Contents

Program of Single Cell Omics Beijing 2021.

   Oct 15, 2021     31 min read

Notes from Program of Single Cell Omics Beijing 2021.

Oct. 15-16, 2021. Beijng China

Opening

Session 1

Steve Henikoff: Single-cell Profiling of Chromatin Landscapes

William Greenleaf: Exploring the Physical Genome in Health and Disease

  • scATAC-Seq and scRNA-Seq of blood development and Acute leukemia

  • Developing of fetal heart

    利用体内分化的ATAC数据指导体外分化，UMAP Projection

  • Predict gene expression

image-20211015100345509

Q&A: 细胞周期在scRNA中影响很大，但是在scATAC中并不明显hhhh

Stephen Quake: The Cell as a Bag of RNA

Tabula Organisms

  • Mouse Aging Cell Atlas: Tabula Mouse

  • Fly Cell Atlas

  • Tabula Sapiens Project (BioRxiv)

    15 donors, 481,120 cells

  • cross-species integration

Bing Ren: A Single-Cell Atlas of Chromatin Accessibility in the Human Genome

  • sciATAC-Seq of Mouse Cerebrum (Nature, 2021, Oct)

  • sciATAC-Seq of fetal and adult brain

    1.2 million cREs, 222 cell types

image-20211015103937578

  • scATAC of lung (covid-19)

    肺泡细胞顺式作用原件上的点突变与预后相关。

Q&A:

  1. 神经细胞的类群注释依赖先验的scRNA-Seq数据

  2. scRNA鉴定的功能基因群在scATAC无法复现，scATAC更稳健，显示的是更深层的稳定结构
  3. 不同组织的消化与提核？Sebastian Preissl多次优化提核条件，对于不同的组织采用了5个不同Protocol，不同的Protocol在一遍bioRxiv中有详述。

Session 2

Sunney Xie: Bisulfite-free High-coverage Detection of DNA Methylation and Hydroxyl Methylation During Early Embryo Development at the Single cell Level

  • Potent Neutralizing Antibodies against Covid-19

    • High throughput screening of antibody, DXP-604不存在antibody escape现象，对所有变种病毒有效。
    • 结构：避免antibody escape的原因：DXP-604结构与ACE2结合位点类似，escape DXP-604的变体不具有感染性。

  • Bisulfite-free High-coverage detection DNA Methylation and Hydroxyl Methylation at the Single cell Level

    • 不使用bisulfite的bulk方法：TET2+β-GT保护，再用APOBEC转化。需要两次纯化，coverage较低。
    • Cabernet and Cabernet -H

image-20211015151926483

  • 高转化率（>99%），高coverage，高mapping rage（~80%）。
  • sci-Cabernet-Seq，barcoded Tn5实现multiplexing。
  • Profiling 5mC and 5hmC in early mouse embryo

image-20211015152409797

Q&A:

  1. cost：成本高于scRNA-Seq，低于scWGS

Amos Tanay: New Single Cell Strategies for Characterizing the Function of DNA Methylation During Gastrulation

  • single cell data and model dynamics
  • disturb: 敲除TET gene的mESC，注射进入ICM，产生完全敲除(TET-TKO) or 嵌合敲除的完整胚胎，再进行全胚胎的scRNA-Seq，检测各种细胞类型的比例。

image-20211015155124866

Ge Gao: Multi-omics Integration and Regulatory Inference for Unpaired Single-cell Data with a Graph-linked Unified Embedding Framework

  • Current challenges:
    • batch effect
    • sophisticated inter/intra-layer interactions
    • scalability to the ever-expanding data size
    • interpretability to translate computational models to biological insights
  • Cell Blast: integration of scRNA-Seq

image-20211015161508355

  • Adversarial Learning to model inter-dataset batches

image-20211015161658795

  • multi-level batch effect

    情景：不同数据集内部仍然存在batch effect，如不同研究，每个研究多个个体，传统方法无法有效处理

  • GLUE: Integration of multi-omics data

image-20211015162150463

​ 整合的效果显著好于之前发表的其他方法：

image-20211015162501055

Q&A:

  1. trade off of batch effect and biological difference.

    fully-auto batch correction is impossible.

Rickard Sandberg: Decoding Transcriptional Regulation and Kinetics Using Single-Cell Transcriptomics

  • Current problem for scRNA-Seq experiments

    • trade off of cell number and gene number

image-20211015164644340

  • Demand for scRNA-Seq technologies

image-20211015164739765

  • Smart-Seq3xpress: scalable, full-coverage scRNA-Seq (bioRxiv)

image-20211015215727125

  • HEK293T K562基因数稳定在6000左右

  • cost-effiecnt: lower than Smart-Seq2 and Smart-Seq3

image-20211015215745611

  • pilot data from PBMCs (16K cells)

image-20211015165226619

16K 细胞准确捕捉到各个亚群

  • UMI and molecular spikes: accurate RNA counting in scRNA-Seq (bioRxiv)

