Program of Single Cell Omics Beijing 2022.
Notes from Program of Single Cell Omics Beijing 2022.
- Opening
- Session 1
- Session 2
- Bart Deplancke: Engineering Next-generation Single Cell Phenomics Technologies
- Rickard Sandberg: Scalable Full-length scRNA-seq for Temporal Analyses of Transcription and Dissections of Cell States and Subtypes
- Angela Ruohao Wu: Multi-step Single-cell Multi-omics Methods for Simultaneous Dissection of Phenotype and Genotype Heterogeneity from Frozen Tumors
- Guoji Guo:Mapping Cell Landscapes at Single cell Level
- Chenghang Zong: Total-RNA Based scRNA-seq Allows Genome-wide Identification of Transcriptional and Post-transcriptional Regulation
- Section 3
- Ning Jenny Jiang: High-throughput and High-Dimensional Single T Cell Profiling
- Yanyi Huang: Improving the Information Efficiency for Fast and Spatially Resolved Sequencing
- Fuchou Tang: Single Cell Omics Sequencing Technologies: The Next Generation
- Zemin Zhang: Dynamic Changes of The Tumor Micro-environment During Immunotherapies
- Xiaoqun Wang: Spatial Mutli-omics Sequencing the Developing Human Cerebellum
- Session 4
- Alexander van Oudenaarden: Acceleration of Genome Replication Uncovered by Single-cell Nascent DNA Sequencing
- David Weitz: Applications of Single Microbe Sequencing
- Amos Tanay: Single Cell Models for Deciphering the Birth of Cell-type Specific Epigenetics During Gastrulation
- Ge Gao: Rationally Design Generative Models for Delineating the Regulator Map in silico
Oct. 13-14, 2022. Beijng China
Opening
Session 1
Moderator: Xiaoliang Sunney Xie
Bing Ren: Illuminating the Dark Matter in Human DNA with Single-cell Epigenomics Analysis
background: “risk variants associated with gene expression regulation”
Method development (sci-based):
Experimental: snATAC-Seq, snMethyl-HiC, Paired-Tag/Seq
Computational: SnapATAC, SnapHiC
Predicting disease-associated cell types
Utilize GWAS data, analysis enrichment in cell types by intersecting with cCREs.
Identify key regulatory elements associated with disease
Summary:
- Q&A:
- Associated cCREs with genes
Jay Shendure: Reconstruction & Recording of Mammalian Development
background: development of single-cell methods
scRNA-seq of ~2 million cells in one experiment (sc-based, $384 ^ 3$ )
Epithelial development
Session 2
Moderator: Fuchou Tang
Bart Deplancke: Engineering Next-generation Single Cell Phenomics Technologies
DisCo
Live-seq
minor perturbation on target cells
sequential Live-seq: state transition of the same cell
transcriptomic recorder
Rickard Sandberg: Scalable Full-length scRNA-seq for Temporal Analyses of Transcription and Dissections of Cell States and Subtypes
NASC-seq2: single-cell nascent RNA sequencing
Co-bursting: do nearby genes burst independently?
general independent transcription of two alleles
co-bursting outliers :
Smart-seq3xpress: scalable, cost efficient
questions:
pseudo-gene expression and duplicated genes may contributed to co-bursting outliers. mentioned pseudo-gene expression. however, the investigation of pseduo-gene influenced by the high sequence similarity, specific steps to resolve this.
Angela Ruohao Wu: Multi-step Single-cell Multi-omics Methods for Simultaneous Dissection of Phenotype and Genotype Heterogeneity from Frozen Tumors
Mouse Lemur Single Cell Atlas
scONE-seq: one tube single-cell WGS and RNA-sequeicing
single-cell multi-omics is especially useful for cancer analysis.
existing single-cell DNA&RNA methods:
principles of scONE-seq
performance:
RNA (total RNA):
CNV:
discoveries:
a novel tumor sub-clone in astrocytoma
Tumor cells with minor difference on transcription identified from CNV information,
summary
Guoji Guo:Mapping Cell Landscapes at Single cell Level
background: equation for cell fate decision
Microwell-seq
Microwell-seq 2.0
- human atlas
- inflamed structural (endothelial, epithelial, stromal) cells, validated in vivo.
mouse atlas
lifespan cell landscape analysis
- inflammation in structural cells
- mitochondria metabolism
how cell types are regulated?
