158 research outputs found
Single genomic enhancers drive experience-dependent GABAergic plasticity to maintain sensory processing in the adult cortex
Experience-dependent plasticity of synapses modulates information processing in neural circuits and is essential for cognitive functions. The genome, via non-coding enhancers, was proposed to control information processing and circuit plasticity by regulating experience-induced transcription of genes that modulate specific sets of synapses. To test this idea, we analyze here the cellular and circuit functions of the genomic mechanisms that control the experience-induced transcription of Igf1 (insulin-like growth factor 1) in vasoactive intestinal peptide (VIP) interneurons (INs) in the visual cortex of adult mice. We find that two sensory-induced enhancers selectively and cooperatively drive the activity-induced transcription of Igf1 to thereby promote GABAergic inputs onto VIP INs and to homeostatically control the ratio between excitation and inhibition (E/I ratio)-in turn, this restricts neural activity in VIP INs and principal excitatory neurons and maintains spatial frequency tuning. Thus, enhancer-mediated activity-induced transcription maintains sensory processing in the adult cortex via homeostatic modulation of E/I ratio
The chromatin remodeling enzyme Chd4 regulates genome architecture in the mouse brain
The mechanisms underlying gene regulation and genome architecture remain poorly understood. Here, the authors investigate the role of chromatin remodelling enzyme Chd4 in granule neurons of the mouse cerebellum and find that conditional knockout of Chd4 preferentially activates enhancers and modulates genome architecture at a genome-wide level
Characterizing axonal myelination within the healthy population: a tract-by-tract mapping of effects of age and gender on the fiber g-ratio
: The g-ratio, equal to the ratio of the inner-to-outer diameter of a myelinated axon, is associated with the speed of conduction, and thus reflects axonal function and integrity. It is now possible to estimate an "aggregate" g-ratio in vivo using MRI. The aim of this study was to assess the variation of the MRI-derived fiber g-ratio in the brain of healthy individuals, and to characterize its variation across the lifespan. Thirty-eight healthy participants, aged between 20 and 76, were recruited. Whole-brain g-ratio maps were computed and analyzed voxel-wise. Median tract g-ratio values were also extracted. No significant effect of gender was found, whereas age was found to be significantly associated with the g-ratio within the white matter. The tract-specific analysis showed this relationship to follow a nearly-linear increase, although the slope appears to slow down slightly after the 6th decade of life. The most likely interpretation is a subtle but consistent reduction in myelin throughout adulthood, with the density of axons beginning to decrease between the 4th and 5th decade
LONGO: An R package for interactive gene length dependent analysis for neuronal identity
Motivation: Reprogramming somatic cells into neurons holds great promise to model neuronal development and disease. The efficiency and success rate of neuronal reprogramming, however, may vary between different conversion platforms and cell types, thereby necessitating an unbiased, systematic approach to estimate neuronal identity of converted cells. Recent studies have demonstrated that long genes (\u3e100 kb from transcription start to end) are highly enriched in neurons, which provides an opportunity to identify neurons based on the expression of these long genes.
Results: We have developed a versatile R package, LONGO, to analyze gene expression based on gene length. We propose a systematic analysis of long gene expression (LGE) with a metric termed the long gene quotient (LQ) that quantifies LGE in RNA-seq or microarray data to validate neuronal identity at the single-cell and population levels. This unique feature of neurons provides an opportunity to utilize measurements of LGE in transcriptome data to quickly and easily distinguish neurons from non-neuronal cells. By combining this conceptual advancement and statistical tool in a user-friendly and interactive software package, we intend to encourage and simplify further investigation into LGE, particularly as it applies to validating and improving neuronal differentiation and reprogramming methodologies.
Availability and implementation: LONGO is freely available for download at https://github.com/biohpc/longo.
