In this episode of the Epigenetics Podcast, we talked with Sarah Marzi from the UK Dementia Research Institute at Imperial College London about her work on epigenetic changes in Alzheimer's Disease, and comparing CUT&Tag to ENCODE ChIP-Seq using limited cell samples. The interview discusses Sarah Marzi's work on ChIP-Seq experiments and their significance in understanding Alzheimer's disease from an epigenetic perspective. The discussion touches on the widespread dysregulation and changes in acetylation, particularly in genes associated with Alzheimer's risk, providing insights into potential links between epigenetic insults and disease onset. Moving on to the technical aspects of the study, the interview examines the strategic use of CUT&Tag. It explores the challenges and optimizations involved in accurately profiling limited cell samples. The dialogue also compares CUT&Tag to ENCODE ChIP-Seq, highlighting the complexities of peak calling and data interpretation across different methodologies. References Kumsta, R., Marzi, S., Viana, J. et al. Severe psychosocial deprivation in early childhood is associated with increased DNA methylation across a region spanning the transcription start site of CYP2E1. Transl Psychiatry 6, e830 (2016). https://doi.org/10.1038/tp.2016.95 Marzi, S. J., Schilder, B. M., Nott, A., Frigerio, C. S., Willaime‐Morawek, S., Bucholc, M., Hanger, D. P., James, C., Lewis, P. A., Lourida, I., Noble, W., Rodriguez‐Algarra, F., Sharif, J., Tsalenchuk, M., Winchester, L. M., Yaman, Ü., Yao, Z., The Deep Dementia Phenotyping (DEMON) Network, Ranson, J. M., & Llewellyn, D. J. (2023). Artificial intelligence for neurodegenerative experimental models. Alzheimer’s & Dementia, 19(12), 5970–5987. https://doi.org/10.1002/alz.13479 Marzi, S. J., Leung, S. K., Ribarska, T., Hannon, E., Smith, A. R., Pishva, E., Poschmann, J., Moore, K., Troakes, C., Al-Sarraj, S., Beck, S., Newman, S., Lunnon, K., Schalkwyk, L. C., & Mill, J. (2018). A histone acetylome-wide association study of Alzheimer’s disease identifies disease-associated H3K27ac differences in the entorhinal cortex. Nature Neuroscience, 21(11), 1618–1627. https://doi.org/10.1038/s41593-018-0253-7 Hu, D., Abbasova, L., Schilder, B. M., Nott, A., Skene, N. G., & Marzi, S. J. (2022). CUT&Tag recovers up to half of ENCODE ChIP-seq peaks in modifications of H3K27 [Preprint]. Genomics. https://doi.org/10.1101/2022.03.30.486382 Related Episodes When is a Peak a Peak? (Claudio Cantù) Development of Integrative Machine Learning Tools for Neurodegenerative Diseases (Enrico Glaab) DNA Methylation Alterations in Neurodegenerative Diseases (Paula Desplats) Contact Epigenetics Podcast on X Epigenetics Podcast on Instagram Epigenetics Podcast on Mastodon Epigenetics Podcast on Bluesky Epigenetics Podcast on Threads Active Motif on X Active Motif on LinkedIn Email: podcast@activemotif.com
In this episode of the Epigenetics Podcast, we talked with Sarah Marzi from the UK Dementia Research Institute at Imperial College London about her work on epigenetic changes in Alzheimer's Disease, and comparing CUT&Tag to ENCODE ChIP-Seq using limited cell samples. The interview discusses Sarah Marzi's work on ChIP-Seq experiments and their significance in understanding Alzheimer's disease from an epigenetic perspective. The discussion touches on the widespread dysregulation and changes in acetylation, particularly in genes associated with Alzheimer's risk, providing insights into potential links between epigenetic insults and disease onset. Moving on to the technical aspects of the study, the interview examines the strategic use of CUT&Tag. It explores the challenges and optimizations involved in accurately profiling limited cell samples. The dialogue also compares CUT&Tag to ENCODE ChIP-Seq, highlighting the complexities of peak calling and data interpretation across different methodologies. References Kumsta, R., Marzi, S., Viana, J. et al. Severe psychosocial deprivation in early childhood is associated with increased DNA methylation across a region spanning the transcription start site of CYP2E1. Transl Psychiatry 6, e830 (2016). https://doi.org/10.1038/tp.2016.95 