    • 可以用于反映scRNA-Seq的准确程度

    • benchmarking UMI collapse stragies

image-20211015165916356

image-20211015170058279

  • BAMboozle: removes genetic variation from human sequence data for open data sharing （NC in press)
    • mask掉人类数据中个体特异的variation，从而减小data sharing带来的风险。
  • Regulation of transcriptional burst
    • NASC-Seq2: 鉴定新合成的mRNA

image-20211015170412704

  • new RNA反映出Total RNA无法反映的异质性

image-20211015170610190

image-20211015170650752

image-20211015170948904

Q&A:

  1. Smart-Seq3xpress vs Smart-Seq3
    • Smart-Seq3 没有UMI，无法绝对定量
    • Smart-Seq3xpress相比于Smart-Seq3没有明显的decreasing（lose the ability to see that you can have better data hhhhh)
  2. NASC-Seq2

Sten Linnarsson: Molecular Architecture of the Developing Mouse Brain Single Cell

image-20211015174012879

Q&A:

  1. quality control of atlas-level scRNA-Seq project
    • shallow sequence对样品进行质控
    • QC 指标：Fraction of unspliced reads，质量不好的细胞or死细胞会有更高比例

Session 3

打球去了……

Chen Wu: Dynamic Molecular and Cellular Alterations in Multi-step Cancer Development

Muzlifah Haniffa: Decoding the Developing Human Immune System

Fan Bai: Somatic Mutagenesis in Morphologically Normal Human Tissues

Xuefei Zhang: Chromatin Loop Extrusion Plays Mechanistic Roles in Antibody Diversification

Session 4

Christopher A. Walsh: The Architecture of Human Brain Somatic Mutations in Health and Disease

  • pathogenic mutations in normal human brain (Cancer Discovery,2021 Aug)

    • 5% of normal humans have cancer-associated mutations

image-20211016083904421

  • pathogenic mutations appears to decrease with age

  • large scale CNV present in 5-8% of normal brains

image-20211016084048170

  • 人各个lineage 的somatic mutation profile (Science,2021 Mar)

image-20211016084431648

  • 早期卵裂产生的细胞，对胚胎贡献的细胞数是高度不平均的

  • human cortex shows surprisingly integrated clonal structure

image-20211016085012393

  • Neuronal genome in the aging brain (bioRxiv)

    • 神经元中的SNP会随着年龄积累(15-20 per year)
    • MDA会带来false positive SNPs，PTA显著好于MDA：扩增均匀，假阳性低
    • PTA and NanoSeq reveals increasing indels in aging neurons, possibly resulting from transcription.

  • summary

image-20211016085658174

Q&A:

  1. functional consequence of accumulated SNPs ? disease ?
  2. Enhancers are enriched for mutations.
  3. survival of mutated neurons. do the colons die? to be expored.
  4. mutation frequency of cycling and non-cycling cells.

Chenghang Zong: Droplet Based High-Throughput Transcriptome Profiling of Individual Synapses Using Single-Cell Total-RNA-Seq

  • MATQ-Drop: Droplet single-cell total-RNA-based chemistry (Unpublished)

    • high degree of morphological and electro-physiological diversity
    • challenges of single-synapse RNA-Seq
      1. synapse are fragile: fixation to prevent RNA leakage and degradation
      2. low RNA abundance in single synapses: higher sensitivity
      3. local RNA splicing in synapses: Total RNA
    • Current scRNA-Seq methods are not applicable to synapses
      • require fresh cee
      • poly-T primers, capture poly-A of mature RNA
      • limited intronic coverage
    • MATI-Drop protocol

image-20211016091704036

  • 测试：等量HEK293T与3T3 混合，物种特异性 > 90
  • sensitivity of MATQ-Drop

image-20211016091850146

sensitivity 略低于Smart-Seq2，与10X类似，但是适用于fixed sample。

  • Construction of cell atlas using only nascent RNA or lncRNA

    • cell atlas of nascent RNA

    • cell atlas of lncRNA

image-20211016092200690

  • Transcriptome profiling of individual synaptosomes

    • subtypes in the synapses and other neuronal junctions

image-20211016092449573

image-20211016092628731

  • Synapse and nuclear specific RNAs

  • Cell-type specific intron retentions

image-20211016093242094

Cai Long: Spatial Multi-omics: RNA and DNA seqFISH+

  • DNA and RNA Sequential Fish + (Nature, 2021)

    • seqFish

      多轮barcoding实现对mRNA的条码编码

    • RNA SeqFish+

image-20211016094803080

  • DNA and RNA SeqFish+

image-20211016094847385

  • Some observations

    • non-repetitive DNA loci are located on the surface of nuclear bodies

    • actively transcribing genes appear at interfaces

image-20211016095839850

  • Chromatin interactions occur on 2D surfaces

  • “Proximity Points” anchor chromosomes to nuclear bodies

  • Summary

image-20211016100951676

Q&A

  1. detection of enhancer RNA

Longzhi Tan: Mapping the Dynamics of the Linear and 3D Genome of Single Cells in the Developing Brain

image-20211016103056888

  • 发育中，很多基因的空间位置向内部移动

  • Summary

image-20211016103235727

Q&A:

