Ts Total Plex

[Jen Ondrey]

D-Plex Total RNA-seq Library Preparation Kit is a tool designed for the study of the whole coding and non-coding transcriptome. The kit is using the D-Plex technology to generate directional libraries for Illumina sequencing directly from total RNAs, mRNAs that has already been enriched by poly(A) selection, or RNAs that has already been depleted of rRNAs.

The D-Plex technology utilizes two innovative ligation-free mechanisms - poly(A) tailing and template switching - to produce sequencing libraries from ultra-low input amounts, down to 50 pg for total RNAs, mRNAs or rRNA-depleted RNAs. Combined with unique molecular identifiers (UMI), this complete solution delivers a high-sensitivity detection method for comprehensive analysis of the transcriptome. It accurately measures gene and transcript abundance and captures the widest possible diversity of RNAs, including known and novel features in coding and non-coding RNAs.

D-Plex Total RNA-seq Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time. The library preparation takes place in a single tube, increasing the efficiency tremendously. This new solution has been extensively validated for both intact and highly degraded RNA samples, including that derived from FFPE preparations.

D-Plex Total RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Unique Dual Indexes were designed and validated to fit the D-Plex technology and are available separately:

D-Plex Total RNA-seq kit enables great transcript detection, even when starting from very low RNA inputs or working with challenging FFPE samples. Increased number of transcripts detected at 1x coverage is an indicator of greater sensitivity.

Gene expression profiling (including protein coding exons and introns) obtained with D-Plex Total RNA-seq kit is conserved for decreasing RNA inputs, keeping transcript diversity across the range of RNA inputs.

Correlation analysis of the protein coding genes detected indicates superior transcript expression correlation between low and high RNA inputs. This result demonstrates that D-Plex is an ideal solution for challenging samples such as FFPE preparations.

Specific D-Plex indexes were designed and validated to fit the D-Plex technology for Illumina sequencing and are not included in the kit. They can be bought separately according to your needs. Please choose the format that suits you best among the compatible references to:

A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.

Pyruvate Kinase M (PKM) binds ribosomes in a poly-ADPribosylation dependent manner to induce translational stalling.
Kejiou N. S. et al.
In light of the numerous studies identifying post-transcriptional regulators on the surface of the endoplasmic reticulum (ER), we asked whether there are factors that regulate compartment specific mRNA translation in human cells. Using a proteomic survey of spatially regulated polysome interacting proteins, we ident...

miR-210 expression is strongly hypoxia-induced in anaplastic thyroidcancer cell lines and is associated with extracellular vesicles \&Argonaute-2
Powell Bonita H. et al.
Hypoxia, or low oxygen tension, is frequently found in highly proliferative solid tumors such as anaplastic thyroid carcinoma (ATC) and is believed to promote resistance to chemotherapy and radiation. Identifying hypoxic cells for targeted therapy may thus be an effective approach to treating aggressive cancers. Her...

Light affects behavioral despair involving the clock gene Period 1.
Olejniczak I. et al.
Light at night has strong effects on physiology and behavior of mammals. It affects mood in humans, which is exploited as light therapy, and has been shown to reset the circadian clock in the suprachiasmatic nuclei (SCN). This resetting is paramount to align physiological and biochemical timing to the environmental ...

Small-Medium Extracellular Vesicles and Their miRNA Cargo inRetinal Health and Degeneration: Mediators of Homeostasis, andVehicles for Targeted Gene Therapy.
Wooff Yvette et al.
Photoreceptor cell death and inflammation are known to occur progressively in retinal degenerative diseases such as age-related macular degeneration (AMD). However, the molecular mechanisms underlying these biological processes are largely unknown. Extracellular vesicles (EV) are essential mediators of cell-to-cell ...

The ribosomal protein S1-dependent standby site in mRNA consists ofa single-stranded region and a 5' structure element.
Romilly Cdric et al.
In bacteria, stable RNA structures that sequester ribosome-binding sites (RBS) impair translation initiation, and thus protein output. In some cases, ribosome standby can overcome inhibition by structure: 30S subunits bind sequence-nonspecifically to a single-stranded region and, on breathing of the inhibitory struc...

mir-21 is associated with inactive low molecular weight Argonautecomplexes in thyroid cancer cell lines
Powell Bonita H. et al.
Thyroid cancer is the most prevalent endocrine malignancy. We and others have shown that several microRNAs, which are post-transcriptional gene regulators, are aberrantly expressed in anaplastic thyroid cancer (ATC) and papillary thyroid cancer (PTC) tissues, as well as cell lines derived from these cancers. In the ...

