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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Updated: Jan 17, 2026

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing
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Scalable single-cell total RNA-seq reveals non-coding programs in immunity, infection, and brain development.

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This study expands single-cell RNA sequencing to capture diverse non-coding RNAs, revealing their roles in cell identity and viral infection. Discoveries include non-coding RNA programs in immune cells, the brain, and during dengue virus infection.

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Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq
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Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

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Area of Science:

  • Genomics
  • Molecular Biology
  • Cell Biology

Background:

  • Non-coding RNAs (ncRNAs) are crucial for post-transcriptional regulation but are often missed by standard single-cell RNA sequencing (scRNA-seq).
  • Existing scRNA-seq methods primarily capture polyadenylated transcripts, limiting the study of short or non-polyadenylated ncRNAs.

Purpose of the Study:

  • To adapt scRNA-seq for comprehensive capture of coding and non-coding RNAs, including short and non-polyadenylated species.
  • To explore the functional roles of ncRNAs in cell identity and state across different biological contexts.

Main Methods:

  • Modified 10x Genomics scRNA-seq platform to capture a wider range of RNA biotypes.
  • Applied the method to immune cells, virally infected hepatocytes, and developing human brain tissue.
  • Analyzed expression patterns and regulatory relationships of identified ncRNAs.

Main Results:

  • Successfully captured diverse ncRNAs (miRNAs, tRNAs, lncRNAs, histone RNAs, viral transcripts) at single-cell resolution.
  • Identified dynamic ncRNA programs in immune cells, infected hepatocytes, and the developing brain.
  • Discovered cell-type-specific ncRNAs in the brain, including MIR137 in Cajal-Retzius cells, linked to neurodevelopmental disorders.

Conclusions:

  • Expanded transcriptome coverage in scRNA-seq reveals critical layers of gene regulation by ncRNAs.
  • ncRNAs play significant roles in defining cell identity, state, and guiding developmental processes.
  • This approach provides a scalable method for comprehensive ncRNA profiling in single cells.