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Genetic Drift03:33

Genetic Drift

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Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
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Mutation, Gene Flow, and Genetic Drift01:09

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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).
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Gene Duplication and Divergence02:37

Gene Duplication and Divergence

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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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Gene Flow02:39

Gene Flow

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Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
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Gene Families01:57

Gene Families

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Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
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Video Experimental Relacionado

Updated: Sep 10, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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De las listas genéticas a la deriva del contexto

Zhongyang Lin1, Dvir Aran2

  • 1Faculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.

Cancer cell
|August 22, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Los investigadores desarrollaron RECODR, un nuevo método para rastrear las relaciones genéticas cambiantes a lo largo del tiempo. Este enfoque identifica nuevos factores de resistencia al tratamiento del cáncer y sugiere terapias combinadas efectivas.

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Área de la Ciencia:

  • En el campo de la oncología
  • La genómica
  • Biología de sistemas

Sus antecedentes:

  • La resistencia al tratamiento es un desafío importante que limita la eficacia de la terapia contra el cáncer a largo plazo.
  • Los biomarcadores actuales a menudo dependen de la expresión génica estática, y no logran capturar cambios biológicos dinámicos.
  • Comprender la dinámica temporal de las interacciones genéticas es crucial para superar la resistencia.

Objetivo del estudio:

  • Introducir RECODR (RElacional CO-expresión DRiving), un nuevo enfoque computacional.
  • Analizar los cambios dinámicos en las relaciones genéticas asociadas con la resistencia al tratamiento del cáncer.
  • Identificar nuevos objetivos terapéuticos y estrategias de combinación.

Principales métodos:

  • Desarrollo y aplicación del algoritmo RECODR.
  • Análisis de la dinámica de la red de coexpresión génica a lo largo del tiempo.
  • Integración de los datos de las relaciones genéticas temporales con los fenotipos de resistencia.

Principales resultados:

  • RECODR identificó con éxito factores de resistencia al tratamiento no reconocidos anteriormente.
  • El método reveló alteraciones dinámicas en las redes de interacción génica subyacentes a la resistencia.
  • Los tratamientos combinados previstos basados en desplazamientos de la red temporal mostraron una eficacia potencial.

Conclusiones:

  • RECODR ofrece un nuevo y poderoso paradigma para analizar las complejidades de la resistencia al tratamiento del cáncer.
  • El análisis dinámico de las relaciones genéticas proporciona ideas más profundas que los enfoques estáticos.
  • Este enfoque puede guiar el desarrollo de terapias combinadas más efectivas y personalizadas para pacientes con cáncer.