- TF dynamics
- Cross-species analysis of common TFs during differentiation
Nvwa
Chenghang Zong: Total-RNA Based scRNA-seq Allows Genome-wide Identification of Transcriptional and Post-transcriptional Regulation
background: Total-RNA based single-cell RNA-seq
chemistry of MATQ-seq:
SMART-MATQ seq
include intron (nascent), more appropriate for RNA velocity.
characterize the cell dynamics in cell cycle
differential gene expression along certain trajectory:
method: tradeSeq (2020, Nat commu)
compare DEG of mature and nascent RNAs defines 3 types of distinct cell cycle genes (CCGs)
Novel cell cycle genes
dynamic modules in different CCGs
Question:
- during CCG identification, the significance of type III CCGs? (nascent only) how to explain stochastic fluctuation or some biological mechanisms.
- why identify novel CCGs in type I? since type 1 could be detected by mature RNA alone.
附赠一个彩蛋hhhh
Section 3
Moderator: Yanyi Huang
Ning Jenny Jiang: High-throughput and High-Dimensional Single T Cell Profiling
pMHC generation by IVTT
TetTCF-seqHD
performance on CD8+ T cells
conclusions
Yanyi Huang: Improving the Information Efficiency for Fast and Spatially Resolved Sequencing
ECC sequencing methods:
bit-seq
Fuchou Tang: Single Cell Omics Sequencing Technologies: The Next Generation
- SCAN-seq: full-length scRNA-Seq
- SCAN-seq2: higher throughput
- SMOOTH-seq2: scWGS sequencing
- single-cell assembly
Zemin Zhang: Dynamic Changes of The Tumor Micro-environment During Immunotherapies
background: tumor microenvironmnt
composition: certain cell types
heterogenity:
pan-cancer analysis of infiltrating myeloid cells
pan-cancer analysis of infiltrating T cells
Temporal dynamics
dynamics of T cells
dynamics of LAMP3+ DCs in TAMs in HCC
clinical relavance
responsive tumor showed decrease of terminal Tex
Xiaoqun Wang: Spatial Mutli-omics Sequencing the Developing Human Cerebellum
Session 4
Moderator: Yanyi Huang
Alexander van Oudenaarden: Acceleration of Genome Replication Uncovered by Single-cell Nascent DNA Sequencing
question: measure velocity of genome replication
single-molecule methods
single-molecule measurement differs from single-cell measurement
scEdUseq: single-cell measurement replication speed
concord with previous repilcation start sites
single pulse and pair pulse
replication velocity increase with s-phase progression
this might be correlated with transcription (increase after inhibition)
mechanism:
hyposis:
inhibit transcription lead to increased DNA damage
conclusions
David Weitz: Applications of Single Microbe Sequencing
background: single microbe sequencing
Msc RNA-seq(fixed cells)
workflow
single-cell selection:
performance:
filter out rRNA using DASH
biological question: drug treatment of E coli, time series
benchmark
Microbe-Seq genome sequencing
work flow
performance
single-strain sequencing
phages associated with strain
Amos Tanay: Single Cell Models for Deciphering the Birth of Cell-type Specific Epigenetics During Gastrulation
What is an atlas?
- dimensional reduction embeddings?
- gene expression profiles?
- A group of linked quantitative distributions over all genes !
how to use atalses in 2020: query projection on atlas
for known cell types:
for novel cell types:
how to use atlas in 2022: model dynamics of cells.
Ge Gao: Rationally Design Generative Models for Delineating the Regulator Map in silico
background: gene expression regulation
intuition: learn the regulating mechanisms from data