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Related Concept Videos

What is an Experiment?01:12

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An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
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When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
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Iteratively improving Hi-C experiments one step at a time.

Rosela Golloshi1, Jacob T Sanders1, Rachel Patton McCord1

  • 1Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, United States.

Methods (San Diego, Calif.)
|May 4, 2018
PubMed
Summary
This summary is machine-generated.

This study evaluates modifications to the chromosome conformation capture (Hi-C) protocol to improve data quality and reduce artifacts. Optimizing Hi-C experiments is crucial for understanding 3D genome organization and its role in cellular functions and diseases.

Keywords:
3D genome structureChromosome conformation captureHi-CHigh throughput sequencing

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Area of Science:

  • Genomics
  • Molecular Biology
  • Biotechnology

Background:

  • The 3D organization of eukaryotic chromosomes is vital for gene expression, DNA replication, cell division, and DNA damage response.
  • Genome-wide chromosome conformation capture (Hi-C) is a powerful technique for mapping 3D genome organization by quantifying interactions between genomic regions.

Purpose of the Study:

  • To evaluate recent Hi-C protocol modifications and sample preparation variables impacting data quality.
  • To identify and understand artifacts in Hi-C library preparation, such as microhomology-based template copying and chimera formation.
  • To pinpoint steps for optimization to enhance Hi-C utility for specialized cell populations and small tissue samples.

Main Methods:

  • Evaluation of Hi-C protocol modifications.
  • Analysis of sample preparation variables.
  • Examination of artifacts including microhomology-based artificial template copying and chimera formation.

Main Results:

  • Identified specific protocol steps and sample preparation variables that influence Hi-C data quality.
  • Characterized artifacts that introduce noise into Hi-C data.
  • Highlighted steps prone to DNA loss, critical for adapting Hi-C to low cell numbers.

Conclusions:

  • Understanding and controlling factors affecting Hi-C experiment success and data quality is essential.
  • Optimization of Hi-C protocols can improve its application in studying 3D genome structure, genomic rearrangements, and disease biomarkers.
  • Further refinement of Hi-C is needed for analyzing specialized cell populations and small primary tissues.