High-resolution prediction of mouse brain connectivity using gene expression patterns

Fakhry, Ahmed; Ji, Shuiwang

doi:10.1016/j.ymeth.2014.07.011

Cited by 31 publications

(28 citation statements)

References 15 publications

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“…Continued research regarding the mechanisms by which ALL and chemotherapy disrupt connectome topology and cognitive function could help identify interventions that will protect against these neurotoxicities without reducing the anticancer efficacy of treatment regimens. Small-world connectomes are highly associated with gene expression networks and also appear to be preserved across species (Calabrese et al, 2015;Fakhry and Ji, 2015). Thus, connectome studies potentially provide unique translational opportunities to identify intervention targets for ALL-related cognitive impairment.…”

Section: Resultsmentioning

confidence: 99%

Atypical Structural Connectome Organization and Cognitive Impairment in Young Survivors of Acute Lymphoblastic Leukemia

et al. 2016

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Survivors of pediatric acute lymphoblastic leukemia (ALL) are at increased risk for cognitive impairments that disrupt everyday functioning and decrease quality of life. The specific biological mechanisms underlying cognitive impairment following ALL remain largely unclear, but previous studies consistently demonstrate significant white matter pathology. We aimed to extend this literature by examining the organization of the white matter connectome in young patients with a history of ALL treated with chemotherapy only. We applied graph theoretical analysis to diffusion tensor imaging obtained from 31 survivors of ALL age 5-19 years and 39 matched healthy controls. Results indicated significantly lower small-worldness ( p = 0.007) and network clustering coefficient ( p = 0.019), as well as greater cognitive impairment ( p = 0.027) in the ALL group. Regional analysis indicated that clustered connectivity in parietal, frontal, hippocampal, amygdalar, thalamic, and occipital regions was altered in the ALL group. Random forest analysis revealed a model of connectome and demographic variables that could automatically classify survivors of ALL as having cognitive impairment or not (accuracy = 0.89, p < 0.0001). These findings provide further evidence of brain injury in young survivors of ALL, even those without a history of central nervous system (CNS) disease or cranial radiation. Efficiency of local information processing, reorganization of hub connectivity, and cognitive reserve may contribute to cognitive outcome in these children. Certain connectome properties showed U-shaped relationships with cognitive impairment suggesting an optimal range of regional connectivity.

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Section: Resultsmentioning

confidence: 99%

Atypical Structural Connectome Organization and Cognitive Impairment in Young Survivors of Acute Lymphoblastic Leukemia

et al. 2016

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“…For both reciprocal and unidirectional connections, correlated gene expression is driven by the same types of functional gene groups, pointing to a uniform transcriptional profile of connectivity that increases with connection reciprocity. Similar functional categories of genes related to the development of neurons, neurites, and synapses, as well as the regulation of neuronal activity and synaptic plasticity, contribute to predicting the presence of a connection between neurons in Caenorhabditis elegans (15,16) and larger-scale neuronal populations of the rat (17) and mouse brains (18,19). The consistency of these findings across species, datasets, and analysis methods points to a robust transcriptional signature of neuronal connectivity characterized by the coordinated expression of genes involved in the development and ongoing function of neuronal networks.…”

Section: Discussionmentioning

confidence: 99%

“…This conservation suggests that hub connectivity may be under tight genetic control. Growing evidence indicates that gene expression affects neuronal connectivity, with studies of worm, rat, and mouse nervous systems showing that the transcriptional profile of an individual neuron or neuronal population can predict its connectivity to other areas with greater than chance accuracy (15)(16)(17)(18)(19). Brain regions with similar transcriptional profiles display similar connectivity profiles (20,21), and gene expression profiles are more correlated between pairs of structurally connected brain regions in the mouse/rat (20) and within functionally coupled networks of the human cortex (22).…”

mentioning

confidence: 99%

A transcriptional signature of hub connectivity in the mouse connectome

Fulcher

Fornito

2016

Proc. Natl. Acad. Sci. U.S.A.

