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Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

22.5K
Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...
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Heterochromatin02:38

Heterochromatin

12.0K
The extent of chromatin compaction can be studied by staining chromatin using specific DNA binding dyes. Under the microscope, the dense-compacted regions that take up more dye are called heterochromatin. Heterochromatin is further classified into two forms – constitutive heterochromatin and facultative heterochromatin.
Constitutive heterochromatin: It is a highly compact region of chromatin that is mostly concentrated in the centromere and telomere. Unlike euchromatin, the amino acid at...
12.0K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

7.5K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
7.5K
LTR Retrotransposons03:08

LTR Retrotransposons

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LTR retrotransposons are class I transposable elements with long terminal repeats flanking an internal coding region. These elements are less abundant in mammals compared to other class I transposable elements. About 8 percent of human genomic DNA comprises LTR retrotransposons. Some of the common examples of LTR retrotransposons are Ty elements in yeast and Copia elements in Drosophila.
The internal coding region of LTR retrotransposons and their mechanism of transposition closely resembles a...
18.1K
General Transcription Factors01:30

General Transcription Factors

5.9K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
5.9K
Non-LTR Retrotransposons03:18

Non-LTR Retrotransposons

12.5K
As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...
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Related Experiment Video

Updated: May 6, 2026

Estimation of Telomeric Repeat-containing RNA from DNA/RNA Hybrid Complexes
11:24

Estimation of Telomeric Repeat-containing RNA from DNA/RNA Hybrid Complexes

Published on: December 5, 2025

391

Cellular Type Is a Major Determinant of R-Loop Genomic Distribution.

K Yu Oleynikova1,2, N A Zhigalova1, A P Hutchins3

  • 1Institute of Bioengineering, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, 117312 Russia.

Acta Naturae
|May 5, 2026
PubMed
Summary
This summary is machine-generated.

Cellular type significantly impacts DNA:RNA hybrid (R-loop) distribution. Comparing R-loop mapping datasets across diverse cell lines is crucial for resolving inconsistencies in genomic R-loop detection methods.

Keywords:
DNA-RNA Immunoprecipitation (DRIP)DNA:RNA hybridsHAP1 cellsR-loopscellular differentiationhPSCs

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Single Nucleotide Polymorphism-sensitive FISH Detection of Locus-specific Ribosomal RNA Transcription in Drosophila melanogaster
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Single Nucleotide Polymorphism-sensitive FISH Detection of Locus-specific Ribosomal RNA Transcription in Drosophila melanogaster

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Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
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Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

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Related Experiment Videos

Last Updated: May 6, 2026

Estimation of Telomeric Repeat-containing RNA from DNA/RNA Hybrid Complexes
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Estimation of Telomeric Repeat-containing RNA from DNA/RNA Hybrid Complexes

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Single Nucleotide Polymorphism-sensitive FISH Detection of Locus-specific Ribosomal RNA Transcription in Drosophila melanogaster
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Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
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Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

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Area of Science:

  • Genomics
  • Molecular Biology
  • Epigenetics

Background:

  • R-loops, structures with DNA:RNA hybrids and single-stranded DNA, are vital for cellular functions and disease development.
  • Existing R-loop mapping techniques show inconsistencies, prompting an evaluation of their robustness and the factors influencing R-loop distribution.

Purpose of the Study:

  • To investigate the influence of cellular type on R-loop genomic distribution.
  • To assess the comparability of R-loop mapping data across different cell lines using a consistent protocol.

Main Methods:

  • Comparison of DNA:RNA immunoprecipitation (DRIP) datasets generated using the same protocol.
  • Analysis of R-loop peak overlap between chronic myeloid leukemia-derived HAP1 cells and human pluripotent stem cells.
  • Evaluation of R-loop peak identity in HAP1-derived double knockout cell lines compared to the parental line.

Main Results:

  • Only 26% of R-loop peaks were shared between HAP1 cells and human pluripotent stem cells, indicating significant cell-type-specific differences.
  • HAP1-derived double knockout cell lines exhibited high fractions of identical R-loop peaks to each other and to the parental line (71% and 55%, respectively).

Conclusions:

  • Cellular type is a major determinant of R-loop genomic distribution.
  • Systematic comparison of R-loop datasets from diverse cell and tissue types is necessary to reconcile discrepancies between different mapping techniques.