scholarly journals Standardizing workflows in imaging transcriptomics with the abagen toolbox

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Ross D Markello ◽  
Aurina Arnatkevičiūtė ◽  
Jean-Baptiste Poline ◽  
Ben D Fulcher ◽  
Alex Fornito ◽  
...  
Keyword(s):  
Gene Expression ◽  
Open Access ◽  
Human Brain ◽  
Brain Atlas ◽  
Systematic Research ◽  
Gene Normalization ◽  
Statistical Inferences ◽  
Research Findings ◽  
Processing Steps

Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack of standardization across research groups has given rise to myriad processing pipelines for using these data. Here, we develop the abagen toolbox, an open-access software package for working with transcriptomic data, and use it to examine how methodological variability influences the outcomes of research using the Allen Human Brain Atlas. Applying three prototypical analyses to the outputs of 750,000 unique processing pipelines, we find that choice of pipeline has a large impact on research findings, with parameters commonly varied in the literature influencing correlations between derived gene expression and other imaging phenotypes by as much as p ≥ 1:0. Our results further reveal an ordering of parameter importance, with processing steps that influence gene normalization yielding the greatest impact on downstream statistical inferences and conclusions. The presented work and the development of the abagen toolbox lay the foundation for more standardized and systematic research in imaging transcriptomics, and will help to advance future understanding of the influence of gene expression in the human brain.

scholarly journals Standardizing workflows in imaging transcriptomics with the abagen toolbox

2021 ◽  
Author(s):  
Ross Markello ◽  
Aurina Arnatkeviciute ◽  
Jean-Baptiste Poline ◽  
Ben D. Fulcher ◽  
Alex Fornito ◽  
...  
Keyword(s):  
Gene Expression ◽  
Open Access ◽  
Human Brain ◽  
Brain Atlas ◽  
Systematic Research ◽  
Gene Normalization ◽  
Statistical Inferences ◽  
Research Findings ◽  
Processing Steps

Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack of standardization across research groups has given rise to myriad processing pipelines for using these data. Here, we develop the abagen toolbox, an open-access software package for working with transcriptomic data, and use it to examine how methodological variability influences the outcomes of research using the Allen Human Brain Atlas. Applying three prototypical analyses to the outputs of 750,000 unique processing pipelines, we find that choice of pipeline has a large impact on research findings, with parameters commonly varied in the literature influencing correlations between derived gene expression and other imaging phenotypes by as much as ρ ≥ 1.0. Our results further reveal an ordering of parameter importance, with processing steps that influence gene normalization yielding the greatest impact on downstream statistical inferences and conclusions. The presented work and the development of the abagen toolbox lay the foundation for more standardized and systematic research in imaging transcriptomics, and will help to advance future understanding of the influence of gene expression in the human brain.

scholarly journals Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain

2014 ◽  
pp. 154-161 ◽  
Author(s):  
Julio Cesar Montoya ◽  
Dianora Fajardo ◽  
Ángela Peña ◽  
Adalberto Sánchez ◽  
Martha C Domínguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Down Syndrome ◽  
Human Brain ◽  
Critical Region ◽  
Expression Profiles ◽  
Brain Atlas ◽  
Normal Human Brain ◽  
Normal Human ◽  
The Brain ◽  
Brain Homeostasis

Background: The information of gene expression obtained from databases, have made possible the extraction and analysis of data related with several molecular processes involving not only in brain homeostasis but its disruption in some neuropathologies; principally in Down syndrome and the Alzheimer disease. Objective: To correlate the levels of transcription of 19 genes located in the Down Syndrome Critical Region (DSCR) with their expression in several substructures of normal human brain. Methods: There were obtained expression profiles of 19 DSCR genes in 42 brain substructures, from gene expression values available at the database of the human brain of the Brain Atlas of the Allen Institute for Brain Sciences", (http://human.brain-map.org/). The co-expression patterns of DSCR genes in brain were calculated by using multivariate statistical methods. Results: Highest levels of gene expression were registered at caudate nucleus, nucleus accumbens and putamen among central areas of cerebral cortex. Increased expression levels of RCAN1 that encode by a protein involved in signal transduction process of the CNS were recorded for PCP4 that participates in the binding to calmodulin and TTC3; a protein that is associated with differentiation of neurons. That previously idenjpgied brain structures play a crucial role in the learning process, in different class of memory and in motor skills. Conclusion: The precise regulation of DSCR gene expression is crucial to maintain the brain homeostasis, especially in those areas with high levels of gene expression associated with a remarkable process of learning and cognition.