223

310

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Connectivity is not distributed evenly throughout the brain. Instead, it is concentrated on a small number of highly connected neural elements that act as network hubs. Across different species and measurement scales, these hubs show dense interconnectivity, forming a core or "rich club" that integrates information across anatomically distributed neural systems. Here, we show that projections between connectivity hubs of the mouse brain are both central (i.e., they play an important role in neural communication) and costly (i.e., they extend over long anatomical distances) aspects of network organization that carry a distinctive genetic signature. Analyzing the neuronal connectivity of 213 brain regions and the transcriptional coupling, across 17,642 genes, between each pair of regions, we find that coupling is highest for pairs of connected hubs, intermediate for links between hubs and nonhubs, and lowest for connected pairs of nonhubs. The high transcriptional coupling associated with hub connectivity is driven by genes regulating the oxidative synthesis and metabolism of ATP-the primary energetic currency of neuronal communication. This genetic signature contrasts that identified for neuronal connectivity in general, which is driven by genes regulating neuronal, synaptic, and axonal structure and function. Our findings establish a direct link between molecular function and the large-scale topology of neuronal connectivity, showing that brain hubs display a tight coordination of gene expression, often over long anatomical distances, that is intimately related to the metabolic requirements of these highly active network elements.connectome | complex networks | hub | rich club | metabolism C ertain neural elements possess an unusually high degree of connectivity, designating them as putative network hubs (1). Analyses of microscale, mesoscale, and macroscale connectomes of multiple species, constructed using a variety of methods, indicate that these hubs are strongly interconnected with each other, forming a so-called "rich club" of connectivity that mediates a large fraction of communication traffic in the brain and supports the efficient integration of otherwise segregated neural systems (2-8).Hub connectivity is functionally advantageous, but it is also costly. Hub regions make more connections with other areas, and these connections often extend over long anatomical distances, thus requiring greater physical space, cellular material, and metabolic resources (3, 9). Accordingly, human neuroimaging studies have indicated that topologically central hub regions have a higher energetic demand than other brain areas (9-12), which may render them particularly vulnerable to the effects of damage or disease (10, 13). This hypothesis is supported by evidence that pathology in a broad range of disorders preferentially accumulates within highly connected brain regions (14).Hub connectivity is thus a topologically central and costly aspect of brain network organization that is conserved across species and spatial scales....

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“…We next set out to test whether gene expression could be used to predict connectivity (Fakhry and Ji, 2015;Fornito et al, 2019). We hypothesized that even though the patterns of gene expression that established wiring during development might have vanished at the time point we were examining, correlates of those patterns might persist into adulthood.…”

Section: Connectivity Determined By Bricseq Could Be Predicted By Lowmentioning

confidence: 99%

BRICseq bridges brain-wide interregional connectivity to neural activity and gene expression in single animals

Huang

Fürth

Musall

et al. 2018

Preprint

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Comprehensive analysis of neuronal networks requires brain-wide measurement of connectivity, activity, and gene expression. Although high-throughput methods are available for mapping brain-wide activity and transcriptomes, comparable methods for mapping region-to-region connectivity remain slow and expensive because they require averaging across hundreds of brains. Here we describe BRICseq, which leverages DNA barcoding and sequencing to map connectivity from single individuals in a few weeks and at low cost. Applying BRICseq to the mouse neocortex, we find that region-to-region connectivity provides a simple bridge relating transcriptome to activity: The spatial expression patterns of a few genes predict region-to-region connectivity, and connectivity predicts activity correlations. We also exploited BRICseq to map the mutant BTBR mouse brain, which lacks a corpus callosum, and recapitulated its known connectopathies. BRICseq allows individual laboratories to compare how age, sex, environment, genetics and species affect neuronal wiring, and to integrate these with functional activity and gene expression.

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High-resolution prediction of mouse brain connectivity using gene expression patterns

Cited by 31 publications

References 15 publications

Atypical Structural Connectome Organization and Cognitive Impairment in Young Survivors of Acute Lymphoblastic Leukemia

Atypical Structural Connectome Organization and Cognitive Impairment in Young Survivors of Acute Lymphoblastic Leukemia

A transcriptional signature of hub connectivity in the mouse connectome

BRICseq bridges brain-wide interregional connectivity to neural activity and gene expression in single animals

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