scholarly journals Enhancement of reporter gene detection sensitivity by insertion of specific mini-peptide-coding sequences

2009 ◽  
Vol 17 (2) ◽  
pp. 131-140 ◽  
Author(s):  
J Cutrera ◽  
D Dibra ◽  
X Xia ◽  
S Li
Keyword(s):  
Reporter Gene ◽  
Detection Sensitivity ◽  
Gene Detection ◽  
Coding Sequences

Simulation of Gold Nanoparticles Aggravating MEMS Cantilever Optical Static Detection Biochip

2013 ◽  
Vol 694-697 ◽  
pp. 966-970 ◽  
Author(s):  
Yue Tao Ge ◽  
Xiao Tong Yin
Keyword(s):  
Gold Nanoparticles ◽  
Low Cost ◽  
Mechanical Systems ◽  
Side Wall ◽  
High Sensitivity ◽  
Detection Sensitivity ◽  
Gene Detection ◽  
Micro Electro Mechanical Systems ◽  
Target Dna ◽  
Static Detection

A kind of gene detection biochip model based on biological micro electro mechanical systems (BioMEMS) technology and micro optical electro mechanical systems (MOEMS) technology is designed and simulated. In order to detect whether there are nucleic acid components in the testing samples, the biochip in this study issues horizontal light by laser, then receives and reads the deformation signals of MEMS cantilever by optical detector. The MEMS optical reflecting system can amplify MEMS cantilever deformation signal 22 times by micro reflectors which are set on the side wall of the cantilever free end. In order to improve optical detection sensitivity, gold nanoparticles (GNPs) which are combined with hybridization information is taken to aggravate MEMS cantilever, and employ Au - S chemical bond of GNPs and dithiol HS(CH2)6SH to combine and fix DNA probe, and then employ target DNA which is marked with biotin to combine GNPs by Biotin - Streptavidin combining. The simulation results show that this biochip can detect biological samples fast, high throughput, low cost, high sensitivity and reliably.

scholarly journals TAS-Seq: a robust and sensitive amplification method for beads-based scRNA-seq

2021 ◽  
Author(s):  
Shigeyuki Shichino ◽  
Satoshi Ueha ◽  
Shinichi Hashimoto ◽  
Tatsuro Ogawa ◽  
Hiroyasu Aoki ◽  
...  
Keyword(s):  
Solid Phase ◽  
Cell Interaction ◽  
Interaction Networks ◽  
Cellular Heterogeneity ◽  
Detection Sensitivity ◽  
Gene Detection ◽  
Flow Cytometric Data ◽  
Amplification Method ◽  
Flow Cytometric ◽  
Highly Correlated

Single-cell RNA-sequencing (scRNA-seq) is valuable for analyzing cellular heterogeneity. Cell composition accuracy is critical for analyzing cell-cell interaction networks from scRNA-seq data. We developed terminator-assisted solid-phase cDNA amplification and sequencing (TAS-Seq), a scRNA-seq method relying on a terminator, terminal transferase, and nanowell/beads-based scRNA-seq platform that could acquire scRNA-seq data, is highly correlated with flow-cytometric data, has gene-detection sensitivity, and is more robust than widely-used methods.

scholarly journals stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics

2021 ◽  
Author(s):  
Shengquan Chen ◽  
Boheng Zhang ◽  
Xiaoyang Chen ◽  
Xuegong Zhang ◽  
Rui Jiang
Keyword(s):  
Gene Expression ◽  
Spatial Organization ◽  
Correlation Coefficients ◽  
Detection Sensitivity ◽  
Gene Detection ◽  
Spatially Resolved ◽  
Expression Of Genes ◽  
Number Of Genes ◽  
Joint Embedding ◽  
Spatial Cell

Motivation: Single-cell RNA sequencing (scRNA-seq) techniques have revolutionized the investigation of transcriptomic landscape in individual cells. Recent advancements in spatial transcriptomic technologies further enable gene expression profiling and spatial organization mapping of cells simultaneously. Among the technologies, imaging-based methods can offer higher spatial resolutions, while they are limited by either the small number of genes imaged or the low gene detection sensitivity. Although several methods have been proposed for enhancing spatially resolved transcriptomics, inadequate accuracy of gene expression prediction and insufficient ability of cell-population identification still impede the applications of these methods. Results: We propose stPlus, a reference-based method that leverages information in scRNA-seq data to enhance spatial transcriptomics. Based on an auto-encoder with a carefully tailored loss function, stPlus performs joint embedding and predicts spatial gene expression via a weighted k-NN. stPlus outperforms baseline methods with higher gene-wise and cell-wise Spearman correlation coefficients. We also introduce a clustering-based approach to assess the enhancement performance systematically. Using the data enhanced by stPlus, cell populations can be better identified than using the measured data. The predicted expression of genes unique to scRNA-seq data can also well characterize spatial cell heterogeneity. Besides, stPlus is robust and scalable to datasets of diverse gene detection sensitivity levels, sample sizes, and number of spatially measured genes. We anticipate stPlus will facilitate the analysis of spatial transcriptomics. Availability: stPlus with detailed documents is freely accessible at http://health.tsinghua.edu.cn/software/stPlus/ and the source code is openly available on https://github.com/xy-chen16/stPlus.

