Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • SEQadmin2
    Administrator
    • Dec 2023
    • 103

    DNA Methylation Study Reveals How Epigenetic Changes Pass Between Generations

    DNA methylation is one of the most studied epigenetic modifications, yet its ancestral function in animals and its capacity for transgenerational inheritance remain incompletely understood. While mammals undergo extensive epigenetic reprogramming after fertilization—largely preventing the transmission of acquired methylation states across generations—this resetting mechanism appears to be absent in invertebrates, raising questions about how methylation patterns are maintained and what consequences arise when they are disrupted.

    To explore what happens when epigenetic patterns are disrupted, scientists from Queen Mary University experimentally removed DNA methylation in the sea anemone Nematostella vectensis. The results were unexpected: animals developed normally despite losing most of their DNA methylation. Rather than causing major defects in gene regulation, the loss of methylation mainly unleashed hidden "jumping genes"—also called "selfish genes"—embedded within active genes. Left unchecked, these genetic parasites can insert themselves into important genes and regulatory regions, potentially disrupting normal development and threatening genome stability.

    The study also revealed that because sea anemones lack the extensive epigenetic resetting that occurs after fertilization in mammals, some abnormal methylation states persisted in offspring. "These inherited epigenetic changes altered how genes are switched on in the next generation, demonstrating that experimentally induced epigenetic variation can be transmitted across generations in an animal," said Alex de Mendoza, senior author of the study published in Nature Ecology & Evolution.

    The findings suggest that the ancestral role of DNA methylation in animals was not primarily to regulate gene expression, but to protect active genes from disruptive jumping genes. In mammals, this same molecular system has since taken on a broader range of functions, including regulating development and silencing one of the two X chromosomes in females.

    The work also shows how incomplete epigenetic resetting can allow heritable variation to persist across generations without requiring any changes to the genetic code itself—potentially providing raw material for evolutionary change. In doing so, the study offers a window into the evolutionary origins of important regulatory systems, and demonstrates how more ancient mechanisms of gene regulation can transmit information through generations.

Latest Articles

Collapse

  • SEQadmin2
    Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
    by SEQadmin2



    Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
    ...
    07-09-2026, 11:10 AM
  • SEQadmin2
    Cancer Drug Resistance: The Lingering Barrier to Rising Survival
    by SEQadmin2



    Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

    There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
    07-08-2026, 05:17 AM
  • GATTACAT
    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
    by GATTACAT
    Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
    07-01-2026, 11:43 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, Yesterday, 10:26 AM
0 responses
12 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-09-2026, 10:04 AM
0 responses
25 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-08-2026, 10:08 AM
0 responses
16 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-07-2026, 11:05 AM
0 responses
33 views
0 reactions
Last Post SEQadmin2  
Working...