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Related Concept Videos

Evolution of New Traits in Microbes01:24

Evolution of New Traits in Microbes

Microorganisms evolve rapidly due to their large population sizes and short generation times, often exhibiting measurable changes within days under laboratory conditions. Natural selection acts on standing genetic variation, enabling the retention and amplification of beneficial traits that confer fitness advantages in changing environments.Adaptive Pigment Regulation in RhodobacterIn Rhodobacter, a genus of purple non-sulfur bacteria, light-harvesting pigments such as bacteriochlorophyll and...
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Microbial evolution occurs rapidly due to short generation times and a variety of genetic processes, including horizontal gene transfer, mutation, recombination, and genetic drift. These mechanisms collectively enable microbes to adapt swiftly to changing environments.Horizontal gene transfer (HGT) allows genes to move between different species and occurs through three main mechanisms: conjugation, transformation, and transduction. Conjugation involves direct cell-to-cell contact for DNA...
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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Evolution of Microbial Genome01:08

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Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.

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Updated: Jun 30, 2026

Discovery of Metastatic Regulators using a Rapid and Quantitative Intravital Chick Chorioallantoic Membrane Model
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Published on: February 3, 2021

Clonal Metamorphosis: Deconstructing MPN Evolution with Single-Cell and Spatial Multi-Omics.

Muhammad Shahid Iqbal1,2, Abdullah K Alahmari1, Mohd Faiyaz Khan1

  • 1Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia.

Clinical and Experimental Medicine
|June 29, 2026
PubMed
Summary
This summary is machine-generated.

Myeloproliferative neoplasms (MPNs) show diverse outcomes despite shared mutations. New single-cell and spatial multi-omic technologies reveal how cell interactions and microenvironments drive MPN complexity and progression.

Keywords:
Bone marrow microenvironmentClonal evolutionMyeloproliferative neoplasmsSingle-cell sequencingSpatial transcriptomics

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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Last Updated: Jun 30, 2026

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Lineage Tracing and Clonal Analysis in Developing Cerebral Cortex Using Mosaic Analysis with Double Markers (MADM)
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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Area of Science:

  • Hematology
  • Genomics
  • Cancer Biology

Background:

  • Myeloproliferative neoplasms (MPNs) exhibit significant patient heterogeneity despite common driver mutations (JAK2, CALR, MPL).
  • Understanding the basis of this heterogeneity is crucial for improved prognostication and treatment.

Purpose of the Study:

  • To synthesize recent advances in single-cell and spatial multi-omic technologies for MPN research.
  • To explain how these technologies resolve the paradox of MPN heterogeneity.
  • To propose a new ecological model for MPN pathogenesis.

Main Methods:

  • Targeted single-cell DNA sequencing to reconstruct clonal architecture.
  • Integrated single-cell transcriptomic and epigenomic profiling.
  • Spatial transcriptomics combined with histopathology and multiplex proteomics.

Main Results:

  • Driver mutations occur in complex mosaics, with order and context influencing outcomes.
  • Within-clone heterogeneity and lineage biases contribute to variable disease presentation.
  • Malignant cells remodel bone marrow niches, creating microenvironments that promote aggressive subclones.

Conclusions:

  • A new ecological model posits that epigenetic hits, clonal dynamics, and niche/immune signals drive MPN pathogenesis.
  • This framework can refine prognostication and guide combination therapies targeting both malignant cells and their ecosystem.
  • Advances enable real-time monitoring of clonal dynamics for actionable clinical strategies.