor and 3-chamber sociability assays, respectively. Overall, 50%/50% healthy/mutant cell density ratios in these sub-networks were required for disease presentation in each behavior. These results suggest female X-linked behavioral penetrance of disease is regulated at the distributed level of mutant cell density in behavioral circuits, which is set by XCI that is subject to parent-of-origin effects. This work provides a novel finding behind the broad and varied behavioral phenotypes commonly featured in female patients debilitated by X-linked mental disorders and may offer new entry points for behavioral therapeutics.

Published
2018
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10. Brain X chromosome inactivation is not random and can protect from paternally inherited neurodevelopmental disease

Author

Szelenyi, Eric R., Fisenne, Danielle, Knox, Joseph E., Harris, Julie A., Gornet, James A., Palaniswamy, Ramesh, Kim, Yongsoo, Venkataraju, Kannan Umadevi, Osten, Pavel, Szelenyi, Eric R., Fisenne, Danielle, Knox, Joseph E., Harris, Julie A., Gornet, James A., Palaniswamy, Ramesh, Kim, Yongsoo, Venkataraju, Kannan Umadevi, and Osten, Pavel

Abstract

Non-random (skewed) X chromosome inactivation (XCI) in the female brain can ameliorate X-linked phenotypes, though clinical studies typically consider 80-90% skewing favoring the healthy allele as necessary for this effect. Here we quantify for the first time whole-brain XCI at single-cell resolution and discover a preferential inactivation of paternal to maternal X at ∼60:40 ratio, which surprisingly impacts disease penetrance. In Fragile-X-syndrome mouse model, Fmr1-KO allele transmitted maternally in ∼60% brain cells causes phenotypes, but paternal transmission in ∼40% cells is unexpectedly tolerated. In the affected maternal Fmr1-KO(m)/+ mice, local XCI variability within distinct brain networks further determines sensory versus social manifestations, revealing a stochastic source of X-linked phenotypic diversity. Taken together, our data show that a modest ∼60% bias favoring the healthy allele is sufficient to ameliorate X-linked phenotypic penetrance, suggesting that conclusions of many clinical XCI studies using the 80-90% threshold should be re-evaluated. Furthermore, the paternal origin of the XCI bias points to a novel evolutionary mechanism acting to counter the higher rate of de novo mutations in male germiline. Finally, the brain capacity to tolerate a major genetic lesion in ∼40% cells is also relevant for interpreting other neurodevelopmental genetic conditions, such as brain somatic mosaicism.

Published
2018

11. Whole brain imaging reveals distinct spatial patterns of amyloid beta deposition in three mouse models of Alzheimer's disease

Author

Whitesell, Jennifer D., primary, Buckley, Alex R., additional, Knox, Joseph E., additional, Kuan, Leonard, additional, Graddis, Nile, additional, Pelos, Andrew, additional, Mukora, Alice, additional, Wakeman, Wayne, additional, Bohn, Phillip, additional, Ho, Anh, additional, Hirokawa, Karla E., additional, and Harris, Julie A., additional

Published
2018
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13. The organization of intracortical connections by layer and cell class in the mouse brain

Author

Harris, Julie A., primary, Mihalas, Stefan, additional, Hirokawa, Karla E., additional, Whitesell, Jennifer D., additional, Knox, Joseph E., additional, Bernard, Amy, additional, Bohn, Phillip, additional, Caldejon, Shiella, additional, Casal, Linzy, additional, Cho, Andrew, additional, Feng, David, additional, Gaudreault, Nathalie, additional, Gerfen, Charles R., additional, Graddis, Nile, additional, Groblewski, Peter A., additional, Henry, Alex, additional, Ho, Anh, additional, Howard, Robert, additional, Kuan, Leonard, additional, Lecoq, Jerome, additional, Luviano, Jennifer, additional, McConoghy, Stephen, additional, Mortrud, Marty T., additional, Naeemi, Maitham, additional, Ng, Lydia, additional, Oh, Seung W., additional, Ouellette, Benjamin, additional, Sorensen, Staci A., additional, Wakeman, Wayne, additional, Wang, Quanxin, additional, Williford, Ali, additional, Phillips, John W., additional, Jones, Allan, additional, Koch, Christof, additional, and Zeng, Hongkui, additional

Published
2018
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15. Whole brain imaging reveals distinct spatial patterns of amyloid beta deposition in three mouse models of Alzheimer's disease.

