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Related Concept Videos

Conservative Site-specific Recombination and Phase Variation02:53

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.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Related Experiment Video

Updated: May 21, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
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Published on: July 11, 2025

Two-phase analysis in consensus genetic mapping.

Y Ronin, D Mester, D Minkov

    G3 (Bethesda, Md.)
    |June 7, 2012
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a novel two-phase approach for multiple consensus genetic mapping (MCGM), effectively integrating diverse genetic mapping data to create robust consensus maps. The method addresses challenges like varying marker quality and recombination rates for improved genomic analysis.

    Keywords:
    consensus genetic mappingguided evolution strategy optimizationsynchronized marker ordering analysistwo-phase approach

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    Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
    05:53

    Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

    Published on: June 21, 2018

    Area of Science:

    • Genetics
    • Bioinformatics
    • Computational Biology

    Background:

    • Numerous genetic mapping projects yield abundant, yet varied, multilocus maps for the same organism.
    • Inconsistencies in map quality arise from diverse populations, marker sets, and software, necessitating data integration for consensus maps.
    • Multiple consensus genetic mapping (MCGM) presents significant challenges due to inter-population recombination rate differences, marker dominance variations, and distinct marker subsets used across studies.

    Purpose of the Study:

    • To introduce a robust two-phase computational approach for solving the complex problem of multiple consensus genetic mapping (MCGM).
    • To develop a method capable of handling arbitrary patterns of shared markers and varying data quality across different genetic mapping datasets.
    • To generate reliable consensus genetic maps by integrating information from multiple, heterogeneous multilocus maps.

    Main Methods:

    • Phase 1 involves multilocus ordering and iterative jackknife resampling for each dataset, reducing the ordering problem to the Traveling Salesperson Problem (TSP).
    • The TSP formulation seeks the marker order that minimizes the sum of recombination distances between adjacent markers within each dataset.
    • Phase 2 selects the optimal consensus order for shared markers by minimizing the total length of non-conflicting maps, incorporating data quality variations and resolving conflicts using heuristic or exact algorithms.

    Main Results:

    • The proposed two-phase approach successfully integrates diverse genetic mapping data, producing stable and reliable consensus marker orders.
    • The method effectively addresses challenges related to differing recombination rates, marker dominance, and varying marker subsets across datasets.
    • Testing on simulated and real maize datasets demonstrated the approach's efficacy in generating accurate consensus genetic maps.

    Conclusions:

    • The developed two-phase method provides an effective solution for multiple consensus genetic mapping (MCGM), significantly advancing the integration of genomic data.
    • The approach, framed as a synchronized TSP, offers a flexible framework adaptable to variations in data quality and mapping complexities.
    • This methodology enhances the construction of high-quality consensus genetic maps, crucial for comparative genomics and trait mapping across different species.