Supplementary information: Supplementary data are available at Bioinformatics online
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Small RNA pathway genes identified by patterns of phylogenetic conservation and divergence
Genetic and biochemical analyses of RNA interference (RNAi) and microRNA (miRNA) pathways have revealed proteins such as Argonaute/PIWI and Dicer that process and present small RNAs to their targets. Well validated small RNA pathway cofactors, such as the Argonaute/PIWI proteins show distinctive patterns of conservation or divergence in particular animal, plant, fungal, and protist species. We compared 86 divergent eukaryotic genome sequences to discern sets of proteins that show similar phylogenetic profiles with known small RNA cofactors. A large set of additional candidate small RNA cofactors have emerged from functional genomic screens for defects in miRNA- or siRNA-mediated repression in C. elegans and D. melanogaster1,2 and from proteomic analyses of proteins co-purifying with validated small RNA pathway proteins3,4. The phylogenetic profiles of many of these candidate small RNA pathway proteins are similar to those of known small RNA cofactor proteins. We used a Bayesian approach to integrate the phylogenetic profile analysis with predictions from diverse transcriptional coregulation and proteome interaction datasets to assign a probability for each protein for a role in a small RNA pathway. Testing high-confidence candidates from this analysis for defects in RNAi silencing, we found that about half of the predicted small RNA cofactors are required for RNAi silencing. Many of the newly identified small RNA pathway proteins are orthologues of proteins implicated in RNA splicing. In support of a deep connection between the mechanism of RNA splicing and small RNA-mediated gene silencing, the presence of the Argonaute proteins and other small RNA components in the many species analysed strongly correlates with the number of introns in that species
Promoting understanding of chemical representations: Students' use of a visualization tool in the classroom
Many students have difficulty learning symbolic and molecular representations of chemistry. This study investigated how students developed an understanding of chemical representations with the aid of a computer-based visualizing tool, eChem, that allowed them to build molecular models and view multiple representations simultaneously. Multiple sources of data were collected with the participation of 71 eleventh graders at a small public high school over a 6-week period. The results of pre- and posttests showed that students' understanding of chemical representations improved substantially ( p  < .001, effect size = 2.68-. The analysis of video recordings revealed that several features in eChem helped students construct models and translate representations. Students who were highly engaged in discussions while using eChem made referential linkages between visual and conceptual aspects of representations. This in turn may have deepened their understanding of chemical representations and concepts. The findings also suggest that computerized models can serve as a vehicle for students to generate mental images. Finally, students demonstrated their preferences of certain types of representations and did not use all types of three-dimensional models interchangeably. © 2001 John Wiley & Sons, Inc. J Res Sci Teach 38: 821–842, 2001Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34515/1/1033_ftp.pd
CHARGE syndrome protein CHD7 regulates epigenomic activation of enhancers in granule cell precursors and gyrification of the cerebellum
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Disruption of DNA methylation-dependent long gene repression in Rett syndrome
Disruption of the MECP2 gene leads to Rett syndrome (RTT), a severe neurological disorder with features of autism1. MECP2 encodes a methyl-DNA-binding protein2 that has been proposed to function as a transcriptional repressor, but despite numerous studies examining neuronal gene expression in Mecp2 mutants, no clear model has emerged for how MeCP2 regulates transcription3–9. Here we identify a genome-wide length-dependent increase in gene expression in MeCP2 mutant mouse models and human RTT brains. We present evidence that MeCP2 represses gene expression by binding to methylated CA sites within long genes, and that in neurons lacking MeCP2, decreasing the expression of long genes attenuates RTT-associated cellular deficits. In addition, we find that long genes as a population are enriched for neuronal functions and selectively expressed in the brain. These findings suggest that mutations in MeCP2 may cause neurological dysfunction by specifically disrupting long gene expression in the brain
Developing a new teaching approach for the chemical bonding concept aligned with current scientific and pedagogical knowledge
The traditional pedagogical approach for teaching chemical bonding is often overly simplistic and not aligned with the most up-to-date scientific models. As a result, high-school students around the world lack fundamental understanding of chemical bonding. In order to improve students' understanding of this concept, it was essential to propose a systemic treatment, namely, revising the scientific content, the pedagogical approach, and the assessment methods regarding this concept. Therefore, the main goal of this study was to build a conceptual framework that provides an advanced scientific and pedagogical foundation regarding the chemical bonding concept—one that will guide chemistry curriculum developers as well. A conceptual framework for a new teaching approach was constructed with lead-chemistry teachers, science (chemistry) educators, and research chemists. We suggest that chemical bonding should be taught based on elemental principles and by using the idea of a continuum of bond strengths. Our process includes the formulation of learning goals aligned with current scientific knowledge. Moreover, we suggest that constructing assessment tasks on carefully specified learning goals, which are described in terms of learning performances , may enable educators to foster and examine much deeper levels of students' understanding. © 2007 Wiley Periodicals, Inc. Sci Ed 91: 579–603, 2007Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56057/1/20201_ftp.pd
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