Author

Whitesell, Jennifer D., Buckley, Alex R., Knox, Joseph E., Kuan, Leonard, Graddis, Nile, Pelos, Andrew, Mukora, Alice, Wakeman, Wayne, Bohn, Phillip, Ho, Anh, Hirokawa, Karla E., and Harris, Julie A.

Abstract

A variety of Alzheimer's disease (AD) mouse models overexpress mutant forms of human amyloid precursor protein (APP), producing high levels of amyloid β (Aβ) and forming plaques. However, the degree to which these models mimic spatiotemporal patterns of Aβ deposition in brains of AD patients is unknown. Here, we mapped the spatial distribution of Aβ plaques across age in three APP‐overexpression mouse lines (APP/PS1, Tg2576, and hAPP‐J20) using in vivo labeling with methoxy‐X04, high throughput whole brain imaging, and an automated informatics pipeline. Images were acquired with high resolution serial two‐photon tomography and labeled plaques were detected using custom‐built segmentation algorithms. Image series were registered to the Allen Mouse Brain Common Coordinate Framework, a 3D reference atlas, enabling automated brain‐wide quantification of plaque density, number, and location. In both APP/PS1 and Tg2576 mice, plaques were identified first in isocortex, followed by olfactory, hippocampal, and cortical subplate areas. In hAPP‐J20 mice, plaque density was highest in hippocampal areas, followed by isocortex, with little to no involvement of olfactory or cortical subplate areas. Within the major brain divisions, distinct regions were identified with high (or low) plaque accumulation; for example, the lateral visual area within the isocortex of APP/PS1 mice had relatively higher plaque density compared with other cortical areas, while in hAPP‐J20 mice, plaques were densest in the ventral retrosplenial cortex. In summary, we show how whole brain imaging of amyloid pathology in mice reveals the extent to which a given model recapitulates the regional Aβ deposition patterns described in AD. [ABSTRACT FROM AUTHOR]

Published
2019
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19. Endogenous pathology in tauopathy mice progresses via brain networks.

Author

Ramirez DMO, Whitesell JD, Bhagwat N, Thomas TL, Ajay AD, Nawaby A, Delatour B, Bay S, LaFaye P, Knox JE, Harris JA, Meeks JP, and Diamond MI

Abstract

Neurodegenerative tauopathies are hypothesized to propagate via brain networks. This is uncertain because we have lacked precise network resolution of pathology. We therefore developed whole-brain staining methods with anti-p-tau nanobodies and imaged in 3D PS19 tauopathy mice, which have pan-neuronal expression of full-length human tau containing the P301S mutation. We analyzed patterns of p-tau deposition across established brain networks at multiple ages, testing the relationship between structural connectivity and patterns of progressive pathology. We identified core regions with early tau deposition, and used network propagation modeling to determine the link between tau pathology and connectivity strength. We discovered a bias towards retrograde network-based propagation of tau. This novel approach establishes a fundamental role for brain networks in tau propagation, with implications for human disease., Competing Interests: Competing interests: Authors declare that they have no competing interests.

Published
2023
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20. High-resolution data-driven model of the mouse connectome.

Author

Knox JE, Harris KD, Graddis N, Whitesell JD, Zeng H, Harris JA, Shea-Brown E, and Mihalas S

Abstract

Knowledge of mesoscopic brain connectivity is important for understanding inter- and intraregion information processing. Models of structural connectivity are typically constructed and analyzed with the assumption that regions are homogeneous. We instead use the Allen Mouse Brain Connectivity Atlas to construct a model of whole-brain connectivity at the scale of 100 μm voxels. The data consist of 428 anterograde tracing experiments in wild type C57BL/6J mice, mapping fluorescently labeled neuronal projections brain-wide. Inferring spatial connectivity with this dataset is underdetermined, since the approximately 2 × 10 5 source voxels outnumber the number of experiments. To address this issue, we assume that connection patterns and strengths vary smoothly across major brain divisions. We model the connectivity at each voxel as a radial basis kernel-weighted average of the projection patterns of nearby injections. The voxel model outperforms a previous regional model in predicting held-out experiments and compared with a human-curated dataset. This voxel-scale model of the mouse connectome permits researchers to extend their previous analyses of structural connectivity to much higher levels of resolution, and it allows for comparison with functional imaging and other datasets., Competing Interests: Competing Interests: The authors have declared that no competing interests exist.

Published
2018
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