P.1.i.034 Gene expression and protein distribution of serotonergic key proteins in the human brain revealed by PET in vivo and postmortem quantification

2015 ◽  
Vol 25 ◽  
pp. S319-S320
Author(s):  
A. Komorowski ◽  
G. Gryglewski ◽  
G. James ◽  
M. Hienert ◽  
S. Kasper ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Protein Distribution

scholarly journals Genetically defined cellular correlates of the baseline brain MRI signal

2018 ◽  
Vol 115 (41) ◽  
pp. E9727-E9736 ◽  
Author(s):  
Jie Wen ◽  
Manu S. Goyal ◽  
Serguei V. Astafiev ◽  
Marcus E. Raichle ◽  
Dmitriy A. Yablonskiy
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Brain Activity ◽  
Brain Mri ◽  
Blood Oxygenation ◽  
Brain Atlas ◽  
Functional Connections ◽  
Fmri Signal ◽  
Useful Signal

fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.

New brain atlas—Mapping the human brain in vivo with 7.0 T MRI and comparison with postmortem histology: Will these images change modern medicine?

2008 ◽  
Vol 18 (1) ◽  
pp. 2-8 ◽  
Author(s):  
Zang-Hee Cho ◽  
Young-Bo Kim ◽  
Jae-Yong Han ◽  
Hoon-Ki Min ◽  
Kyoung-Nam Kim ◽  
...  
Keyword(s):  
Human Brain ◽  
Modern Medicine ◽  
Brain Atlas

scholarly journals Imaging transcriptomics: Convergent cellular, transcriptomic, and molecular neuroimaging signatures in the healthy adult human brain

2021 ◽  
Author(s):  
Daniel Martins ◽  
Alessio Giacomel ◽  
Steven CR Williams ◽  
Federico E Turkheimer ◽  
Ottavia Dipasquale ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Regional Distribution ◽  
Partial Least Square ◽  
Least Square ◽  
Synaptic Proteins ◽  
Brain Atlas ◽  
Wide Range ◽  
Neuroimaging Data ◽  
The Brain

The expansion of neuroimaging techniques over the last decades has opened a wide range of new possibilities to characterize brain dysfunction in several neurological and psychiatric disorders. However, the lack of specificity of most of these techniques, such as magnetic resonance imaging (MRI)-derived measures, to the underlying molecular and cellular properties of the brain tissue poses limitations to the amount of information one can extract to inform precise models of brain disease. The integration of transcriptomic and neuroimaging data, known as 'imaging transcriptomics', has recently emerged as an indirect way forward to test and/or generate hypotheses about potential cellular and transcriptomic pathways that might underly specific changes in neuroimaging MRI biomarkers. However, the validity of this approach is yet to be examined in-depth. Here, we sought to bridge this gap by performing imaging transcriptomic analyses of the regional distribution of well-known molecular markers, assessed by positron emission tomography (PET), in the healthy human brain. We focused on tracers spanning different elements of the biology of the brain, including neuroreceptors, synaptic proteins, metabolism, and glia. Using transcriptome-wide data from the Allen Brain Atlas, we applied partial least square regression to rank genes according to their level of spatial alignment with the regional distribution of these neuroimaging markers in the brain. Then, we performed gene set enrichment analyses to explore the enrichment for specific biological and cell-type pathways among the genes most strongly associated with each neuroimaging marker. Overall, our findings show that imaging transcriptomics can recover plausible transcriptomic and cellular correlates of the regional distribution of benchmark molecular imaging markers, independently of the type of parcellation used to map gene expression and neuroimaging data. Our data support the plausibility and robustness of imaging transcriptomics as an indirect approach for bridging gene expression, cells and macroscopical neuroimaging and improving our understanding of the biological pathways underlying regional variability in neuroimaging features

scholarly journals Divergent connectomic organization delineates genetic evolutionary traits in the human brain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elisenda Bueichekú ◽  
Jose M. Gonzalez-de-Echavarri ◽  
Laura Ortiz-Teran ◽  
Victor Montal ◽  
Federico d’Oleire Uquillas ◽  
...  
Keyword(s):  
Human Brain ◽  
Information Flow ◽  
Brain Function ◽  
Homo Sapiens ◽  
Biological Data ◽  
Brain Atlas ◽  
Cellular Functions ◽  
The Relationship ◽  
Brain Connectomics

AbstractThe relationship between human brain connectomics and genetic evolutionary traits remains elusive due to the inherent challenges in combining complex associations within cerebral tissue. In this study, insights are provided about the relationship between connectomics, gene expression and divergent evolutionary pathways from non-human primates to humans. Using in vivo human brain resting-state data, we detected two co-existing idiosyncratic functional systems: the segregation network, in charge of module specialization, and the integration network, responsible for information flow. Their topology was approximated to whole-brain genetic expression (Allen Human Brain Atlas) and the co-localization patterns yielded that neuron communication functionalities—linked to Neuron Projection—were overrepresented cell traits. Homologue-orthologue comparisons using dN/dS-ratios bridged the gap between neurogenetic outcomes and biological data, summarizing the known evolutionary divergent pathways within the Homo Sapiens lineage. Evidence suggests that a crosstalk between functional specialization and information flow reflects putative biological qualities of brain architecture, such as neurite cellular functions like axonal or dendrite processes, hypothesized to have been selectively conserved in the species through positive selection. These findings expand our understanding of human brain function and unveil aspects of our cognitive trajectory in relation to our simian ancestors previously left unexplored.