Marzi, S. J., Schilder, B. M., Nott, A., Frigerio, C. S., Willaime‐Morawek, S., Bucholc, M., Hanger, D. P., James, C., Lewis, P. A., Lourida, I., Noble, W., Rodriguez‐Algarra, F., Sharif, J., Tsalenchuk, M., Winchester, L. M., Yaman, Ü., Yao, Z., The Deep Dementia Phenotyping (DEMON) Network, Ranson, J. M., & Llewellyn, D. J. (2023). Artificial intelligence for neurodegenerative experimental models. Alzheimer’s & Dementia, 19(12), 5970–5987. https://doi.org/10.1002/alz.13479 Marzi, S. J., Leung, S. K., Ribarska, T., Hannon, E., Smith, A. R., Pishva, E., Poschmann, J., Moore, K., Troakes, C., Al-Sarraj, S., Beck, S., Newman, S., Lunnon, K., Schalkwyk, L. C., & Mill, J. (2018). A histone acetylome-wide association study of Alzheimer’s disease identifies disease-associated H3K27ac differences in the entorhinal cortex. Nature Neuroscience, 21(11), 1618–1627. https://doi.org/10.1038/s41593-018-0253-7 Hu, D., Abbasova, L., Schilder, B. M., Nott, A., Skene, N. G., & Marzi, S. J. (2022). CUT&Tag recovers up to half of ENCODE ChIP-seq peaks in modifications of H3K27 [Preprint]. Genomics. https://doi.org/10.1101/2022.03.30.486382 Related Episodes When is a Peak a Peak? (Claudio Cantù) Development of Integrative Machine Learning Tools for Neurodegenerative Diseases (Enrico Glaab) DNA Methylation Alterations in Neurodegenerative Diseases (Paula Desplats) Contact Epigenetics Podcast on X Epigenetics Podcast on Instagram Epigenetics Podcast on Mastodon Epigenetics Podcast on Bluesky Epigenetics Podcast on Threads Active Motif on X Active Motif on LinkedIn Email: podcast@activemotif.com
In this episode of the Epigenetics Podcast, we talked with Sarah Marzi from the UK Dementia Research Institute at Imperial College London about her work on epigenetic changes in Alzheimer's Disease, and comparing CUT&Tag to ENCODE ChIP-Seq using limited cell samples.
The interview discusses Sarah Marzi's work on ChIP-Seq experiments and their significance in understanding Alzheimer's disease from an epigenetic perspective. The discussion touches on the widespread dysregulation and changes in acetylation, particularly in genes associated with Alzheimer's risk, providing insights into potential links between epigenetic insults and disease onset.
Moving on to the technical aspects of the study, the interview examines the strategic use of CUT&Tag. It explores the challenges and optimizations involved in accurately profiling limited cell samples. The dialogue also compares CUT&Tag to ENCODE ChIP-Seq, highlighting the complexities of peak calling and data interpretation across different methodologies.
References
Kumsta, R., Marzi, S., Viana, J. et al. Severe psychosocial deprivation in early childhood is associated with increased DNA methylation across a region spanning the transcription start site of CYP2E1. Transl Psychiatry 6, e830 (2016). https://doi.org/10.1038/tp.2016.95
Marzi, S. J., Schilder, B. M., Nott, A., Frigerio, C. S., Willaime‐Morawek, S., Bucholc, M., Hanger, D. P., James, C., Lewis, P. A., Lourida, I., Noble, W., Rodriguez‐Algarra, F., Sharif, J., Tsalenchuk, M., Winchester, L. M., Yaman, Ü., Yao, Z., The Deep Dementia Phenotyping (DEMON) Network, Ranson, J. M., & Llewellyn, D. J. (2023). Artificial intelligence for neurodegenerative experimental models. Alzheimer’s & Dementia, 19(12), 5970–5987. https://doi.org/10.1002/alz.13479
Marzi, S. J., Leung, S. K., Ribarska, T., Hannon, E., Smith, A. R., Pishva, E., Poschmann, J., Moore, K., Troakes, C., Al-Sarraj, S., Beck, S., Newman, S., Lunnon, K., Schalkwyk, L. C., & Mill, J. (2018). A histone acetylome-wide association study of Alzheimer’s disease identifies disease-associated H3K27ac differences in the entorhinal cortex. Nature Neuroscience, 21(11), 1618–1627. https://doi.org/10.1038/s41593-018-0253-7
Hu, D., Abbasova, L., Schilder, B. M., Nott, A., Skene, N. G., & Marzi, S. J. (2022). CUT&Tag recovers up to half of ENCODE ChIP-seq peaks in modifications of H3K27 [Preprint]. Genomics. https://doi.org/10.1101/2022.03.30.486382
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Development of Integrative Machine Learning Tools for Neurodegenerative Diseases (Enrico Glaab)
DNA Methylation Alterations in Neurodegenerative Diseases (Paula Desplats)
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