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Transcript amplification from single bacterium for transcriptome analysis

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TLDR
Data indicate that RNA-seq of TTA from a single cell is possible using this novel method and suggests that B. thailandensis, when exposed to the aromatic amino acid biosynthesis inhibitor glyphosate, induces (or represses) genes to possibly recuperate and balance the intracellular amino acid pool.
Abstract
Total transcript amplification (TTA) from single eukaryotic cells for transcriptome analysis is established, but TTA from a single prokaryotic cell presents additional challenges with much less starting material, the lack of poly(A)-tails, and the fact that the messages can be polycistronic. Here, we describe a novel method for single-bacterium TTA using a model organism, Burkholderia thailandensis, exposed to a subinhibitory concentration of the antibacterial agent, glyphosate. Utilizing a B. thailandensis microarray to assess the TTA method showed low fold-change bias (less than twofold difference and Pearson correlation coefficient R ≈ 0.87–0.89) and drop-outs (4%–6% of 2842 detectable genes), compared with data obtained from the larger-scale nonamplified RNA samples. Further analysis of the microarray data suggests that B. thailandensis, when exposed to the aromatic amino acid biosynthesis inhibitor glyphosate, induces (or represses) genes to possibly recuperate and balance the intracellular amino acid pool. We validated our single-cell microarray data at the multi-cell and single-cell levels with lacZ and gfp reporter-gene fusions, respectively. Sanger sequencing of 192 clones generated from the TTA product of a single cell, with and without enrichment by elimination of rRNA and tRNA, detected only B. thailandensis sequences with no contamination. These data indicate that RNA-seq of TTA from a single cell is possible using this novel method.

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Dual RNA-seq of pathogen and host

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eulerAPE: drawing area-proportional 3-Venn diagrams using ellipses.

TL;DR: EulerAPE is presented as the first method and software that uses ellipses for automatically drawing accurate area-proportional Venn diagrams for 3-set data and various other methods that are currently available are compared and differences between their generated diagrams in terms of accuracy and ease of understanding are discussed.
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Single-cell transcriptome sequencing: recent advances and remaining challenges.

TL;DR: This work states that single-cell RNA-sequencing methods are now robust and economically practical and are becoming a powerful tool for high-throughput, high-resolution transcriptomic analysis of cell states and dynamics, and offers new insights into the cellular diversity underlying superficially homogeneous populations.
References
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TL;DR: Molecular Cloning has served as the foundation of technical expertise in labs worldwide for 30 years as mentioned in this paper and has been so popular, or so influential, that no other manual has been more widely used and influential.
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TL;DR: The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.
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TL;DR: A thorough description of laser-capture microdissection techniques is provided, with an emphasis on tips and troubleshooting advice derived from LCM users.
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