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polycomb_in_neurons_msc's Introduction

๐Ÿง ๐Ÿงฌ The Role of Polycomb Group Proteins in Neuronal Chromatin Structure and Epigenetics ๐Ÿง ๐Ÿงฌ

Nikita Vaulin Skoltech
tg: @nvaulin
[email protected]

This is repo for my Master thesis bioinformatics analysis results (Skoltech 2023-2024).

Supervisor: Prof. Ekaterina Khrameeva


About

Neurons, genetically identical to all other cells in our body, nevertheless differ greatly in morphology and function. These differences originate from epigenetic processes going on inside the cell. In this work, we investigate the role of Polycomb group proteins โ€“ specific repressor and chromatin structuring factors โ€“ in the 3D genome, epigenome, and transcriptome of neurons. We show that Polycomb forms a unique network of long-range loops that propagate gene silencing programmes. Polycomb activity differs in different cell types of the human brain. The genetic basis for these differences lies in the presence of a large pool of subunits, the different assembly of which leads to functionally different Polycomb complexes. Ultimately, we find links between how the genetic diversity of Polycomb was formed and how our nervous system has evolved.

Keywords: Polycomb, 3D genome, neurons, epigenetics

Graphical abstract

In previous episodes

This study is the continuation of the Pletenev 2024 work. Check it out to see the beginning of our Polycomb story!

Spin-offs

Some conclusions of this work were used in our recently published review:

The picture above is also taken from this review. Maybe I'll make some beautiful illustrations for current work separately.

Contents

You can find all the results in the notebooks folder:

Raw data

Almost all data necessary for the analysis is located in the data folder:

  • polycomb_subunits.tsv - Table of the Polycomb subunits (names, types)
  • polycomb_dot_anchors.hand_made.bed - Polycomb anchors manually marked-up by Ilya Pletenev (๐Ÿ’•)
  • polycomb_loops.tsv and polycomb_loops_in_single_cells.tsv - Loops found for the abovementioned anchors.
  • H3K27me3_Neuron.bw, H3K27me3_NonNeuron.bw - ChIP-seq BigWigs from the Dong 2022 work
  • cells_fullmeta_m3C.tsv - scHi-C metainformation from the Tian 2023 work
  • rnaseq.rizzardi2019... - Genes expressed in neurons from the Rizzardi 2019 work
  • cluster_annotation.xlsx, clusters_abbrevs.csv - scRNA-seq metainformation from the Siletti 2023 work.

Yet, some data is too big for GitHub :((

  • hc_plus.mcool and hc_minus.mcool - Human Brain (BA22p) post-mortem Hi-C maps obtained and described in detail in the Pletenev 2024 work. You can get them from the GEO (GSE229816). There are individual maps, and here I use maps that were merged using 01_merge_Hi-C.sh script (PLUS_MRG_OUT and MINUS_MRG_OUT names).
  • scRNA-seq of human brain STG (superior temporal gyrus) cells (6323dc85-7d67-4640-a407-c9724877f412.h5ad). You can find this and other datasets from the Siletti paper via their GitHub repo: github.com/linnarsson-lab/adult-human-brain
  • ChIPseq peaks and signal tracks for RYBP/YAF2 comparison - you can get them the GEO (GSE213416), which is for Yanjiang Liu 2023 paper.

References

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