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Homologous Recombination

Homologous Recombination

Homologous Recombination

Homologous Recombination

The basic reaction of homologous recombination (HR) involves two chromatids that contain DNA sequences sharing a significant stretch of identity. One of these sequences uses a strand from another as a template to synthesize DNA in an enzyme-catalyzed reaction. The final product is a novel amalgamation of the two substrates. To ensure an accurate recombination of sequences, HR is restricted to the S and G2 phases of the cell cycle. At these stages, the DNA has been replicated already and the...

Conservative Site-specific Recombination and Phase Variation

Conservative Site-specific Recombination and Phase Variation

Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...

Exon Recombination

Exon Recombination

The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes.
Exon shuffling follows “splice frame rules.” Each exon...

In-vitro Mutagenesis

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

In vitro Mutagenesis

In vitro Mutagenesis

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Related Experiment Video

Updated: Apr 15, 2026

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

VDJSeq-Solver: in silico V(D)J recombination detection tool.

Giulia Paciello¹, Andrea Acquaviva¹, Chiara Pighi²

¹Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy.

|March 24, 2015

Summary

This summary is machine-generated.

VDJSeq-Solver identifies the main clone in neoplastic cells using RNA sequencing. This tool accurately detects V(D)J rearrangements, overcoming limitations of previous methods for high-throughput data.

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Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter

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Last Updated: Apr 15, 2026

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

Detection of Homologous Recombination Intermediates via Proximity Ligation and Quantitative PCR in Saccharomyces cerevisiae

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Published on: September 11, 2022

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter

Published on: March 31, 2022

Area of Science:

Immunology
Bioinformatics
Oncology

Background:

Identifying clonal lymphocyte populations is crucial for understanding lymphoid malignancies.
Current methods for recognizing lymphocyte rearrangements are not suitable for high-throughput sequencing data.
Neoplastic cells in lymphoid tissues are characterized by specific V(D)J rearrangements.

Purpose of the Study:

To present VDJSeq-Solver, a novel methodology and tool for identifying clonal lymphocyte populations from RNA sequencing reads.
To detect the most abundant V(D)J rearrangement, representing the main clone in neoplastic samples.
To provide a tool applicable to high-throughput sequencing data, overcoming existing limitations.

Main Methods:

Development of VDJSeq-Solver, a software tool implemented in JAVA/Perl/Bash.
Utilizing paired-end RNA sequencing reads from mRNA neoplastic cells.
Analyzing V(D)J rearrangements to identify the most abundant clone sequence, accounting for enzymatic modifications.

Main Results:

VDJSeq-Solver successfully detected the main clone and identified its sequence in five Mantle Cell Lymphoma samples.
The tool was further validated on twelve Diffuse Large B-Cell Lymphoma samples.
The methodology demonstrated effectiveness in handling high-throughput sequencing data for clone identification.

Conclusions:

VDJSeq-Solver is an effective tool for identifying clonal lymphocyte populations from RNA sequencing data.
The tool accurately determines the dominant V(D)J rearrangement sequence in neoplastic cells.
VDJSeq-Solver offers a significant advancement for analyzing high-throughput sequencing data in lymphoid cancer research.