  1. 测序深度与cell type resolution:

    • 区分大的细胞类型3k-5k contact

    • 具体的神经细胞亚群20k contact

  2. Cell Cycle

    • cortex 不分裂，影响不大
    • 部分galia存在细胞周期，且对3D基因组的影响很明显，需要解决

Session 5

Guoji Guo: Inferring Genetic Models from Cell Landscapes

  • Microwell-Seq (Cell, 2018)

image-20211016153458157

  • gentle to cell (no FACS)
  • low cost

  • high throughput

  • Microwell-Seq 2.0 (in press)

image-20211016153652426

  • random primer, higher sensitivity

  • higher throughput

  • Cell Landscape Project

    • Questions: how many cell types? how cell fate determined?

    • Human Cell landscape (Nature. 2020)

    • Mouse Cell landscape: 120,000 cells

    • Observations:

      • Immune-related stromal and epithelial cells

      • transitional cells

image-20211016154501659

  • How is cell fate regulated?

    • Entropy Reduction
    • lineage specific and common TF dynamics

  • Predicting probability of expression by deep learning

image-20211016155230935

​ overall AUC在0.8左右

Q&A:

  1. doublet and transitional cells.

    pre-barcoding，多重barcode，无法百分百 保证不存在doublet

Alexander van Oudenaarden: Ribosomal Profiling in Single Cells

  • Ribosome profiling provides attractive approach to measure translation

image-20211016161208420

  • scRibo-Seq: Experimental Procedure

image-20211016161414221

  • ribosomal protected fragments(RPF) are enriched in coding sequencing and have 3-nt periodicity

image-20211016161545823

  • Arg-codon-pausing predominately occurs during expression of histone genes

image-20211016162257676

  • Pronounced GAA stalling is observed during mitosis, and affects many genes

  • Summary

image-20211016162914292

Q&A

  1. how many cells to sequence?

    单细胞分辨率，稳健结果1k~2k cells

Xiaoqun Wang: The Diversity of Neurogenesis and Evolution in Human Cerebral Cortex

不感兴趣 at all…

Wolf Reik: Single Cell Multi-Omics Landscape of Development and Ageing

  • Conceptual limitations of single-cell genomics

image-20211016171401783

Session 6

Yanyi Huang: Sequencing Trace Amount of Nucleic Acids: for Mini-bulk and Single-cell Samples

吃饭去了

Q&A

  1. FISH validation of CNVs
  2. Cause of CNV in normal somatic cells

Fuchou Tang: Decoding the Mechanisms of Human Development and Diseases by Single cell Genomics Approaches

image-20211016200859986

image-20211016201651771

image-20211016201704384

image-20211016201714740

image-20211016201723415

image-20211016201735074

image-20211016201800319

​ 当时数据质量这么好……泪目。

image-20211016202427254

image-20211016202536518

Identify the ‘dark matter’ in the genome!

Q&A:

  1. better cell typing on isoform level? To be tested on tissue sample.
  2. Long WGS on cancers? In progress.

Zemin Zhang: Dynamic Changes of Tumor Infiltrating Immune Cells During Immunotherapies

image-20211016203411325

  • Early work on infiltrating myeloid cells cross cancer types

  • Immunotherapy is all about modulating tumor micro-environment (TME)

  • mechanisms of T cell exhaustion in lung cancer

    • responsive tumors shows preferential decrease of terminal Tex cells

image-20211016204039661

  • identify Tex/tumor responsive T cell subset by Tex TCR

image-20211016204208814

  • Tex precursor (Texp) accumulates in responsive tumor after treatment

image-20211016204330021

  • Mechanisms for the formation and accumulation of Texp cells

image-20211016204509264

  • Summary

image-20211016204749825

  • Triple negative breast cancer (TNBC)

image-20211016204946940

  • Experiment Design

<img src=”https://raw.githubusercontent.com/liuzhenyu-yyy/liuzhenyu-yyy.github.io/main/assets/img/posts/post_20211016/image-20211016205046331.png” alt=”image-20211016205046331” heigh=”150”

  • single profiling

image-20211016205142400

  • CXCL13+ T cells play a key role

image-20211016205326511

  • B cells were enriched in responders of the combination therapy

  • B cells were highly correlated with CXCL13+ T cells in TME

image-20211016205502470

  • Pro-inflammatory macrophages play roles in T cell recruitment

  • CXCL13+ T cells were highly correlated with Mφ

  • Summary

image-20211016205726165

  • Overview of functional properties of immune cells in TME

image-20211016205821740

Q&A:

  1. Dynamic changes of stromal cells (fibroblast) during treatment.
  2. Texp: tumor reactive, molecular mechanisms to be determined.

Ending

© 2020 - 2024 Zhenyu Liu. All rights reserved.

Powered by Jekyll and GitHub Pages.