scholarly journals Streamlined low-input transcriptomics through EASY-RNAseq

2019 ◽  
Author(s):  
Yiwen Zhou ◽  
Hao Xu ◽  
Haiyang Wu ◽  
Haili Yu ◽  
Peng Zhou ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Transcriptome Profiling ◽  
Small Cell ◽  
Detection Sensitivity ◽  
Biological Research ◽  
Human Embryos ◽  
Cell Populations ◽  
Gene Detection ◽  
Cell Stage ◽  
Protein Coding

ABSTRACTHigh-throughput sequencing for transcriptome profiling is an increasingly accessible and important tool for biological research. However, accurate profiling of small cell populations remains challenging due to issues with gene detection sensitivity and experimental complexity. Here we describe a streamlined RNAseq protocol (EASY RNAseq) for sensitive transcriptome assessment starting from low amount of input materials. EASY RNAseq is technically robust enough for sequencing small pools of homogenous and heterogeneous cells, recovering higher numbers of genes and with a more even expression distribution pattern than other commonly used methods. Application of EASY RNAseq to single human embryos at the 8-cell stage was able to achieve detection of 70% protein-coding genes. This workflow may thus serve as a useful tool for sensitive interrogation of rare cell populations.

Methods on In Situ Hybridization, Immunohistochemistry and �-Galactosidase Reporter Gene Detection

2001 ◽  
Vol 39 (3) ◽  
pp. 169-191 ◽  
Author(s):  
Diego Franco ◽  
Piet A.J. de Boer ◽  
Corrie de Gier-de Vries ◽  
Wouter H. Lamers ◽  
Antoon F.M. Moorman
Keyword(s):  
In Situ Hybridization ◽  
Reporter Gene ◽  
Gene Detection

scholarly journals Dual chromogenic reporter gene detection in mammalian cells withlacZand arabinofuranosidase

BioTechniques ◽  
2004 ◽  
Vol 37 (6) ◽  
pp. 896-897
Author(s):  
Tomiko Tsuchida ◽  
William K. Berlin ◽  
Brian Sauer
Keyword(s):  
Reporter Gene ◽  
Mammalian Cells ◽  
Gene Detection

Methods on In Situ Hybridization, Immunohistochemistry and �-Galactosidase Reporter Gene Detection

2001 ◽  
Vol 39 (1) ◽  
pp. 3-25 ◽  
Author(s):  
Diego Franco ◽  
Piet A.J. de Boer ◽  
Corrie de Gier-de Vries ◽  
Wouter H. Lamers ◽  
Antoon F.M. Moorman
Keyword(s):  
In Situ Hybridization ◽  
Reporter Gene ◽  
Gene Detection

scholarly journals Benchmarking full-length transcript single cell mRNA sequencing protocols

2020 ◽  
Author(s):  
Victoria Probst ◽  
Felix Pacheco ◽  
Finn Cilius Nielsen ◽  
Frederik Otzen Bagger
Keyword(s):  
Single Cell ◽  
Cellular Heterogeneity ◽  
Detection Sensitivity ◽  
Gene Detection ◽  
Mrna Sequencing ◽  
Sequencing Technologies ◽  
High Gene ◽  
The Absolute ◽  
Commercial Kits ◽  
Full Length Transcript

AbstractSingle cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. Here, we present a performance evaluation of three different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications requiring high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext® Single Cell/ Low Input RNA Library Prep Kit (NEB®), SMART-seq® HT kit (Takara®), and the non-commercial protocol Genome & Transcriptome sequencing (G&T). G&T delivered the highest detection of genes per single cell, at the absolute lowest price. Takara® kit presented similar high gene detection per single cell, and high reproducibility between sample, but at the absolute highest price. NEB® delivered a lower detection of genes but remain an alternative to more expensive commercial kits.

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