scholarly journals Widespread correlation of KRAB zinc finger protein binding with brain-developmental gene expression patterns

2020 ◽  
Vol 375 (1795) ◽  
pp. 20190333 ◽  
Author(s):  
Grace Farmiloe ◽  
Gerrald A. Lodewijk ◽  
Stijn F. Robben ◽  
Elisabeth J. van Bree ◽  
Frank M. J. Jacobs
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Human Brain ◽  
Zinc Finger ◽  
Zinc Finger Protein ◽  
Expression Patterns ◽  
Repetitive Sequences ◽  
Brain Atlas ◽  
Gene Promoters ◽  
The Impact

The large family of KRAB zinc finger (KZNF) genes are transcription factors implicated in recognizing and repressing repetitive sequences such as transposable elements (TEs) in our genome. Through successive waves of retrotransposition-mediated insertions, various classes of TEs have invaded mammalian genomes at multiple timepoints throughout evolution. Even though most of the TE classes in our genome lost the capability to retrotranspose millions of years ago, it remains elusive why the KZNFs that evolved to repress them are still retained in our genome. One hypothesis is that KZNFs become repurposed for other regulatory roles. Here, we find evidence that evolutionary changes in KZNFs provide them not only with the ability to repress TEs, but also to bind to gene promoters independent of TEs. Using KZNF binding site data in conjunction with gene expression values from the Allen Brain Atlas, we show that KZNFs have the ability to regulate gene expression in the human brain in a region-specific manner. Our analysis shows that the expression of KZNFs shows correlation with the expression of their target genes, suggesting that KZNFs have a direct influence on gene expression in the developing human brain. The extent of this regulation and the impact it has on primate brain evolution are still to be determined, but our results imply that KZNFs have become widely integrated into neuronal gene regulatory networks. Our analysis predicts that gene expression networks have been repeatedly innovated throughout primate evolution, continuously gaining new layers of gene regulation mediated by both TEs and KZNFs in our genome. This article is part of a discussion meeting issue ‘Crossroads between transposons and gene regulation’.

scholarly journals Task-independent acute effects of delta-9-tetrahydrocannabinol on human brain function and its relationship with cannabinoid receptor gene expression: a neuroimaging meta-regression analysis

2021 ◽  
Author(s):  
Brandon Gunasekera ◽  
Cathy Davies ◽  
Grace Blest-Hopley ◽  
Mattia Veronese ◽  
Nick F Ramsey ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Repeated Measures ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Brain Atlas ◽  
Angular Gyrus ◽  
Protein Distribution ◽  
Middle Temporal ◽  
Repeated Measures Design

Background: The neurobiological mechanisms underlying the effects of delta-9-tetrahydrocannabinol (THC) remain unclear. Here, we examined the spatial acute effect of THC on human on regional brain activation or blood flow (hereafter called 'activation signal') in a 'core' network of brain regions that subserve a multitude of processes. We also investigated whether the neuromodulatory effects of THC are related to the local expression of its key molecular target, cannabinoid-type-1 (CB1R) but not type-2 (CB2R) receptor. Methods: A systematic search was conducted of acute THC-challenge studies using fMRI, PET, and arterial spin labelling in accordance with established guidelines. Using pooled summary data from 372 participants, tested using a within-subject repeated measures design under experimental conditions, we investigated the effects of a single dose (6-42mg) of THC, compared to placebo, on brain signal. Findings: As predicted, THC augmented the activation signal, relative to placebo, in the anterior cingulate, superior frontal cortices, middle temporal and middle and inferior occipital gyri, striatum, amygdala, thalamus, and cerebellum crus II and attenuated it in the middle temporal gyrus (spatially distinct from the cluster with THC-induced increase in activation signal), superior temporal gyrus, angular gyrus, precuneus, cuneus, inferior parietal lobule, and the cerebellum lobule IV/V. Using post-mortem gene expression data from an independent cohort from the Allen Human Brain atlas, we found a direct relationship between the magnitude of THC-induced brain signal change, indexed using pooled effect-size estimates, and CB1R gene expression, a proxy measure of CB1R protein distribution, but not CB2R expression. A dose-response relationship was observed with THC dose in certain brain regions. Interpretation: These meta-analytic findings shed new light on the localisation of the effects of THC in the human brain, suggesting that THC has neuromodulatory effects in regions central to many cognitive tasks and processes, with greater effects in regions with higher levels of CB1R expression.

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