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Defining novel multilineage progenitor populations using single-cell RNA-Seq Nathan Salomonis Department of Biomedical Informatics, CCHMC
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Page 1: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Defining novel multilineage progenitor

populations using single-cell RNA-Seq

Nathan SalomonisDepartment of Biomedical Informatics,

CCHMC

Page 2: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Uncovering Cell Heterogeneity from

Single-Cell RNA-Seq

HSC

Monocytes

Granulocytes

Erythrocytes

Megakaryocytes

• Major Objectives• Define major cell populations.

• Identify ultra-rare cells.

• Identify hidden cellular

heterogeneity and transition states.

?

?

??

Page 3: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Conflicting Evidence Mixed-Lineage

States Exist

Page 4: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Isolation and Analysis of Diverse Mouse

Hematopoietic ProgenitorsOlsson et al. Nature 2016

•Analyze using the 96-cell Fluidigm platform.

•Average 3 million reads of PE 75nt reads.•Exclude outliers (depth, alignment %).

Page 5: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Automated Single Cell Analysis in AltAnalyze:Iterative Clustering and Guide-gene Selection

All detected genes

Kallisto in AltAnalyze

FASTQ files or pre-processed

Optionally Exclude

Cell Cycle Effects

Integrated

Cell Type

Predictions

Page 6: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Molecular Dissection of Hematopoiesis from scRNA-Seq using ICGS

Multi-lineage priming??

Olsson et al. Nature 2016

Page 7: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Monocyte and Granulocyte Progenitors Defined by Opposing Transcription Factors

Olsson et al. Nature 2016

Page 8: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Gfi1and Irf8 Interact on Promoters to Regulate Myeloid Specification

Olsson et al. Nature 2016

Page 9: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Intermediate Gfi1 and Irf8 Define a Metastable Bipotential Progenitor Population

Olsson et al. Nature 2016

Page 10: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Biopotential

Progenitor

Multi-Lineage

Progenitor

Page 11: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Initial Conclusions

1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory networks.

2. Appears to require deep RNA-Seq.

3. Non-HSC, Multi-Lineage progenitors are frequently found in CMP and GMP gated cell populations.

4. These cells are primarily defined by multi-lineage gene priming and only weakly defined by unique marker genes.

5. Multi-Lin’s can be captured and enriched by sorting for progenitors with dual lineage programs (Gfi1 and Irf8 expression).

6. Genetic deletion of these factors traps cells in an undecided state.

Page 12: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Controversies and Questions from scRNA-

Seq Predictions

1. Other myeloid biologists argue Multi-Lin’s are

technical artifacts (doublets).

2. Bi-Potential progenitors enriched but not purified.

3. Multi-Lineage progenitors and MEPs not identified.

Page 13: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Optimized Isolation of CMP Multi-Potential Progenitors

Manuscript in preparation Mono-PotentialMulti-PotentialOptimized Markers

Original Cells

Page 14: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

New Algorithms to Predict Multi-Lineage States from scRNA-Seq (Schrodinger)

Predicted Mixed-Lineage

Cells and Cell States

Page 15: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

>200k reads/library1.8k cells

HSC-1

Eryth

Mono

DC

Multi-LinPre-B

Meis1Satb1

Irf8

Itga2b

MpoGfi1

Gata1

➢ Identification of similar Multi-

lineage states from other scRNA-

Seq datasets (ICGS +

examination of lineage markers).

ErythP

HSCP-1

Gran

B1

Meg

Predicted Multi-Lineage Progenitors from Other scRNA-Seq Datasets

Page 16: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Schrodinger Detection of Multi-Lineage States in ~500 Mouse Bone Marrow Progenitors (Nestorowa et al.)

Also validated in data from:

Tusi BK, Klein AM, Socolsovsky M et al. Nature. 2018 Mar 1;555(7694):54-60

Page 17: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Can This Approach Be Used to Find Similar

Cell Populations Across Technologies?

Magela et al. 2017 Developmental Biology

? ? ?

Page 18: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Consistent Schrodinger Prediction of Multi-Lineage States in Embryonic Kidney

Page 19: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Grimes Lab (CCHMC)

Meenakshi Venkatasubramanium

Kashish Chetal

H. Leighton Grimes

Andre Olsson

Harinder Singh

Virendra Chaudhri

Bruce Aronow

Phil Dexheimer

Salomonis Lab

NIH (R01HL122661 – Grimes

CCHMC Center for Pediatric

Genomics Award

Funding

Acknowledgements

Singh Lab (CCHMC)

Aronow Lab (CCHMC)

Steve Potter

Mike Adam

Bliss Magella

Potter Lab (CCHMC)

Page 20: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Identifying Bi-Potential Megakaryocyte-Erythroid

Intermediates from Human scRNA-Seq

Page 21: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Monocle Trajectory Analysis of MarkerFinder

Results Finds Distinct MEP Subsets

Page 22: Defining novel multilineage progenitor populations using single-cell RNA-Seq · 2018-05-08 · 1. scRNA-Seq combined with TF-deletion and ChIP-Seq can define transcriptional regulatory

Mix

ed

-Lin

ea

ge

Z-s

co

re

0

1

2

3

4

5

6

MEP

ERP

Mixed

-c2

Mixed

-c1

MKP

Mixed-c1 : SLC44A1, ACTN1, TTC27, PDLIM1, FERMT3, TMSB4X, ITGA2B, ABCB1, MYH9, PTGS1, STOM, CTR9, SH2B3, C6orf25, CXCL8, TUBA4A, PKM, PLEK, CD9, GSNMixed-c2 : CA1, MPC2, SF3B3, CD55, FBXO7, PRDX2, CD36, SDCBP, SPTA1, ANXA2, APOC1, RB1CC1, CALM2, WDR48, ACSM3, GOLGA4, ELL2, HBS1L, FAM45A, IARS, DLD, AHI1, SLC39A8, SKIL, ACSM1, BLVRB, SEC22C, CXADR, IRF1, ZDHHC2, USP12, RHOBTB3, EZR, KIT, FBXO34, ANK1, YBX1, STARD7, PDZD8ERP : CNRIP1, TMEM14C, SLC40A1, FAM118A, RYR3, CASP3, U1, ZFP36L1, ELOVL6, HERC2P2, TRIB2, MYC, RREB1, P2RX5, SNORD3AMEP : HSD17B11, FCER1A, RPS3AP47, CPA3, TESPA1, MEIS1, FREM1, SERPINB1, PBX1MKP : CD52, CD74, FNBP1, IDS, CD37, KIAA0125, SORL1, AJ006998.2, AHNAK, EGR1, KLF4, KLF2, NPR3, CRHBP, PROM1, ADAM28, SMIM24, CLEC2B, ID2, ID3, VIM, ATP8B4

Schrodinger Accurately Predicts that MEPs are Mixed-Lineage Progenitors


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