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Small-RNA Sequencing of Single Cells | GEN Genetic Engineering & Biotechnology News - Biotech from Bench to Business | GEN

High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing | RNA-Seq Blog

Scientists have for the first time sequenced an ancient RNA genome – of a barley virus once believed to be only 150 years old – pushing its ...

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Identification of Editing Sites in Mature miRNAs Using RNA Sequencing - Deep sequencing has many possible applications; one of them is the identification and quantification of RNA editing sites. The most common type of RNA editing is adenosine to inosine (A-to-I) editing. A prerequisite for this editing process is a double-stranded RNA (dsRNA) structure. Such dsRNAs are formed as part of the microRNA (miRNA) maturation process, and it is therefore expected that miRNAs are affected by...

New microRNA Analysis App in BaseSpace - miRNAs are a class of non-coding RNAs mainly involved in post-transcription control of gene expression although they are also involved in other non-canonical functions. Furthermore, they represents an interesting class of biomarkers for a large variety of diseases. Small RNA-sequencing is consolidating as the election method for the quantification of miRNAs. The steps needed to analyze Small RNA-sequencing data require the use of dedicated hardware…

from Healthinnovations

Researchers unlock another piece of the RNA sequencing puzzle.

Now, a study from researchers at Rockefeller University and Columbia University has identified a protein that recognizes a chemical instruction tag affixed to an RNA sequence, an important step in the decision-making process. The team state that their findings help to explain how the destiny of an RNA sequence is achieved. The opensource study is published in the journal Cell.

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2016-Little is known about the heterogeneity of small-RNA expression as small-RNA profiling has so far required large numbers of cells. Here we present a single-cell method for small-RNA sequencing and apply it to naive and primed human embryonic stem cells and cancer cells. Analysis of microRNAs and fragments of tRNAs and small nucleolar RNAs (snoRNAs) reveals the potential of microRNAs as markers for different cell types and states.