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Open AccessJournal ArticleDOI

A multiregional proteomic survey of the postnatal human brain.

TLDR
An in-depth proteomic survey of regions of the postnatal human brain, ranging in age from early infancy to adulthood, revealed varied patterns of protein–RNA relationships, with generally increased magnitudes of protein abundance differences between brain regions compared to RNA.
Abstract
Detailed observations of transcriptional, translational and post-translational events in the human brain are essential to improving our understanding of its development, function and vulnerability to disease. Here, we exploited label-free quantitative tandem mass-spectrometry to create an in-depth proteomic survey of regions of the postnatal human brain, ranging in age from early infancy to adulthood. Integration of protein data with existing matched whole-transcriptome sequencing (RNA-seq) from the BrainSpan project revealed varied patterns of protein-RNA relationships, with generally increased magnitudes of protein abundance differences between brain regions compared to RNA. Many of the differences amplified in protein data were reflective of cytoarchitectural and functional variation between brain regions. Comparing structurally similar cortical regions revealed significant differences in the abundances of receptor-associated and resident plasma membrane proteins that were not readily observed in the RNA expression data.

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Microglial regional heterogeneity and its role in the brain.

TL;DR: A review of current knowledge on regional heterogeneity of microglia in the context of their diverse neighboring neurons and other glia may provide an important clue for future development of innovative therapies for neuropsychiatric disorders.

Child Abuse, Depression, and Methylation in Genes Involved With Stress, Neural Plasticity, and Brain Circuitry

Joan Kaufman
TL;DR: This study suggests that epigenetic changes in ID3, GRIN1, and TPPP genes, in combination with experiences of maltreatment, may confer risk for depression in children.
Journal ArticleDOI

Effects of Neurotrophic Factors in Glial Cells in the Central Nervous System: Expression and Properties in Neurodegeneration and Injury

TL;DR: This review focuses on the relationship between glia and NTFs including neurotrophins, GDNF-family ligands, CNTF family, and CDNF/MANF-family proteins as well as existing data on the glial phenotypes of NTF knockout mice and their effects on glia in disease models such as AD, PD, stroke, and retinal degeneration.
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Cell-Surface Proteomic Profiling in the Fly Brain Uncovers Wiring Regulators

TL;DR: A cell-type-specific, spatiotemporally resolved approach to profile cell-surface proteomes in intact tissues and revealed that the lipoprotein receptor LRP1 cell-autonomously controls PN dendrite targeting, contributing to the formation of a precise olfactory map.
References
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Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Journal ArticleDOI

MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

TL;DR: MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data, detects peaks, isotope clusters and stable amino acid isotope–labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space and achieves mass accuracy in the p.p.b. range.
Journal ArticleDOI

STRING v10: protein–protein interaction networks, integrated over the tree of life

TL;DR: H hierarchical and self-consistent orthology annotations are introduced for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution in the STRING database.
Journal ArticleDOI

Adjusting batch effects in microarray expression data using empirical Bayes methods

TL;DR: This paper proposed parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples.
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