Dysfunction of microglia is known to play an important role in Alzheimer’s disease (AD). Here, we investigated the role of RIPK1 in microglia mediating the pathogenesis of AD. RIPK1 is highly ...expressed by microglial cells in human AD brains. Using the amyloid precursor protein (APP)/presenilin 1 (PS1) transgenic mouse model, we found that inhibition of RIPK1, using both pharmacological and genetic means, reduced amyloid burden, the levels of inflammatory cytokines, and memory deficits. Furthermore, inhibition of RIPK1 promoted microglial degradation of Aβ in vitro. We characterized the transcriptional profiles of adultmicroglia from APP/PS1mice and identified a role for RIPK1 in regulating the microglial expression of CH25H and Cst7, a marker for disease-associated microglia (DAM), which encodes an endosomal/lysosomal cathepsin inhibitor named Cystatin F. We present evidence that RIPK1-mediated induction of Cst7 leads to an impairment in the lysosomal pathway. These data suggest that RIPK1 may mediate a critical checkpoint in the transition to the DAM state. Together, our study highlights a non-cell death mechanism by which the activation of RIPK1 mediates the induction of a DAM phenotype, including an inflammatory response and a reduction in phagocytic activity, and connects RIPK1-mediated transcription in microglia to the etiology of AD. Our results support that RIPK1 is an important therapeutic target for the treatment of AD.
Neuronal types in the central nervous system differ dramatically in their resilience to injury or other insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) ...following optic nerve crush (ONC), which severs their axons and leads to death of ∼80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC; characterized transcriptomic, physiological, and morphological changes that preceded degeneration; and identified genes selectively expressed by each type. Finally, using loss- and gain-of-function assays in vivo, we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury and demonstrates that differential gene expression can be used to reveal molecular targets for intervention.
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•46 transcriptionally distinct type of retinal ganglion cells (RGCs) in mice•RGC types differ dramatically in survival following axonal transection•Different genes expressed by resilient and vulnerable RGC types•Manipulation of differentially expressed genes promotes RGC survival and regeneration
High-throughput single-cell RNA-seq characterizes 46 types of adult mouse retinal ganglion cells and documents dramatic differences among them in their ability to survive axotomy. Manipulation of genes differentially expressed between resilient and vulnerable types enhances survival and axon regeneration.
Patterns of gene expression can be used to characterize and classify neuronal types. It is challenging, however, to generate taxonomies that fulfill the essential criteria of being comprehensive, ...harmonizing with conventional classification schemes, and lacking superfluous subdivisions of genuine types. To address these challenges, we used massively parallel single-cell RNA profiling and optimized computational methods on a heterogeneous class of neurons, mouse retinal bipolar cells (BCs). From a population of ∼25,000 BCs, we derived a molecular classification that identified 15 types, including all types observed previously and two novel types, one of which has a non-canonical morphology and position. We validated the classification scheme and identified dozens of novel markers using methods that match molecular expression to cell morphology. This work provides a systematic methodology for achieving comprehensive molecular classification of neurons, identifies novel neuronal types, and uncovers transcriptional differences that distinguish types within a class.
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•Unsupervised clustering of 25,000 single-cell transcriptomes reveals 15 bipolar types•Molecularly defined types correspond 1:1 to morphologically defined types•One previously undescribed bipolar cell type has hybrid bipolar-amacrine features•Shallow sequencing of large cell numbers facilitates comprehensive classification
Single-cell transcriptome sequencing of retinal bipolar cells reveals known and new types including one with a non-canonical morphology.
Strand-specific, massively parallel cDNA sequencing (RNA-seq) is a powerful tool for transcript discovery, genome annotation and expression profiling. There are multiple published methods for ...strand-specific RNA-seq, but no consensus exists as to how to choose between them. Here we developed a comprehensive computational pipeline to compare library quality metrics from any RNA-seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library-construction protocols, including both published and our own methods. We found marked differences in strand specificity, library complexity, evenness and continuity of coverage, agreement with known annotations and accuracy for expression profiling. Weighing each method's performance and ease, we identified the dUTP second-strand marking and the Illumina RNA ligation methods as the leading protocols, with the former benefitting from the current availability of paired-end sequencing. Our analysis provides a comprehensive benchmark, and our computational pipeline is applicable for assessment of future protocols in other organisms.
The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have ...not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.
RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical ...to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis.
See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.
Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and ...phenotypic output, with important functional consequences. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs or proteins simultaneously, because genomic profiling methods could not be applied to single cells until very recently. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Long noncoding RNAs (lncRNAs) comprise a diverse class of transcripts that structurally resemble mRNAs but do not encode proteins. Recent genome-wide studies in humans and the mouse have annotated ...lncRNAs expressed in cell lines and adult tissues, but a systematic analysis of lncRNAs expressed during vertebrate embryogenesis has been elusive. To identify lncRNAs with potential functions in vertebrate embryogenesis, we performed a time-series of RNA-seq experiments at eight stages during early zebrafish development. We reconstructed 56,535 high-confidence transcripts in 28,912 loci, recovering the vast majority of expressed RefSeq transcripts while identifying thousands of novel isoforms and expressed loci. We defined a stringent set of 1133 noncoding multi-exonic transcripts expressed during embryogenesis. These include long intergenic ncRNAs (lincRNAs), intronic overlapping lncRNAs, exonic antisense overlapping lncRNAs, and precursors for small RNAs (sRNAs). Zebrafish lncRNAs share many of the characteristics of their mammalian counterparts: relatively short length, low exon number, low expression, and conservation levels comparable to that of introns. Subsets of lncRNAs carry chromatin signatures characteristic of genes with developmental functions. The temporal expression profile of lncRNAs revealed two novel properties: lncRNAs are expressed in narrower time windows than are protein-coding genes and are specifically enriched in early-stage embryos. In addition, several lncRNAs show tissue-specific expression and distinct subcellular localization patterns. Integrative computational analyses associated individual lncRNAs with specific pathways and functions, ranging from cell cycle regulation to morphogenesis. Our study provides the first systematic identification of lncRNAs in a vertebrate embryo and forms the foundation for future genetic, genomic, and evolutionary studies.
The complete extent to which the human genome is translated into polypeptides is of fundamental importance. We report a peptidomic strategy to detect short open reading frame (sORF)-encoded ...polypeptides (SEPs) in human cells. We identify 90 SEPs, 86 of which are previously uncharacterized, which is the largest number of human SEPs ever reported. SEP abundances range from 10-1,000 molecules per cell, identical to abundances of known proteins. SEPs arise from sORFs in noncoding RNAs as well as multicistronic mRNAs, and many SEPs initiate with non-AUG start codons, indicating that noncanonical translation may be more widespread in mammals than previously thought. In addition, coding sORFs are present in a small fraction (8 out of 1,866) of long intergenic noncoding RNAs. Together, these results provide strong evidence that the human proteome is more complex than previously appreciated.
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