Dataset Information

Sequencing cell-type-specific transcriptomes with SLAM-ITseq.

ABSTRACT: Analysis of cell-type-specific transcriptomes is vital for understanding the biology of tissues and organs in the context of multicellular organisms. In this Protocol Extension, we combine a previously developed cell-type-specific metabolic RNA labeling method (thiouracil (TU) tagging) and a pipeline to detect the labeled transcripts by a novel RNA sequencing (RNA-seq) method, SLAMseq (thiol (SH)-linked alkylation for the metabolic sequencing of RNA). By injecting a uracil analog, 4-thiouracil, into transgenic mice that express cell-type-specific uracil phosphoribosyltransferase (UPRT), an enzyme required for 4-thiouracil incorporation into newly synthesized RNA, only cells expressing UPRT synthesize thiol-containing RNA. Total RNA isolated from a tissue of interest is then sequenced with SLAMseq, which introduces thymine to cytosine (T>C) conversions at the sites of the incorporated 4-thiouracil. The resulting sequencing reads are then mapped with the T>C-aware alignment software, SLAM-DUNK, which allows mapping of reads containing T>C mismatches. The number of T>C conversions per transcript is further analyzed to identify which transcripts are synthesized in the UPRT-expressing cells. Thus, our method, SLAM-ITseq (SLAMseq in tissue), enables cell-specific transcriptomics without laborious FACS-based cell sorting or biochemical isolation of the labeled transcripts used in TU tagging. In the murine tissues we assessed previously, this method identified ~5,000 genes that are expressed in a cell type of interest from the total RNA pool from the tissue. Any laboratory with access to a high-throughput sequencer and high-power computing can adapt this protocol with ease, and the entire pipeline can be completed in <5 d.

SUBMITTER: Matsushima W

PROVIDER: S-EPMC6997029 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Sequencing cell-type-specific transcriptomes with SLAM-ITseq.

Matsushima Wayo W Herzog Veronika A VA Neumann Tobias T Gapp Katharina K Zuber Johannes J Ameres Stefan L SL Miska Eric A EA

Nature protocols 20190626 8

Analysis of cell-type-specific transcriptomes is vital for understanding the biology of tissues and organs in the context of multicellular organisms. In this Protocol Extension, we combine a previously developed cell-type-specific metabolic RNA labeling method (thiouracil (TU) tagging) and a pipeline to detect the labeled transcripts by a novel RNA sequencing (RNA-seq) method, SLAMseq (thiol (SH)-linked alkylation for the metabolic sequencing of RNA). By injecting a uracil analog, 4-thiouracil, ...[more]

PMID: 31243395

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Project description:BackgroundOrgan-specific gene expression contains rich information about in vivo biological processes. This kind of information, previously gathered through microarray profiling, has been proven fruitful to the understanding of specific mutants, regulatory events, signaling, and development. With the advent of the next-generation sequencing (NGS) of RNAs, more quantitative and detailed information of gene expressions than previously available can now be collected for each organ or organ developmental stages. The combination of an object-oriented experimental design and an efficient treatment of the high volume information generated through a NGS platform may offer a powerful tool for inferring previously intractable developmental processes.ResultsWe collected transcriptomic data over a Solexa/Illumina platform on samples of Ipomoea leaf, sepal, and petals (at three developmental stages), and presented a method for analyzing transcriptomic variations within and between organs. We demonstrated that in vivo signals of transcriptomes can be retrieved de novo through the NGS techniques, proper data handling, bioinformatic tools, and the current understanding of molecular networks. We found that numbers of transcribed genes from both nuclear and chloroplast genomes decreased by the same order of leaf → sepal →petal. Petal resembled leaf in cell division patterns and abundance level of commonly expressed organelle genes. Its chloroplast transcripts constituted a subset of those in leaf. Moreover, reconstructions of multiple metabolic networks for each organ enabled inferences of substance flow, providing transcript evidence for the path of sucrose in leaf to anthocyanin synthesis in petal.ConclusionOur results attest that developmental transcriptomes are highly informative for exploring connections between morphological traits and the associated molecular networks. Significant hypotheses have been developed, including that the petal is a derived organ of leaf and that its color can be modified by fluctuations of substance flow within the associated metabolic networks among organs.

Project description:Microglial cells form a context-dependent network of brain immunoeffector cells. Despite their indispensable roles, unresolved questions exist around biomarker discovery relevant to their cellular localization, self-renewing potential, and brain developmental dynamics. To resolve the existent gap in the annotation of candidate biomarkers, we conducted a meta-analysis of brain cells using available high-throughput data sets for deciphering microglia-specific expression profiles. We have identified 3,290 significant genes specific to microglia and further selected the top 20 dysregulated genes on the basis of p-value and log2FC. To this list, we added 7 known microglia-specific markers making the candidate list comprising 27 genes for further downstream analyses. Next, we established a connectome of these potential markers with their putative protein partners, which demonstrated strong associations of upregulated genes like Dedicator of cytokinesis 2 (DOCK2) with early/mature microglial markers such as Sphingosine kinase 1 (SPHK1), CD68, and CD45. To elucidate their respective brain anatomical location, we deconvoluted the BrainSpan Atlas expression data. This analysis showed high expression of the majority of candidate genes in microglia-dense regions (Amygdala, Hippocampus, Striatum) in the postnatal brain. Furthermore, to decipher their localized expression across brain ages, we constructed a developmental dynamics map (DDM) comprising extensive gene expression profiles throughout prenatal to postnatal stages, which resulted in the discovery of novel microglia-specific gene signatures. One of the interesting readout from DDM is that all the microglia-dense regions exhibit dynamic regulation of few genes at 37 post conception week (pcw), the transition period between pre- and postnatal stages. To validate these findings and correlate them as potential biomarkers, we analyzed the expression of corresponding proteins in hESC-derived human microglia precursors. The cultured microglial precursors showed expression of Pentraxin 3 (PTX3) and SPHK1 as well as several known markers like CD68, Allograft inflammatory factor 1 (AIF1/IBA1). In summary, this study has furnished critical insights into microglia dynamics across human brain ages and cataloged potential transcriptomic fingerprints that can be further exploited for designing novel neurotherapeutics.

Dataset Information

Sequencing cell-type-specific transcriptomes with SLAM-ITseq.

Publications

Sequencing cell-type-specific transcriptomes with SLAM-ITseq.

Similar Datasets

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