Profiling Histone Modifications in Single Cells to Reveal the Dynamics and Control of Blood Cell Differentiation
Event details
| Date | 24.07.2019 |
| Hour | 15:00 › 16:00 |
| Speaker | Jake Yeung, Ph.D., van Oudenaarden group, Hubrecht Institute, Utrecht (NL) |
| Location | |
| Category | Conferences - Seminars |
BIOENGINEERING SEMINAR
Abstract:
Histone modifications form an adaptable epigenetic regulatory layer that package the genome inside the nucleus and mediate dynamic transcriptional programs. This packaging can be modulated by a wide spectrum of post-translational histone modifications, regulating the expression of associated genes. During cell differentiation, the distribution of these histone modifications changes to support the new expression state. These dynamics are ideally studied at the single-cell level, because it is challenging to isolate discrete intermediate states for bulk analysis. We therefore developed a high-throughput method that uses chromatin immunocleavage (ChIC) to profile histone modifications in more than 15000 individual cells (scChIC-seq).
In this talk, I will focus on the challenges of analyzing single-cell histone modification data to reconstruct differentiation dynamics from single-cell signal. In particular, I will present machine learning strategies that model sparse count data and project onto lower-dimensional manifolds in order to predict relationships between cells as well as relationships across genomic regions.
I will also discuss using systems biology methods to infer transcription factor (TF) activities and how to apply this to single cell data. This approach infers key TF binding motifs and predicts master regulators underlying transcriptional programs of hematopoiesis.
Finally, I will talk about integrating single-cell datasets of different histone modifications to elucidate coordination of epigenetic reprogramming during blood cell differentiation. Overall, scChIC-seq enables the dynamic reconstruction of the global chromatin landscape during in vivo differentiation.
Abstract:
Histone modifications form an adaptable epigenetic regulatory layer that package the genome inside the nucleus and mediate dynamic transcriptional programs. This packaging can be modulated by a wide spectrum of post-translational histone modifications, regulating the expression of associated genes. During cell differentiation, the distribution of these histone modifications changes to support the new expression state. These dynamics are ideally studied at the single-cell level, because it is challenging to isolate discrete intermediate states for bulk analysis. We therefore developed a high-throughput method that uses chromatin immunocleavage (ChIC) to profile histone modifications in more than 15000 individual cells (scChIC-seq).
In this talk, I will focus on the challenges of analyzing single-cell histone modification data to reconstruct differentiation dynamics from single-cell signal. In particular, I will present machine learning strategies that model sparse count data and project onto lower-dimensional manifolds in order to predict relationships between cells as well as relationships across genomic regions.
I will also discuss using systems biology methods to infer transcription factor (TF) activities and how to apply this to single cell data. This approach infers key TF binding motifs and predicts master regulators underlying transcriptional programs of hematopoiesis.
Finally, I will talk about integrating single-cell datasets of different histone modifications to elucidate coordination of epigenetic reprogramming during blood cell differentiation. Overall, scChIC-seq enables the dynamic reconstruction of the global chromatin landscape during in vivo differentiation.
Practical information
- Informed public
- Free