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In this study, we extended co-indexing of transcriptomes and epitopes (CITE) to the spatial dimension and demonstrated high-plex protein and whole transcriptome co-mapping. We profiled 189 proteins and whole transcriptome in multiple mouse tissue types with spatial CITE sequencing and then further applied the method to measure 273 proteins and transcriptome in human tissues, revealing spatially distinct germinal center reactions in tonsil and early immune activation in skin at the Coronavirus Disease 2019 mRNA vaccine injection site.

We conducted validation for selected proteins using multiplexed immunofluorescence imaging (Extended Data Figs. 3 and 4)14. In particular, using an adjacent tissue section, we conducted a head-to-head comparison for selected protein markers (Extended Data Fig. 4a). CD21, CD279 and CD19 were mainly detected within the GCs of tonsil. T cell markers CD90 and CD3 were observed mainly in the regions surrounding the GCs. CD31, an endothelial cell marker, depicts the vasculature, and its spatial pattern corresponds well to that obtained by spatial-CITE-seq. We next validated the spatial-CITE-seq by comparing it with single-cell CITE-seq (scCITE-seq). The pseudo-bulk data generated from spatial-CITE-seq were compared with those obtained from scCITE-seq data15, and a strong correlation was observed, with an R value of 0.78 (Extended Data Fig. 4b). We further integrated scCITE-seq and spatial-CITE-seq datasets using the Seurat integration package, which revealed that the two datasets share highly concordant protein expression patterns in 2D uniform manifold approximation and projection (UMAP) even for the low-frequency cell populations (Extended Data Fig. 4c). In addition, we also demonstrated the applicability of spatial-CITE-seq to other human tissues, including spleen and thymus (Extended Data Fig. 5).

Single-cell RNA sequencing (scRNA-seq) was conducted with the same skin biopsy tissue specimen (Extended Data Fig. 7). It was combined with spatial transcriptomes to perform clustering that gave rise to 13 major clusters, and the major cell types were identified based on gene oncology (Fig. 2g). Label transfer of cell types from scRNA-seq to spatial tissue pixels allowed for visualization of the distribution of different types (Fig. 2h). We can also visualize the expression of individual genes (Fig. 2i). For example, CCNL2 and NOL3, which are apoptosis-related genes, were expressed in the vascular region; APOC1 (responsible for lipoprotein metabolism), GJA1 (connexin protein encoding) and PRDX2 (peroxiredoxin encoding) were expressed mainly in the vascular. Transmembrane protein-encoding genes TMEM132D and glycosyltransferase ALG5 were both expressed in the dermis region. CYP4F8, encoding CYP450 protein, was shown in most skin regions. The whole transcriptome sequencing could identify the cell types in general but were not specific enough here to show the different populations of T cells. Next, we focused on several immune cell types, including antigen-presenting cells (APCs), B cells and two subsets of T cells, as indicated by differentially expressed proteins (Fig. 2j). APCs and T cells are localized in spatially distinct regions, whereas B cells are distributed throughout the tissue (Fig. 2k). Specifically, T cell subset 2 expresses a set of markers, including lymphocyte activation gene 3 (LAG3)16, associated with peripheral helper T (Tph) cell population17 (Fig. 2m) as definitely by Tph signature score defined by expression levels of LAG3, PD-1 and CXCR6 (Fig. 2n). Tph cells are implicated in local T cell activation in response to vaccination. Thus, through integration of spatial high-plex protein and transcriptome mapping with scRNA-seq data from the same skin biopsy tissue, we identified major skin and immune cell types and a subset of Tph cells highly enriched at the injection site, which may contribute to the local immune activation that initiates systemic vaccine response. We also used the SPOTlight18 package to deconvolve the spatial spot and found that most cells were keratinocytes and fibroblasts, which matches the scRNA-seq data (Extended Data Fig. 7b).

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